NHS Digital Data Release Register - reformatted

University Of Oxford projects

7321 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

🚩 University Of Oxford was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. University Of Oxford may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.

Long-term outcomes following traumatic brain injury: a retrospective cohort study — DARS-NIC-726391-M6D4Z

Opt outs honoured: (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2025-03 – 2027-03

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death

Type of data: Identifiable

Objectives:

The University of Oxford requires access to NHS England data for the purpose of the following research project:
Long-term outcomes following traumatic brain injury: a retrospective cohort study

The following is a summary of the aims of the research project provided by the University of Oxford:

This study addresses the long-term effects of traumatic brain injuries. A traumatic brain injury (TBI) is a head injury which results in symptoms of brain dysfunction. TBI can be classified according to the mechanism of injury in relation to the damage sustained by the skull. Closed TBI (CTBI) describes when external forces are transmitted through the skull to cause brain dysfunction without breaching the skull. Open TBI (OTBI) describes when brain dysfunction results from external forces and the skull is breached by a foreign body. In civilian populations, OTBI accounts for between 5–12% of all cases of TBI, and yet long- term outcomes after this type of brain injury remain unclear.

CTBI is associated with a long-term increase in mortality and reduced life expectancy. CTBI is also associated with an increased risk of developing a range of neurological and psychiatric conditions later in life, including dementia, stroke, epilepsy, depression, and sleep disorders. Because OTBI is less common and more often fatal than CTBI, the extent to which it is associated with other condition in the long-term is less clear. Patients with OTBI are at higher risk of medical complications following injury compared to those with CTBI, and often require expert intensive care. Given this, and the biological differences between OTBI and CTBI, it is plausible that OTBI is associated with greater risks to the health of long-term survivors; and yet, due to a lack of evidence, strategies for the prevention and mitigation of these risks do not form part of current TBI guidelines. More research is needed to understand why this is the case and what can be done to reduce these risks.

Recent studies have revealed important insights into the long-term effects of certain types of brain injuries, especially concussion. However, we still know very little about other types of brain injuries, including the most severe cases which involve direct damage to the brain caused by injuries that penetrate the skull. To address this, we will study a uniquely detailed collection of information gathered over the lifetime of three thousand veterans who were treated at the Military Hospital for Head Injuries (MHHI), established at St Hugh’s College in Oxford during World War II. This information describes physical and mental health outcomes (in the form of previously collected archived research records), which the University of Oxford propose to link with information describing life expectancy (mortality data from central registers). Through this study, the University of Oxford aim to answer the following question:

What are the long-term effects of penetrating brain injuries on physical health, mental health, and life expectancy?

This study is an update to an earlier epidemiological study which followed a standard historical cohort design. The cohort is already assembled, and no new study members will be recruited or registered. For the original study, recruitment took place between 1940-1954 and involved extracted information from archived research records that was linked with national registry data on mortality collected between 1940-2003. This study will update information on mortality by 21 years. The analyses will use standard epidemiological methodology.

The following NHS England Data will be accessed:
> Civil Registration Mortality – necessary to provide a status update on the cohort.

The level of the Data will be:
> Identifiable*

*Although the Data disseminated from NHS England to the University of Oxford under this Data Sharing Agreement is pseudonymised, the PhD student accessing the pseudonymised Data will also have access to the identifiers, and therefore, although there will be no attempt to re-identify participants, there is the technical means to do so.

The Data will be minimised as follows:
> Limited to a study cohort identified by the University of Oxford – the cohort consists of soldiers who showed evidence of brain dysfunction following a suspected head injury (cases), or peripheral nerve injuries (controls) during World War II and the Korean war and were subsequently treated at the Military Hospital for Head Injuries in St Hugh’s College, and formed the cohort of a previous study in 1998.
> Latest available data is required to update the study to a time when it is expected that almost all members of the cohort will be deceased.

The University of Oxford is the research sponsor and the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

A member of staff from King's College London may provide support and guidance based on what the University of Oxford proposes, but the research team at the University of Oxford will be solely responsible for determining the purpose and means of the processing of personal data.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because of the potential impact of future results in understanding the long-term effect of different types of brain injuries, therefore rests on four key points: (1) Public interest and understanding future risk of traumatic brain injuries, (2) Need to utilise the uniqueness of the MHHI veteran cohort, (3) Efficient use of an assembled cohort, and (4) Increased statistical power and ability to address new questions.

The funding is provided by a Medical Research Council in the form of a PhD fellowship. The funding is for the PhD student and this project.

The funder will have no ability to suppress or otherwise limit the publication of findings.

Data will be accessed by:
> Substantive employees of the University of Oxford.
> A PhD Student enrolled with the University of Oxford. The individual has completed mandatory data protection and confidentiality training and is subject to the University of Oxford’s policies on data protection and confidentiality. The individual accessing the data will do so under the supervision of a substantive employee of the University of Oxford. The University of Oxford would be responsible and liable for any work carried out by the individual. The PhD student would only work on the data for the purposes described in this Data Sharing Agreement (DSA).

The University of Oxford have consulted with stakeholders representing the original study participants and veteran communities more broadly regarding this study and the proposed use of patient identifiable data without consent. As part of this consultation, the University of Oxford have engaged with a relative of a veteran in the study cohort. They were strongly supportive of the study, including specifically the use of personal data without consent as described in the protocol.

The Concussion Legacy Foundation (CLF) is a leading global charity addressing the effects of brain injuries on veterans. The University of Oxford have consulted with the UK branch of the CLF and provide their views regarding the acceptability of this project, which were also strongly supportive. In addition, researchers involved in the original study and related projects who met many of the original participants, have also offered their support.

Expected Benefits:

In 2022, the Brain Trauma Foundation emphasised the urgent need for more research into the long-term effects of OTBI. Opportunities to study long-term outcomes among people with OTBI are limited, and while prospective studies are underway, the study of existing cohorts can provide timely insights to inform brain injury management guidelines in the near term and inform the design of prospective studies in the longer term. The largest study of long-term outcomes after OTBI to date involved 1,221 veterans of the Vietnam War and spanned more than 40 years. Among the many insights gained from the Vietnam Head Injury Study (VHIS), it revealed a high burden of motor, visual, and memory impairment and an increased risk of epilepsy 15 years after injury among survivors of OTBI compared to uninjured controls. Thirty-five years after injury, OTBI survivors remained at higher risk of epilepsy and also cognitive impairment. Along with the VHIS, the MHHI cohort remains one of the largest and most detailed collections of data describing long-term outcomes among people with OTBI. The main benefit of this study is therefore that it will reveal lifelong effects of OTBI on mortality, supporting the anticipation and mitigation of adverse outcomes for this group of patients.

The use of the data could:
> help the system to better understand the health and care needs of populations.
> lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
> advance understanding of the need for, or effectiveness of, preventative health and care measures for particular populations or conditions.
> support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

The University of Oxford hope to contribute towards improving the lives of people affected by traumatic brain injuries.

This study will be the largest of its kind ever performed. The results will be used to inform brain injury management guidelines, which currently do not provide guidance for people affected by penetrating brain injuries.

The University of Oxford aim to achieve these benefits in three main stages:
1) Reveal the lifelong effects of OTBI on mortality through analysis of the data provided (2025). Planned analyses to be conducted within the PhD include comparisons of age at death and frequency of neurological causes of death between open and closed TBI groups.
2) Publication and dissemination of these results will occur towards the end of the PhD and in the period immediately afterwards (2025-2026).
3) The University of Oxford foresee that applying these results to inform the development of TBI management guidelines is a longer-term goal (2026-2030). Practically, it is anticipated that the results of this study will be shared with the Brian Trauma Foundation, who produce authoritative guidelines on the management of TBI. The PhD student will be well-placed to sustain this effort, as an academic neurology trainee based in Oxford for at least the next five years.

Findings of this study will also be disseminated with any surviving veterans and their relatives, and veterans more broadly, through the Concussion Legacy Foundation (CLF). The CLF is a global leading brain injury charity who work closely with veteran communities, sharing the latest research through webinars, conferences, social media, and press engagement.

Outputs:

The expected outputs of the processing will be:
> Submissions to peer reviewed journals, including at least one high-impact scientific paper
> Presentations at appropriate conferences, including at least one international conference presentation
> Findings will form part of the PhD student’s thesis

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
> Journals
> Conferences
> Updates to the University of Oxford’s departmental webpages
> Social media
> St Hugh’s College webpage updates aimed at any surviving veterans and their relatives
> Newsletters aimed at any surviving veterans and their relatives

The target date for the above outputs to be achieved are throughout 2025 and 2026.

Processing:

The University of Oxford will transfer data to NHS England. The data will consist of identifying details (specifically name, sex, date of birth, NHS number, postcode and a unique person ID) for the cohort to be linked with NHS England data.

NHS England will provide the relevant records from the mortality dataset to the University of Oxford. The Data will contain no direct identifying data items but will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient.

The Data will not be transferred to any other location.

The Data will be stored on servers at the University of Oxford.

The Data will be accessed by authorised personnel via remote access.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Remote processing will be from secure locations within England. The data will not leave England at any time.

Access is restricted to employees or PhD students at the University of Oxford who have authorisation from the Chief Investigator.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will be linked at person record level using study IDs with pseudonymised mortality, exposure, and morbidity data obtained from index cards stored in St Hugh’s College Archive at the University of Oxford, which describe the date of injury/admission/discharge, nature of the injury, presenting characteristics, medical assessments, and responses to postal surveys describing neurological and psychiatric symptoms up to ten years after discharge from the MHHI. Pseudonymised mortality data will also be collected from death certificate index cards provided by the Office for National Statistics up to and including 2003, which are also stored in St Hugh’s College Archive.

The Data will not be linked with any other data.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset.

Researchers from the University of Oxford will analyse the Data for the purposes described above.

Motor Neuron Disease Register — DARS-NIC-657032-T7Z5C

Opt outs honoured: (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261(2)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2025-01 – 2030-01

Access method: One-Off

Data-controller type: KING'S COLLEGE LONDON, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)
  4. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

King’s College London and University of Oxford require access to NHS England data for the purpose of the following research and non-research purposes:
The MND Register.

Motor Neuron Disease (MND) is a neurodegenerative disease that involves loss of function or death of the cells which relay messages between the brain and muscles (known as motor neurons). The pathology causes progressive muscle wasting and paralysis, and death is often by respiratory failure. Apart from a small genetic subset of people, there is currently no cure for MND.

Currently, the project receives health record data from sites across England, Wales, and Northern Ireland that treat people with MND. The data include a demographic subset and a clinical subset with details of the MND diagnosis and key features. It is necessary to collect data directly from treating services to ensure that the diagnosis has been confirmed by a neurologist and to request clinical details related to disease progression that are not collected in routine healthcare datasets. However, due to the burden on people collecting the data at individual sites the study team are seeking to supplement the clinical data with routinely collected administrative healthcare data in order to better address the research questions.

The following is a summary of the aims of the research project provided by King’s College London and University of Oxford: (covered by s251 21/CAG/0009)

The MND Register is a population register that aims to collect information about all people with a diagnosis of MND in England. The team aim to use this information to accurately estimate incidence and prevalence of MND in those areas. The team also aim to investigate epidemiological research questions including geographical spread of disease including clustering, natural history of disease, factors related to disease progression, hospitalisation need, and access to disease modifying interventions. This application is for England only.

The following is a summary of the aims of the non-research project provided by King’s College London and University of Oxford (covered by s251 21/CAG/0028)

To improve care planning, looking at regional differences, and enabling the applicants to provide answers associated with the NICE MND Audit. Development of a mathematical model of MND. Such models can inform future studies, drug discovery and knowledge of
pathogenesis of the disease.

The following NHS England Data will be accessed:
• Hospital Episode Statistics (HES)
- Admitted Patient Care (APC) – necessary because people with MND may be offered interventions such as gastrostomy, tracheotomy, and non-invasive ventilation.
- Outpatients – necessary because people with MND are seen regularly at outpatient appointments.
- Accident & Emergency (A&E) – necessary because people with MND are admitted to A&E for respiratory arrest.
• Civil Registration Mortality – necessary because disease duration is commonly used as an endpoint for many research studies as MND currently does not have a cure. It is important to have up-to-date mortality data for the cohort to support statistical analysis.

There are two parts to this request

Identifiable:
Necessary because the data needs to be linked to the clinical dataset collected by the MND Register to allow analysis of individual records.

Aggregated:
Aggregated HES APC data will be accessed on people with MND (identified by ICD10 code G12.2) who are not present in the MND cohort to estimate case ascertainment. This will be broken down by Lower layer Super Output Areas (LSOAs) in order to estimate case ascertainment against the catchment areas. As this project is a population register aiming to count every person with MND in England, case ascertainment statistics are important in assessing the success of the register and the generalisability of the statistics. The purpose of the aggregated data is to ascertain the coverage that the current MND Register Cohort provides and the study team are not seeking to necessarily capture the data of people who have opted out of the MND register and not requesting patient level information relating to these individuals.

The Data will be minimised as follows
• Limited to a study cohort of 9605 patients identified by King’s College London and University of Oxford – the cohort comprises people with a confirmed diagnosis of MND over the age of 16 diagnosed between 01/04/2020 and 01/04/2024, identified by the case load of services treating people with MND.
• Limited to data between 2020/21 and 2023/24.

Aggregated HES APC data:
Limited to patients identified in HES APC through the following inclusion and exclusion criteria:
• Inclusion criteria: any patient diagnosed with MND between 01/04/2015 and 31/03/2024 who was aged over 16 at diagnosis and who have records of MND diagnosis or treatment based on ICD-10 diagnosis code G12.2.
• Exclusion criteria: any patient who is included in the cohort submitted to NHS England for linkage.

King’s College London as the research sponsor, and University of Oxford as the main collaborator, are joint controllers as the organisations responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) – processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.

The lawful basis for processing special category personal data under the UK GDPR is:
Article 9(2)(j) – processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
This processing is in the public interest because it will be used for research into MND.

The funding is provided by the MND Association. The funding is specifically for the project described. Funding is in place until 30/06/2025.
The funder(s) will have no ability to suppress or otherwise limit the publication of findings.

The following organisations are involved in the above project but will not access the data:
• Steering committee: Sheffield University, Edinburgh University, and MND Association
• Data access committee: MND Association, Cambridge University, and South Wales MND Care Network

Patients from the Sheffield MND Research Advisory Group, the MND LOROS Patient Support Group, and the South London MNDA Patient Focus Group were consulted. The feedback received was very positive with patients strongly supporting the proposal. Copies of the patient-facing documents were distributed to the group for review, and the group explained that they felt that some of the terminology used in these documents was complicated to understand. After further discussions with the group, the documents were updated to include terminology that was easier to understand for patients and carers.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for local decision-makers to inform best practice to improve the care and treatment of health care users relevant to motor neuron disease. The research database will be a resource for people studying motor neuron disease to help drive research insights.

The use of the data could:
• help the system to better understand the health and care needs of populations.
• advance understanding of regional and national trends in health and social care needs.
• advance understanding of the need for, or effectiveness of, preventative health and care measures for people with motor neuron disease.
• inform planning health services and programmes, for example to improve equity of access, experience and outcomes.
• inform decisions on how to effectively allocate and evaluate funding according to health needs.
• provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.
• support knowledge creation or exploratory research through modelling projects using the data (and the innovations and developments that might result from that exploratory work).
• development of a mathematical model of MND. Such models can inform future studies, drug discovery and knowledge of pathogenesis of the disease which will benefit patients with MND (this sits within non research).

The research is hoped to contribute towards knowledge of the causes of MND due to the linkage to different familial, demographic, environmental, and lifestyle risk factors with the development of MND and disease progression.

The register has the potential to benefit patient treatment because results are anticipated to inform clinical trial design making power scores more accurate. This means that physicians could make more informed decisions on how patients are treated based on their presenting symptoms. The MND register is hoped to inform care planning because it will provide counts of how many people in an area have the disease, what their prognostic characteristics are, and what care different groups require.

It is hoped that through publication of the findings of this research will add to the body of evidence that is considered by the organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

The research will be promoted on the MND social media accounts to optimise the potential public benefits from the use of the data. The MND Association has an active research promotion team which will be utilised to publish the research findings. The sites that submit data will be contacted to enable the research findings to be used locally to inform patients about their services.

Outputs:

The expected outputs of the processing will be:
• Annual reports of findings to the MND Association.
• Submissions to peer reviewed journals – the number and frequency of publications will be determined following receipt of the data.
• Annual presentations at appropriate national and international conferences (such as the ENCALS meeting in Turin in 2025, and the International Symposium on ALS/MND in San Diego).

The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Social media
• Public reports
• Briefing documents provided to policy organisations such as National Institute for Health and Care Excellence
• Posters displayed at appropriate conferences
• Patient Information leaflets available at MND services
• Press/media engagement
• Public promotion of the research by the MND Association
• Participant newsletters

A general report and manuscripts are expected to be produced a year on receipt of the data.

Processing:

King’s College London will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, Postcode, Gender, and a unique person ID) for the cohort to be linked with NHS England data.

NHS England will provide the relevant records from the HES APC, HES Outpatients, HES A&E, and Civil Registration Mortality datasets to King’s College London. The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient

The data will not be transferred to any other location.

The data will be stored on servers at King’s College London hosted on the OpenStack private cloud.

The data will be accessed by authorised personnel via remote access.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Remote processing will be from secure locations within England. The data will not leave England at any time.

Access is restricted to substantive employees and enrolled students King’s College London, University of Oxford, and London School of Hygiene and Tropical Medicine who have authorisation from the Principal Investigators.

All personnel accessing the data have been appropriately trained in data protection and confidentiality.

Analysts/researchers from King’s College London, University of Oxford, and London School of Hygiene and Tropical Medicine will analyse the data for the purposes described above.

MyMelanoma Study - NHS DigiTrials Recruitment Service — DARS-NIC-743571-K7X4R

Opt outs honoured: (Excuses: Section 251 NHS Act 2006, Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2024-11 – 2025-10

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Customer - Data Quality Report - Aggregate (Recruitment)
  2. Mailing - Cohort - Non-aggregate (Comms & Recruitment)

Type of data: Anonymised - ICO Code Compliant, Identifiable

Expected Benefits:

Achieving the recruitment target for the study is expected to enable the aims of the study to be realised, namely:

This resource will enable researchers to answer key research questions around melanoma, including:

* Why are some people more prone to develop melanoma, and what factors modify a genetic risk of melanoma?
* What are the long-term cancer risks in people who carry a genetic risk of melanoma?
* Are there biomarkers that can help identify those who are more likely to respond well to different treatments?
* What effects does a melanoma diagnosis, treatment and associated side effects have on the quality of life of people diagnosed with a melanoma?
* What is the biology underlying secondary melanomas and how is the immune system involved?
* What lifestyle factors play a role in melanoma?

The use of the Data from the NHS DigiTrials recruitment service could:
• inform study planning and decisions on how to improve equity in participation.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

Monitoring recruitment rate directly associated from the recruitment service will help determine whether the service can be used in future studies planned by the University of Oxford. Metrics derived from reports provided by DigiTrials will help identify sub-group populations which may be underrepresented in the overall cohort, driving future recruitment strategy aiming to maximise accessibility to research.

The ability to utilise large message quantities will help to optimise recruitment, in order to deliver the MyMelanoma study in a timely, effective and efficient manner. Using NHS England’s NHS DigiTrials Recruitment Service to generate mailing lists, in order to send invitations to members of the public about joining the MyMelanoma study is expected to significantly increase the recruitment reach of the study.

Participants will not benefit directly from signing up to the study, but the data they provide, and data generated from any samples they donate, will further research progress which may benefit others with similar health conditions in the future.

Recruiting individuals into the MyMelanoma study, using the NHS DigiTrials recruitment service, is ultimately expected to provide benefits to health and social care by creating the biggest melanoma data resource ever collected in the UK.

This resource will enable researchers to answer key research questions around melanoma, including:

* Why are some people more prone to develop melanoma, and what factors modify a genetic risk of melanoma?
* What are the long-term cancer risks in people who carry a genetic risk of melanoma?
* Are there biomarkers that can help identify those who are more likely to respond well to different treatments?
* What effects does a melanoma diagnosis, treatment and associated side effects have on the quality of life of people diagnosed with a melanoma?
* What is the biology underlying secondary melanomas and how is the immune system involved?
* What lifestyle factors play a role in melanoma?

The study team engage with various stakeholders and influencers to ask for their support with engaging members of the public who are eligible to join the MyMelanoma Study. They will be asked to raise awareness of the MyMelanoma study via their own communication channels which will increase familiarity and trust to the letter invite, for example:
* MyMelanoma website
* GP Practices
* Hospitals
* Integrated Care Boards
* Cancer Alliances
* Research Delivery Networks
* Charities
* Councils
* Healthwatch
* Community Organisations and groups

Outputs:

The expected outputs of this recruitment Agreement will be the University of Oxford reaching their recruitment target for the MyMelanoma Study, having sent adequate numbers of invitations to potentially eligible participants.

Progress against recruitment targets will inform:
* Establishing a large-scale, accessible research resource to support current and future melanoma research globally.
* Development of novel, translational research questions with potential scientific, medical and societal benefit
* Potential future academic and commercial collaborations with the aim of progressing cancer research.

Any reports will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived. Identifiable health data requested from NHS England will only be used to identify and invite potential participants.

The outputs will be communicated to relevant recipients through the following dissemination channels:
* Social media
* Press/media engagement
* Participant newsletters

Additionally, people who consent to take part will receive update emails annually giving news about how the research is progressing, news items from other participants, invitations to new projects to consider taking part in and seeking information on any new treatments received. Participants will of course be able to unsubscribe from this at any point.


The results of any tests performed on samples will not be returned to participants. The principal reason is that because the tests are being performed for research, therefore the significance for MyMelanoma participants of test results will not be clear until much later. Additionally, due to the scope and size of the study, it would also not be feasible to feedback results with the necessary support for participants. Research groups based in Oxford and the NHS are carrying out projects to devise mechanisms to address this issue and MyMelanoma study could utilise these systems if possible, at a later stage.

The single exception to this will be taken for people taking part in Route to Entry 3, with melanoma in their family. People who are considering participation in this study will be provided before consenting with additional information on what taking part means to them and what MyMelanoma would be able to do if a potentially important finding was made.

The University of Oxford hope to reach their recruitment target for the MyMelanoma study by 30th June 2025.

Processing:

No data will flow to NHS England for the purposes of this Data Sharing Agreement (DSA). University of Oxford will provide to NHS England the core eligibility criteria for those potential participants who will receive invitations.

NHS England will use the criteria provided by University of Oxford to identify potential participants who meet the criteria. NHS England will remove any records where a National Data Opt-Out or study-specific opt-out has been registered, as well as special categories of people for whom the data should not be disseminated.

NHS England will provide the relevant records of the identified potential participants from the Personal Demographics Service dataset to Datagraphic Ltd. The Data will contain directly identifying data items including Title, First Name, Surname, Address and Postcode, which are required for the purposes of contacting potential participants. Datagraphic Ltd will also receive additional fields which will enable them to ensure that the correct invitation format and template are used for each round of invitations. Datagraphic Ltd will use Research Ethics Committee-approved template invitation letters.

NHS England will also provide an aggregate report with small numbers supressed containing information about gender, age and geographic demographics of the mailing to University of Oxford for the purposes of confirming that inclusion and exclusion criteria have been met for each mailing. This report will also contain the total number of people who received the letter from Datagraphic Ltd, and the number of people removed from the cohort prior to mailing based on trial-specific opt out, national data opt out, and special categories of people for whom the data should not be disseminated, such as those on a witness protection programme.

The Data will not be transferred to any other location. Datagraphic Ltd will contact individuals as specified by University of Oxford. All potential participants will receive a letter containing their Forename, Surname, address, postcode and an invitation QR code.

The invitation letters are refined via participant engagement and then tested in live settings, as outlined below.

Datagraphic Ltd will send out invitations in approximately 10 batches of 17,000 letters - (up to approximately 170,000 total mailouts) using an automated system.

The Data will be stored on servers at Datagraphic Ltd.

Processing will be from secure locations within England. The Data will not leave England at any time.

Access is restricted to substantive employees of NHS England and Datagraphic Ltd only.

The University of Oxford and other recruiting sites will not have access to NHS England Data as described in this Data Sharing Agreement. The University of Oxford and other recruiting sites will not have access to individual’s data unless they are contacted directly by said individual following the mailout.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality

The Data will not be linked with any other data.

Datagraphic Ltd will destroy all data files received from NHS England 2 weeks post mail-out, as instructed by NHS England.

Each time NHS England create and disseminate an extract, the records will be added to a mailing list cohort dataset. Should a fresh extract be produced, it will be checked to ensure that any records appearing in this mailing list dataset are removed in order to prevent potential participants receiving multiple invitations. This mailing list dataset will be maintained for six months after the invitation process is complete in case this is required for analysis purposes by University of Oxford, however it is anticipated that the data quality report will meet the trial's needs for monitoring how many individuals from different demographics were contacted in each 'mailing'. Only aggregated data would be used for such analysis.

Waiting times in Emergency Departments: Inequalities and impact on health outcomes — DARS-NIC-714765-G1P5S

Opt outs honoured: unknown (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-09 – 2025-08 2024.09 — 2025.03.

Access method: System Access
(System access exclusively means data was not disseminated, but was accessed under supervision on NHS Digital's systems)

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death
  2. Hospital Episode Statistics Accident and Emergency (HES A and E)
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)
  4. Hospital Episode Statistics Critical Care (HES Critical Care)
  5. Hospital Episode Statistics Outpatients (HES OP)
  6. Uncurated Low Latency Hospital Data Sets - Emergency Care

Type of data: Anonymised - ICO Code Compliant (note: this information not disclosed for TRE projects )

Objectives:

The University of Oxford requires access to NHS England data for the purpose of the following research project:
Waiting times in Emergency Departments: Inequalities and impact on health outcomes.

The following is a summary of the aims of the research project provided by the University of Oxford:

The work in the project for which the University of Oxford will use the data in this Data Sharing Agreement seeks to answer the following questions:
Q1) Are there inequalities in Emergency Department (ED) waiting times by socioeconomic status, between and within hospitals, allowing for severity of the patient’s presenting condition?
Q2) Do longer waits translate into worse patient health outcomes, by severity of condition?
There is a further work package (WP2) in the overall project which will use qualitative research methods (and none of the data in this application) which seeks to answer:
Q3) Are there differences in professional behaviour and organisational cultures in EDs that influence waiting times? Are these patterned by socioeconomic status and other patient characteristics?

Building on existing evidence about health inequalities and the use of ED care, the project will consider all health conditions, controlling for severity, and will then focus on a set of specific health conditions known to be more prevalent in deprived areas:
1. Heart failure, a common ambulatory care sensitive condition (that can be managed in the community) for which there is a known association between deprivation and adverse outcomes.
2. Chronic obstructive pulmonary disease (COPD), which has a known association with socioeconomic disadvantage and frequent ED attendances.
3. Asthma among children and adults. There is evidence that children in inner cities make heavy use of EDs.

The main objectives are to:
1. Understand waiting time variation in EDs by socioeconomic status, age, gender, ethnicity, attendance mode (ambulance, walk-in) and referral mode (by GP or 111), controlling for patient case-mix and severity (Q1), and other factors.
2. Provide evidence showing if/how differences in waiting times affect health outcomes for patients (Q2) and explore if this is patterned by socioeconomic deprivation (Q2).

The following NHS England Data will be accessed:
• Hospital Episode Statistics
o Admitted Patient Care
o Accident & Emergency
o Critical Care
o Outpatients
• Uncurated Low Latency Hospital Data Sets - Emergency Care
• Civil Registration Mortality

These datasets are necessary for the research team at the University of Oxford to identify whether patients that attend ED are discharged or admitted, classify the cause of attendance, understand whether the diagnosis, procedure and length of stay if the patient was admitted, and ascertain whether the patient subsequently died. Emergency Care data linked to HESA&E, HESOP, HESAPC, and HESCC data will make it possible to:
1. Follow patients that attend ED through any stage of health care (i.e., inpatient / outpatient / discharged),
2. Record their process of admission and outcome (e.g., length of stay and clinical health outcome);
3. Control for the utilisation of hospital care before and after an acute illness that required ED attendance.
Civil Registrations of Death data will allow the research team to link ED attendances with out-of-hospital mortality outcomes.

The level of the Data will be:
• Pseudonymised

The Data will be minimised as follows :
• Limited to data between 2016/17 and 2023/24 latest available (as a one-off drop of data);

The University of Oxford is the research sponsor and the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research, which protects and promotes the interests of patients, service users and the public, and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care.

The funding is provided by the NIHR Health and Social Care Delivery Research (HS&DR). The funding is specifically for the study described. Funding is in place until July 2025.

The University of Oxford is working alongside a PPIE group in relation to this study. The group were able to advise and contributed to the study design. The University of Oxford has made a commitment to share the results of this study (after it has been sufficiently anonymised with small number suppression rules upheld). The group have expressed a positive outcome of the need of this study.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for policy-makers, local decision-makers such as doctors, and patients to inform best practice to improve the care, treatment and experience of health care users relevant to the subject matter of the study.

The evidence produced by this research will be directly relevant to:
a) NHS patients and NHS organisations,
b) policymakers, planners and decision-makers, and
c) health care providers, managers and practitioners.

The study has considerable potential for positive health care, societal and economic impacts. As an important objective of the NHS Constitution is equality of access to health care, it is hoped that the NHS would be keen to address any inequalities in ED waiting times with the support of new evidence. Understanding and tackling inequalities should improve public confidence in the NHS, especially among disadvantaged groups. This is likely to benefit society by increasing social solidarity. Addressing inequalities can also lead to more efficient use of resources, if, as is likely, inequalities mean that decisions on prioritisation of patients in ED are currently less than optimal. This would be a valuable economic benefit.

This research will have impact for health care services policy and research. It will provide new evidence to help policy makers and healthcare professionals consider how best to address any inequalities in waiting times. This will benefit policy makers who are currently interested in issues of inequality in the context of the Government priority on ‘levelling up’. The research team will use collaborative networks established through previous work for DHSC and NHS England to convey our findings to them.

It is intended that this study will provide evidence and recommendations that will lead to reduction and ultimately elimination of any socioeconomic inequalities in waiting times in EDs. It will in this way benefit NHS patients, especially patients from disadvantaged communities. Achieving this aim will require promoting impact among NHS decision-makers. The research team will therefore seek opportunities to give seminars or hold discussions with DHSC, NHS England, NHS agencies and professional organisations, as well as patient networks and voluntary organisations.

Researchers’ links, and those of the project advisers and colleagues, with PPI networks, Royal Colleges, NHS and voluntary organisations and DHSC will be used to promote impact of our study.

The use of the data could:
• help the system to better understand the health and care needs of populations.
• advance understanding of regional and national trends in health and social care needs.
• inform planning health services and programmes to improve equity of access.
• inform decisions on how to effectively allocate and evaluate funding according to health needs.

To maximise the impact on academia and implementation, three papers will be submitted to leading economic, health policy and health services journals and our research will be presented at conferences and seminars, including the BSA Medical Sociology Group and UK Health Economists’ Study Group meetings. This multi-professional study will provide scope for learning between researchers and for new collaborations to develop further proposals.

Regular meetings with PPI groups and the advisory group will be held every 6 months.

Two members of the qualitative research team and 2 members from the quantitative research team will attend conferences in late summer 2024 to share findings.

A workshop will bring together stakeholders from different backgrounds to discuss the work.

This study could potentially lead to several benefits for patients. Here are some potential benefits that could be expected based on the findings:

• Improved access and reduced wait times: If the study identifies factors contributing to longer wait times for certain patient groups, such as those from disadvantaged backgrounds or minority populations, the findings could inform strategies to address these disparities. Implementing measures to reduce wait times for these groups could lead to more equitable access to emergency care.

• Enhanced patient experience: Prolonged waiting times in emergency departments can contribute to patient dissatisfaction, anxiety, and frustration. By addressing systemic factors that lead to longer wait times for specific patient populations, the overall patient experience could be improved, leading to greater satisfaction and better health outcomes.

• It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

These are the actions that we will take to optimise the potential public benefits from the use of these data:

Publish the findings in peer-reviewed medical journals and make them open access to reach a wide academic audience.
Present the research at relevant healthcare conferences and seminars to share the findings with medical professionals, administrators, and policymakers.
Issue press releases and conduct media outreach to raise awareness among the general public through news outlets and online channels.

Stakeholder engagement:
Reach out to patient advocacy groups, charities, and societies focused on healthcare access, equity, and patient rights to share the findings and seek their support in amplifying the message.
Collaborate with professional medical associations and healthcare provider organizations to disseminate the findings among their members and encourage implementation of recommended changes.
Engage with policymakers, legislators, and government agencies responsible for healthcare regulations and policies to advocate for systemic changes based on the findings.

Public awareness campaigns (if findings warrant significant attention):
Develop educational materials (brochures, infographics, videos) that explain the findings in an accessible manner for the general public.
Utilize social media platforms and online channels to reach broader audiences with the findings and raise awareness.
Partner with community organizations, local governments, and grassroots movements to amplify the message within various communities.

Continuous engagement and updates:
Host regular meetings, forums, or webinars to discuss the findings, gather feedback, and provide updates on the implementation of recommendations.
Establish advisory committees or working groups with relevant stakeholders to guide the implementation process and track progress.
Provide periodic progress reports or updates to maintain transparency and accountability.

Outputs:

The expected outputs of the processing will be:
• A final report of findings available for everyone interested in this topic. [Month 17/18]
• Submissions to peer-reviewed journals [at months 6,12,18, 24]
• Presentations to academia at national and international conferences

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

Dissemination of results/outputs
The research team will promote the dissemination of the research to stakeholders during the project and after its completion. The dissemination activities will target an audience of health care professionals, patient organisations, health care providers, national and local policy-makers, and researchers. The aim of the dissemination activities will be two-fold:
1. To enable engagement with scientific and policy-making communities,
2. To ensure that knowledge developed by the research can inform policy and practice and thus benefit patients, their families and communities.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Workshops involving stakeholders and researchers
• Social media
• Public reports
• Press/media engagement
• Participant newsletters

The research team will disseminate the research findings to patients, clinicians, professional bodies and policymakers, as well as publish in academic journals. The evidence produced by this research will be directly relevant to:
1. Policymakers, planners and decision-makers,
2. Health care providers, managers, practitioners,
3. Patients and their families.

The dissemination activities are designed to inform and support health and care policy through developing evidence that is crafted and presented with the policy user in mind, rigorous and authoritative, and timely.

The dissemination activities will include a one-day conference for key stakeholders at the end of the project, seeking their responses to the study’s results. The research team will ensure that a range of relevant organisations are included at the conference, such as professional organisations, patient organisations, health care providers, ICSs, DHSC and NHS England. This event will be press released.

The project will inform practice at local and national levels, drawing on the roles and contacts of the co-applicants and collaborators to ensure wide dissemination to policymakers, professional societies, health care providers and relevant research centres.

The project will raise public awareness by producing lay summaries of the results in accessible formats, including through webinars and blog entries, which will ensure broad dissemination through the extensive networks of the stakeholders which are collaborators in the project or with which the research team have contacts.

Communication of results/outputs - Active communication activities will ensure that: information about the project and its results reaches interested groups and civil society. Communication channels: website and newsletters, open lectures and talks, exhibition at public events, posters, press/media engagement and other public promotion of the research, stakeholder mailing list, etc.

The research team at the University of Oxford will draw on the roles and contacts of the co-applicants, collaborators, and funder to ensure wide dissemination of the outputs of the research to policymakers such as Getting It Right First Time, DHSC, NHS England and other NHS bodies among others.

The research team will ensure that the research findings are synthesised and communicated in a meaningful and clear way, such that the results of this study can be employed by all beneficiaries in practice to deliver real healthcare benefits.

Processing:

No data will flow to NHS England for the purposes of this Data Sharing Agreement (DSA).

NHS England will grant access to the Data via the Secure Data Environment (SDE). The SDE is a secure data and research analysis platform. It allows approved researchers with approved projects access to pseudonymised data and industry-leading analytics tools.

NHS England will provide access to the relevant records from the HES, mortality, and Emergency Care Data to the University of Oxford. The Data will:
• Contain special categories of personal data but with no direct identifying data items. The Data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

The Data will not be transferred to any other location.

SDE users can request exportation of aggregated analysis results (suppressed and summarised according to the NHSE SDE Disclosure Control rules) subject to review and approval by the NHS England SDE Output Checking team. The SDE Output Checking team will ensure that no output contains information which could be used either on its own or in conjunction with other data to breach an individual's privacy.

Access to the SDE is controlled via a multi-factor authentication mechanism and access is restricted to the datasets and periods detailed within this DSA. The access and use of the system is fully auditable, and all users must comply with the use of the Data as specified in this DSA.

Users are only authorised to access the Data specified in this DSA and can utilise a variety of analytical tools available within the SDE platform. Users are not permitted to export record-level data from the SDE.

The Data will be stored on servers at NHS England.

Remote processing will be from secure locations within the England.

The Data will not leave the England at any time.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will be combined (for each individual) with freely available data such as the number of beds at the trust level, unemployment rates at the LSOA (Lower Layer Super Output Area) level, and the number of benefit claims at the LSOA level,

Analysts from the University of Oxford will analyse the Data for the purposes described above.

The Effect of Operational Interventions on Maternity Care Pathways and Health Outcomes — DARS-NIC-712819-X8G2J

Opt outs honoured: unknown (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-07 – 2026-12 2024.08 — 2025.03.

Access method: System Access
(System access exclusively means data was not disseminated, but was accessed under supervision on NHS Digital's systems)

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Emergency Care Data Set (ECDS)
  2. Hospital Episode Statistics Accident and Emergency (HES A and E)
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)
  4. Maternity Services Data Set (MSDS) v1.5
  5. Maternity Services Data Set (MSDS) v2
  6. Uncurated Low Latency Hospital Data Sets - Emergency Care

Type of data: Anonymised - ICO Code Compliant (note: this information not disclosed for TRE projects )

Objectives:

University of Oxford requires access to NHS England data for the purpose of the following research project:

The Effect of Operational Interventions on Maternity Care Pathways and Health Outcomes

The following is a summary of the aims of the research project provided on behalf of University of Oxford:

The purpose of this project is to analyse maternity services & secondary care data to determine how different operational interventions impact maternity care pathways and consequently, different health outcomes.

The NHS has set out several priorities in addressing health inequalities. One of the main areas which is consistent within national and local planning are inequalities in maternity and neonatal care, as set out within the annual NHS Priorities and Operational Planning Guidance. These priorities are largely in response to the findings of reports such as those by Mothers and Babies: Reducing Risk through Audits and Confidential Enquiries across the UK (MBRRACE-UK), revealing disparaging outcomes in maternity and neonatal care for socioeconomic deprived individuals and ethnic minorities.

This research project aims to support these priorities by addressing this topical issue through:

- Developing tools to understand how the study can use the mother’s demographic data and ante-natal care pathways to segregate the population in a meaningful way.
- Investigating the impact of operational interventions such as continuity of care for the different sub-populations.
- Proposing personalised pathways to address health inequalities and improve the operational efficiency of the public health system based on the characteristics of mothers.

The operational interventions refer to changes in the way the patient is treated throughout their interaction with healthcare services. The study will look to consider:

1. Continuity of Care: This refers to providing a consistent healthcare experience for the patient by minimizing changes in healthcare providers throughout the maternity care pathway. Continuity of care ensures that patients are treated by the same healthcare professionals (like midwives or obstetricians) during prenatal visits, labor, delivery, and postnatal care. This consistency fosters a better understanding of the patient's history, preferences, and needs, leading to improved communication, trust, and personalized care. On the other hand, continuity of care may result in increased system congestion.
2. Frequency of Visits: This intervention addresses the number of scheduled appointments or check-ups during the pregnancy. A tailored approach to visit frequency can identify potential risks or complications early, ensure proper monitoring of the baby's development, and provide adequate support to the mother. By adjusting the frequency of visits based on individual needs, healthcare providers aim to enhance the quality of care while managing resources efficiently.
3. Frequency of Scans: Ultrasound scans are an essential component of maternity care, used to monitor fetal development, identify abnormalities, and assess pregnancy progress. Operational interventions may involve adjusting the number and timing of scans to ensure they align with patient health conditions, while avoiding unnecessary scans to minimize risks and reduce costs.
4. Staffing Levels and Skill Mix: Ensuring that maternity care units are appropriately staffed with qualified professionals, with the right balance of experience and expertise, can significantly impact care quality and outcomes. This intervention involves adjusting staffing levels to meet patient demands and ensure safe care delivery.
5. Integration of Technology: The use of telemedicine, and other digital tools can improve communication among healthcare providers, streamline care processes, and enhance patient engagement. Operational interventions in this area might focus on implementing or optimizing technology to support continuity of care and better patient outcomes.
6. Collaborative Care Models: These models encourage collaboration between various healthcare providers involved in maternity care, such as midwives, obstetricians, pediatricians, and primary care physicians. By fostering teamwork and communication, these interventions can lead to more coordinated care pathways and improved outcomes for mothers and newborns.

This project has the following aims:
1. Compare outcomes across different sub-groups of patients to determine disparities in health outcomes of those subject to different socioeconomic factors.
2. Compare care cluster pathways across different sub-groups of patients to provide intelligence on how varying care pathways can impact the health outcomes of patients, including time under care. Specifically, to perform analysis to cluster the ante-natal pathways and examine what are the significant distinguishing factors between the pathways.
3. Evaluate the impact of operational interventions on health outcomes. This will aim to assess the effectiveness of interventions such as continuity of care, frequency of visits, frequency of scans and whether these have a meaningful impact on health outcomes. Further to this, to assess whether the impact of these interventions for socioeconomic deprived patients is more significant. For example, the ability to see the same provider who they have built a relationship with at each appointment for deprived patients.
4. Prescriptive analysis - Based on the analyses in aims 1-3, the study then aims to develop personalised pathways based on the clinical and socioeconomic characteristics of the mother. The study will develop and validate novel ante-natal pathways that account for both clinical and socioeconomic patient characteristics as well as operational constraints of the NHS.

The following NHS England Data will be accessed:
• Hospital Episode Statistics
o Admitted Patient Care – necessary to provide information on patients use of secondary care services that may not be recorded within the Maternity Services Dataset (MSDS), but will still contribute to accurately determining the care pathways and health outcomes of patients & provide insight into any acute and relevant chronic conditions that may confound pregnancy outcomes.
o Accident & Emergency / Emergency Care Data Set (ECDS) & Uncurated Low Latency Hospital Data Sets - Emergency Care – necessary to provide information on patients use of emergency care services, who have or are currently receiving maternity care. This data will allow the study to consider the full picture of these patients care pathways and account for emergency care events which can contribute to health outcomes during pregnancy within the analysis.
• Maternity Services Dataset (MSDS) – necessary to provide information on the care pathways of maternity, natal & neonatal patients whilst also helping the study to build a picture the socio-economic characteristics of these patients for analysis addressing the aims of the study.

The level of the Data will be pseudonymised. The Data contains multiple sensitive fields which have been selected for the purpose of this analysis. The sensitive data items are key to ensure the the effectiveness of the analysis. In order to reconstruct maternity pathways effectively, it is imperative to understand the circumstances under which patients accessed emergency care, which requires data on start dates and times, and expiry dates and times. This information is essential for creating a chronological timeline for each patient, allowing for a comprehensive understanding of their healthcare journey. The inclusion of ethnic categories aligns with the aims and objectives of the study. Specifically, the study aims to identify and investigate potential disparities in maternity pathways and health outcomes across different ethnic groups and explore recommendations for improvements.

Access to consultant codes and referrer codes within the HES APC data is vital for tracking which professionals are involved in each patient’s care along their maternity journey. This information allows the study to explore the continuity of care, collaboration among healthcare providers, and any variations in care delivery. Understanding these patterns can provide insights into best practices and areas needing improvement, so that the study can conduct a comprehensive analysis of maternity pathways and associated outcomes.

Several factors pertaining to the mother's health and social circumstances may significantly impact her pregnancy journey and subsequent outcomes. Variables within the MSDS dataset corresponding to complex social factors, mental health conditions, adherence to folic acid supplementation, smoking and alcohol consumption, are crucial for identifying vulnerable groups and tailoring interventions accordingly. Additionally, previous pregnancy outcomes serve as important controls to account for in the analysis. The outcome of the current pregnancy is of central importance in our study, since the study hypothesizes that maternity pathways influence outcomes of the pregnancy. Moreover, factors such as the support network and employment status of the mother can affect her overall well-being and mental health, which are also known to impact pregnancy outcomes.”

The Data requested from the Maternity Services Dataset (MSDS) will be minimised as follows:
• Limited to data between 2018/19 to 2022/23 financial years.
• The Data will cover patients nationally & will include all pregnancies recorded within the above time frame.
• The Data will look at all patients episodes, including the unborn child and neonatal records of patients.
• The Data will be limited to a subset of the total available fields available within the datasets as selected by University of Oxford.

The Data requested from Hospital Episodes Statistics & Emergency Care Datasets (ECDS) will be limited to only include individuals who appear in the MSDS Data requested under this agreement, in addition to:
• Limited to data between 2016/17 to 2022/23 financial years - the study requires access to patients secondary care data from the period preceding their appearance within the MSDS datasets in order to analyse any acute and relevant chronic conditions and associated care delivered which may impact a pregnancy.
• The Data will be limited to a subset of the total available fields available within the datasets as selected by University of Oxford.

University of Oxford is the research sponsor and the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest as it aims to support improved intelligence in the development of policy and guidance on provision of health care regarding maternity care decisions. Through this improved research, the study aims to help address the key priorities set by the NHS focused on improving the health outcomes of maternity patients & reducing inequalities that a large proportion of the population may be subject to. This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research, which protects and promotes the interests of patients, service users and the public, and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care.

The funding is provided by the John Fell Fund at University of Oxford. The funding is specifically for the study described. The funder(s) will have no ability to suppress or otherwise limit the publication of findings.

Data will be accessed by researchers from the University of Oxford and individuals with an honorary contract with University of Oxford – a collaborating researcher from University of Cambridge working within the study and with the Data and an individual from London Business School specialising in statistical analysis & interpretation of results for stochastic modelling and optimization of service systems focused on by the study. The individuals have completed mandatory data protection and confidentiality training and is subject to University of Oxford’s policies on data protection and confidentiality. The individuals accessing the data will do so under the supervision of a substantive employee of University of Oxford. University of Oxford would be responsible and liable for any work carried out by the individuals. The honorary contractors would only work on the data for the purposes described in this Data Sharing Agreement (DSA).

The study has engaged with two different healthcare professionals prior to the initiation of the study. The input hoped to be gained from their involvement were for the purpose of:

- Providing insights into outcomes
- Associate data driven findings with clinical knowledge and real world impacts
- Ground proposed solutions from these outcomes into practise

Upon initially reviewing the proposed study, the individuals supported the study overall and the use of the data for the purposes described above.

The study has set out an ongoing Patient & Public Involvement & Engagement plan for the duration of the study. The plan includes engagement with patient & public representative groups such as Women's Voice & Maternity Action. The groups will be consulted on their views of the research hypothesis & questions posed by the study, the processing of the Data for the purpose of the study & interpretation of the outputs generated by the study. Engagement is planned throughout 2024 & 2025 for the term of the study and the review of study outcomes.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for policy-makers, local decision-makers such as doctors, and patients to inform best practice to improve the care, treatment and experience of health care users relevant to the subject matter of the study.

The use of the data could:
• Help the system to better understand the health and care needs of populations.
• Advance understanding of regional and national trends in health and social care needs.
• Advance understanding of the need for, or effectiveness of, preventative health and care measures for particular populations or conditions that may cause concern during pregnancy such as cardiovascular problems or diabetes.
• Inform planning health services and programmes, for example to improve equity of access, experience and outcomes.

It is hoped this project will yield valuable insights on the impact of operational interventions on maternity care pathways and health outcomes, to inform potential policy changes made by NHS around both ante-natal and post-natal operational interventions on maternity pathways. By focusing on these operational interventions, this research project aims to explore how changes in these areas can affect maternity care pathways and health outcomes, ultimately providing insights into best practices for the UK NHS.

The project hopes to provide detailed understanding of the maternity care pathways and health outcomes of different sub-groups, which informs social care and health policy making and intervention design. In particular, the findings “the findings will include recommendations on how to effectively reduce the existing health inequality in the field of maternal services, better support patients from deprived areas in the provision of health services and social care, and facilitate local maternity systems in implementing evidence-based and targeted interventions for different sub-groups and risk-factors of patients. The Data will be used to measure the effect of currently established pathways of care on quality and access to care, to estimate the impact of operational intervention on the population and the healthcare system, and ultimately to develop and analyse the performance of new personalised pathways of maternal care for the national healthcare system.

The project seeks to deliver these benefits through application of its outputs, specifically:
• Informing NHS Policy and Operations: By analysing the effects of various operational interventions on maternity care pathways, this study provides data-driven insights to inform NHS policy decisions. The findings can guide both antenatal and postnatal interventions, helping to shape operational strategies that improve care quality and patient outcomes. The results may lead to enhanced protocols, better resource allocation, and improved operational decision-making within maternity units.
• Reducing Health Inequalities: The project's focus on sub-groups within maternity care pathways has the potential to address health disparities. By identifying patterns and outcomes across different demographic groups, including those from deprived areas, the study can inform social care and health policy. This insight will allow policymakers to design targeted interventions to reduce health inequalities, thereby improving access to quality maternity care for underrepresented or marginalized groups.
• Academic Contribution and Dissemination: This study seeks to address a gap in the current academic literature on healthcare operations management in maternity services. To date, the sole relevant paper in the field of healthcare operations management is the work by Freeman et al. (2016), published in Management Science, which demonstrated the significant influence of resource availability on patient-care pathways in the context of maternity care, drawing on data from a maternity hospital in the UK. Given the limited research in this specific field, the project has the potential to drive further academic interest and research.

Academically, it is noteworthy that there is a noticeable lack of studies that specifically focus on the operational implications of maternal services. To date, the sole relevant paper in the field of healthcare operations management is the work by Freeman et al. (2016), published in Management Science, which demonstrated the significant influence of resource availability on patient-care pathways in the context of maternity care, drawing on data from a maternity hospital in the UK. As such, this research project looks to drive more operations related research in maternity services.

The aims of the study seek to yield operationally valuable insights in the field of maternal services and to effectively reduce the existing gap between patients from deprived areas and facilitate local maternity systems in implementing evidence-based and targeted interventions for different sub-groups of patients. It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

Outputs:

The expected outputs of the processing will be:
1. Submissions to peer review journals, including publications in reputable health journals such as British Medical Journal, as well as Management Science, Manufacturing & Service Operations Management journals among others.
2. Presentations at relevant international conferences, such as the Institute for Operations Research and the Management Sciences (INFORMS)
3. Presentations, conferences, and partnerships with clinical partners, experts in the field, and collaborators in Oxford, Cambridge and London, e.g., maternity units in the Oxford university Hospitals and Cambridge university Hospitals to ensure that the results are disseminated widely among the maternity services community. To maximize the impact of the findings, the research team plans to share the results with key stakeholders and decision-makers in maternity services, including NHS executives, healthcare policymakers, and professional bodies.
4. Publications on social media outlets such as business reviews in universities.

The outputs will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset from which the information was derived. No data that identifies an individual consultant or their performance is permitted to be published.

The output will be communicated to relevant recipients through the following dissemination channels:
1. Peer review journals
2. Social media: The study will promote results through social media platforms and business school magazines/websites, such as Think at London Business School. The research team will work with the media team at the institution to write media pieces about the research findings, including newspapers, online media platforms, and other media outlets.

The target time frame for achieving these outputs is the early 2025 and will be ongoing throughout access to the data.

This research project examining the impact of operational interventions on maternity care pathways and health outcomes offers a range of significant benefits across multiple dimensions. Below is a more detailed description of these benefits, including plans for dissemination and the broader impact on maternity services and healthcare policy.

Processing:

This data sharing agreement is for online access to the record level datasets via the NHS England Secure Data Environment (SDE). The system is hosted and audited by NHS England meaning that large transfers of data to on-site servers is limited and NHS England has the ability to audit the use and access to the data. NHS England will grant University of Oxford access to the relevant records from the HES, ECDS & MSDS datasets via NHS England’s Secure Data Environment (SDE). The Data will contain no direct identifying data items. The Data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

The Secure Data Environment (SDE) is a data storage and access platform that enables approved users to access de-identified data and analytical tools for approved projects. Users must identify themselves via a multi-factor authentication mechanism and are only able to access the datasets detailed within this agreement. Users can request that aggregated outputs are exported from the system following approval by trained NHSE staff. The access and use of the system is fully auditable, and all users must comply with the use of the data as specified in this agreement.

Users can produce aggregate outputs from the system, however, record level extracts are not permitted. As record level data cannot be extracted from SDE. The system accommodates a variety of technical tools for data analysis.

Researchers will conduct analyses with various levels of complexity, some will be interested in simple summary statistics, some will look at trend analysis, others will apply more complex analysis techniques.

Data processing will be carried out by substantive employees of the University of Oxford who have been appropriately trained in data protection and confidentiality. Additional data processing may be carried out by University of Oxford honorary contractors who have signed a contract with the University ensuring they abide by the University's statutes and regulations encompassing data protection and confidentiality. NHS England are listed as a data processor as they host the SDE environment in which the data will be accessed.

Only registered users will have access to record level or aggregate data containing small numbers downloaded from the system. All users with access to the data are restricted to substantive employees or honorary contractors of the University of Oxford. Following completion of the study & analysis, access to the record-level data will be closed.

The Data will not leave England at any time. The Data will not be linked with any other data.

Any outputs that are produced from the data that are to be published or shared with a third party (individuals or organisations outside of the analytical team) will be aggregated with small number suppressed, as set out within NHS England guidance applicable to each data set (to note, no pseudonymised data will be downloaded from the SDE; this refers to aggregated outputs only).

Following similar principles to those adopted by the SAIL Databank for Wales (https://saildatabank.com/saildata/data-privacy-security/#secure-access) and the Scottish National Data Safe Haven (https://www.isdscotland.org/Products-and-Services/EDRIS/Use-of-the-National-Safe-Haven/), only summary, aggregate results data are exported from the SDE by Department of Health and Social Care, subject to the approval of NHS England’s trained output checkers. This ensures that no output contains information which could be used either on its own or in conjunction with other data to breach an individual's privacy.

Researchers from the University of Oxford will analyse the Data for the purposes described above

Outcomes Data for A Study of Cardiovascular Events iN Diabetes – PLUS (ASCEND PLUS) — DARS-NIC-717832-F6F3H

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-07 – 2027-07 2024.09 — 2025.03.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Cancer Registration Data
  2. Civil Registrations of Death
  3. Demographics
  4. Diagnostic Imaging Data Set (DID)
  5. Emergency Care Data Set (ECDS)
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)
  7. Hospital Episode Statistics Critical Care (HES Critical Care)
  8. Hospital Episode Statistics Outpatients (HES OP)
  9. Medicines dispensed in Primary Care (NHSBSA data)
  10. National Diabetes Audit

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires access to NHS England data to follow-up participants recruited to the following clinical trial:
Outcomes Data for A Study of Cardiovascular Events iN Diabetes – (ASCEND PLUS)

The following is a summary of the aims of the clinical trial:
The trial aims to provide evidence about both the efficacy and safety of prolonged treatment with oral semaglutide in individuals aged at least 55 years, with Type 2 Diabetes (T2DM), without a history of a heart attack or stroke, and without any upper or lower Haemoglobin A1c (HbA1c) threshold.

Oral semaglutide and other GLP-1 RAs control blood sugar, reduce weight and, in high-risk patients, reduce the risk of adverse cardiovascular health outcomes (e.g. heart attacks and strokes). There is also some evidence that oral semaglutide may protect against other complications such as dementia and kidney disease. However, these medications are not currently widely used, partly because they have not yet been shown to be beneficial in patients with T2DM without existing cardiovascular disease. The ASCEND PLUS trial is aiming to provide substantive evidence in these patients both during the 5-year treatment phase and longer term.

The trial will assess the effect of treatment on prevention of heart attacks, strokes or mini strokes, the need for heart artery ‘balloon’ and bypass procedures, and deaths, and assess the overall safety of prolonged use of oral semaglutide in treating T2DM.

The following NHS England Data will be accessed:
• The Hospital Episode Statistics (HES) Admitted Patient Care (APC), Outpatients (OP) and Critical Care (CC) subsets – necessary to determine the cause of death, cardiovascular outcomes, serious outcomes (such as major adverse limb events, the need for surgical treatment to improve poor limb blood flow, decline in kidney function), and other adverse outcomes (including dementia, cognitive impairment, chronic diseases related to excess weight)

• Emergency Care Dataset (ECDS) - necessary because for the same purposes as the HES, but also allows the study to detect A&E presentations that may have occurred as a result of low blood sugar
• Cancer Registration Data - necessary because this is necessary to detect cancer events that arise and enable the reliable assessment of the long-term safety of the treatment.
• Civil Registrations of Death - necessary to detect date and cause of deaths.
• Demographics - necessary because the trial needs to identify when to censor participants during follow-up. The censor date is needed to calculate the follow-up time for each participant.
• Diagnostic Imaging Dataset (DIDs) - necessary because the dataset may identify or confirm outcomes of heart attacks, TIAs, strokes and heart failure helping to provide the most reliable information on the outcomes being investigated for the ASCEND PLUS trial
• Medicines dispensed in Primary Care (NHS BSA data) - necessary to assess the medicines dispensed to study participants to get more comprehensive detail on their outcomes. For example, prescriptions of dementia treatments will provide crucial evidence on the diagnosis and treatment of dementia. This dataset will be used for other outcomes e.g. identifying the date when participants commence insulin therapy. The data will enable further measurement of the safety and effectiveness of oral semaglutide, including in the long-term. This information is hugely relevant to large numbers of patients in the UK and globally.
• National Diabetes Audit (NDA) - necessary to detect diabetes-specific outcomes; retinal screening results, weight, biochemistry (including HbA1c, blood lipids, serum creatinine and estimated glomerular filtration rate (eGFR), Urine Albumin-to-Creatinine Ratio (UACR).

The Data will be minimised as follows:
• Limited to a study cohort who consented to participate in the study, following being identified (as being over the age of 55 and having type 2 diabetes) and invited to join the study by the NHS DigiTrials recruitment support service. The total cohort is expected to be between 25,000 and 30,000 individuals.
• For HES CC, HES OP, ECDS, DIDS the Data will be limited to records between 1st of April 2023 and the Latest Available, with quarterly updates thereafter until the expiry of this Data Sharing Agreement.
• For HES APC, Medicines Dispensed in Primary Care and NDA the Data will be limited to records between 1st of April 2018 to the Latest Available, with quarterly updates thereafter until the expiry of this Data Sharing Agreement (with exception to NDA which will be annually thereafter).
• For Demographics and Civil Registrations of Death, the Data will be limited to reflect the current details of the participants, with quarterly updates thereafter until the expiry of this Data Sharing Agreement.
• For Cancer Registration, the Data will include all history, with annual updates thereafter until the expiry of this Data Sharing Agreement.

The University of Oxford is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

The funding is provided by Novo Nordisk, who provides the drug being tested as part of this trial. The funding is specifically for the trial described. Funding is in place until 2029.

The funder will have no ability to suppress or otherwise limit the publication of findings.

Novo Nordisk has contributed to the overall purpose and high level design of the trial but has not in any way determined the purposes and means of processing, and has not commissioned the University of Oxford to carry out this work on their behalf.

The study was initiated and designed by the independent investigators at NDPH, University of Oxford.

Novo Nordisk will provide funding and study medication (oral semaglutide and matching placebo). There is a safety data exchange agreement between the sponsor (University of Oxford) and the funder (Novo Nordisk) describing potential safety reporting obligations of the funder. There are no obligations of any commercial nature with this company at this point. However, if the trial results are positive (i.e. participants in the semaglutide arm have less occurrence of illness & death than those in the placebo arm), and the drug is successfully relabelled and remarketed, it is likely that Novo Nordisk will benefit financially from this. However, the primary aim of the study is to improve the health of people with T2DM by providing reliable evidence about the benefits and harms or oral semaglutide.

The ASCEND PLUS trial is overseen by a Steering Committee of 19 people chaired by members of the University of Oxford, and composed of academics from the contributing regions, lay members and 4 employees of Novo Nordisk. The Steering Committee has an advisory and oversight capacity for making major organisational and policy decisions and providing scientific advice. Its purpose is to determine the strategy of the trial and oversee its delivery.

There will be no Steering Committee decisions around the use of NHS England data. The ratified Steering Committee Charter prevents the possibility that Novo Nordisk members could unilaterally influence the publication of results.

Two lay members were recruited to the trial Steering Committee (TSC) and attended the first TSC meeting in June 2021 and subsequent meetings, ensuring patient and public involvement in the high-level strategic decisions for the trial.

The trial has convened the ASCEND PLUS Public Advisory Group (ASCEND PLUS PAG), a diverse group of patients and the public, to input into the whole life-cycle of the trial. The ASCEND PLUS PAG give feedback, advice and opinions across different aspects of the trial including recruitment materials, participant questionnaires, website development, strategies to maintain participant adherence and engagement, and dissemination of the trial results.

The Study Team is undertaking continued involvement and engagement by the ASCEND PLUS PAG to ensure that all those living with diabetes in mainland UK are represented in the trial and to encourage and support participant retention.

Expected Benefits:

According to Diabetes UK (https://www.diabetes.org.uk/), in February 2022 4.3 million people in the UK had a diagnosis of diabetes and this number is rising each year.

Globally, the 10th Edition of IDF Diabetes Atlas estimates that in 2021 there were more than half a billion people living with diabetes, affecting men, women, and children of all ages in every country. The number is projected to more than double to 1.3 billion people in the next 30 years by 2050, with every country seeing an increase. In 2019, diabetes was the direct cause of 1.5 million deaths and 48% of all deaths due to diabetes occurred before the age of 70 (https://www.who.int/news-room/fact-sheets/detail/diabetes).

The data collected from central NHS registries for the ASCEND PLUS study will be used to assess whether there are any benefits or harms of semaglutide during the 5- year treatment phase of the trial helping to provide evidence for the treatment of people with T2DM. Following this, the study will assess whether the treatment provides additional benefits or harms, during the long term follow-up phase of the study (anticipated to be for 20-years after the scheduled treatment period ends).

T2DM is associated with elevated risks of cardiovascular disease and other health conditions. Delaying the severity and onset of these are some of the benefits expected to be found from the study. The conditions we anticipate seeing benefit for are:

Cardiovascular Outcomes
• Pooled data from observational studies, predominantly conducted in Europe and North America show that the presence of diabetes approximately doubles the risk of vascular outcomes such as coronary heart disease, ischaemic stroke and cardiovascular death while more extreme risks are observed in regions where medications to control glycaemia are not widely available. It is hoped that semaglutide will delay or prevent these outcomes.

Decline in Kidney Function
• Other diabetic complications include kidney disease. It is possible that semaglutide may slow the rate of kidney decline which will improve lives.

Cognitive decline and dementia
• Observational studies have shown that diabetes and obesity are both associated with a 50% increased risk of dementia and a 20% increase in the rate of cognitive decline. These conditions present major health care and social burdens which are worsening globally with increasing lifespan, so using the NHS England data to obtain randomised evidence of the effect of semaglutide therapy on these outcomes would be highly beneficial worldwide.

Vision
• With diabetic retinopathy and diabetic maculopathy being among the most common causes of registerable blindness among working-age adults in the UK. Using NHS England data, ASCEND PLUS study will be able to reliably assess the treatment effects on diabetic retinopathy, macular degeneration and cataracts through linkage to diabetic screening registry information. Visual loss impacts significantly on the quality of life for those people affected, as well as generating financial costs to the NHS ophthalmology services. Therefore the preservation of vision is extremely important.

Informing guidelines
• Oral semaglutide and similar drugs given by injection, are new treatments for diabetes, but clinical trials have only tested them in selected individuals with very high cardiovascular risks. If ASCEND PLUS shows that oral semaglutide is beneficial in a wider range of patients with T2DM (not just those at high cardiovascular risk) then the results could change national and international guidelines. This would mean more patients could be offered the treatment which is of wide public interest and importance to healthcare in general.

Methodology
• The trial should also generate important methodological insights, tools and resources to benefit future research especially using NHS England data linkage.

IMPACTS
1. Impact on patients
If the trial is positive (i.e., participants in the semaglutide arm have less occurrence of illness & death than those in the placebo arm) and the drug is successfully relabelled and remarketed, this should translate to improved outcomes for diabetes patients worldwide. Furthermore, updated guidelines based on the ASCEND PLUS results, if they show benefits of the oral semaglutide, would translate to the treatment being made available to a wider range of patients within the current marketing authorisation, resulting in a reduction in complications of diabetes.

2. Impact on healthcare providers in the UK and Worldwide
Diabetes has major effects on the health of those diagnosed, and incurs major costs to the NHS and health care providers worldwide. Any delay in the progression of the disease could result in improved health for diabetes patients and significant savings for health care providers.

Should ASCEND PLUS provide important new information, the Study Team hopes that data from the results of the trial will inform patients, clinicians and guideline groups globally. It could also provide evidence to submit to regulators for an extension of the current licenced indication in the UK and across the world.

3. Impact on trial design and cost
Other clinical trials run by NDPH such as ASCEND have found that in the UK, routine electronic health data such as that from NHS England, provides a cost-effective method of assessing the impact of treatment on disease. The ASCEND PLUS study design keeps the costs down as it does not need physical trial sites or complex data collection procedures. All interactions with participants will be conducted using innovative patient-centred web-based technology, with limited supplementation by telephone, video call and mailed letters. Study treatment is mailed to participants making it easier for them to participate and less expensive for the Study Team to implement. The design of the ASCEND PLUS study could inform the development of other trials.

Outputs:

The following details the expected outputs of the processing:

• Results will be communicated directly to trial participants. The Study Team plan to distribute plain English results co-developed by the ASCEND Patient Advisory Group (PAG) to surviving study participants by mail and shared with the public via the trial website. (https://www.ascend-plus-trial.org/).
• Submissions to peer reviewed journals such as the New England Journal of Medicine and the Lancet, with the next publication expected Q4 2028.
• Presentations at appropriate conferences such as the American Diabetes Association, the American Heart Association, the European Society of Cardiology and the International Clinical Trials Methodology.
• Posters displayed at departmental, national and international conferences (as above)
• Summaries of key findings will be placed on the study website and disseminated through Oxford University Communications channels.
• Press/media engagement and other public promotion of the research (e.g. via the Nuffield Department of Population Health website (https://www.ndph.ox.ac.uk/), or X (formerly Twitter) account (@oxford_ndph).
• Open lectures and talks
• Advice to government (including NHS England).

No individuals will be identified in any study reports.

We anticipate that the results from ASCEND PLUS will inform National and International guidelines. Examples of these guidelines could include the NICE guideline “Type 2 diabetes in adults: management” (https://www.nice.org.uk/guidance/ng28), the American Diabetes Association Standards of Medical Care in Diabetes guidelines (https://professional.diabetes.org/content-page/practice-guidelines-resources), and the diabetes guidelines from the European Society of Cardiology and the European Association for the Study of Diabetes. ASCEND PLUS could also potentially contribute to NICE guidelines such as the “Cardiovascular disease: risk assessment and reduction, including lipid modification” [https://www.nice.org.uk/guidance/cg181] as did the ASCEND trial (another NDPH diabetes trial, and the predecessor of ASCEND PLUS).

Any outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived e.g. the HES analysis guide.

University of Oxford’s contract with Novo Nordisk prohibits Novo Nordisk from preventing any publication that the Steering Committee has approved, even if trial results are negative.

Processing:

During the active recruitment period the cohort will be increasing and the Study Team will update the cohort provided to NHS England quarterly. Once recruitment has completed, the Study Team will update the cohort quarterly to remove any participants who have withdrawn. There will be no further additions after the recruitment finishes. The cohort will include participants who are eligible at screening, have provided written informed consent and entered the pre-randomisation run-in period. The Study Team have a regulatory requirement to report adverse events that occur during the run-in period as participants are taking active treatment. Any participants who are not randomised will be subsequently withdrawn from the cohort.

As part of this Data Sharing Agreement, to enable data linkage, the Study Team will send NHS England the cohort with the following identifiers:

• Study ID (unique participant identifier)
• NHS Number
• Date of Birth

NHS England will provide the relevant records from the following datasets on a quarterly frequency:
• HES APC – plus 5-years historical data
• HES CC
• HES OP
• ECDS (replaces HES A&E)
• Demographics
• Civil Registrations and Mortality
• Medicine dispensed in Primary Care (NHSBSA data) – plus 5-years historical data
• Diagnostic Imaging Dataset (DID)

NHS England will provide the relevant records from the following datasets on an annual frequency:
• National Diabetes Audit (NDA) – plus 5-years historical data
• Cancer – plus historical data

When new participants are added to the cohort, NHS England will provide the relevant records from the following datasets for each new participant::• HES APC, NHSBSA and NDA - back to 1 April 2018
• Cancers - all history

Historical data is necessary to help confirm that events that occur during the trial are new outcomes.

NHS England data will provide the relevant records from the HES, ECDS, deaths, cancer, demographics, NHSBSA, DIDs, and NDA datasets to University of Oxford. The data returned to NDPH will contain directly identifying data items including NHS Number and Date of Birth which are required to verify the cohort linkage and to link the data at record level with data already held by the University of Oxford.

Identifiable data is necessary for the purpose of data linkage and quality assurance of that linkage. The Data includes a range of detailed information that is necessary for analysis of the safety and effectiveness of the treatment.

Identifying data will need to be retained to enable further data linkages, such as that which will take place under this DSA. In addition, it is NDPH policy to retain research data for at least 25-years after the end of the trial as per the 2014 Clinical Trials Regulation (EU) No 536/2014: https://eur-lex.europa.eu/eli/reg/2014/536/oj.

The Data will be accessed by authorised personnel via remote access. The Data will be stored and remain on the servers at the University of Oxford at all times.

The data will not be transferred to any other location.
All information is stored securely on servers at the University of Oxford.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

The data will not leave the England at any time.

Access is restricted to individuals within the NDPH of the University of Oxford who have authorisation from the Information Asset Owner. All such individuals are substantive employees of the University of Oxford.

The Study Team need to link to all study participants at person record level with other Electronic Health Registries (which may include):

• NHS Central Register (NHSCR) - Scotland
• Public Health Scotland (PHS) - Scotland
• Digital Health & Care Wales (DHCW) - Wales
• Secure Anonymised Information Linkage (SAIL) – Wales
• Healthcare Quality Improvement Partnership (HQIP) – England & Wales
• National Institute for Cardiovascular Outcomes Research (NICOR) – England & Wales
• UK Renal Registry

Researchers from the NDPH of the University of Oxford will analyse the data for the purposes described above.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Study Team will not provide or otherwise make available the NHS England registry data to any third party or allow use of it or them by or on behalf of any third party, in whole or in part, whether by way of sale, resale, loan, transfer, hire or any other form of exploitation except and exclusively in the following circumstances:

1. In circumstances where there may be a need to contact an individual participant’s GP or other medical professionals for further clarification about a medical event or death to support the medical event coding process undertaken by the Study Team.
2. In circumstances when a Medicines and Healthcare products Regulatory Agency (MHRA) inspector, may see an individual record with a medical event or death recorded, which may have been supplied by NHS England.
3. When the trial is required to provide de-identified data to the MHRA as part of the annual regulatory reporting procedures. These reports contain counts of serious adverse events including hospitalisations and deaths among the trial participants. Small numbers cannot be suppressed in these regulatory reports.

There are no contractual obligations to provide record level data to anyone until the Study Team are contractually required to share data with Novo Nordisk 1-year before the end of study (data sharing is anticipated in 2027). The University of Oxford is not permitted to share NHS England Data, included Manipulated Data, with Novo Nordisk. The University of Oxford intend to share Derived Data with Novo Nordisk but must first request a review by NHS England and must receive written confirmation from NHS England that the dataset to be shared has been verified as meeting the criteria for Derived Data.

The Children’s Surgery Outcome Reporting research database (CSOR) - DigiTrials Comms Service - Patient List Update Service — DARS-NIC-674822-S2K9T

Opt outs honoured: (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261(5)(d); Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2024-04 – 2026-08

Access method: One-Off

Data-controller type: OXFORD UNIVERSITY HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Customer - Data Quality Report - Non-aggregate (Comms)

Type of data: Identifiable

Objectives:

This Data Sharing Agreement (DSA) is for the University of Oxford and Oxford University Hospitals NHS Foundation Trust to utilise the NHS DigiTrials' Patient List Update Service (previously known as "Vital Status") to undertake a status check of their cohort of very young children to ensure they have not passed away before sending out communications to their parents or guardians related to the project, The Children’s Surgery Outcome Reporting research database (CSOR). This check is felt necessary by the study team, as the conditions included within the CSOR research database have a high mortality rate, and therefore, without the status check, there is a risk of contacting a recently bereaved parent or guardian which may cause significant further distress. As a result, the CSOR team wish to use NHS England’s DigiTrials Communications' Patient List Update Service to obtain the fact of death for those infants in the CSOR study cohort, and the current contactable address held in the Patient Demographics Service to enable the study to confirm which children have passed away, and therefore to prevent contact with the parents or guardians of these children.

The overall purpose of the CSOR study is to investigate whether it is possible to collect paediatric surgical outcomes data using a system that links routinely collected health data and parent reported outcomes data and provides a platform for centre specific feedback of outcomes in order to reduce unwarranted outcome variation.

At present, significant variation exists in the way children with surgical conditions are managed. Some of this variation is expected and unimportant, but some is unwarranted and associated with variation in outcome. Due to multiple limitations in the paediatric surgical data that are available for analysis (both in terms of research data, and real-time centre specific outcomes data), it is not possible to differentiate the two. There are therefore children being treated for surgical conditions whose outcomes are worse than they would be if better data were available for analysis. The CSOR research database will make it possible to identify unwarranted variation in management and outcome, and will therefore provide the data that are required to improve the care of children with surgical conditions.

There are six main workstreams to this programme of work:

1) Developing a summary metric for determining successful treatment of multiple paediatric surgical conditions
2) Identifying the additional information needed to provide feedback on outcomes
3) Collecting parent reported aspects of the minimum dataset
4) Developing the CSOR research database to collect the minimum dataset from multiple sources
5) Development of the feedback model
6) Implementation study

The data subjects in the CSOR study will be all children treated in any of the participating sites during the Data Sharing Agreement period who have a new diagnosis of one of six conditions: necrotising enterocolitis (NEC), Hirschsprung’s disease (HD), gastroschisis, posterior urethral valves (PUV), congenital diaphragmatic hernia (CDH) and oesophageal atresia (OA). There are no control subjects.

The CSOR research database will be established to collect and link the data that are required to identify unwarranted variation between hospitals in management and outcomes of children with surgical conditions. The collected data will primarily be used to determine whether hospitals observed outcomes differ to the outcomes expected based upon the case-mix of the children they have treated. This analysis will inform a facilitated feedback process through which participating sites are helped to understand why the outcomes they have achieved for children are better or worse than would be expected. This closed loop of data collection, analysis and feedback will help hospitals understand how they can improve their practice and will facilitate rapid identification and sharing of good practice. A secondary use of the collected data will be to conduct studies falling within the remit of improving the health and wellbeing of children with surgical conditions.

The CSOR study has a separate Data Sharing Agreement (DARS-NIC-608743-H5X9Z) for outcomes data relating to the study.

The University of Oxford is the sponsor for this study. The University of Oxford and Oxford University Hospitals NHS Foundation Trust are Joint Data Controllers. Only the University of Oxford will also process the data requested in this Data Sharing Agreement.

The CSOR study is funded by the National Institute for Health Research. They are involved in monitoring the progress of the study and reviewing study protocols, but do not decide the purpose and means of processing the data in the CSOR study, and are therefore not considered to be a Data Controller in this Data Sharing Agreement. NIHR have no ability to control or suppress the outcomes published under this study.

The CSOR study team have sought consent from participants to communicate with them during the course of the CSOR study at key target points. The majority of the infants in the cohort submitted under this Data Sharing Agreement to be processed through the Patient List Update Service check will be fully consented. However, there will be some invitees for whom the study team are in the process of trying to obtain consent and want to ensure that the child hasn’t died, or the parent’s contact details changed, between the time of identification of eligibility and approach to obtain consent. As a result, the study has support under section 251 of the NHS Act 2006 to enable the common law duty of confidentiality to be temporarily lifted so that confidential patient information can be processed without consent. National Data Opt-Outs will be upheld only for those individuals in the cohort for whom Section 251 applies - in other words, those who have not provided consent.

PATIENT AND PUBLIC INVOLVEMENT AND ENGAGEMENT (PPIE)
The need for the CSOR programme was first identified and developed through work with the Parental Advisory Group (PAG) set up by the study team at the University of Oxford. The PAG, consisting of over 100 parents/families of children with surgical conditions, charities and support group representatives from across the UK, remain actively involved throughout the course of the programme. As a minimum, annual meetings have been held to update, discuss and gather feedback on the aims and methods of establishing the research database. Feedback from the PAG has been key to the development of the proposed parent consent and data collection process. There will be two parent or patient representatives on the CSOR Research Database Steering Committee to ensure that the parent/patient voice is maintained in the functioning of the CSOR Research Database. The CSOR Research Database will continue to be reviewed at the annual PAG meeting. The members of the CSOR Research Database Steering Committee will have no access to the NHS England data described in this Data Sharing Agreement.

UK GDPR LEGAL BASIS FOR THE PROCESSING OF DATA
The University of Oxford, as a joint Data Controller who is also processing the Data will process Personal Data under UK GDPR Article 6 (1) (e) - Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. As a higher education establishment, the University of Oxford conducts research to improve health care and services, and the data requested is necessary for the performance of a task carried out in the public interest.

Oxford University Hospitals NHS Foundations Trust, as a joint Data Controller will process Personal Data under UK GDPR Article 6 (1) (e) - Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. Oxford University Hospital NHS Foundation Trust is a public authority. The Data Protection Act 2018 s7(1)(a) defines ‘public bodies’ for the purpose of the UK GDPR as “a public authority as defined by the Freedom of Information Act 2000”. The FOI Act 2000 Part 1, section 3 (1)(a)(i) specifies that a public authority means any body which is listed in Schedule 1. Schedule 1 Part 3 (40A) of the FOI Act 2000 stipulates “An NHS foundation trust” is a public authority.

The NHS Act 2006 section 43(5), which describes the functions of authorised NHS Foundation Trusts, states that ‘The authorisation must authorise and may require the NHS foundation trust— (a) to carry out research in connection with the provision of health care, (b) to make facilities and staff available for the purposes of education, training or research carried on by others'.

Additionally, under GDPR Article 9(2)(j) processing of Special Category Personal Data (of which Health data is one) is necessary for archiving for research purposes. Data minimisation processes are being followed and only Data that is specifically required for the purposes of this study have been requested, to protect the rights of the data subjects. The Controllers have satisfied themselves that this request is appropriate, necessary and proportionate for the performance of the task described in the Purpose statement and that there is no other reasonable and less intrusive means to achieve their purpose.

Expected Benefits:

To enable ongoing contact with parents for the purposes of maximising data collection in relation to children’s quality of life, whilst minimising the potential for causing distress by contacting parents of children who have died between recruitment and follow-up.

Outputs:

The key immediate output will be to ensure that no communications related to the CSOR study goes to the parents or care-givers of participating individuals who have died. This will mean that all efforts are made to ensure communications do not cause undue distress to grieving parents or care-givers.

The CSOR study has a separate Data Sharing Agreement (DARS-NIC-608743-H5X9Z) for outcomes data relating to the study, which should generate outputs such as results, presentations or reports.

Processing:

The University of Oxford will send in on a regular basis (to a maximum of 100 uploads over a 24 month period) a cohort of child participants via NHS England's Secure Electronic File Transfer service (SEFT). The cohort will consist of the following identifiers:
- Study ID
- NHS Number
- Date of Birth
- Column to indicate if individual has provided consent or not.

NHS England will first apply National Data Opt-Outs to individuals in the cohort who have not provided consent, and then cross-reference the Patient Demographics Service to ascertain if a date of death has been registered for the individual, and create a report on the cohort of individuals containing – where applicable - fact of death, and latest contact address held in the Patient Demographics Service. The report will then be sent back to University of Oxford via SEFT.

Processing will only be carried out by substantive employees of University of Oxford. All computers and virtual machines used by the research database team to NHS England record-level Data will be password protected at turn on. All computers and virtual machines used by the research database team to access CSOR Research Database data will be password protected at turn on. All CSOR staff handling data will be trained in the principles of Information Governance, the DPA and the UK General Data Protection Regulation (UK GDPR).

Data processing will be carried out either directly in person or remotely, using an appropriate statistical package using University of Oxford or Oxford University Hospitals NHS Foundation Trust owned devices with appropriate security protection. A software firewall on the host and hardware firewalls at the perimeter will provide network security. Access is limited to the IP range of University of Oxford clients. Log on security will use industry standard authentication methods, with passwords stored and validated by University of Oxford IT infrastructure. Access to the database itself will be restricted using role-based active directory controls. All computers and virtual machines used by the research database team to access CSOR Research Database data will be password protected at turn on. Physical access to servers is limited. The XNAT server has nightly security patches. Unneeded services are disabled. Logs are monitored and daily summaries are emailed to system admin. Remote desktop access to the CSOR Research Database is granted via virtual machine. All data analysis will be conducted within the confines of the University’s secure server, and cannot be downloaded to remote devices for storage or processing or otherwise copied. All remote access is within the specified territory of use (i.e. England and Wales).

The received Data will not be linked with any other datasets. They will be cross-checked against existing study data stored in the CSOR research database.

Where consent is not received from parents, all identifiable data will be removed within 13 months of being received.

Children's Surgery Outcome Reporting (CSOR) Research Database - Clinical Data — DARS-NIC-608743-H5X9Z

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261(5)(d), Health and Social Care Act 2012 - s261(2)(d)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-02 – 2026-02 2024.04 — 2025.03.

Access method: Ongoing

Data-controller type: OXFORD UNIVERSITY HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death
  2. Demographics
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)
  4. Hospital Episode Statistics Critical Care (HES Critical Care)

Type of data: Identifiable

Objectives:

The University of Oxford and Oxford University Hospitals NHS Foundation Trust requires access to record-level identifiable health Data from NHS England for the purpose of the following research programme: The Children’s Surgery Outcome Reporting (CSOR) programme.

The CSOR programme is a five-year, NIHR-funded pilot programme which is working to improve the health and wellbeing of children with surgical conditions. There are three linked Data Sharing Agreements being made to NHS England for the CSOR Programme. This Data Sharing Agreement, DARS-NIC-674822-S2K9T and DARS-NIC-717299-R5H5N .

The following is a summary of the aims of the CSOR research programme provided by the study team:

At present, significant variation exists in the way children with surgical conditions are managed. Some of this variation is expected and unimportant, but some is unwarranted and associated with variation in outcome. Due to multiple limitations in the paediatric surgical data that are available for analysis (both in terms of research data, and real-time centre specific outcomes data), it is not possible to differentiate the two. There are therefore children being treated for surgical conditions whose outcomes are worse than they would be if better data were available for analysis.

The overall purpose of the Children’s Surgery Outcome Reporting (CSOR) programme is to investigate whether it is possible to collect paediatric surgical outcomes data using a system that links routinely collected data and parent reported outcome data and provides a platform for centre specific feedback of outcomes in order to reduce unwarranted outcome variation.

The CSOR research database will be established to collect and link the data that are required to identify unwarranted variation between hospitals in management and outcomes of children with surgical conditions. Three sources of data will be linked within the CSOR research database.

1) Data collected in hospitals’ electronic patient record systems
2) National routine sources of data available from NHS England (this Data Sharing Agreement)
3) Data collected annually from the child or their parent/guardian about the child’s quality of life

The collected data will primarily be used to determine whether hospitals observed outcomes differ to the outcomes expected based upon the case-mix of the children they have treated. This analysis will inform a facilitated feedback process through which participating sites are helped to understand why the outcomes they have achieved for children are better or worse than would be expected. Results of analysis will also be shared via a public facing web-based dashboard.

On a quarterly basis the datasets listed below are required for all infants/young people in the cohort in order to predict how successfully they would be expected to be treated, and determine how successfully they are observed to have been treated. The level of data will be Identifiable to facilitate linkage with other data sources and maintain ongoing contact with parents for the purposes of colleting quality of life data. The combination of NHS Number and Date of Birth provides the minimum level of identifiable information required for robust linkage. The data requested are required to enable case-mix adjustment and determination of outcomes.

For this DSA, the following NHS England Data will be accessed:

• Hospital Episode Statistics (HES) Admitted Patient Care (APC)
• HES Critical Care (CC)
• Person Demographics Service (PDS)
• Civil Registration of Deaths

The rationale for specific data categories is described below:
1) The infant’s demographics and identifiers – Required to ensure accurate linkage with other collected study data.
2) Maternal and infant health characteristics – required to take account of co-morbidities that may impact how successful an infant’s treatment is.
3) Infant health outcomes – required to calculate an infant’s treatment success score, the primary measure that will be used to identify unwarranted variation in practice.

Data will only be requested for infants whose eligibility according to diagnosis (oesophageal atresia, posterior urethral valves, congenital diaphragmatic hernia, necrotising enterocolitis, congenital diaphragmatic hernia and gastroschisis) and treatment in a participating site after launch of the CSOR research database has been confirmed. The CSOR pilot programme will involve 10 participating hospitals from across England and Scotland. The requested geographical area has been restricted to patients treated in the participating hospitals. The occurrence of the six conditions is not limited by specific demographics, and therefore the dataset cannot be limited by demography.

The data requested are the minimum required in order to enable linkage of the three sources of information and achieve the objectives described above. A standing item is retained on the agenda of the CSOR steering committee to review the programme data collected and requested to ensure that it remains the minimum possible to achieve the aims of the CSOR programme.

The data subjects will be all children treated in any of the participating sites during the Data Sharing Agreement period who have a diagnosis of one of six conditions: necrotising enterocolitis (NEC), Hirschsprung’s disease (HD), gastroschisis, posterior urethral valves (PUV), congenital diaphragmatic hernia (CDH) and oesophageal atresia (OA).

There are no control subjects.

All analyses will be carried out on pseudonymised datasets.

For every child in the CSOR research database, the collected data will be utilised to calculate an observed CSOR treatment success score and to predict an expected CSOR treatment success score based upon the child’s underlying characteristics. The CSOR Treatment Success Score is a composite outcome that is calculated based upon the numbers and types of operations a child has undergone, the numbers of times they have been admitted for an infection related to their surgical condition, their quality of life, and the duration for which they survive. The difference between a child’s observed and expected CSOR treatment success score will be calculated. Each participating hospital’s mean difference between observed and expected CSOR treatment success scores will be calculated. If this value is greater than 0 it suggests the hospital’s outcomes are better than expected, and if less than 0 it suggests their outcomes are worse than would be expected. The analyses will be used to inform a facilitated feedback process to help participating hospitals understand why their outcomes may be better or worse than expected.

Secondarily, the data contained within the CSOR research database will be used to conduct studies within the scope of improving the health and wellbeing of children with surgical conditions.

The CSOR Steering Committee provide overall supervision, management, strategic direction and governance of the activities of the CSOR Research, including monitoring and supervising the progress of data collection and analysis. The steering committee will review all proposals to utilise data within the CSOR research database.

The University of Oxford is the sponsor for this study. The University of Oxford and Oxford University Hospitals NHS Foundation Trust are joint Controllers responsible for ensuring that the data will only be processed for the purpose described above. Both organisations will also process the data in this agreement.

The following organisations have collaborated on devising the programme and will provide electronic patient record data to the CSOR research database:
• Alder Hey Children’s Hospital
• Birmingham Children’s Hospital
• Cambridge University Hospitals NHS Foundation Trust
• Chelsea & Westminster Hospital
• Evelina Children’s Hospital
• Great Ormond Street Hospital
• Oxford University Hospitals NHS Foundation Trust
• Royal Hospital for Children
• Royal Manchester Children’s Hospital
• Southampton General Hospital

These organisations in the bulleted list above are not involved in any way in determining the means and purpose of processing personal Data received from NHS England and will have no access to record level Data from NHS England.

The CSOR study is funded by the National Institute for Health Research. The current funding period is 01/03/2020 to 28/02/2025. The NIHR are involved in monitoring the progress of the study and reviewing study protocols, but do not decide the purpose and means of processing the data in the CSOR study, and are therefore not considered to be a Data Controller in this agreement. NIHR have no ability to control or suppress the outcomes published under this programme.

UK GDPR LEGAL BASIS FOR THE PROCESSING OF DATA
The University of Oxford, as a joint Controller who is also processing the Data will process Personal Data under UK GDPR Article 6 (1) (e) - Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. As a higher education establishment, the University of Oxford conducts research to improve health care and services, and the data requested is necessary for the performance of a task carried out in the public interest.

Oxford University Hospitals NHS Foundations Trust, as a joint Controller who is also processing the Data will process Personal Data under UK GDPR Article 6 (1) (e) - Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the Controller. Oxford University Hospital NHS Foundation Trust is a public authority. The Data Protection Act 2018 s7(1)(a) defines ‘public bodies’ for the purpose of the UK GDPR as “a public authority as defined by the Freedom of Information Act 2000”. The FOI Act 2000 Part 1, section 3 (1)(a)(i) specifies that a public authority means any body which is listed in Schedule 1. Schedule 1 Part 3 (40A) of the FOI Act 2000 stipulates “An NHS foundation trust” is a public authority.

The NHS Act 2006 section 43(5), which describes the functions of authorised NHS Foundation Trusts, states that ‘The authorisation must authorise and may require the NHS foundation trust— (a) to carry out research in connection with the provision of health care, (b) to make facilities and staff available for the purposes of education, training or research carried on by others'.

Additionally, under GDPR Article 9(2)(j) processing of Special Category Personal Data (of which Health data is one) is necessary for archiving for research purposes. Data minimisation processes are being followed and only data that is specifically required for the purposes of this study have been requested, to protect the rights of the data subjects. The Controllers have satisfied themselves that this request is appropriate, necessary and proportionate for the performance of the task described in the Purpose statement and that there is no other reasonable and less intrusive means to achieve their purpose.

PATIENT AND PUBLIC INVOLVEMENT AND ENGAGEMENT
The need for the CSOR programme was first identified and developed through work with the Parental Advisory Group (PAG) set up by the study team at the University of Oxford. The PAG, consisting of over 100 parents/families of children with surgical conditions, charities and support group representatives from across the UK, remain actively involved throughout the course of the programme. As a minimum, annual meetings have been held to update, discuss and gather feedback on the aims and methods of establishing the research database. Feedback from the PAG has been key to the development of the proposed parent consent and data collection process. There will be two parent or patient representatives on the CSOR Research Database Steering Committee to ensure that the parent/patient voice is maintained in the functioning of the CSOR Research Database. The CSOR Research Database will continue to be reviewed at the annual PAG meeting. The members of the CSOR Research Database Steering Committee will have no access to the NHS England Data described in this Data Sharing Agreement.

The dissemination for this Data Shairng Agreement will require sharing of identifiable data items about eligible children and their parents without the consent of either party. There is the potential that some parents may object to this, and subsequently finding out that their/their child's data have been used for research purposes without consent may cause them distress. Instead, the study has support under section 251 of the NHS Act 2006 to enable the common law duty of confidentiality to be temporarily lifted so that confidential patient information can be processed without consent. This is an area that has been explored in depth with a parent advisory group consisting of a large number of parents of children with surgical conditions, as well as representatives of charities and support groups. Feedback from this group has been overwhelmingly positive. Most parents assume that data are already shared for the purposes of research, and as long as data are appropriately protected, parents did not have any objections to these data being shared. The potential benefit from sharing of the data in terms of developing a far greater understanding of the models of care and treatments that are best for children with surgical conditions, as well as the potential to reduce unwarranted variation in management and outcomes for these children therefore far outweighs the potential harms of the data collection.

Previous attempts to set up condition-specific databases for key paediatric surgical conditions have been limited by significant issues with case ascertainment, as they relied on voluntary case reporting by surgical staff. These databases have shown that reliance on site staff to supply contact details results in approximately 30% of the eligible population not being approached for consent, as site staff have been unable to supply their contact details. Where contact details are received though, and parents are approached for consent without prior knowledge that their contact details have been shared, this results in a relatively high consent rate (~60%). In a recent (2017-2019) paediatric surgical study in which approximately 190 parents were approached by a research team without prior consent, no complaints were received about the fact that their contact details had been shared outside of their usual clinical team without prior consent.

Expected Benefits:

The anticipated improvement in children’s health, and the re-structuring of delivery of care as outputs from the CSOR Programme hopes to benefit the wider public through producing a more efficient health care system and reducing the long-term financial costs of treating children with these surgical conditions. Collecting the data regularly from routine sources will allow children’s Treatment Success Scores to be updated in a contemporaneous manner as they age, without placing an unacceptable burden on clinical staff to repeatedly provide data for children.

Additional benefits to arise from the dissemination include:
• Development of a ‘case mix adjustment model’ that can be used to predict how successful an infant’s treatment is expected to be based upon their underlying characteristics. Peer reviewed publications describing the development of this model.
• Population of a live dashboard accessed by hospitals and the public describing the activity in participating hospitals and comparisons of the hospital’s observed and expected outcomes, thus enabling professionals to interrogate their own hospitals data and if necessary, make changes to practice based upon their data.
• Podcasts, posters, information leaflets and videos explaining to parents, patients and the public, the results of analyses conducted using data contained in the CSOR Research Database – Share findings from analyses with the wider public to enable them to make more informed choices regarding the care of their child.
• Peer reviewed publications and presentations relating to the results of analyses conducted on the linked pseudonymised dataset. These will include, but not be limited to, analyses describing management strategies, infant outcomes, and factors affecting outcomes – Ensure wider sharing of knowledge that has been gained from collecting and analysing the data, and therefore enable implementation of evidence-based practice across a range of different hospitals.
• Professional and public facing annual reports describing the activities of the CSOR Research Database, and including, amongst other things, information relating to case ascertainment, national management strategies, and national benchmarks for infant outcomes - Share key findings from the previous year’s analyses, enabling transfer into practice by clinicians.

Five-yearly, a process evaluation will be conducted to assess the benefit of the CSOR research database. The first of these will take place in 2025-26.

Under the current funding arrangement, the CSOR Research Database is being implemented in 10 pilot hospitals out of the 24 in England and Scotland that are commissioned to provide specialised surgery for children. If the process evaluation conducted in 2025/26 shows benefit to the programme, it is expected that the CSOR Research Database and facilitated feedback programme will be incorporated into NHS ‘Business and Usual’, and the remaining 14 hospitals providing specialised surgery for children will be brought into the programme over 2026/27. The impact of the outputs from the initial pilot programme, and therefore the disseminations covered by this DSA, are anticipated to directly benefit children treated in the pilot centres, but without necessarily direct benefit at that stage to children treated outside these centres. It is therefore anticipated that in this initial pilot phase, the number of children and their families that are directly benefited by the data dissemination will be limited to approximately 400-500/year.

The initial pilot phase is necessary to provide a proof of concept for the Programme prior to wider role out to the remaining hospitals providing specialised surgery for children. Once all hospitals are included in the programme, approximately 1,200 children and their families are anticipated to be benefited each year. On a five yearly basis, additional surgical conditions will be brought into the CSOR Research Database, and with each condition added, the number of children directly benefited by the outputs of the data dissemination will be increased. Although the numbers of people directly affected will remain relatively small (several thousand per year), the impact of a single child being treated for one of the surgical conditions included in the CSOR Research Database is significant. Caring for children with surgical conditions frequently results in the need for housing modifications and modifications to the activities that families can take part in, as well as leading to parental separation, parents giving up work, and a detrimental psychological and social impact on other children in the family. If, as anticipated, the health and wellbeing of future children diagnosed with these conditions can be improved through the proposed outputs arising from the data disseminations, the magnitude of benefits to the child’s family, the health service, and wider society are therefore, over the longer-term, likely to be significant.

At the pilot stage, many of the analyses conducted will be hypothesis generating, with these hypotheses reported in the outputs of the programme. As the programme is expanded to other hospitals, case ascertainment will be sufficient to allow those hypotheses to be tested. It is at this stage, which is anticipated to be two-four years after expansion of the programme (~2028-2030), that sufficient data will have been gathered to allow robust recommendations to be made regarding the optimal models of delivering care for children requiring specialised surgery. At this stage, it is therefore impossible to quantify what the cost benefit will arise from the Data disseminations described in this DSA.

Outputs:

Currently, children with the conditions included in this Programme have poor outcomes and significant long-term health needs. These include 25-30% one-year mortality rates for infants with necrotising enterocolitis and congenital diaphragmatic hernia, 60% rates of primary school aged faecal incontinence for children with Hirschsprung’s disease, and the need for multiple operations in the first 28 days of life, for infants with gastroschisis. Management of these children in the UK currently varies widely. No mechanisms exist to determine which elements of this variation are acceptable, and which are unwarranted and associated with variation in outcome. The Data disseminated under this DSA hopes to provide the information that is needed to calculate the number and types of operations that children have undergone, as well as the number of times they have been admitted and treated for an infection related to their underlying surgical condition.

These outcomes contribute towards calculating a child’s CSOR treatment success score. When used in conjunction with the additional data held in the CSOR research database, knowledge of a child’s CSOR treatment success score will create for the first time the ability to understand which elements of management are inconsequential, and which are unwarranted. The ability to detect unwarranted variation in management hopes to help standardise delivery of care across different surgeons and hospitals, with the expectation that the overall delivery of care for children with these conditions will improve. This hopes to, in the long run, improve the health and wellbeing of children born with these conditions in the future, as well as allowing evidence-based restructuring of the way care is delivered for these children.

The following outputs hope to be developed:

1) A Research Database (the CSOR Research Database) which can be utilised for identifying unwarranted variation in the management and outcomes of children with surgical conditions, and for the conduct of approved research to improve outcomes for children with surgical conditions. Data collection is anticipated to begin in quarter 3 of 2023.

2) Peer reviewed publications and presentations relating to development of the CSOR Research Database and CSOR Research Database methodology. Publication is anticipated in quarter 3 of 2024.

3) A ‘case mix adjustment model’ used to predict how successful an infant’s treatment is expected to be based upon their underlying characteristics. The initial model will be developed using data collected in the first year of the CSOR Research Database, and will be revised initially on a yearly, and then likely five-yearly, basis as additional data are added to the database.

4) Peer reviewed publications and presentations describing the development of the case-mix adjustment model. Publication of the initial model is anticipated in quarter 2 of 2025.

5) Peer reviewed publications and presentations relating to the results of analyses conducted on the pseudonymised dataset. These will include, but not be limited to, analyses describing management strategies, infant outcomes, and factors affecting outcomes. The date of these publications will be influenced by case incidence and ascertainment but are not anticipated until quarter 4 of 2025 at the earliest.

6) Live dashboards accessed by hospitals and the public describing the activity in participating hospitals and comparisons of the hospital’s observed and expected outcomes. Development is anticipated to be complete by quarter 4 of 2023.

7) Facilitated feedback and peer review processes, the aims of which are to help hospitals understand their own performance, will be informed by analysis of data contained in the final linked, pseudonymised dataset. Development of these processes is anticipated throughout 2023, with implementation in quarter 3 or 4 of 2024.

8) Professional and public facing annual reports describing the activities of the CSOR Research Database, and including, amongst other things, information relating to case ascertainment, national management strategies, and national benchmarks for infant outcomes. Anticipated yearly from quarter 3 2024 onwards.

9) Podcasts, posters, information leaflets and videos explaining to parents, patients and the public, the results of analyses conducted using data contained in the CSOR Research Database. The date of these outputs will be influenced by case incidence and ascertainment but are not anticipated until quarter 4 of 2025 at the earliest.

10) Peer reviewed publications and presentations describing the periodic process evaluation conducted to determine whether implementation of the CSOR Research Database and facilitated feedback programme has improved the health and wellbeing of children with surgical conditions. The results of the initial process evaluation are anticipated to be published in quarter 3 of 2025.

All outputs will contain only aggregated data with small numbers suppressed as per the HES Analysis guide. As per funder requirements (NIHR) all publications will be open access. All data and knowledge are owned by the University of Oxford.

A wide range of routes will be used to disseminate the results of the programme to the beneficiaries, including children with one of the included conditions, adults who were previously treated for one of the included conditions, parents of children with one of the included conditions, professionals and policy-makers.

Dissemination strategies to parents and the public will be guided by one of the CSOR co-investigators who is an expert by experience (a parent of a child with a surgical condition), as well as by an established parental advisory group consisting of parents of children with surgical conditions, and representatives of relevant support groups and charities. Leaflets, videos, infographics and social media will be used as appropriate to aid dissemination.

The programme has direct links with NHS England and the Department of Health and Social Care and will disseminate directly to relevant policy-makers. that the CSOR programme team aim to ensure the outputs are appropriately used to commission services in England, and that full dissemination of outcomes to professional colleagues and integration with professional standards and guidelines. The study team have agreement to specifically hold a dissemination event at the British Association of Paediatric Surgeons Annual Conference to ensure the results reach the paediatric surgical audience directly. The study team also hope to disseminate through journal publications and presentations at other key conferences. Dissemination to the wider public aims to be via regular newsletters available on our website, website bulletins and social media communications via the CSOR Twitter account.

The key route of dissemination to the involved professionals/stakeholders will be through the use of the live dashboards, and facilitated feedback and peer review processes. Through these, professionals involved in the care of infants whose data are included in the CSOR Research Database will be guided through the interpretation of the data for their own hospital in order to help identify any ways in which practice could be changed to improve the care that is being delivered. Data collected by the CSOR system will be used to develop benchmarked, auditable standards for delivery of paediatric surgical services, against which individual units can compare themselves, and be compared.

Agreement has been forthcoming from the National Consultant Information Programme for this database, once successfully developed to reside within NHS England in order to facilitate individual surgeon feedback via the The National Council of Integrative Psychotherapists (NCIP) portal (http://gettingitrightfirsttime.co.uk/ncip/), and the study team have also had an indication that in Scotland it could be hosted within the Information Services Division. This important surgeon-level ‘building block’ will allow the data to be built from surgeon to unit to national level. Use of the data to identify gold-standard practice hopes to allow clinicians, managers and commissioners to review and modify the way their services are organised and delivered.

Processing:

The University of Oxford will send in on a quarterly basis, a cohort file containing a pseudonymised study ID, NHS Number and Date of Birth from the secure servers at Oxford University Hospitals NHS Foundation Trust to NHS England via a secure file transfer service.

NHS England will first match and link the cohort of individuals to the datasets and dates requested, and then remove individuals who have registered a National Data Opt-Outs.

NHS England will then supply the requested data files back to the Oxford University Hospitals NHS Foundation Trust (OUH) via a secure file transfer service.

At the point of receipt on the secure servers at the Oxford University Hospitals NHS Foundation Trust, all NHS Numbers will be encrypted using Hashing/Salting encryption. Linkage of data from NHS England to data received from hospital’s EPR systems, or directly from parents in the form of parent proxy reported quality of life data for the child will take place using the encrypted NHS Number along with date of birth. This linkage will occur on the Oxford University Hospitals NHS Foundation Trust secure servers. A pseudonymised, linked dataset will be securely exported to the University of Oxford servers for analysis. The key used to encrypt NHS numbers will be held only on the Oxford University Hospitals NHS Foundation Trust servers. Without this key it will not be possible to re-identify an infant’s NHS Number. There will be no requirement/attempt to re-identify individuals by University of Oxford.

Where contact details have been received on the secure servers of the University of Oxford, these will be stored separately to any received research data. All research data will only be stored against a CSOR Research Database Case ID.

The health data will be pseudonymised using an encryption key (Study ID), and then linked with Electronic Patient Record (EPR) data received directly from hospitals for the same cohort of infants, and parent proxy reported quality of life data received for the same cohort of infants.

The linked, pseudonymised dataset will be exported to the Health Table of the CSOR Database, held on the secure servers at the University of Oxford. At this stage, processing will be carried out by the University of Oxford. Only the encryption key and unlinked files, not the linked dataset, will be retained on the servers at Oxford University Hospitals NHS Foundation Trust. All analyses will take place on the linked pseudonymised dataset held on the University of Oxford servers.

Following the initial processing described above, the linked, pseudonymised dataset that has been exported to the University of Oxford servers will be utilised periodically to:
1) Describe the number of cases treated in each hospital providing data to the CSOR Research Database
2) Describe the management strategies utilised in each hospital providing data to the CSOR Research Database
3) Calculate the mean difference between participating hospital’s observed and expected CSOR Treatment Success Scores.
4) Inform a facilitated feedback and peer review process in which participating hospitals are guided through the descriptions of the management strategies they use and outcomes they attain.

Health data received from NHS England will be linked using NHS Number and Date of Birth to data received directly from hospitals EPR systems, and to the parent proxy reported quality of life data received from parents. Parental contact details will be stored separately to all other data and will not be linked to any other datasets.

Processing will only be carried out by substantive employees of Oxford University Hospitals NHS Foundation Trust, or University of Oxford. All computers and virtual machines used by the research database team to NHS England record-level data will be password protected at turn on. All computers and virtual machines used by the research database team to access CSOR Research Database data will be password protected at turn on. All CSOR staff handling data will be trained in the principles of Information Governance, the DPA and the UK General Data Protection Regulation (UK GDPR).

A software firewall on the host and hardware firewalls at the perimeter will provide network security. Access is limited to the IP range of University clients. Network security will include strong encryption of data during its passage from Oxford University Hospitals NHS Foundation Trust to the University of Oxford. Log on security will use industry standard authentication methods, with passwords stored and validated by Oxford University Hospitals NHS Foundation Trust IT infrastructure. Access to the database itself will be restricted using role-based active directory controls. All computers and virtual machines used by the research database team to access CSOR Research Database data will be password protected at turn on. Physical access to servers is limited. The XNAT server has nightly security patches. Unneeded services are disabled. Logs are monitored and daily summaries are emailed to system admin. Remote desktop access to the CSOR Research Database is granted via virtual machine. All data analysis will be conducted within the confines of the University’s secure server, and cannot be downloaded to remote devices for storage or processing or otherwise copied. All remote access is within the specified territory of use (i.e. England).

Unprocessed Comma Separated Values (CSV) files containing clinical information transferred from hospitals will be retained on the secure servers at OUH NHS Foundation Trust for 3 years from the point of receipt.
Data entered into the participant questionnaires will be retained for 60 years. Parental contact details will be retained in the Participant and Parent tables of the University Data Holding on the University of Oxford secure servers until the child consent process is completed following the child’s 16th birthday. This will be completed at the latest by 1 month after the child’s 17th birthday. Contact details for participants consented at age 16 will be retained in the Parent table of the University Data Holding on the University of Oxford secure servers for a period of 44 years (until the participants 60th birthday).

Pseudonymised data contained within the Health Table of the University Data Holding will be retained for 60 years.

An open label Phase I/IIa clinical trial to assess the safety, immunogenicity and efficacy of the malaria vaccine candidate RH5.2-virus-like particle (VLP) (BIO001) - NHS DigiTrials Recruitment Service — DARS-NIC-647363-F3R4R

Opt outs honoured: (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d)

Purposes: Yes (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2024-02 – 2024-07

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Customer - Data Quality Report - Aggregate (Recruitment)
  2. Mailing - Cohort - Non-aggregate (Comms & Recruitment)

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

The Oxford Vaccine Group (OVG) based at the University of Oxford requires access to NHS England Data for the purpose of the following clinical trial :
'An open label Phase I/IIa clinical trial to assess the safety, immunogenicity and efficacy of the malaria vaccine candidate RH5.2-virus-like particle (VLP) in Matrix-MTM, and to compare the safety and immunogenicity of the malaria vaccine candidates RH5.2-VLP in Matrix-MTM and RH5.1 soluble protein in Matrix-MTM used in various regimens' (Known as Study Reference: BIO-001)

THE AIM OF THE TRIAL
Malaria in humans is caused by five species – Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae and Plasmodium knowlesi. Plasmodium falciparum causes the most morbidity and mortality of the Plasmodium species, accounting for an estimated 241 million cases of malaria and 627,000 deaths worldwide in 2020. The currently available methods for preventing and treating malaria remain inadequate. Although focused efforts have led to substantial reductions in morbidity and mortality worldwide, progress has now stalled.

Although the World Health Organisaiton (WHO) has now recommended the deployment of the RTS,S vaccine in high risk populations, work on a more efficacious vaccine is ongoing. There are promising data from RH5 (next generation blood-stage malaria) candidate vaccines, both in the UK and malaria endemic regions in sub-Saharan Africa. RH5.2-VLP has not yet been trialed in humans, however, pre-clinical studies are encouraging.
The BIO001 challenge study is an open-label, single-centre Phase I/ IIa P. falciparum blood-stage controlled human malaria infection (CHMI) trial to assess the safety, immunogenicity and efficacy of the candidate malaria vaccine RH5.2-VLP formulated in adjuvant* Matrix-M.
*An adjuvant is an ingredient used in some vaccines that helps create a stronger immune response in people receiving the vaccine. In other words, adjuvants help vaccines work better.

As part of the study, a small number of vaccinated and unvaccinated participants will be infected with the malaria parasite (with their consent) for a short period of time to see whether the vaccine is effective in preventing disease. To do this, the study will include 6 groups:
• Groups 1 and 3-5 will have three doses of malaria vaccine.
• Group 2 will have three doses of malaria vaccine followed by a malaria ‘challenge’. A challenge is when we deliberately infect volunteers with malaria by injecting a tiny amount of malaria infected blood into the vein.
• Group 6 will not receive any malaria vaccines and will only take part in the malaria ‘challenge’.

By using this very controlled setting to expose people to malaria parasite, the BIO-001 study team hope to see if an experimental vaccine can protect against p. falciparum infection and to understand which parts of the immune response may be important in preventing disease. They hope that the knowledge gained from this trial will help in the development of vaccines and make Malaria a preventable disease.

The Primary Objective of the BIO-001 study is to:
1. To assess the safety of RH5.2-VLP in Matrix-M and RH5.1 soluble protein in Matrix-M in healthy adult volunteers at different doses and used in various regimens (Groups 1-5).
2. To assess efficacy of the RH5.2-VLP in Matrix-M by assessing its impact on parasite multiplication rate (PMR) in vaccinated subjects (Group 2) compared to infectivity controls (Group 6), against 3D7 clone P. falciparum parasites in a Phase IIa blood-stage controlled human malaria infection (CHMI) model (only to be evaluated if the GIA target is met in Group 1).

This Data Sharing Agreement (DSA) is specifically to support the recruitment of a cohort for the BIO-001 study by writing out to approximately 4,000 individuals who meet the initial recruitment eligibility criteria of age and post-code area.

Although past methods of recruitment have been sufficient to meet study target recruitment numbers across studies, the OVG's portfolio of studies has grown substantially over recent years, and in particular ‘human challenge model’ studies such as BIO-001 can be difficult to recruit to (particularly due to the comprehensive screening process, strict study inclusion/exclusion criteria and the intensive nature of the study requiring frequent visits to the study site/s for safety and to ensure participants are closely monitored), requiring additional methods in order to optimize recruitment and effective delivery of trials. This is in order to achieve key study outcomes (in design, development and evaluation of vaccines), provide high quality and robust scientific data, and inform vaccine policy locally and globally.

The BIO-001 team hope to recruit approximately 56 participants to the study. Since the start of recruitment, the trial team have used a range of routine recruitment methods which include advertisements across OVG platforms and other social media accounts of collaborators); posters, flyers and post-card drops (thousands distributed); public and community events/engagement; newsletters and email circulars (including to thousands of people who have subscribed to our monthly newsletters. However, in spite of this concerted efforts, the recruitment rate has been very low and are unlikely to meet the recruitment target within the planned time period. Recruitment to BIO-0001 started on 18 August 2023 and so far only 8 people have been recruited.

In the past, OVG has found, for more intensive and complex studies such as those involving a challenge agent, that the enrolment rate is ~ 0.1%. Therefore, to enrol approx. 50 participants into these types of studies, OVG would need to reach out directly to over 50,000 individuals. This type of recruitment method is time and resource intensive. Furthermore, previous participants from previous studies are not always able to re-enrol in new studies (due to study exclusion criteria). Additionally, Oxford is a highly research-intensive area, with several different drug and vaccine clinical research studies competing for a relatively small pool of interested potential participants. Therefore, OVG need to expand their outreach to beyond what they have already utilised (i.e., university mailing lists, posters, social media, GP surgeries) and perhaps exhausted. For this reason the study is inclusive and open to all healthy individuals between the ages of 18 and 45 years, without targeting any specific sub-groups (noting of course the key exclusion criteria).

The NHS DigiTrials Recruitment service has undertaken several Recruitment Service pilots, with a response rate of 1.5 -2%, and so it is estimated that approximately 4,000 invitations would be required to meet the objective of 56 participants. Therefore the OVG study team wish to use the NHS DigiTrials Recruitment service (extended pilot) to undertake this recruitment. Being able to use NHS England data extracts to generate large mailing lists, in order to send invitational material to members of the public on joining the BIO001 study (and thus significantly increase their recruitment reach) will be vitally important in order to reach their recruitment target and complete delivery of the trial in a timely, effective and efficient manner.

Should the number of participants not be met by the time approximately 4,000 invitations are sent out, then the OVG will submit a further amendment to request more invitations, based on the recruitment rate calculated from the original batch of approximately 4,000 mail-outs.

The BIO-001 team at the University of Oxford will provide NHS England specific inclusion and exclusion criteria to identify potential individuals to be invited to participate by a postal letter.

BIO001 is part of a series of recruitment pilots testing new user cases and capabilities for minimal viable product (MVP) recruitment service. As part of the pilot OVG will provide suitable feedback regarding response rates to the invitations in order for NHS DigiTrials to undertake suitable analysis to validate if it is a valid user case (challenge). Additionally, OVG will inform DigiTrials of dropout rates at the screening stage, and the reasons, so changes to the MVP design e.g. datasets available, automated production pipeline etc; can be considered to improve the results and/or minimise the size of the cohort required.

PATIENT AND PUBLIC INVOLVEMENT AND ENGAGEMENT
The Oxford Vaccine Group (OVG) has a Public and Patient Involvement (PPI) strategic group which is consulted on matters such as how best to perform recruitment for our trials, how to better design our studies, how to ensure participant-facing documents have appropriate content, language and are easily understood, and how to disseminate and communicate our findings to the wider public. They also regularly seek feedback from participants who have completed their studies about their motivation for taking part, as well as their experience of the research process and how this could be improved. OVG incorporates PPI input in their studies through reviewing study materials (such as lay summaries and public-facing documents), funding applications and focus group discussions. Feedback from the PPI group reviews are provided to the study team for their review, reflection and integration into study design, document content and communication of research to the public, among other impacts.


INCLUSION AND EXCLUSION CRITERIA FOR INVITATION
Lists of potentially eligible individuals will be generated from electronic searches of the Person Demographics Service (PDS), a centrally held NHS Dataset at NHS England.
• Individuals will be between 18 and 55 years of age.
• Living in England within specific postcode areas provided by the OVG

NHS England will generate extracts on the basis of date of birth and postcode details as provided by OVG. NHS England will ensure they exclude any flag patients or national data opt outs. NHS England will upload a final .csv file containing name and addresses of potentially eligible participants to Datagraphic Ltd, who will send out invitation letters in batches according to the areas and numbers specified by OVG. The invitation letters will include a link to the BIO-001 trial website, detailed Patient Information Sheet and how to join the pre-screening element of the trial.


UK GDPR LEGAL BASIS FOR PROCESSING OF PERSONAL DATA
University of Oxford, as Controller, are using Article 6(1)(e) "processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller." As part of the application process, the requirement for the Data requested has been assessed and the University of Oxford is content that it is appropriate, necessary and proportionate for the performance of the task described in the purpose statement and that there is no other reasonable and less intrusive means for the Processor to achieve their purpose.

Additionally (as health data is a special category of Personal Data), University of Oxford is using Article 9(2)(j): Special category Data used for “Archiving in the public interest, scientific or historical research or statistical purposes”.


ORGANISATION’S ROLES AND RESPONSIBILITIES:
• The University of Oxford is the Sponsor and Controller. They are responsible for the BIO-001 study and overseeing the work carried out to aid recruitment into the study, and for ensuring that the data will only be processed for the purpose described above. They are also responsible for providing the core eligibility criteria for participants. The University of Oxford will not process NHS England data described in this DSA.

• NHS England are acting as a Processor on behalf of University of Oxford and are responsible for applying the inclusion and exclusion criteria to NHS England Data sets to generate a list of invitees and forwarding the resultant cohort of potential individuals identifiable contact information to PSL Print Management Ltd via Datagraphic Ltd. NHS England does not specify what data are required to deliver the work nor how the data shall be processed to achieve that purpose. Such decisions are taken by the University of Oxford.

• PSL Print Management Ltd are acting as a data processor on behalf of NHS England and are responsible for maintaining a service contract with NHS England and managing the mailout performed by Datagraphic Ltd. PSL Print Management Ltd will not receive, store or have access to NHS England record level Data under this DSA. *

• Datagraphic Ltd are acting as a data processor on behalf of NHS England and PSL Print Management Ltd and are responsible for receiving the list of updated cohort participants from NHS England and mailing out to them accordingly.*
* PSL Print Management Ltd and Datagraphic Ltd work in partnership to provide robust, secure and time critical communication solutions. PSL Print Management Ltd provide project management, training and implementation skill and knowledge. Datagraphic Ltd develop, maintain and host the systems that enable secure and resilient communication to occur. Datagraphic Ltd also provide secure data processing, document composition, sortation, mail item production, enclosing, despatch and inbound mail services from their UK Midlands based development and production hub. NHS England maintains a service contract with PSL Print Management Ltd, and Datagraphic Ltd, in turn, are contracted to PSL, therefore both organisations are considered Processors in this DSA.

• The study is funded by PATH (www.path.org), through a grant from United States Agency for International Development (USAID). PATH is an international public health organization. USAID is an international development agency funded by the U.S. government. The funding is specifically for the BIO-001 trial described. The funder will have no ability to suppress or otherwise limit the publication of findings and will not have access to NHS England Data as described in this Data Sharing Agreement (DSA)

• The BIO-001 Data Safety and Monitoring Committee are acting in an advisory capacity and will not have access to NHS England Data as described in this DSA.

COMMERCIAL INVOLVEMENT
For the purposes of transparency, it is noted here that this study is funded by PATH (www.path.org), through a grant from USAID. PATH is an international public health organization. USAID is an international development agency funded by the U.S. government. The candidate vaccine (RH5.2-SpyTag drug substance and the final SpyTag-SpyCatcher conjugated RH5.2-VLP drug product) will be manufactured initially by Oxford at Genlbet, Portugal and then further in partnership with the Serum Institute of India PVT Limited (SII), while Novavax is the manufacturer and provider of the vaccine adjuvant (Matrix-M). These institutions are biopharmaceutical institutions engaged in the drug discovery, drug development, manufacture of active substances for Investigation Medical Products, vaccines, bio-therapeutics, pharmaceuticals and health care products. Using the funding provided by PATH, University of Oxford scientists and investigators working with Genlbet, SII and Novavax generated Good Manufacturing Practice (GMP) material for use in the trial to generate a finished vaccine product.

USAID, PATH, Genlbet, SII and Novavax will have no involvement in the academic coordination and delivery of the study and will have no ability to suppress or otherwise limit the publication of findings and will have no access to NHS England data. The Senior Laboratory Investigator has an interest in patents relating to the RH5-based vaccines and is a shareholder in a company developing vaccines using SpyTag-SpyCatcher technology used to manufacture the RH5.2-VLP used in this study. The Chief Investigator has a family member who is an inventor on patents for RH5-based vaccines and a shareholder in a company developing vaccines using SpyTag-SpyCatcher technology. While both individuals therefore have a conflict of interest, the integrity of the trial is maintained by samples being analysed by non-clinical researchers who cannot link them to individuals (thereby ensuring no bias), as well as the monitoring of safety by an independent Data Safety Monitoring Committee.

At the current stage the BIO-001 study team aim to provide the proof in principle that the vaccine is safe and immunogenic and warrants further development. If the results of the trial show that the information can be used to contribute to the development of a safe and effective P. falciparum vaccine and make malaria a preventable disease, Oxford, SII and Novavax will continue to work on further clinical development of the vaccine by conducting further phase I/II/III immunogenicity and safety and/or efficacy studies, supported by various funders which could include USAID and PATH, to provide data for potential licensure. These commercial institutions may ultimately benefit financially from the successful licensing and sale of this vaccine, if this comes to pass (in line with NHS England's DAS Standard for Commercial Purpose). However, any further detail on these benefits are impossible to predict at this stage.

Expected Benefits:

The ability to utilise large mailouts will help to optimize recruitment, in order to deliver this clinical trial in a timely, effective and efficient manner. This is in order to achieve key study outcomes (as stated in the design, development and evaluation of vaccines), provide high quality and robust scientific data, and inform malaria vaccine policy both locally in the UK and globally.

Additionally, for more intensive and complex studies such as those involving a challenge agent, OVG have found that the enrolment rate is ~ 0.1% from previous experience. Therefore, to enrol ~50 participants into these types of studies, a trial would need to reach out directly to over 50,000 individuals. Furthermore, previous participants from previous studies are not always able to re-enrol in new studies (due to study exclusion criteria) and therefore, OVG need to expand their outreach to beyond what they have already utilised (i.e., university mailing lists, posters, social media, GP surgeries) and perhaps exhausted. OVG believe it may be a deterrent to research participation long-term if they repeatedly contact the same potential participants about the same ongoing studies. Additionally, Oxford is a highly research-intensive area, with several different drug and vaccine clinical research studies competing for a relatively small pool of interested potential participants.

Therefore, being able to use NHS England's NHS DigiTrials Recruitment Service to generate mailing lists in order to send invitational material to members of the public on joining the BIO001 study (and thus significantly increase their recruitment reach) will be vitally important in order to reach their recruitment target and complete delivery of the trial in a timely, effective and efficient manner.

Ultimately, the information gained from this trial may contribute to the development of a safe and effective P. falciparum vaccine. This would ultimately benefit UK travellers to malaria-endemic areas, as well as reduce the risk of imported malaria cases to the UK. Accruing valuable data on performance of next generation vaccine platforms such as the virus-like particle used in this study may also help inform on vaccine development for other infectious diseases that affect the UK population.

Outputs:

As a result of this DSA with NHS England to use the NHS DigiTrials' Recruitment Service, the BIO-001 trial team are hoping to recruit to target having posted out adequate numbers of invitations to potentially eligible participants.

Identifiable health Data requested from NHS England will only be used to identify and invite potential participants.

Processing:

The University of Oxford will provide to NHS England the core eligibility criteria for those potential participants who will receive invitations.

The Oxford Vaccine Group (OVG) offers an alternative for individuals who:
• Do not want to receive invitations for vaccine trials.
• Still want to contribute to health research.
• Prefer not to register a National Data Opt-out.

How it works:
• Individuals opt-out of vaccine trials with OVG.
• OVG filters this list for those meeting the specific criteria for their study, BIO-001.
• The filtered list is shared with the Digitrials platform, ensuring their removal from potential invite lists.

The benefits of this approach is that participants maintain control of their research involvement allowing OVG to efficiently conduct the study and Digitrials avoids contacting unsuitable or unwilling individuals.

The OVG opt-out form (https://apps.ovg.ox.ac.uk/redcap/surveys/?s=A3NJMTCFK8) states, “All data will be stored on secured University of Oxford servers where the data will only be available to authorised University or NHS staff solely for the purpose of ensuring an individual is not contacted with regards OVG clinical studies.”

NHS England will interrogate the PDS Dataset to identify potential living individuals based on the inclusion and exclusion criterion and extract one batch of potential candidates up to approximately 4,000 individuals.

NHS England will apply National Data Opt Out to the file of potential candidates.

NHS England will securely send the identifiable file to Datagraphic Ltd, containing:
- Individual Study Identifier called a 'GUID'
- Title
- Given Name
- Family Name
- Address and Post Code
- Batch Reference number
- Type of Comms and Letter reference number

Datagraphic Ltd will send out invitations in ad-hoc batches up to approximately 4,000 mailouts using an automated system.

The Data will be stored on servers at Datagraphic Ltd. Access to confidential patient identifiable data is restricted to employees or agents of Datagraphic Ltd using devices owned by Datagraphic Ltd. All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will not leave England at any time.

Datagraphics Ltd will delete the confidential patient identifiable data 2 weeks post mail-out.

The University of Oxford and other recruiting sites will not have access to NHS England Data as described in this Data Sharing Agreement. The University of Oxford and other recruiting sites will not have access to individual’s data unless they are contacted directly by said individual following the mailout.

Study to investigate the accuracy with which breast cancer recurrence can be identified in women registered with invasive breast cancer using routinely collected data compared with recurrence information collected by the AZURE trial ( ODR1718_364 ) — DARS-NIC-656816-Z3N6R

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2023-09 – 2026-09

Access method: One-Off

Data-controller type: NHS ENGLAND (QUARRY HOUSE), UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Pathway
  2. NDRS Cancer Registrations
  3. NDRS Linked Cancer Waiting Times (Treatments only)
  4. NDRS Linked DIDs
  5. NDRS Linked HES AE
  6. NDRS Linked HES APC
  7. NDRS Linked HES Outpatient
  8. NDRS National Radiotherapy Dataset (RTDS)
  9. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Type of data: Anonymised - ICO Code Compliant

Objectives:

Breast cancer is the commonest cancer in the UK and around 55,000 women are diagnosed with the disease each year. Breast cancer incidence rates have been increasing since the mid-1970s and the disease now accounts for almost 1 in 3 of all newly diagnosed cancers in women. Although a large amount of population-based information is available on death and survival from breast cancer in the UK, much less information is available on breast cancer recurrence. Reliable information on breast cancer recurrence is crucial for decision making in several areas of breast cancer management, including:

i. comparing the outcomes of various treatments so that the best treatments can be identified for each woman diagnosed with breast cancer
ii. establishing the prognosis for individual breast cancer patients so that clinicians can advise patients appropriately.
iii. determining the burden of breast cancer so that appropriate policies for the management of the disease can be put in place.

The reason that there is a paucity of data on recurrence of breast cancer is that recurrence information has not traditionally been part of the standard NHS information flow. To rectify this, Public Health England (PHE) mandated that, from 1st January 2013, all women newly diagnosed with breast cancer after 1st January 2013 and who subsequently suffer a recurrence of their cancer should be ‘flagged’ in the new Cancer Outcomes and Services Dataset (COSD). Since then, there have been variables in COSD to indicate recurrence (2). However, they are not completed reliably. In addition, on 1st January 2013 there were around half a million women alive in the UK who had already been diagnosed with breast cancer. Little is known about how many of these women had a recurrence before 1st January 2013 and at present there is no mechanism in place to record any recurrences that they have developed since then, or may develop in the future.

To fill this information gap, researchers at the University of Oxford have been collaborating with National Disease Registration Staff to identify recurrences in women registered with breast cancer using a number of routinely collected data sources, such as Cancer Analysis System (CAS), Hospital Episode Statistics (HES) Cancer Waiting Times (CWT), Digital Imaging Dataset (DID), Radiotherapy Dataset (RTDS) and Systemic Anti-Cancer Therapy dataset (SACT). As part of this study, an algorithm has been developed to identify which women have had a recurrence of their breast cancer and, for those who did, the date of the recurrence. This algorithm has had promising results when validated internally against recurrence information collected by the former West Midlands Cancer Intelligence Unit. However, it has not yet been validated nationally against an external and independent dataset.

The aim of this project is to undertake this external validation using data from the AZURE trial.
This project is a data-linkage study that will use data from the AZURE trial and link it to routinely collected data sources within NHS England to help evaluate the accuracy of an algorithm to identify breast cancer recurrences and serious adverse events using routinely collected data. This study will be carried out using data already held by the Leeds Clinical Trials Unit and by NHS England. No study participants will be contacted. This study comprises secondary use of information that has already been collected via trial follow-up and routine methods.

Primary objective: Characterise the accuracy of using routinely collected data to identify breast cancer recurrences known to have occurred in women enrolled in the AZURE trial in England, and identify the factors that determine this accuracy.

Secondary objective: Characterise the accuracy of using routinely collected data to identify serious adverse events known to have occurred in women enrolled in the AZURE trial in England, and the factors that determine this accuracy.

If it can be shown that the algorithm produces valid results, then it will be possible for the first time to have validated nationwide long-term recurrence data for women with breast cancer. The availability of such data:
i. would help to catalyze policy improvement for the management of breast cancer patients
ii. would facilitate scientific research into the field of outcomes after breast cancer.
iii. would allow follow-up of the women in randomised trials such as the AZURE trial to be undertaken much more cheaply and easily in the future.

This agreement seeks an amendment to allow the University of Oxford to utilise honorary contract working arrangements and to add NHS England as joint data controller to reflect the joint working arrangements with NDRS.

The study team will not be requesting any further data under this agreement, this application seeks to retain and continue to process the following data previously disseminated by NHS England for a further 3 years.

NDRS Cancer Registrations
NDRS Cancer Pathway
NDRS Linked Cancer Waiting Times (CWT) Monitoring
NDRS Linked Diagnostic Imaging Dataset (DID)
NDRS Linked Hospital Episodes Statistics AE (HES AE)
NDRS Linked Hospital Episodes Statistics Admitted Patient Care (HES APC)
NDRS Linked Hospital Episodes Statistics Outpatients (HES OP)
NDRS Radiotherapy dataset (RTDS)
NDRS Systemic Anti- Cancer Therapy (SACT) dataset

The quantum of data requested is necessary to achieve the objectives of this project listed above. Data are required only for the study to investigate the accuracy with which breast cancer recurrence can be identified in women registered with invasive breast cancer using routinely collected data compared with recurrence information collected by the AZURE trial.

The level of the data is pseudonymised and will be minimised as follows:
-Limited to the approximately 2200 women registered in the AZURE trial in England
-Limited to the approximately 2200 women mentioned above for whom Patient IDs (usually NHS numbers) have been previously submitted to the NDRS by the University of Leeds.
-Limited to women randomised to the AZURE trial between 2003 and 2006
-Limited to data between the date on which the woman was diagnosed with breast cancer and the date of her last follow-up in the AZURE trial. Follow-up can last for up to 10 years.
-Limited to variables in the dataset listed above that either do or may indicate that the woman has had a recurrence of her breast cancer.

The data will be processed by the University of Oxford in England.

University of Oxford relies on General Data Protection Regulation Article 6(1)(e) - the processing is necessary for you to perform a task in the public interest or for your official functions, and the task or function has a clear basis in law. The public interest in this circumstance is research to increase medical knowledge for the benefit of all and to improve public health.

University of Oxford relies on General Data Protection Regulation Article 9(2)(j) - processing is necessary for archiving purposes in public interest, scientific or historical research purposes. The legitimate need for processing special category data under 9(2)(j) is that it adheres to the UK Policy Framework for Health and Social Care Research and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care.

Before starting this project, a pilot project was carried out using just data from the West Midlands Cancer Registry. The results of this pilot were presented to several groups, including the Association of Breast Surgeons and the project was discussed with those present. The views of consumer representatives (Independent Cancer Patients Voice) were also sought in an advisory capacity in dedicated meetings.

Funding is provided by the University of Oxford and by Grants from Cancer Research UK to the University of Oxford. Cancer Research UK will have no ability to suppress or otherwise limit the publication of findings of this research. There are no other organisation(s) involved or accessing the NHS England data, including organisations acting in an advisory capacity or as part of an oversight or steering committee.

In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and (11) of the National Health Service Act 2006.

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out.

Yielded Benefits:

Positive feedback have yielded from recent presentations derived from development work so far. July 2023: “Breast Cancer Recurrence Algorithm for Routinely Collected Data” Presentation of project by (University of Oxford), and the NDRS analysts (National Disease Registration Service) to the Health Quality Improvement Partnership (HQIP) commissioned National Audits of Primary Breast Cancer (NAoPri) and Metastatic Breast Cancer (NAoMe). These audits sit within the National Cancer Audit Collaborating Centre (NATCAN) established as a new national centre of excellence in October 2022 with the aim of strengthening NHS cancer services by looking at treatments and patient outcomes across the country. The members of these audits indicated how impressed they were with the project. They thought that the identification of recurrence is vital for both breast audits and that this work will inform parallel initiatives in other cancer sites. August 2023: “Developing an Algorithm to Identify Breast Cancer Recurrences using Routinely Collected Data in England”. Oral presentation at the 44th Annual Conference of the International Society for Clinical Biostatistics: Joint Conference with the Italian Region of the International Biometric Society, Milan, Italy.

Expected Benefits:

It is hoped the research will be able to provide a method of identifying when a patient who has been diagnosed with breast cancer has had a recurrence of that cancer. This would be a major improvement in NCRAS capability and would allow them to provide better follow-up for randomised trials and more informative data for observational studies. This study will help provide reliable information on breast cancer recurrences for research to improve treatment and for decision making in different areas of breast cancer management in the future.

The public benefits that are expected to be achieved as an outcome of this project include:
• Better determination of the burden of breast cancer so that appropriate policies for the management of the disease can be put in place.
• Catalyzation of policy improvement for the management of breast cancer patients
• Facilitation of scientific research into the field of outcomes after breast cancer

The specific benefits to patients are expected as an outcome of this project are that:
• It is hoped it will enable comparison of the outcomes of various treatments so that the best treatments can be identified for each woman diagnosed with breast cancer.

• It is hoped it will enable the prognosis for individual breast cancer patients to be established so that clinicians can advise patients appropriately.

It would allow follow-up of the women in randomised trials to be undertaken much more cheaply and easily in the future.

Outputs:

The research team are currently conducting analyses of these data prior to preparing a manuscript for publication.

The expected outputs of the data processing are:
• A peer-reviewed publication describing the process of deriving the algorithm, testing its validity and describing its strengths and limitations.

• A written document describing the technical details of the algorithm and accompanying computer code written by NDRS staff that implements it on data available within NCRAS.

The peer-reviewed publication will not contain NHS England data and will contain only aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The written document describing the technical details of the algorithm and accompanying computer code written by NDRS staff will not contain any data.

In addition to the above, presentations will be made at conferences relating to breast cancer and other meetings to publicise the work. Results will be presented to groups of clinicians and scientists whose work focuses on breast cancer, including the UK Breast Intergroup and the UK Breast Cancer Group. Once they are aware of this algorithm researchers will be able to include recurrence as an endpoint in their studies.

In addition, the algorithm will be available for use within NHS England allowing the NDRS to make those curating the data for other cancers aware of the possibility of identifying recurrences in this way, thus leading to the development of recurrence algorithms for recurrence for other cancers.

The first requirement is to confirm that the algorithm functions satisfactorily. Once this has been done, then the outputs will be communicated to relevant recipients through the following dissemination channels:

• Journals
• Social media (e.g. press releases)
• Public reports (all journal publications are accessible by the public)
• Briefing documents provided to clinicians [details to be decided]
• Open source frameworks [it is planned that, when all are satisfied with its performance, the source code for identifying recurrences will be available within NCRAS for use by NCRAS staff and other researchers]
• Oral presentations and poster displays at conferences
• Patient Information leaflets [results will form the basis of revised patient information leaflets]
• Press/media engagement
Public promotion of the research [e.g. via press/media engagement]

The research team expect the outputs to be available in from 2024-2026. Both Cancer Research UK and Independent Cancer Patients Voice are aware of this work. Other societies and charities will be informed in due course.

Processing:

The AZURE trial was a randomised controlled trial conducted in women diagnosed with invasive breast cancer in which some women standard treatment only and some women received zoledronic acid in addition to standard treatment. The objective of the trial was to compare the rate at which recurrences occurred in the two groups. Women were recruited from 2003 to 2006. Following recruitment, the women were followed up by inviting them to attend the clinic at which they were treated at regular intervals for 10 years. The data were assembled and collated by the Clinical Trials Research Unit at the University of Leeds. For the present study, the trials office in Leeds assigned an anonymous Study ID to each woman in the AZURE trial and then submitted these Study IDs, accompanied by patient identifiers (usually NHS number) to Public Health England (PHE) using standard operating procedures.

PHE identified the women in the AZURE trial in the National Cancer Registration Database. They then, using the algorithm that had already been developed, they identified women likely to have had a recurrence of their breast cancer and the date of the recurrence to a sample of the women in the AZURE trial. PHE then notified the Chief Investigator at the University of Oxford of these events and dates, using the anonymous Study IDs as the only identifiers. This process was repeated several times until the algorithm appeared to be working as well as could be expected for the women in the sample. The final version of the algorithm was then applied to the remaining women in the AZURE trial to test its validity and the Chief Investigator at the University of Oxford was notified of these events and dates.

The data linkages between the AZURE trial and the Cancer Registry have already been carried out and completed. Follow-up is not being extended for the AZURE trial, but the studies analyses are not yet complete, so The University of Oxford wish to continue and complete them until 2026.

The Leeds Trials Office provided the data collected during the course of the AZURE trial to the Chief Investigator at the University of Oxford, with the anonymous Study IDs as the only identifiers. Thus, no identifiable information is accessible to anyone outside the Leeds Clinical Trials Unit and NDRS at Public Health England (now NHS England) (both of whom already have access to these data). Researchers at the University of Oxford received only de-identified data with anonymised IDs.

This study has been granted ethical approval (Reference 17/WM/0347) and a Clinical Data Disclosure Agreement between the University of Leeds and the University of Oxford is in place.

The data will remain on the servers at the University of Oxford at all times. The data will not be transferred to any other location. The University of Oxford provides IT support and all IT hosting services. Data will be stored within Nuffield Department of Population Health (NDPH) in Oxford University. Electronic data files are kept on password-protected network servers behind a local firewall. Servers are kept in a locked room with access restricted to IT staff. Backups are held on private internal servers spread over three locations within the Old Road Campus of the University of Oxford. Backed up data is encrypted both in transit and at rest. Access to data is restricted via user identification. No data are moved or copied from these servers.

Access to electronic data is restricted via user identification.The IT department have setup a special permissions compliant folder to receive and hold data securely. The PI of the study team controls who can access this folder and the list is reviewed every 6 months. Data are not copied but can be accessed by analysis programs. Receipt of data is recorded in an asset register within NDPH. When data are to be deleted a request is made to the NDPH IT department who provide a deletion certificate which the study team enter into the asset register (any backups resulting from the 28-day back-up cycle are also deleted).

The data will not leave England/Wales at any time.

The data will be accessed by authorised personnel via remote access. Personnel are prohibited from downloading or copying data to local devices. The University of Oxford will ensure the correct supervisory and contractual requirements for personnel accessing the data are in place and that the University of Oxford’s organisational governance policies and controls are adhered to.

Whereby during the term of this agreement processing is required to be carried out by students affiliated with the University of Oxford (to potentially form part of studies ie: a DPhil degree) The University of Oxford, will only do so if beneficial to the research.

Whereby during the term of this agreement processing is required to be carried out by individuals with honorary contracts (to help introduce increased level of clinical expertise), The University of Oxford will only do so if beneficial to the research to help achieve the study objectives.

Data processing and access will be carried out only by personnel who have authorisation from the PI and who have been appropriately trained in data protection and confidentiality.

No other organisation is permitted to access the data, including the funder Cancer Research UK. The funder Cancer Research UK will not have influence on the outcomes nor suppress any of the findings of the research.

All data held by the University of Oxford are de-personalised and no linkages other than those described above will be carried out. Analysts and researchers from the Nuffield Department of Population Health at The University of Oxford will analyse the data for the purposes described above and there will be no requirement and no attempt to re-identify individuals when using the data in Oxford.

ORION-4: Data linkage to support outcome and other clinical data collection for consented participants — DARS-NIC-630656-V9W9M

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Sensitive

When:DSA runs 2023-01 – 2026-01 2023.05 — 2025.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Demographics
  2. Medicines dispensed in Primary Care (NHSBSA data)

Type of data: Identifiable

Objectives:

The University of Oxford requests access to the Medicines Dispensed in Primary Care dataset, and fact of death (referred to as 'Vital Status'), current address and GP surgery details from the Personal Demographics Service dataset, for a randomised controlled trial entitled ORION-4 (“A Randomized Trial Assessing the Effects of Inclisiran on Clinical Outcomes Among People With Cardiovascular Disease”).

ORION-4 is registered in clinicaltrials.gov (NCT03705234) and has approval from the Health Research Authority (IRAS 240684).

ORION-4 is an ongoing trial of a new cholesterol lowering drug called inclisiran, and is co- sponsored by the University of Oxford and Novartis. Inclisiran is administered as an injection 2-3 times per year and reduces low-density lipoprotein (LDL) cholesterol. The ORION-4 trial will determine if this drug is helpful in reducing cardiovascular events such as strokes and heart attacks in people with a previous history of such conditions, and who have high cholesterol levels despite available treatment with established cholesterol-lowering medications. The main purpose of the medicines data research project is to enable the assessment of the efficacy and safety of inclisiran in relation to non-study medications. The trial aims to recruit 12,000 participants in the UK. If shown to be effective, this treatment could substantially reduce premature death and disability from these conditions. A secondary objective is developing streamlined trial methods that would benefit future research.

This study was initiated by independent scientists at the Clinical Trial Service Unit (CTSU) based at the University of Oxford.
It is sponsored by the University of Oxford, and the Medicines Company (MDCO), which was acquired by Novartis - a Swiss-American multinational pharmaceutical corporation - in January 2020, in collaboration with the TIMI Study Group - an academic research organisation - based at Brigham and Women’s Hospital, Harvard Medical School, Boston.

It is noted that Novartis is named as a study sponsor in the study protocol, however, The University of Oxford are the sole data controller for this Agreement, The University of Oxford determines which personal data should be collected (in line with the protocol) and how, when and by whom personal data is processed and is responsible for the security of those data.

The University of Oxford and Novartis will act as co-sponsors of the trial and will share sponsorship responsibilities: the University will be the academic lead and sole Data Controller for the trial and Novartis will be the regulatory lead (e.g. managing regulatory submissions and interactions). Novartis will also provide packaged study medication (Inclisiran and matching placebo) for the study.

The aim of ORION-4 is to improve the health of patients with cardiovascular disease. However, if proven safe and effective, Novartis will benefit from the increased use of inclisiran.
This an investigator initiated trial with a purpose of improving the health of people with vascular disease. If the results show that inclisiran is safe and effective this could also increase revenue for the manufacturer, funder and cosponsor Novartis, as the manufacturer of the drug.

Patient and Public Involvement and Engagement:
Most aspects of the ORION-4 study design have been closely modelled on previous successful studies undertaken by the Clinical Trial Service Unit. In particular, the patient population, eligibility criteria, recruitment strategies and follow-up methods are very similar to those of the HPS-2THRIVE study and the REVEAL study, both of which successfully recruited over 8000 UK participants. Participant feedback from these studies has informed the design of ORION-4. Furthermore, the ORION-4 study design, methods and participant information has been reviewed by the Nuffield Department of Health participant panel which includes previous trial participants. This panel will be involved in developing future participant facing materials, including participant newsletters and eventually, the communication of study results.

No data obtained as part of this agreement will be shared with Novartis. However, as part of the trial Steering Committee, Novartis may be presented with results from this study in the form of aggregated outputs with small numbers suppressed, and will have the opportunity to review any papers prior to publication. The Steering Committee determine the scientific objectives of the trial, ensure adequate progress towards those objectives and review any papers prior to publication. As is usual with this type of trial, the Steering Committee has representatives from the funder/co-sponsor Novartis and also has other experts from other institutions to advise the trial management team. Neither the Steering Group nor Novartis will have access to or process any NHS England record-level Data. The funders have no ability to supress any findings or control any of the outputs.

In respect of the data under this Agreement, the University of Oxford is the sole data controller who also processes the data for this study. The University of Oxford determine how, when and by whom personal data is processed and is responsible for the security of those data.

Potentially eligible trial participants are currently identified on an ongoing basis via centralised electronic health record screening, in collaboration with NHS England (under data sharing agreement DARS-NIC-172240-R4R0L). If willing to take part, eligible trial participants are invited to attend a screening visit where eligibility is confirmed and consent is collected, and then enter a placebo run-in after a first injection (enables exclusion of patients who respond well to the placebo intervention). Approximately 2 months later, consented participants attend a randomisation visit and start receiving either active or placebo injections. Follow-up visits with treatment administration are then performed after 3 months, and then every 6 months onwards until the scheduled treatment period is complete (estimated to be about 5 years).

Randomized controlled trials (RCTs) are the gold-standard for the assessment of efficacy and safety of medical interventions. Data used in RCTs is usually collected specifically for research during long time periods and with a high level of detail, making the conduct of high-quality RCTs both a complex and costly endeavour. With regards to concomitant medications, these data are usually collected by research staff based on patient-reported information, making this process the de facto standard in trials. However, data routinely collected for health care purposes is considerably similar to that collected for medical research (including on medications), sparking an interest in the use of routinely collected data (RCD) to inform the design and conduct of RCTs. Moreover, RCD is usually gathered via electronic systems and may prove to be more accurate than manually-recorded data. Harnessing RCD might therefore provide enhanced data integrity and completeness for planning, recruitment and follow-up purposes, bearing the promise of reduced costs and improved external validity of results.

Validating the use of routinely collected data on medications for randomised trials:

Under this agreement, The University of Oxford request access to the Medicines Dispensed in Primary Care dataset to conduct methodological research on the use of routinely-collected data on medications for the purpose of large-scale randomized trials. This will provide direct benefit to the ORION-4 study by enabling the study team to understand the accuracy of the data entered by the local research staff. After the development of preliminary methodological work to assess the agreement between BSA Medicines data and that entered by trial staff, the BSA Medicines dataset will be used to further characterise the cohort at baseline, allowing analysis of the effects of the treatments in different types of patients, and may help to identify new diagnoses (e.g. diabetes). This will help the team identify long-term outcomes in the cohort and assess the effects of the treatments on these outcomes. The processing of this data and use of the BSA Medicines dataset for ORION-4 is in line with the Direction covering that dataset where the purpose is to drive the linkage of medicines data with other data sets to provide intelligence about the safety and effectives of medicines.

The Medicines Dispensed in Primary Care dataset contains all records of medications prescribed or dispensed in the community setting in England and submitted for reimbursement to the NHS Business Services Authority, starting from April 2018. Given its wide scope and broad coverage, these data hold significant potential for use in medical research and clinical trials in particular.

Under this agreement, the University of Oxford propose to compare self-reported medication data collected by local research staff during trial visits with the data collected from the Medicines Dispensed in Primary Care dataset.

The main aim will be comparing capture of specific drugs of interest to the ORION-4 trial at the time of each individual participant study visit. Drug groups of interest will include:
- cholesterol-lowering drugs
- antithrombotic drug
- antihypertensive / heart failure drugs
- antidiabetic drugs

Secondary aims will be:
1) to calculate the total number of individual drugs identified at each time point, and highlight drug groups that may be missed by each of the two sources,
2) to derive measures of medication adherence using the Medicines Dispensed in Primary Care dataset for lipid-lowering drugs (namely for statins) and assess how they relate to total cholesterol levels measured at randomisation, and 3) to assess the feasibility of aligning this RCD source with CDISC standards for medications data collection in trials.

The ultimate goal of all the aims described is to develop the methodology needed to use the Medicines Dispensed in the Community dataset to look at the safety, efficacy, and management of drugs, in this trial and other future settings, as specified by the dataset directions.

Vital Status and updated contact details for trial participants:

Also under this agreement, The ORION-4 Coordinating Centre at the University of Oxford is requesting use of the Personal Demographics Service (PDS) to undertake a 'vital status' check on current study participants. The study team needs to mail letters to UK trial participants who have provided informed consent at their screening visit (for example to confirm inclusion in the study, further study appointment bookings, general correspondence with the study team about participation in the study, or newsletters). In order to avoid causing distress to family members the Coordinating Centre team would like to undertake a vital status check before any central participant mailings to remove those participants who have since sadly passed away. In addition, the University of Oxford request the participant's current address and GP surgery code. These details are checked by the local research coordinator at each study visit. However, some participants have moved and not updated the study team with their new address and GP surgery especially during the clinic disruption due to COVID-19. Having their latest address and GP surgery code from the Personal Demographics Service (PDS) would enable the University of Oxford to get in contact with study participants to offer them a further study appointment if possible in their new area and ensure that any communication is sent to their correct GP. Vital status and updated contact details are requested at monthly intervals for the 3 year duration of this DSA to allow rolling updates to the data already held by the study during this period.

All data will be processed in secure servers within the Nuffield Department of Population Health, University of Oxford, which is the sole data processor for this Agreement. These data will only be used for the purpose of this research project, and they will not be provided to any third party.

The University of Oxford, as the sole Data Controller who is also processing the data will process Personal Data under GDPR Article 6 (1) (e) - Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. As a higher education establishment, the University of Oxford conducts research to improve health care and services, and the data requested is necessary for the performance of a task carried out in the public interest.
Additionally, under GDPR Article 9(2)(j) processing of Special Category Personal Data (of which Health data is one) is necessary for archiving for research purposes. Data minimisation processes are being followed and only data that is specifically required for the purposes of this study have been requested, to protect the rights of the data subjects. The data are required for research purposes in the public interest – meeting the conditions in the DPA 2018 Schedule 1 Part 1 (4) – which GDPR Recital 52(2) determines is an appropriate derogation from the prohibition on processing special categories of personal data.

The duty of confidentiality is met as all study participants have provided written informed consent.

This research project will also contribute to an ongoing DPhil (Philosophy Doctorate) thesis, by a student who is a substantive employee of the University of Oxford. Funding is provided by the Medical Research Council through a studentship awarded to the project lead by the Population Health Research Unit at the Nuffield Department of Population Health, University of Oxford. Funding for the ORION-4 trial was provided by a research grant from The Medicines Company to the University of Oxford for the trial. Novartis acquired The Medicines Company in 2020 and took over the funding of the study.

In the interests of Transparency, it is noted here that this an investigator-initiated trial with a purpose of improving the health of people with vascular disease. Novartis will provide study funding and packaged study medication (Inclisiran and matching placebo) for the study and are co-sponsor of the trial. Novartis holds the UK marketing authorisation for Inclisiran, and Inclisiran is from a class of drugs called siRNAs. As the sole manufacturer of an siRNA for use in lipid management, Novartis could hold a unique competitive position to gain financially if inclisiran is widely prescribed within the NHS. However this is not the primary purpose or outcome of ORION-4. Inclisiran was selected for study in ORION-4 because it has a number of features which make it a potentially useful population health intervention: infrequent 6-monthly injections, storage at room temperature (no cold-chain requirements) and a 50% reduction in LDL-cholesterol. If the results of ORION-4 show that inclisiran is safe and effective this will also increase revenue for the Novartis but this is not the primary purpose of ORION-4.

Expected Benefits:

The main purpose of the medicines data research project is to enable the assessment of the efficacy and safety of inclisiran in relation to a matching placebo, including the potential impact of other (non-study) medications being taken by a participant. After the development of preliminary methodological work to assess the agreement between BSA Medicines data and that entered by trial staff, the BSA Medicines dataset will be used to further characterise the cohort at baseline, allowing analysis of the effects of the treatments in different types of patients, and may help to identify new diagnoses (e.g. diabetes). This will help the team identify long-term outcomes in the cohort and assess the effects of the treatments on these outcomes. The processing of this data and use of the BSA Medicines dataset for ORION-4 is in line with the Direction covering that dataset where the purpose is to drive the linkage of medicines data with other data sets to provide intelligence about the safety and effectives of medicines.
Use of these data for medical research purposes may help reduce the costs and burden of data collection for research purposes and enable the deployment of broader, faster, and cheaper trials, streamlining the deployment of new interventions that can benefit patients and the NHS, as well as increasing University of Oxfords understanding of health and disease. Similarly, making better use of available data leads to fewer burden of resources for GP practices and hospitals participating in research, as well as to patients volunteering their time and information. It can also facilitate easier access to NHS organisations and patients that want to take part in research.

The secondary outputs aim to help streamline the use of these data for medical research. The lessons learnt may also inform the development of new international standards for data reporting in clinical trials that are able to accommodate routinely collected data on medications, enhancing trial procedures on a global scale.

Finally, the validation work proposed here hopes to help to pave the way for more randomised trials to be performed in the UK, contributing to make the NHS the world-leader in data-enabled clinical trials and thus supporting the broader healthcare and science economy, as outlined in the UK Government Life Sciences Industrial Strategy.

The data about current address, GP surgery and vital status aims to help the trial successfully communicate with participants and their GPs. This is important for a high quality participant experience but also important to allow the study to achieve high levels of adherence to study treatment. This is critical in producing robust results and hopes to help the study to generate practice changing results which, if the treatment is safe and effective, may improve outcomes for people with cardiovascular disease within the UK and around the world.

Outputs:

The main direct outputs of the work relating to the prescribing data will be scientific research papers and presentations at scientific meetings. The University of Oxford will aim for publication in trial methodology journals such as Trials and Clinical Trials, although broad medical journals, such as JAMA Network Open (a monthly open access medical journal published by the American Medical Association) or BMJ Open (a peer-reviewed open access medical journal that is dedicated to publishing medical research from all disciplines and therapeutic areas), and those in the pharmacoepidemiology and cardiovascular fields may also be considered.

Scientific presentations hope to be aimed at trial methodology conferences such as the International Clinical Trials Methodology Conference, the Society for Clinical Trials meeting, and the Cardiovascular Clinical Trialists Forum, although cardiology conferences such as the European Society of Cardiology (ESC) conference or the ESC Digital Summit may also be considered.

The results are aimed to also be disseminated through collaboration with the Health Data Research UK clinical trials program and the MRC-NIHR Trials Methodology Research Partnership.

The focus of the results presented centre on how routinely-collected data compares with self-reported medication as collected during trial visits. This hope to provide valuable information to the ORION-4 trial team on the accuracy of the data held within the trial database and inform future trials. Secondary outputs of this work aims to also include the coding and processes developed to handle these data.

The methods and results spanning from this work are hoped to also be included in a DPhil thesis to be submitted to the University of Oxford.

The target data for all the planned outputs of the Medicines methodology development work will be the end of the year 2023. A three year Agreement is required to accommodate the regular disseminations of Demographics data.

The ability to centrally mail study participants across the UK will reduce pressure on local research staff at a time of scarce resource within the NHS. By checking vital status prior to any mailings the ORION-4 coordinating centre aism to avoid causing distress to family members of participants who have passed away. In addition, the updated address and GP details aim to ensure that important communications to trial participants are correctly addressed and that participants can be offered an ongoing trial follow-up visit appointment.

Processing:

Under this agreement, one extract of the Medicines dispensed in Primary Care data linked to the ORION-4 cohort of participants will be requested from NHS England. The Demographics dataset will be returned separately linked to the ORION-4 cohort. The cohort will include all participants randomised in England/Wales.

The details for linkage purposes will include ORION-4 study number (Study ID), NHS Number, name, date-of-birth and postcode. After receipt of the cohort details and respective linkage, NHS England will provide a linked copy of the Medicines dispensed in Primary Care data dataset on a one-off basis as soon as possible. NHS England will also provide a report to the University of Oxford on any NHS Numbers that are not found.

The data will be transferred via NHS England's Secure Electronic File Transfer System (SEFT).

All data processing will be carried out by substantive employees of the University of Oxford who have received appropriate training in data protection and confidentiality.

Record-level data will be stored, accessed and backed up at back-up storage sites on campus at University of Oxford.

All data received will be kept, accessed, and processed within the University’s systems using a secure password-protected environment, with access granted on a need-to-know basis. Personally-identifiable data will be kept in a highly secure specific data store with access restricted to a small number of employees. The pseudonymised data is stored in a separate secure location with separate controls on whom can access these data for analysis.

Statistical data analysis will be carried out via devices owned and managed by the University of Oxford by connecting to internal networks where the data are stored securely, either directly in person or remotely, using an appropriate statistical package. To remotely access the devices requires a secure 2-factor authenticator (VPN) and users are then able to securely access the secure server on the University’s IT framework. All data analysis will be conducted within the confines of the University’s secure server, and will not be downloaded to remote devices for storage or processing.

No record level data will be shared or stored outside the University of Oxford or supplied to any third party. Access will be provided only to individuals directly involved in processing these data for the purpose outlined in this Agreement.

No data received under this agreement will be shared with any parties other than the University of Oxford. In particular, no record-level data provided by NHS England as part of this agreement will be provided to Novartis.

The data will not be onwardly shared in any way other than in the form of aggregated outputs with small numbers suppressed (as per the HES analysis guide), which may be presented to other investigators in the ORION-4 study, Novartis, and the broader scientific community via research publications and presentations.

Data will be retained for a period of 25 years to allow internal monitoring by the University of Oxford and for academic archiving purposes, in line with the information given to consenting participants in the study Patient Information Leaflet.

The data requested will be restricted to that required for the analyses proposed here, namely details on drug prescribed and drug paid/dispensed, as well as prescription and dispensing setting. NHS Number and Date of Birth will be requested to confirm correct linkage, although these are already known to the study and will be provided by the University of Oxford to NHS England upon provision of the cohort details. NHS number and date of birth are requested from NHS England so that these can be cross-checked with the ones already held by the study.

NHS England data provided under the Data Sharing Agreement will not be combined with data from the US or used in joint analyses. The data requested in the DSA will be used to check and validate the existing data collection method in the UK and as such improve the quality of the research data collected as part of the trial.

Data obtained about vital status of the cohort will be used to avoid mailing letters to individuals who have sadly passed away since being recruited to the study. Data about updated address and GP surgery details will be used to ensure that letters to participants and their GPs are correctly addressed. This data will be stored securely within NDPH servers and accessed only by members of the team developing the IT applications required for the mailings and by senior members of the ORION-4 team who may need to resolve queries. Monthly extracts will be requested to ensure that vital status is up-to-date.

The data from NHS England will not be used for any other purpose other than that outlined in this Agreement. The data will be collected, analysed, and published independently of any sources of funding. The funders will have no ability to suppress any findings should they lead to any negative outcomes on their products.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by Personnel(as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

Health economics analysis for FAME: In younger adults with unstable ankle fractures treated with close contact casting, is ankle function not worse than those treated with surgical intervention? — DARS-NIC-595090-W5R3K

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2023-01 – 2029-12 2025.02 — 2025.03.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Accident and Emergency (HES A and E)
  4. Hospital Episode Statistics Admitted Patient Care (HES APC)
  5. Hospital Episode Statistics Critical Care (HES Critical Care)
  6. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

Every day approximately 170 people sustain an ankle fracture in the UK. They may experience pain and physical impairment for several months and years after injury, either through the index injury or from complications of treatment. Prolonged work absence, chronic pain, psychological distress, and later post-traumatic arthritis are all commonly reported.

This study covers only non-complex fractures, which include a wide range of injuries over a wide age range and for which the mechanisms of injury vary substantially. Treatment options are wide, which presents an important challenge to the NHS. Many non-complex fractures get better with minimal clinical intervention; however, they can also appear minor and be easily missed, but lead to potential poor long-term outcome. In the case of non-complex ankle fracture, the broad aim of ankle fracture treatment is to maintain the alignment of the joint whilst the fracture heals and to reduce the risks of problems such as stiffness. More severe injuries to the ankle are routinely treated surgically. However, even with advances in surgery, there remains a risk of complications; for patients experiencing these, the associated loss of function and quality-of-life is considerable. Non-surgical treatment is an alternative to surgery and involves applying a cast carefully shaped to the patient’s ankle to correct and maintain alignment of the joint; the key benefit being a reduction in the frequency of common complications of surgery. The main potential risk of non-surgical treatment is a loss of alignment with a consequent reduction in ankle function.

Fractures that are judged to be unstable are usually treated surgically with the aim of correcting and then stabilising the alignment of the ankle bones in an attempt to ensure good ankle function once the fracture has healed. Even with advances in surgery, there remains a risk of complications. Many of these complications are related to the surgical treatment – failure of bone healing (1%), wound breakdown (9.1%), metal implant failure (1.7%) or irritation from implants requiring removal (1.3%) and infection (2.7%). For those people experiencing complications, the functional loss and decline in quality-of-life are still experienced months and sometimes years after injury.

Non-surgical treatments have the key benefit of avoiding the risks of surgical complications. For example, close contact Casting (CCC) involves applying a cast, carefully shaped to the patient’s ankle, to correct and maintain alignment of the joint through external support. This avoids the need for incisions in the skin and implantation of metalwork, thereby reducing the risk of wound complications, infection, and irritation from implants. The concern with non-surgical treatment, where the opportunity to directly and anatomically realign and fix the bones of the ankle is not realised, is that it may yield inferior outcomes compared with surgery.

However, there is increasing recognition across other orthopaedic conditions that perfect anatomical reconstruction of the bones does not necessarily correlate with improved functional outcomes. The clinical uncertainty here lies in whether non-surgical treatment can yield similar outcomes compared with surgical treatment.

Moreover, 60% of ankle fractures occur in adults less than 60 years of age. The majority of these fractures in younger adults will be treated non-operatively with a standard plaster cast or walking boot. Forty per cent, however, are more severe, and currently treated with an operation; representing around 14,000 surgically treated fractures per annum in the UK. Younger adults typically have a higher functional demand and may have a greater risk of developing late post-traumatic arthritis. It is reasonable to expect that treatments may yield different outcomes in this younger population and that the findings of previous studies may not be generalisable.

Opinion is genuinely divided amongst trauma and orthopaedic surgeons in how best to manage unstable ankle fractures. To University of Oxford's knowledge, there are no existing trials comparing CCC with surgical treatment of unstable ankle fractures in younger adults. There are compelling reasons to believe that outcomes and resource use will be different in younger, working-age adults compared with older people. The risk of complications following surgical treatment in younger, fitter adults may well be lower and poor outcomes therefore less frequent; equally, productivity losses associated with work absence may substantially influence cost-effectiveness in this working-age population. With this substantial instance of disease, and uncertainty in the clinical and cost-effectiveness of the technologies, high quality evidence is required to determine whether the drawbacks of surgical management of ankle fracture are balanced by any improvement in functional outcomes in younger adults and a need to definitively test if non-surgical management can produce similarly acceptable outcomes as surgical management in adults aged 60 years and younger.

The clinical and cost-effectiveness of surgical management of unstable ankle fractures in younger adults was a ‘Top 5 research recommendation’ in the recent guidance by the National Institute for Health and Care Excellence (NICE) and identified as a priority at the joint Royal College of Surgeons and The National Institute for Health Research (NIHR) Research Prioritisation Exercise 2017.

The Fractured Ankle Management Evaluation (FAME) study aims to determine whether ankle function, four months after treatment in patients with unstable ankle fractures treated with close contact casting (an alternative to surgery which uses less padding than a traditional cast and sets the bones by being a close anatomical fit), is not worse than in those treated with surgical intervention, which is the current standard-of-care. The study is conducted as a randomised clinical trial. The overarching objective of this study is to investigate the difference in ankle function, the risk of late complications and comparative cost-effectiveness between the trial treatment groups over five years.

The objectives that are addressed through this data processing are:
1. To assess the longer-term incidence of complications of the two treatments under investigation
2. To validate patient-reported hospital healthcare use collected during the trial against data collected from NHS Hospital Episode Statistics
3. To assess the longer-term cost-effectiveness of close contact casting (CCC) compared with surgery in the patient population of the trial

A randomised clinical trial is the best method to compare treatments to guide the care of patients. Randomisation will be used to produce two groups of patients: those who undergo internal fixation of their fracture, and those who undergo close contact casting (CCC). Patient follow-up will extend to 5 years post-treatment via hospital records. The trial is funded by the National Institute for Health Research (NIHR) Health Technology Assessment, project reference NIHR127273. The project is not part of a wider project, collaboration, or associated work.

Adult patients, aged 60 years and younger, with unstable ankle fractures are identified in daily trauma meetings and fracture clinics and approached for recruitment prior to their treatment. The study includes only adult participants since injuries in children behave differently and should not be grouped with all injuries. Older adults (above 60 years of age) are not included since we already have a trial for this age group (AIM) that has addressed the role of the treatments in this older group with different injury patterns. Treatments are performed in trauma units across the UK by a wide range of surgeons. Details of the surgical treatment, including how the operation is done, implant choice and the recovery programme afterwards is at the discretion of the treating surgeon.
The non-surgical treatment is close-contact casting performed under anaesthetic, a technique which has gained in popularity since the publication of the Ankle Injury Management (AIM) trial. Eight hundred and ninety (445 per arm) participants will be randomly allocated to surgical or non-surgical treatment. Data regarding ankle function, quality-of-life, complications, and healthcare related costs will be collected at eight weeks, four and twelve months and then annually for five years following treatment. The primary outcome measure is patient-reported ankle function at four months from treatment.

The trial team will aim to recruit 890 patients over a 24-month period, from more than 26 hospitals within the UK. Recruitment started in December 2019, and as of July 2022, 580 people have been recruited with recruitment ongoing. Access to data from hospitals not in England will be requested from the relevant data sources (e.g.: ISD Scotland). Every participant for whom data are requested will provide prospective consent to access their personal data.

The data subjects will be the trial participant cohort who fulfil all eligibility criteria as defined below:
Inclusion Criteria
• Patient is able and willing to give informed consent for participation in the trial, and
• Patient is aged 18 to 60 years inclusive with an unstable ankle fracture and
• who in the opinion of the treating surgeon may benefit from surgical treatment with internal fixation.

Exclusion Criteria
The patient may not enter the study if ANY of the following apply:
• The fracture is open.
• The fracture is complicated by local tumour deposits.
• The injury is an isolated fracture of the medial malleolus (The injury only involves the inner side of the ankle joint).
• The index injury occurred more than 14 days prior to recruitment.
• They are unable to adhere to trial procedures.
• Previous randomisation in the current trial.

The University of Oxford relies on GDPR Article 6(1)(e) as the lawful basis for processing the data within this Agreement. There is public interest for patients, healthcare staff and the NHS, as this research will decrease uncertainty and allow standardisation of care and promotion of development of pathways for more efficient and cost-effective care.

The Agreement requires processing of special category data and relies on Article 9(2)(j) as a lawful basis for processing data. Data for this project has been minimised to ensure researchers only have access to the data they require to carry out the statistical and scientific processing of the data and to meet the purpose of the project for which there is a public interest. There is public interest for patients, healthcare staff and the NHS, as this research will decrease uncertainty and allow standardisation of care and promotion of development of pathways for more efficient and cost-effective care. There has been consideration given to any potential ethical or moral issues, and as such an NHS Research Ethics Approval has been granted for this study and all participants have prospectively consented to share their data in line with the processing described in this Data Sharing Agreement (DSA).

NHS Digital datasets to be used include HES Admitted Patient Care, Outpatients, Accident and Emergency and Critical Care, as well as Civil Registration - Deaths and ECDS. Each of the requested datasets provide distinct data that are not available elsewhere and are required to determine outcome necessary to answer the research questions described in the objectives.

Data will be required at the level of the participant in order to construct an adequately explanatory statistical model to address the research questions; all data will be deidentified prior to transfer to University of Oxford. Only consented trial participants in England will be included in the requested cohort. The study team have carried out a multicentre trial in order that the results are generalisable to NHS practice and therefore require data from participants across England.

Not all the study team are employees of Oxford. However, only substantive employees of University of Oxford will be allowed access to any data from NHS Digital.

The research team is minimising data requested to only the trial participant cohort; data for each participant in the cohort will be requested for the period that they are involved in the trial follow-up (up to five years).
In planning the study with patient representatives and gaining NHS Research Ethics approval, the team explored alternative means to address these objectives and the chosen approach was considered both proportionate and appropriate.

This study was developed through collaboration with several stakeholders, most importantly patient representatives. Collaborating stakeholders contributing to the trial development included orthopaedic surgeons, physiotherapists, occupational therapists, trainees in orthopaedic surgery, and patient representatives. The study design was also supported by the British Orthopaedic Association and the UK Orthopaedic Trauma Society. Patient and Public Involvement (PPI)s confirmed the appropriateness of the outcome instrument to measure effectiveness in the defined clinical setting; determined the exact nature of the health technologies; and drafted and revised the text of the project application. PPIs are also involved in the dissemination of the main results of the study.

The University of Oxford's patient representatives will lead dissemination to the patients and carers directly through their extensive network of patient advocacy organisations, which include the Arthritis Research UK (ARUK) Centre for Epidemiology, Wales Centre for Primary and Emergency Care (Including Unscheduled) Care research (PRIME) and the Oxford Link and other local interface organisations. They will help generate a plain language summary for patients and the public.

University of Oxford is the sole data controller who also processes the data for the purposes described in this Agreement.

The University of Oxford is working with other NHS and research organisations to deliver this study:
• University of Bristol, Musculoskeletal Research Unit
• South Tees Hospitals NHS Foundation Trust
• University of Warwick, Clinical Trials Unit
Members of the study team from these organisations will only have access to aggregated data for the purposes of contributing to the oversight, analysis and reporting of the study

The Chief Investigator is substantively employed by Queen Mary University London (QMUL) but is an honorary departmental associate of trauma surgery at the University of Oxford. QMUL have no role in FAME. Co-investigators named in the protocol associated with University of Bristol and University of Warwick will have input on reviewing and approving the health economic analysis plan (HEAP) and interpreting the aggregated results of the analysis, but they will not have any access or involvement in determining the purpose, processing the data, acting on behalf of the data controller, or carrying out any operation on the requested data. University of Oxford only will act in the capacity of data controller to conduct and implement the health economics analysis plan. The trial steering committee (TSC), which includes independent members, provides overall supervision of the trial on behalf of the funder. The data safety and monitoring committee (DSMC) is a group of independent experts external to the trial who assess the progress, conduct, participant safety and, if required critical endpoints of a clinical trial. TSC, and DSMC will not have access to NHS Digital data.

Yielded Benefits:

This is a new study and there are therefore no yielded benefits to report.

Expected Benefits:

The outcomes of this project are hoped to lead to updating NICE guidance on non-complex fractures.

This is highly likely to be the only definitive trial addressing the research question and it is the therefore expected to directly influence national clinical practice within five years. These outputs would be expected to directly benefit patients, healthcare staff and the NHS by decreasing uncertainty, allowing standardisation of care and promoting the development of pathways for better care by providing greater information and guidance regarding the treatment of non-complex fractures.

In addition, the health economic evaluation results on the cost-effectiveness of both treatment strategies will provide decision-makers with evidence to inform commissioning decisions. In this way, University of Oxford expect the results of this trial to improve value-for-money of treatments for ankle fracture in the NHS.
The realisation of benefits will begin immediately once the outputs are delivered. The study is not in support of a PhD/post graduate research study.

Outputs:

At the conclusion of this study, the University of Oxford will hope to have provided the most robust evidence available to infer whether ankle function in patients with unstable ankle fractures treated with close contact casting, is not worse than in those treated with surgical intervention. Patients and members of the public will help design a publicity strategy so that the results of the study are distributed outside of the routine scientific literature.

A report will be produced, which will inform the full update of fractures (non-complex): assessment and management guidance (NICE Guidance NG38) for healthcare professionals in 2027. Plain English outputs will include papers and web and blog media.

All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. Data will be aggregated and presented at the level of the randomised treatment arm. Applicable data within cells will be suppressed if they are small values to reduce the risk of re-identification.

No participant-level data falling under this Agreement will be shared with any third-party.

The dissemination strategy will consist of three strands. The first will ensure that patients and the public are informed of the trial results; the second will engage practitioners and health-care providers, and the third will inform national guideline and policymakers.

Patients, patient advocacy groups & members of the public:
Patient representatives will lead dissemination to the patients and carers directly through their extensive network of patient advocacy organisations. They will help generate a plain language summary for patients and the public. This document will be available in paper copy, podcast and as a blog. An abstract will be submitted to the biannual “Involve” Conference. Posters will also be prepared with the Patient and Public Involvement (PPI) team for inclusion at any workshop or conference where relevant PPI is being discussed. In addition, to disseminate directly to study participants, findings will be more widely available locally through posters in appropriate outpatient rooms and liaising with identified service user groups.

Health care providers: the trial team will work with the Oxford National Institute for Health Research Biomedical Research Centre (NIHR BRC) and Collaboration for Leadership in Applied Health Research (CLARHC) media teams to maximise the reach of the press and publicity outputs from this study. University of Oxford have costed the application to include five free-to-access publication in the mainstream literature. The final results will be submitted for presentations at annual meetings of the British Orthopaedic Association (BOA) and the Orthopaedic Trauma Society (OTS). University of Oxford will present the findings to the entire NHS via the NHS national electronic Library for Health (NHS Evidence). International ‘reach’ of the published research findings will be supplemented by presentations at high visibility meetings such as the Orthopaedic Trauma Association (OTA) Annual Meeting (United States) and BOA Annual Congress (Europe). In addition, University of Oxford are developing complementary systems incorporating non-traditional media. The chief investigator has been developing an enhanced web presence through blogging on the leading UK trauma and orthopaedic websites. These blogs engage both trauma and research communities. They have been very successful and have provided a means for rapid dissemination. University of Oxford plan to expand this activity into additional subject-specific and general blogs such as the British Medical Journal (BMJ).

National guidelines: University of Oxford will use their established network involvement to disseminate these research findings. These include the NIHR Clinical Research Network, and specialist interest groups (BOA/OTS/OTA/ European Federation of National Associations of Orthopaedics and Traumatology (EFORT)). University of Oxford will alert the relevant NICE standing committee to the results of the trial by notifying their surveillance team.

The study team is due to report in March 2023 and inform the full update to NICE Guidance NG38 in 2027.

A Study of Cardiovascular Events iN Diabetes – PLUS (ASCEND PLUS) - Recruitment agreement — DARS-NIC-655024-S2H5Q

Opt outs honoured: (Excuses: Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(2)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: Yes (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2022-12 – 2024-12

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Customer - Data Quality Report - Aggregate (Comms)
  2. Customer - Data Quality Report - Aggregate (Recruitment)
  3. Demographics
  4. Mailing - Cohort - Non-aggregate (Comms & Recruitment)

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

BACKGROUND
Around one in 11 adults worldwide has diabetes: a long-term condition where a person’s blood sugar levels are too high.
There are two main types of diabetes:
• Type 1 diabetes – where the body’s immune system attacks and destroys the cells that produce the hormone insulin so that no insulin is produced. This is treated with insulin injections.
• Type 2 diabetes – where the body does not produce enough insulin, or the body’s cells do not react to insulin. This usually occurs later in life and is often treated with tablets. Some patients eventually need to be treated with insulin.
People with diabetes are more likely to suffer from other major health problems. These include heart and circulatory problems (including heart attacks and strokes), high blood pressure and dementia. Diabetes can cause kidney disease, problems with feeling in the feet, and eye problems that may affect vision.

ASCEND PLUS is a clinical trial led by the University of Oxford. It is a randomised, double-blind, parallel-group, placebo-controlled event driven trial designed to test the hypothesis that oral semaglutide reduces cardiovascular events and other complications of diabetes in people with type 2 diabetes mellitus (T2DM) without a prior heart attack or stroke. The study will use streamlined methodology to randomise approximately 20,000 people with T2DM in the UK and follow them during a scheduled treatment period with a median duration of approximately 5 years.

OUTCOMES DATA (Not part of this agreement however for future information)
With consent, the ASCEND PLUS team will collect linked healthcare data from NHS Digital and other organisations for the 5-year scheduled treatment period and the following 20 years in order to find out the medium and long-term effects of oral semaglutide (this linkage for consented trial participants will be covered by a separate Data Sharing Agreement).

THE AIM OF THE TRIAL
The ASCEND PLUS trial aims to provide evidence about both the efficacy and safety of prolonged treatment with oral semaglutide. The hypothesis of the ASCEND PLUS trial is that treatment with oral semaglutide reduces cardiovascular events and other complications of diabetes in individuals aged at least 55 years, with T2DM, without a history of a heart attack or stroke, and without any upper or lower Haemoglobin A1c (HbA1c) threshold.

STUDY TEAM
Any reference to "the study team" in this agreement refers to members staff substantively employed by University of Oxford directly working on the ASCEND PLUS programme.

PATIENT AND PUBLIC INVOLVEMENT AND ENGAGEMENT (PPIE)
Two lay members were recruitment to the trial Steering Committee (TSC) and attended the first TSC meeting in June 2021 and subsequent meetings, ensuring patient and public involvement in the high-level strategic decisions for the trial.

Between June and October 2021, the ASCEND PLUS team convened six patient and public focus groups, largely involving people with type 2 diabetes. The groups included people from diverse backgrounds across the UK, with the exception of Northern Ireland, as the trial will not take place in this location. The trial’s proposed consent model formed a key focus of each group. There was strong support for potential trial participants to have a choice of consent method (self-directed online consent or consent via nurse telephone or video call interview). The trial procedures were amended in light of the advice from these groups to offer this choice within the reply form. The use of patient data without consent (to invite patients to join the study) formed a focus of the group discussions at 5 of the meetings. There was broad support for this process to enable the study to recruit the large number of participants required.

The trial has convened the ASCEND PLUS Public Advisory Group (ASCEND PAG), a diverse group of patients and public, to input into the whole life-cycle of the trial. Members were recruited from the existing Nuffield Department of Population Health public advisory panel and the focus groups described above. The ASCEND PAG give feedback, advice and opinions across different aspects of the trial including recruitment materials, participant questionnaires, website development, strategies to maintain participant adherence and engagement, and dissemination of the trial results. The first meeting was held on 6 September 2021. Group members have subsequently provided input into all the patient-facing trial documents. As a result of feedback from the ASCEND PAG and the focus groups, the material was divided into three leaflets; an initial information leaflet to be sent out with the invitation letter and then a full participant information leaflet and a separate data protection leaflet, which are to be sent to individuals who express an interest in the trial. Text and content change recommendations from ASCEND PAG members were implemented throughout, unless these were inconsistent with the study processes.

This has resulted in documents which are easier to understand and more inclusive. For example, for the invitation letter, ASCEND PAG members edited the transparency notice wording to plain English and added the text box, ‘If you would like this information in a non-English language or other format, such as large print, please contact us’ to the start of the invitation letter. In other places, the ASCEND PAG requested a change to the order of the information presented. For example in the participant information leaflet the section, ‘Will taking part affect my medical insurance or travelling?’ was moved earlier in the document.

The ASCEND PAG also co-developed the consent animation, which is part of the self-directed online consent process. First they contributed to the development of the script and then provided feedback on the images used in the storyboard, most of which were implemented. The ASCEND PAG was also instrumental in the selection of which quality of life questionnaires to include in the protocol and have reviewed the draft screening form questions and provided detailed feedback.

To optimise the wording for the letter invites, NHS DigiTrials team in NHS Digital have tested different letter variants with members of the public. Initially, NHS DigiTrials conducted desk research and developed hypotheses on behavioural techniques that would help optimise invitation letters.

NHS DigiTrials analysed the results and focussed on people with Type II Diabetes in order to help inform invites for the ASCEND PLUS trial. For people with this health condition, all experimental letter variants outperformed the control on all reported measures of taking action. As a result of this, the content of the invitation letters for the ASCEND PLUS trial may be amended slightly to align with the optimum performing letters from the testing

LEGAL BASIS FOR COMMON LAW DUTY OF CONFIDENTIALITY
University of Oxford as data controller, are requesting to use NHS Digital data to support a clinical trial called ASCEND PLUS. This agreement is specifically to support the recruitment of a cohort by writing out to individuals who meet the required eligibility criteria.
For the first element of the recruitment process, the legal basis for the identifiable data from NHS Digital to flow to Paragon Customer Communications Ltd for the purpose of University of Oxford inviting them to join the ASCEND PLUS trial is Section 251 approval (NHS Act 2006), approved by the Confidentiality Advisory Group (CAG).

For the second element of the recruitment process, the University of Oxford are relying on consent. Interested potential participants will return a reply form to University of Oxford which will include consent to obtain participant information. Further details on this are detailed within Processing Activities section.


GDPR LEGAL BASIS FOR PROCESSING OF PERSONAL DATA
University of Oxford, as sole Data Controller, are using Article 6(1)(e) "processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller." As part of the application process, the requirement for the data requested has been assessed and NHS Digital is content that it is appropriate, necessary and proportionate for the performance of the task described in the purpose statement and that there is no other reasonable and less intrusive means for the data processor to achieve their purpose.

It is acknowledged that University of Oxford has no direct relationship with the potential research participants up until the time (if they choose to) they respond to the postal invitation by returning the reply form to University of Oxford. At that point, University of Oxford relies on the potential research participant’s consent to
A) obtain participant identifiable information from NHS Digital, and
B) issue the participant with more information regarding the trial and make contact to undergo trial screening and solicit consent to participate in the trial.
Potential participants may experience minor inconvenience of being contacted and invited to take part in the research programme. However, the inconvenience is restricted to the receipt of a letter through the post. Therefore, the likelihood of any adverse impact on the data subjects is low and the severity of any such impact is judged to be minimal.

Additionally (as health data is a special category of Personal Data), University of Oxford is using Article 9(2)(j): Special category data used for “Archiving in the public interest, scientific or historical research or statistical purposes”. If the Study Team demonstrate that oral semaglutide is beneficial in a wide range of patients with type 2 diabetes then the results could change national and international guidelines and more patients could be offered the treatment. This should reduce the risk of complications in patients with diabetes which is in the interest of the public.

INCLUSION AND EXCLUSION CRITERIA FOR INVITATION
The trial will be conducted throughout the UK* and the aim is to recruit a total of 20,000 participants. It is anticipated that about 18,000 of these participants will be recruitment through the collaboration with NHS Digital in England but this may change as the trial recruitment progresses.
Lists of potentially eligible individuals will be generated from electronic searches of centrally held NHS datasets at NHS Digital
*NOTE: NHS Digital will be providing data for England only. The study will be obtaining the related data from the other devolved nations from the relevant organisations.

Invitation inclusion criteria:
• Reside within England
• Age at least 55 years (this is to ensure that the individuals taking part in the trial are at sufficiently high risk of the relevant cardiovascular disease outcomes (e.g. heart attack and stroke).
• Have type 2 diabetes (based on either a relevant diabetes ICD-10 code in their Hospital Episode Statistics data and/or receipt of diabetes treatment in the NHSBSA Medicines data)

Invitation exclusion criteria:
The overall cohort of participant aims to be representative across UK geographical locations, age, and gender. It is possible as part of the creation of each NHS Digital mailout, that specific criteria will be applied to the searches to create the invitee list for that mailout. This may involve increasing the proportion of invitees from particular criteria groups to facilitate balancing the overall cohort make up.
In addition, participants should not have a recorded history of heart attack, stroke, recent cancer or dementia.

Recruitment is expected to begin around December 2022 and take place over 2 years. For the first year of recruitment, approximately half a million patients will be identified and contacted. With an assumed response through to randomisation rate of 2%- , approximately 9,000 patients should be recruited, however this recruitment target is an estimate and may be subject to change. The study team anticipate that a further half million invites will be required in the second year, however, should the study team require a substantial change to the recruitment target or number of invitees, an amendment to this agreement will be required with justification for the change, with appropriate Ethics and CAG approval.

REQUESTING NOT TO TAKE PART IN THE PROGRAMME:
In addition to the National Data Opt-out, members of the public will be able to specifically request not to be contacted for the ASCEND PLUS trial. University of Oxford will promote this information via the dedicated programme website (http://www.ascend-plus-trial.org) and via local media for two weeks prior to letters being issued to enable those who do not wish to receive a letter to declare this. NHS Digital will also promote this information via a dedicated page on its website (http://digital.nhs.uk/ascend-plus). There will also be an option for people to register their request not to take part in ASCEND plus by telephone. In order to provide a single point of contact for all trial related queries, individuals who do not want to be contacted for ASCEND PLUS but are unable to access the study-specific opt-out form on the NHS Digital website will be asked to call the trial Freephone number at the University of Oxford. The trained switchboard team will then record the study specific opt-out on the NHS Digital website on the individuals behalf with no personal data entered into the University of Oxford systems.

NHS Digital will ensure that anyone who has registered for the study specific opt-out will be excluded from the cohort selection and as a result their details will not be on the list passed to Paragon CC for invitations to be sent.

MAILOUTS
Potential participant will be sent one invitation for the ASCEND PLUS trial unless any of the following criteria apply:
1. A national data opt-out has been applied
2. A trial specific opt-out has been applied

Each letter will be mailed with a reply form and the Initial Information Leaflet.

ORGANISATION’S ROLES AND RESPONSIBILITIES:
University of Oxford is the applicant and data controller, who also process data. They are responsible for the programme and overseeing the work carried out to aid recruitment into the programme. They are also responsible for providing the core eligibility criteria for participants.

University of Oxford are responsible for:
1. Generating the invitation request(s) and sending to NHS Digital on a regular basis
2. Monitoring uptake by invitees (i.e. numbers of invitees consenting to participate in the programme)
3. Monitoring scope of the population sending back reply forms
4. Adjusting the selection criteria for invitations to adjust for underrepresentation of target populations taking up the programme, as necessary.
5. Compiling weekly cohorts of interested participants (from the returned reply forms) and securely transferring to NHS Digital for linkage with further participant identifiers and vital status.

NHS Digital are acting as a data processor on behalf of University of Oxford and are responsible for:
1. Applying the inclusion and exclusion criteria to NHS Digital Datasets to generate a list of invitees
2. Feeding back to University of Oxford the number of invitees actually fulfilled out of the total target population, via an aggregate report with small numbers suppressed.
3. Removing objections or opt outs (where a national data opt-out has been registered, as well as special categories of people for whom the data should not be disseminated. The purpose of the restriction is to ensure that patient information that might imply a location is protected.)
4. Sending the list of invitees on to University of Oxford's third-party provider (Paragon Customer Communications Ltd) for generating the invitation letters and mailing these out
5. Agreeing with University of Oxford key processing timelines, including
a. Time from submission to Paragon Customer Communications to mailout
b. Date of the mail outs
c. Daily cut-off times (i.e. after which processing will take place the next day)
d. Time to feedback to University of Oxford the numbers selected
6. Where the number of invitees is less than the population available, invoking a system to choose invitees at random
7. Maintaining a record of people who have returned reply forms to University of Oxford (details of which University of Oxford will supply to NHS Digital securely via Secure Electronic File Transfer (SEFT) and ensuring that these participants are excluded from a second or any further rounds of invitations.
8. Maintaining a record of people invited to the study ensuring they are excluded from any further rounds of invitations.
9. Processing the cohort of interested participants (approximately on a weekly basis) and providing vital status update and updated cohort information securely back to University of Oxford.
10. Processing the cohort of interested participants (on an ad-hoc basis) against the cohort of invitees to produce an aggregate recruitment conversion report, with small numbers suppressed. This report is to be securely shared with University of Oxford.

Paragon Customer Communications are acting as a processor of University of Oxford. Their responsibility is to receive the lists of invitees from NHS Digital and mail out to them accordingly.

A 'return to sender' address will need to be included on the letters. When letters are unable to be delivered to the participant address provided by NHS Digital - they will be returned to Paragon Customer Communications where they will be shredded. Paragon Customer Communications will provide University of Oxford with an aggregate report of number of returned letters.

FUNDING and COMMERCIAL PURPOSE.
The ASCEND PLUS trial was initiated and designed by investigators at the University of Oxford aiming to improve the health of people with type 2 diabetes. The trial is funded through a grant to the University of Oxford from Novo Nordisk, a Danish multinational pharmaceutical company. Additionally, Novo Nordisk - who manufacture the treatment being studied, oral semaglutide - will also be providing the study treatment for the trial. Oral semaglutide is the only oral medication in this class. There are other drugs in this class produced by other companies, however these are given by injection so would not be suitable for the ASCEND PLUS trial design and may be more difficult for patients to take. This is why the study team approached Novo Nordisk rather than any other manufacturer for this study. In the interests of transparency, it is stated here that if the results show that oral semaglutide is beneficial for a wide range of people with diabetes, then this could also increase revenue for the manufacturer Novo Nordisk. Nordisk will have no influence over any of the findings and will have no ability to suppress any outputs produced by the study.

NHS Digital record level data covered by this Data Sharing Agreement will not be shared with any funders and final decision making on processing of the data rests with University of Oxford senior trial management team who are all substantive employees, therefore the funders are not considered Data Controllers or Data Processors on this agreement. The ASCEND PLUS study is sponsored by The University of Oxford. The protocol and procedures have been developed by the investigators at the Clinical Trial Service Unit, University of Oxford with contributions from Novo Nordisk. The Steering Committee determine the scientific objectives of the trial, ensure adequate progress towards those objectives and review any papers prior to publication. As is usual with this type of trial, the Steering Committee has representatives from the funder and also has other experts from other institutions to advise the trial management team. The Steering Group will not have access to or process any NHS Digital record-level Data.

Expected Benefits:

One in 11 people worldwide has diabetes including around 5M people in the UK. Individuals with diabetes have increased risks of adverse cardiovascular health outcomes (such as heart attacks and strokes) which can be fatal or disabling, and of other health problems such as dementia. People with diabetes can also develop complications such as kidney disease, reduced vision, amputation and pain or numbness in their feet (neuropathy). There are several new treatments for diabetes, including oral semaglutide and similar drugs given by injection, but clinical trials have only tested them in selected individuals with very high cardiovascular risks.

ASCEND PLUS is testing oral semaglutide, the first oral Glucagon-Like Peptide-1 Receptor Agonist (GLP-1 RA), in a wide range of people with type 2 diabetes. The main aim is to assess the effects of the treatment on adverse cardiovascular health outcomes but the trial will also assess effects on other complications of diabetes. Oral semaglutide and other GLP-1 RAs control blood sugar, reduce weight and, in high-risk patients, reduce the risk of adverse cardiovascular health outcomes. However, these medications are not widely used, partly because they have not been shown to be beneficial in most patients with type 2 diabetes who don’t already have cardiovascular disease. The trial will also be able to find out the long-term effects of oral semaglutide. There is some evidence that oral semaglutide may protect against dementia and kidney disease but this is not proven.

If ASCEND PLUS shows that oral semaglutide is beneficial in a wide range of patients with type 2 diabetes then the results could change national and international guidelines and more patients could be offered the treatment. This should reduce the risk of complications in patients with diabetes.

The main results are expected in 2028 with long-term follow-up continuing for 20 years after that. The study team aims to present results at scientific conferences and publish in high-impact peer reviewed journals. The study team plan to distribute plain English results co-developed by the ASCEND PAG to surviving study participants by mail and shared with the public via the trial website.

The trial should also generate important methodological insights, tools and resources to benefit future research. These will be share where possible during the trial through presentations, publications and via collaboration with Health Data Research UK and the MRC-NIHR Trials Methodology Research Partnership.

Outputs:

As a result of this recruitment agreement with NHS DigiTrials, the ASCEND plus study team are hoping to recruit to target having posted out adequate numbers of invitations to potentially eligible participants.

Identifiable health data requested from NHS Digital will only be used to identify and invite potential participants. NHS Digital record Level Identifiable data will only be available to University of Oxford after participants have expressed interest and returned the consenting reply form.

Progress against recruitment targets may be reported to the University of Oxford, the funder Novo Nordisk and the Trials Steering Committee in an aggregated and suppressed format.

Key recruitment targets have been set for first year of recruitment and will be closely monitored and reported. NHS DigiTrials forms the main route to recruitment for the trial and the sole method of recruitment in England.

Successful recruitment will enable to trial to test the effects of oral semaglutide in a wide range of people with type diabetes. The main results of the trial are expected in 2028 and should inform National and International guidelines. Examples of these guidelines could include the NICE guideline on “Type 2 diabetes in adults: management”, the American Diabetes Association Standards of Medical Care in Diabetes guidelines and the diabetes guidelines from the European Society of Cardiology and the European Association for the Study of Diabetes. The study team aim to publish the main trail report in a high-impact medical journal with a public summary on the trial website.

Results will also be communicated directly to trial participants.

Processing:

As data controller, the University of Oxford will provide to NHS Digital the core eligibility criteria for those potential participants who will receive the initial invitation letters and information sheets. University of Oxford refine the population that receive these invitations based on first half of a postcode, making adjustments as required to ensure adequate representation of target populations.

NHS Digital would be using a mailing provider (Paragon Customer Communications) to fulfil the communications. Paragon Customer Communications will use Research Ethics Committee (REC)-approved template invitation letters and would add address details and unique barcode references onto the letters prior to mailing it out. All identifiable data provided to Paragon Customer Communications by NHS Digital will be done so under the legal basis of Section 251 support as provided by the Confidentiality Advisory Group (CAG) for this element of the ASCEND PLUS trial recruitment.

Data processing is carried out by employees of NHS Digital who have been appropriately trained in data protection and confidentiality. NHS Digital will access records allowing them to gather the following information needed to determine suitability for invitation to the ASCEND PLUS trial.

COHORT SPECIFICATION:
• University of Oxford are accountable for providing the specification to NHS Digital for each mail out. These specifications will be based on a combination of multiple postcodes, age limits, sex at birth and ethnicities for potential participants. The information they will provide to NHS Digital on each occasion is:

• Lower and upper age limits (55 and over as per the inclusion criteria).
• Male / female percentage split, if required.
• A selection of postcodes (first half of postcode only), if required.
• The number of invitations required for each request.
• The geographical specifications are based on ensuring a broad range of individuals from across England.
• At a pre-determined point, University of Oxford will transfer details of the specification to NHS Digital via SEFT. This will be on a flexible ad-hoc basis, determined by the number of responses received for each request, but could be up to once weekly.

COHORT IDENTIFICATION:
• Using the inclusion and exclusion criteria as specified by University of Oxford, NHS Digital will interrogate the Patient Demographics Service (PDS), NHS Business Services Authority (NHSBSA) Medicines Dispensed in Primary Care and the Hospital Episode Statistics (HES) datasets and extract all those potential participants who meet the criteria within the latest specification as provided by University of Oxford.*
• NHS Digital will then remove any records where a national data opt-out has been registered, as well as special categories of people for whom the data should not be disseminated. The purpose of the restriction is to ensure that patient information that might imply a location is protected.
• The remaining records will have their relevant contact details (Forename, Surname, Address, Postcode) extracted ready for despatch to Paragon , as well as a unique barcode reference for each potential participant.

*NOTE: Although the HES APC and NHSBSA Medicines datasets are being cross-referenced to produce the cohort of potential participants for this agreement, these datasets are not considered as data products on this Data Sharing Agreement as no record level HES APC or NHSBSA Medicines data will be shared with either University of Oxford or Paragon Customer Communications. The processing of HES APC and NHSBSA Medicines data is covered under a separate Data Processing Agreement between NHS Digital and University of Oxford

COHORT DISSEMINATION AND MAILOUT
• Each time NHS Digital create and disseminate an extract, the records will be added to a mailing list cohort dataset, including individual participant IDs.
• Every time a fresh extract is produced, it will be checked to ensure that any records appearing in this mailing list dataset are removed in order to prevent potential participants receiving multiple invitations.
• NHS Digital will provide Paragon Customer Communications with Forename, Surname, Address, Postcode and Unique barcode reference via SEFT.
• Paragon Customer Communications will then mail out to individuals as required.
• All potential participants will receive an invitation letter containing their Name, Address and Postcode and Unique barcode reference,
• Paragon Customer Communications will destroy all data received from NHS Digital 30 days after mailing as instructed by the University of Oxford.

PARTICIPANT EXPRESSION OF INTEREST VIA CONSENT REPLY FORM
The invitation letter is mailed with an enclosed Initial Information Leaflet, a Reply Form and a Freepost envelope. The information includes the Freephone telephone number of the ASCEND PLUS team, the study e-mail address and the study website URL, so that potential participants can find out more about the study at this stage if they chose. If the recipient is potentially interested in taking part, they are asked to complete the Reply Form. This is pre-populated with the person's name and unique barcode reference. The potential participant is asked to add their telephone number and e-mail address and indicate whether they would prefer to engage with the study online or via telephone / video call with a research nurse. They can also add any special requirements such as large print or non-English language. By returning the Reply Form the potential participant is giving permission for the University of Oxford to receive their personal data including receiving their Name, address, postcode, NHS number, date of birth, gender and GP practice details from NHS Digital, so that the study team can complete the screening assessment, and, if they are eligible and consent to the study, inform their GP. Each reply form is checked and logged by the study team. The name and unique identifier will be extracted from the Reply Form using a barcode scanner to reduce errors. Permission to use personal details in order for University of Oxford to make further contact is clearly described on the reply form.

INTERESTED PARTICIPANT COHORT LINKAGE TO ADDITIONAL DATA
On a weekly basis, the University of Oxford will securely provide NHS Digital with the unique identifiers (barcode reference) for all those individuals who have returned their reply form. NHS Digital will use the unique barcode reference to link back to the potential participants full name, address, postcode, NHS Number, date of birth, gender and GP practice details, from the Demographics dataset. These data items will be returned securely to University of Oxford via SEFT.

Personal data for patients who have return the reply form (and therefore given permission for University of Oxford to receive their details in order to do the screening assessment) but then either don’t complete the screening assessment or are not eligible at screening and so don’t provide full informed consent for the trial will be held until the end of recruitment and then destroyed. University of Oxford retain this data until the end of recruitment in case a potential participant changes their mind and decides to attend screening, becomes eligible or has any other queries about the trial. University of Oxford feel this is in line with their permission given by returning the reply form. After recruitment is completed and there is no possibility of them completing the screening assessment and therefore no rationale for University of Oxford to hold their personal data longer.

AGGREGATE RECRUITMENT CONVERSION REPORT
On an ad-hoc basis (up to once a week), NHS Digital will compare the cohort of invitees to the cohort of interested participants (who have returned their reply form to University of Oxford) to produce a report detailing the percentage uptake of participants in relation to the inclusion and exclusion criteria provided by University of Oxford. This report will only contain aggregate data with small numbers suppressed and is represented within this Data Sharing Agreement under section 3B (Additional Data Access Requested) as “Customer – Data Quality Report – Aggregate (Communications)”

The permitted territory of use for data provided by NHS Digital for this agreement is England and Wales.

Potential participants will receive one postal invitation for the ASCEND PLUS study; at present there will be no further attempts to remind or re-approach patients who do not respond. The study team may consider sending out an additional reminder in future, and if required, will submit an amendment to this agreement and seek relevant ethical approval. It is possible that patients who move from England to Wales or Scotland during the recruitment period, may receive a further invitation from a search conducted by other data custodians in those regions but this is likely to only affect a small number of individuals and an explanation would be provided.

An aggregate report with small numbers supressed (as per the HES Analysis Guide) containing information about gender, age and geographic demographics of the mailing cohort will be provided to University of Oxford from NHS Digital for the purposes of confirming that inclusion and exclusion criteria have been met for each mailing. This report will also contain the total number of people who received the mail out and the number of people removed from the cohort prior to mailing based on trial-specific opt out, national data opt out and special categories of people for whom the data should not be disseminated, such as those on a witness protection programme.

The data from NHS Digital will not be used for any other purpose other than that outlined in this Agreement. The data from NHS Digital will not be linked to any other data other than those outlined in this Agreement.

HES and ECDS DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, data processors must make sure that:
• National-level figures only may be presented unrounded, without small number suppression
• cell values from 1 to 7 (inclusive) are suppressed at a sub-national level to prevent possible identification of individuals from small counts within the table.
• Zeros (0) do not need to be suppressed.
• All other counts will be rounded to the nearest 5.
Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

SYMPLIFY Trial Communications via NHS DigiTrials request — DARS-NIC-661736-Y2Q9R

Opt outs honoured: (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic, Commercial)

Sensitive: Sensitive

When:DSA runs 2022-11 – 2023-11

Access method: One-Off

Data-controller type: GRAIL BIO UK LTD, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Mailing - Cohort - Non-aggregate (Comms & Recruitment)

Type of data: Identifiable

Expected Benefits:

Keeping participants informed of results of trials they are involved with is a high priority according to the Health Research Authority and is best practice. The communications will also provide an opportunity to inform participants regarding the planned sharing of data with USA so ensure transparency.


GRAIL Bio UK Ltd and University of Oxford hope that by communicating with participants via this mailout, that they will help to keep them engaged with the work of SYMPLIFY and make it clear that participants are partners in the research.

The letters will also provide an opportunity to remind participants that information about how their data are handled is available on the trial website.

Outputs:

The key immediate output will be a mailing delivered to the participants of the SYMPLIFY trial.

The ultimate output of this data processing will be participants being mailed a letter to inform them of an update to the SYMPLIFY trial and to remind them of the flow of data being sent to the USA. No other outputs are expected (such as results, presentations or reports) as a result of this Data Sharing Agreement. The SYMPLIFY trial has a separate data sharing agreement (DARS-NIC-604851-W0M3S) for outcomes data relating to the study, which should generate outputs such as results, presentations or reports.

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e: employees, agents and contractors of the Data Recipient who may have access to that data).

Proposed Methodology::

>Cohort:
1. GRAIL Bio UK Ltd will create a list of participant Study IDs (excluding anyone GRAIL Bio UK Ltd knows to have withdrawn consent for all forms of follow-up), NHS Number and Date of Birth and provide this securely to NHS Digital using Secure Electronic File Transfer (SEFT)
2. The cohort is validated using an automated pipeline to check for errors.
3a. If the file has more than 2% errors, the file is sent back from NHS Digital to GRAIL Bio UK via SEFT to be reviewed and corrected.
3b. If the file has less than 2% errors, this will be accepted by NHS Digital and processed using an automated pipeline to check for vital status and addresses.

>Vital Status Check
NHS Digital will perform a vital status check and remove any additional participants known to have died (whom GRAIL Bio UK Ltd may not have been aware of due to the intermittent nature of the vital status update that SYMPLIFY receives).

>Data Out
After performing the vital status check, NHS Digital will then retrieve the latest address and postcode for the remaining participants:
• A file containing participant's Title, Forename, Surname, Address and Postcode will be sent to NHS Digital's third party mail house, Datagraphic Ltd from NHS Digital via SEFT.
• Datagraphic Ltd will then mail out to individuals using an ethically approved letter provided by GRAIL Bio UK Ltd.
• All participants will receive a letter containing their Title, Name, Address and Postcode.
• Datagraphic Ltd will destroy all data received from NHS Digital within 20 working days after mailing as instructed by NHS Digital.

NOTE: For this agreement, no data will be returned to GRAIL Bio UK Ltd. GRAIL Bio UK Ltd do not store participant address details for the SYMPLIFY study therefore do not require for these to be returned. GRAIL Bio UK Ltd obtain outcomes data (including Civil Registration - Deaths data) via a separate agreement (DARS-NIC-604851-W0M3S) and therefore do not require vital status information to be returned under this agreement.

> Return to sender and follow up queries
The letter will provide details for how to contact the SYMPLIFY team at University of Oxford for follow up enquiries. A 'return to sender' address will need to be included on the letters, which will be Datagraphic Ltd. When the returned item is received, Datagraphic Ltd will carry out an automatic reconciliation using a 2D Mailcare barcode contained within the address window, which identifies the mail date and originating client. The unopened letter will be scanned, and the return recorded. The database is updated with a ‘reason code’ for the undelivered mail items, alongside the original address fields, and the piece of mail is then securely destroyed.

>Opt Outs
The mailing(s) will include information for participants on how to opt out of SYMPLIFY should they wish. This information will also be on the trial website and included in the privacy notice. Participants will be able to write or e-mail their intention to the SYMPLIFY team at University of Oxford who will update their records accordingly.

Any such participants would be removed from the list of participant IDs that GRAIL Bio UK Ltd send to NHS Digital for any subsequent mailing(s) (along with those who have died, withdrawn consent for follow-up or elected to receive communications electronically). v

PANORAMIC: Platform Adaptive trial of NOvel antiviRals for eArly treatMent of covid-19 In the Community — DARS-NIC-605115-L0W3V

Opt outs honoured: unknowNo (Excuses: Statutory exemption to flow confidential data without consent, Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 - s261(5)(d); Health and Social Care Act 2012 – s261(2)(c), CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(5)(d); Health and Social Care Act 2012 – s261(2)(c), CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(5)(d), CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(2)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-12 – 2022-03 2022.12 — 2025.03.

Access method: Ongoing, System Access, One-Off
(System access exclusively means data was not disseminated, but was accessed under supervision on NHS Digital's systems)

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. COVID-19 Access to Summary Care Records
  3. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Critical Care
  6. Medicines dispensed in Primary Care (NHSBSA data)
  7. Emergency Care Data Set (ECDS)
  8. Hospital Episode Statistics Outpatients
  9. Uncurated Low Latency Hospital Data Sets - Admitted Patient Care
  10. Uncurated Low Latency Hospital Data Sets - Critical Care
  11. Civil Registrations of Death
  12. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Hospital Episode Statistics Critical Care (HES Critical Care)
  15. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant, Identifiable (note: this information not disclosed for TRE projects )

Objectives:

Despite high uptake of vaccination against COVID-19, the disease remains prevalent in the UK and in many countries around the world, with many patients continuing to require hospital admission. Early treatment with antiviral agents may prevent progression to the later phase of COVID-19. Therefore, there is an urgent need to identify treatments for COVID-19 for use in the community early on in the illness that prevent the need for hospital admission and improves time to recovery. It is therefore vital that the University of Oxford use this opportunity to accelerate enrolment into COVID-19 therapeutics trials.

The PANORAMIC (Platform Adaptive trial of NOvel antiviRals for eArly treatMent of covid-19 In the Community) trial is the only national priority clinical trial evaluating potential novel antivirals for COVID-19 in the primary care setting, endorsed by the Chief Medical Officers (CMOs) of all four devolved nations. The primary aim is to determine the effectiveness of selected antiviral agents in preventing hospitalisation and/or death in higher-risk patients with a confirmed positive SARS-CoV-2 PCR test result.

PANORAMIC is:
• Recruiting across the whole UK* - anyone age 18** or over who match the participant criteria can participate, regardless of location.
• For both recruiters and patients it is a simple process to complete enrolment on to the trial.
• Obtaining consent, checking eligibility, issuing study medication and materials, and follow-up is managed remotely through a central facility at the University of Oxford.

*PLEASE NOTE - The University of Oxford is obtaining data from NHS Digital related to residents in England only.
** PLEASE NOTE - The first treatment included in the PANORAMIC trial has conditional licensing for adults and therefore the study team are unable to include under children at this stage. Depending on the advice from the Antiviral Taskforce regarding future treatment arms, and their licensing conditions, the inclusion criteria may be amended in future to include under 18’s.

Primary objective -
To determine whether antiviral treatment in the community safely reduces non-elective hospitalisations/deaths in higher risk, symptomatic patients with confirmed COVID-19

Secondary objectives - To explore whether trial treatment reduces:
1) Time to recovery (defined as the first instance that a participant report of feeling recovered from the illness)
2) Participant reported illness severity, reported by daily rating of how well participant feels, enabling identification of sustained recovery.
3) Duration of severe symptoms and symptom recurrence
4) Contacts with the health services
5) New infections in household
6) To investigate the safety of antiviral agents
7) Longer term effects
8) Cost effectiveness

The study team are requesting the Covid-19 UK Non-hospital Antigen Testing Results (pillar 2) dataset in order to identify and successfully recruit potential patients into the trial, early on in their stage of COVID-19 disease. A positive PCR test is essential for inclusion into the trial. The positive PCR test result will be participant reported prior to randomisation, and confirmation of the positive result will be sought at a later date via the Pillar 2 dataset.

The University of Oxford would like to receive names and contact details (including preferably a telephone number and email address) of people who have received a positive COVID-19 swab result from the Pillar 2 testing system. The trial team, based at the University of Oxford, will then contact these potential participants, inform them about the trial and if they are happy, go on to screen and consent them into the PANORAMIC trial. Daily, the trial team would like to receive identifiable record-level data on a random cohort (up to 500) of people aged 18+.

The trial already has a centre set up and operating remotely at the University of Oxford to manage this recruitment in a timely manner. Management of the recruitment to the trial will be undertaken by substantive employees of the University of Oxford who have been appropriately trained in data protection and confidentiality.

The question of whether ‘cold calling’ is appropriate has been considered for this application. As time is of the essence for recruitment into PANORAMIC, the telephone is the most efficient and quickest means to ensure direct contact with the individual, who can answer questions instantly over a call. The study team would also like to use the Short Messaging Service (SMS) and email option for invitation, for those patients who they cannot reach via telephone or those who require a follow-up information. During the calls, clear explanation will be given to individual about how the trial has been able to contact them and what to do if they do not wish to be contacted again (i.e. registering a National Data Opt-out). The trial team will apply the Telephone Preference Service. The trial team will also ensure the required comorbidities are discussed early on in the calls so as to not to get the individual’s hopes up if they are not in fact eligible for the trial.

Other considerations that have been taken into account in relation to contacting individuals:
• The data relating to positive COVID-19 tests is sent to NHS Digital at the same time that it is sent to the Business Services Authority, the latter process triggering the SMS to the individual informing them of their result. It then takes around four hours for the Covid-19 UK Non-hospital Antigen Testing Results (pillar 2) dataset within NHS Digital to be updated with this information. Given that this information then needs to be extracted from the dataset at some point in the next 24 hours, then used by the trial team to make contact with the individual, the risk of the individual being informed of their test result by the trial team before they have read their SMS is small. However, the trial team should have a suitable script prepared to deal with this slim possibility.
• The chances of people having multiple positive COVID-19 test results are rare, and rarer still is the likelihood that they will be one of the 500 people extracted from the thousands of daily test results to be sent to the trial team on more than one occasion. Therefore, the risk of an individual being contacted twice for recruitment into PANORAMIC is extremely low.
• NHS Digital recognises that there are likely to be more requests of this nature in future and therefore, if multiple trial require extracts of people to contact, suitable controls need to be in place within the extract process to ensure that individuals are not getting contacted for recruitment into trials more than is reasonably expected.

Patient and Public Involvement & Engagement (PPIE)
The Panoramic trial has had extensive PPIE engagement to support development of trial materials and processes and to discuss the plans for efficient and safe use of patient data and has plans for significant engagement throughout the period of the study.

The main study PPIE group includes members of five different cultural and faith communities and representatives of those with learning disabilities. They have had three meetings prior to this application, focussing on acceptability of trial processes and optimising patient-facing materials including redesigning the Pictorial Patient Information Sheet (PIS) and co-developing a summary front page for this document. They have reviewed the online trial interface and instructions for participants. This group will continue to meet at least every month when the trial commences recruitment.

The study team have begun to convene additional PPIE groups in Scotland, Northern Ireland and Wales to focus on nation-specific recruitment and dissemination issues and will work with individual cultural and community leaders to ensure inclusion of the most diverse range of participants possible.

Request to use SCR for consented participants:

The PANORAMIC trial team are requesting to access the Summary Care Record (SCR) for patients recruited into the trial for the purposes of ensuring timely prescribing and safe patient care. SCR access will be essential to successfully recruit participants in the very restrictive timeframe of five days since symptom onset. For the first treatment arm, the trial is run remotely, therefore removing the need for participants to be near to a GP practice. Screening and contact with the trial team is all completed online. The trial team are requesting access to Summary Care Records as part of this application as it will not be possible within the five day window of recruitment from symptom onset, for the trial team to request such information regarding safe prescribing from the participant’s GP.

The PANORAMIC trial team therefore to seek permission for the clinical trial team, a group of dedicated doctors and nurses who are fully qualified, study-trained, accredited and registered, to review consenting patients’ Summary Care Records, in order to be able to confirm key information obtained from the patient relevant to safe patient care in the trial. Only nurses and doctors who are registered and accredited with the General Medical Council of the UK or the Nursing and Midwifery Council of the UK who are clinical members of the PANORAMIC study team would review the Summary Care Record for information relevant to safe prescribing and participant care.

The Summary Care Record will be used as a timely, second check regarding medication, allergy, and co-morbidities information to support reconciliation, to ensure safe prescribing. These are all elements of a patient’s SCR with additional information which is a subset of their wider GP record. This access provides an immediate available information source to meet the need to support safe prescribing in a proportionate and timely way. In addition, the Summary Care Record will provide a further safety check, in that access to it will facilitate the opportunity for double-checking participants’ NHS Number and GP practice.

There is a five-day window from symptom onset to enrolment into the trial and so SCR access is critical to confirm eligibility within this very limited time-period.

Access is sought only for those people who have screened eligible to be part of the trial, and who have already signed informed consent for participation in the study and for the trial to access their clinical records. All potential participants are asked specifically for permission for the trial team to access their medical records and have the opportunity to decline this access. In addition, they will be asked specifically and separately for permission about access to their Summary Care Record. For a patient who has provided consent to join the trial and for their SCR to be accessed, the data will be accessed by a clinician to support safe prescribing decisions immediately prior to prescribing medications. A Summary Care Record will only ever be accessed on one occasion for each individual participant/

Access to SCR is required for the period that the trial is recruiting - currently this is December 2021 until Sept 2023.

This request for SCR access for PANORAMIC, along with the similar request for the sisters trial, PRINCIPLE, together form a first-of-type access request and as an interim position it is included in the Data Sharing Agreement. This is a holding position whilst considerations are undertaken to agree whether to offer this as a service more widely to clinical trials for patient safety purposes. This allows time for an appropriate access and approval process to be developed in future, but in the meantime ensures that SCR access is recognised within the research data access process alongside the normal direct care process for access to SCR.

FOLLOW UP DATA:
In this agreement, the University of Oxford are requesting access to record-level data from the following data sets in order to receive follow up data on trial participants:

> Hospital Episode Statistics (HES) Admitted Patient Care (APC)
>HES Critical Care (CC)
> Civil Registration (Deaths) data set
> Medicines dispensed in Primary Care (NHSBSA data)

The trial follows up all consented participants for 28 days and then at three and six months following randomisation.

Due to the high rate of recruitment, the Data Safety Monitoring Committee review the trial data weekly and can ask for recruitment into a trial arm to be stopped immediately. Therefore trial data needs to be made available as soon as possible so that the team can quickly issue a press statement and publication of results if required to do so. There is a need to capture the required data in a more timely and efficient manner via monthly extracts from NHS Digital.

HES APC, HES Critical Care, and Civil Registration of Deaths datasets will be essential to collect the primary outcome, which relates to all-cause hospitalisation/death.

LEGAL BASIS FOR COMMON LAW DUTY OF CONFIDENTIALITY
The lawful basis for the release and use of the confidential data (Covid-19 UK Non-hospital Antigen Testing Results (pillar 2) and Summary Care Record (SCR)) being shared under this version of the agreement is Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations entitled to process this under COPI for COVID-19 purposes. The only permitted activities under this Data Sharing Agreement (DSA) are for COVID-19 purposes and within bounds of Reg 3(2) COPI. Reg 3 (2) COPI states that: "2) For the purposes of this regulation, “processing” includes any operations, or set of operations set out in regulation 2(2) which are undertaken for the purposes set out in paragraph (1)." The research relates to the monitoring and managing of COVID-19 and would therefore be covered by Reg 3(1)(d) of COPI.

Consent is in place to allow the pseudonymised follow-up data to be provided to the study team from NHS Digital and details of the trial and expected data flows are explained on the latest version of Patient Information Sheet which will be hosted on the trial website: https://www.panoramictrial.org/ (currently in development).

Only the study team at the University of Oxford will access the requested data. No other organisations are involved in the processing or storage of NHS Digital record level data. NHS Digital Record level data will not leave the UK.

LEGAL BASIS FOR PROCESSING DATA
The University of Oxford, as the Data Controller who is also processing the data will process Personal data under GDPR Article 6 (1) (e) - Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. As a higher education establishment, the University conduct research to improve health care and service and the data requested is necessary for the performance of a task carried out in the public interest.

Additionally, under GDPR Article 9(2)(j) processing of Special Category Personal Data (of which Health data is one) is necessary for archiving for research purposes. Data minimisation process is being followed and only data that is required specifically for the purposes of this study has been requested, to protect the rights of the data subjects.
Article 9(2)(h) is additionally being used to cover the processing of SCR specifically: ‘processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services’ as it is being used as a timely, second check regarding medication, allergy, and co-morbidities information to support reconciliation, to ensure safe prescribing.

The PANORAMIC trial is funded by the National Institute of Health Research (NIHR), but do not make any decisions determining the purposes and means of the processing of data or the study purpose and methodology, and are therefore not considered a Data Controller. Additionally, the NIHR will not have access to any NHS Digital record level data and are therefore not considered a Data Processor.

A collaborator agreement is in place between University of Oxford and the institutions listed on the protocol for this clinical trial. The study team have confirmed that the institutions listed within the protocol will not have access to NHS Digital record level data and therefore, in line with NHS Digital’s DARS standards, does not consider these other institutions as a joint Data Controller or Data Processor for this agreement.

Expected Benefits:

The NIHR has commissioned a research consortium to deliver a complex community-based clinical trial platform for NOVEL antiviral candidates, to enable an evidence-based approach to identify whether such treatments are effective in treating COVID-19. PANORAMIC hopes to uniquely expand the evidence about the effectiveness of novel antivirals to benefit COVID patients in the NHS and worldwide.

Antivirals, if deployed rapidly, have the potential to break chains of transmission, reduce symptoms and hospitalisations, all of which will protect the vital gains of the vaccination programme, particularly if new variants of concern emerge which reduce vaccine efficacy. The emergence of the SARS-CoV2 virus has had a profound impact on the UK population, especially in relation to those more at risk groups. It is vital to ensure that a significant rise in infections and spread of the virus in the population is controlled as far as possible. The development of antiviral treatments is integral to a longer-term response to COVID-19 and will enhance pandemic preparedness in the years ahead. In addition to clinical data showing reductions in viral load and time to alleviation of symptoms or illness duration, other data are of great importance to Antiviral Taskforce (ATF) and DHSC in terms of national policy. These include data on reducing hospitalisations and mortality as well as data on reducing secondary transmission in households.

The primary focus of the trial will be early treatment of confirmed (PCR positive) SARS-CoV2 infections in high-risk individuals to prevent hospitalisation, reduce symptoms, and speed up recovery, thus reducing clinical impact of the virus on individuals and the strain on NHS hospitals. Individuals where the vaccine is less effective, such as the immunosuppressed or the elderly are key targets for this type of treatment. Additionally, antivirals may be particularly useful in managing outbreaks, working alongside other public health interventions, to prevent infection in known contacts of positive cases and to offer protection to those who are not vaccinated or do not respond to vaccination.

Outputs:

All outputs will be aggregated with small number suppression applied as per the HES analysis guide.

The PANORAMIC trial will recruit to target much quicker than using current methods if the team can receive the requested NHS Digital identifiable data. The statistical analysis team aim to receive follow up data in a more timely manner, therefore answering the COVID-19 treatment in the community question more quickly with the aim of preventing COVID-19 patients being hospitalised so in turn reducing NHS burden.

The trial team intends to disseminate results via media channels: pre-prints/publications in peer-reviewed journals such as the New England Journal of Medicine (NEJM); press releases in local and national newspapers; BBC news coverage; Department of Health and Social Care (DHSC) press briefings; DHSC Social media updates; via the Antiviral Taskforce webpage; Twitter and Facebook University of Oxford accounts. Results will be disseminated to trial participants via the trial website, supported by the University of Oxford. The study team will provide regular updates to the NIHR Evaluation, Trials and Studies Coordinating Centre.

From the start of the trial (beginning of December 2021), the data will be reviewed on a weekly basis to determine whether the antiviral treatment arms meet the superiority/futility criteria. The trial aims to recruit participants within 4 months (by the middle of April 2022) to identify whether the initial antiviral agent is effective in treating COVID-19. The first interim analysis is scheduled for the start of January 2022, after 1,000 study participants have been randomised in the trial.

The study team will update participants by signposting them from their ‘end of trial letter’ to the trial website for the latest results and information. Due to the limited resources of the study trial team and the potential number of study participants involved, the study trial team have made the decision that distributing newsletters or email updates would be difficult to manage at such a scale. The study trial team believe that signposting to the website also ensures that the most up to date information is always available to participants, as newsletters can soon become outdated due to the fast-paced and evolving nature of this platform trial. The study team are also considering the use of video/audio updates and other formats to the website depending on capacity.

The trial is of national and international relevance during this pandemic.

Processing:

Covid-19 UK Non-hospital Antigen Testing Results (pillar 2) - The processing of the data will be as follows:

• On a daily basis (seven days a week) NHS Digital will interrogate the Pillar 2 data and extract up to 500 individuals at random who are aged 18 or over who have received a positive COVID-19 test result in the previous 24 hours.
• The individuals will be residents of England only.
• Filters will be applied to remove patients who have registered a National Data Opt Out, as well as special categories of people for whom the data should not be disseminated. The purpose of the restriction is to ensure that patient information that might imply a location is protected.
• Individuals who have signed up for the Telephone Preference Service will not be contacted via Telephone.
• The flow from NHS Digital to University of Oxford will be automated via a Secure Electronic File Transfer service called SEFT.
• University of Oxford will use the data provided to make outbound contact to ask if eligible individuals would be interested in being recruited into the trial.
• The study aims to recruit 200 people into the trial per day, 1000 participants before January 2022.
• The number of individual contact details supplied by NHS Digital to University of Oxford will be reviewed once the take-up rate is better understood.
• On an interim basis, the PANORAMIC trial will use the Pillar 2 Data flow already provided under DARS-NIC-411161-G4K7X-v5 (PRINCIPLE trial) - noting that this data is provided to the same study team at the University of Oxford. Once a separate data flow is in place specifically for PANORAMIC, this permission will be revoked.

The trial team at University of Oxford will hold the data securely adhering to all Information Governance (IG) Policies in the Department. The trial team will call these contacts to inform them of the trial, screen, consent and randomise them.

It will take 5,319 patients per arm to answer the question for the drug of that arm. The trial has pre-defined futility and superiority (failure and success) criteria, which will determine when it closes and whether it reaches the sample size. The trial will involve Usual Care and 2-3 antiviral agent arms.

Participants will be randomised using a secure, fully validated and compliant web-based randomisation system. Once deemed eligible, the medically qualified clinician or research nurse from the central clinical team or Hub will randomise the participant. Participants will be randomised to one study arm using equal allocation ratios corresponding to the number of eligible arms in the trial. For instance, if there are two active interventions (A & B), the allocation ratio will be 1:1:1 for Usual Care, active A, active B (respectively), such that 33% of participants are randomised to Usual Care. If there are 3 active interventions, the allocation ratio will be 1:1:1:1, such that 25% of participants are randomised to Usual Care. Patients must be eligible for at least two arms (Usual Care and at least one novel antiviral intervention). Stratification will be by age and vaccination status. The randomisation database will automatically alert the relevant Investigational Medicinal Product (IMP) distributor and the participant, trial team and legal representative if applicable will be notified electronically of the treatment allocation. If the participant does not have an email address, they will be notified by telephone.

Statistical data analysis will be carried out via University of Oxford owned devices connected to the University of Oxford network either directly in person or remotely, using an appropriate statistical package. To remotely access the devices requires a secure 2-factor authenticator (VPN) and users are then able to securely access the secure server on the University’s IT framework. All data analysis will be conducted within the confines of the University’s secure server, and will not be downloaded to remote devices for storage or processing.

Berry Consultancy in the USA will also be undertaking data analysis, however this will be performed using non-NHS Digital data. No NHS Digital data will be processed by any organisation not already stated in this agreement, nor will any NHS Digital data be sent, stored or processed outside of the UK.

The identifiable data received from NHS Digital will be deleted on a weekly basis as the trial team will no longer require it.

• Summary Care Record (SCR) for consented participants:

Once participants are recruited into PANORAMIC, the trial team will access their Summary Care Record. This will be through ‘SCR Core’ or ‘SCR Additional Information’, depending on what is available for each participant.

SCR Core includes:
• current medication
• allergies and details of any previous bad reactions to medicines
• the name, address, date of birth and NHS number of the patient

SCR Addition Information includes:
• significant medical history (past and present)
• reason for medication
• anticipatory care information (such as information about the management of long term conditions)
• end of life care information (from the SCCI1580 national dataset)
• immunisations.

Data is minimised as access is only for the consented cohort for the trial.
The Clinical trial team will use SCR and build on best practice by identifying the patient’s NHS Number after a demographic search and using this to confirm the patient’s identity as well as ensuring the NHS Number is noted on any paperwork being returned to the patient’s practice regarding their participation in the trial.

The SCR Team at NHS Digital will use a position for the trial team which allows access to SCR via SCRa/Spine Portal and does not include emergency access. SCR access is time limited for the duration of the trial; this will be achieved with the use of roles to be applied to smartcards to be time limited for the duration of the trial.

The trial team will not retain information obtained from SCR once the eligibility checks have been done: they will record that the SCR has been accessed, and the audit trail within the SCR will also log who has accessed the record.

• Follow up data (HES APC, HES Critical Care, Medicines dispensed in Primary Care data and Civil Registration of Deaths):

On a monthly basis the trial team will send to NHS Digital the relevant data items for those cohort members who have hit the 28 day follow up window.

The University of Oxford will provide NHS Digital with the following information via Secure Electronic File Transfer (SEFT) for consented participants: Study ID, NHS Number, Date of Birth, trial recruitment date, withdrawal date (if applicable).

NHS Digital will link the cohort members to the aforementioned datasets and return the record-level pseudonymised outputs to the Study team at the University of Oxford via SEFT.

NHS Digital Record Level Data will not be linked to any other datasets.

HES and ECDS DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, data processors must make sure that:
• National-level figures only may be presented unrounded, without small number suppression
• cell values from 1 to 7 (inclusive) are suppressed at a sub-national level to prevent possible identification of individuals from small counts within the table.
• Zeros (0) do not need to be suppressed.
• All other counts will be rounded to the nearest 5.
Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

MR415 COHORT STUDY OF CANCER INCIDENCE AND MORTALITY AMONGST WOMEN TREATED FOR SUPERTILITY — DARS-NIC-147910-HHGGZ

Opt outs honoured:

Legal basis: , Health and Social Care Act 2012 - s261(2)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2021-12 – 2022-12

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Personal Demographics Service
  2. Cancer Registration Data
  3. Civil Registrations of Death
  4. Demographics

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

This Data Sharing Agreement permits the retention of the data provided under previous iterations of this Agreement but no further processing, for an interim period. This is a pragmatic approach to provide an active Agreement whilst enabling the University of Oxford to complete the necessary actions to enable a subsequent application to extend the Agreement meeting all applicable data sharing standards as published in NHS Digital’s website (see: https://digital.nhs.uk/services/data-access-request-service-dars/dars-guidance).

The data supplied by NHS Digital to Childhood Cancer Research Group will be used only for the approved Medical Research Project.

Yielded Benefits:

In any future application, the applicant will be required to provide details of the actual benefits achieved as a result of the study.

Expected Benefits:

This Agreement permits the secure retention of the data only and no other processing.

In any future application, the applicant will be required to provide details of the expected benefits resulting from the study.

Outputs:

This Agreement permits the secure retention of the data only and no other processing.

No new outputs will be produced under this Data Sharing Agreement.

In any future application, the applicant will be required to provide details of the outputs that were produced and disseminated by the study as well as details of any future outputs planned.

Processing:

Under this Agreement, the data may be securely stored but not otherwise processed. No new data will be provided by NHS Digital under this Agreement.

Astrazeneca/Oxford - Re-use of existing data for data validation exercise — DARS-NIC-480562-G9R5X

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: Yes (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2021-07 – 2021-09

Access method: One-Off

Data-controller type: ASTRAZENECA UK LIMITED, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. COVID-19 Hospitalization in England Surveillance System
  2. COVID-19 Second Generation Surveillance System
  3. Secondary Uses Service Payment By Results Accident & Emergency
  4. Secondary Uses Service Payment By Results Episodes
  5. Secondary Uses Service Payment By Results Outpatients
  6. Secondary Uses Service Payment By Results Spells
  7. COVID-19 Second Generation Surveillance System (SGSS)
  8. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford and AstraZeneca wish to use data currently held by University of Oxford (disseminated under DARS-NIC-381683) to do initial internal development work ahead of receiving a fresh data extract under DARS- NIC-459114. The work will support the preparatory work for the data management of the extract building models and internally validating them against other work that the University of Oxford are involved in / are in the public domain.

DATA CONTROLLERS AND PROCESSORS
The University of Oxford (Oxford's Royal College of GPs (RCGP) Research and Surveillance Centre (RSC)) are Joint Data Controllers with AstraZeneca Limited UK (also known as AstraZeneca Global). The data will only be processed by University of Oxford's Royal College of GPs (RCGP) Research and Surveillance Centre (RSC) and by Momentum Data. University of Oxford have subcontracted a part of the analysis to Momentum Data who will be acting as data processors on the instructions from University of Oxford and AstraZeneca UK Limited.

LEGAL BASIS
The lawful basis for processing data under GDPR has been reviewed and been assessed as acceptable. The University of Oxford process data under Article 6(1)(e): "processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller" as they are a Public Authority.

AstraZeneca UK Limited process data under Article 6(1)(f): “Legitimate interests: the processing is necessary for your legitimate interests or the legitimate interests of a third party, unless there is a good reason to protect the individual’s personal data which overrides those legitimate interests. (This cannot apply if you are a public authority processing data to perform your official tasks.)”

Additionally, the University of Oxford and AstraZeneca UK Limited process the Special Category Health Data under Article 9(2)(j): "processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject" as the data are required for research purposes in the public interest.

Expected Benefits:

The benefits will be internally initially to ensure that the data managers are ready to work on the extracted data for the Vaccination effectiveness studies as soon as they are available thus enabling the results of the study to be published more rapidly.

Outputs:

No outputs are expected other than preparing databases for the receipt of the extracted data once available via the main research agreements.

Processing:

Date will only be accessed by staff substantively employed by University of Oxford who are a data controller and processor and Momentum Data, who are a data processor. No data will leave the University of Oxford.

The data will be controlled and processed by a group of staff who are all substantive employees of the University of Oxford. Additionally, for the purpose of this study, given the tight turnaround and the urgency in providing these analyses in the interest of public health, University of Oxford have subcontracted a part of the analysis to Momentum Data who will solely be acting as data processors on the instructions from University of Oxford and AstraZeneca (joint data controllers). Analysts from Momentum Data will first have to complete the IG training in order to get access to the secure environment at the University of Oxford. Although acting as data processors, all the analysis and processing will take place within the secure environment at University of Oxford. (ORCHID)

University of Oxford staff are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Language Query (SQL) developers, RCGP RSC practice liaison officers, a project manager and a head of department. The team work from secure workstations or secure laptops with encrypted drives within the group’s secure network.

Data will only be accessed by individuals within the RSC who have authorisation. The authorisation process includes:
(1) Contractual requirement to follow IG principles;
(2) Using the email registered with Human Resources to complete IG training and to return the certificate;
(3) Staff email is authorised by the IT department for one year to access the secure network and staff computers are configured to allow this;
(4) At any point the project managers or Head can have access to the secure network turned off.

Momentum will be data processors, however they will only access data within a secure environment via a secure client and can’t download data.

University of Oxford- National Core Studies Can phenotypes developed from enhanced remote primary care assessment of COVID-19 be used to identify a cohort of community cases, and enable comparison of recovered and long COVID? — DARS-NIC-431881-N8B0N

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-03 – 2021-08

Access method: Ongoing

Data-controller type: IMPERIAL COLLEGE LONDON, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. COVID-19 Hospitalization in England Surveillance System
  3. COVID-19 Second Generation Surveillance System
  4. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  5. Diagnostic Imaging Dataset
  6. Emergency Care Data Set (ECDS)
  7. Mental Health Services Data Set
  8. Secondary Uses Service Payment By Results Accident & Emergency
  9. Secondary Uses Service Payment By Results Episodes
  10. Secondary Uses Service Payment By Results Outpatients
  11. Secondary Uses Service Payment By Results Spells
  12. Civil Registrations of Death - Secondary Care Cut
  13. COVID-19 Second Generation Surveillance System (SGSS)
  14. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  15. Diagnostic Imaging Data Set (DID)
  16. Mental Health Services Data Set (MHSDS)
  17. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Type of data: Anonymised - ICO Code Compliant

Objectives:

Since the outbreak of COVID-19 in Wuhan, China, and the subsequent pandemic, Public Health England (PHE) has commissioned the Oxford- RCGP RSC, based at the University of Oxford, to incorporate the monitoring of COVID-19 into its virology surveillance scheme. A vital part of this work has been to monitor the number of suspected COVID-19 cases in the community and ultimately establish the effect of COVID-19 infection on hospitalisation as the outcome measure.

OVERALL AIM
Primary aim of the RECAP (Remote COVID-19 Assessment in Primary Care) project is to assist primary care providers to improve patient care and health outcomes. Most COVID-19 patients are diagnosed and managed remotely by GP’s. This helps reduce the burden on hospitals. However, due to the wide number of possible symptoms, it is hard to predict and diagnose COVID-19.

Through this project, we aim to develop and validate an early warning score for GPs based on data collected to a remote GP consultation and then link this to the outcomes such as hospital admissions as a measure of clinical deterioration.

The purpose of this application is to link data held by NHS digital to support the RCGP RSC to conduct observational epidemiological studies that inform the national public health response to COVID-19. The RCGP RSC dataset includes individual patient level up-to-date primary care data which can be easily queried. Primary care/general practice data is rich in terms of diagnosis and information about the process of care.

For the purpose of this study, datasets coming into ORCHID as part of the MAINROUTE study (DARS-NIC-381683-R6R6K) will also be utilised.

The datasets included are:
- Detailed demographic and risk factor data.
- COVID-19 appointments: information on whether or not a virology swab was taken and the outcome of the swab
- Non-COVID-19 appointments
- Detailed data for the 32 conditions monitored by RCGP RSC on behalf of PHE
- Co-morbid conditions
- Medication which may be associated with better or adverse outcomes.
- Test results
- Referrals made
- A&E visits
- Inpatient appointments, including critical care
- COVID-19 SARI Watch (Formerly CHESS)
- Mortality data (if applicable)

Additional datasets under DARS-NIC-431355-B1L8W will also be utilised:
- COVID-19 Second Generation Surveillance System (SGSS) – (Pillar 1)
- COVID-19 UK Non-hospital Antigen Testing Results (Pillar2)
- Civil Registrations (Deaths)– Secondary Care Cut

The GDPR Lawful basis for processing the requested data under this agreement are;

Imperial College London:
Since Imperial College are the sponsors of this study, they are joint data controllers.

All the data will flow into the secure environment at University of Oxford, thus are data controllers. Furthermore, only University of Oxford will be processing the data.

The data controllers for the processing being undertaken within this agreement are University for Oxford and Imperial Collage London who have together the joint responsibilities. Some of the data which will be accessed under this agreement will be data which is already in the hands of University of Oxford under a different agreement DARS-NIC-381683 for which University of Oxford operate as a Data processor for on behalf of Pubic Health England (PHE) and the Royal Collage of GPs (RCGP) and for DARS-NIC-431355-B1L8W where University of Oxford are a data controller for different purpose.

The lawful basis for processing the data are as follows:

Article 6(1)(e) (Public Task processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller).

Article 9(2)(j) (processing is necessary for reasons of public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interest of the data subject.

Expected Benefits:

The RECAP (Remote COVID-19 Assessment in Primary Care) project aims to assist primary care providers to improve patient care and health outcomes. Most COVID-19 patients are diagnosed and managed remotely by GP’s. This helps reduce the burden on hospitals. However, due to the wide number of possible symptoms, it is hard to predict and diagnose COVID-19.

Through this project, an early warning score for GPs based on data collected to a remote GP consultation will be developed and validated which will then be linked to outcomes such as hospital admissions as a measure of clinical deterioration.

Outputs:

Specific Outputs for this study are:
• To track the impact of COVID-19, visual descriptions (dashboards) of the number and rates of patients presenting specific symptoms (primary care data), being tested for specific tests, hospitalisation outcomes confirming deterioration
• Subgroups of data will be identified to enable display by GP practice, region, age group, gender, and ethnicity.
• Establishing a risk score for the predictability of COVID-19 diagnosis.

Furthermore, articles will be published in international scientific journals.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Flows of data:
- Data are extracted from practices that are members of the Royal College of General Practitioners (RCGP RSC) Research and Surveillance Network by Wellbeing. The University of Oxford subcontracts with Apollo to do this as part its contractual responsibilities.
- The University of Oxford will provide NHS digital with a list of pseudonymised NHS numbers and pseudonymised date of birth for the cohort each quarter.
- NHS Digital will link the cohort to the requested datasets and send pseudonymised linked datasets securely back to University of Oxford.
- University of Oxford will store the data on the secure network.
- University of Oxford will process and aggregate pseudonymised data to produce approved reports for surveillance (as part of the National surveillance process); and for the purpose of COVID-19 vaccine pharmacovigilance and quality improvement.

No identifiable data items will be passed into or out of NHS Digital

SALTING METHODLOGY:
The University of Oxford will follow a salting method in a manner that all the data will be non-identifiable. The process is as follows:
1. An encryption salt is held by a designated staff member of the University of Oxford Medical Science Division who is not a member of the ORCHID staff.
2. When a data linkage is required, the encryption salt holder sends the encryption salt to the data provider (NHS Digital)
3. The data provider will hash personal identifiers (in the data requested by ORCHID) using a hashing algorithm
4. The hashing algorithm is SHA2-512.
5. To make this key unique, an encryption salt is added at the end of the NHS number (e.g. NHS number= 12345678 ; SALT (held by someone other than ORCHID staff) = bob. So, hashing would take place using the SHA2-512 alogrithm by 12345678bob = return pseudonymised data)

The RCGP RSC data is controlled and processed by a group of staff who are all based at the University of Oxford; all are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Language Query (SQL) developers, RCGP RSC practice liaison officers, a project manager and a head of department. The team work from secure workstations or secure laptops with encrypted drives within the group’s secure network.

Data will only be accessed by individuals within the RSC who have authorisation that are substantive employees of University of Oxford. The authorisation process includes: (1) Contractual requirement to follow IG principles; (2) Using the email registered with Human Resources to complete IG training and to return the certificate; (3) Staff email is authorised by the IT department for one year to access the secure network and staff computers are configured to allow this; (4) At any point the project managers or Head can have access to the secure network turned off. There is special authorisation to have access to the main database.

Only three SQL developers and one senior project manager can access the main database. Surveillance databases are
created for approved analyses once they have been agreed by the RCGP RSC approval committee. This agreed protocol
includes the list of variables required for the database. The SQL developers create separate databases for individual projects only including the required variables, for the required time interval.

The additional linkages will be added to the data that the University of Oxford already receives from the RCGP RSC network practices and PHE reference laboratories.

This process for previous projects linking different sets of data, and the linkage has been successful, provided both parties use the same pseudonymisation algorithm (SHA-512).

There will be no requirement nor attempt to re-identify individuals from the data. The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

The use of national data is needed as the University of Oxford are a national surveillance centre and the cohort are from across England and Wales.

The use of pseudonymised NHS numbers are essential as the request to link to the data that the University of Oxford already received from the RCGP RSC network general practices and PHE reference laboratories.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Investigating a vaccine against COVID-19 — DARS-NIC-396423-H4Z6Z

Opt outs honoured: (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2020-08 – 2020-12

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Permission to Contact

Type of data: Identifiable

Objectives:

This Data Sharing Agreement authorises the use of information voluntarily provided to NHS Digital by individuals who have given permission to be contacted about potential participation in COVID-19 vaccine clinical trials. The data will be processed on behalf of the data controller, the University of Oxford, by the data processor, NHS Digital, for the purpose of supporting recruitment to participate in a COVID-19 vaccine trial being run by the University of Oxford.

The following provides background to the Permission to Contact (PtC) Service:

NHS Digital has agreed to work in partnership with the National Institute of Health Research (NIHR) to build and host a first of type online Permission to Contact (PtC) Service on nhs.uk where members of the public can register their details and give their permission to be contacted by researchers working on NIHR approved UK coronavirus vaccine trials about participating in those trials. As at 14th August 2020 there are two such trials. One is run by Oxford University and the other by Imperial College London. This PtC Service, which is called “Sign Up to be Contacted about Coronavirus Vaccine Studies” on the nhs.uk website was launched as a national service on 20th July 2020.

This Service enables participants to:
• Provide permission for NHS Digital to share an individual’s details provided through the Service with the researchers undertaking COVID-19 UK vaccine trials for the purposes of researchers contacting that individual about taking part in those trials.
• Provide their permission to be contacted by NHS Digital about progress and outcomes from CV19 vaccine studies and in relation to the development of the PtC Service, including to inform them of opportunities to participate in other types of health research.

The data collected from individuals who sign up includes sufficient information to achieve the following purposes:
• Matching potentially eligible participants to eligibility criteria provided by the vaccine trials for their specific studies. This data will comprise of age, sex, geographic locations, type of employment, and a number health question e.g. about whether they have long-term health conditions.
• Providing relevant details of potentially eligible participants which have been obtained through the Service to researchers. This will allow the researchers to contact the participants with a view to discussing their taking part in a trial and if so, to obtain their further permission to take part in the trial.
• NHS Digital will provide access to the information obtained from individuals through the Service via the existing Data Access Request Service (DARS) process available to researchers working on UK COVID-19 vaccine trials sponsored by the National Institute of Health Research. The Service will only provide researchers with the data collected directly from individuals themselves through the Service.

The contact details will be used to invite potentially eligible individuals to undertake an eligibility assessment and, if eligible, to give informed consent to participate in this trial. NHS Digital, as data processor acting on behalf of the Oxford Vaccine Study, will be sending the email to eligible participants.

The following provides information about the University of Oxford’s clinical trial:

A new virus causing respiratory disease emerged in Wuhan, China in December 2019 and has since rapidly spread to many other countries around the world, despite unprecedented containment efforts. The virus is part of the Coronavirus family which can cause respiratory infections ranging from the common cold to more severe diseases. This virus causes the disease known as COVID-19. Common symptoms of COVID-19 include fever, tiredness, and dry cough. Whilst about 80% of infected people have no or mild symptoms and will recover from the disease without needing special treatment, 1 in every 6 people who gets COVID-19 becomes seriously ill. Older people and those with underlying medical problems are more likely to develop serious illness. Thousands of deaths have been reported so far. The World health Organisation declared the COVID-19 epidemic a Public Health Emergency of International Concern on 30th January 2020.

There are no currently licensed vaccines and only a limited number of specific treatments for COVID-19.

The University of Oxford is undertaking a study to assess how well people of all ages can be protected from COVID-19 with a new vaccine called ChAdOx1 nCoV-19. This study will also provide valuable information on safety aspects of the vaccine and its ability to generate good immune responses against the virus.

The University of Oxford aims to enrol small numbers of older adults (aged 56-70 years, then 70+ years) before expanding to large numbers of adults across all ages (18+ years). After this, the University of Oxford will also assess the vaccine in a small cohort of children (5-12 years). In total the University of Oxford aims to enrol up to 12,330 volunteers.

The Permission to Contact (PtC) Service will be utilise to assist in recruitment of individuals aged 56+ who will be contacted and invited to participate in the vaccine trial.

Personal data can be lawfully processed under GDPR Articles 6(1)(e) and 9(2)(j) as this is a task in the public interest and classed as research.

Consent allows the data subjects’ confidential data to be used for this purpose satisfying the duty of confidence.

The organisations involved in the processing under this Agreement are the University of Oxford, the data controller, and NHS Digital which, as data processor, will extract a subset of individuals’ information from the PtC dataset and send these individuals emails inviting them to contact the University of Oxford to sign up to participate in the trial.

The University of Oxford will not directly access any of the data under this Agreement.

Organisations involved in the wider vaccine trial are:
• AstraZeneca UK Limited – who have licensed the vaccine and undertaken some of the vaccine manufacture and trial sample analysis
• Public Health England - research collaborator
• Numerous clinical trial sites (primarily NHS trusts)
• Various academic collaborators

None of these organisations have any involvement in the decisions taken by the University of Oxford in respect of the data under this Agreement.

The other organisation involved as the trial funder is the National Institute for Health Research (NIHR)/Department of Health and Social Care. The NIHR has supported the University of Oxford’s request to use the PtC service.

Expected Benefits:

The primary benefit of using the data will be to recruit participants for the clinical study/trial in a manner which:
• Enables individuals to volunteer in advance to participate in COVID-19 vaccine trials as an alternative to other potentially more intrusive mechanisms, e.g. sharing data with researchers about individuals under section 251 consents or COPI notices, which although lawful is initially less transparent.
• Allows researchers to identify a suitable cohort and recruit them quickly into the vaccine trials – thus reducing the overall time to recruit into the trials and to accelerate the delivery of an effective vaccine to treat individuals to manage the COVID-19 outbreak and to save lives.
• Reduces burden on research staff in identifying and contacting potential clinical trial participants.
• Supports the Vaccines Taskforce objectives to drive forward, expedite and coordinate efforts to research and then produce a coronavirus vaccine and make sure one is made available to the public as quickly as possible.

Outputs:

The information from NHS Digital will be used to facilitate contact with individuals who are potentially eligible and who have indicated willingness to potentially participate in studies/trials of COVID-19 vaccines.

This is expected to result in individuals entering the trials screening process with a view to them participating, with fully informed consent, in the Investigating a Vaccine Against COVID-19 study.

The main trial results of Investigating a Vaccine Against COVID-19 study are expected to inform development of a safe and effective vaccine against COVID 19.

Processing:

NHS Digital will extract a list of patients meeting the following criteria:

Volunteers must be:
• 56 years old or older and living in Sheffield, Northwick Park, Edinburgh or Liverpool, OR
• 70 years old or older and living in Birmingham or Hull (Castle Hill)

Volunteers must NOT:
• have had a positive COVID-19 swab/PCR/'antigen' test (antibody tests of any result are acceptable so if your database does not make a distinction between these, then ignore this item)
• be receiving current treatment for cancer
• have a bleeding disorder
• be pregnant, breastfeeding, or planning a pregnancy

NHS Digital will identify all individuals within the PtC dataset meeting the above criteria and will extract their names and email addresses.

It is not known in advance how many individuals meeting the above criteria will have records in the PtC dataset. The number may be amended and the process may be repeated depending on the level of response.

NHS Digital will write to the individuals in the subset inviting them to participate within the trial using ethically approved text provided by University of Oxford. The email will remind the individuals of the background of the permission to contact programme and give them the opportunity to state that they do not wish to be contacted again.

Individuals will not be contacted multiple times under this Agreement and NHS Digital will record the fact that the individuals have been contacted to ensure compliance with the maximum number of contacts outlined as part of consent.

No other processing of the data will take place and the data will not be linked with information from any other sources.

The University of Oxford will not hold or access the data directly and no data will be shared more widely. The data will only be accessed by NHS Digital employees.

Request to share information from the Shielded Patient List (SPL) for Covid-19 Purposes — DARS-NIC-381632-M4D9L

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

Legal basis: Other-Health and Social Care Act 2012 Section 261(1) and Section 262(2)(e)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2020-05 – 2020-09

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Shielded Patient List

Type of data: Anonymised - ICO Code Compliant

Objectives:

Background and Aims
The University of Oxford are requesting access to the Shielded Patient List (SPL) to support the development and validation of a new risk prediction tool to identify people in the England at high risk of severe outcomes from COVID-19 infection.

The first cases of infection caused by coronavirus SARS-CoV-2 (COVID-19) in the UK were confirmed on 24th January 2020 and the first UK death on 28th Feb 2020. Since then the disease has spread rapidly through the population. There are no vaccines, preventative or curative treatments for COVID-19 disease and only one possible disease modifying treatment so the government has used social distancing as a population-level intervention to limit the rate of increase in cases.

Case series of confirmed COVID-19 have identified age, sex, certain co-morbidities, and ethnicity as potentially important risk factors for susceptibility to infection, hospitalisation, or death due to infection. In addition chronic use of some medications at the time of exposure has been suggested as a potential risk factor for infection or severe adverse outcomes due to infection, although the evidence is currently too limited to confirm or refute these concerns. Understanding these risk factors is important especially where exposure, risk factors or medication could be modified in individuals or at a population scale to alter the likelihood of infection or adverse outcomes. Furthermore, associations between medications and improved outcomes, if confirmed from large cohorts, might provide important insights into disease mechanisms and pathogenesis.

As illustrated by a recent systematic review, prediction models for COVID-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. Three models have been identified that predict hospital admission from pneumonia and other events (as proxy outcomes for COVID-19 pneumonia) in the general population. Eighteen diagnostic models were identified for detecting COVID-19 infection (13 were machine learning based on CT scans); and 10 prognostic models for predicting mortality risk, progression to severe disease, or length of hospital stay. The systematic review indicated that proposed models are poorly reported, at high risk of bias, and their reported performance is probably optimistic8.

Thus, the Data Controller proposes to develop and validate a new risk prediction tool to identify people in England at high risk of severe outcomes from COVID-19 infection. This research will form the basis for a rapid research study to inform national COVID-19 and shielding policy. The study will describe the development and validation of novel COVID-19 risk prediction equations for initial use in the NHS in the UK but potentially available internationally (subject to local validation). It is anticipated that the equations will be widely available for use and that the equations will be updated regularly as understanding of COVID-19 increases, better data become available and as the underlying population changes or the virus itself mutates

The purposes for sharing the requested data are set out below (Agreed Purposes):
• NHS Digital has agreed to share a pseudonymised identifier (Pseudonymised NHS Number) and COVID 19 risk code (High or moderate if present) for each patient on the SPL (the Disclosed Data) with the Data Controller for the research purposes below.
• The Data Controller proposes to develop and validate a new risk prediction tool to identify people in England at high risk of severe outcomes from COVID-19 infection. This research will form the basis for a rapid research study to inform national COVID-19 and shielding policy. The study will describe the development and validation of novel COVID-19 risk prediction equations for initial use in the NHS in the UK but potentially available internationally (subject to local validation). It is anticipated that the equations will be widely available for use and that the equations will be updated regularly as understanding of COVID-19 increases, better data become available and as the underlying population changes or the virus itself mutates.

Cohort
University of Oxford will undertake a cohort study in a large population of primary care patients using the QResearch® database (version 44). They will include all practices in England who had been using their EMIS computer system for at least a year. The University of Oxford will randomly allocate three quarters of QResearch practices to the derivation dataset and the remaining quarter to a validation dataset.

The University of oxford will identify a second validation dataset from GP practices using a different system (e.g. using the TPP clinical system). This could either be achieved through (a) the new OpenSafely platform or (b) an extract provided by TPP to Oxford to link to QResearch (in line with REC approvals ref 18/EM/0400 obtained 01.04.2020) The advantage of (a) is that it available now and accessible by one of the investigators. The advantage of (b) is that it will allow TPP data to be linked to mortality, HES, ICNARC and COVID-19 national datasets since these datasets are already held by the QResearch team at Oxford and updated regularly (weekly or monthly).

Open cohorts of patients aged 0-100 years registered with practices on or after 1st January 2020 will be identified. Patients who do not have a valid NHS number will be excluded. Patients will enter the cohort on 1st Jan 2020. Patients will be censored at the earliest date of the diagnosis of the relevant outcome of interest, death (non-COVI-19) or the date of most recent data for each outcome.

It is relevant to note here that Data which is being anonymised by NHS Digital to share with the University of Oxford for QResearch includes data which has been collected from GPs about patients who may have registered a Type 1 as the data was shared for a direct care purpose – namely to identify those who are extremely clinically vulnerable and who need to shield. However, there is no mechanism to identify those patients to exclude them from this dissemination. Given their data will be anonymised when shared with University of Oxford, the public interest in those individuals who are on the SPL being given appropriate advice on how to protect themselves from COVID-19 and that this research is directly about identifying those who are at most risk, it is considered the objective of the research and the benefits it will bring to those what are shielding and others who may need to shield, overrides any objection registered by a patient.

Legal Basis
The SPL data was obtained by NHS Digital under the COVID-19 Public Health Directions 2020 which permit NHS Digital to collect and analyse data for COVID-19 Purposes and to share the Disclosed Data with the Data Controller for the Agreed Purposes under section 261(1) and s261(2)(e) of the Health and Social Care Act 2012 (2012 Act).
The Agreed Purposes are COVID-19 purposes for the promotion of health as required by s261(1A)(b) of the 2012 Act as the study will inform policy in relation to shielding and will develop a tool that will provide information about the COVID-19 risks to individuals. Under the General Data Protection Regulation 2016 (GDPR), NHS Digital is relying on Article 6(1)(c) Legal obligation: the processing is necessary for complying with the law (not including contractual obligationswith the Data Controller for the Agreed Purposes above. As this is health information and therefore special category personal data
NHS Digital is also relying on Article 9(2)(g) – substantial public interest and para 6 of Schedule 1 DPA – statutory purpose, to share the Disclosed Data for the Agreed Purposes.

Oxford University does not have a s251 approval for the data it holds for QResearch as it is considered to be anonymised data (in context) and HRA have confirmed that CAG approval is not required.

The data in the QResearch database is not considered to be confidential patient information and the Confidentiality Advisory Group (CAG) has confirmed to the Data Controller, including in March 2020 in relation to its COVID-19 research, that section 251 support from CAG is not required.
As the NHS number for patients from the SPL will be replaced with a pseudonymised identifier by NHS Digital, the Disclosed Data when shared with the Data Controller and used with other data in the QResearch Database will also be anonymised data, as the Data Controller and those who will process the Disclosed Data for the Agreed Purposes will not be able to identify the individuals to whom the Disclosed Data relates. As the Disclosed Data will be anonymised data, there will be no breach of the common law duty of confidence through the processing by the t Data Controller of the Disclosed Data for the Agreed Purposes. As the Disclosed Data will by anonymised data when processed by the Data Controller, it will not be regarded as personal data and therefore is not subject to GDPR and the Data Protection Act 2018. NHS Digital will publish details about the sharing of the Disclosed Data with the Data Controller in its Data Release Register and on its website page about the SPL List here https://digital.nhs.uk/coronavirus/shielded-patient-list/distribution.

Data Requested
NHS Digital has produced a Shielded Patient List (SPL) which contains details of those individuals who have been identified by clinicians as being extremely vulnerable in relation to the COVID-19 virus as a result of their pre-existing medical conditions. The University of Oxford has requested NHS Digital to share with it certain anonymised information identified below as Disclosed Data from the SPL, for the development and validation of a risk prediction algorithm to estimate short term adverse outcomes from COVID-19 disease which can be used as a risk stratification tool and to inform national shielding policy as more fully detailed below.
Data to be disclosed will come from the Shielded Patient List (SLP):
Shielded Patient List (SPL)
Versions 1.0, 2.0, 3.0, 5.0 and 7

The data refers to list records of who have been identified as Clinically Extremely Vulnerable (CEV) and added to the Shielded Patient List.

The data to be disseminated is:
• Pseudonymised Identifier (Pseudonymised NHS Number)
• COVID 19 risk code (High or moderate if present)

The sole data controller and processor is the University of Oxford.

Expected Benefits:

It is important for patients, staff and the NHS that there is one widely used, validated tool which is consistently implemented across the service and which is supported by the academic, NHS and patient communities. This will then help ensure consistent policy and clear communication between policy makers, professionals and the public.

The risk algorithms can be used in various ways (examples below are based on the various ways which www.qrisk.org has been implemented and used across the NHS over the last 12 years).
1. Within a consultation between the patient and a clinician with the intention of sharing the information with the patient to assess management options.

For example, a 54-year old Asian man wishes to know his risk of serious COVID-19 disease in order to modify risk factors (lifestyle, medication, occupational exposure etc). This could be achieved through development of a risk calculator for use within a consultation.

2. To risk electronically stratify populations to target clinical interventions towards different groups of patients based on levels of risk.

For example, a GP practice needs to identify patients shielding or prioritisation for vaccination (once one is available). This could be achieved through the implementation of the equations as risk stratification software embedded in GP clinical computer systems. This will ensure the tool can be applied to up-to-date electronic health records for direct clinical care purposes.

3. To model impact of interventions or changing policy (e.g. shielding, prioritisation for vaccination, occupational health, health economic analyses) through the analysis of the equations are applied to consolidated research databases.

For example, DH/PHE/NHS Digital need to assess the impact of changing guidelines on the risk categories or thresholds at a national or regional level e.g. how many patients would be reclassified as high/medium/low risk and what would the resource implications be?

4. Adapted for use by the general public to improve communication and understanding of risk (David S to add more) through implementation into web-based tools.

For example, a school or community needs to highlight risk factors and link to recommendations in behaviours to help reduce transmission of COVID-19.

5. Use by researchers to help generate new knowledge or insights.

For example, a risk stratification tool could be used to identify high risk patients to be invited to join a clinical trial or to adjust an analysis for baseline risk factors.

Outputs:

COVID-19 is an emerging pathogen which presents a significant threat to the population in terms of increased morbidity and mortality, particularly among vulnerable groups such as those with pre-existing disease.

The primary objective and thus output of the study will be the development and validation of novel COVID-19 risk prediction equations for initial use in the NHS in the UK but potentially available internationally (subject to local validation). It is anticipated that the equations will be widely available for use and that the equations will be updated regularly as understanding of COVID-19 increases, better data become available and as the underlying population changes or the virus itself mutates. It is also important to recognise at the outset that there will be limitations to any model that is produced and that the use of the model reviewed and updated regularly to ensure it remains fit for purpose.

All outputs produced will be in the form of aggregated reports with small number suppression applied.

Processing:

The Disclosed Data will be linked to other data held by the Data Controller in the QResearch Database, a GP practice research database. The database is linked at individual patient level to hospital admissions data, cancer registrations and mortality records obtained from the Office for National Statistics. In 2020, two additional national databases were linked to QResearch for COVID-19 research: the national registry of COVID-19 RT-PCR positive test results held by Public Health England (PHE) and the Intensive Care National Audit and Research Centre (ICNARC) Case Mix Programme (CMP) database. It is proposed that a register of healthcare workers is also added to the QResearch database and that together with the Disclosed Data this will also enable the research objectives for the study to be expanded to specifically examine the risks for both groups of people (shielded and health care workers) which could directly inform national policy regarding the maintenance and operation of the SPL and also quantify the risks experienced by health care worker to inform occupational health considerations.

• All records in the QResearch database are de-identified and are linked using a project specific pseudonymised NHS number. The pseudonymisation keys are not held by the Data Controller. The Disclosed Data will be de-identified by NHS Digital before it is shared with the Recipient and NHS Digital only will hold the pseudonymisation key.
• The Recipient will ensure that the Disclosed Data when linked with other data in the QResearch database will remain de-identified and will be considered to be anonymised in context in accordance with the ICO Code of Practice on Anonymisation.1

The Disclosed Data will be securely shared on or around 24 May 2020 with the University of Oxford via SEFT.

The Data Controller will ensure that when processing the Disclosed Data that it will not be processed in a way which would enable the identify of any individual to be ascertained either directly or indirectly and as such that the Disclosed Data will be maintained as anonymised data by the Data Controller who will ensure there are sufficient controls in place to achieve this as required by the ICO Code of Practice on Anonymisation.

If any of the Disclosed Data becomes identifiable and personal data through the processing activity carried out by the Data Controller, the Data Controller shall: a.) immediately cease processing the Disclosed Data and shall notify NHS Digital and agree changes to these terms of release which will require the Data Controller to have a legal basis to continue to process the Disclosed Data; and b.) comply with the GDPR, the Data Protection Act 2018, all applicable law concerning privacy or the processing of personal data and the Common Law Duty of Confidence when processing the Disclosed Data.

The Data Controller may process the Disclosed Data for the Agreed Purposes only.

NHS Digital will share the Disclosed Data in a one-off transfer securely with the Data Controller on or around 24 May 2020. If any further versions of the Disclosed Data are required, this will be agreed with the NHS Digital Caldicott Guardian.

The Data Controller will ensure that the Disclosed Data is subject to the same level of security and shall be stored and processed in the same locations as the other data disclosed to it by NHS Digital through the NHS Digital Data Access Request Service (DARS) under Data Sharing Agreements reference numbers NIC-240279 and NIC-375354.

The Data Controller shall if required apply for updated Research Ethics Committee approval in relation to the inclusion of the Disclosed Data in the COVID-19 research it is carrying out, if this is required (noting that the Disclosed Data is anonymised data which would be made available to the Data Controller.

The Data Controller and the Processor will on completion of the processing activity for the Agreed Purposes securely destroy the Disclosed Data (including any copies it was necessary for it take for the Agreed Purposes) and on the request of NHS Digital shall provide a data destruction certificate signed by the lead applicant.

NHSD will pseudonymise the NHS number. There will be no identifiable information in the data shared with QResearch. The data will be linkable via the pseudonym to other datasets University of Oxford holds all of which are anonymised in context due to the control in place under contracts under which they are shared and through the controls put in place by Oxford.

QResearch
QResearch is a high-quality research database established in 2002 which has been used extensively used for the development of risk prediction tools which are widely used across the NHS as well as a wide range of high impact epidemiological research. QResearch is a large, representative validated GP practice research database nationally. Until April 2020, there were 1205 practices contributing covering a population of 10.5 million patients. Following a recruitment invitation, the database has now doubled to 2519 practices in England, 193 in Northern Ireland and 3 in Scotland which will cover approximately 21 million current patients. There are currently no practices in Wales.

All data shared under this agreement will be processed and stored in secure locations within England and Wales and will not be shared outside University of Oxford, other than in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

4CHILD - Four Counties Database of Cerebral Palsy, Vision Loss and Hearing Loss in Children (Berkshire, Buckinghamshire, Northamptonshire, Oxfordshire) — DARS-NIC-148239-M8RTP

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-10 – 2021-10

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Flagging Current Status Report

Type of data: Identifiable

Objectives:

The University of Oxford received data from ONS and subsequently NHS Digital from 2003 onwards for the purpose of 4Child. 4Child is a database which was established in 1984 to collect information about children with cerebral palsy and/or severe vision loss and/or hearing loss born to residents of Berkshire, Buckinghamshire, Northampton and Oxfordshire. It was used as a resource to carry out surveillance, research and service evaluation on the causes and consequences of the three potentially disabling conditions of cerebral play, vision loss and hearing loss; to access the effectiveness of interventions during pregnancy and soon after births; as well as to assess the need for services to support affected children.

Formerly called the Oxford Register of Early Childhood Impairments (ORECI) 4Child has been collecting information about children with cerebral palsy (CP), sensorineural deafness or severe vision loss born to residents of Berkshire, Buckinghamshire, Northamptonshire and Oxfordshire since 1984 and has information about 2,700 children with one or more of these impairments.

The register was set up against a background of uncertainty of the contribution of increased numbers of low birth weight survivors on the numbers of disabled children in the population. At the time, there were no routinely collected and easily accessible data on early childhood morbidity and so the register was set up as a framework to examine clinical associations of disabling conditions, to assess services, and to assess the effectiveness of perinatal intervention.

The aims of the database when it was established were to:

i. Monitor the prevalence of cerebral palsy, vision loss and hearing loss in children from 1984 onwards in the four counties of Berkshire, Buckinghamshire, Northamptonshire and Oxfordshire.
ii. To provide a research platform and support research and service audit initiatives using data from 4Child, in order to contribute to knowledge and understand of the causes and consequences of the impairments and how they might be prevented and better managed.
iii. To develop links with other researchers and collaborate in research within the UK, Europe and other centre around the world.

The 4Child database was run by the 4Child research team within the National Perinatal Epidemiology Unit (NPEU) at the University of Oxford.

The operation of the 4Child database involved receiving information about children who were born or lived during in early childhood (up to age 5 years) in one of the four counties, who were suspected and then diagnosed as having one of the three impairments: cerebral palsy, vision loss or hearing loss; of note some children have more than one of these impairments.

The information about the affected children was provided by any health professional who came into contact with the child during early childhood – so called multi-source notification. Multi-source notification is the mechanism used to ensure that no children were missed. The 4Child team at the University of Oxford also received information from the Office for National Statistics about any children who died. This enabled the team to carry out research into death rates for children with these impairments and to understand the reasons why some children and adults with these impairments die earlier than would normally be expected.

The information received about the children was identifiable personal data and included the names, addresses and dates of birth of the children. Receiving identifiable information was necessary to enable the team to identify when a child was notified to the team more than once so that that any duplicate notifications could be removed. The identifiable information was also used to enable collection of follow-up information about the children to obtain details about the extent and impact of their impairment. Using the information, with relevant regulatory permissions, the team were able to contact some families to invite them to participate in research.

Funding was provided to support the work of 4Child from a number of sources over the years. Latterly it was funded by the Department of Health but this final grant ended in 2010. The 4Child research team was disbanded once the funding ran out. Only one member of the research team remains in the NPEU.

As it was not possible to obtain further funds the database closed to registrations of newly diagnosed children in 2010. Nevertheless, the existing database is an invaluable and unique source of whole population data about children with these three important impairments as currently there is no other similar information collected in England in this systematic way.

In view of the fact that was not possible to obtain further funding to continue the active work of the database a decision was recently made to remove all the identifiable personal information on the database and this process was completed in August 2019. This means that all names, addresses, postcodes, dates of birth, dates of notification and diagnosis, where applicable dates of death, and all other date-related information held in the database have been deleted. All relevant date information was replaced with age at the event. The information held includes the cause of death.

The database will be securely archived to comply with good practice and also to preserve the resource for potential future research subject to the necessary approvals including an application to NHS Digital.

The need to keep the data in the long term will be subject to review. Initially, the mortality data will be retained for two years. Before the end of this period the University of Oxford will decide whether there is a continuing purpose for the mortality data which would justify keeping the information for longer. In the event a decision is made not to continue holding the data from death certificates, this information will be deleted from the database. At that stage the University of Oxford will also review the value of continuing to hold the rest of the data in the 4Child database.

This Data Sharing Agreement will permit the retention of the data previously supplied by NHS Digital and predecessor organisations. No other processing activities will be permitted. No new data will be supplied and/or linked to the dataset and no uses of the data (e.g. for research) are permitted.

Yielded Benefits:

The 4Child register contributed vital data to enable important research into the trends, aetiology and consequences of cerebral palsy to be carried out in: the 4Child region, across the UK as part of the UKCP collaboration and across Europe as part of the SCPE collaboration. The other key contribution that the 4Child data made was tracking the trends in the prevalence of cerebral palsy in the four counties. These were published in a series of annual reports and made available to clinical staff, policy makers and service planners. One of the important uses of the prevalence data was in the planning of service provision for children with cerebral palsy based on the number of affected children and the extent and severity of their impairments. Over 90 peer-reviewed research papers using data from the 4Child register were published prior to the closure of the register. Examples of the research conducted using 4Child data include: 1. A study to describe trends in the prevalence of cerebral palsy in preterm and low birthweight infants which demonstrated that over the period 1980 to 1996 the prevalence fell indicating the beneficial impacts of improved maternity and neonatal care over this period (Platt et al 2007). 2. A aetiological study to investigate the effects of gestational age at birth on the risk of cerebral palsy which identified and quantified the role of inflammatory factors which influenced the gestational-age specific risks, including, intrapartum hypoxia, neonatal sepsis, pre-eclampsia (Greenwood et al 2005). 3. A study to describe the long term consequences of cerebral palsy and the impact of cerebral palsy on subsequent risk of premature mortality and the predictors of mortality. This study demonstrated that the number and severity of impairments were the strongest predictors of risk of death (Hemming et al 2005).

Expected Benefits:

This data will be retained to comply with University of Oxford guidance and policy on good clinical practice. It also preserves a unique database of children with cerebral palsy, vision loss and hearing loss in England, which could still yield future benefits.

Processing:

This 4Child programme is now completed and closed.

The 4Child register was originally a disease register to enable surveillance, research and service evaluation to be carried out. The register is no long active.

This Data Sharing Agreement permits the retention of the data previously supplied by NHS Digital and predecessor organisations, which has now been pseudonymised.

This agreement permits processing of the data for the purpose of secure storage and back up.

This agreement does not permit any further processing that involves analysis, linkage, onward sharing. If further data processing is required the applicant must submit an amendment request to NHS Digital before data is accessed.

The data originally requested from NHS Digital was for use in the 4Child Four Counties Database of Cerebral Palsy, Vision Loss and Hearing Loss (PIAG 4-09 b)/2003).

The intention is to archive the pseudonymised dataset for the immediate future to preserve it as a resource to be used in future research subject to funding and the necessary approvals.

Any further analysis will only take place following an amendment to this Agreement that would allow further processing of the data.

The data will be stored in the National Perinatal Epidemiology Unit (where it has been stored since inception). The NPEU is part of the Nuffield Department of Population Health at the University of Oxford. The data will be stored on NDPH servers since this is the department in which the NPEU sits.

MR461 - A long term follow-up study of Aperts Syndrome — DARS-NIC-148106-PP9LS

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-08 – 2024-07

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Flagging Current Status Report

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

Civil Registration mortality data and Cancer Registration data were supplied to the University of Oxford for the purpose of a long-term follow-up study of individuals with Apert Syndrome.

This study is now complete and closed. This study ran from 1994 to 2013. Data processing finished in 2015, when information on ages at event (death, cause of death, still living on 08/05/2013), with all identifiers removed, were provided to a statistical epidemiologist substantively employed by the University of Oxford. The findings (now in aggregated form) have been ready for publication since 2015 but this has been delayed pending clarification of the legal basis for retaining the data.

This Agreement permits the release of the publication, and the processing of the data for the purpose of secure storage and back up to ensure it is possible to verify the conclusions published from this study..

This Agreement does not permit any further processing that involves analysis or linkage other than for the purpose of verifying findings in line with the original objectives of the study by repeating previous analyses described in this Agreement. Following publication of the study findings, it is possible that the findings will be questioned or challenged by third parties through direct contact with the University of Oxford, contact via the publishing journal or an open letter. In such circumstances, the University of Oxford may re-run the previously analyses undertaken to verify that the published results were accurate and may write a response to be issued directly to the challenger or published. The University of Oxford may not use the data to undertake different analyses to those undertaken during the original analysis.

This Agreement does not permit any onward sharing of the data. The data controller may process the data for the purpose of audit.

If any further data processing is required in addition to the above purposes or if the data needs to be moved to a different location/organisation the applicant must submit an amendment request to NHS Digital and receive formal approval in an amended Data Sharing Agreement before data is accessed.

Since 1960 there has been very little further research into Apert syndrome in this country until in 1994 a new study was created at the University of Oxford. The purpose of this new study at the University of Oxford was to try to find out what causes Apert syndrome. Apert syndrome is a rare malformation syndrome comprising two distinctive features, namely a characteristic appearance of the face and skull due to early closure of the skull bones (craniosynostosis) and bony fusions of the fingers and toes (syndactyly). This due to an alteration in one of the many thousands of genetic instructions which human beings carry from the time of conception. This study has already managed to identify which particular genetic instruction is altered, but much work needs to be done to try to understand why the alteration occurs in the first place, and how it causes the features of Apert syndrome.

In 1994 the University of Oxford sought permission from the head researcher of the 1959 study (who was based at the University of Sheffield) in order to obtain the names and dates of birth of the 24 participants in the 1959 study. These are the only data subjects.

The University of Oxford used these details to obtain data from the Medical Research service under the Office of Population Censuses and Surveys (OPCS). in January 1995. The service subsequently transferred to the Office for National Statistics (ONS) and then the Health and Social Care Information Centre (now known as NHS Digital). This detail was used to give the University of Oxford two options;
1 - Should the participant have passed away at time of flagging, the University of Oxford obtained the cause of death, and cancer registration data to understand whether there was an increased incidence of certain cancers.
2 - Should the participant be alive at time of flagging, the University of Oxford would invite them through their General Practitioner to take part in the study.

This study is considered to be in the public interest because it provides new (not previously available) information on the long-term survival of the medical disorder Apert syndrome. The retention of the data, which is now pseudonymised, is not expected to raise ethical issues because no individually identifying information on ages and causes of death is held.

It should be noted that this (currently unpublished) study provides very valuable information for people with Apert syndrome and their parents and carers, because it establishes for the first time that many individuals with the condition live into their 50s-70s. Moreover, although mortality is higher than average before this age, the causes are varied with no one frequent cause (for example a particular type of cancer), being revealed by the data. There is a strong public interest in making these findings widely known by publication in the medical literature.

Data collected were mortality and cancer data from 1994 until 2013. Initially data were supplied by OPCS/NHSCR on whether each individual was already deceased, and if so, the cause of death. In the case of individuals still alive, tracing of dates and causes of death, or cancers, continued (following necessary approvals after each administrative reorganisation) by ONS/NHSIC/HSCIC until 8 May 2013

Since then, actions have been taken to pseudonymise the Apert Syndrome data. These included converting date of birth to week and month of birth, deleting names, and deleting NHS Numbers. No identifying details are held by the University of Oxford in respect of this study.

The data controller is the University of Oxford which is also the only organisation which has processed this data. The analysis of the data completed in 2015, when information on ages at event (death, cause of death, still living on 8/5/2013), with all identifiers removed, were provided to a University of Oxford statistician who has completed a paper on this Apert syndrome. No external parties have been involved in this work. The findings have been ready for publication since 2015, but this has been delayed pending clarification of the legal basis for retaining the data. Following advice from NHS Digital, the University of Oxford has pseudonymised the data.

Yielded Benefits:

None, as the work has remained unpublished up to this point.

Expected Benefits:

This data will be retained to comply with guidance and policy on good clinical practice and regulations. It also preserves a unique database which could still yield future benefits for young families by looking at the effects on children in the longer term.

It is expected that this will improve knowledge of long-term prognosis of Apert syndrome, and causes of mortality, in adulthood. This will assist health professionals in providing better quality, evidence-based information to patients with Apert syndrome and their parents. Improved medical knowledge about this rare condition represents a public good.

The peer-reviewed publication will provide the objective data supporting the broad conclusions. The Headlines article will make these data known to the patient/parent constituent groups.


The benefits anticipated are two-fold:
(i) Psychological: Apert syndrome is a serious disorder providing many challenges for affected children and their parents. It will be very reassuring for families to know that being affected by Apert syndrome does not in addition indicate a high likelihood of early mortality as an adult because of a particular later-onset disease.
(ii) Scientific. It is known that one of the most common genetic associations of endometrial cancer is the identical FGFR2 mutation to that causing Apert syndrome, but occurring as a somatic mutation (ie, in a particular cell in the body at a later stage of life, rather than something you are born with). It is of great scientific interest that being born with the identical mutation is not necessarily associated with markedly increased risk of a similar type of cancer.


Major action/change is likely to be empowerment provided by new knowledge and associated psychological benefit, given that the new knowledge is largely reassuring regarding prognosis. The impact is small at population level, because this is relevant only to Apert syndrome (prevalence ~1 in 65,000); but nevertheless important for this group of individuals.

This agreement seeks to assure data integrity for a reasonable period of time (up to 5 years) following dissemination. This will enable evidence supporting findings to be examined, if necessary, should be findings be questioned or challenged for reputable scientific reasons.

Outputs:

This study is now completed and closed.

On approval of this Data Sharing Agreement, a completed publication from 2015 will become publicly available. No new analyses will be undertaken using the data under this Agreement.

An online article would be prepared for Headlines, the UK Craniofacial Support Group, so that parents of children with Apert syndrome, and affected young adults, would be made aware of the findings. No new use of the data would be required for this. It would simply be targeting the already-existing information to a specific audience and in simple language.

A summary of the findings would be published in a peer-reviewed medical genetics journal, for example, American Journal of Medical Genetics.

Causes of death, or whether still alive at the end of the study, would be summarised in 5-year bins. As there are only 24 data subjects in the study, each 5-year bins contain fewer than 5 individuals and consequently if someone knew of a person who had Apert syndrome and was in the 1959 study and died within a specific 5-year age-range, they may be able to identify that person. However, the only additional information they may be able to determine about this individual from the summary data might be their primary cause of death which is a matter of public record. Death and cancer data would be summarised in the form of Kaplan-Meier survival curves or similar demonstrating the proportion of individuals still alive at a given age.

An Open Access charge would be paid to the publisher of the peer-reviewed article, to ensure that the article could be read by anybody wishing to do so.

The Headlines web-based article would ensure that the knowledge reached the relevant patient/parent group.

The Publication is expected to be made available for submission of manuscript for peer-review towards the end of 2019, with publication and associated Headlines article in 2020.

This is the sole planned data dissemination and therefore integral to the overall purpose of the work.

Processing:

This study is now completed and closed.

This Agreement permits processing of the data for the purpose of secure storage and back up.

This Agreement does not permit any further processing that involves analysis or linkage other than for the purpose of verifying findings in line with the original objectives of the study by repeating previous analyses described in this Agreement.

This Agreement does not permit any onward sharing of the data. The data may be viewed for the purpose of an audit.

If any further data processing is required in addition to the above purposes or if the data needs to be moved to a different location/organisation the applicant must submit an amendment request to NHS Digital and enter into an Amended Data Sharing Agreement before the data is accessed.

In the event that the data needed to be accessed for the purposes of audit or to enable verification of previous findings, the dataset with authorisation from the Principal Investigator will be accessed by the study statistician only for the purposes of verifying results of previous analyses by rerunning analyses that were previously undertaken. Data would be accessible only for as long as is required to enable verification of the analyses and to write a response as appropriate.

The data may not be transferred to any other location and may only be accessed by substantive employees of the University of Oxford for the purposes described above.

The data originally requested from NHS Digital was for use in the long-term follow-up study of Apert Syndrome. Civil registration mortality and Cancer Registrations data were used to follow-up individuals involved in the study.

Study data needs to be retained and accessible for 5 years after publication.

PRINCIPLE: Platform Randomised trial of INterventions against COVID-19 In older peoPLE — DARS-NIC-411161-G4K7X

Opt outs honoured: Yes - patient objections upheld, No - Statutory exemption to flow confidential data without consent, unknown, Yes, No (Excuses: Statutory exemption to flow confidential data without consent)

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261 - 'Other dissemination of information', CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 – s261(2)(c), CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2020-11 – 2021-05 2020.11 — 2025.03.

Access method: One-Off, System Access, Ongoing
(System access exclusively means data was not disseminated, but was accessed under supervision on NHS Digital's systems)

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  2. COVID-19 Access to Summary Care Records
  3. Hospital Episode Statistics Critical Care
  4. Hospital Episode Statistics Admitted Patient Care
  5. Civil Registration - Deaths
  6. GPES Data for Pandemic Planning and Research (COVID-19)
  7. Medicines dispensed in Primary Care (NHSBSA data)
  8. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  9. Civil Registrations of Death
  10. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  11. Hospital Episode Statistics Admitted Patient Care (HES APC)
  12. Hospital Episode Statistics Critical Care (HES Critical Care)

Type of data: Identifiable, Anonymised - ICO Code Compliant (note: this information not disclosed for TRE projects )

Objectives:

Over recent weeks, there has been an increase in the number of COVID-19 cases in the community and in hospitalisation. Currently, there are no treatments that have been proven in rigorous trials to help people with COVID-19 symptoms in the community recover quicker and reduce the need for hospital admission. It is therefore vital that the University of Oxford use this opportunity to accelerate enrolment into COVID-19 therapeutics trials.

The PRINCIPLE (Platform Randomised trial of Interventions against COVID-19 In older peoPLE) trial is the only national Urgent Public Health priority clinical trial evaluating potential therapeutics for COVID-19 in the primary care setting, endorsed by the CMOs of all four devolved nations . The trial aims to find out whether early treatment in the community speeds recovery and reduces the need for hospital admission for those with COVID-like-Illness.

PRINICIPLE is:
• Recruiting across the whole UK: anyone can participate, regardless of location.
• Light burden for both recruiters and patients; it only takes couple of minutes to complete enrolment on to the trial.
• Obtaining consent, checking eligibility, issuing study medication and materials, and follow-up is manged remotely through a central facility.

Primary objective - To assess effectiveness of trial treatments in reducing the need for hospital admission or death, for patients aged ≥50 years with comorbidity, and aged ≥65 with or without comorbidity and suspected COVID-19 infection during time of prevalent COVID-19 infections.
Secondary objectives - To explore whether trial treatment reduces
1) Duration of severe symptoms
2) Time taken to self-report recovery
3) Contacts with the health services
4) Consumption of antibiotics
5) Hospital assessment without admission
6) Oxygen administration
7) Intensive Care Unit admission
8) Mechanical ventilation
9) To determine if effects are specific to those with the infections syndrome but who test positive for COVID-19
10) Duration of hospital admission

The trial is currently recruiting via GP practices and the website and have c. 1000 participants but need to rapidly increase this to 3,000 (and beyond to support further trial arms). To achieve this, use of the Pillar 2 testing data is proposed.

The University of Oxford would like to receive names and contact details (preferably a telephone number) of people who have received a positive covid-19 swab result from the Pillar 2 testing system. The trial team based in Oxford will then contact these potential participants, inform them about the trial and if they are happy, go on to screen and consent them into Principle. Daily, the trial team would like to receive data on a random cohort (initially 200) of people aged 50+. They may need to increase this age to 65+ if those they contact screen as ineligible for the trial as they lack the required comorbidities.

Consideration has been given to whether the trial should be contacting individuals directly, and whether the recruitment could be managed through the Test and Trace service, i.e. the service are already set up to contact individuals and could inform them of the trial when they get in touch. However, given the use of contractors to operate this service, and thereby creating an extra layer to the process, this is unlikely to fit with the timescales the trial are working to (which ties in with why they have decided to switch from GPs as the primary source of recruitment). Additionally, the trial already has a centre set up and operating remotely to manage this recruitment in a timely manner.

The question of whether ‘cold calling’ is appropriate has been considered for this application, especially against alternatives such as SMS and emailing. As time is of the essence for recruitment into PRINCIPLE, telephone is the most efficient and quickest means to ensure direct contact with the individual, who can answer questions instantly over a call. This also ensures ‘human contact’, as opposed to SMS / emails, with trained and experienced CTU research nurses working directly to the trial team providing that contact. During the calls, clear explanation will be given to individual about how the trial has been able to contact them and what to do if they do not wish to be contacted again (i.e. registering a national opt-out). The trial team will decide whether to apply the Telephone Preference Service under their own discretion. The trial team will also ensure the required comorbidities are discussed early on in the calls so as to bot to get the individual’s hopes up if they are not in fact eligible for the trial. Lessons have been learned from a recent NHS Digital request for contact details provided to researchers contact people to donate blood and plasma, with careful attention paid to the various take up rates and any changes rates in these between the first and second waves of the pandemic. However, unlike that trial, PRINCIPLE could potentially be of direct benefit to the individual.

Other considerations that have been taken into account in relation to contacting individuals:
• The data relating to positive COVID19 tests is sent to NHS Digital at the same time that it is sent to the Business Services Authority, the latter process triggering the SMS to the individual informing them of their result. It then takes around four hours for the Pillar 2 dataset within NHS Digital to be updated with this information. Given that this information then needs to be extracted from the dataset at some point in the next 24 hours, then used by the trial team to make contact with the individual, the risk of the individual being informed of their test result by the trial team before they have read their SMS is small. However, the trial team should have a suitable script prepared to deal with this slim possibility.
• The chances of people having multiple positive COVID19 test results are rare, and rarer still is the likelihood that they will be one of the 200 people extracted from the thousands of daily test results to be sent to the trial team on more than one occasion. Therefore the risk of an individual being contacted twice for recruitment into PRINCIPLE is extremely low.
• NHS Digital recognises that there are likely to be more requests of this nature in future and therefore, if multiple trial require extracts of people to contact, suitable controls need to be in place within the extract process to ensure that individuals are not getting contacted for recruitment into trials more than is reasonably expected.

Expected Benefits:

The trial has co-primary endpoints: 1) Time taken to self-reported recovery; and 2) hospitalisation and/or death. The main objective of the trial is to assess the effectiveness of the interventions in reducing time to recovery and in reducing the incidence of hospitalisation and/or death for covid-19 sufferers.

Key secondary outcomes include: Hospital assessment without admission; Oxygen administration; Intensive Care Unit admission; Mechanical ventilation (components of the WHO Ordinal Scale); Duration of hospital admission; Duration of severe symptoms; Sustained recovery; Contacts with the health services; Consumption of antibiotics; Effects in those with a positive test for COVID-19 infection; WHO Well-being Index.

Target date - recruit 3000 by Dec 2020

Outputs:

The Principle trial will recruit to target much quicker than using current methods if the team can receive this data, therefore answering the covid-19 treatment in the community question more quickly with the aim of preventing covid-19 sufferers being hospitalised so reducing NHS burden.

The trial’s current sample size is 3000 participants which the aim is to recruit by Dec 2020.

The trial team will ensure that trial results are disseminated to all relevant parties (regular updates to the Therapeutic Taskforce, UPH committee, NIHR, DoHSC) and dissemination via media channels and to trial participants, supported by the University of Oxford. Publications will be produced as quickly as possible.

The trial is of national and international relevance during this pandemic.

Processing:

The trial is run remotely, therefore removing the need for participants to be near to a GP practice. Screening and contact with the trial team is all done online. The trial team will, however, contact the participant’s GP for information from their summary care record, to ensure safe prescribing – for example, that they will not be allergic to the proposed treatments.

The processing of the data will be as follows:

• On a daily basis (seven days a week) NHS Digital will interrogate the Pillar 2 dataset and extract 200 individuals at random who are 50 or over who have received a positive COVID 19 test result in the previous 24 hours.
• The individuals will be England-only.
• Filters will be applied to remove patients who have registered a national opt-out, as well as special categories of people for whom the data should not be disseminated, such as prisoners.
• Individuals who have signed up for the Telephone Preference Service will need to be taken into account.
• The flow from NHS Digital to University of Oxford will be automated via a SEFT account.
• University of Oxford will use the data provided to make outbound to ask if the individuals would be interested in being recruited into the trial.
• The aim is to recruit 100 people into the trial per day.
• The number of individual contact details supplied by NHS Digital to University of Oxford will be reviewed once the take-up rate is better understood.

The trial team in Oxford will hold the data securely adhering to all IG Policies in the Dept., the team will call these contacts to inform them of the trial, screen, consent and randomise them.

The identifiable data received from NHS Digital will be deleted on a weekly basis as the trial team will no longer require it.

R1 (D09) - Data support to COVID-19 RCT — DARS-NIC-365354-R3M0Q

Opt outs honoured: No - consent provided by participants of research study, No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c),

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-03 – 2023-03 2020.05 — 2025.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No, Yes

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. COVID-19 Hospitalization in England Surveillance System
  3. COVID-19 Second Generation Surveillance System
  4. Civil Registration - Deaths
  5. COVID-19 Second Generation Surveillance System (Beta version)
  6. SUS plus - Admitted Patient Care (beta version)
  7. GPES Data for Pandemic Planning and Research (COVID-19)
  8. Cancer Registration Data
  9. Medicines dispensed in Primary Care (NHSBSA data)
  10. Civil Registration (Deaths) - Secondary Care Cut
  11. HES-ID to MPS-ID HES Admitted Patient Care
  12. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  13. COVID-19 Vaccination Status
  14. Demographics
  15. Electronic Prescribing and Medicines Administration (EPMA) data in Secondary Care for COVID-19
  16. Emergency Care Data Set (ECDS)
  17. Hospital Episode Statistics Critical Care
  18. Civil Registrations of Death - Secondary Care Cut
  19. Hospital Episode Statistics Admitted Patient Care (HES APC)
  20. Civil Registrations of Death
  21. COVID-19 Second Generation Surveillance System (SGSS)
  22. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  23. COVID-19 Electronic Prescribing and Medicines Administration (ePMA) in Secondary Care
  24. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  25. Hospital Episode Statistics Critical Care (HES Critical Care)
  26. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

This is a new application from the University of Oxford. University of Oxford request to use the NHS Digital Clinical Trials Service for access to data for a study entitled Randomised Evaluation of COVid-19 thERapY (RECOVERY).

In 2019 a novel coronavirus-induced disease (COVID-19) emerged in Wuhan, China. A month later the Chinese Center for Disease Control and Prevention identified a new betacoronavirus (SARS coronavirus 2, or SARS-CoV-2) as the aetiological (causing or contributing to the development of a disease or condition) agent. The clinical manifestations of COVID-19 range from asymptomatic infection or mild, transient symptoms to severe viral pneumonia with respiratory failure. As many patients do not progress to severe disease the overall case fatality rate per infected individual is low, but hospitals in areas with significant community transmission have experienced a major increase in the number of hospitalized pneumonia patients, and the frequency of severe disease in hospitalised patients can be as high as 30%. The progression from prodrome (an early symptom indicating the onset of a disease or illness - in this case usually fever, fatigue and cough) to severe pneumonia requiring oxygen support or mechanical ventilation often takes one to two weeks after the onset of symptoms. The kinetics of viral replication in the respiratory tract are not well characterized, but this relatively slow progression provides a potential time window in which antiviral therapies could influence the course of disease.

In early 2020, as the protocol for this trial was being developed, there were no approved treatments for COVID-19, a disease induced by the novel coronavirus SARS-CoV-2 that emerged in China in late 2019. The UK New and Emerging Respiratory Virus Threats Advisory Group (NERVTAG) advised that several possible treatments should be evaluated, including (but not limited to) Lopinavir-Ritonavir, Interferon β, and low-dose corticosteroids. These groups also advised that other treatments will soon emerge that require evaluation. A World Health Organization (WHO) expert group issued broadly similar advice. This trial allows reliable assessment of the effects of multiple different treatments (including re-purposed and novel drugs) on major outcomes in COVID-19.

This study aims to compare several different treatments that may be useful for patients with COVID-19. These treatments have been recommended by the expert panel that advises the Chief Medical Officer in England. Some are tablets and some are injections. Although these treatments show promise, nobody knows if any of them will turn out to be more effective in helping patients recover than the usual standard of care at hospitals (which all patients will receive).

The treatments, given in addition to the usual care at hospital, are: Lopinavir-Ritonavir (commonly used to treat HIV); dexathasone (a type of steroid, which is used in a range of conditions typically to reduce inflammation) and Hydroxychloroquine. Hydroxychloroquine, a derivative of chloroquine, has been used for many decades to treat malaria and rheumatological diseases. It has antiviral activity against SARS-CoV-2 in cell culture. As of 07/04/2020 - Azithromycin has been added as an arm to the trial (replacing a previous drug type called interferon beta). Azithromycin is a macrolide antibiotic. The macrolides inhibit the growth of bacteria and are often prescribed to treat rather common bacterial infections. Azithromycin has immunomodulatory properties that has shown benefit in inflammatory lung disease.

As of 16/04/2020 - a second randomisation arm has been added to the protocol.
This is for participants who meet certain simple physiological and inflammatory criteria - for example those in the cohort receiving oxygen therapy or oxygen saturations <92%) who can be randomised for a second time to receive either tocilizumab (an immunosuppressive drug, mainly for the treatment of rheumatoid arthritis) or control (both in addition to the treatment assigned at the first randomisation)

Other arms can be added if evidence emerges that there are suitable candidate therapeutics. Conversely, in some patient
populations, not all trial arms are appropriate (e.g. due to contraindications based on co-morbid conditions or concomitant medication); in some hospitals, not all treatment arms will be available (e.g. due to manufacturing and supply shortages); and at some times, not all treatment arms will be active (e.g. due to lack of relevant approvals and contractual agreements). Therefore,other treatments may be added to the protocol as time goes on and more information is gathered. This will not impact or change the level of data that is required from NHS Digital - as the cohort in the trial remains the same, regardless of what drug is being trialed.

Data from the trial will be regularly reviewed so that any effective treatment can be identified quickly and made available to all patients. The RECOVERY Trial team will constantly review information on new drugs and include promising ones in the trial.

Patients are eligible for the study if all of the following are true:

(i) Aged at least 18 years
(ii) Hospitalised
(iii) Proven SARS-CoV-2 infection.
(iv) Suspected SARS-Cov-2 infection. In general, SARS-CoV-2 infection should be suspected when a patient presents with
(i) typical symptoms (e.g. influenza-like illness with fever and muscle pain, or respiratory illness with cough and shortness of breath); and (ii) compatible chest X-ray findings (consolidation or ground-glass shadowing); and (iii) alternative causes have been considered unlikely or excluded (e.g. heart failure, influenza). However, the diagnosis remains a clinical one based on the opinion of the managing doctor.
(v) No medical history that might, in the opinion of the attending clinician, put the patient at significant risk if he/she were to participate in the trial

The anticipated scale of the epidemic is such that hospitals, and particularly intensive care facilities, may be massively overstretched. Under some models of pandemic spread, up to 50% of the adult population may fall sick over a period of 8-12 weeks, of whom around 10% may require hospitalisation. In this situation, even treatments with only a moderate impact on survival or on hospital resources could be worthwhile. Therefore, the focus of the COVID-19 Core Protocol is the impact of candidate treatments on mortality and on the need for hospitalisation or ventilation. Critically, the trial (and subsequent data collection) is designed to minimise the burden on front-line hospital staff working within an overstretched care system during a major epidemic. Eligibility criteria are therefore simple and trial processes (including paperwork) are minimised.

The primary objective is to provide reliable estimates of the effect of study treatments on in-hospital death (with subsidiary analyses of cause of death and death at various timepoints following discharge).

The secondary objectives are to assess the effects of study treatments on duration of hospital stay; the need for (and duration of) ventilation; and the need for renal replacement therapy.

Data from routine healthcare records (including linkage to medical databases held by organisations such as NHS Digital) and from relevant research studies (such as UK Biobank and Genomics England) will allow subsidiary analyses of the effect of the study treatments on particular non-fatal events (e.g. ascertained through linkage to Hospital Episode Statistics), the influence of pre-existing major co-morbidity (e.g. diabetes, heart disease, lung disease, hepatic insufficiency, severe depression, severe kidney impairment, immunosuppression), and longer-term outcomes (e.g. 6 month survival) as well as in particular sub-categories of patient (e.g. by genotype).

Follow-up information is to be collected on all study participants, irrespective of whether or not they complete the scheduled course of allocated study treatment. Study staff will seek Follow-up information through various means including medical staff, reviewing information from medical notes, routine healthcare systems, and registries.

The study team require the following information from NHS Digital:

- Prompt feed from SUS on hospital discharge
- Quarterly feed on HES data
- Quarterly feeds on civil registration data (death certificate information)

This study is supported by a grant to the University of Oxford from UK Research and Innovation/National Institute for Health Research (NIHR) and by core funding provided by NIHR Oxford Biomedical Research Centre, the Wellcome Trust, the Bill and Melinda Gates Foundation, Health Data Research UK, and the Medical Research Council Population Health Research Unit, and NIHR Clinical Trials Unit Support Funding.

The new trial has been classed as an Urgent Public Health Research Study. It is one of a round of projects to receive £10.5 million as part of the £20 million rapid research response funded by UK Research and Innovation, and by the Department of Health and Social Care through the National Institute for Health Research.

Yielded Benefits:

By the end of April 2020, the Recovery trial had successfully established over 160 sites across the UK and recruited over 8000 participants treated in hospital for Covid-19. The data linkage already established to received SUS+ and other data is providing important information to the Data Monitoring Committee on a weekly basis about patients' recovery (i.e. discharge from hospital), in-hospital death and procedures required. Provision of complete and reliable data to the DMC through May and early June 2020 is critical to allow robust assessment of the effects of the the trial treatments with a major contribution to these data expected from analysis of the routine health care data requested under this agreement.

Expected Benefits:

- improving the health of the whole population by sharing information and expertise, and identifying and preparing for future public health challenges/COVID-19 challenges

- researching, collecting and analysing data to improve understanding of this public health challenge, and come up with answers to public health problems arising from COVID-19

- providing reliable information on potential treatments for COVID-19 and potentially changing the standard of care that the NHS offers which could improve outcomes for many thousands of patients

Outputs:

COVID-19 is an emerging pathogen which presents a significant threat to the population in terms of increased morbidity and mortality, particularly among vulnerable groups such as those with pre-existing disease.

The primary objective is to provide reliable estimates of the effect of study treatments on in-hospital death (with subsidiary analyses of cause of death and death at various timepoints following discharge).

The secondary objectives are to assess the effects of study treatments on duration of hospital stay; the need for (and duration of) ventilation; and the need for renal replacement therapy.

The interim trial results will be monitored by an independent Data Monitoring Committee (DMC). The most important task for the DMC will be to assess whether the randomised comparisons in the study have provided evidence on mortality that is strong enough (with a range of uncertainty around the results that is narrow enough) to affect national and global treatment strategies. In such a circumstance, the DMC will inform the Trial Steering Committee who will make the results available to the public and amend the trial arms accordingly.

The data requested will be used to evaluate the efficacy and safety of the study treatments and will help shape the public health response. The rapid feed will be used to ensure that the trial Data Monitoring Committee have complete, up-to-date information on the major outcomes in the trial on which to base their decisions. If they find compelling evidence of efficacy or safety then that arm may be stopped and – if effective – added to standard care across the NHS.

All outputs produced will be in the form of aggregated reports with small number suppression applied.

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e: employees, agents and contractors of the Data Recipient who may have access to that data).

The University of Oxford will act as the trial Sponsor. The trial will be coordinated by a Central Coordinating Office within the Nuffield Department of Population Health staffed by members of the two registered clinical trials units – the Clinical Trial Service Unit and the National Perinatal Epidemiology Unit Clinical Trials Unit. Both of these units are at the University of Oxford. University of Oxford is the sole data controller for this piece of work. The data will be collected, analysed and published independently of the source of funding.

The initial proposal is to set up a feed of SUS APC data for the patients in a cohort list provided by University of Oxford. The process is as follows

• Details of the patient cohort (initial list and updates) to be emailed to a secure nhs.net account from another nhs.net account. It will be indicated that the email is in regards to the Oxford COVID-19 Study Trial. The initial list of patient identifiers will include study ID's and NHS numbers and date of birth.
• NHS Digital SUS team will report back any NHS Numbers which are not found in PDS (will do this for any new numbers that NHS Digital are sent as NHS Digital are sent them)
• Each week NHS Digital will provide a file of all records received by SUS for patients in the cohort (as updated with any new NHS Numbers)
• NHS Digital will send the extracts of data (baseline and deltas) to a MESH mailbox.
• The SUS APC extract will also include the date of death from PDS and the death status from PDS - this will all be sent as one extract in replacement of the Civil Registration Data Set for this iteration of the data sharing agreement.

Following on from the SUS APC dissemination - NHS Digital will do the following

• Link the cohort to Hospital Episode Statistics Data (HES) and provide back to University of Oxford

The linked data set will be sent back to Oxford via SEFT [Secure Electronic File Transfer System].


Further developments could include (and would be subject to approvals); the following:

• Automate the update of the patients in the cohort list
• Provide historic data for NHS numbers added to the cohort
• Use the Master Patient Service to try to identify the correct NHS Number based on patient name etc

All data shared under this agreement will be processed and stored in secure locations within England and Wales and will not be shared outside University of Oxford, other than in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

MR779: ASCEND (A Study of Cardiovascular Events iN Diabetes) — DARS-NIC-302994-C2Q2Y

Opt outs honoured: No - consent provided by participants of research study, No (Excuses: Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Informed Patient consent to permit the receipt, processing and release of data by NHS Digital, Health and Social Care Act 2012 – s261(2)(c)

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2019-10 – 2022-10 2017.09 — 2025.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Hospital Episode Statistics Critical Care
  5. Hospital Episode Statistics Outpatients
  6. Hospital Episode Statistics Accident and Emergency
  7. Hospital Episode Statistics Admitted Patient Care
  8. Civil Registration - Deaths
  9. Demographics
  10. Cancer Registration Data
  11. Emergency Care Data Set (ECDS)
  12. HES-ID to MPS-ID HES Accident and Emergency
  13. HES-ID to MPS-ID HES Admitted Patient Care
  14. HES-ID to MPS-ID HES Outpatients
  15. National Diabetes Audit
  16. Hospital Episode Statistics Accident and Emergency (HES A and E)
  17. Hospital Episode Statistics Admitted Patient Care (HES APC)
  18. Hospital Episode Statistics Critical Care (HES Critical Care)
  19. Hospital Episode Statistics Outpatients (HES OP)
  20. Civil Registrations of Death
  21. Diagnostic Imaging Data Set (DID)
  22. Medicines dispensed in Primary Care (NHSBSA data)
  23. Mental Health and Learning Disabilities Data Set (MHLDDS)
  24. Mental Health Minimum Data Set (MHMDS)
  25. Mental Health Services Data Set (MHSDS)

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

The aim of the British Heart Foundation (BHF)-funded ‘A Study of Cardiovascular Events iN Diabetes’ (ASCEND) randomised trial is to determine reliably whether aspirin (100mg daily or matching placebo) and/or supplementation with omega-3 fatty acids (1g capsule or matching placebo) safely prevents cardiovascular events and deaths in patients with diabetes, who do not already have clinically manifest arterial disease. Although aspirin is recommended for people with arterial disease, since it also causes bleeding, the balance of benefits and possible harms are not clear in this group with diabetes.

The study is funded by the British Heart Foundation and the packaged study treatment is provided free of charge by Bayer Pharma AG [100mg aspirin/matching placebo] and Abbott Products Operations AG [1g omega-3 capsule/matching placebo].

15,480 participants were randomized between June 2005 and July 2011 and median follow-up is currently ~4 years with a planned duration of at least 7 years. All serious adverse events (SAEs) are to be recorded among the randomised participants to allow detailed analyses of both the safety and efficacy of trial treatments. In order to reliably record and code reported SAEs during follow-up, as outlined within the study protocol, the team require clinical information about diagnoses and operations, including dates of occurrence. Access to electronic central records of hospital episodes will allow this complete and unbiased follow-up and appropriate intention-to-treat analyses.

The sensitive identifiable fields are required to ensure robust linkage to ensure that the records pertain to the correct participant, which is vital for the accuracy of the study data. The HES data will also provide additional confirmation of some participant reported events. The HES data relevant to the trial outcomes (heart attacks, strokes etc.) will be further followed up via GPs for additional information, and will be reviewed by study clinicians (who remain blind to treatment allocation) with the aim of confirming or refuting events.

Yielded Benefits:

For the on-treatment phase of the ASCEND study, the analyses have shown conclusively that aspirin reduces the risk of vascular events in primary prevention, as it does in people who already have cardiovascular disease, but these benefits are largely counter-balanced by the number of major bleeds caused by aspirin. This is an important finding with implications for many millions of people who have diabetes but have not yet had cardiovascular events. Previous clinical guidelines have varied in their recommendations about the use of aspirin for primary prevention because of a previous lack of clear evidence. The results of ASCEND now provide much needed clarity. The findings are likely to be widely incorporated into future guidelines for the prevention of cardiovascular events in people with diabetes both nationally and internationally. The World Health Organisation statistics detail 422 million people with diabetes in 2014, a rise of almost 400% since 1980. The prevalence of diabetes in the UK and global population is expected to continue to rise.

Expected Benefits:

ASCEND is a high profile trial (already widely referred to in international journals) whose results have the possibility of influencing national and international guidelines for the use of anti-platelet therapy in this very large patient group (currently at least 3M in the UK and over 300M worldwide). Access to the data requested will allow a complete and unbiased analysis of the benefits and hazards of allocation to aspirin and to omega-3 fish oils in the ASCEND study, thus enhancing the reliability of the study findings. The study results are expected in 2018 but any changes to treatment guidelines as a result of the ASCEND trial may take several years to emerge.

Outputs:

The main outputs from the research will be in the form of scientific reports of the results of the trial. If ASCEND can reliably demonstrate that aspirin and/or omega-3 FA safely reduce the risk of cardiovascular events, cancers and deaths in diabetic patients, without pre-existing occlusive arterial disease, this would be relevant to some hundreds of millions of people world-wide currently not receiving such therapy, and could save tens of thousands of lives each year. On the other hand, if the risks of serious bleeding outweigh or are similar in magnitude to the cardiovascular benefits in this group, then these risks could be avoided by the very large number of diabetic patients who are currently being treated with aspirin.

The results will be presented during 2018 at international scientific meetings and published in a prominent peer-reviewed medical journal within about a year. The arrangements are not yet finalised but the international meeting is likely to be one of: American Diabetes Association, European Society of Cardiology or the American Heart Association. The journal is likely to be The Lancet but again not finalised at this stage. In addition the BHF will play a role in the advertising and promotion of the results. The results are likely to be incorporated into an individual participant data meta-analysis of similar trials run by the Anti-thrombotic Trialists Collaboration.

All outputs will consist of aggregate data only with small numbers suppressed in line with HES analysis guide.

In addition to this the two pharmaceutical companies providing the medication and matching placebo for the study and some funds to cover the costs of packaging the treatment have an interest in seeing these treatments (aspirin and fish oils) properly evaluated in a large well run randomised trial. They will receive the same publically available results. If the study results show benefits for diabetic patients, the pharmaceutical companies may wish to use tabular data from the study to seek approval from the regulatory agencies for the marketing of these treatments to this group. The data provided would be aggregated with small numbers suppressed in line with the HES Analysis Guide.

If a submission is made to a regulatory agency, the Clinical Trial Service Unit at Oxford University would provide relevant information in the form of tabulations of numbers (for example: number of participants randomized, experiencing serious or other adverse events) with no individuals being identifiable in any submission. There would be considerable overlap between any tabulations provided to the companies and the published results, however the companies might ask for specific detail that were not considered necessary to publish. No participants will be identifiable in any information provided and the pharmaceutical companies do not have any influence in the research or the results. All data provided to the companies would be aggregate with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Information is collected routinely of the ~15,480 participants who were randomised between June 2005 and July 2011 by postal questionnaire however, over time, some participants stop returning questionnaires and this is more likely among people who have also stopped their study treatments. To minimise bias all participants need to be followed-up irrespective of whether they have been taking their study treatments and all events included in intention-to-treat analyses.

In order to comply with the EU Clinical trials directive, the data received will be transferred into the trial database by the person registered to receive data. The ASCEND trial database is study specific and is stored on an ASCEND specific server. The identifiable HSCIC data is stored in an encrypted TrueCrypt container to which access is granted on a "need to know" basis i.e. the level of access will depend on the staff role. All such access will be granted on the instruction of the Information Asset Owner for ASCEND. Access is routinely reviewed and revoked when the team member leaves ASCEND. The complete supplied HES data will need to be retained for 15 years (as per the ASCEND Protocol, section 2.4.6) as the team need to be able to trace all study medical events (some of which may be identified from HES data) back to source data to comply with the European Medicines Agency guidelines for good clinical practice and have this readily available during any Medicines and Healthcare Products Regulatory Agency (MHRA) inspection.

The ASCEND study team shall not, except as may be strictly necessary for carrying out the project, provide or otherwise make available the HES or ONS data to any third party or allow use of it or them by or on behalf of any third party, in whole or in part, whether by way of sale, resale, loan, transfer, hire or any other form of exploitation. This statement is intended to cover the situation where there may be a need to write to an individual participant’s GP for further clarification about a medical event or death to support the adjudication coding process undertaken by the study medical team. The event/death may have been supplied by ONS/HSICIC although the source of the event would not be supplied to the GP. Clinical trials involving Investigational Medicinal Products (IMPs) are legally required to comply with GCP which is regulated by the MHRA so this phrase also covers MHRA Good Clinical Practice inspections, during which an inspector may see an individual record with a medical event or death recorded which may have been supplied by ONS/HSCIC.

Cause of death data from the Office for National Statistics has been processed by NHS Digital through a separate Data Sharing Agreement and will be assessed separately when the agreement is due for review in March 2017.

MR1247 - Evaluating the age extension of the NHS Breast Screening Programme — DARS-NIC-147931-DT25Y

Opt outs honoured: Yes - patient objections upheld, Yes, No (Excuses: Section 251, Section 251 NHS Act 2006, , )

Legal basis: Section 251 approval is in place for the flow of identifiable data, Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7), , National Health Service Act 2006 - s251 - 'Control of patient information'.; Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., National Health Service Act 2006 - s251 - 'Control of patient information'. ; Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. ; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2011-05 – 2026-05 2016.05 — 2025.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. MRIS - Members and Postings Report
  5. Hospital Episode Statistics Admitted Patient Care
  6. MRIS - Scottish NHS / Registration
  7. Demographics
  8. Cancer Registration Data
  9. Civil Registration - Deaths
  10. MRIS - Personal Demographics Service
  11. MRIS - Bespoke
  12. HES-ID to MPS-ID HES Admitted Patient Care
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Civil Registrations of Death

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

Evaluating the age extension of the NHS Breast Screening Programme - Age Extension (AgeX) trial

The NHS Breast Screening Programme (NHSBSP) routinely invites women aged 50-70 years to come for three-yearly screening. Because of uncertainty about the effects of screening outside this age range, an England-wide cluster-randomised trial is under way to assess the risks and benefits of additional invitations for screening at ages 47 to 49 and, separately, after age 70 (currently 71-73).

Random allocation of small clusters of participants is used to determine (in a 50:50 ratio) which women are offered one additional screening invitation before age 50 and which are not, and which women are offered additional screening after age 70 and which are not. This trial will involve about 71 of the 81 breast screening units in England and will randomize at least two million women aged 47-49 and one million aged 71-73 to be invited for additional screening. Women will be followed up by routine electronic linkage to NHS and ONS mortality records to assess short-term and long-term effects of the additional screening on: patterns of investigation, detection and treatment of breast lesions; breast cancer incidence; breast cancer mortality; hospital admissions; and overall mortality.

The principal outcome for screening before age 50 and, separately, after age 70 will be breast cancer mortality, eventually subdivided by 5-year time periods (0-4, 5-9, 10-14 years, etc.) since random allocation. Subsidiary analyses will assess effects on other outcomes. The main results are expected in the mid-2020s.

When the main results of the trial are available results will be reported to the Advisory Committee on Breast Cancer Screening which oversees the NHSBSP and reports to government ministers. The NHSBSP sets the standards for the screening units and monitors performance through a national quality assurance network.

The data will be pseudonymised before analysis and will not be shared with any third parties.

The reason for this trial is to provide definitive evidence on an issue that has been the subject of controversy for over 15 years – specifically whether the harms of breast screening outweigh the benefits. Previous trials have evidenced the benefits without sufficiently evidencing the potential harms. Numerous claims and counter claims have been made and continue to be made emanating from such sources as patient groups, publications, scientific literature and in the media. The nature of the claims varies over time. For example, it may, at different times, be claimed that harms include increases in operations, hospital stays, related health episodes of specific types, etc. Such claims are typically varied with a lack of definitive supporting evidence.

This trial aims to amass and analyse sufficient evidence that will enable the final reports to provide definitive unequivocal evidence. Where such claims of harm have been made, the trial will investigate the validity and tailor the content of planned reports to provide responses. Due to the potentially wide variety of possible harms which might be attributed to screening, the trial requires wide ranging hospital episode data not restricted to specific types of episode.

The number of women involved in the trial is necessarily large in order to ensure that the findings of the trial are unequivocal. The sample size has been reviewed by numerous committees and accepted as being appropriate.

In terms of the number of years of data required, it is necessary to have data over such a long period because firstly, the screening programme currently offers women 7 screenings between the ages of 50 and 70 and the trial is investigating the effect of adding just one screen to the existing 7 routinely offered. Therefore the screening period is already more than 20 years and effects of screening are likely to become visible at least 10 years after the first screening. Secondly, it is essential for the trial design to have information on morbidity prior to randomization. It is well established that women with prior co-morbidities are less likely to attend for screening, when invited. It is stated explicitly in the protocol that groups of women will be excluded from the main analyses where there are known (on the basis of information collected before randomization) to be unlikely to accept an invitation for screening. It is therefore a fundamental requirement that the trial analyses HES data going back as far as is possible.

Yielded Benefits:

No benefits to date the study is due to be completed in the mid-2020s

Expected Benefits:

The aim of the trial is to assess reliably the risks and benefits of additional NHS invitations for breast screening before age 50 and, separately, after age 70. The results are expected to help determine future NHS policy on age at breast screening. The main results are not expected before the mid-2020s but interim results will be reviewed and the trial end date may be brought forward if the evidence is clear before then.

Public Health England will use the findings to inform government and influence policy. This will affect breast screening policy in the UK and influence policy in much of the rest of the world for decades after the results have published.

The benefits of interim analyses are that these will be used to monitor the protection and safety of trial participants in addition to feeding into the wider trial aims.

Outputs:

The primary output of the study will be findings disseminated by publications in peer-reviewed open-access journals and presented at medical conferences to academics, NHS national policy makers and on the web. The results are expected to help determine future NHS policy on breast cancer screening outside the 50-70 age group. The main results are not expected before the mid-2020s.

Outputs will include only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

As with any clinical trial, it is necessary to gather evidence incrementally throughout the course of the trial in order to check that the trial itself is not exposing participants to increased risk of harm or, conversely, to check for evidence of benefits. The trial end date is not fixed and may be brought forward if at any stage, sufficient evidence is obtained.

The outputs from the interim analyses will be annual reports to the Data Ethics and Monitoring Committee who may also request additional analyses within the scope of the clinical trial’s objectives if they identify the need. The Data Ethics and Monitoring Committee report any concerns about the trial or findings to the trial management group.

Processing:

To date, identifiable details have been supplied to NHS Digital (formerly known as HSCIC) in separate batches for flagging on NHS Digital's MIDAS system and NHS Digital has supplied periodic updates on deaths, cancers and exits from NHS registration. Approximately 2 million cohort members have been flagged to date with the number to rise to 2.5m.

Further batches of trial participants will be supplied as new participants are randomised into the trial on an ongoing basis.

In addition to the ongoing supply of notifications, NHS Digital will perform further linkage to Hospital Episode Statistics data and supply the linked data to the CEU.

All data received from NHS Digital is linked with trial participants’ records from the National Breast Screening System and PHE cancer outcome datasets.

The purpose for collecting the data is to assess the short-term and long-term effects of the additional screening on: patterns of investigation; detection and treatment of breast lesions; breast cancer incidence; breast cancer mortality; hospital admissions, and overall mortality.

The data will be held exclusively at the Cancer Epidemiology Unit (CEU) at the University of Oxford and used solely for the purpose of this project.

All data (core trial data, including personal details, flagging information, deaths, cancers, externally linked data, some admin data) is held in a central database. Several internal ID's exist so that data can be appropriately structured. No statistical analyses of the data are performed directly on this database. Direct access to the entire database is limited to the database manager. Access to personal identifiers is required to process externally linked data, and to prepare datasets for external linkage to HES, ONS, Cancer Registration, NHS Registration and NHS Screening records.

Pseudonymised analysis data is extracted from the database, either as database views or via text files. When accessing views directly, appropriate roles exist to limit access to the required view(s) only. Analysis datasets will have no individual level identifiers but may have a group identifier e.g. year recruited or site recruited. Analysis datasets will never contain any personally identifiable data e.g. name, NHS number etc. ONLY linkage datasets will require this information. If required year and month of birth will be used instead of full date of birth or death.

Epidemiological and health services research using routine NHS data: work programme of the Unit of Health-Care Epidemiology, Oxford University — DARS-NIC-315419-F3W7K

Opt outs honoured: No - data flow is not identifiable, No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-10 – 2022-09 2017.09 — 2025.03.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Office for National Statistics Mortality Data (linkable to HES)
  3. Civil Registration - Deaths
  4. HES:Civil Registration (Deaths) bridge
  5. Civil Registration (Deaths) - Secondary Care Cut
  6. HES-ID to MPS-ID HES Admitted Patient Care
  7. Civil Registrations of Death - Secondary Care Cut
  8. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The Unit of Health-Care Epidemiology (UHCE) was founded in 1963 as a research Unit that, among other activities, undertook research using routinely collected hospital admissions data and mortality data. The Unit’s overall aims, currently, are to undertake epidemiological and health services research, in particular by using routine NHS statistical data and by undertaking studies that use cohort methodologies.

Pseudonymised data is required to support the following work projects :-

1. Trends in admission rates in hospital specialties; trends in admission rates for individual diseases and operations

UHCE is undertaking research into trends in most hospital specialities, and for many individual diseases, distinguishing the extent to which increases or decreases have occurred; distinguishing between episode-based rates, multiple episodes per person, and person-based rates; assessing the extent to which changes represent or go beyond demographic changes in the resident population; profiling changes in the clinical content of specialties’ work and in lengths of stay (including the use of day case care); and, involving clinicians, attempting to explain the trends.

UHCE is also undertaking studies of trends in the use of hospital care by particular demographic groups including children, adolescents, and the elderly. In addition to the study of individual diseases, UHCE will also include studies of medical problems defined by behaviour and aetiology (e.g. self-poisoning in teenagers and young adults; accidental injury), where appropriate studying age and cohort effects as well as period effects.

The overall aim is to undertake a comprehensive study of trends in hospital admission rates in England from the 1960s to the present. The study will serve two main purposes. First, it will provide a detailed understanding of factors underpinning the long-term growth in hospital admission rates in the NHS: hospital admission rates in England have risen seemingly inexorably for decades. Second, it will provide epidemiological insights into trends in incidence and prevalence of diseases that warrant hospital care.


2. Geographical variation in hospital admission rates across England

UHCE have used the data to analyse the distribution of hospital admission rates across England. Where admission rates for a condition vary – particularly for chronic conditions like asthma and diabetes – linked data are invaluable in distinguishing whether the variation is attributable to differences in the number of individuals admitted or in the scale of multiple admissions per person. The geographical units would vary according to the topic (and in particular according to the incidence/prevalence of the condition). For example, local authority level would be appropriate for common conditions such as myocardial infarction, asthma and diabetes; county or regional level would be appropriate for less common conditions such as multiple sclerosis, motor neurone disease or haemophilia. UHCE intend to update the ‘atlases’ of disease across England.


3. Mortality rates for each diagnosis and operation

This data can be used to develop ‘a science of prognosis’. The aim is to study mortality rates following admission for each diagnosis and operation. UHCE will focus on diseases and operations for which there is likely to be interest in long-term trends, using the benefit of the five-decade runs of data. For example, in studies in the former Oxford region UHCE have shown substantial declines in 30-day and 90-day mortality after emergency admission for myocardial infarction and stroke.


4. Natural history of disease: disease associations

The aim is to use patient pathways within the data to investigate associations between diseases and, where relevant, between operations and diseases, to determine the likelihood that, given one clinical condition, other conditions may follow. The work programme will quantify known disease associations accurately; will test hypotheses about suspected associations; and will generate hypotheses about possible hitherto unrecognised relationships between diseases. Associations between diseases may indicate shared genetic susceptibility, e.g. leukaemia and other cancers in people with Down’s syndrome. Clinical conditions may be associated because one may predispose to the other, e.g. ulcerative colitis and large bowel cancer, benign and malignant breast disease.


5. Maternal, obstetric and perinatal factors and subsequent disease

One area of work currently proposed is a study of maternal and perinatal factors and subsequent asthma in the child; others include the study of perinatal factors and cerebral palsy and congenital malformations. The maternal and perinatal factors include, for example, mother’s history of disease, mother’s smoking in pregnancy, child’s birth weight, gestational age, and number of siblings. Similar studies have been done by UHCE on diabetes mellitus and on congenital conditions in the past.

Work is underway to analyse characteristics of the pregnancy and its ‘child’ outcomes for women with a range of diseases (e.g.mothers with diabetes); and to analyse the maternal and pregnancy characteristics of children with a range of diseases (e.g. maternal and pregnancy characteristics of children who develop diabetes, bronchiolitis, cancer, and other child outcomes).


Yielded Benefits:

This database and the research which uses it significantly contributes to the body of evidence and knowledge available which leads to changes in treatment, care and policies which are of benefit to the patient and the health care system. By way of further illustration, the following provides a small sample of publications and the impact they have had. 1. Seagroatt V, Goldacre MJ. Crohn's disease, ulcerative colitis, and measles vaccine in an English population, 1979-1998. J Epidemiol Community Health. 2003 Nov;57(11):883-7 Key point: This study directly influenced official NHS public engagement policy in relation to the measles vaccine. Detail: Publication of this study was followed immediately by a NHS Immunisation Information press release (11 Dec 2003), which stated: “A new study has confirmed that the introduction of measles vaccine in this country played no part in causing Crohn’s Disease and Ulcerative Colitis. The theory that measles vaccine was linked to bowel disease and then autism depended on a belief that measles virus damaged the bowel. This study adds to the available evidence that says that this is not the case.” 2. Martin NG, Iro MA, Sadarangani M, Goldacre R, Pollard AJ, Goldacre MJ. Hospital admissions for viral meningitis in children in England over five decades: a population-based observational study. Lancet Infect Dis. 2016;16:1279-87 Key point: The study was reported directly to Public Health England for use as evidence in communication with the general public concerning the need to maintain the highest possible MMR vaccination levels. Detail: This study of 50-year trends in hospital admission rates for viral meningitis in childhood documented the impact of MMR on viral meningitis and an upsurge in the 2000s when MMR coverage dropped following the Andrew Wakefield scandal; it also documented trends in several other viral aetiologies. 3. Seminog OO, Goldacre MJ. Risk of pneumonia and pneumococcal disease in people hospitalized with diabetes mellitus: English record-linkage studies. Diabet Med. 2013 Dec;30(12):1412-9. doi: 10.1111/dme.12260. Epub 2013 Jul 24 Key point: This study directly informs the position statements of high-profile diabetes charities in the UK. Detail: Following publication of this study, position statement from Diabetes UK: “All people with diabetes over the age of two years should be offered the pneumococcal vaccine.” 4. Goldacre RR. Associations between birthweight, gestational age at birth and subsequent type 1 diabetes in children under 12: a retrospective cohort study in England, 1998-2012. Diabetologia. 2018;61(3):616-625 Key point: High birthweight for gestational age and low gestational age at birth were both found to be significantly associated with subsequent type 1 diabetes. Detail: These findings demonstrated the potential role of gestational and early life environmental risk factors in the pathogenesis of type 1 diabetes, including the potential roles of insulin sensitivity and gut microbiota. 5. Goldacre MJ, Maisonneuve JJ. Mortality from meningococcal disease by day of the week: English national linked database study. J Public Health (Oxf). 2013 Sep;35(3):413-21. doi: 10.1093/pubmed/fdt004. Epub 2013 Feb 1 Key point: This study directly informed the legal debate about the 7-day NHS and the "weekend effect". Detail: This study featured in various mainstream news outlets at the time and was referenced in the High Court judicial review case between NHS junior doctors, the British Medical Association and the Secretary of State for Health in relation to the new NHS contract for junior doctors. The study was described by Mr Justice Green as a "trenchant" piece of evidence. 6. Dharmasena A, Hall N, Goldacre R, Goldacre MJ. Time trends in ophthalmia neonatorum and dacryocystitis of the newborn in England, 2000-2011: database study. Sex Transm Infect. 2015;91:342-5 Key point: This study demonstrated to Public Health England that linked hospital data are the best available data for routinely monitoring the national incidence of newborn conjunctivitis. Detail: The annual figures for this notifiable disease that were reported during the study period under statutory health protection regulations drastically underestimated the actual occurrence of this disease among individuals in hospital (only 1 in 20 cases were reported to Public Health England). 7. Mukhtar TK, Yeates DR, Goldacre MJ. Breast cancer mortality trends in England and the assessment of the effectiveness of mammography screening: population-based study. J R Soc Med. 2013 Jun;106(6):234-42 Key point: This study directly informed the public debate about breast cancer screening. Detail: Publication of this study was immediately followed by an NHS news release, which stated: “There is a great deal of information on both the pros and cons of screening…This study provides additional valuable population data to inform the breast cancer screening debate.” 8. Hallifax RJ, Goldacre R, Landray MJ. Trends in the Incidence and Recurrence of Inpatient-Treated Spontaneous Pneumothorax, 1968-2016. JAMA. 2018;320(14):1471-1480. doi:10.1001/jama.2018.14299. Key point: This study is immediately expected to enable general practitioners and respiratory specialists to make more informed prognoses about the risk of pneumothorax recurrence within specified time periods based on the patient’s comorbidity profile and demographic characteristics. Detail: The study of pneumothorax incidence and recurrence in England has put the current rates of this disease into a 50-year historical context as a matter of public record. The linked national data enabled precise estimations of the likelihood of recurrence based on patient characteristics such as age, sex and the presence of comorbid chronic lung disease.

Expected Benefits:

UHCE’s database and research is unique. Nowhere else can research use hospital data from 1963 to present day to provide such a complete picture of the progress of secondary care and cover such a large percentage of the history of the NHS.

With 50 years’ worth of hospital data, research into areas such as hospital trends, mortality rates, disease history and maternal disease links, that could take years to complete, can be achieved extremely efficiently. This means UHCE can react extremely swiftly to issues arising for the health care system or from patients. For example, in the questions over the ‘week-end effect’, UHCE was able to publish on mortality rates for meningococcal meningitis. There are few other diseases which can act as such a good marker to show the difference between expert treatment or no or suboptimal treatment. The study showed no evidence of an adverse day of the week effect.

This database and the research which uses it significantly contributes to the body of evidence and knowledge available which leads to changes in treatment, care and policies which are of benefit to the patient and the health care system.

There are many examples of benefits; the following provides just a small sample;

1.Hospital Trends:
One of the overall aims is to undertake a comprehensive study of trends in hospitals from the 1960s to now. This will provide policy makers with an understanding of the factors that have led to the seemingly inexorable rise in hospital admissions over the decades, the trends in which diseases are being treated and the changes in mortality rates from these diseases. This programme of research will form a body of publications which will be of benefit to clinicians and policy makers who want to understand impacts such as the use of prevention versus treatment in particular conditions.

There are hundreds of publications using this data for this aim; the following are just a few some examples;
I. Publications on hospital admissions for children
Using this unique database research was able to look at the long term trends in hospital admissions for children with various conditions. In particular to document the beneficial impact of the MMR vaccination when uptake was high, and the negative impacts when MMR coverage dropped. This research was reported into NICE as well as the Department of Health’s Joint Committee on Vaccination and Immunisation in order to add to the information used in polices to reduce disease rates.

II. Public health finding for the Department of Transport
This research looked at the hospital admission rates over time compared with falling police reported incidents. UHCE were able to report back to the Department that the hospital data showed no such fall and advised the department and the Chief Medical Officers that there was a need for closer collaboration with official statistics in order to fully understand the numbers of injuries and fatalities on the roads and so improve road safety.

III. Public health finding on Rickets
UHCE was able to show that admission rates in 2011 were higher than at any time since the 1960s. This publication adds to the evidence and knowledge used by public health policy makers in advising the general public in how to avoid this preventable disease.

2. Geographical Variation:
Another aim is to study geographical variation in hospital rates, some cases to study of the epidemiology of a particular disease or to investigate potential clinical variations in treatment and care. Again, these outputs cover a large amount of time and so are of benefit in adding robust research to the evidence base in these areas for the improvement of patient outcomes. An example of a past publication, which was aimed at ENT surgeons, was about the huge variation in tonsillectomy rates. As this was unlikely to be warranted by epidemiology it was more likely to be variation between clinicians. NIHR went on to use this research as an example of variation which could be used by commissioners and clinicians to identify cost savings.

3. Mortality rates:
There have been many publications on mortality rates with many aimed at clinicians. For example, a study showing the elevated mortality rate following admission for anorexia nervosa adding to the evidence that this can be a life threatening disorder and this was published in journals specifically aimed at clinicians who treat these disorders.
Being able to provide accurate knowledge mortality risk provides benefits in terms of (i) its value in informing clinicians, public health and the public about success (or lack of it) in health-care performance, and (ii) its value in informing clinicians about the likely course of illness and risk in their individual patients.

4. Disease:
It is crucial that clinicians, researchers, patients and public-health policymakers are made aware of important associations between diseases in order to prevent multi-morbidity and to reduce "years of life lost" and "years lost due to disability" through identification of at-risk groups of the population. This crucial database and associated research provides this opportunity. The following are examples of recent UHCE studies in this area;
- Significantly increased risk of primary malignancies in people with non-melanoma skin cancers, particularly the young
- Severe under-diagnosis and under-treatment of cataract and other sight disorders in people with dementia
- Significantly increased risk of dementia in people with obesity
- Significantly increased risk of autoimmune disease in people with vitamin D deficiency, and vice versa
- Significantly increased risk of biliary tract and liver complications in people with polycystic kidney disease

By way of further illustration, the following provides a small sample of publications and the impact they have had.

1. Seagroatt V, Goldacre MJ. Crohn's disease, ulcerative colitis, and measles vaccine in an English population, 1979-1998. J Epidemiol Community Health. 2003 Nov;57(11):883-7
Key point: This study directly influenced official NHS public engagement policy in relation to the measles vaccine.
Detail: Publication of this study was followed immediately by a NHS Immunisation Information press release (11 Dec 2003), which stated: “A new study has confirmed that the introduction of measles vaccine in this country played no part in causing Crohn’s Disease and Ulcerative Colitis. The theory that measles vaccine was linked to bowel disease and then autism depended on a belief that measles virus damaged the bowel. This study adds to the available evidence that says that this is not the case.”

2. Seminog OO, Goldacre MJ. Risk of pneumonia and pneumococcal disease in people hospitalized with diabetes mellitus: English record-linkage studies. Diabet Med. 2013 Dec;30(12):1412-9. doi: 10.1111/dme.12260. Epub 2013 Jul 24
Key point: This study directly informs the position statements of high-profile diabetes charities in the UK.
Detail: Following publication of this study, position statement from Diabetes UK: “All people with diabetes over the age of two years should be offered the pneumococcal vaccine.”

3. Goldacre MJ, Maisonneuve JJ. Mortality from meningococcal disease by day of the week: English national linked database study. J Public Health (Oxf). 2013 Sep;35(3):413-21. doi: 10.1093/pubmed/fdt004. Epub 2013 Feb 1
Key point: This study directly informed the legal debate about the 7-day NHS and the "weekend effect".
Detail: This study featured in various mainstream news outlets at the time and was referenced in the High Court judicial review case between NHS junior doctors, the British Medical Association and the Secretary of State for Health in relation to the new NHS contract for junior doctors. The study was described by Mr Justice Green as a "trenchant" piece of evidence.

4. Mukhtar TK, Yeates DR, Goldacre MJ. Breast cancer mortality trends in England and the assessment of the effectiveness of mammography screening: population-based study. J R Soc Med. 2013 Jun;106(6):234-42
Key point: This study directly informed the public debate about breast cancer screening.
Detail: Publication of this study was immediately followed by an NHS news release, which stated: “There is a great deal of information on both the pros and cons of screening…This study provides additional valuable population data to inform the breast cancer screening debate.”









Outputs:

All outputs will be aggregated analysis, with suppression in accordance with the HES analysis guide. Such data will appear within research papers, academic journals and conference presentations. The presentation format of that data may vary – from individual tabulation, through to geographical presentation through the Atlases mentioned previously.

Such analysis is derived from data provided by UHCE, who receive requests for aggregated, non-sensitive, non-identifiable tabulated data in fulfilment of its research work programme (as detailed above). These tabulations require statistical analysis prior to being provided to researchers, whilst equivalent in format to those provided by NHS Digital (hence could not be provided directly).

UHCE does not solicit requests for tabulations through any web advertising or promotional activity. It does welcome collaborative research work with academic researchers on topics that can be covered by its existing research themes already described in this document. For researchers outside the UHCE but working with the UHCE, the UHCE will only provide aggregated tabulations, not individual-level records. It does not and will not provide UHCE tabulations on request to people outside the UHCE for any purpose other than research.

UHCE have a long track record in published work in the programme of work described in this document. More information can be found here https://www.uhce.ox.ac.uk/uhce/publications.php

The Unit was, historically, very closely associated with the Regional tier of the NHS and with the Department of Health. Although the UHCE is part of Oxford University, it was based on the Oxford RHA’s site from 1963 until the reorganisation of Regional Health Authorities in the mid-1990s. In particular, the UHCE worked closely with the Oxford RHA on medical statistics, record linkage (including the Oxford Record Linkage Study (ORLS), and health services research. From 1998-2005, the Unit had strong service links with the Department of Health’s National Centre for Health Outcomes Development (NCHOD) - the Unit Director, directed the work programme of the Oxford site of NCHOD. As part of the NCHOD work, the DH commissioned the UHCE to construct and analyse English national record-liked HES files, with HES-to-HES linkage and HES-to-mortality linkage, along the lines of the Oxford Record Linkage Study.

The Unit Director was also Co-founder and Scientific Director of the South East England Public Health Observatory from its inception in 2000 until 2005. The UHCE has run a continuous work programme of rolling research, notably using hospital statistics, mortality data, and record linkage, from 1963 to the present. It is part of the University of Oxford’s Department of Public Health (now, as from 2013, the Nuffield Department of Population Health).

Processing:

Only substantive employees of the University of Oxford will have access to the data and only for the purposes described in this document. The University of Oxford will amend this agreement if the requested data is needed for research which does not fall under the themes described here.

Background of the datasets used in these projects:
UHCE undertakes research on hospital statistics, and on mortality, using four different datasets. These are the :-
a. Oxford Record Linkage Study, phase 1 (1963-1998) (ORLS1);
b. the Oxford Record Linkage Study, phase 2 (1989/90-2013/14) (ORLS2);
c. the Hospital In-patient Enquiry for England (1968-1985) (HIPE);
d. Hospital Episode Statistics (HES) for England, 1989/90-2013/14 (provided by NHS Digital)

These four datasets are not linked to one another as individual-level records.

These four datasets constitutes the longest run of hospital data in England. The UHCE dataset for the ORLS spanning 1963-2013/14 is the longest run of hospital data in England at regional level and is the only long-running dataset in England with record linkage going back decades (to 1963).

UHCE holds ONS data which was provided directly by ONS. This will be the first time that UHCE are requesting ONS data from NHS Digital.

In the development and use of large datasets of routine health data, UHCE undertakes original research; it collaborates with others on research projects; and it provides support as required to the NHS, DH and their information functions.

Processing:
NHS Digital will supply pseudonymised HES and the ONS (including month and year of death) data to UHCE via a secure file transfer system.

The data are held in individual SQL databases, subject to individual user control. The HES and ONS national data are processed on receipt so as to have the same database configuration, in order to ‘look like’ the hospital and mortality data in the ORLS. This is done to facilitate the running of the same software across all the databases.

The datasets are all de-identified and are held securely within the UHCE and no individual-level records are ever provided to anyone outside the UHCE.

The datasets are not linked to one another as individual-level records. When there is a need to construct studies based on data that span the time frame of the years covered by the different datasets – typically in, for example, studies of hospital admissions across five decades – the UHCE software packages are invoked to run the analyses within each dataset to produce aggregated statistical results. At the stage of the aggregated statistics, UHCE software templates are used to bring together the tabular results that span individual results from within each dataset – e.g. electronic tables for admission rates in the years 1968-1985, 1989-1998, 1989/90-2013/14 are brought together – into combined tables for the whole period 1968-2013/14.

UHCE have suites of software, developed over many years in the UHCE, which can be used to run the trend analyses in a highly automated way. Researchers do not need to ‘see’ individual level records in order to ‘queue and run’ the software. The UHCE has developed a ‘front end’ to the analytical software such that, for each new run, the member of staff uses a menu. The menu gives the operator a choice of selecting the ICD code and diagnostic code (or equivalent for operations), the required age groups, selection of gender, selection of people, the calendar or financial years required, whether to select the primary diagnosis or all diagnostic fields, whether to select all cases or just electives or just emergencies, and so on. A suite of templates and data manipulation tools then analyses the data in the four files separately (ORLS1, ORLS2, HIPE, HES 1989/90-2013/14) automatically. When the results in each separate dataset have run, another suite of templates and data manipulation tools automatically ‘pulls together’ the results from each set of electronic tables and combines them into tables and graphs giving (seemingly) continuous runs of trends

Similarly, in studies that require data for the full length of the ORLS (1963-2013/14), UHCE software packages are invoked to run the analyses within ORLS1 and, separately, within ORLS2 to produce aggregated statistical results based on the data within each of the two datasets separately. At the stage of the production of the aggregated statistics, UHCE software templates are used to bring together the tabular results that span individual results e.g. electronic tables for admission rates in the years 1963-1998 and for 1999-2013/14 – into a combined table for the whole period 1963-2013/14.

Outputs are therefore all aggregated data, suppressed in line with the HES analysis guide. No record level data may be extracted from the server.

Access to the data is controlled through specific user access controls. Each user has to complete a staff declaration form which ensures that the user is aware of their obligations in relation to the data (eg: to not attempt any re-identification, to use the data solely for the purposes of the individual project).

The information systems used by the Unit of Health-Care Epidemiology are secure and comply with the principles outlined in BS7799 (The Code of Practice for Information Security Management).

All the datasets proposed for use in these studies are pseudonymised. They include no direct identifiers, no NHS number, and the smallest geographical unit associated with each record is that of the person’s Local Authority area of residence (of which there are currently 354 in England).

UHCE have no requirement to re-identify the individuals within the datasets and will make no attempt to re-identify.

UHCE will not share any record level data and all outputs will be aggregated with small numbers suppressed in line with the HES analysis guide.

UHCE will not link the data provided with the dataset described, or any other datasets.

The processing of ONS data is in accordance with standard ONS terms and conditions.

MR565: The Million Women Study - addition of only 1 year complete HES data for 2018/2019. — DARS-NIC-389134-S8L1C

Opt outs honoured: No - consent provided by participants of research study, No - data flow is not identifiable, No (Excuses: Reasonable Expectation, Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(2)(c)

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2020-05 – 2021-07 2017.06 — 2025.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No, Yes

Datasets:

  1. MRIS - Cause of Death Report
  2. Hospital Episode Statistics Admitted Patient Care
  3. MRIS - Members and Postings Report
  4. MRIS - Cohort Event Notification Report
  5. MRIS - Scottish NHS / Registration
  6. MRIS - Bespoke
  7. Civil Registration - Deaths
  8. Demographics
  9. Cancer Registration Data
  10. MRIS - Flagging Current Status Report
  11. HES-ID to MPS-ID HES Admitted Patient Care
  12. Civil Registrations of Death
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Mental Health and Learning Disabilities Data Set (MHLDDS)
  15. Mental Health Minimum Data Set (MHMDS)
  16. Mental Health Services Data Set (MHSDS)
  17. NDRS Cancer Registrations

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

The Million Women Study (MWS) is a national study of women’s health funded by Cancer Research UK and the Medical Research Council. The study involves 1.3 million UK women, recruited in 1996-2001, who have given written consent for follow up of their health through their medical records, to examine how reproductive and lifestyle factors affect their future health.

Yielded Benefits:

The Million Women Study research using linked health data has already directly influenced health care. Results showed, for example, that women using hormone replacement therapy are at increased risk of breast cancer; this work, published in 2003, was shared with the Medicines and Healthcare Regulatory Agency and helped inform changes in prescribing guidance both for the UK and elsewhere. It is estimated that tens of thousands of cases of cancer worldwide have been avoided as a result of the subsequent fall in use of hormone therapy. Another example where NHS Digital data contributed to an influential paper was in showing that risk of blood clots after surgery was far higher, and lasted for much longer, than had been previously thought. This work is helping to inform European surgical care guidelines. MWS results on how characteristics of individuals affect participation and outcomes of bowel cancer screening are being incorporated into screening programme development. Recent work on the costs to the NHS of obesity-related conditions, and on breast cancer risk in relation to night shift work, has direct public health relevance. Participants in the Million Women Study are the first generation of women in the UK to have smoked to the same extent as a man and our findings show that female smokers died about 10 years earlier than non-smokers. These effects are much greater than had been reported previously and influence policy.

Expected Benefits:

The Million Women Study research using linked health data has directly influenced health care. Results showed, for example, that women using hormone replacement therapy are at increased risk of breast cancer; this work helped inform changes in prescribing, and it is estimated that tens of thousands of cases of cancer worldwide have been avoided as a result of the subsequent fall in use of hormone therapy.
Another example where HSCIC data contributed to an influential paper was in showing that risk of blood clots after surgery was far higher, and lasted for much longer, than had been previously thought. This work is helping to inform European surgical care guidelines.
Other influential MWS work with direct health care benefits is looking at how to best implement a screening programme for bowel cancer following a study into how characteristics of individuals affect participation and outcomes of screening.

Outputs:

The data set (HES data) will be used to examine relationships between lifestyle and reproductive factors (collected via questionnaire data) and a wide range of outcomes. These outcomes would mainly consist of a variety of cancer diagnoses, hip fractures and joint replacements and cardiovascular disease. CEU plan to publish their anonymised findings in peer reviewed scientific journals so that they can contribute to knowledge of common diseases and causes of hospital admissions.
CEU have successfully published papers using data from their previous HES extract (ET2535) and wish to continue using similar data together with extra information, to increase the understanding of patterns of disease groups including cancer diagnoses, joint replacements, fractures and cardiovascular disease. Further information can be found on the website at www.millionwomenstudy.org

Processing:

The cohort participants are already flagged with the HSCIC, and this will be used to link to the HES data.
Data will be used by teams of researchers/statisticians in the Cancer Epidemiology Unit (CEU) at the University of Oxford. The data will be used solely within the CEU and will not be shared with any other organisation.

MR1224 - HPS 3 / TIMI 55: REVEAL (Randomized EValuation of the Effects of Anacetrapib through Lipid-modifica) — DARS-NIC-147757-8SVGP

Opt outs honoured: No - consent provided by participants of research studYes, No

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Informed Patient consent to permit the receipt, processing and release of data by NHS Digital, Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), , Informed Patient consent to permit the receipt, processing and release of data by NHS Digital; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(c); Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2011-04 – 2021-12 2016.06 — 2025.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Flagging Current Status Report
  5. MRIS - Members and Postings Report
  6. MRIS - Personal Demographics Service
  7. Cancer Registration Data
  8. Civil Registrations of Death
  9. Demographics
  10. Emergency Care Data Set (ECDS)
  11. Hospital Episode Statistics Admitted Patient Care (HES APC)
  12. Medicines dispensed in Primary Care (NHSBSA data)
  13. National Diabetes Audit

Type of data: Identifiable

Objectives:

The study aims to randomise at least 30,000 (6,500 in the UK) aged 50 years or older with pre-existing vascular disease, to receive either anacetrapib 100mg daily or matching placebo for a median of 4 years' follow up. The primary aim is to assess the effect of lipid-modification with anacetrapib on major coronary events (MCE - defined as coronary death, myocardial infarction or coronary revascularization).

Yielded Benefits:

MBRRACE-UK - Delivering the National Maternal, Newborn and Infant Clinical Outcome Review Programme - National Surveillance of Perinatal Deaths — DARS-NIC-359651-H3R1P

Opt outs honoured: Yes - patient objections upheld, Yes, No (Excuses: Section 251 NHS Act 2006, , )

Legal basis: Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2017-04 – 2020-03 2017.06 — 2025.03.

Access method: Ongoing

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Birth Notification Data

Type of data: Identifiable

Objectives:

Purpose 1: Processing for MBRRACE-UK purposes

The Maternal, Newborn and Infant Clinical Outcome Review Programme (MNI-CORP) is a national programme, delivered by the MBRRACE-UK collaboration, which aims to systematically assess quality and stimulate improvement in safety and effectiveness of maternal, newborn and infant healthcare by enabling clinicians, commissioners and policy makers to learn from adverse events and good practice. The purpose of the programme is to (1) monitor, through population surveillance, the frequency of deaths in relation to maternal, perinatal and infant mortality (2) review clinical practice and assess quality of care for women and babies who have died and those who are seriously ill (mortality and morbidity) through confidential enquiries, with the aim of identify factors that can be attributed to suboptimal clinical care, and also examples of good practice.

MBRRACE-UK received from the HSCIC data extracts from the NHS Numbers for Babies (NN4B) dataset (2013 & 2014 births) and the Personal Demographic Services (PDS) dataset (2015, 2016 and 2017 births to date) and needs to retain these copies (to carry out time trend analyses) and also requires further extracts of equivalent annual data going forward to 2021. MBRRACE-UK will link these dataset with statutory birth, stillbirth and infant death notification data supplied under a separate Data Access Agreement with University of Oxford from the Office for National Statistics in order that essential additional data items are available on an individual level, most importantly gestational age at birth and ethnicity (these are not available in the ONS data and can only be obtained from NN4B/PDS data). This linkage process generates the denominator data for the calculation of 'crude' and 'stabilised & adjusted' perinatal mortality rates; individual level data are required for these calculations. The numerator data come from clinical data about perinatal deaths collected directly by MBRRACE-UK from NHS Trusts and Health Boards. The two additional variables derived from PDS data are essential to enable 'adjusted' perinatal mortality rates to be calculated for commissioning and service delivery organisations down to individual hospital level which take into account the risk profile of the population served by those commissioning and service delivery organisations. The risk profile includes high risk pregnancies which are defined by gestational age at birth and the ethnicity of the population served, as well as other risk factors for example maternal age. This enables 'fairer' comparisons of mortality rates between hospitals and organisations which deal with 'high risk' cases, for example tertiary referral centres which have a higher proportion of preterm births compared with smaller 'district general hospital' type hospitals which would refer high risk pregnancies (for example those at risk of preterm birth) to tertiary hospitals. 'Crude' comparisons which fail to take the risk profile of the different patient populations into account lead to spurious conclusions concerning relative mortality rates and variations in outcomes. Data are required at an individual identifiable level to enable both the linkage and adjusted analyses to be performed.

The linkage to the linked ONS/PDS data also allows MBRRACE-UK to identify deaths and missing information which have not been notified directly to MBRRACE-UK and using this information MBRRACE-UK is able to chase up missing cases to collect the relevant clinical information.

Purpose 2: Processing for NNAP purposes

MBRRACE-UK will produce aggregated data with small number suppression, in line with HES analysis guide, and supply it to the National Neonatal Audit Programme (NNAP) based at the Chelsea and Westminster Hospital who are acting as data processors for the National Neonatal Audit Programme under contract to HQIP and the Royal College of Paediatrics and Child Health. This activity is separate to the primary purpose for MBRRACE-UK receiving and processing the data. However, as a consequence of the processing activities involved in MBRRACE-UK’s primary purpose, MBRRACE-UK will produce a dataset that, with minimal additional processing, would meet NNAP’s requirements and thus negate the need for NNAP to duplicate this complex data processing. Further details relating to the use of the aggregated data in support of the aims of NNAP can be found in the latest NNAP Annual Report published on the NNAP website.

http://www.rcpch.ac.uk/improving-child-health/quality-improvement-and-clinical-audit/national-neonatal-audit-programme-nn-3

Yielded Benefits:

The national perinatal mortality surveillance is conducted by MBRRACE-UK in the context that the UK has one of the highest rates of perinatal death (deaths around the time of births which include late fetal losses, stillbirths and neonatal deaths) and infant deaths (deaths from birth to one year of age) in Europe. Recent figures published in the Lancet places the UK 20th out of 28 for highest stillbirth rates in Europe and it has been estimated that had the UK had a similar neonatal mortality rate to the rate in Sweden, in 2013 1,000 fewer babies would have died. The following provides some examples (not an exhaustive list) of the benefits arising from the findings of the MBRRACE-UK programme. 1. The impact of MBRRACE-UK reports on national policy and practice In March 2015 Dr Bill Kirkup published his report of the investigation of perinatal and maternal deaths in the Universities Hospitals of Morecambe Bay – the ‘Morecambe Bay Inquiry’ Report (1). As part of the recommendations of that report it was noted that good information on pregnancy outcomes (including deaths) is a key driver for improvements in the quality of care provided for pregnant women and newborn babies. This is the role of the MBRRACE-UK programme. The findings of the high rates of perinatal deaths in England, the variation between trusts and the results of the Kirkup enquiry resulted in an independent national maternity services review which was launched in March 2015. The findings of this review were published as the ‘Better Birth’ Report in 2016 and MBRRACE-UK surveillance and confidential enquiry findings were highly cited throughout the report as evidence of the need for changes to maternity services to improve the care provided and as a consequence the outcomes for mothers and babies. It was against this background that in November 2015 the Secretary of State for Health announced additional funding for maternity services and the national ambition to reduce the maternal and perinatal mortality rate by half by 2030; this was subsequently redefined in 2016 to achieve this ambition by 2025, with a 20% reduction by 2020. This ambition was re-iterated in the NHS five year forward plan in 2018. MBRRACE-UK provides the mechanism by which the achievement of the ambition can be monitored. It is the role of MBRRACE-UK to monitor progress towards the national ambition and to identify Trusts which are failing to achieve adequate progress. For the MBRRACE-UK second national perinatal surveillance report (published in May 2016), Ben Gummer, the then Parliamentary Under-Secretary of State for Care Quality wrote in his Foreword to the report: “I want to pay tribute to the remarkable academic achievement that is MBRRACE-UK and underline the influence it is now having on the formulation of policy and impact on services. By providing a consistent and robust evidence base on which to take decisions, MBRRACE-UK is already saving lives.” In the 2018 maternal mortality report, reiterated in the 2019 report, we identified the continuing ethnic inequalities in maternal death (there are similar inequalities in perinatal deaths) where women who are Black are five times more likely to die and women who are Asian are over twice as likely to die as a maternal death than their white counterparts. Disseminating this information via our technical report, lay reports and selected information via twitter has led to an enormous amount of policy activity by NHS England/Improvement; the Department of Health and Social Care; the Cabinet office; and groups of individual Black women who have set up their own campaigns, for example the first Black Women’s Maternal Health Awareness Week was run this year organised by the Five X More campaign. 2. The impact of MBRRACE-UK findings on national guidelines and clinical toolkits: Along with NICE, the Royal College of Obstetricians and Gynaecologist (RCOG) are responsible for producing national guidance for care during pregnancy, labour, birth and postpartum. A number of guidelines have been developed or updated as a consequence of MBRRACE-UK findings. For example, two updated RCOG ‘Green-Top Guidelines’ were released with direct relevance to findings reported in the 2014 and 2017 maternal reports: (i) Prevention and management of post-partum haemorrhage (GTG 52) (RCOG 2016a); and (ii) Blood transfusion in obstetrics (GTG 47) (RCOG 2015)). In response to findings of high rates of maternal deaths from sepsis from our reports the UK Sepsis Trust released six new clinical toolkits specifically for women in pregnancy. Tools are available for out of hours/telephone triage, community midwives, pre-hospital/ambulance services, general practice, emergency departments and acute medical units, as well as acute hospital inpatients. Following the publication of the first MBRRACE-UK national perinatal surveillance report in June 2015 NHS England launched the ‘Saving Babies’ Lives Care Bundle’ in March 2016 which was aimed specifically at ensuring Trusts put in place a series of key actions to prevent stillbirths which will also have an impact on neonatal and infant morbidity. The identification in the MBRRACE-UK reports that the majority of perinatal deaths occur in preterm births, when version two of the Care Bundle was released in March 2019, it included a new action and target aimed at the prevention of pre-term birth. As a consequence of the continuing unwarranted variation in perinatal mortality rates between Trusts and the poor quality of local reviews identified in the MBRRACE-UK perinatal confidential enquiries, in 2017 the Department of Health and Social Care commissioned MBRRACE-UK, via the Healthcare Quality Improvement Programme, to develop a national Perinatal Mortality Review Tool (PMRT). Launched in January 2018 the PMRT supports Trusts to carry our robust, systematic reviews of their local perinatal deaths ensuring that every stage of the care of the mother and baby is reviewed from pre-conception through to bereavement and follow-up care. Over 10,000 perinatal deaths have now been through the process of local review using the PMRT, there has been a demonstrable improvement in the quality of reviews conducted and demonstrable improvements in care have been instituted in Trusts as a consequence of their local review findings. Furthermore, as a consequence of the report which is produced following each review bereaved parents are provided with a clearer explanation of why their baby died and any relevant advice and information regarding the care of any future pregnancies they may plan. 3. The impact of MBRRACE-UK findings on service delivery: MBRRACE-UK surveillance data demonstrated that over 60% of all maternal deaths are as a consequence of pregnancy exacerbated medical complications. As a consequence of the MBRRACE-UK findings, in 2017, NHS England committed to developing 12 maternal medicine networks in England. These have now been established with funding to support both training and new posts to develop a hub and spoke model to ensure that pregnant women with medical complications in pregnancy are able to receive consultant level care from obstetric physicians all around the country. 4. The impact of MBRRACE-UK findings on the activities of the regulator: MBRRACE-UK has an ongoing relationship to provide maternal and perinatal data to the Care Quality Commission. This key mortality information is included in CQC inspection packs to support their regulatory activities and visits to inspect maternity and neonatal services. 5. Impacts of MBRRACE-UK findings on local activities in trusts: The first report of national perinatal mortality surveillance by MBRRACE-UK for deaths in 2013, reported for the first time ‘stabilised and adjusted’ perinatal mortality rates for individuals Trusts which enables appropriate comparison of mortality rates across health care organisations, taking into account the fact that some hospitals provide care for high risk women and hospitals care of vastly different numbers of pregnant women each year. This analysis has enabled MBRRACE -UK to not only report the national perinatal mortality rate but also to identify variation in death rates between Trusts. Using comparisons by level of care provided, MBRRACE-UK has identified those Trusts with higher than average mortality rates and published the findings using a traffic light, RAG rating system. For those Trusts with ‘red’ and ‘amber’ mortality rates it is recommended that in addition to reviewing all their perinatal deaths individually using the PMRT they explore system level issues with the delivery of care to identify potentially preventable causes of death. The purpose being to enable them to put actions in place to prevent such deaths in the future. Evidence of action in individual units came from the submission of abstracts to the MBRRACE-UK conference in May 2016 where the second national MBRRACE-UK report was launched. For example, on the back of their review, one small district general hospital introduced a new referral form for antenatal booking to enable risk factors for stillbirths to be clearly identified, so that timely consultant review can be arranged if required and any women meeting the NICE criteria for risk of gestational diabetes have an appropriately timed glucose tolerance test arranged at their dating scan appointment (which ensures that the test is not missed). As a consequence of these and other actions this hospital had seen a reduction in the number of stillbirths over the previous 12 months. (1) Kirkup B. The Report of the Morecambe Bay Inquiry. March 2015. The Stationery Office, London. 2015. [https://www.gov.uk/government/publications/morecambe-bay-investigation-report]

Expected Benefits:

Expected measurable benefits to health and/or social care including target date:
Target date: annual ongoing benefits as below with an end date of 30th September 2021

There are two overarching goals of the MBRRACE-UK programme:

(1) To improve care provided to women during pregnancy and the care provided to their babies following birth; and
(2) To reduce the rate of late fetal losses, stillbirths and infant deaths.

The MNI-CORP programme is commissioned by HQIP on behalf of NHS England. MBRRACE-UK delivers the programme and is responsible for conducting national surveillance of late fetal losses, stillbirths and infant deaths to contribute to national learning to reduce these rates. The MBRRACE-UK team does not have direct responsibility for carrying out any actions which follow from this national learning; our role is to produce the findings and ensure appropriate dissemination to the bodies responsible for changing practice to ensure that the national perinatal mortality rate reduces over time.

The surveillance is conducted in the context that the UK has one of the highest rates of perinatal death (deaths around the time of births which include late fetal losses, stillbirths and neonatal deaths) and infant deaths (deaths from birth to one year of age) in Europe. Recent figures published in the Lancet places the UK 20th out of 28 for highest stillbirth rates in Europe and it has been estimated that had the UK had a similar neonatal mortality rate to the rate in Sweden, in 2013 1,000 fewer babies would have died.

In March 2015 Bill Kirkup published his report of the investigation of perinatal and maternal deaths in the Universities Hospitals of Morecambe Bay – the ‘Morecambe Bay Enquiry’ Report (1). As part of the recommendations of that report it was noted that good information on pregnancy outcomes (including deaths) is a key driver for improvements in the quality of care provided for pregnant women and newborn babies. This is the role of the MBRRACE-UK programme.

The first report of national perinatal mortality surveillance by MBRRACE-UK for deaths in 2013, reported for the first time ‘stabilised and adjusted’ perinatal mortality rates for individuals Trusts which enabled appropriate comparison of mortality rates across health care organisations, taking into account the fact that some hospitals provide care for high risk women and hospitals care of vastly different numbers of pregnant women each year. This analysis has enabled MBRRACE -UK to not only report the national perinatal mortality rate but also to identify variation in death rates between Trusts. Using comparisons by level of care provided, MBRRACE-UK has identified those Trusts with higher than average mortality rates and published the findings using a traffic light system. For those Trusts with ‘red’ and ‘amber’ mortality rates it has been recommended that they review all their perinatal deaths individually to identify potentially preventable causes of death to enable them to put actions in place to prevent such deaths in the future. Evidence of action in individual units has come from the submission of abstracts to the MBRRACE-UK conference in May 2016 where the second national MBRRACE-UK report was launched.

For example, on the back of their review, one small district general hospital has introduced a new referral form for antenatal booking to enable risk factors for stillbirths to be clearly identified, so that timely consultant review can be arranged if required and any women meeting the NICE criteria for risk of gestational diabetes have an appropriately timed glucose tolerance test arranged at their dating scan appointment (which ensures that the test is not missed). As a consequence of these and other actions this hospital has seen a reduction in the number of stillbirths in the past 12 months.

There has also been action at national level. Following the publication of the first MBRRACE-UK national report in June 2015 NHS England launched the ‘Saving Babies’ Lives Care Bundle in March 2016 which is aimed specifically at ensuring Trusts put in place a series of key actions to prevent stillbirths which will also have an impact on neonatal and infant morbidity.

It is against this background that on the 13th November 2015 the Secretary of State for Health announced additional funding for maternity services and the national ambition to reduce the perinatal mortality rate by half by 2030 with a 20% reduction by 2020. It is the role of MBRRACE-UK to monitor progress towards this ambition and to identify Trusts which are failing to achieve progress. For MBRRACE-UK’s second national report (published in May 2016), Ben Gummer, the then Parliamentary Under-Secretary of State for Care Quality wrote in his Foreword to the report: “I want to pay tribute to the remarkable academic achievement that is MBRRACE-UK and underline the influence it is now having on the formulation of policy and impact on services. By providing a consistent and robust evidence base on which to take decisions, MBRRACE-UK is already saving lives.”

(1) Kirkup B. The Report of the Morecambe Bay Investigation. March 2015. The Stationery Office, London. 2015. [https://www.gov.uk/government/publications/morecambe-bay-investigation-report]

Outputs:

Purpose 1: MBRRACE-UK outputs

1A. Data processing by MBRRACE-UK of the 2013 birth notification data has resulted in findings which have been included in Trust level reports which were issued to Trusts/Health Boards in autumn 2015. Findings were also reported in peer-reviewed scientific outputs reporting the methods and results from the analyses. Findings were also published and findings which were published in the 'Perinatal Mortality Surveillance Report - UK Perinatal Deaths for births from January to December 2013' issued on 10th June 2014:
[https://www.npeu.ox.ac.uk/downloads/files/mbrrace-uk/reports/MBRRACE-UK%20Perinatal%20Surveillance%20Report%202013.pdf].

1B. Data processing by MBRRACE-UK of the 2014 birth notification data has resulted in findings which were included in the 'Perinatal Mortality Surveillance Report - UK Perinatal Deaths for births from January to December 2014' which was been issued on 17th May 2016.; this was accompanied by further relevant scientific reports of methodological developments and further in-depth analyses. The data were also be used to generate Trust/Health Board Level reports for issue to Trusts/Health Boards a week before the public release of the national report..

1C. Data processing by MBRRACE-UK of the 2015 birth notification data has resulted in findings which have been included in the 'Perinatal Mortality Surveillance Report - UK Perinatal Deaths for births from January to December 2015' which will be issued on 22nd June 2017. As the third set of analyses we have been able to conduct this report also includes for the first time trend data using the 2013 and 2014 data. The national report will be accompanied by scientific reports of relevant methodological developments and further in-depth analyses. The data are also being used to generate Trust/Health Board Level reports for issue to Trusts/Health Boards on 15th June 2017.

1D. Data processing by MBRRACE-UK of the 2016 birth notification data is underway in preparation for the production of the national report, local Trust/Health Board level reports and scientific peer-reviewed papers. The national and local reports will be issued in May 2018. As well as reporting the 2016 data these outputs will also include trend data incorporating the 2013, 2014 and 2015 data.

1E. Future data processing by MBRRACE-UK will continue for the 2017, 2018 , 2019, 2020 and 2021 births as per the format above with the outputs being the national annual report (including time trend data), the local reporting and scientific peer-reviewed papers. The national and local reports will be issued from May 2019 onwards.



Purpose 2: Outputs for NNAP

2A. Data processing by MBRRACE-UK of the 2013 and 2014 birth notification data to generate aggregated tables of live births by gestational age by hospital by year will carried out to enable NNAP to further analyse the audit measure published in the NNAP report for 2013 and 2014 reports.

2B. Data processing by MBRRACE-UK of the 2015 birth notification data to generate aggregated tables of live births by gestational age by hospital by year will be used in the production of audit measures for the measures generated by NNAP in the 2015 report.

2C. Data processing by MBRRACE-UK of the 2016 birth notification data to generate aggregated tables of live births by gestational age by hospital by year will be used in the production of audit measure for the NNAP report for 2016 which will be issued by NNAP in October 2017.

2D. Data processing by MBRRACE-UK of the 2017, 2018 , 2019, 2020 and 2021 births as per the format above will continue to support the NNAP outputs.

All national outputs (for Purposes 1 and 2) are aggregated with small numbers suppressed adhering to the HES analysis guide. The local MBRRACE-UK Trust/Health Board level reports do not involve small number suppression because we are giving the Trusts/Health Boards back information about the cases they were responsible for caring for and reporting to us so they already know how many cases there are together with all their individual clinical characteristics.

Processing:

Purpose 1: Processing for MBRRACE-UK purposes

The birth notification data are stored on the National Perinatal Epidemiology Unit (NPEU) secure high compliance servers which are used solely for MBRRACE-UK data processing activities.

The servers are accessed only at the National Perinatal Epidemiology Unit (NPEU), University of Oxford. Processing of ONS and NN4B/PDS birth notification identifiable data occurs in the high compliance area.

The birth notification data are linked to the ONS births and stillbirths data in order to add the key variables gestational age and ethnicity to the ONS births/stillbirths information. Once a combined ONS/NN4B or PDS birth notification dataset has been generated and cleaned the clinical data on late fetal losses (in utero deaths 22-23 completed weeks' gestation), stillbirths (in utero deaths 24+ weeks' gestation) and neonatal deaths (0-27 days after birth) collected by MBRRACE-UK are linked to the combined ONS/birth notification dataset.

The identifiable dataset is stored only on the secure NPEU servers. Cleaning and analysis take place in two locations. The MBRRACE team based at University of Oxford link and clean the perinatal data and generate items such as index of multiple deprivation (IMD) using the postcode data.

An extract dataset containing a limited number of identifiers (referred to here as partial identifiers) is transferred to the MBRRACE-UK analysts at the University of Leicester using the University of Oxford secure electronic data transfer mechanism Oxfile. This dataset extract has all identifiers other than the babies dates of birth and dates of death removed. These identifiable data items remain as they are required to generate date-dependent variables by the MBRRACE-UK analysts at the University of Leicester during the course of analysis. All other Identifiable data items are removed before transfer (e.g. name, address, postcode, NHS number etc).

Purpose 2: Processing for NNAP purposes

MBRRACE-UK will produce aggregated data with small number suppression, in line with HES analysis guide, and supply it to the National Neonatal Audit Programme (NNAP).

MR1086 - The Oxford Vascular Study (consent cohort) — DARS-NIC-653950-W8D4Z

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-07 – 2025-06 2023.12 — 2025.02.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Demographics
  3. Civil Registrations of Death

Type of data: Identifiable

Objectives:

The following provides background information on the purpose of the original study:

The Oxford Vascular Study (OxVasc) began in April 2002 to determine mortality, disability, psychological morbidity, cognitive decline and cost of care following stroke, transient ischaemic attack (TIA), Acute Coronary Syndrome (ACS) and acute peripheral vascular events in patients registered in one of eight GP practices in Oxfordshire.

ACS is the leading cause of death in the developed world, causing more than twice as many deaths as stroke. However, mortality data underestimates the burden of stroke. Stroke is the main cause of neurological disability in the developed world, and a common cause of dementia, depression, epilepsy, falls and fractures. The incidence, case fatality, longer term sequelae of stroke and ACS have never been measured in the same population at the same time. Comparison of OCSP (Oxford Community Stroke Project) and OXMIS (Oxford Myocardial Infarction Study) which took place in the early 1980s suggests that mortality due to stroke is lower than that due to ACS, but overall incidence is similar, and the total clinical instance of stroke may be greater. There are no data from the UK on recent time trends in age and sex specific incidence or disability rates for stroke and ACS. However, there have been major changes over the last 20 years in the life-style, primary and secondary prevention treatments and particularly in population demographics. A formal comparison would provide a firm basis on which local and national policy decisions about allocation of limited NHS funding for clinical services and limited governmental funding for medical research could be made.

OxVasc is one of a number of cohort studies funded by the National Institute for Health and Care Research (NIHR) to identify simple low cost interventions and to inform the development of clinical trials to improve the treatment outcomes of vascular disease in the short and long term. By recruiting all eligible participants from a defined population and following them up over a long period of time, OxVasc reduces recruitment bias so the results are more generalizable to the population as a whole and can identify whether the benefits of any intervention are maintained (e.g. sustained blood pressure monitoring and treatment, carotid surgery).

The GDPR legal bases for processing the data held under this Agreement are Article 6(1)(e) (processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller) and Article 9(2)(j) (processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes). This research into the health outcomes for people who have suffered from stroke or other vascular events is a task in the public interest under General Data Protection Regulation (GDPR) as it aims to improve care for all patients considering undergoing this type of process – informing clinicians and commissioners of variation and outcomes and complications to support work to improve and standardise treatment selection choices. The protocol has had appropriate ethics committee approval and CAG support (all documentary evidence is included in this application.

Since 2008, mortality and demographic data were supplied to the University of Oxford by ONS and subsequently the Health and Social Care Information Centre (which has since become NHS Digital) for the purpose of this research study. The overall aims of the study have not changed since 2002 and the benefits of a cohort study of this length and detail will continue to improve the public’s health through disease prevention, earlier disease diagnosis and better disease management. The study to date has had significant impacts (as described in the benefits section) and it is expected that further measurable benefits will be outputs that underpin NICE and other Department of Health strategies for detection, management and treatment of vascular disease.

The minimal information is requested under this agreement to meet the aims of the study and ensure integrity of study outputs, specifically:

Date of death-survival after vascular event to evaluate treatment interventions, natural history of disease and to stop further contact for follow up visits.
Place of normal residence and place of death-health economic analyses of recovery and use of assisted living/institutional care.
Cause of death (including ICD10 codes and free text) to establish underlying and contributing factors to death.

The University of Oxford previously flowed identifying information to NHS Digital for the purpose of list cleaning. The University of Oxford used the list cleaning service to provide a newsletter to participants. Upon receipt of the Demographics data, University of Oxford will destroy this data and provide a data destruction certificate to NHS Digital as it will no longer be required.

No attempt is made to contact families after the death of a participant notified to the study team through this process.

The analyses are determined by the Principal Investigator (PI) and the study statistician and performed by the University of Oxford research team to support the aims and objectives of the study. Ethical approval and grant funding from the Wellcome Trust and the NIHR Oxford Biomedical Research Centre have been granted for the study, for the same purposes as described in this Agreement.

The progress is evaluated annually and new analyses are added or completed based on findings to date and the length of time required to collect outcomes (cause of death) to determine the prognosis of different presentations of vascular disease and/or achieve statistical power to answer the research question. For example, mortality data is required to determine the outcome (disability or death) and time course of bleeding requiring medical attention in patients taking long-term antiplatelet treatment after acute vascular events. This is then used to estimate the age-specific numbers needed to treat to prevent upper gastrointestinal bleeding with routine proton-pump inhibitor co-prescription.

Not all of the work of the Oxford Vascular Study involve use of data on mortality obtained from NHS Digital but use of the data will be important in some analyses in order to determine firstly the impact of any treatment on survival and secondly the health economic value of any intervention e.g. prevention of recurrent stroke and subsequent health resource use.

The data subjects are patients registered in one of eight GP practices in Oxfordshire who have had a stroke, transient ischaemic attack (TIA), Acute Coronary Syndrome (ACS) or acute peripheral vascular events. These are the same practices (and associated demographic characteristics of the previous studies-OCSP/OXMIS) allowing valid comparisons over time. Since 2002, participants have been recruited from hospital, outpatients’ clinics or home following referral from a collaborating GP and interviewed by a researcher following written consent. Clinical information is gathered from participants about their health, medical history, family history and current treatment. The study team extract information about their vascular event and related conditions from health records for the duration of the study in order to follow up on participants health status. Regular face-to-face or telephone contact is maintained with participants and their GPs over the first two years and they are contacted again at five and ten years after entering the study. However, over this period participants may move out of Oxfordshire or register with a different GP. In order to achieve the study aims, accurate information on the date and cause of death of participants in the cohort to evaluate long term morbidity and mortality for the study population is required. For this reason, national data is required. Data will need to be shared at a record level as agreed between the University of Oxford and NHS Digital to flag and receive date and cause of death for each individual cohort member and in order to produce accurate matching. There is no alternative way to obtain all cause mortality data sufficiently robust to achieve the aims of the study. All results will be presented as aggregated data.

The earliest participants were recruited while the study was in a pilot phase and they were all asked to re-consent to participate in the full study when version 2 of the consent form (dated 28/12/2006) came into use. Under this Agreement, the University of Oxford is permitted to share with NHS Digital details of participants who have given consent using version 2 of the consent form or any subsequent version. The current Agreement does not permit the processing of data relating to any participant who was recruited using an earlier version - which did not include a declaration of consent for "information held by the NHS and records maintained by the General Register Office" to be used to maintain contact and follow up their health status - and did not re-consent using version 2 or a subsequent version. The data for these participants is to be obtained using section 251 support from the Confidential Advisory Group (CAG) under a separate Agreement, DARS-NIC-148369-8PPWK.

The University of Oxford is the sole data controller who also process the data supplied by NHS Digital under this Agreement. No other organisation determines the purpose for data processing or has any access to the data. Funding for OxVasc is provided by the Wellcome Trust and the NIHR Oxford Biomedical Research Centre. Past funding has been provided by the Stroke Association which is still acknowledged on some of the study outputs. The funders expect the Nuffield Department of Clinical Neurosciences to undertake research such as this but the funding body can not access data nor has a role in analysis or interpretation.

Yielded Benefits:

Expected Benefits:

The overall aims of the Oxford Vascular Study are to improve the public’s health through disease prevention, earlier disease diagnosis and better management of known risk factors. Results from the study to date have been used to underpin NICE guidelines and other Department of Health strategies (some of these benefits are described in yielded benefits to date) by providing evidence for ways to improve diagnosis of disease and how to effectively treat common risk factors such as high blood pressure.

The Oxford Vascular Study has ongoing funding from the Wellcome Trust and the NIHR to continue recruitment and complete follow up of the 25 year cohort. This will allow the study to continue providing new evidence to inform stroke prevention and vascular disease generally for the benefit of the population at large, with the continuing recruitment and long term follow up of OxVasc participants. These benefits fulfil the requirements necessary for data processing outlined in Article 6(1)(e).

The study also benefits the individual participants by providing:
1. Rapid assessment and treatment following TIA and minor stroke in order to identify the cause and provide treatment.
2. Ongoing assessment of vascular risk factors (BP, cholesterol), health care advice (smoking cessation, lifestyle advice) at follow up, enabling participants and the collaborating GP to improved secondary prevention of vascular disease.

Mortality data from NHS Digital also potentially reduces distress to participant’s relatives by attempting to contact them for follow up/information about circumstances of death.

The OxVasc study has been running for over 20 years, during which time many improvements in assessment/diagnosis and treatment of TIA, stroke and ischaemic heart diseases have been made. Analysis of morbidity and mortality over this time period is expected to provide additional insights into how further gains can be made in stroke prevention and care. An example of how long term cohort studies like OxVasc can direct further research is in stoke incidence in younger age groups, which appears to be increasing. A new study to better understand the role of treatable risk factors in young stroke patients which could potentially be informative for future clinical guidelines are now underway. (https://www.medicalresearchfoundation.org.uk/projects/contribution-of-the-presence-susceptibility-to-and-control-of-modifiable-vascular-risk-factor-in-young-stroke-and-tia-a-prospective-cohort-and-nested-case-control-study). This study is separate from the OxVasc study and does not use that data held under this Agreement, however, the new study builds on OxVasc research to improve treatment for young stroke victims.

Outputs:

The study overall has produced over 250 peer reviewed publications on incidence of disease, risk factor management, prognosis and outcomes. Peer-reviewed manuscripts on original research arising from the study are subject to the Wellcome Trust open access policy and are available to all free of charge on publication. A statement on data used and data sharing is provided in line with the individual publisher guidelines and the NIHR. The data received under this Agreement will continue to be used in the same way as previously outlined and is important for use in analyses of the effects of new/extended uses of primary and secondary prevention of vascular disease over a long period of time.

Research aims and findings from the Oxford Vascular Study are summarised on the study website (www.ndcn.ox.ac.uk/research/oxvasc) and presented at open days organised by the NIHR Oxford Biomedical Research Centre (BRC), Nuffield Department of Clinical Neurosciences and public involvement and engagement groups. Talks on OxVasc and related topics (e.g., high blood pressure, vascular dementia) are also available on YouTube (https://oxfordbrc.nihr.ac.uk/research-themes-overview/stroke-and-vascular-dementia/videos-stroke-and-vascular-dementia). Selected results of the study have been reported in the local, national and international press.

Participants are informed of progress with posters displayed with results of the study to date in the participating GP practices and the general information booklet which participants are given on entry to the study and updated yearly.

Yearly reports on the progress of this research have been given to the funders with all outputs and impacts for the previous year. Many of the outputs arising from the Oxford Vascular Study include data on mortality obtained from NHS Digital, often to corroborate information reported by hospitals, GPs and/or relatives of participants on cause of death. Data from NHS Digital provides the collated ICD10 codes, and these data continue to be important in some analyses together with the detailed clinical information collected from participants as part of the study. A statement regarding sharing of data collected from and about participants is available on the study website.

All outputs (presentations, posters, peer reviewed publications and oral presentations at conferences) report numbers at an aggregated level, with small numbers suppressed.

Processing:

The following provides background on the processing activities undertaken for the original study:

The study data, including data provided by NHS Digital under previous versions of this Agreement, are held by the University of Oxford. The data are stored electronically on University of Oxford central servers which are connected to the main University of Oxford’s network. At no time will sole employees of John Radcliffe Hospital have access to the data held on the server for University of Oxford.

Identifying details of participants have previously been supplied to ONS and subsequently NHS Digital so that their patient records could be flagged and mortality data could be reported to the study. The University of Oxford will flow identifiers (Surname, First name, NHS number, date of birth, study ID) to NHS Digital to update the cohort to flag participants recruited after 2018.

The data disseminated under this Agreement will only cover participants who have consented to this. Where section 251 support has been granted to meet the Common Law Duty of Confidentiality, the data for these participants is disseminated under a separate Agreement for this study: NIC-148369.

The following datasets are processed by the study:

i. Civil Registration Mortality data – details of participants’ deaths including date and cause;
ii. Demographics – details of embarkations or lost to follow up

Data received from NHS Digital will be linked to unique study ID using date of birth and NHS number to ensure a perfect match to each participant’s date of vascular event to calculate outcomes (Kaplan-Meier survival analyses). All data supplied by NHS Digital will be used only for the approved Medical Research Project MR1086-The Oxford Vascular Study. No data will be shared with any individuals or agencies outside of the study team and all study staff are substantive employees of the University of Oxford.

The data is held in an access-controlled server room within the University of Oxford Medical Sciences Division, situated on the Old Road Campus and connected to the main University network, located behind a firewall. Physical access is limited to Computer Services Department staff. Data will be encrypted using industry standard techniques meeting the Information Governance Toolkit standard (RBQ).

MR1086 - The Oxford Vascular Study: incidence and outcome of stroke , transient ischaemic attack — DARS-NIC-148369-8PPWK

Opt outs honoured: N, Yes - patient objections upheld, Yes (Excuses: Consent (Reasonable Expectation), Section 251 NHS Act 2006)

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c), Consent (Reasonable Expectation); Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2019-03 – 2020-10 2017.09 — 2025.02.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. Demographics
  4. MRIS - Scottish NHS / Registration
  5. MRIS - Flagging Current Status Report
  6. MRIS - List Cleaning Report
  7. MRIS - Members and Postings Report
  8. Civil Registration - Deaths
  9. Civil Registrations of Death

Type of data: Identifiable

Objectives:

The Data supplied by the NHSIC to University of Oxford will be used only for the approved Medical Research Project MR1086.

Yielded Benefits:

Some of benefits of data collated in the Oxford Vascular Study (OxVasc) to date include: Emergency prevention of “threatened” stroke Major strokes are sometimes preceded by minor events – so called transient ischaemic attacks (TIA) or minor strokes. It was thought for many years that these events were relatively benign and that investigations were done on a non-urgent basis over weeks or months. Analyses of OxVasc outcomes showed that the risk of major stroke in the first few hours and days after these warning events was, in fact, very high (BMJ 2004), such that they were re-branded as a medical emergency in all international guidelines. A validated and refined simple risk scores (ABCD system) to triage high-risk individuals (Lancet 2005; Lancet 2007) and showed that delays to treatment substantially undermined benefits and showed that urgent use of existing treatments (aspirin, other antiplatelet drugs, blood pressure lowering drugs and statins) reduced the 90-day risk of major stroke by 80% (Lancet 2007; Lancet Neurol 2009. This simple, cheap but highly effective strategy was rolled out across the UK in the Department of Health’s National Stroke Strategy and NICE guidelines, is estimated to prevent 10,000 strokes per year in the UK alone, saving £200 million in NHS costs, and is now the standard of care worldwide. Further work has shown that most of the 80% reduction in the early risk of major stroke seen in OxVasc was due purely to aspirin, which also substantially reduces the severity of recurrent strokes. This new observation has major implications for public education - immediate self-administration of aspirin after possible TIA or minor stroke symptoms has the potential to prevent many millions of strokes worldwide at virtually no cost (Lancet, 2016). Screening for aortic aneursysms The schedule for abdominal aortic aneurysm (AAA) screening in men age 65 might have limited impact on overall AAA death rates if incidence of acute events is moving to older ages. Data form OxVasc showed two thirds of acute AAA occurred at ≥75 years of age, indicating screening older age groups should be considered. In addition, 25% of acute events were in women and the screening of nonsmokers at age 65 is likely to have very little impact on AAA event rates (Br J Surg. 2015, J Am Heart Assoc. 2015). Recovery after stroke Outcome in stroke trials is often based on an assessment of 3-month disability. How disability at this time point relates to longer-term outcomes will depend on late recovery, delayed stroke-related deaths, recurrent strokes, and nonstroke deaths. Data from OxVasc reaffirmed the use of outcome at 3 months in stroke trials. It also showed that although later recovery does occur, extending follow-up to 1 year would capture most long-term stroke-related disability. However, administrative mortality follow-up beyond 1 year has the potential to demonstrate translation of early disability gains into additional reductions in long-term mortality without much erosion by non-stroke-related deaths. Further work is underway to document the time course of long‐term quality‐adjusted life expectancy and healthcare costs in relation to early disability scores. (J Am Heart Assoc. 2017). The following is an extract from the publication ‘The National Institute for Health Research at 10 Years | An impact synthesis: 100 Impact Case Studies’ (see: https://www.rand.org/pubs/research_reports/RR1574.html): Costs arising from the treatment of stroke and costs incurred due to productivity loss of the UK population have been calculated to amount to approximately £8.9 billion a year [1]. Stroke treatment costs represent about 5 per cent of total UK NHS costs [1]. Research resulting from the Oxford Vascular Study (OXVASC), which is partly funded by the NIHR, has had significant impact on stroke prevention and the way minor strokes and transient ischaemic attacks (TIAs, or ‘mini strokes’) are managed, by informing clinical guidelines. The OXVASC study started in 2002 and provides data on the incidence and outcome of all acute vascular events occurring in the population in Oxfordshire [2]. The NIHR has contributed to the research in different ways, such as: funding specific research on cost savings arising from early detection of TIA and stroke, in phase 2 of the OXVASC study, and providing an NIHR Senior Investigator Award to one of the principal investigators [3]. The first phase of the OXVASC study showed that the risk of stroke after a TIA is greater than originally considered, that there is a narrow time-window for prevention, and that individuals who are at highest risk of having a stroke can be identified with a simple clinical score – the ABCD [2]. It also showed that the requirement for appointments could lead to a delay in referrals for patients with a suspected TIA or minor stroke. Based on learning from phase 1, the second phase of the research led to impacts on emergency treatment of TIA and minor stroke in primary care [2]. In this second phase, primary-care physicians were asked to send the patients immediately to the clinic, without any appointment, where treatment was initiated immediately if the diagnosis was confirmed. This led to an 80 per cent decrease in the 90-day risk of recurrent stroke in patients referred to the phase 2 clinic compared with those referred to the phase 1 clinic. In addition, clinic hospital admissions for recurrent stroke were lower when the requirement for appointments was removed, which translated to a savings of £624 per patient [4]. The Early use of eXisting PREventive Strategies for Stroke (EXPRESS) study, nested within OXVASC, determined the effect of more rapid treatment after a TIA and minor stroke in patients who are not admitted directly to hospital [4][5]. These findings have had an impact on service provision and professional education about TIA and minor stroke. This is demonstrated by the changes the research has produced in clinical guidelines. Findings from the EXPRESS study have informed the 2007 National Stroke Strategy; the 2008 National Institute for Health and Care Excellence guidelines Stroke: National Clinical Guideline for Diagnosis and Initial Management of Acute Stroke and Transient Ischemic Attack (TIA); and the 2012 Royal College of Physicians Intercollegiate Stroke Working Party’s National Clinical Guideline for Stroke [3]. The recommendations in these documents reflect the findings from the EXPRESS study that there is a need for identification of patients at high risk of subsequent stroke and early specialist intervention, including commencement of appropriate secondary prevention treatments. Based on the estimations from the EXPRESS study, it was calculated that emergency treatment of TIA and minor stroke in primary care would prevent about 10,000 strokes per year, adding up to savings of up to £200 million annually in acute care costs alone in the NHS [3]. Overall, the health and care system has benefited from improved stroke prevention as a result of determining the resource costs, health outcomes and cost-effectiveness in stroke care using evidence from the Oxford Vascular Study. Evidence 1] Saka Ö, McGuire A, Wolfe C. 2009. Cost of stroke in the United Kingdom. Age and Ageing 38 (1): 27-32. doi:10.1093/ageing/afn281 Study reporting the annual cost of stroke to the UK economy using a combination of direct and indirect cost measures. [2] National Institute for Health Research. 2016. Improving stroke prevention in routine clinical practice: Phase 2 of the Oxford Vascular Study (OXVASC) programme. As of 2 May 2016: http://www.nihr.ac.uk/funding/funded-research/funded-research.htm?postid=2164 Link to a project page on the National Institute for Health Research website, describing the OXVASC Study programme. [3] Research Excellence Framework. 2014. Reduction of stroke risk by risk stratification and urgent intervention after a transient ischaemic attack (TIA) or minor stroke. [Case study 14720.] As of 2 May 2016: http://impact.ref.ac.uk/CaseStudies/CaseStudy.aspx?Id=14720 The case study summarises the achievements of the team from the Stroke Prevention Research Unit in Oxford from early 2000 to 2013. [4] Luengo-Fernandez R, Gray AM, Rothwell PM. 2009. Effect of urgent treatment for transient ischaemic attack and minor stroke on disability and hospital costs (EXPRESS study): A prospective population-based sequential comparison. The Lancet. Neurology. 8: 235-43. doi: 10.1016/S1474- 4422(09)70019-5 This paper summarises the findings on the cost-effectiveness of the phase 2 intervention. It concludes that urgent assessment and treatment of patients with a TIA or minor stroke who were referred to a specialist outpatient clinic reduced subsequent hospital bed-days, acute costs and six-month disability. [5] Health Economics Research Centre. 2016. Resource costs, health outcomes and cost-effectiveness in stroke care: Evidence from the Oxford Vascular Study. Nuffield Department of Population Health. As of 2 May 2016: http://herc.medsci.ox.ac.uk/research/disease-cost-studies/studies-4/resource-costs-healthoutcomes-and-cost-effectiveness-in-stroke-care-evidence-from-the-oxford-vascular-study The page offers a comprehensive account of this part of the research of the Oxford Vascular Study, including the publications resulting from it. This project aimed to: 1) estimate the size and predictors of immediate and long-term (i.e. five years after the event) National Health Service resource use and healthcare costs of stroke and transient ischaemic attacks; 2) estimate the size and predictors of immediate and long-term health outcomes, including five-year life expectancy, patient disability, quality of life, and quality-adjusted life expectancy; and 3) assess if urgent clinical assessment and treatment of nonhospitalised patients with a minor stroke or TIA was cost effective.

Expected Benefits:

The overall aims of the Oxford Vascular Study are to improve the public’s health through disease prevention, earlier disease diagnosis and better management of known risk factors. Results from the study to date have been used to underpin NICE guidelines and other Department of Health strategies by firstly providing evidence for ways to improving diagnosis of disease and secondly how to effectively treat common risk factors such as high blood pressure.

Most outputs arising from the Oxford Vascular Study include data on mortality obtained from NHS Digital and these data continue to be important in some analyses together with the detailed clinical information collected from participants as part of the study.

Outputs:

No new outputs will be produced under this Data Sharing Agreement.

OxVasc is one of a number of cohort studies funded by the NIHR to identify simple low cost interventions and to inform the development of clinical trials to improve the treatment outcomes of vascular disease in the short and long term. By recruiting all eligible participants from a defined population and following them up over a long period of time, OxVasc reduces recruitment bias so the results are more generalizable to the population as a whole and can identify whether the benefits of any intervention are maintained (e.g. sustained blood pressure monitoring and treatment, carotid surgery).

The study overall has produced over 100 publications of incidence of disease, risk factor management, prognosis and outcomes, including:
- Change in incidence, mortality and risk factors for stroke from 1981 to 2004. (Lancet, 2004) showing the fall in incidence over the past 20 years is association with increased use of preventive treatments.
-Reported incidence, case fatality, burden and cost of all acute vascular events in a defined population. (Lancet, 2005)-
- Reported incidence and outcome of acute aortic dissection and Ischemic Peripheral Arterial Events from 2002-2012. (Circulation, 2013, 2015) showing uncontrolled high blood pressure remains the most significant treatable risk factor for acute aortic dissection and focussed use of existing treatments would be beneficial.

Yearly reports on the progress of the researchhave been given to the funders with all outputs and impacts for the previous year.

The study also benefits the individual participants by providing:
1. Rapid assessment and treatment following TIA and minor stroke in order to identify the cause and provide treatment.
2. Ongoing assessment of vascular risk factors (BP, cholesterol), health care advice (smoking cessation, lifestyle advice) at follow up, enabling participants and the collaborating GP to improved secondary prevention of vascular disease.

Research findings from the Oxford Vascular Study are summarised on the study website (www.ndcn.ox.ac.uk/research/oxvasc) and presented at open days organised by the NIHR Oxford BRC. Talks on OxVasc and related topics (e.g. high blood pressure, vascular dementia) are also available on YouTube. Results of the study have been reported in the local, national and international press.

Participants are informed of progress with posters displayed with results of the study to date in the participating GP practices and the general information booklet which participants are given on entry to the study and updated yearly.

Peer-reviewed manuscripts on original research arising from the study are subject to the Wellcome Trust open access policy and are available to all free of charge on publication. A statement on data used and data sharing is provided in line with the individual publisher guidelines and the NIHR. No data, even anonymised, from NHS Digital will be shared.

Processing:

Under this Agreement, the data already provided under previous iterations of this Agreement may be securely stored but not otherwise processed.

The University of Oxford is permitted to supply a file containing identifying details of study participants to NHS Digital.

NHS Digital will supply details of participants' current vital status, current status of registration with an NHS GP and latest known addresses for living participants registered with an NHS GP.

The University of Oxford will use this information to determine which study participants should appropriately be sent a patient notification by post.


The following provides background on the processing activities undertaken for the original study:

The study data, including data provided by NHS Digital under previous versions of this Agreement, are held by the University of Oxford in the Nuffield Department of Clinical Neurosciences Medical Sciences Division, based within the West Wing of John Radcliffe Hospital Oxford. The data are stored electronically on University of Oxford central servers which are connected to the main University of Oxford’s network. At no time will employees of John Radcliffe Hospital have access to the data held on the server for University of Oxford.

Identifying details of participants have previously been supplied to ONS and subsequently NHS Digital so that their patient records could be flagged and mortality data could be reported to the study. The University of Oxford will flow identifying information to NHS Digital for the purpose of list cleaning. The University of Oxford will use the list cleaning service to provide a newsletter to participants. The newsletter will be pre-reviewed by NHS Digital prior to publication.

The study database contains information collected directly from participants (e.g. family history, lifestyle) and from other sources including hospital and GP surgery notes (e.g. scan results, blood test results, blood pressure measurements). These are entered and coded within the database so they can be downloaded for analysis at a later date. The study database contains identifying data on each participant in order to keep up to date contact details for them so they can be contacted for follow up, but the database is encrypted so any data extracted for analysis does not have identifying details (names, addresses, etc.).

Other than the linkages described above, the data will not be linked with any other data.

No attempt is made to contact families after the death of a participant is confirmed through this process.

Data supplied by NHS Digital will be used only for the approved Medical Research Project MR1086-The Oxford Vascular Study. No data will be shared with any individuals or agencies outside of the study team. All study staff are employees of the University of Oxford.

The analyses are determined by the Principal Investigator (PI) and the study statistician and performed by the research team to support the aims and objectives of the study as outlined in the application for ethical approval and grant funding from the Wellcome Trust and the NIHR Oxford BRC.

The progress is evaluated annually and new analyses are added or completed based on findings to date and the length of time required to collect outcomes (cause of death) to determine the prognosis of different presentations of vascular disease and/or achieve statistical power to answer the research question. For example, mortality data is required to determine the outcome (disability or death) and time course of bleeding requiring medical attention in patients taking long-term antiplatelet treatment after acute vascular events. This is then used to estimate the age-specific numbers needed to treat to prevent upper gastrointestinal bleeding with routine proton-pump inhibitor co-prescription.

Not all of the work of the Oxford Vascular Study involve use of data on mortality obtained from NHS Digital but use of the data will be important in some analyses in order to determine firstly the impact of any treatment on survival and secondly the health economic value of any intervention e.g. prevention of recurrent stroke and subsequent health resource use.

The data is held in an access-controlled server room and connected to the main University network, located behind a firewall. Physical access is limited to Computer Services Department staff. Data will be encrypted using industry standard techniques meeting the Information Governance Toolkit standard (RBQ).

The Epidemiology of breast cancer subtypes in England as defined by hormone receptor status and HER2 status (ODR1516_099) — DARS-NIC-656758-N4H9Y

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2024-04 – 2026-09 2024.12 — 2025.01.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked Cancer Waiting Times (Treatments only)
  3. NDRS National Radiotherapy Dataset (RTDS)
  4. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Type of data: Anonymised - ICO Code Compliant

Objectives:

University of Oxford requires access to NHS England data for the purpose of the following research project: The Epidemiology of breast cancer subtypes in England as defined by hormone receptor status and HER2 status.

The following is a summary of the aims of the research project provided by University of Oxford:
Primary objective:
To describe the epidemiology in England of four main breast cancer subtypes, (Luminal A, Luminal B, Her2 enriched, Triple negative) as defined by oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor 2 (HER2) expression, in relation to age and ethnicity of women with breast cancer, and other patient and tumour characteristics.

Secondary objective:
To describe the subsequent treatment patterns of four main breast cancer subtypes, as defined by oestrogen (ER) receptor, progesterone receptor (PR) and human epidermal growth factor 2 (HER2) expression, and other molecular subtyping tools such as OncotypeDX, and impact on subsequent survival of women with breast cancer and to link these treatment outcomes to patient experience.


The following NHS England Data will be accessed:
• NDRS Linked Cancer Registration
• NDRS Systemic Anti-Cancer Therapy Dataset (SACT)
• NDRS Radiotherapy Dataset (RTDS)
• NDRS Linked Cancer Waiting Times (Treatment Data) (CWT)

The level of the Data will be pseudonymised.

The Data will be minimised as follows:
• Limited to patient diagnosed between 01/01/2006 – latest available
• Limited to the following geographic areas: England
• Limited to female patients
• Limited to patients above the age of 24 years at diagnosis
• Limited to conditions relevant to the study identified by specific ICD or OPCS codes;
o ICD10 – C50x or D05x
o OPCS4 - OPCS4 events will be limited to codes BCS (B28, B281, B282, B283, B285, B286, B287, B288, B289 MARGIN: B284 Mastectomy (B27, B271, B272, B27, B274, B275, B276, B278, B279) SLNB: (O142, T87, T873, T878, T879, T91, T911, T912, T919, T928) Sampling: (T86, T862, T868, T869) Axillary Dissection (Z613, T852, T858, T859) Breast Reconstruction: (B29, B291, B292, B293, B294, B295, B298, B299, B30, B301, B302, B303, B304, B308, B31, B311, B312, B313, B314, B318, B319, Biopsy of breast: B32, B321, B322, B323, B328, B329 Incision of breast: (B33, B331, B332, B333, B338, B339) Operations on duct of breast: (B34, B341, B342, B343, B344, B345, B348, B349) Nipple operations: (B35, B351, B352, B353, B354, B355, B356, B358, B359) Reconstruction of nipple and areola: (B36, B361, B362, B363, B364, B368, B369) Other breast procedure: (B37, B371, B372, B374, B375, B378, B379) Reconstruction of breast using flap of skin of buttock: (B38, B381, B382) Reconstruction of breast using abdominal flap: (B39, B391, B392, B393 B398, B399) Destruction of lesion of breast: (B40, B409)



University of Oxford is the research sponsor and the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.


The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.


The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.


The funding is provided by Cancer Research UK. The funding is specifically for the study described.
The funder(s) will have no ability to suppress or otherwise limit the publication of findings.



In line with the national data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and section 251(11) of the National Health Service Act 2006.

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out

Yielded Benefits:

The following peer reviewed publications have arisen from these data: • Gathani T, Reeves GK, Broggio J, Barnes I: Ethnicity and the tumour characteristics of invasive breast cancer in over 116 500 women in England Br J Cancer 2021: doi: 10.1038/s41416-021-01409-7 • Gathani T, Chuiri K, Broggio J, Reeves G, Barnes I: Ethnicity and the surgical management of breast cancer in over 164 000 women in England Br J Surgery 2020: https://doi.org/10.1002/bjs.11865 • Gathani T, Chaudhury A, Chagla L, Chopra S, Copson E, Purushotham A, Raghavan V, Cuttress R: Ethnicity and breast cancer in the UK: where are we now? Eur J Surg Oncology 2021: https://doi.org/10.1016/j.ejso.2021.08.025 These papers formed the basis of a successful grant application to the Prevention and Population Research Committee at Cancer Research UK to investigate further the associations of ethnicity and breast cancer. Update 08 January 2024: This research project is exploring the distribution of four breast cancer subtypes in England by certain patient characteristics and to identify any potential differences, not only in the treatment of these cancers but also in the experience of cancer treatment that these patients receive. By using pseudonymised data from the National Cancer Registration and Analysis Service, the researchers aim to provide detailed, reliable and nationally representative information about the clinical outcomes of different breast cancer subtypes for women in England, adjusted for age and region and other patient and tumour factors. Primary aim: To describe the epidemiology in England of four main breast cancer subtypes, (Luminal A, Luminal B, Her2 enriched, Triple negative) as defined by oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor 2 (HER2) expression, in relation to age and ethnicity of women with breast cancer, and other patient and tumour characteristics. Secondary aim: To describe the subsequent treatment patterns of four main breast cancer subtypes, as defined by oestrogen (ER) receptor, progesterone receptor (PR) and human epidermal growth factor 2 (HER2) expression, and other molecular subtyping tools such as OncotypeDX, and impact on subsequent survival of women with breast cancer and to link these treatment outcomes to patient experience. The following peer reviewed publications have arisen from these data: • Gathani T, Reeves GK, Broggio J, Barnes I: Ethnicity and the tumour characteristics of invasive breast cancer in over 116 500 women in England Br J Cancer 2021: doi: 10.1038/s41416-021-01409-7 • Gathani T, Chuiri K, Broggio J, Reeves G, Barnes I: Ethnicity and the surgical management of breast cancer in over 164 000 women in England Br J Surgery 2020: https://doi.org/10.1002/bjs.11865 • Gathani T, Chaudhury A, Chagla L, Chopra S, Copson E, Purushotham A, Raghavan V, Cuttress R: Ethnicity and breast cancer in the UK: where are we now? Eur J Surg Oncology 2021: https://doi.org/10.1016/j.ejso.2021.08.025 These papers formed the basis of a successful grant application to the Prevention and Population Research Committee at Cancer Research UK to investigate further the associations of ethnicity and breast cancer. Future anticipated work, including the cancer registry data during 2023-2026, will include updating the analyses on tumour characteristics and ethnicity, to incorporate molecular subtypes as and when the numbers of cancers registered are sufficient in the subgroups of interest. Other planned analyses include the associations of tumour characteristics, by age, ethnicity and route to diagnosis. Findings will be disseminated in general cancer journals such as the British Journal of Cancer – likely date for publication would be anticipated to be 2026, with preliminary findings likely presented at relevant scientific meetings such as the UKIBCS in 2024, and the Association of Breast Surgery annual conferences.

Expected Benefits:

This research aligns with the NHS Quality agenda tackling inequalities. The study is wholly aligned to the NHS Cancer Plan which states that the key ambitions will be delivered in a way that reduces variations and inequalities.
This research is focused on describing the associations of breast cancer and ethnicity, the results of will identify gaps in care, and suggest inform the policies needed to address them.
As breast cancer is not a single disease, it is important to understand the patient and tumour factors that influence response to treatment. This will further support the NHS to make decisions about patient-tailored treatment strategies.

As breast cancer is not a single disease, it is important to understand the patient and tumour factors that influence response to treatment. This will further support the NHS to make decisions about patient-tailored treatment strategies.

Outputs:

Findings will be disseminated in general cancer journals such as the British Journal of Cancer – likely date for publication would be anticipated to be 2026, with preliminary findings likely presented at relevant scientific meetings such as the UKIBCS in 2024, and the Association of Breast Surgery annual conferences.

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Scientific meetings

Future anticipated work, including the cancer registry data during 2023-2026, will include updating the analyses on tumour characteristics and ethnicity, to incorporate molecular subtypes as and when the numbers of cancers registered are sufficient in the subgroups of interest.
Other planned analyses include the associations of tumour characteristics, by age, ethnicity and route to diagnosis.

Processing:

No data will flow to NHS England for the purposes of this Data Sharing Agreement (DSA).

NHS England will provide the relevant records from the NDRS Linked Cancer Registration, NDRS SACT, NDRS RTDS and NDRS CWT datasets to University of Oxford. The Data will contain no direct identifying data items but will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient.

The Data will not be transferred to any other location.

The Data will be stored on servers at the University of Oxford.

The Data will be accessed onsite at the premises of the University of Oxford only.

The Data will not leave England/Wales at any time.

Access is restricted to substantive employees of the University of Oxford who have authorisation from the Principal Investigator .

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will not be linked with any other data outside of this agreement.

There will be no requirement and no attempt to reidentify individuals when using the Data.

Analysts from the University of Oxford Cancer Epidemiology Unit (CEU) will analyse the Data for the purposes described above.

Active Monitoring for AtriaL Fibrillation - AMALFI trial — DARS-NIC-470203-Y2L7J

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-08 – 2025-07 2022.09 — 2025.01.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Critical Care
  5. Hospital Episode Statistics Outpatients
  6. Medicines dispensed in Primary Care (NHSBSA data)
  7. Civil Registrations of Death
  8. Hospital Episode Statistics Admitted Patient Care (HES APC)
  9. Hospital Episode Statistics Critical Care (HES Critical Care)
  10. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Identifiable

Objectives:

The University of Oxford requires linked healthcare data for consented participants in the Active Monitoring for AtriaL Fibrillation (AMALFI) study for baseline characterisation of participants and follow-up purposes. This includes centrally-collected data on primary care records, medications dispensed in the community, mortality, and Hospital Episode Statistics (HES) datasets.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide, and is estimated to affect over 1 million people in the UK. In AF, the atria (upper chambers of the heart) beat in an uncoordinated way, which disturbs the normal blood flow and can lead to the formation of blood clots inside the heart. These can travel through the bloodstream and create a blockage in the arteries supplying the brain, causing a stroke. Patients with AF are at a 5-fold increased risk of stroke, but this risk can be effectively reduced by up to two thirds with anticoagulation (blood-thinners). However, AF can occur only in short and infrequent episodes that make it hard to capture and start treatment, and it may also not cause any symptoms; as a result, some patients might have undetected AF until the time when they have a stroke.

A potential solution for this problem is to actively look for silent AF through screening in patients who are considered at risk. This is already routinely done in primary care when patients over the age of 65 years present for some other reason (for example for a routine appointment or a flu jab), in which their doctor might assess their pulse or do an electrocardiogram (ECG). However, this assessment is very short and is unlikely to detect short and infrequent AF episodes. New technology such as extended cardiac monitors and digital wearables offer the potential for increased and more frequent monitoring periods, and easier access to patients - but they are also more expensive and create additional workload for the healthcare system. At the moment, there is no conclusive evidence that screening for silent AF improves either clinical outcomes or patient quality-of-life, or if employing new AF screening strategies is a cost-effective strategy (and if so, how exactly it should be performed).

The AMALFI study is a randomised clinical trial of screening for subclinical (undiagnosed) AF in elderly patients with no previous AF, who are at increased risk of both AF and a subsequent stroke – this selection is based on a CHA2DS2VASc score of 3 or higher in men and 4 or higher in women (the CHA2DS2VASc score is a standard tool used by clinicians to assess stroke risk in patients with AF and help them decide who should receive anticoagulation). AMALFI is comparing a two-week remote continuous cardiac monitoring period with a ZioPatch to usual care alone: consenting participants will be assigned to one of the two groups by chance, in a similar way to tossing a coin, called “randomization”. The study has recruited 5,043 people through primary care practices in England. Recruitment started in 2019 and finished on February 28th 2022. The cohort is composed of 5,043 people, minus those that have withdrawn consent (6 thus far). This number of unconsented individuals may increase within the proposed duration of this Agreement, in which case, the University of Oxford will send NHS Digital an updated cohort. The main outcome of the study is the proportion of participants with newly-detected AF in both arms 2.5 years after randomisation (as shown in primary care records), with additional analyses planned in subgroups of age and sex, and at 5 years. The study may then continue collecting follow-up data for a period of up to 20 years after the initial 5 years. This long follow-up period was envisaged so that further data may be collected for longer-term outcomes (i.e. beyond 5 years), if a longer timeframe for assessment is considered important following the initial results.

If shown to be effective (and cost-effective), this approach to screening could form the basis for a potential future nationwide screening program, which could prevent stroke, disability, and premature death in this patient population. A second objective of the study is to develop streamlined procedures for running clinical trials in primary care, namely by comparing the outputs if using data collected directly from primary care practices or centrally-held data such as the datasets managed by NHS Digital.

AMALFI is sponsored by the University of Oxford and funded by the National Institute for Healthcare Research (NIHR) through the NIHR Oxford Biomedical Research Centre, with additional support from the NIHR Thames Valley and South Midlands Clinical Research Network (CRN) in the form of logistical support with recruitment only. The protocol and study procedures have been developed by a team of investigators spanning the Nuffield Department of Population Health (NDPH), the Radcliffe Department of Medicine, and the Nuffield Department of Primary Healthcare Sciences (all of which are departments of the University of Oxford) and is being run by the Clinical Trial Service Unit (CTSU) at NDPH.

Trial procedures are simple and remote, with no physical sites or dedicated staff apart from a small team at the CTSU, and no study visits. Eligible patients are being identified from primary care records in participating practices associated with the CRN. The practice runs a search of their records and generates a list of eligible patients, which is then uploaded to DocMail (a standard NHS mailing service). DocMail processes the mailing of the study documentation and, if interested, patients will return a completed questionnaire and consent form to the study team at CTSU – this includes their personal details such as name, address, date-of-birth, and NHS number. After this, participants are randomised and mailed a letter with or without a patch to self-administer (depending on the treatment allocation). Patients in the active/screening group are asked to wear their patch for 14 days and then return it using an enclosed box to iRhythm, the patch manufacturer, which analyses the data collected via the patch. iRhythm have not had and will not have any involvement in the design, conduct, analysis, or reporting of this study, nor will they have any access to NHS Digital data. A monitoring report is provided to the study team and the relevant findings shared with the patient’s GP, who manages subsequent treatment if needed. There are no study visits and follow-up data is only currently being collected from electronic record extractions at the individual practices taking part in the study. Information on quality-of-life will be collected through remote completion of mailed EQ5D (EuroQoL-5 Dimensions) questionnaires at two occasions (and for all participants at the same time): once the overall study recruitment has finished, and again approximately 2.5 years after that (i.e., coinciding with the timing of the primary outcome assessment). These questionnaires are a standard tool used in both research and clinical care settings within the NHS to assess several domains of quality-of-life (QoL; mobility, self-care, usual activities, pain/discomfort, anxiety/depression).

The University of Oxford will be the sole data controller who also process data for the study. The University of Oxford is the Data Controller as they determine the purposes for which and the manner in which the personal data disseminated under this Agreement are to be processed. The data will be stored and processed at the University of Oxford in secure servers and under strict access restrictions, and it will not be released to any other organisations or used for other purposes other than this study.

Altogether, the study requires the following datasets:
1. Medicines Dispensed in the Community (NHSBSA data)
2. Civil Registrations (mortality data)
3. HES Critical Care
4. HES Admitted Patient Care
5. Emergency Care Data Set
6. HES Outpatients

The study has also identified the need for General Practice (GP) Data, but at the current time, this data is not available. A national collection of primary care data would be a valuable resource for this study to draw upon for the research.

The data requested will be used to assess the study outcomes (namely the detection of AF) as well as other important events, such as the initiation of medication for AF, the need for additional appointments and tests, as well as hospital admissions and deaths. Altogether, these data will help the University of Oxford understand if AF screening can improve AF detection rates, what are the associated costs of doing so, and if there are particular safety signals of concern. It may also provide some initial indication of whether this procedure can improve clinical outcomes, although this is not the main purpose of the study. In particular, the NHSBSA data will be used to calculate the number of people starting anticoagulation in the active and control groups, which in turn will help the University of Oxford understand what are the likely benefits and risks of anticoagulation for subclinical AF in reducing strokes versus bleeding events.

AMALFI is collecting medications data via two routes: primary records extracted from each GP practice taking part in the study, and the centralised, nationwide NHSBSA dataset. Both sources will be used to assess rates of initiation of anticoagulation and other medications in the study cohort, and their impact on effectiveness (stroke, heart failure) and safety (bleeding) events resulting from new diagnoses of atrial fibrillation.

Given the novelty of the NHSBSA data, it is not yet known how well it overlaps with other pre-existent data sources (primary care records, in this case), and whether the NHSBSA dataset can be used on its own to retrieve medication exposure. If that was the case this would potentially improve clinical trial efficiency significantly via simplified data collection, both in AMALFI and beyond.

This work is to be undertaken in line with the NHSBSA Direction of assessing effectiveness and safety of medicines as the team is developing the methodological work required to guide future research using these data.

Finally, the conjunction of clinical events (detailed in the Civil Registrations, Medicines, HES Admitted Patient Care and HES Accident & Emergency datasets) with information on healthcare resource use (complemented by the HES Outpatients data) will provide a rich resource to assess the relative cost implications of screening from the perspective of the healthcare system, which will be crucial to inform future discussions on implementation. An additional aim of this work will be to undertake trial methodology research, specifically comparing the NHSBSA medicines data to medication data that is already being collected by the study from local GP practices. This exercise will focus on comparing the numbers of people identifying as taking particular drugs in each data source (rather than trying to audit the data collected in the NHSBSA dataset), and is hoped to help pave the way for broader use of the NSHBSA dataset for clinical trials.

Data minimisation will be pursued by only requesting datasets directly related to the outcomes of interest to the trial (clinical outcomes using primary care, admissions, and mortality data; medication initiation using primary care and dispensed medicines data; and health-care resource use using the remaining HES datasets), and requesting only the fields needed in each dataset; these have been reviewed by a clinician and a health-economist to ensure that only the necessary data is requested. Data is also only being requested for as far back as 5 years before the start of recruitment, i.e., from 2014/15 to latest available.

The objective of undertaking the AMALFI research study aiming to improve future patients’ health is the justification for processing under GDPR Article 6(1)(e) and Article 9(2)(j). In particular, AMALFI aims to provide high-grade evidence on the potential efficacy and cost-effectiveness of atrial fibrillation screening in the NHS, which it is hoped will inform future considerations regarding whether and how to roll-out a nationwide screening program, much like the existing programs for breast, cervical, and colorectal cancer. All participants in AMALFI have provided written informed consent to take part in the study, including specific consent for access to data held by NHS Digital to be provided to the University of Oxford for the purpose of this study. The study has received favourable Research Ethics Committee approval from the London - Bromley Research Ethics Committee (REC reference 19/LO/0220) and is registered in the International Standard Randomised Controlled Trials registry (reference ISRCTN15544176) and the NIHR portfolio; the Integrated Research Application System (IRAS) reference number is 234837.

Recruitment under each version of the consent:
Consent Form (v1.1) 06-FEB-19; (284 consented; in use May 2019 - August 2019) - this version only had HES/ONS wording.
Consent Form (v2.0) 15-AUG-19; (1000 consented; in use February 2020 - December 2020) - this version only had HES/ONS wording - edit not related to linkage.
Consent Form (v2.1) 27-APR-20; (2045 consented; in use February 2021 – July 2021) - this version only had HES/ONS - edit not related to linkage.
Consent Form (v3.0) 01-MAY-21; (812 consented; in use September 2021 - October 2021) - this version had GP/Medicines wording.
Consent Form (v3.1) 25-OCT-21; (902 consented; in use November 2021 - January 2022) - this version had GP/Medicines wording - edit not related to linkage.

The University of Oxford established the Clinical Trial Service Unit (CTSU), now within the Nuffield Department of Population Health, in the 1980s to conduct large trials such as the International Study of Infarct Survival (ISIS) trials. Since then CTSU has successfully completed a number of landmark studies including the 20,000 participant Heart Protection Study, the 9500 participant SHARP study, the 26,000 participant HPS-2/THRIVE study and the 30,000 participant HPS-3/REVEAL study. More recently, CTSU has coordinated the 40,000+ RECOVERY trial of treatments for COVID-19, which showed that dexamethasone, tocilizumab, and the REGN-COVID2 monoclonal antibodies were effective in reducing all-cause mortality in this population.

AMALFI is sponsored by the University of Oxford and is adopted onto the NIHR Portfolio as an academic study. iRhythm are the manufacturers of ZioPatch, the device which is being used in the study, and are providing it free of charge. iRhythm have not had and will not have any involvement in the design, conduct, analysis, or reporting of this study.

Although iRhythm could have an indirect commercial benefit if the study was to be positive (i.e., expanded use of the Zio Patch device in UK practice), this would only occur as a consequence of the study providing evidence of a benefit for public health (and pending a detailed assessment by policymakers such as the National Institute for Health and Care Excellence and others, whom would only recommend screening with the Zio Patch if any commercial benefit gained by iRhythm was outweighed by the benefits to health and social care). Moreover, the study will include cost-effectiveness analyses that will factor in not only the benefits but also any costs from the proposed intervention, producing important data for health economics analyses to be conducted in the future by policymakers, such as the National Institute for Health and Care Excellence.

Expected Benefits:

1. Provision of the data requested may help AMALFI provide important results that may affect standard clinical practice in the UK and beyond, by generating reliable evidence on the efficacy and cost-effectiveness of remote screening for subclinical AF using a self-applied patch. In particular, the datasets requested in this data dissemination are expected to form the basis for the assessment of the impacts of AF screening on anticoagulation rates, hospital admissions, outpatient appointments and A&E attendances, and deaths. While several monitoring devices are available, there is scarce randomised evidence of the added value of using such devices on top of usual care, particularly in a longer time frame (which may lead to AF cases being detected regardless of the use of the device, diluting its benefit and therefore cost-effectiveness). It is therefore expected that results from AMALFI might be incorporated in future National Institute for Health and Care Excellence (NICE), the Scottish Intercollegiate Guidelines Network (SIGN), and UK National Screening Committee guidelines; in particular, and depending on what the results of efficacy and cost-effectiveness show, AMALFI might provide the basis for a recommendation of targeted screening in elderly patients with additional comorbidities using a wearable patch in the UK, most likely in the primary care setting (and potentially managed via a central coordinating system replicating the methodology used in AMALFI). These results also have the potential to affect the care of millions of people worldwide, with potentially significant benefits in terms of reduction of fatal or disabling stroke and reduced healthcare costs (by means of reduced number of hospitalisations or A&E attendances) – the extent of which will be assessed by the detailed efficacy and cost-effectiveness analyses planned.

2. AMALFI is a streamlined and remote study with minimal data collection undertaken by participants, and none by their GPs. Participants are only asked to complete a short one-page questionnaire at enrolment (with remote EQ5D questionnaires planned at 2.5 and 5 years after inclusion), while GPs will perform a standard data extraction from their records at approximately 1, 2.5, and 5 years after randomisation. While these simple procedures make it easier for both participants and GPs to take part, they are limited in their capacity to provide detailed data that is of interest to the study (such as hospitalizations, secondary care appointments, mortality, and others). Therefore, access to data held by NHS Digital for participants in the AMALFI study will be crucial for detailed assessments of the impact of AF screening on a range of outcomes that would be hard to capture through more bespoke methods. Moreover, the provision of data on primary care records and medications as held by NHS Digital will allow the study team to potentially drop the need for GPs to run any data extractions for follow-up, further reducing the burden of taking part in research and making clinical trials more efficient, cost-effective, and attractive to busy clinicians. The comparative assessments of data collected directly from GPs or similar data held by NHS Digital may fuel the use of centrally held data by other researchers. The methods developed as part of this study may then be shared with the scientific community to improve the development of streamlined trials in cardiovascular disease and other fields.

3. The results should inform future discussions on the potential implementation of a nationwide screening program for subclinical atrial fibrillation and will be developed and disseminated to the wider public with the assistance of the Public Advisory Panel at the Nuffield Department of Population Health. If such a program were to be implemented based on these results, it could potentially involve several thousands of eligible patients in the UK each year, while paving the way for similar programs in other countries around the world.

4. Finally, the University of Oxford will aim to reach policymakers such as the National Institute for Health and Care Excellence (NICE), the Scottish Intercollegiate Guidelines Network (SIGN), and UK National Screening Committee (UKNSC). Although the University of Oxford does not expect an immediate policy change following the results of this study, the data produced may be used by both bodies to guide future recommendations for subclinical AF screening in UK practice. The University of Oxford will do this by registering as a stakeholder with these institutions and commenting on their AF management and screening guidance documents based on the findings.

Outputs:

The main results of AMALFI are expected in mid-late 2024, with long-term results in 2026. Further long-term results may be published if a longer timeframe for assessment is considered important following these results.

Dissemination of the results will be aimed at three different audiences: 1) clinical and research community; 2) patients and charities; and 3) policymakers.

The results will be disseminated widely within the clinical and research community, including presentation at relevant conferences (such as the European Society of Cardiology congress or the European Heart Rhythm Association congress) and publication in a high-impact medical journal such as Circulation, Journal of the American College of Cardiology, or European Heart Journal. Further academic papers (including results of cost-effectiveness analysis and papers about the trial methods) will be published in high impact, peer-reviewed journals (possible outlets include Trials, Clinical Trials, EuroPace, European Heart Journal Quality of Care and Clinical Outcomes) and on the trial website.

For patients and charities, a non-technical summary of the main study findings will be sent to participants and relevant charities, such as the British Heart Foundation and Arrhythmia Alliance (as well as NIHR who has funded the trial up to this stage) and published on the study website. Patient and Public Involvement will be sought in the design and sharing of outputs from the Public Advisory Panel at the Nuffield Department of Population Health (https://www.ndph.ox.ac.uk/research/participant-panel).

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

The medicines data is not deemed disclosive and information on a GP level is available in the public domain. However, should the study team consider that published information poses a risk of re-identification, the following suppression methodology should be applied:
· Zeros should be shown.
· 1-7 to be rounded to 5.
· Any other numbers rounded to nearest 5.
· Rounding unnecessary for averages etc.
· Percentages calculated from rounded values.
· If zeros need to be suppressed, round to 5.

Processing:

The flows of data:

1. The University of Oxford will provide NHS Digital with personal identifiers (sex, date-of-birth, and NHS number) plus a study ID for a cohort of consenting participants in the AMALFI study, via Secure Electronic File Transfer (SEFT). The University of Oxford will resend the cohort to NHS Digital before each data dissemination to ensure that any potential new withdrawals of consent are removed.

2. NHS Digital will link the cohort to the datasets requested and send the data back to University of Oxford via SEFT. The data will contain
- identifiable data of date-of-birth and NHS number.
- for the Civil Registration Deaths dataset, Cause of Death will also be flowed which is classed as identifiable as it is a free text field and so could potentially contain identifying information.
- requested data from the datasets.

University of Oxford are requesting that date-of-birth and NHS number (which is provided in step 1 above) are flowed back to University of Oxford for the purpose of linkage validation by the research team. The research team would like to ensure that the NHS Digital data is correctly linked given a specific cohort is being studied and many of the study outcomes will rely on the provision of correctly linked data.

The study ID is used to link the information received from NHS Digital to the cohort. However, this does not allow the University of Oxford to confirm that the data actually belongs to the correct person – therefore it is standard practice to cross-check identifiers provided by NHS Digital with those that the University of Oxford already hold to confirm correct linkage (note that NHS number and date of birth are already known to the University of Oxford, therefore NHS Digital will not be providing data that is not already held).

If a participant withdraws their consent to participation in the study (including for data linkage with NHS Digital), their wish will be recorded and they will not be included in the cohort sent to NHS Digital for linkage. The linkage cohort will be updated before each data dissemination to accommodate any potential new withdrawals of consent. Data from withdrawn participants is stored up until the point of withdrawal, with no further data collection taking place after that point.

The record-level identifiable data received from NHS Digital will be stored in a secure location within England and Wales and will only be accessed by individuals within the Clinical Trial Service Unit who have authorisation to access the data for the purpose(s) described, all of whom are substantive employees of the University of Oxford and have been appropriately trained in data protection and confidentiality. The raw data will be securely held at the CTSU within The University of Oxford in a restricted database (with access limited to a very small number of individuals), and it will not be shared outside the University of Oxford.

Data will be stored in an encrypted study database in a pseudonymised form, with identifiable fields such as NHS number or names encrypted in situ using state-of-the-art encryption methods (in line with the NHS Data Security and Protection toolkit). Access to this database is restricted to the study team and on a need to know basis, protected with username and password, and can only be accessed from internal networks. Information stored in the database can be accessed either via an internal desktop program (used to log information and contacts with participants), or directly within the database server. For the desktop program, only the study team individuals who have direct contact with participants can see identifiable fields. Within the database server, access to the identifiable fields is locked with a decryption key held by the two database managers, who are qualified programmers and substantial employees of the University of Oxford. The data will not be used by individuals outside the AMALFI study team and therefore there are no perceived risks of re-identification at this stage (outside the group of people who already have access to identifiable information as a consequence of their roles in managing the trial and contacting with participants).

Besides the data linkage described in this Agreement, AMALFI is also collecting electronic primary care records directly from participating GP practices via local data linkage; besides this, no other linkage is currently being pursued. The linked data received from NHS Digital will be stored separately from the primary care data collected via the participating GP practices until the data analysis stage (where it may be combined to produce the study outcomes). The data to be provided will not be matched to publicly available data.

The data collected via this Agreement will be used to determine the presence of atrial fibrillation diagnoses and associated symptoms (primary care and HES APC), quantify and characterise reasons for hospital admission (HES APC) and death (Civil Registrations), assess medication use (primary care and Dispensing data). In addition to this, the University of Oxford will further estimate healthcare resource use (hospital admissions, A&E attendances, outpatient appointments, need for diagnostic tests) for health economics analyses (using HES APC, HES critical care, Emergency Care Data Set, and HES outpatients).

MR576 - EPIC-Oxford. A prospective cohort study of 65,000 mainly vegetarian men and women, to examine how diet influences the risk of cancer, particularly for the most common types of cancer in Britain, as well as other chronic diseases. — DARS-NIC-148322-TMFVQ

Opt outs honoured: No - consent provided by participants of research study, N, Yes - patient objections upheld, Yes, No (Excuses: Mixed, Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006, Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Other-Data was previously disseminated on the basis of: National Health Service Act 2006 - s251 - 'Control of patient information' , and Health and Social Care Act 2012 – s261(7). Data will be retained and new data will be disseminated on the basis of, Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2019-12 – 2022-12 2018.10 — 2024.12.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. MRIS - Flagging Current Status Report
  5. MRIS - Scottish NHS / Registration
  6. Civil Registration - Deaths
  7. Demographics
  8. Cancer Registration Data
  9. Hospital Episode Statistics Admitted Patient Care
  10. Hospital Episode Statistics Admitted Patient Care (HES APC)
  11. Civil Registrations of Death
  12. HES-ID to MPS-ID HES Admitted Patient Care
  13. NDRS Cancer Consolidated Data Set
  14. NDRS Cancer Registrations

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

EPIC-Oxford is a nationwide cohort study of approximately 65,000 men and women aged 20 and above who were recruited between 1993 and 1999 from throughout the UK. The study was designed to examine the effects of diet on long-term health, with a specific focus on vegetarians; 50% of the participants do not eat meat, with large numbers following lacto-vegetarian and vegan diets, and EPIC-Oxford is the only large prospective study in the world with dietary data and stored blood samples for a large number of vegetarians together with linkage for the whole cohort to medical records covering cancer diagnoses, hospitalisations and causes of death. To produce scientifically valid results it is essential that the whole EPIC-Oxford cohort can be linked with information from medical records, because if linkage was not complete there would be a high risk of the results being biased by showing spuriously low rates of disease in some dietary groups. All EPIC-Oxford participants provided written informed consent at recruitment to the study in the 1990s.

When the study first commenced the records available were for cancer registrations and causes of death. Linkage to data from HES became possible after the completion of the recruitment to EPIC-Oxford, and linkage to HES was first established in 2008.

The study website has been continuously updated since 2010 and has informed participants of the important publications which have been possible through linkage to the HES data, such as the 2013 paper showing for the first time that the risk of hospitalization or death from ischaemic heart disease was 32% lower in vegetarians than in non-vegetarians in the UK, which was widely reported in national media such as the BBC and national newspapers (http://www.bbc.co.uk/news/health-21258509 and http://www.telegraph.co.uk/news/health/news/9837285/Vegetarians-a-third-less-likely-to-develop-heart-disease.html).

EPIC’s research on the long-term health of vegetarians is unique in the world and is supported by a grant from the MRC (“Health of Vegetarians”). All this MRC-funded research, which is focused mainly on cardiovascular diseases, bone and joint health, and gastro-intestinal diseases, is completely dependent on continued ability to link the whole EPIC-Oxford cohort with the records from HES. The study is needed to improve understanding of the effects of diet on health and thus inform advice to governments, health professionals and the public about dietary choices to maximise the potential for long-term good health. Further aims include examining the roles of other lifestyle factors (including shift-work) and of endogenous hormones in relation to health. Many papers on diet and cancer risk have been published and now the availability of the HES data has enabled the extension of the research such as in the study's recent papers on ischaemic heart disease, diverticular disease and cataracts. The study’s overall aim is to provide reliable evidence on choices people can make in adult life to help increase their chances of staying healthy into old age. Further information can be found on the study website www.epic-oxford.org.

Study participants’ records are linked electronically to Hospital Episode Statistics for information on cause-specific hospital admissions, for example cancer diagnoses, cardiovascular disease, joint replacements and fractures. This is to examine the relationships between dietary, lifestyle and other potential risk factors with subsequent health. The aim is to contribute to knowledge of the epidemiology and aetiology of common diseases and other causes of hospital admissions. One of the primary outcomes is cause of mortality so continued receipt of this data is required.

Yielded Benefits:

The EPIC-Oxford study research using linked health data has direct public health relevance, in particular for the more than 1.2 million vegetarians in the UK (NHS Choices:https://www.nhs.uk/live-well/eat-well/healthy-eating-vegetarians-vegans/). For example, the research has shown that, compared to regular meat-eaters, vegetarians have a lower incidence of obesity, lower blood pressure, and a lower risk of ischaemic heart disease, diverticular disease, cataracts and of all cancers combined. This research provides important evidence which enables the NHS to recommend healthy vegetarian diets, and also more broadly expands scientific understanding of the effects of diet on health, which is essential for further development of dietary recommendations for optimum health by the NHS and Public Health England. Other work has shown that vasectomy does not increase the risk for prostate cancer, that shift work does not increase the risk for breast cancer, and that vegetarians are less likely to attend for breast cancer screening than non-vegetarians, all important findings for public health.

Expected Benefits:

Diet has been identified as the number one cause for the burden of disease worldwide, and by providing new evidence on the impact of diet on health EPIC-Oxford will contribute to reducing the work and cost to the NHS of diet-related ill-health.

The aim of EPIC-Oxford is to improve information on diet in relation to the risk of cancer and other chronic diseases, which offers huge potential for improvements in public health in the UK. The results are published in peer-reviewed publications and presented at conferences, and are also reported through national media. Over 500 peer-reviewed publications, mostly on diet and cancer, have included data from EPIC-Oxford: see http://www.epic-oxford.org/publications/.

EPIC-Oxford’s research relates directly to the health of 1.2 million people in the UK who follow vegetarian diets (NHS 2014). The long-term effects on health of a vegetarian diet are not well understood, and little is known about the health effects of a vegan diet. Previous research has demonstrated lower risks of ischaemic heart disease, stomach cancer and perhaps haematological cancers in vegetarians compared with non-vegetarians (Crowe et al 2013, Key et al 2009, 2014), but understanding of these relationships is incomplete. Further research is needed to assess both the potential beneficial effects of a vegetarian diet and also possible hazards associated with low intakes of some nutrients, such as protein, long-chain n-3 fatty acids, vitamin B12, vitamin D and calcium (particularly in vegans). As well as peer-reviewed scientific publications, the EPIC-Oxford website (www.epic-oxford.org) will be used to describe all findings, with lay summaries of findings when appropriate, copies of abstracts, and links to pdfs of full papers. The website provides information both for study participants and for a wider audience in the UK and worldwide and where appropriate we will also communicate with the NHS because the research will provide information to underpin their advice, e.g. as on their website: http://www.nhs.uk/Livewell/Vegetarianhealth/Pages/Goingvegetarian.aspx

EPIC-Oxford will directly benefit health care through the NHS by providing clinicians and other NHS health care professionals with up-to-date evidence-based guidance on the effects of diet on long term health and the risk of death. This will improve clinical health care and inform planners and policy makers to address demands on health and social care in the present and the future.

Target dates are ongoing.

Outputs:

Publications are produced on an ongoing basis. These do not identify individuals and contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide. Results are disseminated in peer-reviewed open-access papers in research journals, and related presentations to national and international colleagues, including clinicians. EPIC currently has funding to follow up patients until 2020.

The data is processed only by those named researchers and students within the Cancer Epidemiology Unit. For all of these outputs data is released only de-identified data in aggregate form (tabulations and figures showing analysis results at the minimum level of detail required, using small number suppression).

Publications and a summary of the research outputs are available to the public, to participants and to health researchers and clinicians through the study website (www.epic-oxford.org).
EPIC–Oxford results are reported in the media such as the BBC and national newspapers e.g. (http://www.bbc.co.uk/news/health-21258509 and http://www.telegraph.co.uk/news/health/news/9837285/Vegetarians-a-third-less-likely-to-develop-heart-disease.html) and its outputs reach a worldwide audience.

Future anticipated work using HES, ONS mortality and Cancer Registry Data:

The EPIC-Oxford’s Medical Research Council Grant MR/M012190/1 "Health of vegetarians" specifies a programme of research on the associations of vegetarian diets and related nutritional factors with the incidence of common diseases. In 2017 and 2018 the study will analyse:
• the relationships of vegetarian diets with the risk for ischaemic heart disease, extending previous published research on this topic with larger numbers of incident cases identified through HES and examining the extent to which the effects of a vegetarian diet may be explained by the consumption of saturated and polyunsaturated fatty acids, fruit and vegetables and dietary fibre. The intention is to complete this manuscript early in 2018 and to submit it to the British Medical Journal.
• In parallel analyses commencing in 2017, the study will examine the associations of vegetarian diets with risk for stroke, using the HES linkage to identify incident cases and to categorise then as ischaemic, haemorrhagic, or other types of stroke. Preliminary analyses based on a previous linkage to the HES data suggested that vegetarians had a somewhat higher risk of stroke than meat-eaters, but the number of cases was too small for robust analyses. With the new linkage to HES about 2000 cases of stroke are expected which will provide sufficient power to conduct reliable analyses, and to explore the possible roles of protein and vitamin B12 in determining stroke risk in vegetarians. The intention is to submit this manuscript in 2018 to the journal Circulation.
• Following these analyses of cardiovascular disease, at the beginning of 2017, the study will commence analyses of the relationships of vegetarian diets with the risk for musculoskeletal disorders: fractures of the forearm, wrist and hip, hip and knee replacement, and carpal tunnel syndrome. The study will examine whether associations of vegetarian diets with the risk for these disorders may be due to differences in intake of calcium and protein, and will aim to submit the papers to the American Journal of Clinical Nutrition in late 2018/early 2019.
• In 2019-2020 the intention is to examine vegetarian diet and gastrointestinal diseases including Crohn’s disease, ulcerative colitis and gallstones.
• The study’s Cancer Research UK grants on the Epidemiology and Aetiology of High Risk Prostate Cancer and the core grant of the Cancer Epidemiology Unit(CEU) specify a program of research on the risk for prostate cancer and the cancers in relation to and related factors and other diseases.

Conferences
The intention is to present the research findings at the following conferences:
• 2017 – Nutritional Society UK Symposium
• 2017 European Association of Urologists
• 2018 7th International Congress on vegetarian Nutrition., Loma Linda California.
• 2018 The National Cancer Research Institute (NCRI)
• 2019 The National Cancer Research Institute (NCRI)

Processing:

The majority of the EPIC-Oxford cohort are flagged on NHS Digital’s MIDAS system. NHS Digital provide monthly updates on participant events including removals and re-entries to NHS registration, cancer registrations and deaths including cause of death details.

The EPIC-Oxford team will supply a file of identifying details for additional participants of the EPIC-Oxford study that are not currently flagged within this cohort on the NHS Digital system. NHS Digital will then flag these members.

NHS Digital will link the full cohort to Hospital Episode Statistics records and supply pseudonymised linked data to EPIC-Oxford.

Using the study ID, the EPIC-Oxford team link the data with study participants’ records collected over time directly from the participants and from NHS Digital and ONS plus linked data from Scotland (via the Public Benefit and Privacy Panel for Health and Social Care) and from Northern Ireland (via the Central Services Agency). The linked data is stored separately from the patient identifiers. Participant identifiers linked to the study ID numbers are stored separately to the dataset for use in analysis and are held only for administrative purposes and for use in facilitating ongoing data linkage. The analysis dataset (containing the study participant’s linked records from the sources specified above) will not be re-linked with the identifiers. The analysis dataset contains full date of death for individuals whose deaths were reported prior to December 2016. This is the only identifiable field held within the analysis dataset. All subsequent data supplied by NHS Digital will be pseudonymised. It will contain month and year of death rather than full date of death. The analysis dataset also contains month and year of birth.

Only month and year of birth and/or death will be used in future analyses. All subsequent analyses use only subsets of the pseudonymised data. All such subsets are customised according to the characteristics relevant to the specific analysis containing only the minimum data required for the specific purpose.

Various types of analyses are undertaken on an ongoing basis for the overarching purpose of assessing cancer incidence, health risks and overall mortality. The data will be held only at the Cancer Epidemiology Unit at the University of Oxford. The datasets will be pseudonymised as described above before statistical analyses are undertaken.

The data will only be accessed by authorised members of the EPIC-Oxford study team, all of whom are substantive employees of the University of Oxford, or non-contractual DPhil,MSc students who complete University Research Services form agreeing to terms and conditions of the project, grant and latest Data Sharing Agreement. These are filed in Research Co-ordinators office with signed copies sent to Director of Research Services at University of Oxford. Access to ONS mortality data is restricted to individuals with Approved Researcher accreditation named within the Data Sharing Agreement. The data will only be used for the objectives of the study as described within the Data Sharing Agreement. The EPIC-Oxford study will not share any data supplied by NHS Digital with any other institution or individual outside of the study team at Oxford University.

OPAL - The Oxford Pain, Activity and Lifestyle (OPAL) Cohort Study — DARS-NIC-288807-P0R9B

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-03 – 2028-10 2024.08 — 2024.11.

Access method: One-Off

Data-controller type: UNIVERSITY OF EXETER, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death - Secondary Care Cut
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Accident and Emergency (HES A and E)
  4. Hospital Episode Statistics Admitted Patient Care (HES APC)
  5. Hospital Episode Statistics Critical Care (HES Critical Care)
  6. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford and the University of Exeter requires access to NHS England data for the purpose of the following research project: OPAL - The Oxford Pain, Activity and Lifestyle (OPAL) Cohort Study.

The following is a summary of the aims of the research study provided by the University of Oxford:

a. Describe the prevalence, severity, course, and prognosis of a range of musculoskeletal problems in older people.
b. Evaluate the impact of back pain on important health outcomes for older people (quality of life, mobility, falls and fractures)
c. Study a range of factors hypothesised to moderate and mediate the effects of back and other musculoskeletal pain for example, co-morbidities.
d. Perform an economic evaluation of cost of NHS resources used by participants mapped to the health conditions that were self-reported at baseline and in subsequent follow-up questionnaires.

The OPAL Cohort Study is being conducted under a programme of works funded by the National Institute for Health Research Programme Grants for Applied Research funding scheme. The OPAL Cohort Study are projects 2, 3 & 6 of the programme of works detailed below:

1. To refine a physiotherapy intervention for Neurogenic Claudication (NC) (Project 1). NC is intermittent leg pain from impingement of the nerves emanating from the spinal cord
2. To complete a feasibility study for a prognostic study and clinical trial of the NC intervention in the UK NHS (Project 2)
3. To develop a tool that is expected to help clinicians and older people recognise when and what types of Low Back Pain (LBP) are important targets for treatment for older people. The outcomes will be mobility disability (primary model), disability, frailty and falls (Project 3)
4. To undertake a definitive randomised controlled trial demonstrating that access and participation in a physiotherapy intervention for NC can improve important outcomes including pain, disability, mobility, frailty and falls (Project 4)
5. Explore whether MRI scans and other factors can help determine who may and may not respond to this treatment (Project 5).
6. To integrate the findings of the trial and the prognostic tool into a package of treatments that can be used in primary care and other settings. This is intended to include exploring GP's attitudes and beliefs to inform implementation and future research (Project 6).

The following NHS England data will be accessed:
> Hospital Episode Statistics;
- Admitted Patient Care
- Accident & Emergency
- Critical Care
- Outpatients
The use of Hospital Episode Statistics data is expected to allow an economic evaluation of the cost of NHS resources used by participants mapped to the health conditions that were self-reported at baseline and in subsequent follow-up questionnaires. Data is requested from the four HES datasets to ensure the study team capture a complete picture of NHS usage by study participants.
> Emergency Care Data Set (ECDS) – necessary because this dataset replaced HES Accident & Emergency dataset from 2019 onwards.
> Civil Registration of Death (Secondary Care Cut) – Necessary to know the time frame that participants may have been accessing health care. In addition, deaths data will be used to minimise any distress caused to surviving family members if further questionnaires regarding the deceased participant were to be sent.

The level of the data will be:
> Pseudonymised

The data will be minimised as follows:
• Limited to a study cohort identified by the University of Oxford – 5,409 community dwelling adults aged 65 years and over, invited from 35 primary care practices across England within West Yorkshire, Merseyside, West Midlands, Gloucestershire, Dorset, Wiltshire, London, Oxfordshire and Cambridgeshire.
• Limited to data between October 2016 and October 2023. For each individual patient, data will only be provided from the date they consented to join the trial until 5-years after the date of consent.

The University of Exeter as the research sponsor, and the University of Oxford as the main collaborator, are joint controllers as the organisations responsible for ensuring that the data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research, which protects and promotes the interests of patients, service users and the public, and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care.

The funding is provided by the National Institute for Health Research. The funding is not specifically limited to the study described. This funding is in place until 31st January 2024. Further funding from the NIHR Oxford and Thames Valley Applied Research Collaboration is place to specifically support this study until 30th September 2024.

The funder(s) will have no ability to suppress or otherwise limit the publication of findings.

Microsoft Limited provides IT hosting services to the University of Exeter and will store the Data as contracted by the University of Exeter.

There are no other organisations involved in an advisory capacity or as part of a steering committee.

The data will be accessed by substantive employees of the University of Exeter.

The University of Oxford worked with a Patient and Public Involvement and Engagement Group of people of 65 years of age throughout the study to refine the purpose of the research. The group were very supportive of the research and strongly supported the collection of the data the purposes described above. The study team met with the PPI group and discussed the relevance of different outcomes related to this programme of work including the importance of health care use as an outcome. In addition, a PPI Representative was part of the study team management group who were responsible for delivering this research and helped develop the protocol in which health research use is included as one of the key outcomes of interest of the OPAL study.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for clients; policy-makers, local decision-makers such as doctors, and patients to inform best practice to improve the care, treatment and experience of health care users relevant to the subject matter of the study.

The use of the data could:
• help the system to better understand the health and care needs of populations.
• lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
• advance understanding of the need for, or effectiveness of, preventative health and care measures for patients over 65 suffering with low back pain.
• inform planning health services and programmes, for example to improve equity of access, experience and outcomes.
• inform decisions on how to effectively allocate and evaluate funding according to health needs.
• provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

The use of a prognostic tool to help General Practitioners understand when low back pain should be considered a substantial threat to the well-being of older people may benefit patients by relieving or preventing loss of mobility, disability, and potentially reduce risk of frailty and falls.

It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

Clients will need to take action based on the information provided to them in order to realise the potential improvement opportunities. For example, General Practitioners would need to adopt and utilise the prognostic tool to maximise benefits to patients.

Outputs:

The expected outputs of the processing will be:
• Submissions to peer reviewed journals such as The Journals of Gerontology and Age and Ageing. The study team expect to submit papers to journals from 2024.
• Presentations at appropriate conferences such as The British Society of Gerontology Annual Conference and The Society for Academic Primary Care Annual Conference.
• Publication of a plain English summary of study results for the general public on the study website (University of Oxford’s website https://opal.octru.ox.ac.uk/welcome )
• Outputs will inform the development of training materials for health professionals working with older people along with findings from the broader programme of research including the prognostic tool developed to identify when older people are at risk of mobility decline. This training would be provided free of change.

The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Website publications - The website will host published articles, conference papers, videos and tutorials for NHS colleagues, health care planners, commissioners, and patients. It is expected that this will include e-learning tutorial videos demonstrating the prognostic tool and providing a prognostic calculator for both the public and healthcare professionals. The website is expected to include oral and video clips of older people describing their experiences of living with lower back pain (LBP).
• Social media
• Posters displayed at relevant conferences.

The University of Oxford expects to produce and disseminate outputs from 2024 onwards.

Processing:

The University of Oxford will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Surname, Forename, Date of Birth, Postcode, Gender and Consent Date), for the cohort to be linked with NHS England data.

NHS England will provide the relevant records from the HES Outpatients, HES Critical Care, HES Admitted Patient Care, HES Accident & Emergency, Emergency Care, and Civil registrations of death datasets to the University of Exeter. The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other identifiable record level data already held by the recipient.

The data will not be transferred to any other location.

The data will be stored on servers at the University of Exeter only.

The University of Exeter stores Data on the Cloud provided by Microsoft Limited.

The Data will be accessed by authorised personnel via remote access.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Remote processing will be from secure locations within England/Wales. The data will not leave England/Wales at any time.

Access is restricted to individuals within The University of Exeter who have authorisation from the Principal Investigator. All such individuals are substantive employees of the University of Exeter.

All personnel accessing the data have been appropriately trained in data protection and confidentiality.

The data will be linked with questionnaire data obtained from OPAL cohort study using the study ID.

The identifying details from the questionnaire data will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset.

Statisticians and data analysts from the University of Exeter will analyse the data for the purposes described above.

Supporting people with type 2 diabetes in effective use of their medicine through a system comprising mobile health technology integrated with clinical care compared with usual care: a randomised controlled trial. — DARS-NIC-684835-V0W0X

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2024-04 – 2026-04 2024.11 — 2024.11.

Access method: One-Off

Data-controller type: BANGOR UNIVERSITY, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Emergency Care Data Set (ECDS)
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)
  3. Hospital Episode Statistics Critical Care (HES Critical Care)
  4. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

Bangor University and the University of Oxford require access to NHS England data for the purpose of the following research project:

Supporting people with type 2 diabetes in effective use of their medicine through a system comprising mobile health technology integrated with clinical care compared with usual care: randomised controlled trial (SuMMiT-D)

The following is a summary of the aims of the research project provided by Bangor University and the University of Oxford:

Type 2 diabetes is a common disease affecting over 400 million people worldwide. Risk of serious complications can be reduced through use of effective treatments and active self-management. However, people are often concerned about starting new medicines and face difficulties in taking them regularly. Use of brief messages to provide education and support self-management, delivered through mobile phone-based text messages, can be an effective tool for some long-term conditions. The University of Oxford and the University of Manchester have developed and tested messages aiming to support patients’ self-management of type 2 diabetes in the use of medications and other aspects of self-management, underpinned by theory and evidence.

The aim of this trial is to compare the effectiveness and cost-effectiveness of brief messaging to support patients with type 2 diabetes taking diabetes medicine (glucose, blood pressure, or lipid lowering) in reducing risk factors for diabetes complications, with usual care. The economic analysis is required as it cannot be assumed that an effective intervention will save costs or offer value for money for the NHS.

To fulfil the objective of the SuMMiT-D study relative to cost-effectiveness, Bangor University will conduct a health economic analysis that will adopt the perspective of the National Health Service (NHS) and Personal Social Services (PSS). By measuring resource use, researchers will estimate the overall cost for each patient. The NHS England data will be analysed using standard statistical and health economic methods, and an existing health economics model will be used to estimate costs and benefits over a lifetime.

Online patient questionnaires have also been administered but are reliant on patient completion as well as patient recall and may introduce biases into the cost-effectiveness analysis results. Questionnaire data will be used to supplement HES data for participants where HES data are unavailable. This information can then be used to inform future support for NHS patients with the condition by indicating which arm offers the best value for money.

Once data processing is complete, the Data will be archived to allow any questions or challenges on the published results to be addressed, which may lead to a need to repeat the previously analyses undertaken to verify that the published results were accurate.

The following NHS England Data will be accessed:
> Hospital Episode Statistics Admitted Patient Care (HES APC), Emergency Care Data Set (ECDS), HES Critical Care (CC) and HES Outpatients (OP). These datasets are required to obtain robust, reliable data on hospital visits and to cost the two intervention arms compared in the study, which comprises an evaluation of the resources used by patients in the SuMMiT-D trial. Some demographic data are requested as they are required for processing using the NHS England Costing Grouper.

The level of the Data will be:
> Pseudonymised

The Data will be minimised as follows:
> Limited to a study cohort identified by the University of Oxford – SuMMiT-D opened for recruitment in March 2021 and reached its recruitment target by July 2021 with a total of 1039 participants. Participants were followed over a period of 52 weeks. Data is restricted to patients who have consented to participate in the SuMMiT-D trial and have agreed for their personal data to be shared with NHS England.
> Limited to data between 2020/21 and 2022/23. For each individual patient, data will only be provided from 3-months prior to their entry in the study and spanning the duration of 12—months after their recruitment, including any episodes that run during this period. Data prior to entry into the study is required to establish a participants baseline costs. Episode start date is required in order to separate episodes in the baseline period from those during the trial period.
> Fields requested are minimised to those required by the NHS England Costing Grouper.

The University of Oxford is the research sponsor. Together, with Bangor University, the organisations are jointly responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because it is expected to inform the NHS, clinical commissioners and other healthcare decision makers on the most clinical and cost-effective intervention for this condition.

The funding is provided by National Institute for Health Research (NIHR). The funding is specifically for the study described.

The funder(s) will have no ability to suppress or otherwise limit the publication of findings.

The University of Manchester was involved in the overall programme design, and collaborators in the University of Manchester were involved in the following activities: creating the text message library, formative work on the text messages, and, during the feasibility and main trials, recruitment of participating GP practices, participant recruitment, qualitative interviews with participants, and qualitative analysis of participant completed questionnaires. A co-investigator for the study based at the University of Manchester assisted in the recruitment phase only. The University of Manchester will not have access to or any influence on how or why the NHS England data will be processed.

A Patient and Public Involvement (PPI) group was established at the start of the programme. The group were involved in reviewing the trial materials (Patient information leaflets, consent forms and posters) prior to submission to the research ethics committee. Throughout the programme, the University of Oxford have continued to hold regular meetings with the PPI group at key stages of the programme to update and gain feedback on patient facing documentation, and plans for dissemination of results when available. The PPI group is also represented on the programme steering committee.

Outputs:

The expected outputs of the processing will be:
> Public reports (one-off submission expected at the end of data processing)
> Contributions to the NIHR PGfAR report underpinning the SuMMiT-D study, which will be a wider report on the entire SuMMiT-D study published on the NIHR website. One of the sections of this report will be dedicated to health economics.
> Submission to a peer reviewed journal, such as the New England Journal of Medicine.
> Presentations at appropriate local, national and international conferences and symposium

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
> Journals
> Presentations at appropriate local, national and international conferences and symposium
> Public reports
> The wider report on the entire SuMMiT-D study will be published on the NIHR website

Outputs are expected to be produced within 18 months of the receipt of data from NHS England.

Processing:

The University of Oxford will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, Names and a unique person ID) for the cohort to be linked with NHS England data.

NHS England will provide the relevant records from the HES and ECDS datasets to Bangor University. The Data will
> contain no direct identifying data items but will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient

The Data will not be transferred to any other location.

The Data will be stored on servers at Bangor University.

The Data will be accessed onsite at the premises of Bangor University only.

The Data will not leave Wales at any time.

Access is restricted to employees or agents of Bangor University who have authorisation from the Principal Investigator. All such individuals are substantive employees of Bangor University.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

Patients will be linked to their arm of the study via their unique person ID. Bangor University researchers will not have access to the unique person ID key that allows patient identification.

Bangor University will derive Healthcare Resource Groups (HRG) codes from the HES data using the NHS England Costing Grouper and will apply HRG costs from publicly available National Tariff registers.

The cost data will then be extracted to the health economics analysis file and linked with study data including self-reported resource use and outcomes obtained from patient questionnaires and primary care and prescribing resource use data obtained via Egton Medical Information Systems (EMIS). The health economics analysis file will be held on secure servers at Bangor University.

The Data will not be linked with any other data.

Researchers from Bangor University will analyse the Data for the purposes described above.

DART: The Integration and Analysis of Data using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases — DARS-NIC-668928-L9N5F

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: Yes (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2023-10 – 2024-10 2024.02 — 2024.11.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Cancer Registration Data
  2. Civil Registrations of Death
  3. Emergency Care Data Set (ECDS)
  4. Hospital Episode Statistics Accident and Emergency (HES A and E)
  5. Hospital Episode Statistics Admitted Patient Care (HES APC)
  6. Hospital Episode Statistics Critical Care (HES Critical Care)
  7. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Identifiable

Objectives:

The University of Oxford requires access to NHS England Data for the purpose of the following research project:
DART (The Integration and Analysis of Data using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases)

The following is a summary of the aims of the research project provided by University of Oxford:

DART is a study developing integrated diagnostics to enable the earlier diagnosis of lung cancer. This study, which began in 2020, aims to improve patient survival, yielding time and cost efficiencies to the NHS. The overall objective of the study is to link data from the Targeted Lung Health Checks (TLHC) programme, collected by the Lung Health Centres and sent to Oxford University Hospitals NHS Foundation Trust (OUH), with NHS England Data to better predict those who will benefit from lung cancer screening and to develop artificial intelligence systems that could improve understanding (through machine learning) of co-morbidities and confirm or improve standard clinical practices. Costs and survival will be summarised for groups of patients for various health states. It is anticipated that limited data will be received on secondary care resource use via the TLHC Programme. Based on initial inspections, this data will be fragmented, will cover a more limited follow-up period, and will not be available in detail for all participants in the TLHC programme. The Data requested from NHS England under this Agreement is expected to considerably enhance the study by providing less biased data and ensuring that missing secondary care resource use data is minimised.

Another objective of DART is to improve and enhance the existing evidence base on outcome prediction for patients with lung cancer. The requested Data will be used to identify patients with lung cancer who relapse or die; analyses using these Data will assess the efficacy of current and proposed clinical approaches.

OUH has been granted and funded for a Trusted Research Environment (TRE). The data from DART will be stored in this TRE, which will be managed in accordance with the relevant approvals from the Confidentiality Advisory Group (CAG), health Research Authority (HRA), and the Research and Development Department of the OUH. Access to the TRE for researchers will be governed by the above regulations and will require detailed applications and approval by the TRE Data Access Committee (TRE DAC). The NHS England data requested for DART will be stored in the DART section of the TRE.

DART has a total of nine work packages
• WP1 Leadership and Project Management
• WP2 Planning for, and management of Datasets, and Integration
• WP3 AI Model Validation on Lung Cancer Screening (LCS) data
• WP4 Digital Pathology AI and Radiomics Model Development and Validation
• WP5 Chronic obstructive pulmonary disease (COPD)/ Coronary artery disease (CAD) Model Development and Validation
• WP6 Primary Care/Population Health and Health Economics
• WP7 Integration of Blood Biomarkers
• WP8 Outcome prediction and new treatment paradigms
• WP9 Quality assurance: radiologist training and monitoring

The requested Data will be used in multiple DART work packages (WPs 4, 5, 6, 8) to further its overall aims:

> WP4: This WP relates to development of an artificial intelligence algorithm to diagnose lung cancer from digital pathology images. The HES data will enable ground truthing (a Gold Standard that can be used to compare and evaluate model results) of cancer diagnoses and for the algorithm to learn which of the cancers are fatal and incurable.

> WP5: This WP relates to lung cancer comorbidity, and to maximising the clinical information gathered during a single computerised tomography (CT) exam study of the chest, to allow for earlier treatment of patients who have underlying, unrecognised diseases or conditions such as Chronic Obstructive Pulmonary Disease (COPD) and Coronary Artery Disease (CAD). The aim of WP5 is to automate the identification of comorbid states (COPD and CAD) related to or caused by lung cancer, by developing and implementing machine learning models. The aim is to utilise all standard of care data captured during the lung cancer screening programme, if available through the normal course of clinical practice, to identify incidental findings that may be picked up in the TLHC patient cohort through the screening programme.

> WP6: The aim of half of WP6 is to assess whether the addition of an AI component to the Lung Cancer Screening Programme (LCSP) in England is cost-effective, compared to current practice. This is to be achieved by constructing a decision-analytic model to evaluate resource use, costs and health outcomes for patients in the LCSP over time, with and without the AI component in place. A specific type of model will be built – a state transition model – in which patients move between different lung cancer specific health states periodically over a time horizon of several years. By spending time in these health states, patients accrue costs and health outcomes. The requested HES-TLHC linked Data will be used to determine an appropriate cost for each health state, and the requested linked mortality Data will be used to inform estimates of survival outcomes in each health state. To achieve the former, the HES-TLHC linked Data will be combined with NHS Reference Costs to calculate the secondary care costs accrued by patients in specific health states.

> WP8: The aim of WP8 is to improve and enhance the existing evidence base on outcome prediction for patients with lung cancer. The aim is to identify predictors of unexpected (usually poor) outcome. This will require a wide spectrum of data that might help predict, for example, greater mortality, lower recurrence-free survival and overall survival than expected having accounted for all of the known factors that influence these (such as age, performance status and stage). This will be achieved by using the requested Data linked to TLHC data to identify patients with lung cancer who relapse or die. Analyses will be undertaken using this data to confirm the efficacy of current clinical approaches and suggest standardised approaches that may reduce unwarranted variation. The results of these analyses will also be used to challenge existing practice that does not meet the outcomes achieved in better services and suggest new paradigms of care by identifying novel markers of unexpected outcomes. WP6 and WP8 are necessarily linked: the model that will be constructed in WP6 will be adaptable such that the cost-effectiveness of standardised and new clinical approaches can be tested.

The other work packages will not use the NHS England data provided under this Agreement.

The following NHS England Data will be accessed:

> Hospital Episode Statistics; necessary for the analysis of the algorithms developed in WP5 to determine if they can detect and quantify clinically meaningful COPD and CAD from the Lung Cancer Screening CT scans, and the requested HES-TLHC linked Data will be used to determine if the AI algorithms developed relate to clinically important episodes. For WP6, HES Data is required for the cost-effectiveness analyses and the requested HES-TLHC linked Data will be used to determine an appropriate cost for each health state. For WP8, the HES data is required for the analysis of the algorithms developed in this work package to determine if they can determine whether and why, patients from the TLHC Lung Cancer Screening CT scans die from lung cancer and are not cured despite having early-stage disease. Specifically, the following HES Data is required:
- Admitted Patient Care - necessary to determine how often patients from the TLHC are admitted to hospital and whether it is due to COPD, CAD or lung cancer.
- Accident & Emergency - necessary to determine how often patients from the TLHC are seen in Emergency Departments, and whether it is due to COPD, CAD or lung cancer and to estimate costs associated with lung cancer treatment.
- Critical Care - necessary to determine how often patients from the TLHC are admitted to ICUs and whether it is due to COPD, CAD or lung cancer and to estimate costs associated with lung cancer treatment.
- Outpatients - necessary to determine how often patients from the TLHC are seen in OPs and whether it is due to COPD, CAD or lung cancer and to estimate costs associated with lung cancer treatment.
> Emergency Care Data Set (ECDS) – necessary to determine how often patients from the TLHC are seen in Emergency Departments, and whether it is due to COPD, CAD or lung cancer and to estimate costs associated with lung cancer treatment.
> Civil Registration Mortality - necessary to determine whether patients from the TLHC centres have died from COPD, CAD or lung cancer and because mortality Data will be used to inform estimates of survival outcomes associated with health states.
> Cancer Registration - necessary to determine who in the cohort has / has had cancer and who has died from it.

The level of the data will be:
> Identifiable – NHS number is required to link the NHS England Data to the TLHC data.

The data will be minimised as follows:
> Limited to a study cohort identified by Oxford University Hospitals NHS Foundation Trust (OUH) – approximately 300,000 participants of the TLHC programme
> Limited to data for episodes after the start date (individual specific; this will be the date the cohort member attended their screening). Cancer and deaths data will not be filtered in this way.
> Data access is minimised according to the research purpose within the TRE. This means that researchers within each distinct work package will have access only to the Data that they need.

The University of Oxford is the sponsor and controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
> Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.

The lawful basis for processing special category data under the UK GDPR is:
> Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Early detection and treatment of asymptomatic patients is crucial. Detecting lung cancer early when it is small and seen on a CT scan as a small nodule is currently recognised as the best way to do this. The ambition the DART study is to see if some of the aspects of lung cancer screening can be improved, which is expected to provide public healthcare benefits.

The funding is provided by Innovate UK, with in kind funding (non-monetary) from GE Healthcare (GEHC) and Roche Diagnostics Ltd. The funding is specifically for the component of the project described. Funding is in place until the end of March 2024.

OUH, GEHC, Optellum and Nottingham University Hospital NHS Foundation Trust (NUH) are processors acting under the instructions of the University of Oxford.

Microsoft Limited provides IT hosting services to OUH and will store the Data as contracted by OUH.

A Patient and Public Involvement and Engagement (PPIE) group assisted with the grant application and another PPIE group assisted with the programme design after the grant was received and has an on-going role in advising the project through quarterly meetings and ad hoc email/video calls as needed.

GEHC are a commercial organisation and a processor under this Data Sharing Agreement for the purpose described. They will be using the data obtained under this agreement, in combination with the data DART is obtaining from the Targeted Lung Health Checks, to develop and improve artificial intelligence algorithms to better predict respiratory conditions such as cardiac diseases and COPD.
GEHC make a considerable (over 1 million pounds) kind contribution to the project and, as a commercial company, would naturally expect a commercial gain and the publicity associated with participating in a prestigious project which has attracted Government and national media attention. The expected health and social care benefits of their contribution into the project outweigh any commercial gain they would receive from the project.

Alongside the University of Oxford academic team, Roche Diagnostics Ltd make an in-kind contribution of their expertise into WP4 and have loaned a Digital Pathology Scanner to DART (in Oxford) and provided a staff member to operate this. As a funder and commercial organisation, Roche Diagnostics reasonably expect a commercial return and to receive acknowledgement and publicity for their participation in the project. In turn, their contribution to the earlier detection of lung cancer far outweighs any likely commercial return.

Expected Benefits:

The requested Data will be used to undertake analyses that are expected to reveal:
• The cost-effectiveness of adding an AI component to the Lung Cancer Screening Programme in England, compared to current practice.
• The efficacy of (a) current clinical approaches to outcome prediction; (b) plausible standardised approaches to outcome prediction, and (c) potential new paradigms of care by identifying novel markers of outcomes.

It is expected that these findings will have the following benefits for patients in the English NHS, and the health sector overall:
• Lung cancer could be more accurately diagnosed, with enhanced prognostic information.
• The time to diagnosis for lung cancer could be reduced.
• The frequency of use of harmful invasive procedures in the diagnostic pathway could be reduced.
• Selection of patients for lung cancer screening could be improved, reducing the overall cost allocation for this.
• The assessment of risks from comorbidities could be improved.

The results of the planned analyses will be communicated directly to the National Screening Committee (NSC) by collaborators who also have a position on this committee, thus ensuring that the findings directly influence and optimise the implementation of the Lung Cancer Screening Programme. Results will be communicated to the NSC upon the completion of DART in March 2024, and are thus expected to begin to translate into direct patient benefit quickly. Around 48,000 people are diagnosed with lung cancer every year in the UK, so the potential health benefits and cost impacts could be significant.

Outputs:

The expected outputs of the processing will be:
> A report of findings to funding bodies (Innovate (part of UK Research and Innovation); Cancer Research UK (CRUK)): expected March 2024
> A summary of findings to relevant stakeholders (Innovate UK, CRUK, Roche, Optellum, GEHC): Expected March – May 2024
> Submissions to peer reviewed open-access journals: Specific target journals will be identified as the work progresses to ensure the study findings are communicated to appropriate audiences. Expected January – June 2024
> Presentations will also be given at national and international conferences relevant to lung cancer and screening

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
> Journals
> The results of the planned analyses will be communicated directly to the National Screening Committee (NSC) upon the completion of DART in March 2024 by collaborators who also have a position on this committee
> Results will be shared with the staff at the TLHC centres and other operational staff involved in lung cancer screening
> DART Patient and Public Involvement and Engagement (PPIE) contributors, including the Roy Castle Lung Cancer Foundation, will be consulted to communicate findings to the general public and patients in an accessible way
> Results will be communicated to the National Screening Committee upon the completion of DART in March 2024
> National and International conferences

Outputs are expected throughout 2024.

Processing:

OUH will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Gender, Date of Birth, and a DART Study ID) for the cohort to be linked with NHS England Data.

NHS England will provide the relevant records from the HES APC, HES CC, HES OP, HES A&E, ECDS, Civil Registrations of Death, and Caner Registration Data datasets to OUH. The Data will:
> Contain directly identifying data items including NHS number which are required to link the NHS England Data to the lung health check data.

The Data will not be transferred to any other location.

The Data will be stored on servers at OUH. OUH also stores data on the TRE which runs on the Azure Cloud provided by Microsoft Limited.

The Data will be accessed onsite at the premises of OUH.

The record-level Data will also be accessed on the DART TRE by authorised personnel via remote access. The Data will remain on the servers at OUH and Microsoft Limited at all times.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Personnel are both prohibited and technically prevented from downloading or copying NHSE data to local devices;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this agreement) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Only aggregated data with small numbers suppressed can be exported from the TRE, via a secure Airlock Policy.

Remote processing will be from secure locations within England/Wales. The data will not leave England/Wales at any time.

All personnel accessing the data have been appropriately trained in data protection and confidentiality.

The Data will be linked at person record level with data from the TLHC programme. The Data will not be linked with any other data.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset.

Analysts from the OUH, NUH and University of Oxford will analyse the data for the purposes described above.
Optellum and GEHC users will access the data for the purpose of developing AI tools to achieve the purpose described above.

MR1004 - ARTERIAL REVASCULARISATION TRIAL ( ART ) — DARS-NIC-147755-C5H4X

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2019-09 – 2020-08 2017.12 — 2024.11.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Members and Postings Report
  4. MRIS - Scottish NHS / Registration
  5. MRIS - Flagging Current Status Report
  6. Civil Registrations of Death
  7. Demographics
  8. Emergency Care Data Set (ECDS)
  9. Hospital Episode Statistics Accident and Emergency (HES A and E)
  10. Hospital Episode Statistics Admitted Patient Care (HES APC)
  11. Hospital Episode Statistics Critical Care (HES Critical Care)
  12. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Identifiable

Objectives:

The data supplied by the NHS IC to Royal Brompton Hospital and Harefield Trust will be used only for the approved Medical Research project.

Yielded Benefits:

The study has provided unique long term information on the efficacy and safety of bilateral internal thoracic artery grafts for CABG, as well as a valuable high quality database to understand factors that influence long term outcomes after CABG and how these may be improved.

Expected Benefits:

The ART study will provide evidence from the first randomised trial for the use of bilateral IMA during CABG surgery. It will provide evidence for patients, doctors and policy-decision makers on the optimum treatment for patients undergoing CABG surgery.

ART is funded by the British Heart Foundation (2004-2014), Medical Research Council (2004-2014) and National Institute of Health Research (2014-2017) to compare 10-year survival after bilateral versus single internal thoracic artery grafting, and secondary outcomes of the composite of death, myocardial infarction or stroke, quality of life and health economic measures. Follow up to ten years is expected to be completed in 2017. This study will provide unique long term information on the efficacy and safety of bilateral internal thoracic artery grafts for CABG, as well as a valuable high quality database to understand factors that influence long term outcomes after CABG and how these may be improved.

All of this information will be used directly to improve the care of patients with advanced coronary artery disease undergoing coronary artery bypass graft surgery. Since coronary artery bypass graft surgery is a common operation and if the use of bilateral internal thoracic arteries lead to improved long term survival this could offer substantial health benefits to patients. Furthermore, the health economic component of ART will provide evidence to policy makers on the relative costs and benefits of performing coronary artery bypass surgery.

Outputs:

The University of Oxford intend to publish finding in high impact and disease specific medical journals as well as present findings at scientific sessions and conferences. Safety data at one year have been published and an interim analysis of five year follow-up results was presented at the American Heart Association Scientific Sessions in November 2016 and published simultaneously in the New England Journal of Medicine.

There has also been a number of other publications, for example;

1. Taggart DP, Altman DG, Gray AM, Lees B, Nugara F, Yu LM, Campbell H, Flather M; ART Investigators. Randomized trial to compare bilateral vs. single internal mammary coronary artery bypass grafting: 1-year results of the Arterial Revascularisation Trial (ART). Eur Heart J. 2010 Oct;31(20):2470-81

2. Taggart DP, Altman DG, Gray AM, Lees B, Gerry S, Benedetto U, Flather M; ART Investigators.. Randomized Trial of Bilateral versus Single Internal-Thoracic-Artery Grafts. N Engl J Med. 2016 Dec 29;375 (26):2540-9 4. Taggart DP, Altman DG, Gray AM, Lees B, Nugara F, Yu LM, Flather M; ART Investigators.

3. Effects of on-pump and off-pump surgery in the Arterial Revascularization Trial. Eur J Cardiothorac Surg. 2015 Jun;47(6):1059- 65 5. Benedetto U, Altman DG, Gerry S, Gray A, Lees B, Pawlaczyk R, Flather M, Taggart DP; Arterial Revascularization Trial investigators.

4. Pedicled and skeletonized single and bilateral internal thoracic artery grafts and the incidence of sternal wound complications: Insights from the Arterial Revascularization Trial. J Thorac Cardiovasc Surg. 2016 Jul;152(1):270-6 6. Benedetto U, Altman DG, Gray AM, Lees B, Gerry S, Flather M, Taggart DP on behalf of the ART investigators. Impact of dual antiplatelet therapy after coronary artery bypass surgery on 1 year outcomes in the Arterial Revascularization Trial (ART). Eur J Cardiothoracic Surgery (accepted 2017) 7.

5. Taggart DP, Altman DG, Gray A M, Lees B, Gerry S, Benedetto U, Flather M,for the ART Investigators. Randomized trial of bilateral versus single internal- thoracic-artery grafts. N Engl J Med 2016;375:2540-2549

It is proposed that once all patients have completed their 10 year follow up (scheduled 2017), the survival data will be analysed and form the basis of a manuscript to be published in a peer-review medical journal(s) as soon as possible after the end of the study .

In addition to further outputs in peer review medical journals and conferences, the ART study team will prepare information for participants once the 10 year analysis has been performed and the findings published (anticipated date: end 2017/beginning 2018).

All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

A cohort of 1837 patients has been flagged by NHS Digital for the ART study. The ART study has informed patient consent for their entire cohort. The data from the UK patients on date of death and cause of death will contribute towards the analysis of the primary outcome of the ART study which is survival at 10 years.

Sensitive and identifiable data (including Date of Death and Cause of Death) will be transferred from NHS Digital to the ART study on a quarterly basis.

Data will be stored by the University of Oxford (Nuffield Department of Surgical Sciences). The data will be held electronically in a file that is only accessible by nominated ART study personnel working at the University of Oxford.

Only authorised ART study personnel at the University of Oxford will have access to the patient ID and patient data from NHS Digital.

The data will not be shared with 3rd parties and will only used for the purposes described in this agreement.

All ONS terms and conditions described in the special conditions section of this agreement will be adhered to.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

The Oxford Risk Factors And Non Invasive Imaging Study (ORFAN) Arm 4 — DARS-NIC-409610-J6L1F

Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2021-03 – 2024-03 2021.03 — 2024.11.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Medicines dispensed in Primary Care (NHSBSA data)
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. COVID-19 Hospitalization in England Surveillance System
  4. Emergency Care Data Set (ECDS)
  5. HES:Civil Registration (Deaths) bridge
  6. Hospital Episode Statistics Accident and Emergency
  7. Hospital Episode Statistics Admitted Patient Care
  8. Hospital Episode Statistics Critical Care
  9. Hospital Episode Statistics Outpatients
  10. Civil Registrations of Death - Secondary Care Cut
  11. Hospital Episode Statistics Accident and Emergency (HES A and E)
  12. Hospital Episode Statistics Admitted Patient Care (HES APC)
  13. Hospital Episode Statistics Critical Care (HES Critical Care)
  14. Hospital Episode Statistics Outpatients (HES OP)
  15. Civil Registrations of Death

Type of data: Anonymised - ICO Code Compliant

Objectives:

The Oxford Risk Factors And Non Invasive Imaging Study (ORFAN) at large has been operational since 2015. Originally the study was limited to arms 1, 2 and 3. Arm 4 has been developed conceptually from 2018, and came into practical existence from 2019 to both address outstanding scientific questions that cannot be answered with the limited pool of participants in arms 1-3, and to further develop and validate novel biomarkers that have emerged from ORFAN Arm 1-3 and other Ox-HVF studies (see below). ORFAN Arm 4 is funded by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre and The British Heart Foundation (BHF).

ORFAN Arm 4 study is a multi-centre observational cohort study involving patients who have had a computed tomography (CT) angiography or CT chest scan.

The study is applying to NHS Digital in order to link study participant's patient identifiers with data held by NHS Digital in order to develop and validate cardiovascular disease risk assessment tools that will lead to earlier detection of disease risk and prevent heart attacks and strokes, amongst other cardiovascular diseases. These tools are for usage in the clinical environment and are intended to change patient care for the better.

The purpose of the project is to develop new and better biomarkers of cardiovascular disease risk using novel approaches to the analysis of CT scans. The overriding purpose of this work is to reduce the large burden of morbidity and mortality that cardiovascular disease such as heart attack and stroke have in our society.

The NHS Digital data requested in this agreement contribute in a fundamental way to the achievement of this purpose by allowing the research team to know what diseases and clinical events had occurred prior to the CT scan of relevance to the study, and what disease and clinical events have occurred for participants following the CT scan. This data is critical to the successful development of image analysis tools as it enables accurate differentiation of participant characteristics, namely imaging characteristics detected from within the CT scans, that can be utilised to predict patient risk.

A further major purpose of the ORFAN Arm 4 project is to understand the cardiovascular disease ramifications of COVID-19 infection. The study team know that deleterious impacts on blood vessels and the heart due to acute COVID-19 infection are commonly reported, but they do not know the long-term impacts or how to predict which patients are most at risk of morbidity due to such disease effects. Access to data related to COVID-19 infection and later cardiovascular disease diagnosis and clinical events, along with relevant CT scans of such patients’ hearts and vessels will enable a much more accurate assessment of this risk for individual patients.

THE ORFAN STUDY PROTOCOL AND OBJECTIVES
The study has two main objectives:
1) To investigate whether biomarkers, including imaging biomarkers, of metabolic risk can predict major adverse cardiovascular events
2) To identify novel biomarkers able to predict cardiovascular disease pathogenesis and extent of pre-existing vascular disease, including in those with COVID-19 infection.

The specific primary objective of the ORFAN study is to investigate whether biomarkers of disease risk can predict major adverse cardiovascular events.

In order to achieve this objective, the primary outcome measures for the study are:
1. Measurements of plasma/imaging markers of cardiometabolic risk - not directly relevant for this application, although the data requested will be linked to the pseudo-anonymised plasma and imaging data already held by the applicant
2. Atherosclerosis progression by Computerised Tomography - not directly relevant for this application, although the data requested will be linked to the relevant pseudo-anonymised imaging data already held by the applicant
3. Major adverse cardiovascular events over 10 years - relevant for this agreement.

The relevant study secondary objective is to identify novel biomarkers able to predict cardiovascular disease pathogenesis and extent of pre-existing vascular disease
The secondary outcome measures that are relevant to this application:
1. Measurement of modification to cardiovascular disease pathogenesis and modulation of pre-existing vascular disease that is attributable to infection with coronavirus disease 2019 (COVID-19), and other pre-existing vascular disease.

The ORFAN Study was assigned COVID-19 Cardiovascular Disease UK Flagship Project status by the NIHR-BHF in May 2020 and has received ethical approval to pursue scientific inquiry into specific risk that is conveyed by COVID-19 infection in regard to stroke and coronary artery disease. The data from this agreement will form a major part of this inquiry so the study team can understand the heart disease risk that COVID infection confers, and will enable the creation of biomarkers for assessing patients individual risk of heart disease complication following COVID-19 infection.

The ORFAN study at large consists of 4 Arms of study. Arms 1, 2 and 3 include a total of 15,500 prospectively recruited participants who are directly consented to be included within the study. The ORFAN Study research arms 1,2 and 3 include directly consented patients for whom the University of Oxford collects and processes data for research purposes. The outcome data of these participants are collected through NHS Digital with whom a data sharing agreement has been signed (DARS-NIC-392669-T1F8B). This agreement herein does not include the collection, processing or storage of any data associated with patients in ORFAN Arms 1, 2 or 3.

ORFAN is part of the Oxford cohort for Heart, Vessels and Fat (Ox-HVF), which means the results from this study may be interpreted together with the findings of other Ox-HVF projects. The Ox-HVF cohort is a cluster of clinical studies run from the University of Oxford that together provide results allowing the deployment of a multi-level strategy to understand the mechanisms of cardiovascular disease, specifically heart attack and stroke.

This agreement concerns ORFAN Arm 4 only, which is a retrospective study arm which includes up to 100,000 adult participants (75,000 - in the UK; 25,000 – internationally; this application only concerns participants located within England and Wales) who have undergone CT chest, abdomen and pelvis scans for clinical purposes at a participating NHS Trust radiology department. The ORFAN study team are focussed on CT coronary angiograms in this project - scans that only include the heart and surrounding blood vessels and tissues.

ORFAN Arm 4 focuses on collecting CT images, patient demographics and clinical information including clinical outcomes and medication usage to aid the development of new CT image analysis algorithms and software tools for the practical application of these algorithms via both traditional and artificial intelligence approaches. ORFAN Arm 4 will provide the required statistical power to allow automation of image analysis processes such as the automated calculation of image analysis techniques developed by the University of Oxford including the perivascular Fat Attenuation Index, the coronary artery Fat Radiomic* Profile and the Atriomic Stroke Algorithm (a novel risk algorithm interrogates the heart atria (the top chambers of the heart) to extract radiomic features, hence ‘atriomic’), as well as the development of new imaging biomarkers - this is the focus of this project. The development of these algorithms and tools has, and will, lead to much improved patient care for those at risk of heart attack and stroke.

* In the field of medicine, radiomics is a discipline and collection of methods concerned with the extraction of a large number of statistical features from radiographic medical images using data-characterisation algorithms. These features, termed radiomic features, have the potential to uncover disease characteristics that fail to be appreciated by the naked eye.

Following the COVID-19 pandemic, the ORFAN study programme pivoted to include relevant research objectives related to the non-invasive assessment of cardiovascular damage caused by infection with the virus. This work has been designated by the NIHR and the British Heart Foundation as a COVID-19 Cardiovascular Disease UK Flagship Project. The influence of COVID-19 infection on the outcome measures of the study will be explored, and novel tools to assess the impact of COVID-19 infection on blood vessels and the heart will be developed. This agreement is of fundamental importance for the success of ORFAN Arm 4. Access to NHS Digital held data will enable the accurate ascertainment of disease status for all relevant study conditions within all participants. The breadth of relevant diseases and clinical activity for this research is large due to the complexity of accurately adjusting imaging analysis for all conditions.

The analysis that will occur will involve the adjustment of patient risk profiles for all clinical events and medication usage prior to the CT scan of interest, and adjustment of all clinical events and medication usage following the CT scan of interest. It is not possible to accurately build risk assessment models without both the prior and post CT scan patient data.

As an example, a specific project that will make use of Arm 4 data that has also received significant funding is explained here. This project is the development and clinical translation of the Atriomic Stroke Algorithm, which has received a BHF Translational award (TG/19/2/34831 – ‘Using radiomics and artificial intelligence to predict cardio-embolic stroke’) to validate a novel imaging biomarker for the direct prediction of stroke risk from CT images. This project intends to make use of ORFAN Arm 4 data to provide the most accurate risk assessment of individual stroke risk available. This award has unlocked new technical ability in the ORFAN project as it has funded a very powerful computer capable of processing many thousands of CT scans for deep-learning purposes. Deep-learning is the field of artificial intelligence concerned with the automated interpretation of images, in the same way a computer can identify if a photo portrays a cat or a dog, a computer can also identify if a CT scan portrays a heart or a stomach, to use a rudimentary example. In this project, the computer will learn to identify patients with inflammation around their heart – inflammation that places them at increased risk of stroke. This computer has been purchased and installed at the University of Oxford for this project. The award also funds suitably qualified engineers to work on the ORFAN study utilising this computer for CT scan analysis purposes.

The University of Oxford research team who will receive the pseudonymised data from NHS Digital will never receive linkage files that enable the matching of the participants clinical information with their identifiable information.

The sole Data Controller is the University of Oxford who also process the data. The team is led by the Professor of Cardiovascular Medicine at the University of Oxford.

There is a third-party company, Caristo Diagnostics Ltd, which is a University of Oxford spin-out company from the Antoniades Laboratory. This company is involved in the wider ORFAN study, along with other research studies coordinated from the Professor Antoniades laboratory as part of the Ox-HVF stable of studies. This company will NOT be involved in any processing of NHS Digital data relating to this agreement and will have no data shared with it. Caristo Diagnostics Ltd also do not play any role in determining the means by which any data will be processed under this agreement.

There are no funders or commissioners directly involved in the collection or processing of data. The ORFAN study has received funding from a number of sources, however the British Heart Foundation has awarded monies specifically for ORFAN Arm 4. The specific project is the development and clinical translation of the Atriomic Stroke Algorithm via a BHF Translational award (TG/19/2/34831 – ‘Using radiomics and artificial intelligence to predict cardio-embolic stroke’). This project intends to make use of ORFAN Arm 4 data to provide the most accurate risk assessment of individual stroke risk available, as is in keeping with the ORFAN scientific aims. The British Heart Foundation has no control over the methodology of the study nor direct access to NHS Digital data and is therefore not considered a Data Controller.

The lawful basis for processing data under GDPR has been reviewed and been assessed as acceptable. The University of Oxford process data under Article 6(1)(e): "processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller" as they are a Public Authority.

Additionally, the University of Oxford process the Special Category Health Data under Article 9(2)(j): "processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject" as the data are required for statistical purposes in the public interest.

The public interest relevant to this work is that the research stands to greatly improve the way in which patients – that is, the public of the UK – receive care in relation to heart attack and stroke. These are the top causes of morbidity and mortality in our community and there is huge public interest in improving patient risk assessment and the management of that risk to save lives.

Yielded Benefits:

The University of Oxford ORFAN team have previously produced multiple results that have been published academically and reported upon within the lay press. Some noteworthy examples include: Evidence that obesity may not be necessarily bad for all patients, and those patients with high body mass index may be protected against cardiovascular mortality because fat in the body may secrete protective substances. This is called the obesity paradox and has major implications for the treatment of patients with heart diseases (published in the journal Diabetes in 2015, link to press coverage about the obesity paradox: https://www.telegraph.co.uk/news/science/science-news/11657811/Why-obesity-protects-against-heart-diseaseand-heart-attack.html). The University of Oxford (ORFAN team) has recently identified a significant therapeutic target for the treatment of heart diseases, and that discovery led to intense research to develop new drugs to modify this target (presented in the European Society of Cardiology 2018 Congress, and received the Best Poster Award). The University of Oxford ORFAN group has developed a novel imaging biomarker (see Antonopoulos et al in Science Translational Medicine, 2017), namely the Fat Attenuation Index (FAI), which has been shown to be a marker of vascular inflammation at early disease stages. Validation of this biomarker in large cohorts of patients with residual cardiovascular risk showed that FAI is able to detect patients at high risk for cardiac mortality and is also predictive of non-fatal heart attacks. This permits reclassification of an individual's risk, above and beyond the current state-of-the-art diagnostic tools, with strong implications for guiding medical management in patients and guiding the use of primary and secondary prevention measures. The development of this technology is a significant example that highlights the strength and unique ability of the Ox-HVF cohort in combining data across different and diverse fields - from clinical and epidemiological data to basic science and imaging data to outcome data (requested in the current application) - to create new, boundary-pushing ideas that promote health and serve the public interest. Of note, FAI was featured by iNews as one of the ten health innovations that could soon be on the NHS (https://inews.co.uk/news/health/the-ten-health-innovations-that-could-soon-be-on-the-nhs/). bFAI has been included into the recent Up-To-Date clinical guidance for use in patients with chest pain (https://www.uptodate.com/contents/cardiac-imagingwith-computed-tomography-and-magnetic-resonance-in-the-adult) and can be used to detect patients who may need intense medical therapy to prevent future heart attacks.”

Expected Benefits:

The dissemination of the data stands to have a huge impact on the provision of cardiovascular care within the UK and further afield. The creation of novel means to assess a patient’s individual risk for heart attack and stroke could revolutionise the way that clinicians currently deal with these deadly diseases. Current means to inform a patient of their risk for both heart attack and stroke rely on population wide data based on demographics (such as age) and clinical measures such as blood pressure. Although these are important risk factors, these clinical tools fail to consider some of the most fundamental causes of heart disease that can now be detected, such as inflammation around the heart and the effect of adipose tissue adjacent to the heart muscle, and hence provide poor accuracy for patients.

The personalisation of risk assessment, as the ORFAN study sets to create via access to NHS Digital data and other sources, unlocks personalised clinical approaches that can provide the right therapy or monitoring for the right patient, at the right time, more often than is currently achieved – saving clinical time and health service resources while improving the health outcome for the patient. The COVID-19 arm of ORFAN Arm 4 is set up to explore the cardiovascular consequences of COVID-19 infection and stands to provide important benefits to patients in regards to the personalised assessment of disease risk for Covid patients following their acute illness with the virus. This benefit stands to be hugely important to the UK, with very high Covid rates and unknown consequences for heart disease and how to assess risk for individual patients.

The dissemination of ORFAN Study findings is in the public interest due to the profound benefits that this work could have on patient care for those at risk of very common conditions including heart attack and stroke. These conditions remain the top two leading causes of death in our society, and efforts to reduce early mortality have stalled in recent years. The ORFAN Study intends to create tools for the most accurate assessment of cardiovascular disease risk available to patients. The dissemination of these tools to clinicians, once appropriately validated, is entirely within the interests of the UK public so that they can receive better care. The dissemination of the requested NHS Digital data for this project is fundamental to the success of the scientific aims, and is firmly in the interest of the UK public.

The outputs hope to facilitate the improvement of patient care in the interests of the UK public. The benefits of processing this data are to develop tools that stand to directly improve patient care in regards to common cardiovascular disease including heart attack and stroke. The dissemination of the research findings should enable uptake of these technologies within the UK and abroad, and provide better management options to patients so that they can avoid the morbidity and mortality associated with cardiovascular disease.

The linkage of NHS Digital data to patients identified by local NHS Trust clinical care teams as being suitable for inclusion in the ORFAN Study arm 4 is fundamental to the achievement of the scientific aims of the ORFAN Study, particularly to create novel disease risk assessment tools for heart attack and stroke. The statistical power to test and validate the novel risk assessment tools is not possible without the requested data. The study team hope that the
analysis of these data as disseminated by NHS Digital will enable the creation of the necessary tools, as the study team will be able to adjust the analysis for the relevant clinical events/disease diagnoses/medications that the patient had prior to the CT scan and after the CT scam. Without this information, the analysis is not possible and there would be no advancement of this scientific field and no advancement of early risk assessment through imaging biomarkers for heart attack and stroke.

ORFAN Arm 4 compliments the other arms of the ORFAN study where direct patient consent is obtained. ORFAN Arms 1, 2 and 3 all involve the direct consent of patients, and the direct follow up of these patients over time. It is not feasible for enough participants to be enrolled into these consented study arms to enable the research to successfully fulfil the scientific objectives and create tools for clinical usage. ORFAN Arm 4, and the requested dissemination of NHS Digital data as a part of that arm, will facilitate the necessary statistical power to develop and test the tools that emerge from ORFAN Arms 1-3 and the other complementary studies within the Oxford Heart Vessel and Fat research group (Ox-HVF) coordinated by the University of Oxford.

Such synergy within the Ox-HVF projects facilitates rapid translation of basic science into clinically useful tools. An obvious continuation of this same project would be to test the perivascular Fat Attenuation Index in the ORFAN Arm 4 cohort, to investigate if the biomarker is able to accurately predict patients who will go on to suffer from heart attack following their CT scan. Such an experiment requires large numbers of participants, with complete datasets of background risk factors and events (diagnoses prior to the CT scan), the CT scan itself, and outcomes data (diagnoses/events following the CT scan).

The Study expect to be publishing key findings related to the development of novel disease risk assessment for cardiovascular disease within 2-3 years of the DSA commencing. The study team expect novel diagnostic and risk assessment tools to be incorporated into clinical practice within 5 years from the DSA commencing, and further publication of the use of these tools from within the ORFAN study, reliant on this agreement by 10 years.

The outputs are hoped to change the clinical approach to patients at risk of heart attack and stroke who have been referred to receive a CT scans that includes their heart. The tools that the ORFAN study intends to create are for the advanced interpretation of these scans, and are hoped to provide clinician with information related to individual disease risk for the specific patient. This information is not currently available from these scans. This information can then be used to change lifestyle and medical therapy as appropriate and/or to change monitoring of that specific patient as appropriate, with the aim being to reduce the patients individual risk for harm. A simplified example of how such tools can impact on an individual patient’s care is provided: A patient has chest pain and is referred for a CT scan of their heart; CT scans are the NICE and ESC recommended first line investigation for chest pain. The scan shows clear coronary arteries free from blockage however when the novel Fat Attenuation Index (FAI) is assessed on the scan the patient is found to have highly inflamed coronary arteries. This patient is likely at elevated risk of heart attack despite no visible blockages. This patient could then be placed on anti-inflammatory medication and monitored carefully for a period as opposed to discharge without any change in therapy and monitoring, as is currently the status quo for a patient with arteries free of blockage. The FAI is a previously developed novel CT measure of coronary artery inflammation developed by the Antoniades laboratory using ORFAN and other studies.

The development of such imaging biomarkers enables more personalised disease risk assessment for patients. These biomarkers are concerned with individualised assessment of risk for common conditions such as heart attacks, strokes and atrial fibrillation. Risk assessments for such conditions are currently based on classical approaches to risk factors that provide blunt population level risk data that are difficult for clinicians and patients to interpret. Risk assessments that make use of biological processes that directly relate to the disease, such as measuring the level of inflammation surrounding the coronary arteries, as is possible with the Fat Attenuation Index, and relating this to other information such as a patients age and cholesterol level, can provide highly accurate and personal risk assessments that clinicians and patients can utilise to reduce risk of events. These risk assessments can be utilised to enact closer monitoring of patients, to motivate lifestyle changes and to guide pharmacological therapies in a way that has not previously been possible.

45’000 CTA scans (CT scans of the heart) are performed in UK per year to manage chest pain, expected to increase to >350’000 when the 2016 NICE guidelines are fully implemented. The 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes recommends CTA as the first line test for the diagnosis of coronary artery disease in all symptomatic patients. This class 1 recommendation will further see the use of CTA increase across Europe. Currently, 80% of CTAs reveal no significant coronary disease, a number that is expected to increase with increasing scan rates. In addition, non-contrast CT scans of hearts are routinely used for screening the population for coronary calcification, as part of risk stratification. As these scans are all focused on the coronaries, any other information is missed. By way of example utilising stroke: An automated technology that can provide risk stratification for stroke and heart attack as a standard element of clinical CTA reporting, may predict (and potentially prevent) up to 900 strokes/year based upon current uptake of CTA in the UK. The study team expect that the method could identify patients with atrial myopathy at risk for cardio-embolic stroke, over and above clinical risk prediction tools such as the widely utilised CHA2DS2-VASc score, so they can be referred for ECG monitoring or possible anticoagulation therapy to prevent events. The proposed technologies to be developed in the ORFAN study can be applied retrospectively to existing cardiac CT scans, acquired with or without contrast, or prospectively as part of usual clinical care.

The financial impact of heart attack and stroke on UK society is very large. Again, utilising the stroke example: 1 in 6 people in the UK will have a stroke during their lifetime, with enormous socioeconomic impact. The average cost of stroke per person is £40,000 in the first 12 months after the event (cost of incident stroke), followed by a lifetime average cost of £25,000/person/year. Grossly, the overall annual cost of stroke to UK society is £26 billion. The rate of first-time strokes in people >45 years old is expected to increase by 59% in the next 15 years, with worldwide stroke-related illness, disability and early death set to double by 2035. The prevention of every stoke via enhanced tools for the detection of risk stands to save enormous resources within the UK’s NHS, and could be an immensely valuable tool for clinicians to wield to both prevent events, but also to better target therapies to those that actually need them – preventing waste.

The possible benefits are hoped to be achieved by the study sponsor, the University of Oxford. Intellectual property developed through this work will be owned by the University of Oxford. Benefit will be measured in the short-term by the impact of peer-reviewed academic publications and presentations of the work at international cardiology conferences. The final result of this work is anticipated to be a number of automated risk algorithms that empower both patients and clinicians with highly accurate prediction of disease events, such as a heart attack or stoke, within the following 5 years. This risk prediction is currently very poor and enhanced prediction ability is critical for managing patients in regard to lifestyle changes, monitoring and the initiation or escalation of medical therapy. The long-term benefit will be measured by the total number of patients for whom the disease assessment tools are applied to clinically, and how many clinical events are assessed to have been prevented through the technology. This longer-term impact will require specific study to understand, and the ORFAN study will enable this through the 10-year follow-up period as requested in this DSA. It should be possible to adjudicate which patients do go on to suffer clinical events via the requested annual NHS Digital data extractions, hence allowing an ongoing enquiry into the effectiveness of the diagnostic and risk assessment tools that the study team propose to develop.

Results related to the development of novel imaging tools for the prediction of heart attack and stroke will be available within 2 years of the commencement of the DSA. The results are hoped to be published and subsequently updated in the following years once further clinical outcomes data is collected from NHS Digital, as requested. The project is forecast to be finally concluded at the end of the 10 year follow up period as agreed to within the agreement, at which time all final analysis of the outcomes will occur and final validation papers will likely be published, although the study team anticipate by then the tools developed for the assessment of individual patient risk to be adopted clinically and clinical trials to be ongoing as to the effectiveness of the tools.

Outputs:

The major outputs from this data processing are twofold:
1) The creation of novel disease risk calculating algorithms algorithms (patient assessment algorithms and the necessary software tools to practically apply the algorithms) for conditions such as heart attack and stroke ready for incorporation into patient care within health services, and
2) the communication of these outputs via scientific and lay-person publications.

The research outputs to convey the results will be led by peer reviewed publications in leading international journals, presentations in international and national scientific meetings and subsequent media reporting and public engagement lead by the University of Oxford.

Journals being targeted to submit to/publish in:
i) The New England Journal of Medicine (NEJM) (impact factor 74.7)
ii) The Journal of the American Medical Association (JAMA) (impact factor 45.5)
iii) The Lancet (impact factor 60.4)
iv) Circulation (impact factor 23.6)
v) Journal of the American College of Cardiology (JACC) (impact factor 20.5)
vi) British Medical Journal (BMJ) (impact factor 30.2)
vii) European Heart Journal (EHJ) (impact factor 22.7)

The study team intend major findings of this work to be published in the top-tier general medicine journals (NEJM, JAMA, Lancet, BMJ) as opposed to more cardiac specific findings which will be aimed at the top cardiology journals (Circulation, JACC, EHJ). This enables far greater readership and targeting of impact. All publications in major journals such as those listed here will be open access, meaning any reader from anywhere on Earth can access the full text of the research article without any cost.

Congresses and conferences targeted to submit work to:
i) Scientific sessions of the American Heart Association
ii) Scientific sessions of the European Society of Cardiology
iii) Scientific sessions of the American College of Cardiology
iv) Scientific sessions of the British Cardiac Society

The outputs from this work will be both immediate - with publications in high impact journals within 2-3 years of the commencement of the agreement as well as long-term - when diagnostic biomarkers are implemented in clinical practice. As the ORFAN study is expected to continue collecting outcomes data for at least the next 10 years, the cohort will continue to generate outputs as more events accumulate over time. These long-term impacts have the potential to change clinical practice worldwide and save lives from improved assessment of cardiovascular disease risk.

Specific algorithms that the ORFAN Study team wish to create and/or validate through the ORFAN arm 4 study include:
1) An algorithm for the specific risk assessment of ischaemic stroke in those with and without atrial fibrillation (provisionally called the Atriomic Stroke Algorithm)
2) An algorithm for the specific risk assessment of cardiovascular complications in those with COVID-19 infection
3) An algorithm for the likelihood of success of invasive catheter ablation in those with atrial fibrillation
4) Validation of the perivascular Fat Attenuation Index (FAI) algorithm for heart attack risk. The FAI algorithm is an already established algorithm for the accurate assessment of heart attack risk, discovered in the ORFAN Study. FAI involves the assessment of CT scan features, in particular attenuation – the CT term for density, of fat surrounding the coronary vessels.
5) Validation of the Fat Radiomic Profile (FRP) algorithm for heart attack risk. The FRP algorithm is a another already established algorithm for long-term heart attack risk discovered in the ORFAN Study. This algorithm relies upon many radiomic features extracted from CT scans from around the coronary vessels. These features cannot be seen by the naked eye, and so require computer extraction and assessment which is what the FRP computes.
6) Likely other algorithms related to specific at risk population depending on data quality and statistical power

All such algorithms are stand-alone patient assessment tools, and any intellectual property created from within the ORFAN Study will be owned by the University of Oxford, and associated intellectual property will be controlled by the University for licensing to health services for inclusion in clinical practice.

The ORFAN research team at the University of Oxford has no personal intention to monetise or generate income from the research outputs generated from the ORFAN Arm 4 study. Were discoveries to be made in the ORFAN Arm 4 study, individual researchers within the ORFAN team would be listed inventors on any patents that the University of Oxford may file.

The study team expect to be publishing important findings related to the development of novel disease risk assessment for cardiovascular disease within 2-3 years of the DSA commencing. It is possible this may occur earlier if the extraction of data in the first year produces enough scientific power for robust results. They expect novel diagnostic and risk assessment tools to be incorporated into clinical practice within 5 years from the DSA commencing, and further major publications related to the use of the tools developed from within the ORFAN study by the end of the 10 year data retention date.

THE LEVEL OF DATA THAT WILL BE CONTAINED IN THE OUTPUTS:

The level of data contained in the outputs is aggregate data with small number suppression applied as per the disclosure rules for the various data sets that has been augmented via statistical processes. No individual participants data is ever published individually, with the nature of this scientific work demanding high numbers of participants data for the testing and validation of disease risk calculators.

The dissemination activities of the ORFAN Study team are focussed on high-impact peer reviewed journals and oral research presentations at international conferences. Other activities through which the ORFAN study findings are communicated include through NHS Trust clinical grand-round meetings at NHS Trusts who deliver services relevant to those explored in the study, NHS Trust newsletters delivered to staff emails and through high level meetings with NHS executives and clinical leads at NHS Trusts to discuss the suitability for the clinical tools to be tested within the clinical environment at their Trusts. This work also involves audit related work to model the impact of novel tools developed from within ORFAN on current service usage, as has occurred within Oxford University Hospitals NHS Trust already.

To target the lay audience, the ORFAN team uses the following approaches and is guided by the Research Services team at the University of Oxford and the Public Engagement team at the Cardiovascular Medicine Division of the University of Oxford:

a) Website (www.oxhvf.com); this is updated with all the most up to date information regarding the outputs of the research. This is a public-facing website, and the public can read about the latest outputs of the study.

b) Newsletters; when major findings or general outputs are available, the ORFAN team post newsletters both on the website and in hard-copy form to ORFA Arm 1-3 participants. This is not possible for Arm 4, as we do not hold patient identifiable information. Media attention including articles in BBC News, The Guardian, The Financial Times and CBN concerning work published in the prestigious journal ‘Science Translational Medicine’ are the sorts of topics highlighted in newsletters (see example from the Antoniades Lab: https://test188076.files.wordpress.com/2018/01/newsletter-adiporedox-15-09-2017.pdf).

c) Press releases; the ORFAN team have an active involvement in outreach activities of the University of Oxford, Oxford University Innovations and the British Heart Foundation communications team, and the major findings from their study lead to press releases, and from there they are distributed to the lay press.

d) Workshops and patient and public involvement; the ORFAN team participate in workshops for patients as part of the Biomedical Research Centre in Oxford, and through that they inform the patients about their research and ask for their involvement in the design of protocols, feedback on research procedures and more, through Patient and Public involvement (PPI) panels

e) Social media – the ORFAN Study group frequently share results and outputs to their social media presence on Twitter, Facebook and LinkedIn.

Exploitation of results/outputs:
All intellectual property and knowhow is owned by the University of Oxford, as the sponsor of the ORFAN Study. The University of Oxford, through Oxford University Innovation, maintains the ability to licence any technology that is created within the ORFAN Study for commercial use or for use within health services such as the NHS.

Processing:

The purpose of this agreement is to carry out health data related research. The agreement is to provide patient identifiable data for the purposes of linkage to health data held by NHS Digital. To achieve this clinical care teams from 13 NHS Trusts who are collaborating on the study will provide the minimum required patient identifiers to NHS Digital (NHS Number and Date of Birth, and Post Code). This is the only flow of identifiable data that will be received by NHS Digital.

The collaborating 13 NHS Trusts with local clinical care teams participating in ORFAN Arm 4 are:
Oxford University Hospitals
Royal United Hospitals Bath
Milton Keynes University Hospital
University Hospitals of Leicester
Barts Health
Royal Brompton and Harefield
Leeds Teaching Hospitals
Royal Papworth Hospital
Guy's and St Thomas’
The Royal Wolverhampton
Sandwell & West Birmingham Hospitals
University Hospitals Birmingham
Manchester University

There is a single cohort group that will be included in the ORFAN Arm 4 study, however the participants of this cohort group will come from a number of different NHS Trusts across England. The data subjects are adults (18-99 year old) who have undergone a relevant CT scan at a NHS Trust where the local clinical team is collaborating on the ORFAN Study Arm 4.
The relevant CT scans include only clinically indicated and successfully performed scans, specifically a CT angiogram (CTA) or CT chest, abdomen and pelvis scan.

The data required is concerned with identifying what diagnoses, clinical events and therapy occurred both prior to the relevant CT scan (from 2005 onwards) and after the CT scan. The data required includes hospital episodes (emergency department attendances, inpatient admissions, critical care admissions, and outpatient clinics), with the focus on diagnoses made during those episodes and procedures that occurred at those episodes. The data required also includes medicine prescribed in the community both prior to and after the CT scan as this greatly influences risk of future disease through the reduction of risk. To address the research objective of how COVID-19 infection influences cardiovascular disease risk the study team will request data related to COVID-19 infection and its severity. Death data is also needed to know what patients in the study have passed away, otherwise these patients will be incorrectly included in certain analysis. The data sets requested from NHS Digital are:

- Civil Registration (Deaths) - Secondary Care Cut
- COVID-19 Hospitalization in England Surveillance System (CHESS)
- Emergency Care Data Set (ECDS)
- Hospital Episode Statistics Accident and Emergency
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Admitted Critical Care
- Hospital Episode Statistics Outpatients
- Medicines dispensed in Primary Care (NHSBSA data).

The first drop of all historical data would be after this agreement is signed off, and a second drop using THE SAME full Arm 4 ORFAN cohort in October 2023 for the periods 2020/21, 2021/22, and 2022/23.

The ORFAN Arm 4 data is analysed only for the purposes of the ORFAN project – to develop and validate imaging biomarkers of cardiovascular disease risk. The ORFAN Arm 4 data as received from NHS Digital will be analysed alongside the actual CT images from the linked patients. This is performed in a completely pseudonymised manner with the only link between the data extracted from NHS Digital and the original CT scan being the study ID originally assigned by the local NHS Trust clinical care team where the patient received care.

The second follow up of patient outcomes via NHS Digital data will further enable the correct ascertainment of individual patient risk through further refinement of imaging biomarkers as increasing numbers of patients suffer from clinical events of relevance to the ORFAN Study.

METHODOLOGY
For the first drop of NHS Digital data at the start of the agreement, the clinical care teams at each collaborating NHS Trust will generate a list of their own patients who met the participation requirements for ORFAN Arm 4, this list will be established and stored within the local NHS Trust firewall at the site where the patient was treated in the first instance. The clinical care teams will assign a unique ORFAN Arm 4 study ID to each participant. When ready and instructed to do so, the clinical care teams will send their ORFAN Arm 4 patient list, including identifiers NHS Number, Date of Birth, and Postcode, plus OFAN Study ID. Cohorts will be sent in via Secure Electronic File Transfer (SEFT) service. 13 Trusts in total will provide their cohorts to NHS Digital.

NHS Digital combines the 13 Trusts' cohorts to create one full ORFAN Arm 4 cohort and links and extracts the required data fields from the required data products and removed identifiers (leaving the Study ID).

NHS Digital send the pseudonymised data extracts to the Study team at University of Oxford via SEFT. No data is sent back to the 13 NHS Trusts that provided the patients that are included in the cohort.

For the second drop of NHS Digital data in October 2023, NHS Digital retrieves the full ORFAN Arm 4 cohort from storage and links and extracts the required data fields from the required data products and removed identifiers (leaving the Study ID). NHS Digital send the pseudonymised data extracts to the Study team at University of Oxford via SEFT.

There is no subsequent flow of pseudonymised data from the data recipient, the University of Oxford, to any other organisation.

DATA MINIMISATION
The study team consider the data they have requested as adequate for the scientific aims of the ORFAN Study protocol, and will achieve the purposes of creating novel risk prediction tools for common cardiovascular diseases. All data requested is relevant to the risk of cardiovascular disease and its complications, and most importantly the request is limited to the achievement of the ORFAN Study aims only.

The NHS Digital datasets requested will be linked to the ORFAN Arm 4 cohort of approx. 75,000 participants.

The study only request linkage to datasets held by NHS Digital that are fundamental to the scientific aims of the ORFAN Arm 4 study. No requested linkages are superfluous to the study or that hold data that will not be utilised in statistical models as proposed in the ORFAN Study protocol. The datasets requests can not be reduced because all datasets as requested hold necessary data for the successful completion of the ORFAN Arm 4 project.
The scientific purpose of the ORFAN Arm 4 require pseudonymised data only, and no identifiable data is requested.

The number of years requested corresponds to the scientific aims of the ORFAN Study. The study team require to know the background medical conditions, hospitalisations and procedures that the participants had in order to adjust the statistical analysis to account for prior risk. This is necessary when creating risk algorithms that seek to predict an individual's risk of a specific medical condition. The study team request data linkage for the years supported by the CAG. This is from 2005 through until the current time, with repeat extraction supported for 10 years following the commencement of CAG support. The ORFAN Study team has compromised on how many years to request linkage for, as the more retrospective years of linkage included within the study, the more accurate the risk prediction algorithms would become. However, 16 years of previous risk of events (2005 through 2021) will provide enough relevant information regarding the participants in ORFAN Arm 4 to allow successful adjustment of the risk algorithms. For example, if a patient had a stroke 5 years prior to the CT scan this will mean that patient is analysed in a different way to patients who did not have such an event.

This study must consider geographic differences in exposure to cardiovascular disease risk factors, differences in socio-economic status and differences in access to health care. It would not be acceptable to include all 75,000 participants from the Oxford University Hospital (OUH) NHS Trust as this analysis would be prone to bias. On more practical terms, it is not possible to enrol patients from a single or smaller number of NHS Trusts due to the fact that most CT radiology services only have several thousand patients relevant to inclusion in the study. For example, the OUH NHS Trust has at most 6,000 relevant participants who could be enrolled in ORFAN Arm 4. For this reason, the study team must extend to multiple NHS Trusts so that the total number of participants is appropriate to achieve the scientific aims of the study.

The study team are only considering participants from across England and Wales. The cohort needs to include all episodes of care across this area as events that occurred at any relevant hospital must be considered in the algorithm. The cohort is limited to those aged 18 years and over. The cohort is primarily limited by the fact inclusion requires a participant to have received a study relevant clinical computed tomography (CT) scan. For the most part for ORFAN Arm 4 this means the participant must have received a clinical CT coronary angiogram (a specific CT scan of the heart).

The ORFAN Study requires all episodes of care, both elective and emergent, to achieve the purpose, bar maternity episodes. The study team do not require maternity episodes and do not require unborn child and neonatal records. Elective episodes are important as these often capture procedures of relevance to cardiovascular disease risk.

The study team have selected the minimum number of fields per dataset that are required for the successful fulfilment of the ORFAN Study scientific objectives. These fields are all necessary for the adjustment of the risk algorithms for cardiovascular disease and as such these fields will be used in the models, or to adjust specific risk factors by severity and/or the confounding of treatment (medical and surgical) prior to being fed into the models. Dates of death can be transformed into the format MM/YYYY.

Following receipt of the linked pseudonymised data from NHS Digital by the ORFAN Study team at the University of Oxford, the study team will perform statistical analysis to develop disease risk models in accordance with the scientific objectives of the ORFAN Study as outlined in the ORFAN Study protocol approved by the Health Research Association’s (HRA) Research Ethics Committee. This processing will include importing the data into statistical data analysis software using R (a programming language) and SPSS (SPSS Statistics is an IBM software package used for interactive, or batched, statistical analysis). The analysis will include the development of models for the prediction of disease such as stroke and heart attack and will involve the simultaneous analysis of CT imaging data (not sourced from NHS Digital).

There will be linkage of the NHS Digital data to the CT scan of the relevant patient that rendered them eligible for inclusion in ORFAN. This linkage occurs through the unique ORFAN Study ID originally assigned to the patient by the patient’s own clinical care team at the NHS Trust where they were treated. Along with sending the minimum required patient identifiers to NHS Digital for linkage, the local clinical care teams will also extract, de-identify and assign the corresponding unique patient ID to the relevant CT scan, and then send this scan to the ORFAN Study team. This will enable the ORFAN study team to analyse the scan in combination with the data received from NHS Digital, a key aspect in achieving the scientific aims of the study.

The ORFAN study team will also request data from national registries (or NHS Digital when available) such as National Institute for Cardiovascular Outcomes Research (NICOR) and the Sentinel Stroke National Audit Programme (SSNAP), both controlled by Healthcare Quality Improvement Partnership (HQIP) and will link the pseudonymised NHS Digital data to ORFAN study participants events recorded in these national registries. This linkage is through the unique ORFAN study ID only, not identifiable data.

There will be no matching of data to publicly available data sources. There will be no requirement or attempt to re-identify any study individuals in ORFAN Arm 4. No ORFAN Arm 4 patients will ever be contacted by the ORFAN Study team, or anyone else on behalf of the ORFAN study team.

Data processing will only be carried out by those who are substantive employees, with formal contracts, of the data processors or the data controller, the University of Oxford.

Once pseudonymised data is received from NHS Digital by the ORFAN Study team at the University of Oxford, the data is saved without any manipulation on secure University of Oxford servers located in University premises, namely the Acute Vascular Imaging Centre at the John Radcliffe Hospital, Oxford. An exact copy is saved on another secure University of Oxford server, namely the researcher server of the Oxford Centre for Clinical Magnetic Resonance Research, also at the John Radcliffe Hospital but in a separate building. This back up is only for disaster recover purposes and is not accessible to any ORFAN researchers/others bar senior University IT staff working in the Division of Cardiovascular Medicine. Both servers are in environment-controlled rooms, with uninterruptable power supplies and fire/flood monitoring. All server rooms require swipe card and physical keypad access, and users are credentialed by both the University of Oxford and the Oxford University Hospital NHS Trust.

The main copy and the back-up copy of the data is controlled by the study team lead, Professor of Cardiovascular Medicine, as the named ORFAN data controller. The study team lead will assign access to the dataset to credentialed researchers actively working on the ORFAN Arm 4 project.

The data will be held on servers owned by the University of Oxford, with the primary storage at the Acute Vascular Imaging Centre at the John Radcliffe Hospital and the secure back up at the Oxford Centre for Clinical Magnetic Resonance Research, also at the John Radcliffe Hospital but in a separate stand-alone building.

No third party organisations listed in the ORFAN Study protocol will receive pseudonymised data that has come to the University of Oxford from NHS Digital for ORFAN Arm 4. The University of Oxford and their ORFAN Study group is the only and final recipient of such data.

The investigators listed in the ORFAN Study protocol do not all retain rights to access ORFAN Arm 4 study data. Only the core ORFAN Study Team at the University of Oxford who have undertaken the appropriate training and have formal contracts in place with the University of Oxford may be eligible to access pseudonymised data disseminated to the University of Oxford from NHS Digital.

HES and ECDS DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, you must make sure that:
· cell values from 1 to 7 are suppressed at a local level to prevent possible identification of individuals from small counts within the table.
· Zeros (0) do not need to be suppressed.
· All other counts will be rounded to the nearest 5.
Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

MEDICINES DISPENSED IN PRIMARY CARE DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
The medicines data is not deemed disclosive and information on a GP level is available in the public domain. However, should the published information pose a risk of re-identification, the following suppression methodology should be applied:
• Zeros should be shown.
• 1-7 to be rounded to 5.
• Any other numbers rounded to nearest 5.
• Rounding unnecessary for averages etc.
• Percentages calculated from rounded values.
• If zeros need to be suppressed, round to 5.

COVID-19 Hospitalisations in England Surveillance System (CHESS) DISCLOSURE CONTROL POLICY
NHS Digital will only disseminate CHESS data collected from PHE where the information is linked to other information controlled by NHS Digital.

MR542 - MRC/BHF HEART PROTECTION STUDY — DARS-NIC-148069-ZB4GM

Opt outs honoured: Yes (Excuses: Consent (Reasonable Expectation), Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(2)(c), , National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2019-12 – 2020-03 2016.04 — 2024.10.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Scottish NHS / Registration
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Hospital Episode Statistics Outpatients
  7. MRIS - Flagging Current Status Report
  8. MRIS - Members and Postings Report
  9. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  10. Cancer Registration Data
  11. Civil Registration - Deaths
  12. Demographics
  13. Mental Health and Learning Disabilities Data Set
  14. Mental Health Minimum Data Set
  15. Mental Health Services Data Set
  16. Hospital Episode Statistics Accident and Emergency (HES A and E)
  17. Hospital Episode Statistics Admitted Patient Care (HES APC)
  18. Hospital Episode Statistics Outpatients (HES OP)
  19. Civil Registrations of Death
  20. Mental Health and Learning Disabilities Data Set (MHLDDS)
  21. Mental Health Minimum Data Set (MHMDS)
  22. Mental Health Services Data Set (MHSDS)

Type of data: Identifiable

Objectives:

The data supplied will be used only for the approved medical research project MR542 - MRC/BHF HEART PROTECTION STUDY

Yielded Benefits:

The HPS demonstrated that lowering Low Density Lipoprotein (LDL) cholesterol with statins reduces vascular morbidity and mortality, and, as a result of the results published in 2002, such medications are now widely prescribed. For various reasons it has not been possible to analyse HES data supplied previously. Initially, the data were more complex than had been anticipated (particularly given the relatively morbid population included in HPS) and it was difficult to decipher incident (i.e. new) events from prevalent disease. Then, problems with data flow from death registries meant it was not possible to censor the study population. Both these problems have now been overcome, but analysis of the data we currently hold without updating with more recent years would invite speculation from reviewers and readers as to why we had not included all available data.

Expected Benefits:

Millions of people at increased risk of heart disease in the UK and around the world are already taking statins. HPS has shown that a much wider range of patients can gain worthwhile benefits, and following these results statin use increased substantially. Reliable evidence about the long-term effects of cholesterol-lowering with statins is therefore necessary. Extended follow-up of the large numbers of participants in HPS can provide substantially more information about any long-term benefits or hazards of about 5 years of statin treatment than can the other statin trials that have been conducted. Importantly, reassurance about the long-term safety of statins should help to maintain long-term compliance, and so realise the full potential benefit of treatment. Moreover, evidence about the effects on major vascular events after the end of the scheduled treatment period is needed to assess the full cost-effectiveness of about 5 years of statin therapy. Extended follow-up of the surviving participants in HPS will also allow assessment of any delayed effects of the antioxidant vitamin regimen studied.

Outputs:

Several major publications describing the long-term safety and efficacy of 5 years lipid-lowering therapy with simvastatin and, separately, antioxidant vitamins are planned. Details will be provided in a future application to NHS Digital.

All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Under this Agreement, the data may be retained and processed by the University of Oxford for the purposes of original study but no new data will be provided by NHS Digital.

The following provides background on the processing activities undertaken for the original study:

All HPS study participants are already flagged with NHS Digital, therefore no transfer of data from Clinical Trial Service Unit (CTSU), University of Oxford to NHS Digital is required. Consent was obtained from participants for the main HPS study for the long-term follow-up of HPS participants in 2011.

CTSU has successfully acquired, analysed and appropriately stored data from HES for the HPS and other studies, and is an approved data safe haven which meets the highest standards for data protection.

The identifiable data, already held, is stored in an encrypted TrueCrypt container, to which access is granted on a “need to know basis”, i.e. the level of access will depend on the staff role. All such access will be granted on the instruction of the Information Asset Owner for HPS. Access is routinely reviewed and revoked when the team member ceases to work on HPS. Only personnel involved in the long-term follow-up study for HPS (processing and analysing data) will have access to this data. CTSU has a Corporate Level Security Policy that has been fully adopted by management and will apply fully to the long-term follow-up study.

The HPS study team shall not make available the NHS Digital data to any third party or allow use of it by them or on behalf of any third party, in whole or in part, whether by way of sale, resale, loan, transfer, hire or any other form of exploitation. No data will be accessed outside of the UK.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

The Data will only be used for the purposes described in this agreement.

Establishing a UK Colorectal Cancer Intelligence Hub - The COloRECTal Cancer Data Repository (CORECT-R) (ODR2021_249) — DARS-NIC-656885-M7T5X

Opt outs honoured: No (Excuses: Does not include the flow of confidential data, Section 251 NHS Act 2006, Statutory exemption to flow confidential data without consent)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2023-02 – 2024-03 2023.03 — 2024.09.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No, Yes

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked Cancer Waiting Times (Treatments only)
  3. NDRS Linked DIDs
  4. NDRS Linked HES AE
  5. NDRS Linked HES APC
  6. NDRS Linked HES Outpatient
  7. NDRS National Cancer Patient Experience Survey (CPES)
  8. NDRS National Radiotherapy Dataset (RTDS)
  9. NDRS Rapid Cancer Registrations
  10. NDRS Somatic Molecular Dataset
  11. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)
  12. NDRS Cancer Pathway

Type of data: Anonymised - ICO Code Compliant

Objectives:

The UK Colorectal Cancer Intelligence Hub is a research programme whose aim is to generate high quality bowel cancer information that will improve care and
outcomes for patients. It does this through compiling and using datasets relevant to the disease in the COloRECTal cancer data Repository (CORECT-R). This platform is available to the wider research community.

The research team will access cancer registration data collated by the National Cancer Registration and Analysis Service (NCRAS; the national cancer registry in
England) about all people who have been diagnosed with bowel cancer since 01 April 1997. This health data will include detailed information about each person:
• (such as their age, ethnicity and the area they live in);
• their diagnosis (the type of cancer they have, the stage and when it was diagnosed);
• the treatment they received (including details of surgery, chemotherapy and
radiotherapy);
• attendances in hospital and their experience of care.

The data will be brought together with other health datasets to build CORECT-R and support researchers to ask important questions about bowel cancer. Access to data within CORECT-R will be made available to the whole research community enabling pioneering research into bowel cancer. The programme will also help support all aspects of bowel cancer research from laboratory studies to the delivery of clinical care to improve survival. The model used will also support research into other cancer sites and disease areas.

Yielded Benefits:

To date, 35 projects have been approved to use CORECT-R (project summaries are available at https://www.ndph.ox.ac.uk/corectr/projects). Many of these projects have published results to inform policy, care and future research. A key example of yielded benefits is the project titled "Variation in post-colonoscopy colorectal cancer across colonoscopy providers in the English National Health Service: A population-based cohort study". Public project description: https://www.ndph.ox.ac.uk/corectr/projects/variation-in-post-colonoscopy-colorectal-cancer-across-colonoscopy-providers-in-the-english-national-health-service-a-population-based-cohort-study-2013-update British Medical Journal paper: https://www.bmj.com/content/367/bmj.l6090 Press release: https://bci.leeds.ac.uk/?page_id=697&preview=true Plain language summary: https://bci.leeds.ac.uk/get-involved/publications/ Around 40,000 people are diagnosed with bowel cancer every year in England. As well as being the main test to detect cancer, colonoscopies can also prevent cancer. Unfortunately, colonoscopies are not perfect and sometimes a person develops bowel cancer after having a colonoscopy. This is referred to as a post-colonoscopy colorectal cancer (PCCRC). This work showed rates of PCCRC were lowest in those performed as part of the Bowel Cancer Screening Programme. Colonoscopies performed at private providers for the NHS had much higher rates. This work has directly benefited patient care by enabling many colonoscopy providers to improve their practice (providers were informed of their rate in relation to other providers and given a mechanism to identify their PCCRC cases for audit). The work has also directly informed the Post Colonoscopy Colorectal Cancer Audit, https://www.bsg.org.uk/clinical-resource/more-information-about-the-national-post-colonoscopy-colorectal-cancer-pccrc-audit/

Expected Benefits:

The aim of the research is to improve bowel cancer treatment and care across the UK through identifying areas of poor practice and opportunities for improvement. It will do this by creating a data research platform, known as CORECT-R which will be made available to the whole research community enabling pioneering research into bowel cancer. The programme will also help support all aspects of bowel cancer research from laboratory studies to the delivery of clinical care to improve survival. The model used will also support research into other cancer sites and disease areas.

Outputs:

Linking multiple datasets relating to the management of bowel cancer together to provide a UK-wide view of care, experience and outcomes and making these available to authorised users for research. This linked data enables:
• better understanding of the reasons for differences in care and outcomes in these patients
• studies into the clinical performance of the NHS and to identify opportunities to improve performance
• the NHS to make sure it delivers the best care and complies with clinical guidelines; and
• supports the running of clinical trials

Processing:

It is imperative that individuals in any routine non-cancer datasets in CORECT-R cannot be
directly identified. Our data management and data flows are designed to prevent identification by
undertaking linkage using a secure pseudonymisation process. Extracts of non-cancer data will be
specified from the relevant data source and their unique identifier (such as their NHS number) will
be put through a cryptographic ‘salt’ process. It is possible that there may be some overlap
between the non-cancer dataset and the cancer dataset (for example, if we seek to find all who
have undergone a colonoscopy there will be some individuals within the population where a
cancer was found and so known to CORECT-R already). As such, the identifiers of cancer
patients will also be put through the same cryptographic ‘salt’ process. When the two datasets are
aligned the colorectal cancer patients within the full population will be identifiable as they will
both have the same salted key. For those without cancer only the resulting encrypted identifier
(and the relevant clinical detail) will be accessible to the CORECT-R data managers. The salt ‘key
keepers’ will be nominated staff within the relevant data controller’s organisation and
separate from the CORECT-R data management team. This will remove the possibility of the
CORECT-R team being able to ascertain the identity of those without cancer

QResearch - COVID-19 Risk Stratification project — DARS-NIC-382794-T3L3M

Opt outs honoured: No - data flow is not identifiable, No - consent provided by participants of research study, No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d), Health and Social Care Act 2012 – s261(2)(a),

Purposes: Yes (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2020-06 – 2020-09 2020.06 — 2024.08.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD, QUEEN MARY UNIVERSITY OF LONDON

Sublicensing allowed: No, Yes

Datasets:

  1. SUS plus - Admitted Patient Care (beta version)
  2. Civil Registration - Deaths
  3. COVID-19 Second Generation Surveillance System
  4. COVID-19 Hospitalization in England Surveillance System
  5. COVID-19 Vaccination Adverse Reactions
  6. COVID-19 Vaccination Status
  7. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  8. Emergency Care Data Set (ECDS)
  9. Hospital Episode Statistics Accident and Emergency
  10. Hospital Episode Statistics Admitted Patient Care
  11. Hospital Episode Statistics Critical Care
  12. Hospital Episode Statistics Outpatients
  13. COVID-19 Therapeutics Programme Data Set’
  14. HES-ID to MPS-ID HES Accident and Emergency
  15. HES-ID to MPS-ID HES Admitted Patient Care
  16. HES-ID to MPS-ID HES Outpatients
  17. MSDS (Maternity Services Data Set) v1.5
  18. Civil Registrations of Death
  19. COVID-19 Second Generation Surveillance System (SGSS)
  20. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  21. Hospital Episode Statistics Accident and Emergency (HES A and E)
  22. Hospital Episode Statistics Admitted Patient Care (HES APC)
  23. Hospital Episode Statistics Critical Care (HES Critical Care)
  24. Hospital Episode Statistics Outpatients (HES OP)
  25. Maternity Services Data Set (MSDS) v1.5
  26. COVID-19 SGSS First Positives (Second Generation Surveillance System)
  27. COVID-19 Therapeutics Programme Data Set
  28. Maternity Services Data Set (MSDS) v2
  29. Demographics

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

This agreement specifically relates to QResearch's urgent piece of COVID-19 work commissioned by the New and Emerging Respiratory Virus Threats Advisory Group (NERVTAG) to prepare a COVID-19 risk stratification tool. To support this work, NHS Digital will provide a one-off release of the latest available SUS+ Admitted Patient Care (APC) and mortality data. This one-off release of data will be used to support the urgent risk stratification work, and not for any additional purpose. In addition to this, the University of Oxford and its data processors are permitted to use the HES and mortality data released under DARS-NIC-240279-Y2V2N and DARS-NIC-375354-G8V1H to support this urgent COVID-19 risk stratification work while those two data sharing agreements remain active.

QResearch is a database of linked medical records that has been used and continues to be used by a variety of research projects undertaken by UK universities, from reviewing the safety of antidepressant medicines to studying factors to predict variations in survival rates for cancer patients. The QResearch database consists of the coded pseudonymised electronic health records from primary care patients registered with approximately 1,500 general practices spread throughout the UK.

QResearch was originally a not for profit collaboration originally between the University of Nottingham and Egton Medical Information Systems (EMIS) but the University of Nottingham’s roles and responsibilities have since been transferred to the University of Oxford. Strategic decisions about the GP data are taken by a Management Board representing the interests of EMIS and the University of Oxford. The University of Oxford is the sole data controller for the datasets which are linked to QResearch (deaths, cancer and hospital data) and the single point of access to the data.

The patient level data linked to QResearch is only accessed by academics employed by University of Oxford or its data processors as named in this data sharing agreement. In all cases, data can only be accessed on site at the University of Oxford. However, the researchers involved in a given project (contributing to the research question, design, interpretation and writing of the paper for publication but not handling the data) may be employed by other UK universities. The NHS Digital data stay on site at the University of Oxford and are only handled by University of Oxford and its data processors. The University of Oxford may have a collaborator at another university on the project team advising on clinical aspects or interpretation of findings, but they will not receive any data. Data will not be used for any solely commercial purposes and all applications for the use of HES and/or mortality linked data are subject to a governance process explained in the Processing Activities section.

Only University of Oxford staff and the named data processors will have access to SUS and Civil Registration - Deaths record level data. External researchers will only have access to tabular outputs that are aggregate with small numbers suppressed in line with the HES Analysis Guide. Record level data are not shared with researchers outside of the University of Oxford.

Research undertaken using the extended database continues to be processed using the existing arrangements with respect to scientific review and annual reports to Trent MREC. Research has to be peer reviewed, original, hypothesis driven or hypothesis testing, intended for publication in an academic peer reviewed journal. All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.

Yielded Benefits:

The first paper was published in Heart as a fast track submission and showed that ACE inhibitors were not associated with an increased risk of poor outcomes from COVID (as had been feared) so provided reassurance to public and professionals on the safety aspect of these drugs. Two other papers have been published - one in the BMJ describing the first version of the risk stratification tool and another in Annals regarding the particularly high risk of poor outcomes for those people with Down's syndrome. Three reports have been produced already for SAGE including (a) risk of COVID-19 associated with variations in household size; differences in COVID-19 risk between the first and second pandemic waves by ethnic group and (c) the first population-based study of COVID-19 outcomes in children including the differential by ethnic group.

Expected Benefits:

The aim is to provide useful knowledge that patients, GPs and intensive care doctors can use to reduce the risk of severe COVID-19 infection within this pandemic.

Specifically it will help research to understand whether drugs commonly taken for chronic conditions such as hypertension or diabetes may exacerbate or reduce the severity of COVID-19 disease. It is hoped this study will be able to identify alternative drugs for patients with chronic conditions, as well as possible drugs to treat COVID-19; and recognise high-risk patients in primary care.

Around 14 percent of the adult population in England take anti-hypertensive medications, and around five percent receive medication to treat diabetes. The prevalence increases with age, making usage particularly common in those at risk of for severe COVID-19 infections. In many cases drugs from a different class could be used instead. If these drugs are increasing the risk of severe infection, they represent one of the few modifiable risk factors for severe COVID-19 infection. Medical and research communities need rapid large-scale accumulation of data on the outcomes of patients who develop COVID-19 infection whilst taking these drugs to allow appropriate risk assessment and clinical decision making for these patient groups. Other drugs in common use in primary care patients are believed to have anti-viral activity to COVID-19, such as hydroxychloroquine, used in rheumatoid arthritis, and lopinavir-ritonavir, used in the treatment of HIV.

There are also immune-suppressive therapies that may either increase the risk of severe illness by preventing the body’s response to infection, or attenuate the hyperinflammation syndrome associated with COVID-19 disease, so preventing severe disease.

The incidence of severe disease in patient groups taking these medications urgently needs to be established to guide both their management and investigation of COVID-19 treatment strategies.

ICNARC is already providing up-to-date information on the admission characteristics and outcomes of all patients with severe COVID-19 infection treated on an ICU in England, Wales and Northern Ireland.

Outputs:

The outputs are research papers which are published in peer reviewer academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by with press releases from the relevant organisations and highlighted on social media.

Results are also shared with policy makers and NICE guideline committees on a regular basis via their stakeholder consultations in order to support development of relevant guidelines.

Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.

The results tables within the papers will only contain statistical information with cell counts of > 5, being suppressed in line with the ICO code on anonymisation. Outputs will only contain aggregate level data with small numbers suppressed in line with the HES analysis guide.

No indicators are produced which show performance of an organisation – indeed the identity of the GP practices contributing to QResearch are not shared with any third party.

Processing:

EMIS and TPP process the GP data from the original data controllers (GP practices) and sends it to the University of Oxford. EMIS and TPP are not able to access or process any GP data once it is located at the University of Oxford.

EMIS and TPP are neither a data processor nor a data controller for the data provided by NHS Digital under this Agreement. EMIS and TPP are not able to access the HES data under any circumstances. EMIS and TPP have given permission for the GP data it supplies to be linked with the data from NHS Digital for purposes determined by the Principal Investigator at the University of Oxford.

Before providing data to the University of Oxford, NHS Digital use the Open Pseudonymiser tool to pseudonymise the HES data. NHS Digital retains the salt key for this pseudonymisation, meaning that the University of Oxford are unable to re-identify the data but as described below they are able to link with GP data that was pseudonymised using the same Open Pseudonymiser tool. The University of Oxford will not be provided with a copy of the pseudonymisation salt key.

NHS Digital provide the pseudonymised data to the University of Oxford which is then linked to the QResearch database at individual patient level using a pseudonymised version of the NHS number which has been supplied in both GP data and the SUS data. The data linkage is undertaken by an employee of the University of Oxford. No data items which would identify the data subjects are received by QResearch as the data is pseudonymised-at-source and at NHS Digital. Date of birth is rounded to year of birth before receipt by the University of Oxford. No other data linkage is permitted without further amendment to the data sharing agreement with NHS Digital. There is no requirement to re-identify individuals from the data and no attempts will ever be made to do this.

The resulting data are then used for undertaking primary research relating to COVID-19. The linked data are only accessed by approved research staff with substantive contracts employed by University of Oxford or its data processors. In order to support the urgent COVID-19 risk stratification work, a small number of employees from the University of Cambridge, University College London, London School of Hygiene and Tropical Medicine, and University of Liverpool may act as additional data processors. These organisations' staff will remotely access the data stored by the University of Oxford and will not store any additional copies of the data. These organisations will not have responsibility for determining the purpose for which, or the manner in which data will be processed, and they are only permitted to process data for the purpose of supporting this urgent COVID-19 risk stratification work. Data is only processed on site on secure servers at the University of Oxford. No individual level data will be shared or stored outside the University of Oxford or supplied to any third party not named in this data sharing agreement.

The data processor Dancing House Consulting undertakes IT consultancy on behalf of the data controller, including administration of data backups, database administration, and secure destruction of data. Dancing House Consulting do not undertake data linkage or analysis of the data.

All outputs are restricted to aggregate data with small numbers suppressed in line with the HES Analysis Guide.

Regular reviews against the ICO code on anonymisation (2012) will be undertaken to ensure that the data remain anonymised and all appropriate controls are in place to minimise any risk of re-identification.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

MR1055 - HPS2-THRIVE Treatment of HDL to Reduce the Incidence of Vascular Events — DARS-NIC-147885-0TV66

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006, Consent (Reasonable Expectation))

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-01 – 2020-09 2016.04 — 2024.08.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  5. Hospital Episode Statistics Admitted Patient Care
  6. Mental Health and Learning Disabilities Data Set
  7. Mental Health Minimum Data Set
  8. Mental Health Services Data Set
  9. MRIS - Flagging Current Status Report
  10. MRIS - Members and Postings Report
  11. Cancer Registration Data
  12. Civil Registration - Deaths
  13. Demographics
  14. Hospital Episode Statistics Admitted Patient Care (HES APC)
  15. Mental Health and Learning Disabilities Data Set (MHLDDS)
  16. Mental Health Minimum Data Set (MHMDS)
  17. Mental Health Services Data Set (MHSDS)
  18. Civil Registrations of Death

Type of data: Identifiable

Objectives:

Background Large-scale randomized trial to access the clinical effects of a combined daily tablet of niacin 2g plus MK-0524 40 mg (MK-0524A) on the risk of heart attack or coronary death, stroke, or the need for atrial bypass procedures in people with a history of circulatory problems. Aims The study will include 20,000 patients aged 50-80 years, 7,500 from around the UK plus (at least 7,500 from China and 5,000 from Scandinavia) with a history of circulatory problem.

Yielded Benefits:

In any future application, the applicant will be required to provide details of the actual benefits achieved as a result of the study.

Expected Benefits:

In any future application, the applicant will be required to provide details of the expected benefits resulting from the study.

Outputs:

No new outputs will be produced under this Data Sharing Agreement.

In any future application, the applicant will be required to provide details of the outputs that were produced and disseminated by the study as well as details of any future outputs planned.

Processing:

Under this Agreement, the data may be securely stored but not otherwise processed. No new data will be provided by NHS Digital under this Agreement.

The study data, including data provided by NHS Digital under previous agreements, are currently held by the University of Oxford. Under this interim extension all devices containing data will be securely locked away in a locked cabinet at the University of Oxford storage address specified in this Agreement.

The following provides background on the processing activities undertaken for the original study:

Identifying data was shared with ONS to carry out the linkage between the study data and civil registration data. Participants records were ‘flagged’ with the Office for National Statistics (ONS). ONS notified the study team at the University of Oxford of participants’ deaths (date and cause) and cancer events when they occurred. The ‘flagging for long-term follow up’ service transferred from ONS to the HSCIC in 2008. Data was last supplied in September 2016.

MR706 - SEARCH: Study of the Effectiveness of Additional Reductions in Cholesterol and Homocysteine — DARS-NIC-148341-TC6TD

Opt outs honoured: Yes (Excuses: Consent (Reasonable Expectation), Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c), National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-01 – 2020-09 2016.04 — 2024.08.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Members and Postings Report
  3. MRIS - Cohort Event Notification Report
  4. MRIS - Scottish NHS / Registration
  5. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  6. Hospital Episode Statistics Admitted Patient Care
  7. Mental Health and Learning Disabilities Data Set
  8. Mental Health Minimum Data Set
  9. Mental Health Services Data Set
  10. MRIS - Flagging Current Status Report
  11. Cancer Registration Data
  12. Civil Registration - Deaths
  13. Demographics
  14. Hospital Episode Statistics Admitted Patient Care (HES APC)
  15. Mental Health and Learning Disabilities Data Set (MHLDDS)
  16. Mental Health Minimum Data Set (MHMDS)
  17. Mental Health Services Data Set (MHSDS)
  18. Civil Registrations of Death

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

The data supplied will be used only for the approved medical research project MR706 - SEARCH: STUDY OF THE EFFECTIVENESS OF ADDITIONAL REDUCTIONS IN CHOLESTEROL AND HOMOCYSTEINE

Yielded Benefits:

In any future application, the applicant will be required to provide details of the actual benefits achieved as a result of the study

Expected Benefits:

In any future application, the applicant will be required to provide details of the expected benefits resulting from the study.

Outputs:

No new outputs will be produced under this Data Sharing Agreement.

In any future application, the applicant will be required to provide details of the outputs that were produced and disseminated by the study as well as details of any future outputs planned.

Processing:

Under this Agreement, the data may be securely stored but not otherwise processed. No new data will be provided by NHS Digital under this Agreement.

The study data, including data provided by NHS Digital under previous agreements, are currently held by the University of Oxford. Under this interim extension all devices containing data will be securely locked away in a locked cabinet at the University of Oxford storage address specified in this Agreement.

The following provides background on the processing activities undertaken for the original study:

Identifying data was shared with ONS to carry out the linkage between the study data and civil registration data. Participants records were ‘flagged’ with the Office for National Statistics (ONS). ONS notified the study team at the University of Oxford of participants’ deaths (date and cause) and cancer events when they occurred. The ‘flagging for long-term follow up’ service transferred from ONS to the HSCIC in 2008. Data was last supplied in September 2016.

European Prospective Investigation into Cancer and Nutrition (EPIC) - Oxford ( ODR1516_018 ) — DARS-NIC-656754-C6S5Q

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-10 – 2024-10 2024.06 — 2024.06.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations

Type of data: Identifiable

Objectives:

The University of Oxford requires data from NHS England for the purpose of the EPIC-Oxford study - a nationwide longitudinal cohort study of 60,642 men and women aged 20 and above who were recruited between 1993 and 1999 from throughout the UK.

The study was designed to examine the effects of diet on long-term health, with a specific focus on vegetarians. 50% of the participants do not eat meat, with large numbers following lacto-vegetarian and vegan diets, and EPIC-Oxford is the only large prospective study in the world with dietary data and stored blood samples for a large number of vegetarians together with linkage for the whole cohort to medical records covering cancer diagnoses, hospitalisations and causes of death.

EPIC’s research on the long-term health of vegetarians is unique in the world and is supported by grants from the MRC (“Health of Vegetarians”), the Wellcome Trust (“Livestock, Environment and People”), Cancer Research UK (Aetiology of prostate cancer”) and the World Cancer Research Fund (“Cancer risk in vegetarians”). All this research funded by competitively awarded grants from government and charities, which is focused mainly on cardiovascular diseases, cancer, bone and joint health, and gastro-intestinal diseases, is completely dependent on continued ability to link the whole EPIC-Oxford cohort with the records from HES.

The study is needed to improve understanding of the effects of diet on health and thus inform advice to governments, health professionals and the public about dietary choices to maximise the potential for long-term good health. Further aims include examining the roles of other lifestyle factors (including shift-work) and of endogenous hormones in relation to health.

The study’s overall aim is to provide reliable evidence on choices people can make in adult life to help increase their chances of staying healthy into old age. The aim of the scientific research is to reliably inform the public and health providers and regulators about the statistical findings on risk factors including diet and lifestyle and environmental factors and risk of cancer and other medical conditions.

The data controller is the University of Oxford, and all data is processed in the Nuffield Department of Population Health (NDPH) at the University of Oxford. The University of Oxford is the sole data processor.

All data collected is processed lawfully under GDPR Article 6(1)(e) as a public task in the public interest and under Article 9(2)(j) (‘research’). The use of ‘Article 6(1)e – processing is necessary for the performance of a task carried out in the public interest’ for research purposes is justified as:
•The study is directly related to population health risks and diet which is in the public interest.
•The University of Oxford is a ‘public authority’ as defined in the Data Protection Act 2018.
•Statute 1(3) of the ‘Statutes of the University of Oxford’ states that “The principal objects of the University are the advancement of learning by teaching and research and its dissemination by every means.” (http://www.admin.ox.ac.uk/statutes/1086-120.shtml).
The condition for processing special category personal data is met by the use of ‘Article 9(2)j - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes’ as, in line with the University’s principle objectives previously indicated, the University will be undertaking processing in line with the research protocol stated in this application. The research protocol has received due consideration for its public interest through peer review by a public funder, appropriate ethics committee review and supporting evidence of which is included as part of this application.

Participants were recruited into EPIC-Oxford through; GP practices; through the memberships of the Vegetarian Society and the Vegan Society and through health food shops and magazines. Participants are both male and female and aged 20 or over at recruitment. They were initially asked to complete a questionnaire about their diet and lifestyle, family history, a food frequency questionnaire and to donate a blood sample at recruitment between 1993 and 1999. All surviving participants also provided written consent to follow up their medical records at this time. Participants who were recruited via GP Practices were also asked for blood pressure and anthropometric measurements. Follow up questionnaires asking about diet, lifestyle and health were sent to all surviving participants approximately 5, 10 and 15 years after recruitment. Following recruitment, all surviving participants were also asked to complete a 7-day food diary to record all food consumed in one week.

When EPIC Oxford commenced in 1993 the records available were for cancer registrations and causes of death. Linkage to data from HES became possible after the completion of the recruitment to EPIC-Oxford, and linkage to HES was first established in 2008.

The following datasets are processed by the study and disseminated under two DARS agreements:

DARS-NIC-148322

-Demographics
-Civil Registrations of Death
-MRIS - Cohort Event Notification Report
-MRIS - Flagging Current Status Report
-Hospital Episode Statistics Admitted Patient Care (HES APC)
-MRIS - Cause of Death Report
-MRIS - Members and Postings Report
-Cancer Registration Data


DARS-NIC-656754

-NDRS Cancer Registration data


There are currently 60,642 EPIC-Oxford participants flagged at NHS England. The HES data required is record level pseudonymised data where the date fields only contain month and year. All morbidities and events are required since recruitment to the study in order to have a full record of cancers and deaths for the primary endpoint and to be able to exclude any co-morbidities and confounding variables from the analysis. A complete history of fact, cause and place of death including text fields are required to have a complete history of mortality for each participant to be able to conduct full analysis of the data and to exclude any confounding co-morbidities to produce accurate and reliable results.

Linkage to data for information on detailed NDRS cancer diagnoses and treatment is needed in order to examine the relationships of dietary, lifestyle and other potential risk factors with subsequent health. The aim is to contribute to knowledge of the epidemiology and aetiology of cancers. The priority endpoints which will be studied until 30/04/2026 and beyond are cancers of the breast, prostate, ovary, endometrium, thyroid and colorectum. Without the linked data provided by the NCRAS datasets, EPIC-Oxford researchers will not be able to fully understand the complete burden of the diseases of interest within the cohort. A complete history of the cancer diagnoses, as well as hospital admissions and fact and cause of death, is required to have a comprehensive documentation of conditions for each participant to be able to conduct full analysis of the data and also to exclude any confounding co-morbidities to produce accurate and reliable results.

The pathological and diagnostic data from the cancer outcomes dataset requested in this application will be used in epidemiological analyses of dietary, hormonal and other environmental and biological factors in relation to cancer risk and will also enable the study team to subdivide cancer types according to pathological features of the cancers. Some of the tumour sites being investigated are breast, prostate, ovarian, thyroid and endometrial cancer. The study team aim to expand our collection of data on tumours, allowing the for more tumour characteristics on more types of cancer, at lower cost. The study team require more detailed information on tumour characteristics to enable the study team to conduct further analyses of diet and other risk factors in relation to the incidence of sub-types of cancer, such as prostate cancers subdivided by TNM stage and Gleason score, and breast cancers subdivided by hormone receptor status.

Participants were recruited from England, Wales, Scotland and Northern Ireland, and may have moved since randomisation so coverage of England and Wales for cancer diagnosis and deaths and England for HES is crucial to follow-up all participants. Approval also exists for these data to be collected in Scotland (cancer, death and hospital admissions) and Wales (for hospital admissions only). It would be complicated, costly and burdensome to collect this information any other way, and full coverage of the cohort would not be achieved. The data has been restricted to cohort participants, with the minimum amount of information necessary to answer the research question e.g. only month and year provided for date fields for HES data. NHS England data is necessary because it provides the key mechanism for researchers to work on diseases that are of interest, and the mechanism to exclude any potentially confounding co-morbidities in these datasets. Under this Agreement HES data will be re-supplied for the whole cohort for the period 1997/98 to 2015/16 and new data supplied from 2016/17 up to the latest available. This is because the HES data (supplied under DARS-NIC-148322) is on the basis of participant informed consent rather than the previous CAG Section 251 support, which required national data opt-outs to be supplied.

The priority endpoints which will be studied over the next five years are ischaemic heart disease, stroke, fractures, joint disorders, digestive tract disorders and cancers of the breast, prostate and colorectum. Without the linked data provided by NHS England EPIC-Oxford researchers will not be able to fully understand the full burden of the diseases of interest within the cohort.

Study participants’ records were linked electronically to Hospital Episode Statistics for information on cause-specific hospital admissions, for example cancer diagnoses, cardiovascular disease, joint replacements and fractures. This was to examine the relationships between dietary, lifestyle and other potential risk factors with subsequent health. The aim is to contribute to knowledge of the epidemiology and aetiology of common diseases and other causes of hospital admissions. One of the primary outcomes is cause of mortality so continued receipt of this data will be required in the future.
The collection of these data provides minimal risk of harm to the participants.

Follow-up in a cohort study needs to be as complete as possible. This is to avoid both unnecessary reduction in size of the cohort (which reduces statistical power of data analyses), and loss-to-follow-up bias (which can cause misleading research results). To produce scientifically valid results, it is essential that the whole EPIC-Oxford cohort can be linked with information from medical records. If linkage was not complete there would be a high risk of the results being biased by showing falsely low rates of disease in some dietary groups.

EPIC-Oxford is committed to ensuring participants continue to be kept aware of progress and developments in the study, and to obtain their opinions on current and proposed research and how their data is being used in the study. The unanimous consensus of the study participant panel is that they strongly support the study’s aims and the research that is currently taking place and the future plans. The panel feel that they had been made aware at recruitment that they had signed up to a long term cohort study and they expected their health records to be followed up over many years. The investigators have not changed the scope of the study since the original participant information sheet and protocol were approved initially in 1993 and a further review by the Ethics committee and CAG took place in 2018. It was always intended that the cohort be followed up for diet and cancer risk and other chronic illnesses.

Updates to the protocol have expanded some of these groups, all within the scope of the original objectives. The participants are also aware that the study would run for a further 10 years.

EPIC-Oxford is an independent study with its own research aims with the University of Oxford acting as the sole data controller. From the initial set-up, the study is also part of a larger collaboration called EPIC-Europe. EPIC-Europe is a collaboration between 23 centres in 10 European countries with a total of 521000 participants. The aims of EPIC-Europe are broadly the same as EPIC-Oxford, to study the effects of diet and lifestyle and environmental factors on cancer and other chronic illnesses. The centres involved and the numbers of participants in each country details can be found at the EPIC-Europe web site (https://epic.iarc.fr/). EPIC-Europe is conducting a large number of analyses on the associations of diet with cancer risk, with a focus on the most common cancers such as cancers of the stomach, colorectum (large bowel), breast, prostate and lung. So far, research has focused on the role of fruit and vegetables, dietary fibre, meat, fish, dairy products and alcohol intake, as well as dietary-related factors such as obesity and physical activity, on cancer risk. More details of the findings from EPIC-Europe are found in the EPIC-Europe publications listed on the EPIC Europe website. This will be the focus of a separate data sharing application for EPIC Europe (DARS-NIC-340646-C8Z6J).

This nationwide cohort study was designed to examine the effects of diet on long-term health. All EPIC-Oxford participants provided written informed consent at recruitment to the study in the 1990s. When the study first commenced the records available were for cancer registrations and causes of death. Linkage to data from HES became possible after the completion of the recruitment to EPIC-Oxford, and linkage to HES was established in 2008.

The EPIC-Oxford study team has engaged with the EPIC participant panel by asking them ‘Given the time that has elapsed is it still reasonably expected that the study team are collecting hospital data as part of their medical records’. The participant panel were explicitly asked if they would expect ‘their medical records’ to cover HES data. The panel were also asked whether they felt that the consent given when enrolling into the study met their reasonable expectation that all medical records including deaths, cancer diagnosis and hospital admissions were part of their medical record.

The panel declared that it was and still is their expectation that hospital data, as well as data on cancers and deaths will be received by the EPIC-Oxford researchers as part of their medical record. The patient group ultimately feel that processing of the data is in line with the reasonable expectations of participants who consented to participate in the study.
The participant panel also contribute ideas for disseminating the results of EPIC-Oxford to the study participants e.g via vegetarian society and vegan society publications which the investigators are now looking into.

The national data opt-out does not apply where explicit consent has been obtained from the patient for the specific purpose.

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out

Yielded Benefits:

Obesity, ischaemic heart disease and diabetes are diet-related diseases which put an enormous burden on the health of people in the UK and on the NHS. EPIC-Oxford has shown that, compared with meat-eaters, vegetarians are less likely to be obese (BMJ 1996 Sep 28;313(7060):816-7.), have lower blood cholesterol and a 22% lower risk of ischaemic heart disease (BMJ. 2019 Sep 4;366:l4897.), and a 37% lower risk of diabetes (Nutr Diabetes 2019 Feb 25;9(1):7.). These findings have not only been published in scientific journals and presented at conferences, both scientific and with a lay audience, but have received enormous media interest. For example, the findings on the low risk of ischaemic heart disease in vegetarians, which were published in the BMJ with an accompanying editorial, had an Altmetric score of 2533 which is in the 99th percentile of outputs, with coverage by 132 news outlets worldwide including the BBC and all the major UK newspapers; it is therefore very likely that the findings were read by millions of people in the UK, providing this reliable information direct to the public to increase knowledge and support beneficial dietary changes which in turn will reduce the associated work and cost to the NHS of diet-related ill-health. Findings from EPIC-Oxford have also provided important evidence used by Public Health England’s Scientific Advisory Committee on Nutrition (SACN) in its expert evaluations of nutritional impacts on health, which underpin government policy through the Department of Health. For example, results from EPIC-Oxford together with EPIC-Europe on the relationship of folic acid with the risk of prostate cancer were part of the evidence considered in SACN’s report on folic acid, while other results from EPIC were evaluated in SACN’s review of carbohydrates. The SACN reports recommended folic acid fortification of the food supply, decreases in the recommended intake of free sugars, and increases in the recommended intake of dietary fibre for the UK population, thus having direct impacts on nutritional policy and the future health of the public

Expected Benefits:

Diet has been identified as the number one cause for the burden of disease worldwide, and by providing new evidence on the impact of diet on health, EPIC-Oxford expect to contribute to reducing the work and cost to the NHS of diet-related ill-health.

The aim of EPIC-Oxford is to provide high quality information on the relationships of diet with long-term health, with a focus on the health of vegetarians and vegans. Although much is already known about diet and health, important questions remain, and in particular it is essential to gain a deeper understanding of the health impacts of “plant-based diets” which are increasingly being recommended as part of strategies to combat climate change and for other environmental reasons. EPIC-Oxford is unique in the world in having a large cohort in which 50% of participants do not eat meat, with long follow-up, a biobank, and linkage to medical records to provide complete and objective follow-up.

Publications from EPIC-Oxford constitute a very substantial proportion of the world literature on the long-term health of vegetarians; the only other comparable prospective study is based in California, but this has no biobank or comprehensive linkage to electronic medical records. Based on the research from EPIC-Oxford and other studies, it is now well-established that vegetarian diets are compatible with good long-term health, and this research underpins the ability of the NHS to provide advice supporting healthy eating as a vegetarian; the NHS could not give such advice without the evidence to support the healthiness of vegetarian diets

Outputs:

Diet has been identified as the number one cause for the burden of disease worldwide, and by providing new evidence on the impact of diet on health EPIC-Oxford will contribute to reducing the work and cost to the NHS of diet-related ill-health. The aim of EPIC-Oxford is to improve information on diet in relation to the risk of cancer and other chronic diseases, which offers huge potential for improvements in public health in the UK. The results are published in peer-reviewed publications and presented at conferences, and are also reported through national media.

A major focus of research in EPIC-Oxford is the long-term health of vegetarians and vegans, and this research relates directly to the health of the more than 1.2 million people in the UK who follow vegetarian diets (NHS 2014). The long-term effects on health of a vegetarian diet are not well understood, and little is known about the health effects of a vegan diet. The earlier research in EPIC-Oxford has demonstrated lower risks of ischaemic heart disease, stomach cancer and perhaps haematological cancers in vegetarians compared with non-vegetarians, but understanding of these relationships is incomplete and much further research is needed to assess both the potential beneficial effects of a vegetarian diet and also possible hazards associated with low intakes of some nutrients, such as protein, long-chain n-3 fatty acids, vitamin B12, vitamin D and calcium (particularly in vegans). As well as peer-reviewed scientific publications, the EPIC-Oxford website (www.epic-oxford.org) is used to describe all findings, with lay summaries of findings when appropriate, copies of abstracts, and links to pdfs of full papers. The website provides information both for study participants and for a wider audience in the UK and worldwide and where appropriate findings will also be communicated to the NHS because the research will provide information to underpin their advice, e.g. as on their website: http://www.nhs.uk/Livewell/Vegetarianhealth/Pages/Goingvegetarian.aspx

During 2019 the study team have published four papers on the health of participants in EPIC-Oxford. In a paper in the BMJ, the study reported for the first time ever on the risk of stroke in vegetarians, and found that vegetarians had a higher risk for stroke than meat-eaters, although this was counter-balanced by a lower risk for ischaemic heart disease https://www.bmj.com/content/366/bmj.l4897.long. This paper was published with a linked editorial in the BMJ https://www.bmj.com/content/366/bmj.l5272 and a detailed commentary on the NHS website https://www.nhs.uk/news/food-and-diet/vegetarian-diet-linked-lower-risk-heart-disease-higher-risk-stroke/, as well as articles in 122 news outlets worldwide and widespread media coverage giving an Altmetric score of 2515, which is in the top 1% of all outputs https://bmj.altmetric.com/details/65924701.

Selected publications in 2019
Tong TYN, Appleby PN, Bradbury KE, Perez-Cornago A, Travis RC, Clarke R, Key TJ. Risks of ischaemic heart disease and stroke in meat eaters, fish eaters, and vegetarians over 18 years of follow-up: results from the prospective EPIC-Oxford study. BMJ. 2019 Sep 4;366:l4897.
Knuppel A, Papier K, Key TJ, Travis RC. EAT-Lancet score and major health outcomes: the EPIC-Oxford study. Lancet. 2019 Jul 20;394(10194):213-214.
Papier K, Appleby PN, Fensom GK, Knuppel A, Perez-Cornago A, Schmidt JA, Tong TYN, Key TJ. Vegetarian diets and risk of hospitalisation or death with diabetes in British adults: results from the EPIC-Oxford study. Nutr Diabetes. 2019 Feb 25;9(1):7.
Papier K, Tong TY, Appleby PN, Bradbury KE, Fensom GK, Knuppel A, Perez-Cornago A, Schmidt JA, Travis RC, Key TJ. Comparison of major protein-source foods and other food groups in meat-eaters and non-meat-eaters in the EPIC-Oxford Cohort. Nutrients. 2019 Apr 11;11(4). pii: E824.

The data used from NHS England combined with EPIC Oxford data demonstrates the benefits of the research being in the public interest. The public are able to choose whether their diet choices may affect their health, particularly in heart disease and stroke.

In the Lancet the study reported analyses in EPIC-Oxford on mortality in relation to compliance with the EAT-Lancet dietary score, showing beneficial associations for ischaemic heart disease and diabetes, but no association with stroke and no clear association with mortality. Other 2019 papers reported that vegetarians have a 37% lower risk of diabetes than meat-eaters, and that non-meat-eaters have higher intakes of high-protein meat alternatives (soya, legumes, pulses, nuts, seeds) and other plant-based foods (whole grains, vegetables, fruits) and lower intakes of refined grains, fried foods, alcohol and sugar-sweetened beverages than meat-eaters.

EPIC-Oxford research findings presented to clinicians, policymakers and other academics at conferences (listed below) and via the press as described above will directly benefit health care through the NHS by providing clinicians and other NHS health care professionals with up-to-date evidence-based guidance on the effects of diet on long term health and the risk of death. This will improve clinical health care and inform planners and policy makers to address demands on health and social care in the present and the future.

Examples of recent findings through the linkage of HES data is a recent high profile publication in the BMJ looking at the risks of ischaemic heart disease and stroke in meat eaters, fish eaters, and vegetarians over 18 years of follow-up https://www.ncbi.nlm.nih.gov/pubmed/31484644. This was a newsworthy article and reached a wide audience via the press https://www.bbc.co.uk/news/health-49579820 , with reports in 122 news outlets throughout the world https://bmj.altmetric.com/details/65924701/news. Earlier this year a study paper on diabetes showed that this risk of this disease is much lower in vegetarians than in meat eaters https://www.nature.com/articles/s41387-019-0074-0. Altogether, this research provides more information for government policy makers to advise the general public on eating a healthy diet.

Target publications for 2021/2023 are:

Vegetarian diets and risk of bone fractures: analyses during 2020, publish 2021
Target journal: BMC Medicine

Vegetarian diets and risk of joint disorders: analyses during 2020, publish 2021
Target journal: Rheumatology
Target conference: Society for Social Medicine and Population Health Annual Scientific Meeting, Cambridge 2020

Vitamin B12 and risk of haemorrhagic stroke: analyses during 2021, publish 2022
Target journal: European Heart Journal
Target conference: European Society of Cardiology Congress 2021

Vegetarian diets and risk of digestive tract disorders: analyses during 2021, publish 2022
Target journal: Gut
Target conference: Nutrition Society Summer Symposium, 2021

Diet and risk of cancers of the breast, prostate and colorectum: analyses 2020-2022, publish 2023
Target journal: British Journal of Cancer
Target conference: National Cancer Research Institute Conference 2022

All information regarding collection, processing and storage of participant data including details of participant panel discussions mentioned previously are on the EPIC –Oxford website at www.EPIC-Oxford.org . This website is updated regularly with publications, contains annual newsletters and details of participant panel meetings ensuring that participants are fully informed of how their data are being used. The website also contains details of how participants may opt-out of the study and contact details for the study team, who receive regular e-mails, letters and telephone messages from study participants to update their contact details, or report an illness or a death. Study participants also contact the EPIC-Oxford team about EPIC-Oxford research findings they see in the national press and online.
The website also regularly publishes results from research in EPIC-Oxford, including on diseases for which the information comes from HES (such as ischemic heart disease, stroke and fractures), and information on these scientific publications is included on the study website. Results are also described in EPIC-Oxford newsletters and have been covered by national media (online and print), and is covered by the Nuffield Department of Population Health website www.ndph.ox.ac.uk . Information regarding publications is also tweeted by the wider Twitter handle for the Nuffield Department of Population Health (@Oxford_NDPH).

Processing:

The identifying information shared with NHS England included names, dates of birth, NHS Number, gender, address and postcode. NHS England retains this information and consequently, there is no requirement for further data to flow from EPIC-Oxford to NHS England unless a participant has moved to England from Scotland and requires to be flagged, or a participant has withdrawn from the study and requires to be removed from the flagged cohort whereupon no further data about this participant will be supplied from NHS England.

A complete history of the cancer diagnoses, hospital admissions and fact and cause of death are required to have a complete history of conditions for each participant to be able to conduct full analysis of the data and to exclude any confounding co-morbidities to produce accurate and reliable results.

NHS England send identifying Demographic, Civil Registration mortality and Cancer data back to University of Oxford including supplied date of birth, Supplied Gender, Supplied Member Number, Cause of Death text and cancer registration details. Cause of death text is important because it enables researchers to determine whether or not the ICD codes provided refer to diseases/conditions that were on the causal pathway. Cancer registration number is important because it enables researchers to correctly identify which cancer is to be deleted in the event of a cancelled cancer; cancer site and morphology (type) data are essential and cancer anniversary year is required to check on the date of diagnosis. Supplied gender and date of birth are necessary for checking that the data really do refer to the participant identified by the member number.

The HES data provided by NHS England is pseudonymised record level data and the participants are not re-identified.

The Demographic, Civil Registration mortality and Cancer Data is held separately from the HES data, When an analysis file is created the fields are merged using a pseudonymised ID into a file containing no other identifying information. During this process there will be no attempt to re-identify any individuals who are taking part in the study.

These data from NHS England provide the study with the most accurate and cost-effective method of participant follow-up. Using any other means would be laborious and costly, and the results would not be as accurate or comprehensive than those that are collected centrally at NHS England.

The data is received from NHS England by a single named Statistician, who processes the files, storing the data, and creating an updated events data file from which analysis files for researchers and other statisticians who work on the study are generated. The analysis files contain the minimum of individual level data required to answer the research question, and are pseudonymised, containing no identifiable data. During this process there will be no attempt to re-identify any individuals who are taking part in the study.

Two named EPIC-Oxford Statisticians have access to the main administrative database, which includes identifiable information on participants (allowing for linkage to health-related records) and is located and maintained separately from the research database (which contains all the data of analysis files for researchers but no data from which any participant could be identified).

1. HES data and identifying Demographic, Civil Registration mortality and Cancer data are downloaded from the NHS England server to Oxford by a named statistician.
2. Pseudonymised NHS England data including event dates and particulars are stored in events databases in NDPH at the University of Oxford, with access limited to named individuals. These databases do not contain participant identifying information (name, date of birth, NHS number, gender, and postcode).
3. Identifying participant information linked to the study ID numbers are stored separately to the dataset for use in analysis and are held only for administrative purposes and for use in facilitating ongoing data linkage.
4. Data files for analysis by epidemiologists, statisticians and students are created by the named statisticians, merging data from the events databases with baseline, follow-up and biological data provided by participants as required.
5. The analysis dataset contains full date of death for individuals whose deaths were reported. These data files contain only pseudonymised data (gender, month and year of birth, month and year of any events, but no names or other identifiable data), and contain the minimum amount of data required to answer the research question. The analysis dataset (containing the study participant’s linked records from the sources specified above) will not be re-linked with the identifiers. All subsequent analyses use only subsets of the pseudonymised data. All such subsets are customised according to the characteristics relevant to the specific analysis, containing only the minimum data required for the specific purpose.
6. Data files for analysis are retained in a secure location on the server only for as long as necessary, for example, to answer questions from journal correspondents and commentators on published papers, and in order to re-run analyses as required.

The research questions and analyses are overseen by the Chief and Principal Investigators of EPIC Oxford who are employees of the University of Oxford and apply for funding to use these data in accordance with the protocol for the benefit of the public to be able to make choices regarding their diet and lifestyle and their risk of cancer or other chronic illnesses.

The datasets will be pseudonymised as described above before statistical analyses are undertaken. Various types of analyses are undertaken on an ongoing basis for the overarching purpose of assessing cancer incidence, health risks and overall mortality. The data will be held only at the NDPH at the University of Oxford. The data will only be accessed by authorised members of the EPIC-Oxford study team of epidemiologists and statisticians, all of whom are substantive employees of the University of Oxford, or non-contractual DPhil and MSc students who complete a University Research Services form agreeing to terms and conditions of the project, grant and relevant sections of the latest Data Sharing Agreement with NHS England. These are filed in the Research Coordinators office with signed copies sent to the Director of Research Services at University of Oxford. Every member of staff working on these data receives an IG induction and made aware of the terms of use of these data. The staff and students also complete an MRC course on Research and GDPR and confidentiality https://byglearning.co.uk/mrcrsc-lms/course/index.php?categoryid=1 for which a certificate with the appropriate pass mark needs to be submitted before access to data is authorised. The data will only be used for the objectives of the study as described within the Data Sharing Agreement. The EPIC-Oxford study will not share any data supplied by NHS England with any other institution or individual outside of the study team at Oxford University.

The IT security measures in the NDPH include:
• Access control: controlling access to resources using a default “deny-all” policy, user, authentication and policies to commission and decommission access on receipt of the appropriate permissions
• Boundary control: configuration and management of a perimeter firewall and interior firewalls within the network, monitoring, DDOS and other attack mitigation,
• Secure storage: NHS England -supplied data is stored on a dedicated, access-controlled server which facilitates encryption-at-rest and prompt data deletion.

The Data will be accessed by authorised personnel via remote access. The Data will remain on the servers at NDPH at the University of Oxford at all times

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this agreement) and complies with the organisation’s remote access policy.

MR1134 - The Oxford Monitoring System for Attempted Suicide: Mortality following Deliberate Self-harm — DARS-NIC-147957-4444C

Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251, Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7); Other-Section 251, Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.; Other-Section 251, Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. ; Other-Section 251, Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. ; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2018-08 – 2021-07 2019.02 — 2024.06.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Flagging Current Status Report
  5. MRIS - Members and Postings Report
  6. Demographics
  7. Civil Registration - Deaths
  8. MRIS - Bespoke
  9. Civil Registrations of Death

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

The data supplied by the NHSIC to University of Oxford will be used only for the approved Medical Research Project MR1134.

Yielded Benefits:

Conducted studies which are relevant to clinical services and policy on suicide prevention. One example is how through linking episodes of self-harm with suicide as an outcome, researchers are able to identify clinically important risk factors for suicide following an episode of self-harm (non-fatal self-harm being the most important risk factor for suicide). For example, in children and adolescents is has been shown that risk of future suicide is strongest in boys, and in those with multiple episodes of previous self-harm and where certain specific methods of self-harm have been used. In adults it has been shown that a particularly high risk of subsequent suicide in people who have a history of multiple episodes of self-harm. Another example concerns the relationship between clinical management and subsequent suicide. Thus, the researchers have been able to investigate whether receipt of a psycho-social assessment while a person is in hospital following self-harm decreases the risk of future suicide. A further example has been to show that a measure of suicidal intent (that is of an individual’s apparent wish to die that is associated with an episode of self-harm) is related to short-term risk of future suicide, but not longer-term risk. This is relevant to clinical practice because suicidal intent is often measured by clinicians using a specific scale (the one used in this research).

Expected Benefits:

Every year there are about 200,000 presentations to general hospitals following self-harm in England and Wales. Self-harm is the strongest risk factor for completed suicide and is associated with non-suicidal premature death. It is also associated with considerable healthcare costs. Self-harm has been highlighted as a priority area for research in the National Suicide Prevention Strategy for England and especially in the 2017 update of the strategy.

Understanding risk factors for mortality following self-harm and how clinical services may mitigate these risks are key to reducing premature mortality. Data from this study are expected to improve understanding of specific risk factors for premature mortality and specific causes of death following presentation to hospital for self-harm. In addition, this study is expected to improve the University of Oxford’s understanding of how specific aspects of in-hospital care for patients who self-harm are related to risk of premature death. This will help design better services for patients who self-harm which aim to reduce distress, self-harm repetition and mortality.

The study is part of a collaboration between three centres: University of Oxford, University of Manchester, and Derbyshire Healthcare NHS Foundation Trust. Sharing of de-identified data between these three centres is important for maintaining this collaboration.

Findings from this study inform the research community as well as policy and decision-making bodies who translate the findings into healthcare benefits.

Outputs:

The Oxford monitoring System and the Multicentre Study of Self-harm in England (including data from the monitoring systems for self-harm at University of Manchester and Derbyshire Healthcare NHS Foundation Trust) are ongoing projects. Outputs from these projects are multiple. The aims of this study are to identify risk factors for specific causes of death (including suicide) in persons who present to hospital after self-harm and to investigate how specific aspects of in-hospital care relate to mortality following self-harm. Specific outputs planned for the next 18 months include:

* Identifying overall risk factors for suicide and other specific causes of death following self-harm.
* Identifying risk factors for suicide and non-suicidal premature mortality in children and adolescents
* Specific method of self-harm as a risk for suicide and premature death
* Epidemiology of paracetamol poisoning and risk of death by suicide.

* The findings from these studies will be published in peer-reviewed journals aimed at clinicians and researchers.
* Periodic reports for the Department of Health (the study funding body) and the National Suicide Prevention Strategy for England Advisory Group to communicate progress and key findings will be produced.
* Findings are published on the website of the Multicentre Study of Self Harm in England where information is summarized in layman's terms.

Other outputs include:
* Presentations of research findings at scientific meetings aimed at clinicians, researchers and stakeholders
* Presentations at meetings with clinical staff involved in delivering care for individuals who self-harm
* Meetings with policy making and regulatory bodies such as the National Institute for Health and Care Excellence (NICE), Medicines and Healthcare products Regulatory Agency (MHRA), National Suicide Prevention Strategy working group

In all the above, data will be presented in an aggregate format and individuals cannot be identified.

The University of Oxford has previously produced a large number of studies on mortality following self-harm using the linked data from NHS Digital.
All outputs including lay summaries of publications are accessible on the Centre for Suicide Research webpages on the University of Oxford’s website:
http://cebmh.warne.ox.ac.uk/csr/recentpubs.html

Details of publications by the Multicentre Study are published on the Multicentre Study website: http://cebmh.warne.ox.ac.uk/csr/mcm/index.html

Processing:

For the purpose of the Oxford Monitoring System for Attempted Suicide, the University of Oxford collects information about every visit to the Accident and Emergency department of the John Radcliffe Hospital following self-harm.

The University of Oxford submits identifying details of study members (i.e. individuals included on the Oxford self-harm database) to NHS Digital so that the individuals can be ‘flagged’ for long-term follow up. NHS Digital then supplies notifications of study members’ deaths (date and cause) or exits from or re-entries into the NHS.

The University of Oxford has been receiving data on individuals recorded in the Oxford self-harm database from 1976 onwards. Reports on all flagged patients are supplied to the University of Oxford on an annual frequency.

On receipt of the data from NHS Digital, the University of Oxford cleans the data and links it with the existing data on self-harm by the same person. The data are stored on the High Compliance System (HCS) at the University of Oxford.

Data will be checked and processed on the HCS at the University of Oxford. After all identifiers are removed a de-identified version of the data using unique numerical identifiers will be merged into the Oxford Monitoring System study file for the purpose of local analysis.

Identifiers are needed as this is an ongoing study with multiple updates about mortality. Therefore, identifiers from NHS Digital are required in order to check the accuracy of specific records. For example, if a specific individual who has been updated on the University of Oxford’s records as deceased re-presents to hospital for self-harm after their recorded date of event, the University of Oxford will need to retrieve the original record from NHS Digital to check this record. The University of Oxford has considered the number of identifiers required and have minimised these to include only NHS number, date of birth, forename, surname and gender of patient for the purpose of record checks and verification.

As the Multicentre Coordinator, the University of Oxford receives deidentified data from the two other collaborating sites (University of Manchester and Derbyshire Health NHS Foundation Trust). On receipt of this data, the University of Oxford becomes the data controller. At the University of Oxford, the data is amalgamated to create a combined de-identified dataset consisting of data from all three sites. A copy of the combined pseudonymised dataset is transferred from University of Oxford to Derbyshire Healthcare NHS Foundation Trust and the University of Manchester. On receipt of their copies of the combined dataset, Derbyshire Healthcare NHS Foundation Trust and University of Manchester become the data controllers for their respective copies and will process the data in accordance with their respective Data Sharing Agreements with NHS Digital. The University of Oxford in turn is the data controller for its copy of the combined dataset.

The de-identified dataset is stored separately from the Oxford self-harm cohort and, while the combined cohort contains a copy of the Oxford self-harm cohort, the two datasets are not directly linked.

NHS Digital variables securely submitted by the collaborating sites to the study coordinator in Oxford are:
- Date of death
- Cause of death text (A to E)
- Date of registration
- ICD10 underlying cause
- ICD10 multiple cause codes (1 to 15)
- Event type

The same variables from the Oxford Monitoring System for Attempted Suicide are shared with the collaborating sites as described above.

No patient-identifiable data are shared between the three collaborating centres.

Both datasets are analysed by University of Oxford staff to identify risk factors for specific causes of death including suicide and other causes in persons who present to hospital after self-harm and to investigate how specific aspects of in-hospital care, may relate to subsequent mortality.

The University of Oxford must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

EMPA-KIDNEY (The Study of Heart and Kidney Protection With Empagliflozin) - Post-Trial Follow-up (PTFU) — DARS-NIC-743681-L8G9L

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Sensitive

When:DSA runs 2024-05 – 2025-05 2024.05 — 2024.05.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Demographics

Type of data: Identifiable

Outputs:

The expected outputs of the processing will be:

• Lay summaries of important results to be shared with the public via the trial website https://www.empakidney.org/
• Submission to a major peer-reviewed journal (for both the main PTFU results and associated health economic outputs)
• Presentations at relevant scientific meetings e.g., the World Congress in Nephrology, American Society of Nephrology, European Renal Association.
• Open lectures to the public.
• Posters
• Press/media engagement and other public promotion of the research (e.g. via the Nuffield Department of Population Health website (https://www.ndph.ox.ac.uk/), or X (previously Twitter) account (@oxford_ndph).
• Advice to government (including NHS England).

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The University of Oxford plans to present results at the American Society of Nephrology in October 2024. The corresponding publication should be issued in Q4 2024. Results from the Health Economic analysis are intended to be published by Q1 2025.

Processing:

The University of Oxford will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth and a unique person ID) for the cohort to be linked with NHS England Data.

NHS England will provide the relevant records from the Demographics dataset to the University of Oxford. The Data will contain directly identifying data items including NHS Number and Date of Birth which are required for the purposes of validating linkage. This enables the Study Team to ensure that the linkage process is robust and accurate.

The Data will not be transferred to any other location.

The Data will be stored on servers at the University of Oxford.

The Data will be accessed onsite at the premises of the University of Oxford, and will be accessed by authorised personnel via remote access.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Remote processing will be from secure locations within England and Wales. The data will not leave England and Wales at any time.

Access is restricted to employees of the University of Oxford. Access is granted on a “need to know” basis on the instruction of the Information Asset Owner for the EMPA-KIDNEY trial. Only personnel involved in the EMPA-KIDNEY trial will have access to the Data under this Agreement.

Boehringer Ingelheim International GmbH (BI) is not permitted to access the Data.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will not be linked with any other data.

The University of Oxford will retain the Data until sites have confirmed any deaths that the EMPA-KIDNEY Study Team report to them. Identifiers received from NHS England will be destroyed after validation of deaths. The University of Oxford will not be destroying the identifiers held directly from participants.

The Data received from NHS England will be used as follows:

• Information on deaths will be crosschecked with the trial database. If new deaths are identified (i.e. deaths not previously reported by the site), the fact and date of death will be reported to sites to assist them with identifying deceased participants and find medical records relating to their death held locally.

• NHS England death Data will not be entered into the trial database, or used for analysis. In the event that an unreported death is identified, the site responsible for the participant will be prompted to check their records (which include access to the NHS Spine) and to report the death into the study database via the web-based system, as they would do routinely for deaths reported in other ways (e.g. via a relative or other healthcare provider).

MR1231 - The 3C Study (Campath, Calcineurin inhibitor reduction and Chronic allograft nephropathy) — DARS-NIC-388486-D9M5N

Opt outs honoured: No - consent provided by participants of research study, No - data flow is not identifiable, No (Excuses: Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-02 – 2022-01 2017.09 — 2024.05.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Outpatients
  6. MRIS - Scottish NHS / Registration
  7. Civil Registration - Deaths
  8. Cancer Registration Data
  9. Demographics
  10. MRIS - Flagging Current Status Report
  11. Hospital Episode Statistics Admitted Patient Care (HES APC)
  12. Hospital Episode Statistics Outpatients (HES OP)
  13. Civil Registrations of Death

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

Despite improvements in short-term outcomes in kidney transplantation (e.g. acute rejection rates) there has been no improvement in long-term outcomes (e.g. transplant survival at 5 – 20 years after transplantation). One reason for this is that drugs (in particular, calcineurin inhibitors or “CNIs”) used to prevent rejection in fact damage the transplant in the long-term and are major reasons for its ultimate failure. The 3C Study is investigating two strategies that may allow the use of CNIs to be minimised or removed completely. Nearly all kidney transplant trials to date have been both too small and in particular too short-term to detect any clinically meaningful treatment effects in outcomes that matter to patients i.e. long-term function and survival of the transplant. The 3C study therefore aims to study a large enough group of patients for long enough to detect such treatment effects.

In order to detect the long-term effects of the study treatments cost-effectively, the Clinical Trial Service Unit at University of Oxford (CTSU) prospectively planned to flag all participants with available NHS registries (including ONS and HES) to capture information on relevant outcomes. The outcomes that are covered by the registries relevant to this, and previous, applications include cause-specific mortality, site-specific cancer and hospitalisation (which includes infections which are a particularly important outcome for kidney transplant recipients).

The 3C Study is investigating two possible strategies that could improve the lifespan of kidney transplants: firstly, is Campath-based induction treatment superior to standard basiliximab-based treatment; secondly, is sirolimus-based maintenance treatment superior to standard tacrolimusbased treatment. Although the primary outcomes of the study are relatively short-term, there is considerable scientific interest in the long-term (i.e. 5 – 20 year) outcomes from this study. In particular, there is uncertainty about the safety of such treatments with malignancy being one complication of transplantation that often occurs late.

The data from NHS Digital (formerly known as Health and Social Care Information Centre) will therefore be crucial to the ability of the trial to provide uniquely reliable information on the short- and long-term effects of different immunosuppression strategies in kidney transplantation.

Yielded Benefits:

Two major publications have informed practice nationally and internationally. In particular, the first Lancet publication has increased the use of alemtuzumab (one of the tested interventions) nationally.

Expected Benefits:

The results of analyses based on the data received from NHS Digital would be considered by guidelines writers and agencies such as NICE when updating recommendations for the care of transplant recipients. They would be unique in the field of kidney transplantation in that they would provide unbiased, randomised assessment of the long-term effects of different immunosuppression strategies. They are highly likely to affect the management of future patients receiving kidney transplants.

Future Benefits

Once the outputs from this study are publicly available they will be included in systematic reviews of immunosuppression in kidney transplantation, including those conducted by organisations such as the National Institute for Health and Care Excellent (NICE). Such reviews would consider the outputs from this trial along with those from other trials in the same area and make clinical practice recommendations based on the totality of the evidence.

NICE have recently published guidance on this topic and therefore it will be automatically reviewed in the next few years. The 3C study have not engaged directly with NICE but expect that the outputs from the trial will be considered when the topic area is updated.

The benefits will depend crucially on the results of the analyses. The published outputs have indicated that alemtuzumab-based induction therapy reduces the risk of rejection compared to current standard treatment with no early complications. This has led some kidney transplant units to adopt alemtuzumab as their standard of care, whereas others are waiting for the longer-term results (and NICE appraisal) to decide whether to change. The avoidance of rejection is of benefit to patients as rejection may reduce the longevity of the transplant. It is also costly so strategies to reduce rejection can save money.

If analysis of long-term outcomes (which requires linkage with NHS Digital) shows that one or other of the treatments being tested in the 3C Study improves transplant survival this would be a substantial benefit to patients (who experience longer and better quality of life with a functioning transplant compared to being on dialysis), providers (because it is substantially less-expensive to care for patients with a functioning transplant than patients on dialysis) and the wider public (because if transplants last longer then the demand for re-transplantation will fall and thus reduce pressure on the waiting list).

Outputs:

Outputs to date

The 3C Study has already had one publication in the Lancet (Volume 384, No. 9955, p1684–1690, 8 November 2014). The data requested here would be used to generate presentations at international medical conferences and subsequent publications in high-impact medical journals.

Future Outputs

Another publication is in preparation (and an abstract has been accepted for presentation at an international conference). The University of Oxford hope to publish a further output in a major medical journal later this year. Further outputs will follow in later years.

The long-term follow-up is also likely to be of substantial interest and would be presented and published in the future. For example, the protocol-specified 5 year follow-up will be conducted in 2017/18, but later analyses will also be of substantial interest.

Participants will be followed (where possible) for their lifetime and beyond the period of questionnaire-based follow-up. The outputs from this trial will not be limited to the assessments specified in the protocol.

The results of the 3C Study will be published in general and renal/transplant journals. The early results were published in The Lancet and the first results using these data will also be published in a high-impact medical journal. In addition, they will be presented at national and international meetings such as the British Transplantation Society, the Renal Association, the European Society of Transplantation, the American Transplant Congress and the Transplantation Society. The outputs will also be shared with all appropriate bodies such as NICE and the Cochrane Centre.

The University of Oxford will send a plain English summary of the results to all surviving participants (and publish the same on the University website) at the time of any publication of the relevant output. The University of Oxford will ensure the results are available in open-access format so anyone with an interest can access the outputs.

All outputs will contain only data that is aggregated with small numbers supressed in line with the HES Analysis Guide.

The commercial sponsors provided funding for the trial and will receive copies of any outputs prior to their public dissemination. They have the right to comment on these outputs but they cannot require or mandate any changes. For the avoidance of doubt, the principal investigators (all employed by the university) have the final decision regarding any outputs.

Processing:

The 3C study includes 800 patients aged over 18 years who were listed for kidney transplantation.

Participants were recruited around the time of transplantation when informed consent was sought (see attached consent form which includes long-term follow-up through NHS registries) and they were randomised into the study prior to receiving their transplant. They have then been followed-up alongside their routine clinical care for one year with study clinic visits. In addition, data will be collected on adverse events they have experienced, current medication, laboratory results, quality of life and healthcare usage through annual mailed questionnaires.

The approved study protocol also specifies that all participants will be “flagged” with NHS registries such as the Medical Research Information Service and Hospital Episode Statistics. CTSU would seek information on cause-specific mortality, cancer diagnoses and hospital admissions on an annual basis. Any relevant information supplied may be verified with the participant’s managing doctors and then used in the study analyses.

In addition, information on mortality would be used to prevent the coordinating centre from contacting any participant known to be dead.

The study has already provided a list of participant identifiers along with a unique study participant ID number to NHS Digital. The flow of information back from NHS Digital can therefore be anonymised.

Update

Data is only accessed by substantive employees of the university within the Clinical Trial Service Unit, Nuffield Department of Population Health, the University of Oxford.

The data provided by NHS Digital is reviewed by clinicians using bespoke programs. Events of interest that are identified are then entered into the study database using a separate program which records the details of interest (namely, nature, date and outcome of event). The analysis is then run on the study database.

Data will be processed in line with ONS terms and conditions

EXTEND Study: Needs-Assessed Care for Early Psychosis — DARS-NIC-474674-R3F7S

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2022-11 – 2025-11 2023.02 — 2024.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  2. Civil Registration - Deaths
  3. Emergency Care Data Set (ECDS)
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Mental Health Services Data Set
  7. Civil Registrations of Death
  8. Hospital Episode Statistics Accident and Emergency (HES A and E)
  9. Hospital Episode Statistics Admitted Patient Care (HES APC)
  10. Mental Health Services Data Set (MHSDS)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires access to NHS Digital data for the purpose of the following research project: EXTEND Study: Needs-Assessed Care for Early Psychosis

The EXTEND study team are researchers from universities across the UK, led by the Chief Investigator from the University of Oxford.

The following is a summary of the aims of the research project provided by the University of Oxford:
'The purpose of this research is to investigate the impact of alternative durations of Early Intervention in Psychosis (EIP) care on service users’ health outcomes. This will include understanding and contextualising the existing variations in the duration of EIP care provided and service user outcomes, and estimating the cost-effectiveness of an alternative, flexible, needs-assessed EIP service. To do this, the study team proposes to create and analyse a pseudonymised dataset linking routine health service data from NHS Digital, to a clinical audit dataset held by the Royal College of Psychiatrists (National Clinical Audit of Psychosis- NCAP).'

Early Intervention in Psychosis (EIP) services are phase-specific, multidisciplinary, community-based mental health teams that treat people who are experiencing, or who have recently experienced, their first episode of a psychotic illness. EIP services are the principal pathway for the treatment of an emergent psychosis in the NHS in England.

It is not known what the optimal length of treatment should be for individuals within EIP services. It is not known whether the length of treatment, in itself, improves or reduces the chance of a ‘good’ outcome. The majority (58%) of individuals with First Episode Psychosis (FEP) will have an initial remission of their symptoms after the first episode of psychosis and 38% will reach eventual symptomatic and functional recovery. There is also a significant proportion who do not reach remission nor recovery criteria after their FEP, representing 3000 people a year in England. Furthermore, there is a range of illness trajectories following a first episode, meaning the eventual outcome is not easy to predict at the beginning of the illness.

Given this range of possible outcomes and trajectories, it is likely that a flexible, needs-focused treatment is required for those who experience FEP, rather than the current standard package of 3 years of assertive community treatment for everyone. It is possible, therefore that some people would benefit from longer treatment within EIP to help sustain the improvements made in the first few years. Conversely, it is possible that the length of treatment in itself is not relevant, but it is the delivery of NICE-recommended treatments that is the most effective component of treatment, which could be delivered over a shorter timeframe.

The following NHS Digital data will be accessed:
• Hospital Episode Statistics (HES) Admitted Patient Care (APC)
• HES Accident & Emergency (A&E)
• Emergency Care Data Set (ECDS)
• Mental Health Services Data Set (MHSDS)
• Civil Registration Deaths (mortality)

The requested data from MHSDS, ECDS, HES and mortality will be linked with the pseudonymised records from the National Clinical Audit of Psychosis (NCAP). The linked dataset will provide data on a large representative cohort of patients receiving care from EIP services, together with detailed data on health service use and outcomes. This will allow an analysis of the objectives of the EXTEND study - the impact of the duration of EIP care on outcomes.

The level of the data will be pseudonymised.

The data will be minimised as follows:
• Limited to data for a study cohort identified from NCAP data in 2019/20 and 2020/21 which the Royal College of Psychiatrists will provide to NHS Digital.
• Limited to data between 2016/17 and latest available at the time of dissemination (expected in 2023).

The University of Oxford is the data controller and is the organisation responsible for ensuring that the data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care.

The funding is provided by the National Institute for Health Research (NIHR). The funding is specifically for the EXTEND study - Personalised Care for Early Psychosis, funding is in place until May 2025.

Cardiff University and Imperial College London (co-investigators on the EXTEND project) will be data processors acting under the instructions of the University of Oxford.

The Office for National Statistics (ONS) is a data processor. The role of ONS role is limited to hosting and providing access to the NHS Digital data in their Secure Research Service (SRS). ONS will receive the NHS Digital data and will upload it to the Secure Research Service (SRS). NHS Digital data will not be stored on any premises other than those of the Office for National Statistics.

Other co-investigators on the project (including from Pennine Care NHS Foundation Trust, Leeds and York Partnership NHS Foundation Trust, Keele University, Centre for Mental Health and Manchester Metropolitan University) do not require access to the NHS Digital data and do not determine the means and purposes for processing for this specific study. These institutions are conducting qualitative, policy or project management work as part of the broader NIHR grant. This includes a Manchester Metropolitan University (MMU) professor who is the co-chief investigator (and is therefore listed as leading the project on publicly available material, including the privacy notice) but does not determine the means and purposes for the processing in this agreement.

This EXTEND study is part of an overall programme of research funded through the NIHR through a Programme Grant for Applied Research (PGfAR) and for which the Professor from MMU is Programme Chief Investigator. There are several work packages that different universities are leading and this study is being led by the Professor from University of Oxford as Chief Investigator for this specific study. Therefore, whilst the Professor at MMU has responsibility for the overall programme of research, for the purpose of this specific processing Oxford University is the sole data controller.

Data will be accessed by a PhD student affiliated with Imperial College London. The individual has completed mandatory data protection and confidentiality training and is subject to the University of Oxfords' policies on data protection and confidentiality. The individual accessing the data will do so under the supervision of a substantive employee of Imperial College London. Imperial College London would be responsible and liable for any work carried out by the individual. The PhD student would only work on the data for the purposes described in this Agreement.

A Public and Patient Information and Engagement (PPIE) group was consulted regarding the collection of the data for the purposes described above.

The study has convened an EXTEND patient and carer Involvement Group (EXTEND-InG), chaired by the two PPI co-investigators, which has already met to discuss the proposed data linkage and the methods for informing individuals affected.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for policymakers, and local decision-makers such as doctors, and patients to inform best practice to improve the care, treatment, and experience of healthcare users relevant to the subject matter of the study.

The use of the data could
• help the health and social care system to better understand the health and care needs of populations.
• lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
• advance understanding of regional and national trends in health and social care needs.
• inform planning health services and programmes, for example, to improve equity of access, experience, and outcomes.
• inform decisions on how to effectively allocate and evaluate funding according to health needs.
• provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from or areas of poorer practice that need to be addressed.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

This study intends to estimate the impact of alternative models of provision of Early Intervention in Psychosis care. If it finds that extended, or more flexible, duration of EIP care benefits patients experiencing First Episode Psychosis (FEP) and is cost-effective, it could guide the direct improvement of the National Health Service (NHS).

Evidence generated from the study may have relevance to tens of thousands of people with a diagnosis of psychosis. Furthermore, the data generated has the potential to impact on their carers, clinicians, service managers and Integrated Care Boards (ICBs).

Through the publication of findings in appropriate media, the findings of this research may add to the body of evidence that is considered by the bodies, organisations, and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

The linked NCAP data and NHS Digital data may be suitable to be used as a resource for future research into care for early psychosis, subject to the required approvals.

Outputs:

The outputs will not contain NHS Digital data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the datasets from which the information was derived.

The outputs of the processing will be national-level aggregates and modelling. Some statistics will be reported at the EIP team level (<100 individuals). Statistical disclosure risk for small numbers will be managed in line with the ONS protocols on disclosure risk for health data.

The expected outputs of the processing and how they will be communicated to relevant recipients through the following dissemination channels:
- Interim reports to the funder on the progress of data linking and causal inference.
- End of programme reports to the funder on each of the key work packages: understanding existing duration in EIP care; causal impact of different durations of EIP care on patient outcomes; cost-effectiveness of alternative duration EIP provision.
- Submissions to open-access peer-reviewed journals (e.g. Lancet Psychiatry or British Journal of Psychiatry).
- Presentations at national and international conferences (e.g. International Early Intervention Association / International Congress of The Royal College of Psychiatrists).
- Specific reports on findings for healthcare policymakers.
- Guidance for EIP service providers to aid in the development of a national implementation strategy if the intervention is found to be effective.

Production of policy-focused and Patient and Public Involvement (PPI)-focused outputs (such as blogs, videos, briefings and short reports) will be ongoing throughout the course of the funded project period (June 2022 to May 2025). The funder requires interim reports at 9 months and 18 months. Final reports, including journal submissions, are intended to be completed by the end of the funded project period (May 2025).

Processing:

Royal College of Psychiatrists (RCPsych) will transfer data from NCAP to NHS Digital. The data will consist of identifying details (specifically NHS Number, age, gender, and partial postcode) along with a unique person ID ('pseudonymous key') for the cohort to be linked with NHS Digital data.

NHS Digital will provide the relevant records from the HES APC, HES A&E, ECDS, MHSDS, and Civil Registration Deaths datasets to ONS. The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other record level data (NCAP data) already held by ONS.

RCPsych is also sending directly to ONS the same unique person ID with their pseudonymised NCAP data which the EXTEND study team will then use to link to the NHS Digital data via the unique person ID.

The ONS will store the NHS Digital data as part of its Secure Research Service (SRS), which only grants access to accredited and approved researchers. The ONS Information Asset Owner (IAO) will take overall responsibility for the Controller’s data after delivery to ONS. The ONS IAO will ensure all data are managed in accordance with Standard Disclosure Control (SDC), and all applicable Data Protection Legislation.

Researchers from the University of Oxford, Cardiff University and Imperial College London will have access to the pseudonymised linked dataset through the ONS SRS.

Once researchers and their research projects are accredited or approved, projects using the SRS have a project space created. Data sets requested for projects will be mapped to the project space. Researchers named on projects will then be provided with their account details and instructions on how to access the SRS. Access to the SRS is through a safe setting. Safe settings may be in safe rooms on ONS sites, in safe rooms on other certified sites, or through an organisation that has an Assured Organisational Connectivity Agreement with ONS and which maintains current certification.

The data will not leave England/Wales, at any time.

Access is restricted to employees or agents of the University of Oxford, Imperial College London and Cardiff University who have authorisation from the University of Oxford Chief Investigator.

All personnel accessing the data have been appropriately trained in data protection and confidentiality.

The NHS Digital data will be linked at person record level to the NCAP data obtained from RCPsych.

ONS will not be linking any of their datasets to the NHS Digital data (i.e. the NHS Digital data will be held in isolation on SRS but will be linked by the pseudo key to the NCAP data (all pseudonymised).

There will be no requirement and no attempt to reidentify individuals when using the data.

Researchers from the University of Oxford, Cardiff University, and Imperial College London will conduct statistical analysis to understand the existing variation in duration of EIP care, estimate the effect of increasing EIP duration from 3 to 5 years and estimate the cost-effectiveness of alternative models of EIP provision. All statistical outputs from this work will be checked by the ONS for disclosure and will take the form of aggregate statistics and modelling.

The short and long-term cardiovascular consequences of critical illness: The C3 Study — DARS-NIC-352725-V1X2R

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(a); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05 – 2024-05 2022.02 — 2024.02.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Admitted Patient Care
  4. Civil Registrations of Death
  5. Hospital Episode Statistics Accident and Emergency (HES A and E)
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The C3 Study: The short and long-term cardiovascular consequences of critical illness is designed to find out which patients are at risk of heart attacks/strokes up to several years after discharge from an Intensive Care Unit (ICU).

This study will also investigate whether treatments and events occurring in an Intensive Care Unit ICU contribute to this risk.

The mortality of patients who survive a period of treatment on an ICU is considerably higher than an age and sex matched general population. There is evidence of a high rate of major adverse cardiovascular events (MACE) amongst ICU survivors. MACE events include nonfatal stroke, nonfatal myocardial infarction, heart failure and cardiovascular death.

There are no data resources in existence that combine data collected during the episode of critical illness (occurring in ICU and during admission to hospital), with longer-term health data such as repeat hospital admissions, cardiovascular events, treatment and other related medical conditions.

The aim of this study will be to find out which patients are at risk of MACE after discharge from an ICU. This study will also investigate whether treatments and events occurring in ICU contribute to this risk.

In order to perform this study, a data resource needs to be generated that is sufficiently large and detailed. In an ICU, patients’ vital signs, treatments and blood tests are often electronically recorded as part of normal care. Following successful treatment on ICU patients remain admitted to the hospital before being discharged. During this time, they continue to accumulate electronic test results such as laboratory reports and diagnostic data. During this period on the wards they may also experience a heart attack or stroke which it is vital that is captured for purposes of the study.

By linking these highly detailed electronic health care records with NHS long-term follow-up data, the study team can unpick what factors increase patients’ long-term risks and identify patients at highest risk of having heart attacks/strokes years after ICU care.

This study will provide new knowledge about the associations between baseline cardiovascular risk, the disease resulting in ICU admission and therapies / events on ICU with subsequent MACE events, to allow the ongoing risk of these events to be determined. This may identify modifiable risk factors and allow for preventative treatments, improving the health outcomes of this vulnerable group of patients.

University of Oxford’s justification for processing is GDPR Article 6 (1) (e): The processing necessary to perform this task is in the public interest and the task has a clear basis in law. This is an issue of patients suffering critical illness and the clinicians treating it, what happens to patients after they leave ICU and whether the study team can identify those at risk and potentially prevent it.

The dissemination of the aggregated results of this study pose no risk to the public.
GDPR Article 9 (2)(j): processing is necessary for scientific research purposes and shall be proportionate to the aim pursued, respect the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

The data requested will allow the study team to build a novel database linking intensive care therapies and individual patient responses with longer term time to event data (both fatal and non-fatal) medical events requiring hospitalisation. Using this data, the study team can study in unprecedented detail both the event rate and methods of predicating who is at greatest risk or suffering an adverse event.

This study is staffed by two NIHR funded doctoral research fellows who are substantive employees of University of Oxford and work for the Critical Care Research Group in the University of Oxford. The themes of the two research programmes are focused on cardiovascular health after intensive care from both the myocardial event rate and the cardiac rhythm perspectives, respectively. This request relates to The C3 (short- and long-term consequences of critical illness) study (c3study.org). This is an NIHR funded observational study of patients admitted to certain intensive care units with the aim to find out which patients are at risk of heart attacks/strokes up to several years after discharge from an ICU. The team will also study how much the treatment the patients received on ICU contributes to this risk.

• Conduct a detailed review of what has been written in this area
• Find out how many patients suffer strokes/heart attacks after ICU care in England
• Work out which diseases and ICU treatments make heart attacks/strokes more likely
• Determine which patients are at greatest risk of heart attacks/strokes up to several years after leaving ICU

By linking these highly detailed ICU records with NHS long-term follow-up data, the study team can unpick what factors increase patients’ long-term risks and identify patients at highest risk of having heart attacks/strokes years after ICU care.
This study is a standalone project, and no wider collaboration is planned.

Retrospective observational cohort study of patients >16 years of age admitted to an Intensive Care Unit (ICU) in one of the study sites. This is a non-interventional cohort study comparing those patients who experience cardiovascular events and patients in the post ICU population who do not.

This study will provide new knowledge about the associations between baseline cardiovascular risk, the disease resulting in ICU admission and therapies / events on ICU with subsequent MACE events, to allow the ongoing risk of these events to be determined. By understanding who is at risk, it may be possible to modify known risk factors. Where the risk factors cannot be modified, the study team may be able to add preventative treatments.

The study team will create a new database to containing patients’ vital signs, treatments and blood tests, data routinely collected in ICU. By linking these highly detailed ICU records with NHS long-term follow-up data (HES & Civil Registration Data data), the study team can unpick what factors increase patients’ long-term risks and identify patients at highest risk of having heart attacks/strokes years after ICU care.

To understand how events in ICU effect cardiovascular risk after ICU discharge it is important to obtain data about subsequent events. Linking ICU data to key data items in the HES and Civil Registration data datasets are key in this regard.
Only pseudonymised data will be retained and used for analysis by the study team. HES data is an essential feature of this study providing the follow-up and coding data required to define the outcome of interest. HES data will be received on a per patient basis as it must be linked to the study dataset. However, only pseudonymised data will be received by the coordinating site (Critical Care Research Group Oxford University) from NHS Digital (all postcodes will be translated into LSOA codes by NHS Digital). No data from NHS Digital will be transferred to the participating sites. At the co-ordinating site the dataset to which it is being linked will not contain any direct identifiers

To adequately answer the study’s questions, many years’ worth of data is needed. This will provide the scale required to provide robust results and predictive model development. Relatively few people are admitted to ICU every year at each hospital (around 1000 admissions for a teaching hospital ICU). The study will include admissions dating back to 2006 (around the time the digital systems needed to conduct the study started to be used on ICU) to gain about 14k admissions to ICU per hospital. Some of these NHS Trusts have several ICUs but not all the ICUs have been using the digital systems for the entire 14 years. The study team therefore estimates that the 4 NHS Trusts currently in the study will provide around 84k admissions. The study needs a minimum of 5 years of HES data prior to the incident admission to ICU to assess co-morbidities and risk factors. The request for this number of years of data is therefore based on a recruitment period starting in 2006 to the current day and 5 years prior to the first admission.

Obtaining data from different types of hospital (district general and teaching hospitals) from different geographical locations, will make the study results more generalisable to the UK as a whole. The published data will only ever be published in aggregated form (this includes all mediums both published and websites etc.) and will apply small number suppression to prevent the results of small sub-groups of patients being published. The study results may will then be heeded by more hospitals, potentially benefiting more patients.

In studies of this size, individual patient consent is not feasible. No alternative study method was available that could provide the necessary data. The study team have therefore taken steps to ensure data processing is minimised and as unobtrusive as can be. The study team obtained full support from the Confidentiality Advisory Group.

The study will extract only data that will aid with the answering of the questions of the study. The study team require up to 120K ICU encounters (defined as a single visit to ICU) in order to overcome many of the challenges studying this outcome represents. The size of the cohort required has been determined by an a priori sample size calculation to provide adequate power to detect risk factors associated with MACE events after ICU admission. The number of years of historical data required were determined by this sample size. All patient episodes within the specified timeframe are required so ensure readmissions and repeated events are properly recorded. Cohort minimisation will occur at each participating site. Only those patients with valid admissions to participating ICUs will be included

HES – Used for timings and coding of co-morbidities and events that occur in the 5 years prior to ICU admission and the 5 years post.
Lower Layer Super Output Areas (LSOA) codes - Map different areas of the country to published deprivation indices which can be used to adjust for variations in deprivation across the England.
Civil Registration of Deaths – Limited to timing and cause of death with LSOA and occupation added for the purposes of correction for deprivation.

The study team have gone to some lengths to ensure that personal data collected will be relevant and limited to what is necessary in relation to the purposes of the study.

The organisations involved are:
a. Co-ordinating site (data controller, processor and guardian) – Critical Care Research Group, University of Oxford.
b. The participating sites (which will submit identifiers directly to NHS Digital and pseudonymised data to the participating site):
i. Oxford University Hospitals NHS Foundation Trust
ii. Royal Berkshire NHS Foundation Trust
iii. Imperial College NHS Foundation Trust
iv. King College NHS Foundation Trust

By having each site submit their identifiers directly to NHS Digital using their encrypted file transfer service, this improves data security as the identifiers do not need to be aggregated or stored for any period of time by the co-ordinating centre.

c. Internal linkage is performed by NHS Digital to Civil Registration of Deaths, HES APC and HES A&E.

The protocol and CAG application forms discuss third party linkage to NICOR via NHS Digital. This is currently on hold from a study management perspective and will not proceed without future amendment of both the CAG and this NHS Digital Data Sharing Agreement.

Expected Benefits:

Through addressing questions about the impacts of critical illness / ICU on subsequent cardiovascular disease amongst survivors, the outputs of this work will inform:

- Clinicians regarding the ongoing/future cardiovascular risks to their patients (journals and conference presentations)
- Patients now and in the future of their short, medium and long-term cardiovascular risks (twitter and specialist interest groups)
- The wider health care community and health services that are tailored to the treatment of patients during and after ICU (combination of journals, conference presentations, twitter and specialist interest groups)

Likely action/change/decision from this work:
Derive a method of identifying which patients are at risk of heart attacks, strokes and arrythmias and understand common risk factors. This work will identify potentially modifiable risk factors that may lead to identification and treatment of vulnerable patients.

Magnitude of impact:
The research will be able to estimate both the size of the affected population and therefore the number of potentially preventable cardiac events following ICU in England.

Actions leading to benefit:
Through publication of several scientific papers and presentations at scientific meetings on the topic the study team will raise the understanding of the scale of this problem faced by patients following ICU. This work should lead to further funded work that result in prevention and treatment options.

Measuring benefit:
Ultimately the benefit will depend on which risk factors are identified and the degree to which they can be modified in clinical practice.

Achievement:
The aim is to achieve these goals within the 3-year study period.

Outputs:

This study aims to publish at least two journal articles within the first 3 years of the study tackling the areas of cardiovascular risk and atrial fibrillation following critical illness respectively. These will be published in high-impact open access peer-reviewed journals (e.g European Society of Intensive Care Medicine Journal and Critical Care).

All published output will be accompanied by a corresponding press releases including lay summaries of the findings and its applicability to patients. Findings will be presented at national and international conferences to experts in the field.
Outreach will occur to specialist interest groups such as ex-patients and their families via:
- ICU charity “ICUsteps” (https://www.icusteps.org/)
- Intensive Care Society’s patient group
- Oxford patient forum

Outputs could include commentary, tweets and statements of support

When major findings are published, the departmental (Critical Care Research Group at University of Oxford) press office will assist with press releases, social media messages and interviews. The study has a significant social media presence using a Twitter account comprising of patients and health care professionals. All findings and comments will be manged through this Twitter account.

The study website will be updated with all the details of the above.

The study team will engage with policy makers, such as Intensive Care Society should the results suggest that areas of clinical practice might be improved.

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)”

The participating sites will submit identifiers to NHS Digital. These individuals identifiers will be linked to the corresponding Hospital Episode Statistics (HES), HES Admitted Patient Care, HES A&E (Accident and Emergency) Data, and, Civil Registration Data by NHS Digital.

The individual sites will each contribute to the study cohort by uploading the local identifiers via the NHS Digital secure upload system. Members of the study team will attend the individual sites and assist with this process, but these identifiers will never be transferred to the co-ordinating site. All the participating / individual sites will be combined to form one study cohort by NHS Digital to form one single cohort.

Pseudonymised patient level data from HES and Civil Registration data will be requested from NHS Digital by the co-ordinating site, University of Oxford.

Data flow will consist of:
- Each participating site will allocate participants a unique study ID.
- Identifiers (specified below) will be submitted from each site to NHS Digital using their secure file transfer system
- NHS Digital will merge these identifiers into a single cohort
- NHS Digital will link to the requested datasets.
- NHS Digital will send the co-ordinating site (Critical Care Research Group – University of Oxford) historical and yearly updates from the above-mentioned data products for the duration of the agreement as specified.

The co-ordinating site will hold and process the pseudonymised dataset.
Data from NHS Digital (HES/ Civil Registration data), and the participating sites will be linked and then subject to a process of data cleaning and data quality assessment. The resulting dataset will then be used for statistical analysis in keeping with the statistical analysis plan detailed in the study protocol.
All linkage will be performed via/by NHS Digital. The study database (held by the co-ordinating centre will not hold any direct identifiers. The identifiers used for linkage to NHS Digital (listed also in the s251 approval form are)
- NHS number
- Data of birth
- Sex
- Postcode

There is no matching or linkage with any other public data.

There will be no requirement/attempt to re-identify individuals.

Data processing is only carried out by substantive employees of the data processor(s) and or data controller(s) who have been appropriately trained in data protection and confidentiality. All data processing takes please within a secure system which is designed in keeping with the principles of a data safe haven. The data does not leave the system at any time. The system is compliant with the NHS Digital DSPT Toolkit.

All data is held within the environment which is owned and run solely by the data controller/data processor and data guardian / co-ordinating site – Critical Care Research Group, University of Oxford.

Evaluating the age extension of the NHS Breast Screening Programme (AgeX Trial) (ODR_2014_367) — DARS-NIC-656752-G2L2P

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(2)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-07 – 2026-03 2024.01 — 2024.01.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS National Radiotherapy Dataset (RTDS)
  3. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Type of data: Identifiable

Objectives:

The University of Oxford requires National Disease Registration Service (NDRS) data for the purposes of the following research project: Evaluating the age extension of the NHS Breast Screening Programme (known as the AgeX Trial). This request was previously managed by Public Health England (PHE), prior to their dissolution in October 2021, under the reference ODR_2014_367.

The NHS Breast Screening Programme (NHSBSP) routinely invites women aged 50-70 years to come for a three-yearly screening. Because of uncertainty about the effects of screening outside this age range, an England-wide cluster-randomised trial is underway to assess the risks and benefits of additional invitations for screening at ages 47 to 49 and, separately, after age 71 (currently 71-73).

The following is a summary of the aims of the research project provided by the University of Oxford:
• Amass and analyse sufficient evidence that will enable the final reports to provide definitive unequivocal evidence on an issue that has been the subject of controversy for over 15 years – specifically whether the harms of breast screening outweigh the benefits.
• Assess the risks of screening (in particular, the chances of being diagnosed and treated for non-life-threatening cancer) and benefits (in particular, the chances of saving a life) for women undergoing additional screening at ages 47-49, and 71-73.

The findings will help the UK government decide whether to widen the age range for routine breast screening.

The University of Oxford requires continued access to the following NDRS data previously disseminated by PHE:
• NDRS Cancer Registration Data (01/01/1995-31/12/2018)

In addition, this request covers the dissemination of:
• NDRS Cancer Registration data (01/01/2019 – latest available).
• Systemic Anti-Cancer Therapy (SACT) dataset (01/04/2012- latest Available)
• Radiotherapy Data Set (RTDS) (01/04/2009-latest available)
Data will be disseminated annually until the end of this Data Sharing Agreement (DSA).

NDRS Cancer Registration Data provides the study with information on tumour characteristics of incident cancers (including histology, size, stage, grade, nodal involvement, and receptor profile); and treatment information. Additional information from the SACT dataset and the RTDS provide information on the subsequent treatment of incident cancers. These data can be used to better understand the health outcomes of women included in the trial.

The level of the data held and disseminated will be identifiable. Identifiable data is required to permit the linkage of the data being disseminated under this Agreement with the Civil Registration (Deaths), Demographics, Cancer Registrations and Hospital Episode Statistics (HES) Admitted Patient Care (APC) disseminated under DARS-NIC-147931-DT25Y; and NHS Screening records (previously provided by PHE, but now provided by NHS England). However, it should be noted that only pseudonymised data is processed for the purpose of analysis. All identifiers will be stored separately from the pseudonymised data used for analysis, with access restricted to the senior systems analyst. The identifiers need to be stored in the event any participant withdraws from the trial so the study team can identify and delete their data from further analysis

The data requested has been limited to the minimum amount necessary to achieve the purposes outlined within this DSA, and will be minimised as follows:
• The data will be limited to a cohort of ~4.5 million women that have been included in the AgeX trial in England. This includes all women aged 47-49 or 71-73 who have been randomised into or randomised out of receiving additional breast screenings.
• The request is limited to data between 01/01/1995-Latest Available, it is necessary to have data over such a long period because firstly, the screening programme currently offers women 7 screenings between the ages of 50 and 70 and the trial is investigating the effect of adding just one screen to the existing 7 routinely offered. Therefore, the screening period is already more than 20 years and the effects of screening are likely to become visible at least 10 years after the first screening. Secondly, it is essential for the trial design to have information on morbidity prior to randomization.

In addition, the AgeX trial team have undertaken extensive work with the NDRS Analysts to ensure compliance with the General Data Protection Regulation (GDPR) Principle of Data Minimisation.

The University of Oxford is the research sponsor and controller who determines the purpose and means of processing the requested data and is the organisation responsible for ensuring that the data will only be processed for the abovementioned purpose. Only the University of Oxford is permitted to process the data disseminated under this DSA.

The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is as follows: Article 6(1)(e)- processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.

The lawful basis for processing special category data under the UK GDPR is as follows: Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

The processing has been deemed to be in the public interest as the research has the potential to determine future policy on National Breast Screening.

The funding is provided by the Department for Health and Social Care, Cancer Research UK and the Medical Research Council. The funding is specifically for the study described. Funding is currently in place until April 2024 with applications in train for future funding. No funder will be given access to the data disseminated under this Agreement or plays a role in determining the purpose and means of processing nor have the ability to suppress or otherwise limit the publication of findings.

Members of the public who are representative of women in the trial have worked in collaboration with the AgeX investigators to ensure that the public voice is represented and included in decision making at all stages of the trial. These members of the public currently include two lay members of the Trial Management Group, and Women members of three public advisory groups: Oxford Biomedical Research Centre PPI Advisory Group; the Oxford Cancer Patient and Public Advisory Group; and Independent Cancer Patients’ Voice. The scope of involvement of the lay members of the Trial Management Group has included providing a public’s perspective on the ongoing progress and conduct of the trial including adherence to the protocol, the need for changes to the protocol, considering recommendations of the data monitoring and ethics committee, and publicly available lay information. The members of the three public advisory groups have provided further input to publicly available lay information. Other PPI activities include, but are not limited to, developing the participant facing information during randomisation, reviewing the content on the AgeX website which has recently been updated (https://www.ceu.ox.ac.uk/research/agex-trial), commenting on the lay summary for a recent grant application. When study results are available, they will be further consulted to provide input to draft manuscripts and grey literature reports, as well as the co-creation of press releases, lay summaries, infographics, and multimedia content such as podcasts and short videos to maximise opportunities for dissemination”.

The study has support under section 251 of the NHS Act 2006 to enable the common law duty of confidentiality to be temporarily lifted so that confidential patient information can be processed without consent, in line with the s251 approvals obtained by this study the national data opt-out applies.

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). Further details on the NDRS opt out can be found here - https://digital.nhs.uk/ndrs/patients/opting-out

Yielded Benefits:

The AgeX Trial is ongoing. The first analysis of the data will not be complete until 2027/28, therefore there are no yielded benefits to date.

Expected Benefits:

The aim of the trial is to assess reliably the risks and benefits of additional NHS invitations for breast screening before age 50 and, separately, after age 70. The results are expected to help determine future NHS policy on age at breast screening, as well as providing a greater understanding of costs and benefits to the NHS and its patients of extending the current breast screening age. The main results are not expected before the mid-2020s but interim results will be reviewed and the trial end date may be brought forward if the evidence is clear before then.

The UK Health Security Agency may use the findings to inform government and influence policy. This may affect breast screening policy in the UK, and influence policy in much of the rest of the world for decades after the results have been published.

While it is not certain whether the results of the study will lead to the extension of the national breast screening age, revisions to national policy based on scientific evidence have the potential to:
• Improve patient outcomes
• Lead to a more informed allocation of funds for screening services
Ultimately benefitting the provision of health and social care.

The benefits of interim analyses are that these will be used to monitor the protection and safety of trial participants in addition to feeding into the wider aims.

Outputs:

The AgeX trial is ongoing. Results on mortality until 2026 will be reported as soon as they become available (no earlier than 2027), but electronic follow-up could still continue, and longer follow-up will be reported as it becomes available. Results on process indicators will be reported in 2023-24.

These outputs, when available, will be communicated to relevant recipients through the following dissemination channels:
• Submission of academic papers to open-access, high-impact, peer-reviewed journals.
• Public reports developed in collaboration with NHS regulatory bodies to ensure the results are used to help provide evidence for health guidelines and best clinical practice.
• The AgeX Trial website at www.agex.co.uk will provide links to open-access peer-reviewed publications and offer free downloads of lay summaries of key and important findings.
• The Twitter handles at NDPH (@Oxford_NDPH) and Oxford Medical Sciences Division (@OxfordMedSci) with a combined following of over 11,000 will promote all significant findings.
• Presentation of research findings at conferences e.g. the UK Interdisciplinary Breast Cancer Symposium, a biennial conference for all those with an interest in the prevention, early treatment and diagnosis of breast cancer last held in 2022; and the European Breast Cancer Conference, an annual conference for all stakeholders in the breast cancer community

As with any trial, it is necessary to gather evidence incrementally throughout the course of the trial in order to check that the trial itself is not exposing participants to increased risk of harm or, conversely, to check for evidence of benefits. The outputs from the interim analyses will continue to be annual reports to the Data Ethics and Monitoring Committee which may also request additional analyses within the scope of the clinical trials objectives if they identify the need. The Data Ethics and Monitoring Committee must report any concerns about the trial or findings to the trial management group.

Outputs will include any data aggregated with small numbers suppressed in line with the appropriate suppression rules.

Processing:

To support future dissemination the University of Oxford will transfer data to NHS England. The data will consist of identifying details: NHS Number, Date of Birth and AgeX ID (StudyID).

NDRS Data Production will provide the relevant records from NDRS Cancer Registrations, NDRS RTDS and NDRS SACT to the University of Oxford. The data will contain directly identifying data items including NHS Number, Date of Birth and AgeX ID to support linkage with other datasets obtained by the study.

All data received from NHS England is added to the core AgeX database. The data will not be transferred to any other location.

The data will be held on servers exclusively at the Cancer Epidemiology Unit (CEU) within the Nuffield Department of Population Health (NDPH) at the University of Oxford and used solely for the purpose of this project.

Backup storage is in three separate secure rooms within NDPH buildings. Backups should be useable in the event of a disaster at the main site and will be accorded the same physical & electronic protections as live data.

The data will be accessed onsite at the premises of the University of Oxford. Data will also be accessed remotely using laptops provided by the University of Oxford using a secure VPN.

The data will not leave England/Wales at any time.

Access is restricted to individuals within the Cancer Epidemiology Unit in the Nuffield Department of Population Health at the University of Oxford, who have authorisation from the Principal Investigator. All such individuals are substantive employees of the University of Oxford and have received appropriate training in data protection and confidentiality.

The data will be linked as described above at an individual record level with the following datasets:
• Civil Registration (Deaths) – disseminated under DARS-NIC-147931-DT25Y
• Cancer Registration Data- disseminated under DARS-NIC-147931-DT25Y
• Demographics Data- disseminated under DARS-NIC-147931-DT25Y
• HES APC Data- disseminated under DARS-NIC-147931-DT25Y
• NHS Screening Data – previously disseminated by PHE

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use a pseudonymised subset of the data provided. When using the pseudonymised data there will be no requirement or attempt to reidentify individuals.

WAX: Weight Bearing in Ankle Fractures. A randomised clinical trial of weight-bearing following operatively treated ankle fracture. — DARS-NIC-504846-J6X8M

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2022-10 – 2025-10 2023.06 — 2024.01.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Emergency Care Data Set (ECDS)
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Critical Care
  4. Hospital Episode Statistics Outpatients
  5. Hospital Episode Statistics Admitted Patient Care (HES APC)
  6. Hospital Episode Statistics Critical Care (HES Critical Care)
  7. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires access to NHS Digital data for the purpose of the following research project: WAX: Weight Bearing in Ankle Fractures. A randomised clinical trial of weight-bearing following operatively treated ankle fracture.

The study aims to determine whether functional outcomes after early weight-bearing in patients with operatively treated unstable ankle fractures are not worse than adopting a delayed weight-bearing regime which is usual care.

University of Oxford will analyse the dataset to:
1. Investigate the difference in risk of adverse events between the trial treatment groups in the first 12 months post-surgery.
2. Investigate the resource use, costs and comparative cost utility between the trial treatment groups in the first 12 months post- surgery.

This study is a randomised clinical trial, which is the best method to compare treatments to guide the care of patients. Randomisation will be used to produce two groups of patients: those given advice to walk on their operated ankle 2 weeks after surgery, and those who wait until 6 weeks. Patient follow-up will extend to 12 months.

It is funded by the National Institute for Health Research (NIHR) Research for Patient Benefit (RfPB) programme, reference number PB-PG-1217-20029. There will be a report submitted to the funder currently planned for the end of February 2023. The study cohort will go through a one-year follow up in January 2023. The data has been requested until 2025 to allow peer review of submitted manuscripts and/or responses to readers, as there may be a need for additional analyses.

The University of Oxford relies on GDPR Article 6(1)(e) as the lawful basis for processing the data within this application. There is public interest for patients, healthcare staff and the NHS, as this research will decrease uncertainty and allow standardisation of care and promotion of development of pathways for more efficient and cost-effective care.

The study requires processing of special category data and relies on Article 9(2)(j) as a lawful basis for processing data.

Data for this project has been minimised to ensure researchers only have access to the data they require to carry out the statistical and scientific processing of the data and to meet the purpose of the project for which there is a public interest.

NHS Research Ethics Approval has been granted for this study and all participants have prospectively consented to share their data in line with the processing described in this agreement.

The project is not part of a wider project, collaboration, or associated work.

The data subjects will be the trial participant cohort who fulfil all eligibility criteria as defined in the project Protocol. Every participant has provided prospective consent to access their personal data.

The cohort will include adults (18 years+) undergoing surgery for an ankle fracture. All participants will be treated non-weight-bearing until their two-week postoperative follow-up visit. They will then be instructed to either begin weight-bearing on the injured leg or remain non-weight-bearing for an additional 4 weeks. The decision on which instruction they are given will be made by chance using a process called randomisation so that neither patients nor surgeons can influence the choice. All other care will be as per usual treatment. Participants will report how well their ankle is healing and working, and their quality of life using questionnaires at intervals over the first year following surgery. Differences in healthcare costs will also be compared as another element of this research.

The University of Oxford recruited 562 participants over a 21-month period (between 13th January 2020 and 29th October 2021), from more than 20 hospitals. At least 436 participants were required in this study. This number was calculated based on previous scientific research to ensure that the study was large enough to reach a firm conclusion about its aims. The published results will inform NICE recommendations and will influence clinical practice.

The participant population for this study consisted of adult patients with an operatively treated ankle fracture:

Inclusion Criteria
• Age 18 years and above.
• The patient has undergone operative fixation for an unstable ankle fracture.
• Surgery was performed within 14 days of the injury.
• In the opinion of the treating surgeon, the participant might benefit from early weight-bearing.
• Able and willing to give informed consent.

Exclusion Criteria
The participant may not enter the study if ANY of the following apply:
• A lack of protective sensation (e.g. peripheral neuropathy).
• Inability to adhere to trial procedures.
• Bilateral operatively treated ankle fractures.
• Already in a trial for ankle fracture.
• Patient has received a hindfoot nail to treat index fracture.

There are around 170 ankle fractures each day in the UK. Many of these injuries heal with support in a plaster cast or splint, but some require surgery to restore the natural alignment of the bones and fix them in place with screws and plates. This improves how the ankle works once the fracture has healed.

Following surgery for an ankle fracture, patients are commonly told not to walk on the affected leg for six weeks in order to allow the bones to heal. Restricting the weight put through the affected leg may reduce the chance of surgical complications such as infection, breakage of the plates and screws, and loss of alignment requiring revision surgery. However, this restriction has been associated with problems such as blood clots, muscle weakness, stiffness, and poor recovery. It is unclear that the traditional six weeks period of limited walking is of any benefit. A recent national review found that surgeons gave patients very varied instructions following ankle fracture surgery, indicating that overall, UK surgeons have differing opinions about the best extended treatment pathway.

There has been little high-quality research in this area. The National Institute for Health and Care Excellence (NICE) and the James Lind Alliance (JLA) Priority Settings Partnerships have identified this question as one of their top priorities for research in trauma.

The objectives that are addressed through this data processing are:
1. Investigate the difference in risk of adverse events between the trial treatment groups in the first 12 months post-surgery.
2. Investigate the resource use, costs, and comparative cost utility between the trial treatment groups in the first 12 months post- surgery.

Emergency Care Data set (ECDS), Hospital Episode Statistics (HES) Admitted Patient Care and Outpatient datasets will be used.

Each of the requested datasets provide distinct data that are not available elsewhere and are required to adjust for between-participant variation and to determine outcomes necessary to answer the research questions described in the objectives.

Data will be required at the level of the participant in order to construct an adequately explanatory statistical model to address the research questions; all data will be de-identified prior to transfer to University of Oxford.

Only 4 years of data for each participant is required in order to fully describe important characteristics of the participants to determine between-participant variation. This includes the one-year follow-up data to determine any adverse events that required treatment and the associated costs.

Only consented trial participants in England will be included in the requested cohort. The team carried out a multicentre trial in order that the results are generalisable to NHS practice (for a better comparison) and therefore require data from participants across England.

In planning the study with patient representatives and gaining NHS Research Ethics approval, the team explored alternatives means to address these objectives and this approach was considered both proportionate and appropriate.

The research team is minimising data requested to only the trial participant cohort; data for each participant in the cohort will be requested for the period of time that they are involved in the trial follow-up.

University of Oxford is the sole data controller and processor for these data. No other third-party organisations are involved in this study. The study team plan, and have ethical approval to, archive the de-identified data required for the study for 3 years beyond the end of the study. It is usual to do this in this type of clinical trial so that if there are queries around the study, the interpretation or the statistical methods used can be answered fully and if necessary with reference to the original data.

Outputs:

At the conclusion of this study, it is hoped that the University of Oxford will have provided the most robust evidence available to infer whether patients who have had surgery for an ankle fracture should wait 6 weeks before walking on the operated leg or walk on their operated leg sooner following surgery. Patients and members of the public will help design a publicity strategy so that the results of the study are distributed outside of the routine scientific literature.

A report will be produced, which will inform the full update to the National Institute for Health and Care Excellence (NICE) Guidance NG38 (Fractures (non-complex): assessment and management) in 2024. Plain English outputs will include papers and web and blog media. A major international free-to-access publication is planned, alongside two national and two international presentations.

The University of Oxford have worked with members of the public who have personal experience of lower limb fractures and have knowledge of how weight-bearing advice can affect patients’ lives. A Patient and Public Involvement (PPI) member has access to the wider pool of experienced representatives who make up the Oxford Trauma and Emergency Care Patient and Public Involvement Group (the study's own PPI group). This group provides wider review of materials and provides input in reviewing plain language literature prior to dissemination, giving a broader forum for review, and providing efficient utilisation of the Patient and Public Involvement member. Using the INVOLVE guidance, the University of Oxford have given the members information on how they can be involved in the research and the type of support and training available to them.

Patients sit on the trial management and steering committees and have a key role in drafting trial documents for participants, attending conferences and assisting with the publication of the results. A Patient and Public Involvement member and a clinical expert led on the final drafting of the patient written intervention instructions.

For wider dissemination, the patient representatives will lead dissemination to the patients and carers directly through their extensive network of patient advocacy organisations which include the ARUK Centre for Epidemiology, Wales Centre for Primary and Emergency Care (Including Unscheduled) Care research (PRIME) and the Oxford Link and other local interface organisations.

They have already helped to generate a plain language summary for patients and the public. This document is available in paper copy, podcast and as a blog. An abstract will be submitted to the biannual NIHR INVOLVE Conference (https://www.invo.org.uk/current-work/) and a PPI member will give a presentation. Posters will also be prepared with the PPI team for inclusion at any workshop or conference where relevant PPI is being discussed.

In addition, to disseminate directly to study participants, findings will be more widely available locally through posters in appropriate outpatient rooms and liaising with identified service user groups.

All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. Data will be aggregated and presented at the level of the randomised treatment arm. If applicable data within cells will be suppressed if they are small values to reduce the risk of re-identification.

No participant-level data falling under this agreement will be shared with any third-party.

The dissemination strategy will consist of three strands. The first will ensure that patients and the public are informed of the trial results; the second will engage practitioners and health-care providers, and the third will inform national guideline and policymakers.

Patients, patient advocacy groups, and members of the public:
Our patient representatives will lead dissemination to the patients and carers directly through their extensive network of patient advocacy organisations which include the ARUK Centre for Epidemiology, Wales Centre for Primary and Emergency Care (Including Unscheduled) Care Research (PRIME) and the Oxford Link and other local interface organisations.

They will help generate a plain language summary for patients and the public. This document will be available in paper copy, podcast and as a blog. An abstract will be submitted to the biannual INVOLVE Conference and a Patient and Public Involvement member will give a presentation. Posters will also be prepared with the PPI team for inclusion at any workshop or conference where relevant PPI is being discussed. In addition, to disseminate directly to study participants, findings will be more widely available locally through posters in appropriate outpatient rooms and liaising with identified service user groups.

Health care providers:
The trial team will work with the Oxford NIHR Biomedical Research Centre (BRC) and Collaborations for Leadership in Applied Health Research and Care (CLARHC) media teams to maximise the reach of the press and publicity outputs from this study. The team has costed the application to include one free-to-access publication in the mainstream literature. The final results will be submitted for presentations at annual meetings of the British Orthopaedic Association (BOA) and the Orthopaedic Trauma Society (OTS). The findings will be presented to the entire NHS via the NHS national electronic Library for Health (NHS Evidence). International ‘reach’ of the published research findings will be supplemented by presentations at high visibility meetings such as the Orthopaedic Trauma Association (OTA) Annual Meeting (US) and European Federation of National Associations of Orthopaedics and Traumatology (EFORT) Annual Congress (Europe).

In addition, the team is developing complementary systems incorporating non-traditional media. The Chief Investigator has been developing an enhanced web presence through blogging on the leading UK trauma and orthopaedic websites. These blogs engage both trauma and research communities. They have been very successful and have provided a means for rapid dissemination. The team plans to expand this activity into additional subject-specific and general blogs such as the British Medical Journal (BMJ).

National guidelines:
The research team will use their established network involvement to disseminate these research findings. These include the NIHR Clinical Research Network, and specialist interest groups (British Orthopaedic Association, Orthopaedic Trauma Society, Orthopaedic Trauma Association and The European Federation of National Associations of Orthopaedics and Traumatology).

The team will alert the relevant NICE standing committee to the results of the trial by notifying their surveillance team.

The study team is due to report in March 2023 and inform the full update to NICE Guidance NG38 in 2024. Progress in the work has been successful despite COVID and they are confident of hitting this timeline. De-identified data will be stored securely for a period of 3 years by University of Oxford following the final report to respond to any queries regarding the study.

Processing:

A file of unique identifiers and patient-level identifiers (NHS number, date of birth, sex, and postcode) will be sent from the University of Oxford to NHS Digital. The cohort includes 562 participants.

NHS Digital will link HES data for each patient identified in the cohort using the matching data file (containing NHS number, date of birth, gender, and postcode) to the unique identifier. The HES data will be at patient level and de-identified. NHS Digital will destroy the linkage file once linkage is achieved. The de-identified HES data, which will include special category health data, with the linked ID will be sent to the University of Oxford.

There will be no subsequent flows of data.

The processing organisation is University of Oxford. Two processing/storage sites will be used: Botnar Research Centre and Nuffield Department of Primary Care Health Sciences.

The trial team will initially prepare the linkage file as described above. On receipt of the linked, de-identified data from NHS Digital the trial team will carry out a prospective economic evaluation, conducted from an NHS and personal social services perspective, using the data provided by NHS Digital, augmented with participants’ self-reports. The economic evaluation will estimate the difference in the cost of resource inputs used by participants in the two arms of the trial, allowing comparisons to be made between the two weight-bearing strategies following ankle fracture fixation and enabling costs and consequences to be compared. Resource utilisation will be captured through the data provided by NHS Digital. The costs of the treatment options, including supplementary interventions (e.g., revision surgery) and rehabilitation inputs will be estimated using NHS reference costs and standardised to current prices. Health-related quality of life will be collected from participants’ self-report at randomisation, and at 6 weeks, 4- and 12-months post- randomisation using the EuroQol EQ-5D-5L measure; responses will be used to generate quality adjusted life-years (QALYs). The economic evaluation will be framed as a cost-utility analysis with results expressed in terms of incremental cost per QALY gained. The team will use non-parametric bootstrap estimation to derive 95% Confidence Intervals (CIs) for mean cost differences between the trial groups and to calculate 95% CIs for incremental cost- effectiveness ratios. The magnitude and significance of the coefficients on the interactions between the covariates and the intervention variable will provide estimates of the cost-effectiveness of the treatment options by participant subgroup.

The data will not be linked to any other data and only the linkages described are permitted under this Agreement.

Routine statistical procedures to suppress small cell numbers (less than 5) will be used to reduce the risk of re-identification. No attempt will be made in the processing to re-identify individuals.

Data processing will only be carried out by substantive employees of the University of Oxford who have been appropriately trained in data protection and confidentiality.

Data will only be accessible to these employees in a designated, locked, secure data processing office with standalone computers in accordance with the data security policies of the University of Oxford, Big Health Data Group (NDORMS), and Nuffield Department of Primary Care Health Sciences.

Tumours of the Central Nervous System: Incidence, Survival and Variation in Treatments (ODR1819_255) — DARS-NIC-656841-D0P8Y

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-08 – 2024-08 2023.08 — 2023.10.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer registration (pre-1995)
  2. NDRS Cancer Registrations
  3. NDRS Linked Cancer Waiting Times (Treatments only)
  4. NDRS Linked HES AE
  5. NDRS Linked HES APC
  6. NDRS Linked HES Outpatient
  7. NDRS National Radiotherapy Dataset (RTDS)
  8. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires access to NHS England National Disease Registration Service (NDRS) data for the following research project: Tumours of the Central Nervous System: Incidence, Survival and Variation in Treatments (ODR1819_255).

The following is a summary of the aims of the research project provided by the University of Oxford:

1. Characterise the incidence of developing various types of primary Central Nervous System (CNS) tumours since 1971
2. Characterise survival following a primary CNS tumour diagnosis
3. Characterise the medical histories leading to a primary CNS tumour diagnosis

The study will further:

1. Characterise the causes of death attributed to patients dying after a diagnosis of a primary CNS tumour and the factors associated with this risk.
2. Characterise the risk of experiencing a further CNS tumour-related event among patients who have been diagnosed with a primary CNS tumour and the factors associated with this risk.
3. Characterise the risk of subsequent events that may be treatment-related.

The following NHS England National Disease Registration Service (NDRS) National Cancer Registration and Analysis Service (NCRAS) data have already been accessed in support of this study :
- NDRS Cancer registration– necessary to estimate CNS tumour incidence, mortality and survival rates
- NDRS Hospital Episode Statistics Admitted Patient Care (HES APC) – necessary to provide information on hospital admissions that may be related to the CNS tumour diagnosis and to describe hospital resource use
- NDRS Hospital Episode Statistics Outpatients (HES OP) - necessary to provide information on outpatient visits following a CNS tumour diagnosis and to describe hospital resource use
- NDRS Hospital Episode Statistics Accident & Emergency (HES A&E) - necessary to provide information on emergency admissions before and following a CNS tumour diagnosis
- NDRS Systemic Cancer Dataset (SACT) - necessary to provide information on chemotherapy treatments received by CNS tumour patients to describe usage and trends over time
- NDRS Radiotherapy Dataset (RTDS) - necessary to provide information on radiotherapy treatments received by CNS tumour patients to describe usage and trends over time
- NDRS Cancer Wait Times (CWT) – necessary to investigate relationships between wait times and CNS tumour diagnoses and their outcomes
Data was released for all individuals who had been diagnosed with a primary CNS tumour between 01/01/1971 to 31/12/2017.

The University of Oxford now wishes to request a refresh of the above-listed datasets for individuals diagnosed with a primary CNS tumour between 01/01/2018 to 31/12/2020.

All data already held, and data being requested is Pseudonymised

The data already held has been minimised as follows:
• Limited to data for a study cohort identified by the NDRS that includes all individuals diagnosed with a primary CNS tumour (defined by specific ICD codes)
• Limited to data for England
• Limited to data between 1st January 1971 and 31st December 2017

The data requested will be minimised as follows:
• Limited to data for a study cohort identified by the NDRS that includes all individuals diagnosed with a primary CNS tumour (defined by specific ICD codes)
• Limited to data for England
• Limited to data between 1st January 2018 and 31st December 2020

The University of Oxford is the controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above. Only the University of Oxford processes the data for the purposes described above.

The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is as follows:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

The Nuffield Department of Population Health, University of Oxford funds the project.

Data will be accessed by:
A PhD student affiliated with the University of Oxford, who is undertaking this project in support of the completion of their PhD. The individual has completed mandatory data protection and confidentiality training and is subject to the University of Oxford’s policies on data protection and confidentiality. The individual accessing the data will do so under the supervision of a substantive employee of the University of Oxford. The University of Oxford would be responsible and liable for any work carried out by the individual. The PhD student would only work on the data for the purposes described in this Agreement.

The project team have consulted individuals affected by a CNS tumour (patients and carers) via online support groups regarding the collection and analyses of the data for the purposes described above. This was achieved through individual discussions to identify aspects of research that are of relevance and importance to patients.

In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in sections 251(10) and (11) of the National Health Service Act 2006.

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out.

Yielded Benefits:

· The manuscript cited in the outputs has proven useful in providing the clinical community with detailed insights into the apparent long-term increase in incidence of CNS tumours in the English population. In particular it has yielded a potential explanation for the observed increases in incidence of non-malignant CNS tumours by identifying important differences in the methods of diagnosis. · An extension of the work published in the aforementioned manuscript was presented to attendees of the largest annual national meningioma (the most common non-malignant CNS tumour) meeting. This (not yet published) research identified important geographic (regional) variation in national diagnoses of meningiomas and yielded important discussions and new collaborations in order to develop this work further and guide future clinical management. · The data for this study were originally provided to us via Public Health England prior to NHS England becoming the data controller. Accessing these data has proven useful in allowing the principal investigator to spend extended periods of time thoroughly examining the quality of the national CNS tumour data and identifying areas of improvement which are necessary to conduct high quality and clinically relevant research into these tumours. As a result of this, the principal investigator, alongside two collaborators with experience in epidemiological research pertaining to CNS tumours, have established the Brain Tumour Data Improvement Initiative in early 2023. The goal of this initiative is to engage stakeholders at a national level including data stewards, data users, patients, clinicians, advocacy groups, funders, and charitable organisations in improving the completeness and quality of data on CNS tumours in cancer registries across the four nations. Initial meetings have already taken place and the initiative has attracted attention and support from the CNS tumour patient community, the director of a leading brain tumour charity, the chair of the NCRI Brain Tumour Group, as well as members of the CNS tumour clinical and research community nationally.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for national guidelines on CNS tumours, local decision-makers such as neurosurgeons and neuro-oncologists, and patients to inform best practices to improve the care, treatment and experience of health care users relevant to the subject matter of the study.

The use of the data could:
• Help the NHS to better understand the health and care needs of the CNS tumour population
• Lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience of CNS tumour patients
• Advance understanding of regional and national trends in health and social care needs for CNS tumour patients
• Advance understanding of the need for, or effectiveness of, preventative health and care measures for the CNS tumour patient population.

The study team has regular contact with all the major UK brain tumour charities (Brainstrust, Brain Tumour Research, The Brain Tumour Charity, and Brain Tumour Support) and will optimise the potential public benefits from the use of the data by disseminating findings (in layperson language) to the tens of thousands of CNS tumour patients and their carers that are part of these groups.

The principal investigator of the study is also a member of the National Cancer Research Institute (NCRI) Brain Group which supports, oversees and facilitates collaborative research on brain and CNS tumours nationally, so the findings can reach a larger audience.

Outputs:

The processing carried out thus far has produced the following outputs:
• Seminar at the Cancer Epidemiology Unit Seminar Series - Nuffield Department of Population Health (completed December 2019)
• Presentation at the Nuffield Department of Population Health Annual Symposium (completed January 2020)
• Presentation at the Yorkshire Brain Tumour Symposium (completed July 2022)
• Presentation at the British-Irish Meningioma Symposium Annual Symposium (completed October 2022)
• Presentation at the Yorkshire Brain Tumour Symposium (completed July 2022)
• Presentation at the British-Irish Meningioma Symposium Annual Symposium (completed October 2022)
• Presentation at Cancer Research UK Oxford Centre 2023 Annual Symposium (completed March 2023)

The expected outputs of the continued processing will be:
• Submission to peer-reviewed journals on an ongoing basis
• Presentation at the Nuffield Department of Population Health Annual Symposium (expected June 2023)
• Presentation at the British Neuro-Oncology Society Annual Conference (expected July 2023)
• Nuffield Department of Population Health DPhil Students’ Symposium (expected July/August 2023)
• Presentation at the British-Irish Meningioma Symposium Annual Symposium (expected September 2023)
• Submission of PhD thesis (expected January 2024)

The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Social media
• Posters displayed at conferences and symposia
• Press/media engagement
• Public promotion of the research – shared with major UK brain tumour charities such as Brainstrust, Brain Tumour Research, The Brain Tumour Charity, Brain Tumour Support

Outputs will be produced throughout 2023-2024 as described above.

The study has submitted abstracts to conferences and presented some of the results of our analyses at national conferences as well as seminars within the University of Oxford:

• Seminar at the Cancer Epidemiology Unit Seminar Series - Nuffield Department of Population Health (December 2019)
• Presentation at the Nuffield Department of Population Health Annual Symposium (January 2020)
• Presentation at the Yorkshire Brain Tumour Symposium (July 2022)
• Presentation at the British-Irish Meningioma Symposium Annual Symposium (October 2022)
• Presentation at Cancer Research UK Oxford Centre Annual Symposium (March 2023)

The study has had a manuscript on trends in CNS tumour incidence accepted in January 2023 by the leading scientific journal in the field of neuro-oncology, which is called Neuro-Oncology. https://doi.org/10.1093/neuonc/noad001

Processing:

No data will flow to NHS England for the purposes of this Agreement.

NHS England will provide the relevant records from the following datasets to the University of Oxford:

NDRS Cancer Registration
NDRS Hospital Episode Statistics Admitted Patient Care (HES APC)
NDRS Hospital Episode Statistics Outpatients (HES OP)
NDRS Hospital Episode Statistics Accident & Emergency (HES A&E)
NDRS Systemic Cancer Dataset (SACT)
NDRS National Radiotherapy Dataset (RTDS)
NDRS Cancer Waiting Times (CWT).

Data will contain no direct identifying data items. The data will be pseudonymised and individuals cannot be reidentified through linkage under data in the possession of the recipient.

The data will not be transferred to any other location.

Pseudonymised data will be securely stored within the Nuffield Department of Population Health (NDPH) file store and will remain there until the end of the study.

The University of Oxford (Nuffield Department of Population Health) uses on-campus backup services.

The data will be accessed by authorised personnel onsite at the University of Oxford, and also on some occasions where necessary, via remote access (VPN). Where information is being accessed via VPN individuals are prohibited from downloading or copying data onto local devices.

The data will remain on the servers at the University of Oxford at all times.

The data will only be accessed within England.

Data will be accessed by a PhD student at the University of Oxford. The individual will act as an agent of the University of Oxford and will be operating under the supervision of substantive employees of the University of Oxford.

The data will be linked at the person record level with the dataset(s) already obtained from the National Disease and Registration Service, via a pseudonymised study (patient) ID.

Data will be analysed and processed by a PhD student of the University of Oxford for the purposes described above, and in support of the completion of their PhD.

Hodgkin and Non-Hodgkin Lymphoma:Using routine data to identify recurrence, and variation in the use of radiotherapy ( ODR1920_011 ) — DARS-NIC-656849-P9M6C

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-05 – 2026-05 2023.10 — 2023.10.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked Cancer Waiting Times (Treatments only)
  3. NDRS Linked DIDs
  4. NDRS Linked HES AE
  5. NDRS Linked HES APC
  6. NDRS Linked HES Outpatient
  7. NDRS National Radiotherapy Dataset (RTDS)
  8. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Type of data: Anonymised - ICO Code Compliant

Objectives:

University of Oxford requires access to NHS England data for the purpose of the following research project: Hodgkin and Non-Hodgkin Lymphoma: Using routine data to identify recurrence, and variation in the use of radiotherapy.

The following is a summary of the aims of the research project provided by University of Oxford:

Lymphoma is a form of cancer which is very sensitive to treatment, both with chemotherapy and radiotherapy. Significant variation in the use of radiotherapy was identified in a report in 2015, which may be more related to geographical and organisational factors rather than patient or disease factors.

This project has two main aims:
• undertake analysis of radiotherapy usage in England, to understand the causes and clinical impact of any variation on patient outcomes,
• use the routine datasets available within NHS England to further understand subsequent relapse and recurrence of lymphoma. Factors predicting recurrence will be identified and used to develop a model to help predict those patients who may experience recurrence of their lymphoma following standard treatment.
The final aspect of analysis will be to look at what long-term side-effects survivors of lymphoma develop. In particular to analyse the incidence of heart disease, stroke and subsequent cancers.

The data accessed from NHS England will form the foundation of improving understanding into the use of radiotherapy, recurrence rates of lymphoma, and late-toxicity in an English population. Having access to population-based data spanning decades will allow the identification of trends which may not otherwise be seen. The large cohort size of the NHS England data will allow statistical analysis to identify any significant predictors of recurrence, or factors associated with variations in radiotherapy usage in the UK.

The following NHS England data will be accessed:
• Hospital Episode Statistics
- Accident & Emergency (HESAE)
- Inpatient (HESAPC)
- Outpatients (HESOP)
• Cancer Registry
• Diagnostic Imaging Dataset (DIDS)
• Systemic Anti-Cancer Therapy Dataset (SACT)
• National Cancer Waiting Times Dataset (CWT
• Radiotherapy Dataset (RTDS)

The quantum of Data requested is necessary to determine treatment patterns, patterns of presentation, co-morbidities, initial treatment, recurrence, and investigation. The Cancer Registry data is necessary to provide a cohort of unique individuals, to allow analyses by age, sex, ethnicity, and vital status and to allow ascertainment of the index diagnosis including multiple prognostic factors and help determine the treatments used.


The level of the data will be pseudonymised and will be minimised as follows:
• Limited to data indexing between 01st January 1997 to 31st December 2020 ;
• Limited to approximately 264,443 records
• Limited to the following geographic areas: England
• Limited to conditions relevant to the study identified by specific ICD or OPCS codes which cover;

Hodgkin Lymphoma, Follicular and non Follicure Lymphoma Mature T/NK-cell lymphomas, Other specified and unspecified types of non-Hodgkin lymphoma, Other specified types of T/NK-cell lymphoma, Malignant immunoproliferative diseases, Hodgkin’s disease, Lymphosarcoma and reticulosarcoma and other specified malignant tumours of lymphatic tissue. morphology codes.

University of Oxford is the research sponsor and the data controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above.

The University of Oxford rely on Article 6(1)(e) - the processing is necessary for you to perform a task in the public interest or for your official functions, and the task or function has a clear basis in law. The public interest in this circumstance is research to increase medical knowledge for the benefit of all and to improve public health.

The University of Oxford rely on Article 9(2)(j) - processing is necessary for archiving purposes in public interest, scientific or historical research purposes. The legitimate need for processing special category data under 9(2)(j) as: "necessary for scientific research purposes to increase medial knowledge for the benefit of all and to improve public health".

The funding is provided by a grant from Cancer Research UK. The funding is specifically for the study described. Funding is in place for 12 months. Funding to continue the work described will be sought on an ongoing basis via an annual grant cycle.

University of Oxford is the sole data controller and sole data processor.

There are no other organisation(s) involved or accessing the NHS England data, including organisations acting in an advisory capacity or as part of an oversight or steering committee.

The design of the proposed use of the data has been discussed with and supported by a Project Advisory Group comprised of 4 individuals previously treated for lymphoma, contacted via the Oxford Blood Group patient involvement group ( https://oxfordbrc.nihr.ac.uk/ppi/oxford-blood-group).

In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and (11) of the National Health Service Act 2006

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out

Yielded Benefits:

Data for this study has previously been shared when the data were controlled and managed by Public Health England (PHE). As such there are some yielded benefits to be observed from the access to the data for the study prior to NHS England becoming data controller. It should be noted, as the study is, by definition, focused on the long-term outcomes of cancer treatments it is not possible to directly assess the benefits of the research as these would not become measurable for many years following any influence on clinical practice. However, some of examples of this study’s research (the late effects of cancer treatments) have been cited and referenced in clinical guidelines and policy documents nationally and internationally over the past 5. The inclusion of research in multiple clinical guidelines and policy documents, for example recent research on the same themes (long term effects of cancer treatments) from the study has been cited in: • 2022 ESC Guidelines on Cardio-Oncology (10.1093/eurheartj/ehac244) • 2022 Update to NCCN Guidelines: Hodgkin Lymphoma, Version 2.2023 • 2022 ACC/AHA/HFSA Guideline for the Management of Heart Failure (10.1016/j.cardfail.2022.02.010) • 2022Position paper of the Heart Failure Working Group of the Austrian Society of Cardiology • 2022 Radiation Therapy Across Pediatric Hodgkin Lymphoma Research Group Protocols: A Report From the Staging, Evaluation, and Response Criteria Harmonization (SEARCH) for Childhood, Adolescent, and Young Adult Hodgkin Lymphoma (CAYAHL) Group (10.1016/j.ijrobp.2021.07.1716) • 2021 Stratification and management of cardiovascular risk in cancer patients. A consensus document of the SEC, FEC, SEOM, SEOR, SEHH, SEMG, AEEMT, AEEC, and AECC (10.1016/j.rec.2020.11.020) • 2021 Cardiovascular Manifestations From Therapeutic Radiation: A Multidisciplinary Expert Consensus Statement From the International Cardio-Oncology Society (10.1016/j.jaccao.2021.06.003) • 2021 Coronary artery disease surveillance among childhood, adolescent and young adult cancer survivors: A systematic review and recommendations from the International Late Effects of Childhood Cancer Guideline Harmonization Group (10.1016/j.ejca.2021.06.021) • 2020 Fondazione Italiana Linfomi (FIL) expert consensus on the use of intensity-modulated and image-guided radiotherapy for Hodgkin’s lymphoma involving the mediastinum (10.1186/s13014-020-01504-8) • 2020 Onco-Cardiology: Consensus Paper of the German Cardiac Society, the German Society for Pediatric Cardiology and Congenital Heart Defects and the German Society for Hematology and Medical Oncology (10.1007/s00392-020-01636-7) • 2020 Guidelines for Long-Term Follow-Up after Childhood Cancer: Practical Implications for the Daily Work (10.1159/000504200) • 2020 Long-Term Follow-Up Guidelines and Organization of Long-Term Follow-Up Care for Childhood and Young Adult Cancer Survivors (10.1007/978-3-030-49140-6_44) • 2019 Evidence-based recommendations for the organization of long-term follow-up care for childhood and adolescent cancer survivors: a report from the PanCareSurFup Guidelines Working Group (10.1007/s11764-019-00795-5) • 2019 Cardio-Oncology Rehabilitation to Manage Cardiovascular Outcomes in Cancer Patients and Survivors: A Scientific Statement From the American Heart Association (10.1161/CIR.0000000000000679) • 2018 Proton therapy for adults with mediastinal lymphomas: the International Lymphoma Radiation Oncology Group guidelines (10.1182/blood-2018-03-837633) • 2018 Bone sarcomas: ESMO–PaedCan–EURACAN Clinical Practice Guidelines for diagnosis, treatment and follow-up (10.1093/annonc/mdy310) • 2018 Proton therapy for pediatric malignancies: Fact, figures and costs. A joint consensus statement from the pediatric subcommittee of PTCOG, PROS and EPTN (10.1016/j.radonc.2018.05.020) Additionally, examples cited include how the data is being used in the development of clinical studies with examples included below. • Citation in: 2019 The Evolving Design of NIH-Funded Cardio-Oncology Studies to Address Cancer Treatment-Related Cardiovascular Toxicity (10.1016/j.jaccao.2019.08.007) • Use of data to inform the development of the PROSPERITY trial (‘A randomised multi-centre phase II study of protons versus photons to deliver intensity modulated radiotherapy with deep inspiration breath hold for the treatment of mediastinal lymphoma’) • Use of data to inform the development of a study of lung cancer screening in Hodgkin lymphoma survivors (led by Dr Kim Linton, Christie Hospital, Manchester) • Use of data to inform the development and analysis and interpretation of a study of Response Adapted incorporation of Tislelizumab into the Front-line treatment of older patients with Hodgkin lymphoma (RATIFTY) – Funded will open soon These activities were sufficient over the past 5 years for the study team to obtain an extension of CRUK’s programme grant for a further 5 years (from April 2022) to continue research and yield further such benefits.

Expected Benefits:

The study’s CRUK programme grant (‘Benefits and Risks of Cancer Treatment’) utilises data from a variety of different sources (also including clinical trials, large cohort studies and radiation dosimetry studies) to provide relevant information to clinicians and patients and allow optimal treatment decisions to be made. The data provided to The University of Oxford by NHS England is another important source of data that contributes towards the overall project aims. It is therefore in the public interest for this data to be released, processed and the results disseminated.

Specifically, the data provided by NHS England will allow:
• Analysis of variation in radiotherapy use across the country and the possible reasons behind this variation.
• Assessment of the long-term risks (e.g. cause-specific mortality and second cancer incidence) following lymphoma diagnosis and treatment.
• Development of an algorithm to detect lymphoma recurrence in routinely collected data to give population-based indications of how recurrence risk has varied by treatment strategies.
The results of this work will contribute towards an improved understanding of the optimal management of different sub-types of lymphoma to further improve the observed outcomes.

Approximately 16,500 people are diagnosed with lymphoma in the UK each year, making it the 6th most common cancer type overall (after breast, prostate, lung, bowel and melanoma skin cancer). Improvements in the management of, and the long-term outcomes after, lymphoma therefore stand to make a substantial benefit to public health.

The study teams record of delivering planned outputs in this area is evidenced by the publication and citation record originating from the programme. In addition the study contributes through informing national (and international) clinical guidelines and the development of clinical trials.

This study is not in direct support of an individual PhD project, but this study has already formed part of a successful PhD thesis (the original data applicant, Dr Rebecca Shakir) and it is planned that these data will be used as part of a further PhD project over the next 4 years.

Outputs:

The expected outputs of the processing will be:
• Abstracts and presentations at national and international conferences
• Submissions to peer reviewed journals anticipating 1 publication per year over the next 3 years.
• Provision of results to other researchers to help in the development of their research studies and in clinical trials
• Results will also be shared directly with people affected by lymphoma at Lymphoma Action’s National Conference and their Lymphoma Matters publication.
• Planned that these data will be used as part of a further PhD project over the next 4 years.

The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The results of analyses of lymphoma outcomes and late effects will be presented using standard epidemiology measures such as Overall Survival (OS), cause-specific mortality (CSM), standardized mortality ratios (SMR), standardized incidence ratios (SIR), absolute excess risk (AER) and cumulative incidences and mortality. These analyses will be completed, presented and published as a number of smaller projects over the next 4+ years, coinciding with the study’s current programme grant funding cycle from CRUK.

Methods to infer recurrence of lymphoma from routinely collected data will be developed over the next 4+ years as part of a Clinical Research Fellow post funded within our CRUK programme. It is hoped that this work will form a component of a PhD thesis and will also be presented and published separately.

The study research group has a strong record of achieving previous research goals, have an excellent publication record and have maintained continuous programmatic funding from CRUK for >10 years. The study team envisage continuing research using these data into the future, requesting renewals and data up-dates every 2-3 years.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Public events such as conferences
• Publication and citation record originating from the programme
• Contribution through informing national (and international) clinical guidelines
• Contribution through the development of clinical trials
The results of analyses of radiotherapy usage will be presented using the proportion of cases receiving radiotherapy and assessing variation by factors including geography, travel time from nearest radiotherapy centre and multiple deprivation index. This analysis will be completed and presented within the next year and subsequently prepared for appropriate publication.

Processing:

No data will flow to NHS England for the purposes of this Agreement.
NHS England will provide the relevant records from the HES A&E, HES IP, HES OP, CANCER Registry, DIDS, SACT, CWT and RTDS datasets to University of Oxford.

The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other older record level data already held by the recipient within the scope of this study and Data Sharing Agreement. Data will not be linked to other datasets out of scope of this agreement.

The data will not be transferred to any other location.

Within Nuffield Department of Population Health (NDPH) department in Oxford University, electronic data files are kept on password-protected network servers behind a local firewall. Servers are kept in a locked room with access restricted to IT staff.
Access to data is restricted via user identification. No data are moved or copied from these servers. The primary data received from NHS England are also stored on the secure NDPH network behind a firewall. The IT department have setup a special permissions compliant folder to receive and hold data securely. The PI of the group controls who can access this folder and the list is reviewed every 6 months. Data are not copied but can be accessed by analysis programs. Receipt of data is recorded in The University of Oxford asset register. When data are to be deleted a request is made to the IT department who provide a deletion certificate which the study team enter into the asset register (any backups resulting from the 28-day back-up cycle are also deleted).

Backups are held for 6 months on internal servers spread over three locations within the Old Road Campus, at The University of Oxford. Backed up data is encrypted both in transit and at rest. After 6 months, any expired data is deleted from the server. Access to data is restricted via user identification. No data are moved or copied from these servers.

The data will be accessed by authorised personnel via remote access. The data will remain on the servers at University of Oxford at all times. Personnel are prohibited from downloading or copying data to local devices.

The data will not leave England/Wales at any time.

Data processing and access will be carried out by substantive employees of the data processor/controller (University of Oxford) who have authorisation from the PI who is working within University of Oxford under honorary contract. All individuals have been appropriately trained in data protection and confidentiality.

No other organisation is permitted to access the data.

There will be no requirement and no attempt to reidentify individuals when using the data. Analysts from the University of Oxford will process the data only for the purposes described above.

Evaluating Clinical Outcomes in Hip, Knee, Foot, and Ankle Surgery — DARS-NIC-667559-J3L9G

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2023-04 – 2026-04 2023.06 — 2023.09.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD, UNIVERSITY OF BRISTOL, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)
  4. Patient Reported Outcome Measures (Linkable to HES)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires access to NHS England data for the purpose of the following research project:

Evaluating Clinical Outcomes in Hip, Knee, Foot, and Ankle Surgery

The following is a summary of the aims of the research project provided by the University of Oxford:

“The purpose of this project is to analyse national hospital episode data to determine the rate of adverse events associated with commonly performed orthopaedic procedures of the lower limbs, investigate the impact of surgeon and unit volume on outcomes, and benchmark proposed thresholds for care outcomes (rate of adverse events or outcomes) that could permit the monitoring of the quality of care and outcomes in the future.

Building upon previous work (DARS-NIC-68703-R4Y6C-v3.5), these national data will be used to identify adverse events for a range of commonly performed hip, knee, foot, and ankle interventions. This study proposes to determine the rate of complications (such as infection, pulmonary embolism, stroke, heart attack, amputation, death) that occur following these procedures along with the risk of readmission, reoperation and revision surgery. The impact of surgeon and treating unit volume will be analysed for individual procedures or groups of similar procedures. National Joint Registry data shows that low volume caseload surgeons may have a higher reoperation rate (Liddle et al JBJS Am 2016), but a similar analysis has not been performed in the Hospital Episode Statistics for joint replacement to investigate whether similar results can be reported, and no such analysis has been performed for the other commonly performed orthopaedic procedures.”

The following NHS England data will be accessed:
• Hospital Episode Statistics (HES) Admitted Patient Care (APC)
• Civil Registration Mortality.
• Patient Reported Outcome Measures (PROMs)

The data requested are required for the analysis of the following:
- to construct a co-morbidity profile for patients (5-year look back Charlson comorbidity index).
- Analyse trends in the rates of procedures being performed (e.g., changes related to the publication of evidence)
- trends in the rates of complications and trends in associations between procedures over time – such as the association between ankle fracture surgery and subsequent ankle replacement or fusion for osteoarthritis, knee fracture surgery and subsequent knee replacement, etc.
- provide adequate numbers for valid analysis of the less commonly performed procedures.

The level of the data will be Pseudonymised.

The data will be minimised as follows:
- Limited to data for a study cohort identified by NHS England as meeting the following criteria:
- Patients who underwent a procedure identified by a prespecified list of OPCS codes limited to orthopaedic procedures and limited anatomically to hip, knee, foot or ankle between 1998 and 2023
- Limited to data between 1998 and 2023. For each individual patient, HES data will only be provided from the date 5 years before the qualifying procedure and all data after until 2023. 5-years look back and the follow up period is necessary as there is no long term outcome data for these procedures. It makes the best use of all of the patient data requested, maximising the potential benefits and impact of the work. For less commonly performed procedures, this allows a larger sample to be analysed increasing the statistical validity of the work.

The University of Oxford is the data controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research and aims to produce publicly available information to inform future decisions over patients’ treatments or care.

The funding is provided by the Academy of Medical Sciences. The funding is specifically for the project described. Funding is in place until the end of this agreement.

Data will only be accessed by substantive employees of the University of Oxford.

A Public and Patient Information and Engagement group were consulted regarding the collection of the data for the purposes described above. The study will develop plain English summaries of findings for communication to patients and members of the public. These will be freely available and published on the NDORMS website (ndorms.ox.ac.uk). The findings may also be presented at patient and public engagement events. The proposed analysis plan and outputs have been reviewed and approved by an established patient and public involvement (PPI) group.

Expected Benefits:

The use of the data could:

• help the health and social care system to better understand the health and care needs of populations.
• lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
• advance understanding of regional and national trends in health and social care needs.
• inform planning health services and programmes, for example to improve equity of access, experience and outcomes.
• inform decisions on how to effectively allocate and evaluate funding according to health needs.
• provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.

The study aims to improve health practice, reducing harm by disseminating findings on the rate of complications associated with orthopaedic procedures performed for the hip, knee, foot, and ankle. This work is in the public interest in the context of the expected measurable benefits.

Analysis will be reported for the studied procedures in different populations of patients and factors associated with a higher risk of adverse events will be summarised. Variation will be studied and reported along with trends at a geographic level.

The impact of hospital and surgeon volume on outcomes will be studied and reported and this is likely to inform improvements to care through recommendations on service design and care pathways. It is highly likely that complication rates vary by health provider (hospital or surgeon level) for these procedures and this investigation will be important in benchmarking care so that an outlier hospital, for example, could be identified in the future to improve outcomes and avoid harms. It is likely that surgeons with a higher volume practice in some procedures may have better outcomes, but it is not known for which procedures this is important – this study may help to define the procedures that are best performed by more specialist surgeons with a high volume of experience rather than ‘generalists’ performing smaller numbers. This may not be case for all procedures, but it not currently known if this is the case for procedures other than joint replacement.

The outcomes from this study may inform patients and surgeons about the risks of procedures and aims to support the shared decision-making process and could lead to fewer high-risk procedures being performed where this risk was previously unknown. Adverse outcomes for certain procedures performed for similar indications may be identified and compared. For example, in foot and ankle surgery, outcomes of ankle replacement and ankle arthrodesis will be compared. These two procedures can be offered for similar indications but there is little information to inform patients and surgeons on relative risks of rarer but serious adverse events. This is because the number of these procedures performed in single centres is usually small and numbers reported in series in the literature also too small to be adequately powered to report this information.

The study outcomes may inform NHS managers, commissioners and other health professionals of the outcomes and predictors of outcome for some of the most common orthopedic procedures. This may encourage a change in practice where necessary, for example due to geographic variation or inappropriately high rates of surgery or higher than expected complication rates. The study outcomes may provide commissioners with evidence of any factors that can explain or address unwarranted variation.

In summary, it is hoped that some of the measurable benefits to health and or social care will be:

1. Patients may be better informed and empowered in the shared decision-making process around these surgical procedures. They may have a better understanding of the risks and long-term outcomes, and this may be invaluable in the consenting process. This improvement could benefit hundreds of thousands of patients undergoing hip, knee, foot and ankle procedures each year.

2. Surgeons may be informed and supported in delivering evidence-based surgery. This may change practice, encouraging ineffective procedures to be abandoned or improve decision making by providing rich data on the relative risks of procedures. The findings of this study may be disseminated to surgeons through journal publications, conference presentations, and communication through social media and the British Orthopaedic Association (BOA).

3. NHS commissioners may be supported in decision making around pathway design and service improvement. For example, for any specific procedures where low volumes are shown to be associated with poor outcomes. Some types of procedures or procedures for certain groups of patients may be found to be of limited benefit or of unacceptably high risk, and such procedures could be recommended for decommissioning. This may lead to large cost savings and ensure patients do not undergo procedures with high risks of adverse events for limited or no benefit. Similarly, the outcomes could help ensure patients do not undergo treatment on a care pathway that could be optimised, for example, in a higher volume centre (should the data analysis support such a recommendation).

It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

Outputs:

The expected outputs of the processing will be:

• A report of findings to the British Orthopaedic Association (BOA) to produce British Orthopaedic Association Standards (BOASts) which are guidelines on the management of orthopaedic conditions. The evidence generated from the proposed work may inform new BOASts or updates to current BOASts.

• Submissions to peer reviewed journals. The first publication target is 18 months from data receipt, with further publications at 6 monthly intervals.

• Presentations to the British Association of Surgeons of the Knee (BASK), British Orthopaedic Association (BOA), British Hip Society (BHS), and British Orthopaedic Foot and Ankle Society (BOFAS) Annual Meetings are targets for the presentation of the proposed work. International dissemination will also be sought, through journal publications and conferences such as the American Academy of Orthopaedic Surgeons (AAOS) and European Federation of National Associations of Orthopaedics and Traumatology (EFORT).

• Publication of dashboards on the University of Oxfords' website, including social media engagement with patients, surgeons, researchers, and allied health professionals. The NDORMs Twitter account (@ndorms) will be used to announce study progress and results. This is intended to engage patients, surgeons, and researchers with research outputs as they are produced.

• Public reports: The study will develop Plain English summaries of findings for communication to patients and members of the public - these will be freely available and published on the NDORMS website (ndorms.ox.ac.uk). The findings may also be presented at patient and public engagement events.

The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the datasets from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:

• Journals
• Workshops involving patient and public engagement events and groups
• Social media
• Public reports
• Industry newsletters

The target date for publication of the results and other outputs is spring 2025.

Processing:

No data will flow to NHS England for the purposes of this agreement.

NHS England will provide the relevant records from the HES APC, Civil Registration Mortality and PROMS datasets to the University of Oxford. The data will contain no direct identifying data items. The data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

The data will not be transferred to any other location.

The data will be stored on servers at the University of Oxford.

The data will be accessed onsite at the premises of the University of Oxford only.

Personnel are prohibited from downloading or copying data to local devices.

The data will not leave England, at any time.

Access is restricted to individuals within the Botnar Research Centre, Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS) of the University of Oxford who have authorisation from the Principal Investigator. All such individuals are substantive employees of the University of Oxford.

All personnel accessing the data have been appropriately trained in data protection and confidentiality.

The data will not be linked with any other data.

There will be no requirement and no attempt to reidentify individuals when using the data.

Researchers from the University of Oxford will analyse the data for the purposes described above.

QResearch and Q-Covid (ODR1819_247) — DARS-NIC-656839-K5V9L

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: Yes (Academic)

Sensitive: Sensitive

When:DSA runs 2023-05 – 2024-05 2023.07 — 2023.09.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD, QUEEN MARY UNIVERSITY OF LONDON

Sublicensing allowed: Yes

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS National Radiotherapy Dataset (RTDS)
  3. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires access to NHS England National Disease Registration Service (NDRS) data for the following research projects:
Q-Research Linked Database and Q-Covid.

Q-RESEARCH:
The Q-Research project aims to develop and maintain a high-quality database of general practice-derived data linked to secondary care data for use in ethical medical research. The database is used for medical research into the causes of disease, history of treatment and outcomes. The Q-Research database (GP data only) is distinct from the linked asset (QResearch linked database).

Under the Public Health England Office of Data Release (PHE ODR), the Q-Research project was granted permission to onward share the NDRS Cancer Registry data with other UK Universities. The project team are now seeking additional permissions to use the Radio Therapy Dataset (RTDS) and Systemic Anti Cancer Dataset (SACT) data for Q-Research; and, onward share the RTDS and SACT data via the Q-Research database with other UK Universities.

The onward sharing of the data will be subject to the following restrictions:
• The University of Oxford is only permitted to onward share SACT and RTDS where there is a linked cancer registration record.
• The University of Oxford will only share data that can be linked to a GP record they have received from EMIS Health.

Q-COVID:
The Q-Covid project aims to continue to develop an evidence-based risk prediction model that estimates a person’s combined risk of catching coronavirus and being admitted to hospital, catching coronavirus and dying, and dying of coronavirus following a positive PCR test.

There are currently two-ongoing Q-Covid projects that require continued access to RTDS and SACT data, these are:
• Uptake and comparative safety of new COVID-19 therapeutics by age, sex, region, ethnicity, comorbidities, medication, deprivation, risk level and evidence of prior COVID infection. https://www.qresearch.org/research/approved-research-programs-and-projects/uptake-and-comparative-safety-of-new-covid-19-therapeutics/
• Development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population. https://www.qresearch.org/research/approved-research-programs-and-projects/development-and-evaluation-of-a-tool-for-predicting-risk-of-short-term-adverse-outcomes-due-to-covid-19-in-the-general-uk-population/
After these projects conclude NHS England would not expect any further Q-Covid projects to use NDRS data.

To support Q-Research and Q-Covid, Public Health England (PHE) Office for Data Release (ODR) previously disseminated NDRS Cancer Registry data (from January 1993 to December 2018), NDRS Radiotherapy Dataset (RTDS; from July 2018 to May 2020) previously for use in Q-Covid only and NDRS Systemic Anti-Cancer Therapy (SACT) data (from July 2018 to May 2020) previously for use in Q-Covid only.

The study team now requests to receive the latest available data for the NDRS Cancer Registry, RTDS and SACT, and to receive both SACT and RTDS records for cohort members dating back to 2010 onwards.

All data being disseminated is deemed to be pseudonymised.

The data requested will be minimised as follows:
- The NDRS Cancer Registry data is limited to 01/01/1995- 31/12/2020.
- The RTDS and SACT data is limited to 2010- 31/10/2022, only data that link to a NDRS Cancer Registry Record will be supplied
The study team have liaised extensively with the NDRS Production team to ensure that the data being requested and retained is limited to only those data items that are necessary to achieve the purpose outlined within this Data Sharing Agreement (DSA).

Under a separate Agreement (DARS-NIC-382794-T3L3M) NHS England provision Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES). This data will be linked to the NDRS data disseminated under this Agreement, and the GP data contained within the Q-Research database (received from EMIS Health).

The patient-level data linked to QResearch (QResearch linked database) is only accessed by either:
1. the University of Oxford for research projects approved by the University of Oxford QResearch Governance Approvals Route*. This access will be restricted to individuals substantively employed by the University of Oxford, students registered with the University of Oxford and individuals from other universities that have an honorary contract or secondment agreement with the University of Oxford.
2. other UK Universities for research projects that have been approved by the QResearch Governance Approvals Route. This will be supported by the sublicence data-sharing model.

The University of Oxford is the controller who has determined the purpose and means of processing the data being disseminated by NHS England. As the sole controller, the University of Oxford is responsible for ensuring that data will only be processed as described within this DSA.

The lawful basis for processing personal data under the UK General Data Protection Regulation (GDPR) is Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.

The lawful basis for processing special category data under the UK GDPR is Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Dancing House Consulting process the data disseminated under this Agreement under the direction of the University of Oxford.

Dancing House Consulting provide IT services to the University of Oxford, this includes backup services and database administration services. Dancing House Consulting supply support, but do not access data for any other reason. Therefore, any access to the data held under this agreement for any other reason would be considered a breach of the agreement.

The funding for this work comes from multiple sources. Current funders include but are not limited to:
- National Institute for Health Research (NIHR).
- Wellcome Trust
- Health Data Research UK (HDR UK)
- Cancer Research UK
- Blood cancer UK
- Pancreatic cancer UK
- Children with Cancer UK
Funding is ongoing and will continue to be obtained from several different sources.

* The University of Oxford QResearch Governance Approvals Route
Research undertaken using the data from the QResearch-linked database continues to be processed using the existing arrangements with respect to scientific review and the provision of annual reports to the Derby Research and Ethics Committee (DREC).

All research projects have to be peer-reviewed, original, hypothesis-driven or hypothesis tested and intended for publication in an academic peer-reviewed journal. All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.

Researchers are charged for the work in generating the outputs for research projects and a contribution to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch-linked data such as QCancer are published as free open-source software and also licensed for a fee as closed-source software from third parties such as Oxford University Innovations, for organisations unable to use the open source.

A summary of the QResearch Application Governance Process is detailed below:

1) Researchers originate a research question and write an outline protocol.
2) Pre-submission enquiry
3) IF feasible, cost estimate & letter of support
4) Researchers secure funding
5) A detailed data specification is produced
6) Co-produce a lay summary with Patient and Public Involvement (PPI) groups
7) Submit the Application
8) Review by Scientific Committee & feedback is given
9) Revisions if needed
10) Obtain approval
11) Timeline agreed for extraction
12) Approve within one month (with associated sublicence agreement in place before NHS England Data is released, if the application is not from the University of Oxford)

Requests are submitted and then reviewed at the monthly QResearch Science Committee. The minutes of the Science Committee is published here https://www.qresearch.org/about/scientific-committee/committee-minutes/

The committee advises the QResearch team on scientific issues relating to research applications, ensuring that each application has a clear research question or hypothesis which is likely to lead to generalisable findings capable of publication in a peer-reviewed medical journal. They advise if the research meets a minimum scientific standard and if not, amendments that will be required. They also assess the risks involved and will seek advice from QResearch Advisory Group if required. The committee ensures they follow the criteria and principles set out by the QResearch Advisory Board in assessing and advising on research applications where data is requested from the QResearch or QResearch-linked databases.

The Chief Investigator for QResearch is responsible for ensuring that data access is provided in accordance with the protocol, and ethics approval for the research database and following the advice of the advisory and scientific committees.

The researchers do not have access to the entire QResearch-linked database. Once an application has been approved (and a sub-licence agreement is in place), a subset of the pseudonymised record-level data (as approved for the study) will be extracted and stored on the University of Oxford servers (as described in more detail in section 5b Processing Activities) and researchers will be given a login to remotely access the specific extract via the University of Oxford servers to conduct their analysis. All remote access must take place within the UK. No record-level data can be downloaded by researchers as the IT system restricts this.

For further information on the application governance process please see the links to the QResearch website below.

QResearch Home Page: https://www.qresearch.org/
Scientific Committee – QResearch: https://www.qresearch.org/about/scientific-committee/
Approved Research Programs and Projects – QResearch: https://www.qresearch.org/research/research-programs-and-projects/
Data – QResearch: https://www.qresearch.org/data

The data are requested to link to the existing QResearch database to be used for medical research by academics employed by UK universities. QResearch is a not-for-profit collaboration between the University of Oxford and Egton Medical Information Systems (EMIS). QResearch is part of EMIS’ corporate social responsibility portfolio and provides GP data from contributing GP practices on a not-for-profit basis. EMIS are not involved with processing the NHS England or GP data at the University of Oxford.

Researchers are charged for generating the outputs from research projects and contributing to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch linked data such as QRISK2 are published as free open source software and also licensed for a fee as closed source software from organisations such as Oxford University Innovations and ClinRisk Ltd for organisations unable to use the open source.

The data will never be used for sales or marketing purposes.

The NHS England data will only be used for research and analyses where there is a clear benefit to health and social care in England and Wales in order for NHS England to be confident that Oxford meets the requirements under the Health and Social Care Act 2012 as amended by the Care Act 2014.

In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and (11) of the National Health Service Act 2006

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out

Yielded Benefits:

There have been many yielded benefits arising from work. The team have derived two key benefits from the Q Research work, two examples; HES and Mortality Linked data: Cancer prediction modelling The database was used to develop the QCancer – www.qcancer.org which assesses the risk that a patient may have a current undiagnosed cancer based on the patient’s risk factors and symptoms. The tool quantifies overall cancer risk and risk of individual cancers to help management decisions e.g. to refer the patient for an urgent 2-week wait or to organise more investigations or to reassure and review the patients as needed. the tools is embedded in GP systems and available for use in clinical consultations. Similar tools are being developed to help identify cancer among children and young people and to inform targeted screening programs among adults better. QResearch linked database was used to develop the NIHR-funded QCOVID tool https://digital.nhs.uk/coronavirus/risk-assessment/clinical-tool which identifies patients at risk of COVID-19 death and hospital admission. It is used to risk stratify the entire population to add patients to the shielded patient list and prioritise them for vaccination. It is also used as a clinical tool in consultation between patients and clinicians to personalise risk improve decision making and guide interventions including immunosuppressed patients with cancer and those receiving chemotherapy. In summary, the benefits yielded so far include the cancer work; Benefits for individuals – personalised risk estimates to improve decision making; prioritisation for referral, screening and other measures including workplace adjustments. Benefits for clinicians – more reliable objective information on cancer risks to support decision making; automated calculation to supplement decision making (avoids the need for every clinician to assess risk factors individually). Benefits for researchers- tools to stratify patients for clinical trial entry, which may help make trials run more efficiently and report more quickly, Benefits for policymakers – better evidence base to inform the development of policy (e.g. distribution of vaccination, prioritisation of novel therapeutics), ensuing equity (e.g adjusting risk by ethnicity to avoid widening health inequalities), the cost-effectiveness of the use of resources and appropriate defendable prioritisation; planning of services.

Expected Benefits:

The QResearch database is widely used by researchers to help understand patterns of disease, safety or medicines, development of prediction tools, research into health inequalities and other similar research questions where the results are likely to have benefits for patients, the NHS or to improve understanding of the disease. The research results continue to result in new knowledge and experience regarding disease epidemiology, health inequalities, drug safety, and methods of identifying patients at high risk of serious illnesses. Every year new research is published in high-impact international research journals such as the British Medical Journal and the British Journal of General Practice. The research is ongoing with target dates for individual projects rather than one overall target date.

A complete list of research papers using the QResearch database is published at http://www.qresearch.org/SitePages/publications.aspx

Research arising from the QResearch database including the linked data has been used to inform national policy. For example, research findings have been included in NICE guidelines on suspected cancer, fragility fracture, diabetes, and lipid modification. Research findings have informed the NHS Health Checks programme and Department of Health guidelines on health checks.

Examples of research include an assessment of the safety of COVID-19 vaccines among people with cancer; an investigation of potential links between diabetes drugs and cancer; quantification of the risk of breast cancer associated with various types of oral contraceptive pills and HRT.

Outputs:

The outputs are research papers which are published in peer reviewed academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by press releases from relevant organisations and highlighted on social media.

Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.

Examples of conferences include the annual academic conference for the Society of Academic Primary Care and the UK Research and Innovation (UKRI); international conferences such as the North American Primary Care Research Group; the annual conferences of the EMIS National User Group (a national education and research charity representing the GP practices which contribute data to QResearch); annual conferences run by cancer charities such as Macmillan Cancer Support and Pancreatic Cancer UK; local and regional conferences run by the Nottingham Biomedical Research Centre.

Results are also shared with policymakers, including the Chief Medical Officer's (CMO’s) office, the Medicines and Healthcare Products Agency (MHRA), Joint Committee on Vaccination and Immunisation (JCVI), the Department of Health and Social Care (DHSC), Scottish Office and National Institute for Health Care Excellence (NICE) guideline committees on a regular basis via their stakeholder consultations in order to support the development of relevant guidelines.

Outputs will only contain aggregate-level data with small numbers suppressed in line with the HES analysis guide.

No indicators are produced that show the performance of an organisation – indeed the identity of the GP practices contributing to QResearch is not shared with any third party.

Examples of research-related outputs:

The outputs include a risk prediction tool (QCovid) to identify those at high risk of severe outcomes from COVID-19 (including those with cancer and on cancer treatments) and multiple COVID-19-related research reports, research papers which are published in peer-reviewed academic scientific journals (for example, British Medical Journal (BMJ) and Lancet Journals) and presented at academic conferences (for example, Annual Scientific Meeting of the Society for Academic Primary Care (SAPC).

Other outputs include an analysis of the safety of COVID-19 vaccinations and of the uptake, safety and effectiveness of monoclonal antibodies among people with blood cancer.

All research is published in academic journals with a link from the QResearch website on an ongoing basis.

A list of all publications arising from the QResearch database https://www.qresearch.org/publications/research-papers/

Examples of research outputs:

Research funded by INNOVATE UK to develop a risk stratification tool to identify those at high risk of oesophageal cancer will likely lead to a more efficient way of identifying patients who might be eligible for the Cytosponge device (which is an alternative to endoscopy). This is especially important given the limitations on use of endoscopy arising from the COVID-19 pandemic (results expected 2023/4).

Another project funded by INNOVATE UK investigates the risks and benefits and health economic consequences of the pilot lung cancer screening program is expected to inform the development of the national screening program (results expected 2023/4).

Processing:

EMIS Health (commercial supplier of GP computer systems) process the GP data from the original data controllers (GP practices) and sends it to the University of Oxford. EMIS is not able to access or process any GP data once it is located at the University of Oxford.

EMIS Health is neither a data processor nor a data controller for the data provided by NHS England under this Agreement. EMIS Health is not able to access the NHS England data under any circumstances. GP practices (data controllers) have permitted the GP data it supplies to be linked with the data from NHS England for purposes determined by the Principal Investigator at the University of Oxford and described in this agreement.

No data will flow to NHS England for this Agreement.

Before providing data to the University of Oxford, NHS England will use the Open Pseudonymiser software (www.openpseudonymiser.org) to pseudonymise the NHS England data at source. NHS England will use a project-specific ‘salt’ key to ensure that the identifiers are specific to the University of Oxford. NHS England retains the salt key, meaning that the University of Oxford is unable to re-identify the data but can still link the data with the pseudonymised GP data. The University of Oxford will not hold or be given access to a copy of the pseudonymisation salt key.

NHS England will provide the University of Oxford with the relevant records and fields from the following NDRS datasets: Cancer Registration, SACT and RTDS datasets.

The data will contain no directly identifying data items. The data will be pseudonymised, and there will be no attempt or requirement to re-identify individuals by linking the records with other data already held by the University of Oxford.

NHS England provides pseudonymised data to the University of Oxford via Secure Electronic File Transfer (SEFT). The data will be linked to other data already contained within the QResearch database at the individual patient level using a pseudonymised version of the NHS number which has been supplied in both GP data and the NHS England data. The linkage will incorporate the following data, all of which are pseudonymised:
• The NDRS data disseminated under this Agreement
• The Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES) provisioned under DARS-NIC-382794-T3L3M
• Intensive Care National Audit & Research Centre (ICNARC) data
• Lung Cancer Screening Data

The University of Oxford uses offsite backup services provided by Dancing House Consulting.

The data will be accessed by authorised personnel via remote access. The data will always remain on the servers at the University of Oxford.

Researchers are prohibited from and not technically capable of downloading or copying data to local devices.

The data will not leave the UK at any time. All remote access must take place within the UK.

The QResearch database linked to NHS England data will only be accessed by a limited number of substantively employed, individuals within the QResearch unit. They will produce subsets of the data that will be accessed by the University of Oxford (with access restricted to individuals substantively employed by the University of Oxford, students registered with the University of Oxford and individuals from other universities that have an honorary contract or secondment agreement) or its sublicensee(s) as per the QResearch Application and Approvals process.

The subsets of data are then used for undertaking research as described in this agreement. These staff will process and analyse the subset of data to address an approved research question(s).

All personnel accessing the data have been appropriately trained in data protection and confidentiality.

There is no requirement to re-identify individuals from the data and no attempts will ever be made to do this.

Regular reviews will be undertaken to ensure that all appropriate controls are in place to minimise any risk of re-identification.

The University of Oxford conducts an annual internal audit for auditing the technical controls in place. The scope of the internal audit applies to the review of the QResearch Systems Level Security Policy and QResearch Workstation Setup Requirements.

Revision Hip and Knee Replacements: Evaluation of Clinical, Psychological and Surgical Outcomes — DARS-NIC-380650-K4F6X

Opt outs honoured: Yes, No (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(b)(ii); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05 – 2024-05 2022.05 — 2023.09.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care
  4. Patient Reported Outcome Measures (Linkable to HES)
  5. Civil Registrations of Death - Secondary Care Cut
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Expected Benefits:

It is hoped that the expected measurable benefits to health and or social care will be:
1. Patients potentially better informed to participate in the decision to undergo revision hip and knee replacement. Patients will hopefully be informed about the observed joint function, quality of life, short-term complications, longer-term outcomes and variations in care following revision joint replacement. It is hoped patients will be informed via social media engagement, public reports and patient engagement work as listed in the section above. The rationale for a broad, multifaceted engagement strategy is to reach as wide a patient audience as possible. Patients undergoing revision joint replacement are heterogenous and whilst many are avidly engaged with social media, many prefer more traditional engagement activities.

2. It is hoped that surgeons will be supported to change practice to deliver evidence-based surgery. Surgeons will hopefully be informed of the findings via journal publications, conference presentations, a DPhil thesis, and communication through social media and the British Orthopaedic Association (BOA). Target dates have been listed in the output strategy above. A broad engagement strategy has been chosen in order to reach as many surgeons and researchers practicing in this are from across the country. For example, the BOA is in regular communication with more than 5,000 members across the UK.

3. It is hoped that NHS commissioners will be supported to promote evidence-based surgery and appropriate resource allocation. There are approximately 13000 revision joint replacement procedures performed each year in the UK. The hypothesis for this work is that some types of procedures or procedures for certain groups of patients may be found to be of limited benefit and as such may be candidates for decommissioning. This may lead to cost savings, and may also mean that patients do not experience procedures with high risks of adverse events for limited or no benefit. This information will be available to care providers and commissioners via outputs 1/2/5 above.

4. It is hoped that there will be improvement in patient reported outcome measures (PROMs) following revision surgery. The NHS routinely collects data on the patient perspective following revision hip and knee replacement as part of the NHS PROMs programme. If this proposal is successful and changes are implemented into practice, then one might expect improvement in PROMs over time.

Outputs:

The specific outputs from the proposed work can be classified as:
1. Peer reviewed journal publications. This will include original articles on patient-reported outcomes, short term complications and longer term outcomes from revision hip and knee replacements. These publications will be Open Access. A first publication is target at 9 months from data receipt, with further publications at 6 monthly intervals.

2. Conference presentations: The proposed work will be presented at national and international conferences. This is to engage a broad spectrum of surgeons and allied health professionals who practice in or around revision joint replacement surgery across the UK. The British Association of Surgeons of the Knee (BASK) and British Orthopaedic Association (BOA) Annual Meetings in 2021 are targets for presentation of the proposed work.

3. Clinical practice guidelines. The University of Oxford study team work closely with BASK and the BOA and have been involved in recent work to produce British Orthopaedic Association Standards (BOASts) which are guidelines on the management of orthopaedic conditions. The evidence generated from the proposed work will be used to update the BOASTs for revision joint replacement. The target date for this is 2023.

4. Social media engagement with patients, surgeons, researchers and allied health professionals. The NDORMs Twitter account (@ndorms) will be used to announce study progress and results. This is intended to engage patients, surgeons and researchers with research outputs as they are produced.

5. Public reports: A project summary will be provided on the NDORMs study webpage. The proposed work will also produce a summary for the National Joint Registry Annual Report. This first summary is intended for the NJR 19th Annual report in 2022.

6. DPhil thesis. This is intended to be published Open Access in 2023 to provide information on outcomes following revision knee replacement. The DPhil student is funded by the Royal College of Surgeons (RCS). The RCS will have no access to the data and no role in its analysis or interpretation.

7. Patients engagement work: The University of Oxford has already started to involve patients and the public with this proposal and will continue this over the duration of the proposal. The Patient and Public Involvement Strategy for this proposal is as follows:
(i) Establishing key priorities for research on revision joint replacement.
See previous references to James Lind Alliance Priority Setting Partnership work.

(ii) Establishing patient views on data linkage without consent
This has been tested in 4 patients known to the research team (mix of men, women, different ages, from various parts of the country who have had a known problem with an implant after surgery). Patients were chosen as a convenience sample by the Nuffield Orthopaedic Centre, Oxford. 4/4 patients agreed that it would not be practical to contact all patients to obtain consent due to the size of the population. The feedback from all had a common theme: the potential benefits from new information on revision knee replacement meant that it was important for this research to be performed. They were satisfied that opt-out mechanisms were in place should patients wish to do so.

(iii) Establishing patient views on the programme of revision knee replacement research proposed
Telephone interviews have been performed with four patients to describe the proposed research programme. They provided very positive feedback. Some quotes were:
-“This will provide very useful information”
-“I think it can help others in the future, and it seems like a very good idea”
-“I have been through several operations on my knee and there isn’t much information out there for patients like me.”
-“I actually had very good information from Oxford when undergoing my revision knee replacement, and I really wish that information on revision knee replacement was rather better known around the country.”

(iv) Extended PPI work
The University of Oxford is recruiting a PPI group of 8-12 patients who are awaiting or have undergone revision knee replacement. The University of Oxford will explore with this group:
-What factors are important to patients in the decision to undergo revision knee replacement?
-How should outcomes following revision knee replacement be evaluated in a way that is meaningful to patients?
This group is currently being recruited.

(v) Revision arthroplasty study website
This is being set-up. Lay summaries of research will be available on this website.

(vi) Open days
These were held regularly, but are currently paused due to Covid-19, but will be reinstated in-person or virtually within the first year of the project.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

All organisations party to this agreement must comply with the data sharing framework contract requirements, including those regarding the use (and purposes of that use) by “personnel” (as defined within the data sharing framework contract i.e. employees, agents and contractors of the data recipient who may have access to that data).

STAGE 1
(Data Flow 1) On behalf of HQIP, Northgate Information Solutions will transfer the following identifying fields into NHS Digital from the National Joint Registry (NJR):
- NHS number
- Date of Birth
- Gender
- Postcode
- NJR unique identifier (which will be designated the Study ID)

The NJR unique identifier is provided for each eligible patient from the NJR for the purpose of linkage to NHS Digital held datasets.

NHS Digital will create the study cohort:
(i) NHS Digital will link the NJR cohort to HES using sensitive identifiers
(ii) NHS Digital will identify a cohort of patients with a hip or knee replacement (University of Oxford will send in the operation codes) from HES APC (1998/99 to 2019/20)
(iii) NHS Digital will identify all hip and knee replacement procedures on PROMs
(iv) NHS Digital will combine the cohorts from (i), (ii) and (iii), and extract:
-All HES APC episodes for these patients from 1998/99 to 2019/20
-Civil Registrations (Mortality) for these patients

(Data Flow 2) NHS Digital will transfer to the Big Health Data Group (BHDG) at University of Oxford, pseudonymised records of eligible individuals from HES APC, Civil Registration (deaths) and PROMS. The only pseudonym to be returned is the Study ID.

(Data Flow 3) Northgate Information Solutions will transfer to the Big Health Data Group (BHDG) at University of Oxford, pseudonymised records of eligible individuals from the NJR. These records will include:
- Study ID
- Age at surgery in years
- Gender.

(Data Flow 4) On receipt of the NJR/HQIP and NHS Digital data sets, the BHDG will be responsible for linking the two data sources. The resulting pseudonymised record-level data-set will be linked, stored and analysed within the BHDG's Data Security Protection Toolkit (DSPT) compliant environment.

STAGE 2
(Data Flow 5)
When the Master Person Service (MPS - an enhanced person-matching algorithm that increases the number of linkable records where incomplete records have been submitted.) is available for PROMs, NHS Digital will repeat linkage of the NJR to PROMs based on the sensitive identifiers provided in Data Flow 1 (which will have been retained). NHS Digital will supply the PROMS_SERIAL_NO (a unique ID in PROMS) and Study_ID to BHDG in University of Oxford as a separate linkage file.

The University of Oxford is requesting HES APC data for patients found in the NJR cohort AND patients with hip and knee joint replacements not found in the NJR cohort.

There will be no linkage to any publicly available data. There will be no attempt to re-identify individuals from this data-set, and results will be presented at aggregate level with small numbers suppressed in line with the HES Analysis Guide. The linked data set containing data from NHS Digital will not be accessed by the NJR/HQIP. Only substantive employees of the data controller will have access to the data under this agreement. These employees of the data controller have been appropriately trained in data protection and confidentiality. Within the University of Oxford Big Health Data Group, data is held in the Secure Computing Room, which is access controlled. Data are encrypted and stored in a safe. Data are accessed on non-networked computers.

DATA MINIMISATION:
>Datasets
1. NJR-HES-PROMs-Civil Registrations (Mortality) are requested. It is not possible to reduce the number of datasets because: (i) incomplete case ascertainment of NJR (ii) further granularity is required on patient comorbidities and complications (pre-existing and new) from HES and PROMs datasets (iii) data on mortality is required as a competing risk for implant (re)revision
2. The purpose can be achieved in a less intrusive way by using pseudonymised data.

>Years
3. The proposed study will investigate trends over time in modern arthroplasty practices. As such, data from 1998 is appropriate.

>Filtering
4. The proposed study will investigate geographic trends so geographic narrowing is inappropriate.
5. The proposed study will investigate the effect of patient demographics, so filtering is inappropriate - except data for those under 18 is not required.
6. The proposed study requests data on patients who have received a hip or knee joint replacement and requests filtering on this criterion (using OPCS codes supplied and linkage to the NJR dataset)

>Episodes
7. The study is investigating both the effect of pre-existing comorbidity on outcomes and the development of new comorbidity both in the short-term and long-term (up to 15 years). As such, episodes 5 years prior to joint replacement and all subsequent episodes are relevant.
8. Elective episodes are relevant as they may represent further surgery to the joint replacement or a new comorbidity
9. Maternity and neonatal episodes are not required and have not been requested.
10. Timeframe - Data from 1998 is requested to appropriately investigate trends overtime in modern arthroplasty practices.

Fields
11. Fields have been selected to provide predictors and outcomes of interest. This includes ETHNOS as ethnicity may be a predictor of outcome.
12. Full date of death has not been requested, but month/year has been requested instead to prevent intrusion

Cohorts
13/14. Linkage to NJR cohort is requested AND/OR matching with a pre-specified list of hip and knee replacement OPCS codes

There will be no data linkage undertaken with NHS digital data provided under this agreement that is not already noted in the agreement.

Project to Help Improve Decision Aids for Predicting Outcomes in Early Breast Cancer: (ODR1718_390) — DARS-NIC-656818-N1B5Q

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2023-07 – 2026-06 2023.08 — 2023.08.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Pathway
  2. NDRS Cancer Registrations
  3. NDRS Linked Cancer Waiting Times (Treatments only)
  4. NDRS Linked DIDs
  5. NDRS Linked HES AE
  6. NDRS Linked HES APC
  7. NDRS Linked HES Outpatient
  8. NDRS National Radiotherapy Dataset (RTDS)
  9. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires access to NHS England data for the purpose of the following research programme: Project to Help Improve Decision Aids for Predicting Outcomes in Early Breast Cancer.

Female invasive breast cancer is the commonest cancer in England, with over 40,000 new cases diagnosed and nearly 10,000 deaths each year. Invasive breast cancer is a long drawn out disease, and the risk of recurrence or death from breast cancer continues for at least 20 years after diagnosis. Most patients have early stage disease and receive surgery as their first treatment. Outcomes following treatment for early invasive breast cancer differ substantially across different countries and across different patient characteristics within a country. Patients diagnosed with breast cancer and the clinicians who treat them need estimates of their likely prognosis to inform treatment decisions, follow-up, and prediction of event rates for groups of patients in clinical trials. They also need estimates of the risks of diseases other than breast cancer. These estimates require large-scale, population-based studies that consider the effects of multiple patient and tumour factors on the risks of recurrence of breast cancer, of death from breast cancer and of the incidence and mortality of other diseases. It is known that survival from breast cancer has improved and that incidence and mortality of other diseases has changed. However, detailed estimates based on patients treated recently are not currently available. These estimates are needed to enable clinicians to estimate prognosis for patients treated today using characteristics such as age, tumour size, nodal status, grade, receptor status and screening status.

The objectives of this project are as follows:

1. To describe the incidence of second cancers among women diagnosed with breast cancer according to the characteristics of both patients and their tumours, and to assess the extent to which this has changed with calendar year of diagnosis and how it varies with time since diagnosis.

2. To describe patterns of breast cancer mortality and of mortality from other causes according to the characteristics of both patients and their tumours, and to assess the extent to which this mortality has changed with calendar year of diagnosis and how it varies with time since diagnosis.

3. To describe the incidence of other diseases among women diagnosed with breast cancer according to the characteristics of both patients and their tumours, and to assess the extent to which this mortality has changed with calendar year of diagnosis and how it varies with time since diagnosis.

4. To provide predictions of the absolute magnitude of the likely benefits and risks of the various treatment options available for patients diagnosed recently, making them relevant to patients diagnosed today.

5. To provide estimate of the risk of developing a recurrence of breast cancer from routinely collected data, using methods derived in a separate project (ODR1718_364) which is being carried out in conjunction with NDRS staff.

To achieve objective 1 The University of Oxford would like to receive updated versions of two files previously disseminated under Public Health England (PHE). These involve providing data on cancer registrations up to the end of 2020 for patients already in the study. In addition, The University of Oxford received information on the potential prognostic factor Ki67.

To achieve objectives 2-5 The University of Oxford would like to receive the information summarised below and additionally, would like to receive information on the prognostic factor Ki67. This information will be supplied using new pseudo_ids. However, The University of Oxford would like to receive a file linking the old pseudo_ids with the new pseudo_ids for those patients who are in the existing cohort. It is important for the fulfilment of objectives 2-5 that The university of Oxford receive information on patients diagnosed since 2017. As recently shown (BMJ2023;381:e074684), the breast cancer mortality rate increases rapidly during the first two years after initial diagnosis and reaches a peak during the third year. The study team have also shown that mortality rates at any given time after diagnosis have been changing rapidly in recent years. Therefore additional patients diagnosed since 2017 is required in order to be able to provide estimates that are relevant for patients who are being diagnosed now. The study team also need information on patients diagnosed recently to estimate the risk of developing a recurrence, partly in order to provide up-to-date estimates but also in order to make use of recent developments in data capture and storage by NDRS.

To achieve objectives 2-5, the following NHS England data will be accessed:

• National Disease Registration Service (NDRS) Cancer Registration
• National Disease Registration Service (NDRS) Hospital Episode Statistics
- Admitted Patient Care
- Outpatients
- Accident & Emergency
• National Disease Registration Service (NDRS) National Radiotherapy (RTDS)
• National Disease Registration Service (NDRS) Systemic Anti Cancer (SACT)
• National Disease Registration Service (NDRS) Cancer Wait Times (CWT)
• National Disease Registration Service (NDRS) Diagnostic Imaging Dataset (DIDs)
• National Disease Registration Service (NDRS) Cancer Pathway (CWT)

The quantum of Data requested is necessary to achieve the objectives of this project.

The level of the data will be Pseudonymised and will be minimised as follows

• Limited to data for a study cohort identified by NHS England
• Limited to data between 1 Jan 1971 – latest available
• Limited to conditions relevant to the study identified by specific ICD codes for invasive breast cancer ICD10:
C50x, ICD9: 174X, ICD8: 174X;
• Limited to the following geographic areas [England]
• Women only

The University of Oxford is the research sponsor and the data controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above. Additionally, the study team have taken all steps necessary to ensure that they have all the appropriate institutional ethical support in place from University of Oxford.

The University of Oxford rely on Article 6(1)(e) - the processing is necessary for you to perform a task in the public interest or for your official functions, and the task or function has a clear basis in law. The public interest in this circumstance is research to increase medical knowledge for the benefit of all and to improve public health.

The University of Oxford rely on Article 9(2)(j) - processing is necessary for archiving purposes in public interest, scientific or historical research purposes. The legitimate need for processing special category data under 9(2)(j) is that it adheres to the UK Policy Framework for Health and Social Care Research and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care".

The funding is provided by The University of Oxford and Cancer Research UK via a Programme Grant. Funding is in place until 2027. Cancer Research UK will have no ability to suppress or otherwise limit the publication of findings of this research.

The University of Oxford is the sole data controller and sole data processor.

There are no other organisation(s) involved or accessing the NHS England data, including organisations acting in an advisory capacity or as part of an oversight or steering committee.

Before starting the project, the opinions of oncologists, surgeons, breast cancer groups (e.g. the National Cancer Research Institute Breast Clinical Studies Group and the National Cancer Intelligence Network Breast Site Specific Clinical Reference Group) and consumer representatives (Independent Cancer Patients Voices) were sought in an advisory capacity using questionnaires and at meetings to help inform the objectives of the work.

In line with the National data opt-out policy, opt-outs are not applied because the data is not Confidential Patient Information as defined in section 251(10) and (11) of the National Health Service Act 2006

Where individuals have opted out of disease registration by the National Disease Registration Service (NDRS), their data has been permanently removed from the registry and therefore will not be disseminated under this Data Sharing Agreement (DSA). https://digital.nhs.uk/ndrs/patients/opting-out

Yielded Benefits:

Data for this study has previously been shared when the data were controlled and managed by Public Health England (PHE). As such there are some yielded benefits to be observed from the access to the data for the study prior to NHS England becoming data controller. These yielded benefits are noted below: The manuscripts cited in the outputs have proved helpful in planning resources needed for radiotherapy and are hoped will influence clinical practice and guidelines. This research work has already changed clinical practice. In breast cancer where The University of Oxford have provided clinicians with information on the benefits and risks of various treatment options. This allows them to make informed choices about which treatments to recommend to individual patients. Studies derived from this research have been primary references in each of the major international guidelines for the management of breast cancer including those produced by the National Institute for Health and Care Excellence (NICE)1,2 the Scottish Intercollegiate Guidelines Network (SIGN),32 the UK’s Royal College of Radiologists (RCR),4 the American National Comprehensive Cancer Network (NCCN),5 the Japan Breast Cancer Society,6 and the joint American Society of Clinical Oncology/American Society for Radiation Oncology/Society for Surgical Oncology (ASCO/ASTRO/SSO).7 The results of this research are essential in treatment decisions, so they are used in training oncologists and related health care professionals. For example, results have been presented annually at the European Society of Therapeutic Radiation Oncology teaching course since 2009 and at the 4-yearly National Cancer Institute Radiation Epidemiology Dosimetry course. References: 1: Early and locally advanced breast cancer: diagnosis and management. [I] Evidence reviews for postmastectomy Radiotherapy. NICE guideline NG101, Evidence reviews. July 2018; https://www.nice.org.uk/guidance/ng101/evidence/evidence-review-i-postmastectomy-radiotherapy-pdf-176567997780 2: Early and locally advanced breast cancer: diagnosis and management. [H] Evidence reviews for breast radiotherapy. NICE guideline NG101, Evidence reviews. July 2018; https://www.nice.org.uk/guidance/ng101/evidence/evidence-review-h-breast-radiotherapy-pdf-4904666613 3: SIGN 134. Treatment of primary breast cancer. A national clinical guideline. September 2013; https://www.sign.ac.uk/assets/sign134.pdf 4: Postoperative radiotherapy for breast cancer: UK consensus statements. November 2016; https://www.rcr.ac.uk/system/files/publication/field_publication_files/bfco2016_breast-consensus-guidelines.pdf 5: National Comprehensive Cancer Network Clinical Practice Guideline in Oncology: Breast cancer Version 5.2020. https://www2.tri-kobe.org/nccn/guideline/breast/english/breast.pdf 6: Komoike Y, Inokuchi M, Toshikazu T, Kaouru K, Goro K, Takehiko S, Hiromitsu J, Noriaki W, Shozo O, Hirofumi M. Japan Breast Cancer Society clinical practice guideline for surgical treatment of breast cancer. Breast Cancer 2015; 22(1): 37-48. 7: Recht A, Comen EA, Fine RE, Fleming GF, Hardenbergh PH, Ho AY, Hudis CA, Hwang ES, Kirshner JJ, Morrow M, Saleron KE, Sledge Jr GW, Solin LJ, Spears PA, Whelan TJ, Somerfield MR, Edge SB. Postmastectomy Radiotherapy: An American Society of Clinical Oncology, American Society for Radiation Oncology, and Society of Surgical Oncology Focused Guideline Update. Practical Radiation Oncology 2016; 6(6): e219-34

Expected Benefits:

The findings of this project are hoped to provide high quality information to enable patients and clinicians to make informed decisions in the treatment of breast cancer based on the individual characteristics of the patient. For many patients, several different treatment options are available and selecting the best one can be challenging. The results of this project will make this selection easier and can be expected to improve outcomes for breast cancer patients.

The results of the project will also provide baseline figures against which national audits can be compared to assess how widely evidence from recent guidelines has been implemented. These can be used in several ways, including estimation of the number of women needed in randomised trials and to inform radiotherapy resource allocation.

The expected benefit to patients as an outcome subject to the findings is that patients will be better informed of the likely benefits and risks of the various treatment options available to them, taking account of their individual characteristics.

The proposed outputs will be published in peer-reviewed journals. They will also be presented at appropriate conferences focussing on breast cancer and its consequences. The findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

Clinicians will be made aware of the findings through publications in peer-reviewed journals. The University of Oxford are also liaising with groups of patient representatives, such as Independent Cancer Patients’ Voice. The University of Oxford also inform CRUK of the results of our work and, where appropriate, they will issue press releases.

Outputs:

The expected outputs of the processing will be:

• A series of peer-reviewed publications reporting the analyses of the data from the NDRS on outcomes in breast cancer patients, and on the development and validation of the prediction models. These are listed below with their current target dates:

• The first publication appeared in the journal Clinical Oncology in 2020 that provided estimates of the proportion of women receiving adjuvant breast cancer radiotherapy who would be eligible for partial breast radiotherapy according to both the NICE guidelines and the Royal College of Radiologists Consensus Statement. A second publication has been accepted by the British Medical Journal (BMJ) and will be published in June 2023.

A paper describing a population based observational cohort study of breast cancer mortality in 500,000 women diagnosed with early invasive breast cancer in England, 1993-2015 has been accepted for publication in the British Medical Journal (BMJ). These findings:
- A manuscript describing the ability of Ki67 (a marker of cell proliferation which is available from routinely collected pathology reports) to improve prediction of mortality from breast cancer has been prepared and will be submitted for publication shortly. It is expected that this will be completed early in 2024.

• An analysis of the incidence of and mortality from other cancers in women diagnosed with breast cancer. It is expected that this will be completed in 2024

• An analysis of mortality from non-cancer diseases in women diagnosed with breast cancer. It is expected that this will be completed in 2024.

• An analysis of the incidence of non-cancer diseases in women diagnosed with breast cancer. It is expected that this will be completed in 2024.

• Finally, when the algorithm to identify recurrences in women with early breast cancer is ready, analyses of patterns of recurrence in women diagnosed with early breast cancer will be prepared and submitted to peer-reviewed journals. It is expected that this will be completed in 2025.

In addition to the above:

• Presentations will be made at conferences relating to breast cancer and other meetings to publicise the work.

• Periodic updates will be published to incorporate additional follow-up on women already diagnosed with breast cancer, information on women recently diagnosed with breast cancer, and appropriate improvements to the model.

The outputs will not contain NHS England data and will contain only aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Social media (e.g. press releases)
• Public reports (all journal publications are accessible by the public)
• Briefing documents provided to clinicians [details to be decided]
• Open source frameworks [it is planned that, when all are satisfied with its performance, the source code for identifying recurrences will be available within NCRAS for use by NCRAS staff and other researchers]
• Oral presentations and poster displays at conferences
• Patient Information leaflets [results will form the basis of revised patient information leaflets]
• Press/media engagement
• Public promotion of the research [e.g. via press/media engagement]

Processing:

No data will flow to NHS England for the purposes of this Agreement.

NHS England will provide the relevant records from the NDRS HES A&E, HES IP, HES OP, CANCER Registry, SACT, CWT, RTDS and DIDS datasets to University of Oxford.

All data linkage will be undertaken by NHS England, before data are transferred to researchers at The University of Oxford.

The data will remain on the servers at University of Oxford at all times. The data will not be transferred to any other location and will not leave England/Wales at any time.

The University of Oxford provides IT support and all IT hosting services.

Data will be stored within Nuffield Department of Population Health (NDPH) in Oxford University. Electronic data files are kept on password-protected network servers behind a local firewall. Servers are kept in a locked room with access restricted to IT staff.

Access to electronic data is restricted via user identification. Backups are held on private internal servers spread over three locations within the Old Road Campus of the University of Oxford. Backed up data is encrypted both in transit and at rest. Access to data is restricted via user identification. No data are moved or copied from these servers.

The IT department have setup a special permissions compliant folder to receive and hold data securely. The PI of the study team controls who can access this folder and the list is reviewed every 6 months. Data are not copied but can be accessed by analysis programs. Receipt of data is recorded in an asset register within NDPH. When data are to be deleted a request is made to the NDPH IT department who provide a deletion certificate which the study team enter into the asset register (any backups resulting from the 28-day back-up cycle are also deleted).

Analysts and researchers from the Nuffield Department of Population Health at The University of Oxford will analyse the data for the purposes described above and there will be no requirement and no attempt to reidentify individuals when using the data in Oxford.

Data processing and access will be carried out by substantive employees of the data processor/controller (University of Oxford) who have authorisation from the PI and who have been appropriately trained in data protection and confidentiality.

Whereby during the term of this agreement processing is required to be carried out by students affiliated with the University of Oxford (to potentially form part of studies ie: a DPhil degree) The University of Oxford, will only do so if beneficial to the research. Whereby during the term of this agreement processing is required to be carried out by individuals with honorary contracts (to help introduce increased level of clinical expertise), The University of Oxford will only do so if beneficial to the research to help achieve the study objectives.

The University of Oxford will ensure the correct supervisory and contractual requirements for the individuals are in place and The University of Oxfords organisational governance policies and controls are adhered to.

The data will be accessed by authorised personnel via remote access. Personnel are prohibited from downloading or copying data to local devices.

No other organisation is permitted to access the data including the funder Cancer Research UK. The funder Cancer Research UK will not have influence on the outcomes nor suppress any of the findings of the research.

Outcomes of Patients who survived Treatment on an Intensive Care unit for COVID-19 in England and Wales (OPTIC-19): a comparative retrospective cohort study — DARS-NIC-419335-H5P8T

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-09 – 2023-09 2021.11 — 2023.08.

Access method: One-Off

Data-controller type: INTENSIVE CARE NATIONAL AUDIT & RESEARCH CENTRE (ICNARC), UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Emergency Care Data Set (ECDS)
  3. GPES Data for Pandemic Planning and Research (COVID-19)
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Hospital Episode Statistics Outpatients
  7. MSDS (Maternity Services Data Set)
  8. MSDS (Maternity Services Data Set) v1.5
  9. Civil Registrations of Death
  10. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  11. Hospital Episode Statistics Accident and Emergency (HES A and E)
  12. Hospital Episode Statistics Admitted Patient Care (HES APC)
  13. Hospital Episode Statistics Outpatients (HES OP)
  14. Maternity Services Data Set (MSDS) v1.5

Type of data: Anonymised - ICO Code Compliant

Expected Benefits:

Through addressing questions about the impacts of severe COVID-19 on subsequent adverse events among survivors, the outputs of this work hope to inform:
- Clinicians regarding the ongoing/future risks to their patients
- Patients now and in the future of their short, medium and long-term risks.
- The wider health care community and health services that are tailored to the treatment of patients during and after ICU. These organisations are hope to include the ICUsteps charity and Oxford Critical Care Forum.

This work hopes to identify potentially modifiable risk factors that may lead to identification and treatment of patients who have survived treatment for COVID-19 on the ICU. Ultimately the benefit will depend on which risk factors are identified and the degree to which they can be modified in clinical practice. For example, if survivors of severe COVID-19 have an excess risk of cardiovascular disease, these patients might benefit from statin therapy even if identified as low risk by current primary care guidelines (e.g. as predicted by QRISK-2).

ICNARC is one of few organisations internationally who collate detailed data on intensive care patients at scale. For this reason, the study team expect their study to be one of the largest to inform the follow-up care of patients who have survived severe COVID-19.

Through publication of several scientific papers and presentations at scientific meetings on the topic the study team hope to raise the understanding of the scale of the risks faced by patients following ICU. This work should lead to further funded work that result in prevention and treatment options.

Outputs:

This study aims to publish at least two journal articles describing the risk faced by survivors of COVID-19 treated on an ICU. The first article aims to report six month outcomes (target date: 1st October 2021) and the second aims to include one year outcomes (target date: 1st December 2021).

The study team will be responsible for publishing outputs in high-impact open access peer-reviewed journals, such as the British Medical Journal, Intensive Care Medicine and the Lancet. All outputs will be aggregated with small number suppression applied as per the HES analysis guide. All published output aim to be accompanied by a corresponding press releases including lay summaries of the findings and its applicability to patients. When major findings are published, the Departmental press office aims to assist with press releases, social media messages and interviews.

The study hopes to also be promoted through the CCRG Twitter handle (@KadoorieCentre), which has over 1000 followers comprising of patients and health care professionals. Findings hope to be be presented at national and international conferences to experts in the field – for example, the UK Intensive Care Society State-of-the-Art annual conference and one of the European Society of Intensive Care Medicine’s bi-annual conferences.

The study team aim to present their results to relevant patient groups and their families via the ICU charity “ICUsteps” (https://www.icusteps.org/). They hope to also discuss their progress with the Oxford ICU patient forum, whose members include former ICU patients and their relatives. The study team hope to specifically seek the advice of both groups on how best to present the study results to the wider public. The study team developed a patient notification strategy with input from the Oxford Research Ethics Committee (REC) and members of the Oxford ICU Forum (a group of previous ICU patients, families, and lay members). The study will fully implement the National Data Opt-out and will therefore exclude any records related to patients who have notified the NHS of their wish for their data not to be used in research.

For a previous study, the study team were advised by the ethics committee that placing posters in the relative rooms or waiting areas of the participating ICUs to notify patients of the study, “was not practical and should not therefore be used”. All members of the Patient and Public Involvement (PPI) panel agreed with the ethics committee that displaying posters would not be appropriate. However, the PPI group advised that information should be available on a study website. The group advised that the website summary should be brief and accessible, with links to the detail (such as formal privacy policy) available. Members of the previous study PPI group were also consulted for this study (OPTIC-19) and were very clear in their support.

The aim is to achieve these outputs within the 15 month study period.

The study website (https://www.ndcn.ox.ac.uk/research/critical-care-research-group-kadoorie-centre/research-studies/six-month-outcomes-after-surviving-treatment-for-covid-19-disease-on-an-intensive-care-unit-in-england-optic-19) will be updated with all the details of the above.

The study team aim to engage with senior critical care clinicians in Oxford and Thames Valley should the results suggest how clinical follow-up of patients treated for COVID-19 on the Intensive Care Unit (ICU) might be improved.

Processing:

The Data Flow for this agreement will consist of the below:
a. ICNARC will identify the study cohort and allocate participants a unique study ID.
b. Identifiers (NHS Number, Date of Birth, Gender and Post Code) and the unique study ID will be submitted by ICNARC to NHS Digital using their secure electronic file transfer (SEFT) system.
c. NHS Digital will link to record-level HES, MSDS, GDPPR and Civil Registrations using the patient identifiers provided.
d. NHS Digital will then remove identifiers to pseudonymise the extracts.
e. NHS Digital will send the pseudonymised record-level extracts of the above-mentioned data products for the duration of the study via SEFT to the Critical Care Research Group at the University of Oxford.

The pseudonymised data from NHS Digital (HES/MSDS/GDPPR/Civil Registration data) will be linked by The Critical Care Research Group at the University of Oxford to health data and National audits from NHS Wales Informatics Service (NWIS), Barts' health NHS Trust (on behalf of the National Institute for Cardiovascular Outcomes Research (NICOR), Kings College London (on behalf of the Sentinel Stroke National Audit Programme (SSNAP), and the UK Renal Association (UKRR) and then subject to a process of data cleaning and data quality assessment. The study will also link data from the UK Obstetric Surveillance System (UKOSS) to identify patients who were pregnant at the time of ICU admission.

The resulting pseudonymised dataset will then be used for statistical analysis in keeping with a pre-defined statistical analysis plan.

No data will be matched to publicly available data and there will be no requirement/attempt to re-identify individuals.

As ICNARC is responsible for and runs the CMP program, ICNARC will always hold a copy of both the source data (the CMP program) and the study specific pseudo-anonymous data (for analysis purposes). Due to pre-existing privacy commitments if a patient contacted ICNARC and requested their data was removed from the data set then they would be obliged to do so. During the period the study is running, patients who raise requests to have their data removed from the study with either ICNARC or the CCRG will be identified by their ICNARC ID (by ICNARC) and their data removed from the study database by the CCRG/ICNARC. After the study period ends, the study team will destroy the ledger linking the ICNARC CMP ID to the OPTIC-19 Study ID making it impossible to directly link the study dataset to the individual. In terms of the study itself, all analysis will be performed on the anonymous dataset and there is no intention or requirement to re-identify the data at a later stage.

Both ICNARC and Oxford are collaborators on this project and run separate specialist analysis platforms and expertise within the groups (hence the co-data controller relationship). As result we will require the work to be performed by both teams in both environments. All data processing at the Critical Care Research Group at the University of Oxford and ICNARC will take place using secure systems. The data will not leave these systems at any time. All data held within these environments are owned and run solely by the respective data controllers/processors/data guardians.

The final pseudonymised study data will be stored securely within the CCRG Data Safe Haven and ICNARC servers for a minimum of five years after the end of the study, in keeping with the MRC Retention Framework for Research Data and Records.

Data processing is only carried out by substantive employees of the University Of Oxford and ICNARC who have been appropriately trained in data protection and confidentiality.

All data processing within the Critical Care Research Group at the University of Oxford takes place within a secure system which is designed in keeping with the principles of NHS Digital Security Assurance requirements. The data does not leave the system at any time and users connect via a remote desktop connection to a protected analysis environment that runs within the system - all connections are via encrypted tunnels into the system. The remote desktop connection prevents uses from transferring files or copying data in either direction. No data is copied or transferred to the remote device/client machine. Access to the environment is protected by two firewalls, departmental Virtual Private Network (VPN) and requires strong key based login.

The system is located in a locked, access-controlled server room within the CCRG research offices. All remote machines are university owned, standard build computers that conform to Cyber Essentials Plus accreditation and are compliant with the NHS Digital Data Security and Protection Toolkit (DSPT).

The study data set will never be released from this environment and it will be deleted at the end of its retention period.

Members of the study team, both in Oxford and at ICNARC, will undertaking statistical analysis of the study data set. For this reason, a copy of the pseudonymous data set will also be held at ICNARC (conforming with NHS DSP). Data will be stored on secure servers at ICNARC (office in London) or servers which are owned by an authorised contractor called Exponential-e (https://www.exponential-e.com/). Exponential-E are a contractor authorised by ICNARC and provide protection with a leading anti-virus protection. The anti-virus protection that is provided to ICNARC's servers provides protection against all currently known malware whereby is being updated on a daily basis with over 400,000 variations of updates per day. In addition to this signature based protection the level ICNARC also has advanced signatureless protection. This protects against the latest attacks more commonly known as “zero day” . These attacks are seen more with ransomware attacks and will detect an attack in progress, stop it in its tracks and then clean any effected server. The console then provides a function of reporting for analysis to review. Exponential-e are compliant with ISO 9001; ISO 27001; ISO 14001; ISO 22301; ISO 50001; ISO 20000 and also hold a Health & Social Care Network Complaint certificate of compliance. Employees of Exponential-E will not access the data, but will provide storage/back-up, and as such, are listed as processors.

Identifiable data held in the Case Mix Programme will be kept separate to the pseudonymised dataset for analysis. No attempt to reidentify participants will be made.

The data will be accessed from a networked PC via a Local Area Network. Firewalls are in place to prevent unauthorised remote access. Access to the networked PC is via username and password. All data analysis will be conducted within the confines of the ICNARC secure server, and will not be downloaded to remote devices for storage or processing. Only authorised members of staff working on the study will access the data. The CCRG will confirm that this data set is deleted at the end of the same study retention period.

EVAREST/BSE-NSTEP Study Cohort to gather follow up data — DARS-NIC-620484-W0B2K

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2023-05 – 2026-05 2023.07 — 2023.07.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death
  2. Diagnostic Imaging Data Set (DID)
  3. Emergency Care Data Set (ECDS)
  4. Hospital Episode Statistics Admitted Patient Care (HES APC)
  5. Hospital Episode Statistics Critical Care (HES Critical Care)
  6. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford are requesting NHS England pseudonymised record level data for the Study: Echocardiography: Value and Accuracy at REst and STress “EVAREST”

BACKGROUND:
Stress echocardiography is a commonly used test to assess for heart disease. It is performed routinely across the country in many different ways. The University of Oxford are examining how stress echocardiography is used in the diagnosis of heart disease, whether there are differences in how the test is performed between hospitals and how the results of the stress echocardiogram guides patients’ care. The EVAREST study should allow University of Oxford to gather information about how this test was performed and how it has helped doctors give patients the most appropriate care. University of Oxford will also examine how stress echocardiography is performed across the country.

STUDY AIMS
The primary objective of this study is to characterise the change in extracellular MVs and associated blood biomarkers during standardised stress echocardiogram protocols and understand the relevance of this change as a predictive marker of coronary disease. However, the request for data in this agreement relates to part of the secondary objectives of the study, namely to investigate the use of stress echocardiography as a clinical procedure in the UK (Group 1-3).

Identifying the long-term outcome data from these patients post functional imaging, is an integral piece of this research project. This analysis will look to assess performance and accuracy of stress echocardiography practice in the UK, which will also include an analysis on the costs associated with the long-term patient care pathway of those who have received a stress echocardiogram.

ORGANISATIONS AND RESPONSIBILITIES
The University of Oxford will be the sole data controller for this agreement and will also be processing the data. The study team are based within the Cardiovascular Clinical Research Facility (CCRF) within the University of Oxford. The sole sponsor and funder for the data analysis section of this project is the University of Oxford.

The British Society of Echocardiography act as an advisory board for the purposes of the study, but are not the sponsor of the study, nor do they decide the purpose and means of processing the data, and do not/will not have access to record-level data from NHS England. The University of Oxford have reviewed ICO requirements / definition of a Data Controller and are satisfied that the British Society of Echocardiography are not a data controller.

In the past, the study has variously been funded by an National Institute for Health and Care Research (NIHR) - Health Education England (HEE) Healthcare Science Research Fellowship, Ultromics Ltd and Lantheus Medical Imaging Inc but these organisations are no longer involved with the study and will have no access to record level NHS England data. The University of Oxford have reviewed ICO requirements / definition of a Data Controller and are satisfied that these organisaitons are not a data controller.

DATA REQUESTED
The University of Oxford are requesting access to the following record level pseudonymised NHS England datasets from the period 2018/19 to latest available data:

- Hospital Episode Statistics (HES) HES Admitted Patient Care (APC)
- HES Outpatients (OP)
- HES Critical Care (CC)
- Emergency Care Dataset (ECDS)
- Diagnostic Imaging Dataset (DIDS)
- Civil Registration (Deaths) Data

The data requested will create a clinical picture of the immediate and subsequent cardiac history for each patient enrolled in the study. This data will be aligned with the initial clinical reasoning and interpretation of cardiac disease/risk to help identify the initial success of the functional testing (stress echocardiography).

The overarching EVAREST project seeks to investigate the accuracy and feasibility of stress echocardiography as a functional imaging modality for cardiology. This requires primarily a large cohort (there are multiple methods of performing stress echocardiography) and a substantial follow-up period in which it is possible to identify any patterns of disease or trends with associated outcomes/risk factors. These will ultimately help improve the accuracy of the test when being performed if it highlights the needs for alterative testing methods, or greater weighting on certain risk factors or demographics.

In order to ascertain the immediate, short term and long-term outcomes in patients having undergone stress echocardiography, this study requires a detailed and long-term follow-up plan. This includes acquiring data surrounding potential cardiac pathways post stress echocardiography, death, admission to Emergency Department (ED) for chest pain and any cardiac imaging or diagnostic testing that may have been undertaken and subsequently altered a patient’s treatment pathway.

This will ensure that this study can build a cardiac history for each participant, and compare this to their initial presentation, the immediate results of the stress echocardiography and the subsequent intervention strategies should this be implemented.

With regards to the acquisition of this data, whilst some could be obtained from the individual patient notes, it is likely that patients will have moved across Trust boundaries, be seen at different NHS hospitals for acute admissions etc during the lengthy follow-up period, and as a result, NHS England is content that the request is the most appropriate and least intrusive method for obtaining the high-quality data required to make these informed observations.

The study team have worked to minimise the data that is requested so that only data requested relating to cardiac investigations/events, in addition to death data. The disease in investigation is common and will help to minimise risk with patient identification. A pseudonymised study ID is used by the University of Oxford, so that once the data is linked and extracted, the study team can analyse the data meaningfully using only a Study ID.

COHORT
This EVAREST programme of work started in 2014 and seeks to obtain 10-year follow-up data on all participants who have consented to follow-up data from NHS England. This study is still actively recruiting.

Study Participants were added to three groups. Groups 1 and 2 collectively (Phase 1 of the study) consists of 8,000 participants referred for stress echocardiogram by their clinical consultant in order to establish likelihood of coronary artery disease (CAD). Recruitment started in early 2015 and completed in March 2020.
Group 3 (Phase 2 of the study) consists of up to 15,000 participants referred for stress echocardiogram for the investigation of any disease. This includes, but is not limited to, stress echocardiography to assess ischaemia, valvular function, left ventricular outflow tract obstruction, diastology*, myocardial perfusion and tissue viability.

*diastology - The scientific study of the heart muscle when it is not contracting but is in diastole (at rest)

The cohort provided to NHS England will be approximately 6,000 individuals from the above 3 groups. 3,000 from phase 1 and 3,000 from phase 2.

The cohort consists of patients over the age of 18, eligible for recruitment having undergone stress echocardiography at one of the designated recruitment centres.

If a participant requests to withdraw from the study, this will be notated within the Castor eDC system used as part of the study. There is a specific withdrawal Case Report Form (CRF) that will be used for these requests. The participant will have an opportunity to provide a reason for their withdrawal if they so choose. The study team will also ask the participant if the study has permission to keep data after the withdrawal. If the participant does not consent to this, then the database will alert the study team member to delete all data from within the eDC that has been collected to date for that participant with the exception of details of their original consent and withdrawal.

LEGAL BASIS FOR COMMON LAW DUTY OF CONFIDENTIALITY
The study team at University of Oxford will be providing one cohort for this request containing approximately 6,000 individual records. Consent to data linkage has been sought for all participants in phases 1 and 2.

For those study participants in phase 1 (groups 1 and 2) recruited between June 2015 and 21 October 2019 (originally about 8,000 individuals ), consent was originally sought for a 12 month follow up, and then these study participants were re-consented for a further 10 years follow-up period. Only those that re-consented (approximately 3,000) will be a part of the cohort sent to NHS England. Of the phase 1 study participants, the consent documents provide for requesting NHS England data for a maximum of 10 years** from 12 months after the first date they consented into the study.

For those study participants in phase 2 (group 3) recruited from 21 October 2019 onwards (approximately 3,000 individuals), the consent documents provide for requesting NHS England for a maximum of 10 years** from the date of first consent.

**However, it is noted here that due to trial budget constraints, the EVAREST study is requesting NHS England data only between the periods of 2018 to the latest data available under the consent rules stated above.

The cohort provided to NHS England will only contain participants who consent to data linkage. NHS England will not apply National Data Opt-Out for these participants.

UK GDPR LEGAL BASIS FOR PROCESSING OF PERSONAL DATA
The University of Oxford, as the Data Controller who is also processing the data will process Personal Data under UK GDPR Article 6 (1) (e) - Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. As a higher education establishment, the University of Oxford conducts research to improve health care and services, and the data requested is necessary for the performance of a task carried out in the public interest. The University of Oxford hopes that this research study and the dissemination of the results will benefit the health and care of the general public by providing a rich detailed look into Stress Echocardiography practice in the UK and health outcomes following the investigation. This work should enable the study team to identify the accuracy of the investigation as well as areas for improvement. This will allow for corrective action to boost accuracy of Stress Echocardiography and thereby increase the quality of the health of individuals presenting for a Stress Echocardiogram investigation. The dissemination is in the public interest as it should provide evidence for the improvement of patient health and care. The outputs should provide the data needed to identify the accuracy and performance of Stress Echocardiography in across the UK for a large cohort of patients.

Additionally, under UK GDPR Article 9(2)(j) processing of Special Category Personal Data (of which Health data is one) is necessary for archiving for research purposes. Data minimisation processes are being followed and only data that is specifically required for the purposes of this study have been requested, to protect the rights of the data subjects. The data are required for research purposes in the public interest – meeting the conditions in the DPA 2018 Schedule 1 Part 1 (4) – which UK GDPR Recital 52(2) determines is an appropriate derogation from the prohibition on processing special categories of personal data.

TRANSPARENCY ON COMMERCIAL BENEFITS
Whilst Ultromics Ltd and Lantheus Medical Imaging Inc were originally funders of this study but are no longer involved and will have no access to record level NHS England data under this agreement, for the purposes of transparency it is stated here that Ultromics Ltd and Lantheus Medical Imaging Inc may receive indirect benefit from association with the EVAREST study. However, Ultromics Ltd and Lantheus Medical Imaging Inc will have no ability to suppress or otherwise limit the publication of findings from this study.

Expected Benefits:

The research study and the dissemination of the results hopes to benefit the health and care of the general public by providing a detailed look into Stress Echocardiography practice in the UK and health outcomes following the investigation. This work hopes to enable the study team to identify the accuracy of the investigation as well as areas for improvement. This should allow for corrective action to boost accuracy of Stress Echocardiography and thereby increase the quality of the health of individuals presenting for a Stress Echocardiogram investigation.

The dissemination is in the public interest as it hopes to provide evidence for the improvement of patient health and care. The outputs aim to provide the data needed to identify the accuracy and performance of Stress Echocardiography in across the UK for a large cohort of patients. Once the purpose is achieved, the benefits discussed hope to be realised.

The study team hope that the details of the work and dissemination will look to identify room for improvement in the practice of Stress Echocardiography. This could potentially impact all centres in the UK who routinely perform stress echocardiograms (around 120 as of 2014). If areas for improvement are noted and actioned, this could potentially lead to an increase in overall diagnostic accuracy of stress echocardiography, thereby reducing the need for potentially unnecessary further procedures and investigations in the patient care pathway. A reduction in unnecessary procedures and interventions could potentially decrease the burden on the NHS and allow resources to be utilised elsewhere. Individual patients could receive the benefit in having a more experienced and accurate stress echocardiogram investigation. This benefit in the individual level could be identified through further downstream research studies assessing stress echocardiography and patient health outcomes. It could take time to achieve these benefits as implementing trainings and affirmative action plans for increasing centre performance can take time. Policy change and cost savings can also require sufficient time to enact. The University of Oxford would expect that within the next 10 years they could see evidence of change in the patient care pathway, burden to NHS resources, and potentially national/international policy due to this dissemination.

Outputs:

The study team at University of Oxford aim to publish this work in a peer-reviewed journal. During the course of analysis there may be conferences and presentations that are conducted that include mention of EVAREST either in part or fully. All data included in presentations or publications will be anonymised meaning only high-level aggregate data with small numbers supressed (as per the HES analysis guide) will be presented.

The University of Oxford will aim to facilitate the dissemination of the research and scientific work to stakeholders during the project and after completion. The study team will aim to disseminate this research to the scientific public through presentations, publications and discussions. The study team will also aim to disseminate this research to the general public through publications. The study team are also planning to disseminate this work for potential policy change such as with National Institute for Health and Care Excellence (NICE) or European Society of Cardiology (ESC). This should all be accomplished through conferences, publications, presentations, webinars, engagement using professional and established relationships.

The study team aim to analyse the data and public preliminary work in 2023/2024 contingent upon when the data is received from NHS England. There may be various presentations, conferences, public events within that time that the data will also be presented at.

Processing:

DATAFLOW
Transfer of linkage file/identifiers from University of Oxford to NHS England:
- University of Oxford will send the list of Patient Identifiable Data (PID) in the form of one file - including participant Study ID, NHS Number, Date of Birth (DoB) and Post Code along with the date that data should flow from for each individual in the cohort. University of Oxford will send this file securely to NHS England via a Secure Electronic File Transfer Service (SEFT) or other secure, NHS England approved file transfer mechanism.

- The NHS England data production teams will link patient identifiers to the datasets requested and extract data either:
a) for phase one study participants originally consented between June 2015 and 21 October 2019 - from 12 months after the date of consent*.
b) for phase two study participants consented from 21 October onwards - from date of participants' first consent date.
(*PLEASE NOTE: The Study team have requested the extraction of data to be for NHS England data for the periods 2018/19 to latest available data only)

- The NHS England production teams will remove patient identifiers from the linked data.

- NHS England transfers the linked data via SEFT or other secure, NHS England approved file transfer mechanism to University of Oxford. This data is pseudonymised (only the participant ID from the linkage transfer is kept and identifiable fields are removed).

- University of Oxford study team downloads the data from SEFT to an encrypted system within the University of Oxford Medical Sciences Division IT Network.

The data will be accessed through this secure network. To remotely access the devices requires a secure 2-factor Medical Sciences Division IT authenticator (VPN) and users are then able to securely access the secure server on the University’s IT framework. All data analysis will be conducted within the confines of the University’s secure server, and will not be downloaded to remote devices for storage or processing.

All data analysis will be conducted by EVAREST study team members who are substantive employees of the University of Oxford or authorised study team members with an appropriate contract which has been reviewed and approved by NHS England.

The Patient identifiers provided to NHS England were originally collected by the local study teams at each participating site in the study and were then provided to the University of Oxford study team. These identifiers are only held at the University of Oxford for the purposes of providing to the NHS England team for linkage purposes. Once the identifiers are provided to the NHS England team, they will be destroyed by the University of Oxford study team prior to receiving record-level NHS England data.

The University of Oxford will not be sharing record-level NHS England data outside of the University of Oxford. All record-level NHS England data will be maintained and analysed within the University of Oxford.

Those handling the data for the Data Controller will have been authorised to do so internally and will have logged information security training.

Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide (see below)

HES and ECDS DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, data processors must make sure that:
• National-level figures only may be presented unrounded, without small number suppression
• cell values from 1 to 7 (inclusive) are suppressed at a sub-national level to prevent possible identification of individuals from small counts within the table.
• Zeros (0) do not need to be suppressed.
• All other counts will be rounded to the nearest 5.

RCGP Research Surveillance Network Observational Research Umbrella (RCGP RSC ORUm) — DARS-NIC-381683-R6R6K

Opt outs honoured: No - Statutory exemption to flow confidential data without consent, No (Excuses: Statutory exemption to flow confidential data without consent)

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2021-02 – 2024-02 2021.04 — 2023.05.

Access method: Ongoing

Data-controller type: PUBLIC HEALTH ENGLAND (PHE), ROYAL COLLEGE OF GENERAL PRACTITIONERS

Sublicensing allowed: No

Datasets:

  1. Mental Health Services Data Set
  2. COVID-19 Hospitalization in England Surveillance System
  3. COVID-19 Second Generation Surveillance System
  4. Diagnostic Imaging Dataset
  5. Emergency Care Data Set (ECDS)
  6. Secondary Uses Service Payment By Results Accident & Emergency
  7. Secondary Uses Service Payment By Results Episodes
  8. Secondary Uses Service Payment By Results Outpatients
  9. Secondary Uses Service Payment By Results Spells
  10. COVID-19 Second Generation Surveillance System (SGSS)
  11. Diagnostic Imaging Data Set (DID)
  12. Mental Health Services Data Set (MHSDS)
  13. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Type of data: Anonymised - ICO Code Compliant

Objectives:

Since the outbreak of COVID-19 in Wuhan, China, and the subsequent pandemic, PHE has commissioned the RCGP RSC to incorporate the monitoring of COVID-19 into its virology surveillance scheme. A vital part of this work has been to monitor the number of suspected COVID-19 cases in the community in a timely way.

PHE and the RCGP are Joint Data Controllers for this request. The RCGP Research Surveillance Centre (RCGP RSC) is based at the University of Oxford. The RCGP RSC is a growing network of over 1200 GP surgeries based in England. University of Oxford is the data processor.

PHE

Public Health England (PHE) holds a contract with the Royal Collage of Practitioners (RCGP) who in turn hold a contract with the University of Oxford to deliver information to support surveillance and monitoring of vaccine efficacy on Influenza.

RCGP

The Royal College or GPs (RCGP) Research and Surveillance Centre (RSC) has over 50 years’ experience of undertaking surveillance and research activities, predominantly in influenza surveillance. Pseudonymised patient data is extracted from over 1600 practices on a weekly basis, feeding into the disease surveillance and research funded through Public Health England (PHE). The COVID-19 activities set out in this agreement fall within the wider Disease Surveillance activities.

University of Oxford – are a data processor. The secure network which holds the physical data is at the University of Oxford. The University of Oxford acts as Data Processor on behalf of the Data Controller (RCGP and PHE).

The lead Professor who is the RCGP RSC Director, has moved his main appointment from the University of Surrey to the University of Oxford. Oxford currently provide the academic and clinical informatics input to inform data usages and ensure this adheres to contract held with PHE. Additionally, the study produces research outputs from the University of Oxford (these outputs have small numbers suppressed and Oxford are therefore not listed as a data processor).

The surveillance function of the RCGP RSC provides a unique platform upon which to build population based observational epidemiological studies designed to inform the national public health response to COVID-19. Direct COVID-19 analyses will study for example which patient-level characteristics are associated with COVID-19 infection, predictors of adverse outcomes, and potential treatments. Indirect COVID-19 analyses will for example provide near real-time monitoring to inform strategies to mitigate the indirect effects of the national response to COVID-19 on other "COVID-19 sensitive" non-communicable diseases.

Built on high quality primary care electronic health records data, the Joint Data Controllers for this request (PHE and RCGP) hope to add to the existing RCGP RSC HES (Critical Care, Outpatients, A&E, Admitted patient care) and Civil Registration (mortality) Data (CRD) linkages to support the priority observational COVID-19 studies outlined below.

OVERALL AIM

The study aims to establish an umbrella agreement for data linkages to support the RCGP RSC to conduct observational epidemiological studies inform the national public health response to COVID-19.

PRIORITY OBSERVATIONAL WORKSTREAMS

The following three priority workstreams outline analyses underway or in set-up using the RCGP RSC dataset.

1. RGGP RSC COVID-19 SURVEILLANCE

Aim - to identify whether there is undetected community transmission of COVID-19, estimate population susceptibility, and monitor the temporal and geographical distribution of COVID-19 infection in the community.

Specific objectives
1 a. To monitor the burden of suspected COVID-19 activity in the community through primary care surveillance and clinical coding of possible COVID-19 cases referred into the containment pathway

1 b. To provide virological evidence on the presence and extent of undetected community transmission of COVID-19 and monitor positivity rates among individuals presenting ILI or acute respiratory tract infections to primary care. PHE see all specimens (identified by NHS Number within their laboratory department) then pseudonymise this identifier to allow linkage. The PHE data and NHS Digital data will all be pseudonymised using the same algorithm so that a fully linked record for each person in the database will be available for the research team. The analysis will therefore be done by the team at an individual level but without the need to know who that individual is.

1 c. To estimate baseline susceptibility to COVID-19 in the community and estimate both symptomatic and asymptomatic exposure rates in the population through seroprevalence monitoring

1 d. To pilot implementation of a scheme for collection of convalescent sera with antibody profiles among recovered cases of COVID-19 discharged to the community. PHE see all specimens (identified by NHS Number within their laboratory department) then pseudonymise this identifier to allow linkage. The PHE data and NHS Digital data will all be pseudonymised using the same algorithm so that a fully linked record for each person in the database will be available for the research team. The analysis will therefore be done by the team at an individual level but without the need to know who that individual is.


2. DECISION-COVID: DEfining the CharacterIStIcs Of Individuals with suspected Novel COronaVIrus Disease and risk factors for development of the disease.

Aim - To better understand the characteristics of patients being tested for COVID-19 and to determine the associations between demographics, comorbidity and medications on the likelihood of developing COVID-19 and subsequent complications (e.g. hospitalisation, admission to an intensive care unit, death).

Specific objectives
2 a. Identify patient demographics and co-morbidities that predict the diagnosis of COVID-19 and subsequent complications (e.g. hospitalisation, admission to an intensive care unit, pulmonary events, death).

2 b. Identify medications that are associated with and increased or decreased risk COVID-19 infection and complications (e.g. hospitalisation, admission to an intensive care unit, pulmonary events, death).


3. MAINROUTE-C19: Monitoring Attendance, INvestigation, Referral, and OUTcomEs in Primary Care: impact of and recovery from COVID-19 lockdown

Aim - To describe and analyse the impact of the COVID-19 lockdown on presentation patterns, diagnoses, monitoring and outcomes of common non-communicable diseases, such as cancer, cardiovascular disease, diabetes and mental health.

Specific objectives
3 a. To produce practice-level data analytics on presentation, management and diagnoses of common non-communicable diseases and preventive health activities before, during and after COVID-19 lockdown, by region, practice, gender, and age

3 b. To examine the effect of the COVID-19 lockdown (and release) on presentation, management and diagnoses of common non-communicable diseases and preventive health activities by region, practice, gender, age and ethnicity

3 c. To determine the effects of the changes in presentation, management and diagnosis on long-term outcomes such as hospitalisation, morbidity and mortality, and some condition-specific outcomes.


EXISTING DATASET

The main aim of this application is to build on the exiting RCGP RSC database. The RCGP RSC dataset includes individual patient level up-to-date primary and secondary care data which can be easily queried. Primary care/general practice data is rich in terms of diagnosis and information about the process of care. For example, the database contains the following variables for each patient (where present):
• Detailed demographic and risk factor data.
• COVID-19 appointments: including information on whether or not a virology swab was taken and the outcome of the swab
• Non-COVID-19 appointments.
• Detailed data for the 32 conditions monitored by RCGP RSC on behalf of PHE
• Vaccination status: date of vaccination, type of vaccination
• Co-morbid conditions
• Medication which may be associated with better or adverse outcomes.
• Test results
• Referrals made
• A & E visits
• Inpatient appointments, including critical care
• Outpatient appointments
• Mortality data (if applicable).

Existing linkages include CRD and HES data provide key information about the outcomes of care:
• HES: Critical Care
• HES: Outpatients
• HES: A&E
• HES: Admitted patient care
• CRD (mortality) data

ADDITIONAL LINKAGES REQUESTED

Additional individual level linkages to the entire RCGP-RSC cohort will support the priority analyses outlined above. Individual patient level data is required because individual patient level linkage allows much more precise statistical analyses to be made, compared with comparing aggregate data. Additional historical and updating linkages are requested to the following additional datasets:

• Cancer Registration Data
• Secondary Uses Service Payment By Results Episodes
• Secondary Uses Service Payment By Results Outpatients
• Secondary Uses Service Payment By Results Accident & Emergency
• Secondary Uses Service Payment By Results Spells
• Mental Health Services Data Set
• Diagnostic Imaging Dataset
• Emergency Care Data Set (ECDS)
• COVID-19 Hospitalisation in England Surveillance System (CHESS) Dataset
• Second Generation Surveillance System (SGSS) Dataset


Historic data are needed because longitudinal data better enable the RCGP RSC to predict what might happen in the future; even a small increase in the ability to understand flu and COVID-19 and its associated morbidity and mortality would offer benefits for patients and the NHS. Both historical and future data are needed in order to build a robust database and reporting system using up-to-date primary and secondary care data at the individual patient level, which can be easily queried. This will enable the study group to answer a wide range of questions which will have an impact on the provision of health care in England. For example, the data will be used to answer questions posed by PHE, who make many decisions about healthcare, such as the vaccination programme, or preventative measures. In MAINROUTE, for example, longitudinal data will allow time series analyses to be conducted as part of objcetive 3 b. which will compare primary care activity before, during and after "lockdown" to establish whether changed in primary care activity are associated with changes in disease presentation and outcome.

The same pseudonymisation algorithm will be applied to all data involved in this study (and any other studies) so the researchers can draw scientific conclusions for a study population. The PHE data and NHS Digital data will all be pseudonymised at University of Oxford prior to researcher access using the same algorithm so that a fully linked record for each person in the database will be available for the research team.

REGULATORY FRAMEWORK

The GDPR Lawful basis for processing the requested data under this agreement are;

Public Health England;
Article 6(1)(e) (Public Task processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller).

Article 9(2)(h) (processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services)

and

Article 9(2)(i) (processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices).
PHE exist to protect and improve the nation's health and wellbeing, and reduce health inequalities.

RCGP;
Article 6(1)(f) processing is necessary for the purposes of the legitimate interests pursued by a controller, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child. This shall not apply to processing carried out by public authorities in the performance of their tasks.

Article 9(2)(i) (processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices).

Additionally the request for data is supported by PHE as they have an emanation of the Secretary of State for health and social care, to both self-approve the use of Control of Patient Information Regulation 3 and to grant this approval to third parties processing confidential patient information without consent for purposes that fall under the scope of Regulation 3.

This authority to has been in existence since PHE was established in 2013 although the large majority of the Regulation 3 approvals granted since that date have been internal to PHE; only a very small number have been granted by PHE to third parties. Specifically the work being undertaken under Reg 3 in this application is limited to Communicable Disease surveillance and other risks to public health’.

The data will not be shared with third parties and only used within the data processors listed in this agreement. Data disseminated under this application can only be used for different purposes after those different purposes have been approved by NHS Digital under separate applications and a live DSA is in place.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Expected Benefits:

The surveillance work conducted by the RCGP RSC on behalf of the Data Controllers is used by Department of Health, NHS England and PHE to monitor trends in a number of infectious conditions. Specifically for COVID-19, the RSC aims to identify whether there is undetected community transmission of COVID-19, estimate population susceptibility, and monitor the temporal and geographical distribution of COVID-19 infection in the community. In addition, the RCGP RSC will describe and analyse the impact of the COVID-19 lockdown on presentation patterns, diagnoses, monitoring and outcomes of common non-communicable diseases, such as cancer, cardiovascular disease, diabetes and mental health. Furthermore the analyses conducted under RCGP RSC ORUm will lead to a better understanding of the characteristics of patients being tested for COVID-19 and the associations between demographics, comorbidity and medications on the likelihood of developing COVID-19 and subsequent complications (e.g. hospitalisation, admission to an intensive care unit, death).

Specific benefits

The linkages described in this protocol can help assess the severity and mortality of a given condition, thereby alerting PHE on whether larger measures should be implemented. This could lead to improved healthcare and reduced mortality of certain conditions. Additionally, the linkages allow the RCGP RSC to identify how COVID-19 lockdown has put additional pressure on the health system in terms of delayed testing and referral, meaning that plans can be put in place in order to prevent or deal with these pressures during subsequent waves of the pandemic.

By supporting RGGP RSC COVID-19 SURVEILLANCE the researchers will be able to augment direct RCGP RSC COVID-19 surveillance using dedicated national COVID feeds (CHESS/SGSS) and enable full care pathway analysis from presentation to community providers (GP/111) through to secondary/tertiary care (ECDS/HES/SUS).

By supporting DECISION-COVID linked data will allow analyses to determine associations between demographics, comorbidity and medications of patients presenting to GP and the likelihood of developing COVID-19 and subsequent complications such as hospitalisation, admission to an intensive care unit, death (ECDS/SUS/HES/ONS), and to characterise socioeconomic and ethnic disparities in patients being tested (CHESS/SGSS) for COVID-19.

By supporting MAINROUTE-C19 linked data will enable an end-to-end description of the impact of the COVID-19 lockdown on the clinical pathway in terms of presentation patterns (GP RSC), testing (RCGP RSC/SUS/HES/DID) diagnoses (GP RSC/SUS/HES/Cancer/MHDS), monitoring (RCGP RSC) and outcomes (GP RSC/SUS/HES/Cancer/ONS) of common non-communicable diseases, such as cancer, cardiovascular disease, diabetes and mental health.

Outputs:

Specific Outputs for this study are:

• To track the impact of COVID-19 lockdown, visual descriptions (dashboards) of the number and rates of patients presenting with specific symptoms (primary care data), being tested for specific tests (including DID data), or referred for particular conditions will be presented over time (at weekly frequency) from 2018 will be hosted online. The raw data will be overlaid by 7-day moving averages, adjusted for seasonality. Subgroups of data will be identified to enable display by GP practice, region, age group, gender, and ethnicity.
• Using HES, SUS, ECDS, Mental Health Services Data, and Cancer data, outcomes will be examined through 7-day moving averages and presented graphically over time for the years 2018, 2019 and 2020 onwards to descriptively compare levels of activity.

Findings from this study will also contribute to existing outputs as follows:

• The RCGP RSC weekly report is circulated to a selected list of recipients on Wednesdays and it is publicly available on Thursdays at 2 pm at the RCGP RSC website (http://www.rcgp.org.uk/clinical-and-research/our-programmes/research-and-surveillance-centre.aspx). This report currently covers incidence rates of 37 infectious and respiratory conditions in England. It is expected that, in future, hospitalisation trends will be included. This is incorporated into the syndromic surveillance carried out by PHE on a daily basis, which allow them to determine any urgent priorities for local health protection teams.
• Similar to this, an annual report is published covering the annual trends of the 37 conditions. Each year, this report has a new theme which is explored in a paper submitted to a peer-reviewed journal (usually British Journal of General Practice). Themes explored include demographic disparities in disease presentation, higher rates of consultations for lower respiratory infections for boys, and urban/rural disparities of presentation.
• In January of every year, the University of Oxford provide a mid-season flu cohort to PHE with data up to the end of December. This is a fully pseudonymised patient-level extract collected by a PHE statistician using a secure drive. This data extract contains details of influenza swabbing, chronic conditions, and vaccination status for each patient. It is hoped to be able to include details of emergency attendances or admission around influenza, pneumonia, or lower respiratory tract infection events. At the end of the flu season (varies from March to May), a second extract is provided updating the first, with data recorded after December.
• The data from both of these extracts is used to estimate seasonal influenza vaccine effectiveness, stratified by comorbidities and demographics. HES data allow the University of Oxford/PHE and RCGP to include the impact of any changes in effectiveness, assessed through changes in hospital admissions/emergencies due to respiratory conditions. The results are published at the mid-season and at the end of season stage, on the peer-reviewed journal Eurosurveillance.
• Important results from either of these will be further analysed and presented at the RCGP annual conference, the PHE annual conference, and the PHE annual epidemiology conference.

Processing:

Flows of data:
• Data are initially extracted from practices that are members of the Royal College of General Practitioners (RCGP RSC) Research and Surveillance Network by Wellbeing. The University of Oxford subcontracts with Wellbeing to do this as part its contractual responsibilities. The data are pseudonymised at source within the Wellbeing extraction process.

• The University of Oxford, on behalf of RCGP RSC, will provide NHS digital with a list of hashed NHS numbers and hashed date of birth for the cohort. NHS Digital will be operating under instruction as a data processor from the Data Controllers in this agreement to process the cohort data as per the details set out in this agreement and return the linked data asset. That data will flow back from NHS Digital using the same hashed algoritham therefore the research team will only be accessing pseudonymised data.

The Hashing process is as follows:
1. An encryption salt is held by a designated staff member of the University of Oxford Medical Science Division who is not a member of the research team.
2. When a data linkage is required, the encryption salt holder sends the encryption salt to the data provider (NHS D)
3. The data provider NHS D in this case will hash personal identifiers (in the data requested under this agreement) using a hashing algorithm
4. The hashing algorithm is SHA2-512.

The data are then linked across the datasets requested in NHS Digital using hashed NHS numbers.

On receipt of the data from NHS Digital University of Oxford will then link the NHS Digital data with the cohort data already held in the University using the same hashed algorithm. The data will be pseudonymised in a consistent manner so that the research team are then only working with a fully pseudonymised dataset. Each individual in the cohort will have a fully linked record.

NHS digital will provide back linked data including hashed NHS Number and hashed DOB:
• Cancer Registration Data
• Secondary Uses Service Payment By Results Episodes
• Secondary Uses Service Payment By Results Outpatients
• Secondary Uses Service Payment By Results Accident & Emergency
• Secondary Uses Service Payment By Results Spells
• Mental Health Services Data Set
• Diagnostic Imaging Dataset
• Emergency Care Data Set (ECDS)
• COVID-19 Hospitalisation in England Surveillance System (CHESS) Dataset

• University of Oxford will store the data on the secure network.

• University of Oxford will process and aggregate pseudonymised data to produce approved reports for surveillance (as part of the National surveillance process); and quality improvement.

The data is controlled and processed by a group of staff who are all based at the University of Oxford; all are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Language Query (SQL) developers, RCGP RSC practice liaison officers, a project manager and a head of department. The team work from secure workstations or secure laptops with encrypted drives within the group’s secure network.

All record level data will be held and stored within England and Wales.

Detailed explanation of flows of data:

a) Data flow from RCGP RSC network member practices to University of Oxford: Wellbeing extract the data from the practices. Patients who have opted out of data sharing do not have their data extracted, unless they have consented to a specific surveillance programme or study. This extract provides the study with information about patient’s visits to general practices including the date of the appointment, the reason for the visit and any relevant vaccination information. The University of Oxford also receive patient’s NHS numbers and date of births which are pseudonymised using SHA-512 algorithm. Detailed information about this algorithm is held in a separate location by IT services at the University of Oxford. It is this department who will share the identifiers with NHS Digital for the linkage leaving the research team only access to the pseudo data.

b) University of Oxford Storage and processing of data: The data about patients registered with RCGP RSC general practices is stored on the secure server at the University of Oxford which can only be accessed from the University of Oxford. The data will be processed within secure network and dedicated analysis server of the Surveillance Group. The secure network is located behind a firewall within the University’s network, all in-bounded connections are blocked, but out-bounded connections are allowed. Patient level data are held in the database server within the RSC Group’s secure network.

c) Pseudonymised data will be stored on the database server within the RSC’s secure network once fully linked with the NHS digital returned data. The pseudonymisation algorithm is held in a separate location by IT services at the University of Oxford.

d) University of Oxford process and aggregate pseudonymised data to produce reports. For example, University of Oxford on behalf of RCGP RSC provide a mid-season flu cohort to PHE with data up to the end of December. This is a fully pseudonymised patient-level extract collected by a PHE statistician using a secure drive. The University of Oxford also produce an end of season report, an annual report and weekly reports that are available to the public and use aggregated data on rates of infectious and allergic conditions.

The RCGP RSC data is controlled and processed by a group of staff who are all based at the University of Oxford; all are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Language Query (SQL) developers, RCGP RSC practice liaison officers, a project manager and a head of department. The team work from secure workstations or secure laptops with encrypted drives within the group’s secure network.

Data will only be accessed by individuals within the RSC who have authorisation that are substantive employees of University of Oxford. The authorisation process includes: (1) Contractual requirement to follow IG principles; (2) Using the email registered with Human Resources to complete IG training and to return the certificate; (3) Staff’s email is authorised by the IT department for one year to access the secure network and staff’s computers are configured to allow this; (4) At any point the project managers or Head can have access to the secure network turned off. There is special authorisation to have access to the main database.

Only three SQL developers and one senior project manager can access the main database. Surveillance databases are created for approved analyses once they have been agreed by the RCGP RSC approval committee. This agreed protocol includes the list of variables required for the database. The SQL developers create separate databases for individual projects only including the required variables, for the required time interval.

There will be no requirement nor attempt to re-identify individuals from the data by the research team. The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.




MR1483 - HPS-4/TIMI 65/ORION-4: A double-blind randomized placebo-controlled trial assessing the effects of inclisiran on clinical outcomes among people with atherosclerotic cardiovascular disease. Application for data for invitation. — DARS-NIC-172240-R4R0L

Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251, Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d), Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2018-10 – 2020-06 2018.10 — 2023.04.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - List Cleaning Report
  2. Demographics
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Identifiable

Objectives:

The University of Oxford requires demographic, mortality and HES data to recruit participants into the ORION-4 study.

Investigators at The University of Oxford have instigated this work to achieve benefits for patients by obtaining reliable evidence about the safety and effectiveness of a new cholesterol lowering medication called Inclisiran. Inclisiran is given as an injection 2-3 times a year and reduces bad (LDL ) cholesterol. The ORION-4 study will find out whether inclisiran safely reduces heart attacks, strokes and cardiovascular deaths in people who already have cardiovascular disease. If shown to be effective, this treatment could substantially reduce premature death and disability from these conditions. A secondary objective is developing streamlined trial methods that would benefit future research.

The ORION-4 study is co-sponsored by The University of Oxford and The Medicines Company. The protocol and procedures have been developed by the Chief Investigator at the Clinical Trial Service Unit, University of Oxford in an academic collaboration with the TIMI Group - an academic research group within Harvard University - and The Medicines Company which comprise the Steering Committee for the trial. The Steering Committee would determine the scientific objectives of the trial, ensure adequate progress towards those objectives and review any papers prior to publication. As is usual with this type of trial, the Steering Committee also has other international experts from other institutions to advise the trial management team.

In respect of the data under this Agreement, the University of Oxford is the sole data controller. While the Steering Committee signs off the high level plan, the University has full autonomy to determine what personal data is obtained and how it will be processed. The University of Oxford would determine how, when and by whom personal data is processed and is responsible for the security of those data.

The data will be stored and processed at the University of Oxford. Patient’s NHS and Hospital Numbers may be shared with the NHS Trusts that treated them so that the Trust can confirm patient’s eligibility by checking local laboratory results for cholesterol levels. Other than sharing these data items with NHS Trusts, data supplied by NHS Digital would not be released to any other organisation or used for any other purpose. No Harvard University employees will have access to record level data under this Agreement. The Medicines Company will not access data under this Agreement.

The University of Oxford established the Clinical Trial Service Unit (CTSU), now within the Nuffield Department of Population Health, in the 1980s to conduct large trials such as the International Study of Infarct Survival (ISIS) trials. Since then CTSU has successfully completed a number of landmark studies including the 20,000 participant Heart Protection Study, the 9500 participant SHARP study, the 26,000 participant HPS-2/THRIVE study and the 30,000 participant HPS-3/REVEAL study.

The aim of processing the data is to recruit consenting participants for a randomized trial. At the beginning of the trial, half of the participants will be put in the group to be given active inclisiran and the other half will be put in the group to be given placebo injections. This will be done by chance, in a similar way to tossing a coin, called “randomization”. The participants will be followed to find out whether the active inclisiran group experienced fewer heart attacks, strokes and cardiovascular disease outcomes than the placebo group thereby demonstrating the effects of the treatments. The trial will also seek to establish whether the treatment is safe by looking to see whether the active inclisiran group evidenced increased risk of any other health conditions/outcomes.

The demographic (including name, address and GP practice details), mortality and HES data are required to assist the University of Oxford in identifying and recruiting eligible participants. Potentially eligible participants will be invited on behalf of the Local Investigator using local NHS headed paper to attend a Screening Appointment at the ORION-4 clinic (usually in their local NHS Hospital). If they choose to attend, they will be invited to consent to participate in the clinical trial.

For those who provide informed consent, the University of Oxford will apply to NHS Digital for subsequent follow up data under a separate Data Sharing Agreement.

Yielded Benefits:

By 2020, the trial has established around 100 research sites across the UK and recruitment is progressing well. Because of the requirement of the trial to include people with higher cholesterol values a substantial proportion of people volunteering are not able to take part which has meant that recruitment has been slower than expected. However, because of the large-scale central invitation process using the data requested in this application, additional patients can be invited without substantial extra cost.

Expected Benefits:

The results of ORION-4 will be relevant to the 7 million people living with cardiovascular disease in the UK and many more around the world. Bad (LDL) cholesterol is a strong reversible risk factor for cardiovascular disease. Evidence from large, randomized trials have lead to the widespread use of statins in individuals with and at risk of vascular disease which has resulted in substantial benefits for patients. Recent research suggests that further lowering of bad (LDL) cholesterol results in additional reductions in the risk of heart attacks, strokes and death from cardiovascular disease. Inclisiran is a new medication which reduces LDL cholesterol by about half. If shown to be safe and effective and made widely available to high risk individuals, treatment with inclisiran might be expected to prevent a substantial proportion of the 0.5M heart attacks, 0.25M strokes and 0.15M deaths from cardiovascular disease which occur each year in the UK.

It is expected that the results of ORION-4 in 2025 will be incorporated into National and International Guidelines for the treatment and prevention of cardiovascular disease, including guidelines from the National Institute for Health and Care Excellence (NICE) and The Scottish Intercollegiate Guidelines Network (SIGN). Inclisiran is given by injection every 6 months and reduces bad (LDL) cholesterol by about half when given either alone or with statins. Other drugs which work in a similar way to inclisiran are available, but require 4 weekly injections and are expensive to produce. As a result they are not widely available for patients in the UK. Since inclisiran requires an injection only every 6 months and has lower production costs, it is likely that it will become available to patients if proved to be safe and effective in reducing the risk of heart attacks and strokes. Furthermore this treatment may overcome problems with medication adherence which are particularly problematic for long term preventative medicines. Therefore the results of ORION-4 are likely to change clinical practice in the prevention of cardiovascular disease both in the UK and around the world and would be expected to have a substantial impact on the numbers of heart attacks, strokes and deaths from cardiovascular disease globally.

The data from NHS Digital is extremely beneficial in recruiting the large numbers of participants needed for the success of this study. At CTSU large efficient trials have been conducted which produce reliable answers by recruiting large numbers of participants. Both the THRIVE and REVEAL trials each randomized over 8,000 patients in the UK using methods similar to those proposed for ORION-4 although in those studies patients' details were obtained direct from NHS Hospital Trusts rather than from NHS Digital. Many people invited to take part in research choose not to for a variety of reasons, therefore it is necessary to send very large numbers of invitations to successfully recruit to a large study like ORION-4. In REVEAL around 300,000 invitations were required to randomize about 8,000 people into the study. For ORION-4 it is expected that between 400,000 and 500,000 invitation letters would need to be sent to achieve the recruitment target. It would be considerably more difficult to achieve this without the data requested from NHS Digital.

Beyond the ORION-4 study, the recruitment methods using data from NHS Digital would inform trial design and produce benefits to future research. To reliably assess the effects of treatment it is necessary to randomize a large enough numbers of participants to avoid getting the wrong answer by chance and many randomized trials are too small to answer the research question reliably. Recruiting large numbers of participants is difficult and can be prohibitively expensive and many trials fail to reach their recruitment target. Cost-effective, streamlined methods of trial recruitment are needed to improve health by obtaining reliable knowledge about which treatments work and which are harmful. Using NHS Digital data to mail invitation letters to large numbers of potentially eligible people will provide just such a method to ensure the success of this trial and the methods developed would benefit future studies. CTSU is committed to developing streamlined methods of conducting randomized trials so that more trials can produce reliable answers. Members of the ORION-4 team are working with organisations such as the Clinical Trials Transformation Initiative (CTTi), a public-private partnership to develop practices aiming to increase quality and efficiency of clinical trials. Learning from the recruitment methods developed in ORION-4 will be shared by publications in open-access, peer reviewed journals, by courses run by CTSU and shared with other researchers using initiatives such as the CTTi.

Outputs:

The main trial results of ORION-4 are expected in 2025 and will inform the treatment of people living with cardiovascular disease around the world. The results will be disseminated widely, including presentation at relevant conferences and publication in an open-access, high-impact medical journal. Further academic papers (including results of cost-effectiveness analysis and papers about the trial methods) will be published in open-access, high impact, peer-reviewed journals and on the trial website. After the close of the study, additional results assessing the long-term effects of inclisiran obtained through data linkage or participant questionnaires will be published.

A non-technical summary of the main study findings will be sent to participants and relevant charities, such as the British Heart Foundation and Heart-UK, and published on the study website. For each paper a short presentation will be developed to summarise the key findings which will be presented at key conferences.

This study will use streamlined recruitment methods to identify and recruit 15,000 eligible participants cost-effectively. The United Kingdom will recruit around 12,000 participants and the United States of America will recruit the remaining 3000 participants. Recruiting such large numbers in the UK has a number of potential advantages including; enhanced efficiency and lower cost and enabling record linkage for important outcomes both during the scheduled treatment period and after the close of the trial, along with benefits to future UK research. The data requested in this application will be used to identify and recruit most of the 12,000 eligible UK participants by the end of 2019.

From experience with previous trials it is anticipated that between 20 and 30 people will need to be invited for each participant randomized into the study and therefore obtaining large numbers of potentially eligible participants is critical to successful recruitment. In previous studies lists of such individuals have been obtained from individual NHS Trusts, with Section 251 support. Obtaining the list of potentially eligible individuals from NHS Digital leads to the following benefits for the study; First, any delay in obtaining the data while waiting for local data analyst time and technical difficulties associated with dealing with different dataset formats from different NHS trusts would be avoided. Second, the risk of sending the invitation to the wrong address would be reduced. If data is sought directly from the NHS Trust and the patient has moved since they last visited that secondary care provider, then the address for invitation would be out of date. Thirdly, obtaining data directly from NHS Digital allows individual preferences about opt-outs to use of their data be upheld.

Obtaining GP practice information for each potentially eligible participant will help to ensure that correspondence is sent to the correct GP practice. Once a participant has been screened and provided consent, a standard ethics approved letter containing details of the trial and the individual’s current cholesterol lowering treatment, and highlighting the guideline recommended treatment for such patients, will be sent to their GP. The GP is asked to do two things before the randomization appointment 2 months later; (i) review the individual’s cholesterol lowering treatment and (ii) inform the trial coordinating centre if they have concerns about that participant entering the trial. It is therefore very important that letters go to the right practice. Previously, clinical trials have relied on patients to provide their GP details with subsequent checking by the coordinating centre. This is time-consuming and can lead to errors and it will be more efficient and accurate to use up-to-date GP information through NHS Digital’s List Cleaning service.

The List Cleaning outputs will reduce the risk of attempting to contact recently deceased individuals and potentially causing distress to living relatives. Furthermore the regular list cleaning will help to ensure that addresses are accurate. If the invitation were sent to the wrong address opened and the Participant Information Leaflet read carefully it would be possible to infer that the invited individual had vascular disease. Although the risk of this happening is low, it is important to minimise this risk by undertaking regular list cleaning.

Once recruitment is complete, reports will be generated using these data in order to describe the recruitment procedures for the trial (for example establishing the number of individuals invited to participate by age and sex). Such reports will not contain any identifying information (including small groups which could potentially be identified) and will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide. This will be undertaken as soon as possible after the end of the recruitment period in 2020 and before the analysis of the main study results is complete in 2025.

Processing:

The University of Oxford will establish ORION-4 sites (generally in NHS Trusts which treated high numbers of individuals for heart attacks, strokes or cardiovascular conditions). Once a local NHS Trust has completed the study feasibility assessment, the University of Oxford will inform NHS Digital that that NHS Trust is now a confirmed site.

Using a combination of the Hospital Episodes Statistics (HES) and Personal Demographics Service (PDS) databases, NHS Digital will extract the details of patients aged 55 and over for whom a previous hospital episode with an ICD 10 code or other diagnostic code indicating eligibility for the trial has been recorded by one or more of those NHS Trusts. Patients who are deceased or who are not current registered with an NHS GP would be excluded.

NHS Digital will provide to the University of Oxford a file containing the following data items for potentially eligible participants:
• Name
• Latest address and postcode
• Date of Birth
• Sex
• ICD 10 or other diagnostic or procedure codes to indicate eligibility
• NHS Trust
• NHS Number
• Hospital Number
• GP practice code
• Admission date of most recent episode with an ICD 10 code or other diagnostic code meeting the inclusion criteria

The University of Oxford will undertake further work to ascertain eligibility. This may include sending a list of NHS and Hospital Numbers securely to the local NHS Trust so that they can undertake further eligibility checks based on the blood cholesterol levels as recorded in the Trust laboratory system.

During the study recruitment period, the University of Oxford will regularly submit batched lists of potentially eligible individuals back to NHS Digital who will provide a ‘List Cleaning’ service and report back the individuals’ current vital status, current address and current GP practice code. This information is required to minimise the risk of writing to recently deceased individuals or writing to incorrect addresses. The GP practice code is required so that a letter can be sent to the GP immediately after a participant’s screening appointment in order to inform the GP of the participants planned enrolment into the trial and allow the GP to opt that participant out of randomization if they feel appropriate.

The University of Oxford will write to the potential participants identified in the List Cleaning reports inviting them to an ORION-4 Screening Appointment at the ORION-4 clinic within the relevant NHS Trust. Should they choose to attend, at the appointment they will be invited to participate in the trial and give informed consent if they wish.

The data received from NHS Digital will only be accessed by individuals within the Clinical Trial Service Unit who have authorisation to access the data for the purpose(s) described, all of whom are substantive employees of the University of Oxford. The potential exception to this is that NHS and Hospital Numbers may be shared with the NHS Trusts that have previously treated the potential participants. This would not involve giving those NHS Trusts new information about the participants, since they recorded the data in the first place. It would simply be a practical step to enable the Trusts to identify the individuals in their own patient records in order to undertake a further eligibility check based on local laboratory blood cholesterol results.

After invitation, individuals who have not responded will be considered to have declined to participate. These individuals will not be invited again.

Data about those participants who declined to participate, or have been considered to have declined to participate through non-response, will be held initially in order to avoid inviting those individuals again. Once recruitment is complete, reports will be generated using these data in order to describe the recruitment procedures for the trial (for example establishing the number of individuals invited to participate by age and sex). Such reports will not contain any identifying information (including small groups which could potentially be identified). Once these reports have been completed, the data provided by NHS Digital for those individuals will be irrevocably deleted. This will be undertaken as soon as possible after the end of the recruitment period in 2020 and before the analysis of the main study results is complete in 2025.

The data provided under this Agreement will only be used for the purposes of recruitment and recruitment analysis and will not be used for any subsequent purposes within the clinical trial.

The Oxford Heart Vessels and Fat (ox-HVF) Cohort — DARS-NIC-392669-T1F8B

Opt outs honoured: No - consent provided by participants of research study, No (Excuses: Consent (Reasonable Expectation))

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-11 – 2020-10 2017.12 — 2023.04.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Office for National Statistics Mortality Data
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Critical Care
  5. Hospital Episode Statistics Outpatients
  6. Bridge file: Hospital Episode Statistics to Mortality Data from the Office of National Statistics
  7. MRIS - List Cleaning Report
  8. HES:Civil Registration (Deaths) bridge
  9. Civil Registration - Deaths
  10. Emergency Care Data Set (ECDS)
  11. Civil Registration (Deaths) - Secondary Care Cut
  12. Civil Registrations of Death - Secondary Care Cut
  13. Hospital Episode Statistics Accident and Emergency (HES A and E)
  14. Hospital Episode Statistics Admitted Patient Care (HES APC)
  15. Hospital Episode Statistics Critical Care (HES Critical Care)
  16. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Identifiable

Objectives:

The University of Oxford require a list cleaning to take place first following approval. Then there would be a period of time to allow for any participant withdrawals before Oxford supplied the cohort to NHSD for linkage. The purpose of the list clean is to notify the study of any cohort members that have died. Confirmation of deceased cohort members will allow the study not to cause further distress by sending newsletters to the families of the deceased.

Coronary artery bypass graft surgery (CABG) continues to be the optimum revascularisation strategy for most patients with multi-vessel coronary artery disease. Although the biological variability between patients should be crucial for the prediction of long-term outcome of patients undergoing cardiac surgery, the exact mechanism linking the biology of the heart, the vascular grafts used and the myocardium with clinical outcome are unclear.

To address this shortfall in literature evidence, this study is aimed at assessing the venous and arterial redox states of patients undergoing CABG and valve repair/replacement surgery, in addition to data related to myocardial redox state, general biochemistry and imaging.

The cohort includes patients from 3 studies
1) the Arterial Revascularisation Trial (ART) (November 2004 to current; REC: MREC04/03/006) aimed at comparing survival following bilateral versus single internal mammary grafting in coronary revascularisation

2) the Bypass Vascular study (January 2005 to current; REC: 04/Q1605/95 ) aiming among others to compare in vivo measures of vascular function with post-operative clinical outcome after cardiac surgery

3) the AdipoRedOx study (15/09/2011 to current; REC: 11/SC/140), aiming to investigate the role of the interactions between adipose tissue and cardiovascular oxidative stress, in the prediction of post-operative outcome of patients undergoing cardiac surgery.

Each study has gained informed consent from participants to access their medical records to collect post-operative information that may have a predictive value after cardiac surgery.

Importantly, these studies aim to link the collected data (i.e. risk factors, data on vascular function etc.) with patient clinical outcome data, producing the world’s most comprehensive resource comparing vascular biology with clinical outcome post-cardiac surgery.

The primary objectives of the study are to -

Investigate the mechanisms by which adiponectin affects
vascular/myocardial redox state, endothelial function and clinical outcome
of patients undergoing coronary artery bypass grafting operation (CABG).

Secondary objectives are to-

1) Search for a possible signal from the myocardium/vascular wall to
epicardial/perivascular adipose tissue, that regulates the synthesis of
adipokines and other signalling molecules
2) Search for novel biomarkers/signalling molecules identified in
peripheral blood or expressed in adipose tissue, that regulate
vascular/myocardial redox state and/or predict vein graft patency

In summary these objective will then potentially results in the creation of patient risk models with which to improve health outcomes.

The first step in achieving these objectives will be to provide further fair processing information to the participants via a newsletter. This will be followed by linkage to HES and ONS mortality data.

Yielded Benefits:

Recent data have shown that treatment of patients with diabetes with insulin, may lead to significant damage of the heart arteries if the treatment is not accompanied by a drug called insulin sensitizer. This could lead to major changes in the treatment of these patients globally (https://inews.co.uk/news/health/diabetes-drug-prevent-heart-attacks-strokes). The University of Oxford team have previously shown that obesity may not be necessarily bad, and those patients with high body mass index may be “protected against cardiovascular mortality” because fat in the body may secrete protective substances. This is called obesity paradox and has major implications for the treatment of patients with heart diseases (Diabetes 2015, link to press coverage about the obesity paradox: https://www.telegraph.co.uk/news/science/science-news/11657811/Why-obesity-protects-against-heart-disease-and-heart-attack.html). The University of Oxford has recently identified a major therapeutic target for the treatment of heart diseases, and that discovery led to intense research to develop new drugs to modify this target (presented in the last European Society of Cardiology 2018 Congress, and received the Best Poster Award). The University of Oxford has recently develop a method to detect patients at risk for future heart attacks using the ox-HVF cohort (Science Transl Med 2017), which was validated in a recent publication (Lancet 2018). This method has been included into the recent Up-To-Date guidance (https://www.uptodate.com/contents/cardiac-imaging-with-computed-tomography-and-magnetic-resonance-in-the-adult) and can be used to detect patients who may need intense medical therapy to prevent future heart attacks. The University of Oxford group has developed a novel imaging biomarker (see Antonopoulos et al Science Translational Medicine 2017), namely the Fat Attenuation Index (FAI), which has been shown to be a marker of vascular inflammation at early disease stages. Validation of this biomarker in large cohorts of patients with residual cardiovascular risk showed that FAI is able to detect patients at high risk for cardiac mortality and is also predictive of non-fatal heart attacks. This permits reclassification of an individual’s risk, above and beyond the current state-of-the-art diagnostic tools, with strong implications for guiding medical management in patients and guiding the use of primary and secondary prevention measures. The development of this technology is a significant example that highlights the strength and unique ability of the Ox-HVF cohort in combining data across different and diverse fields - from clinical and epidemiological data to basic science and imaging data to outcome data (requested in the current application)- to create new, boundary-pushing ideas that promote health and serve the public interest. Of note, FAI was featured by iNews as one of the ten health innovations that could soon be on the NHS (https://inews.co.uk/news/health/the-ten-health-innovations-that-could-soon-be-on-the-nhs/). The University of Oxford has found that insulin treatment in diabetic people should be accompanied by medication targeting a specific molecule, which is regarded to be able to sensitize the human vessels to insulin signalling, in order to avoid damage to the heart arteries. Furthermore, they have shown that a molecule secreted from fat surrounding the human vessels, can trigger the development of damage and inflammation to them and therefore could constitute a promising therapeutic target.

Expected Benefits:


In summary, this data will be used to characterize the predictors of clinical outcome post cardiac surgery. This will allow for the identification of patients at risk and take measures to improve clinical outcome (survival and hospitalization rates) in this population.

The outputs of this research will be published in high impact peer review journals and will be presented in scientific congresses.

Due to the unique baseline phenotyping of these patients, the tested set of predictors for clinical outcome post cardiac surgery will provide a unique opportunity to understand the mechanisms affecting morbidity and mortality of these patients, and will lead to the development of novel therapeutic strategies to improve health care in this population.

Benefits:
1. The potential design of risk stratification models in primary and secondary prevention to improve clinical outcome at population level in cardiovascular disease
2. Identify high risk features that enable aggressive therapeutic strategies in high risk populations that can be implemented in to clinical practice.
3. Identify potential novel therapeutic targets involved in cardiovascular disease progression which will lead to future drug discovery.


Outputs:

The initial output will be a list of surviving cohort members which will be used to write out to participants with fair processing information and the opportunity to withdraw from the study. The list cleaning will help to ensure material is sent to only cohort members who are alive thus reducing the risk of causing emotional distress to family members of deceased participants. The study will then supply NHS Digital with a 'cleaned' version of the cohort for linkage.

The research outputs will include peer reviewed publications in leading international journals, presentations in scientific meetings and possible media reports.

Access to the data provided will be given only to the study investigators, within the University of Oxford, and no third parties will have access to this information. The study outputs will include publications in peer reviewed journals, presentations in international and national congresses.

The data will be used for research only and not be used to create indicators showing the performance of any organization.

All outputs will only contain aggregated data with small numbers suppressed in adherence to the HES analysis guide.

Outputs are expected 6-12 months after the data is received.

In summary:
Journals being targeted to submit to/publish in:
• The New England Journal of Medicine,
• The Journal of the American Medical Association,
• The Lancet,
• Circulation,
• Journal of the American College of Cardiology or The British Medical Journal.
Congresses targeted to submit to:
• Scientific sessions of the American Heart Association
• Scientific sessions of the European Society of Cardiology
• Scientific sessions of the American College of Cardiology
• Scientific sessions of the British Cardiac Society

Processing:


The data needed from NHS Digital are:

a) Fact of death data via list cleaning - this will be used to send an update to participants describing how data will be linked and providing withdrawal instructions.

b) The mortality data (including cause of death) from the day of surgery (provided) until today. Oxford will provide a list of NHS numbers so the mortality data returned should include the cause of death and the date of death for each individual patient

c) Similarly, hospitalization/admissions (that should include reason for hospital admission and the date, for each individual patient in the cohort).

Collection of this data is vital to obtaining the primary endpoint statistics linking the existing study data with post-surgery clinical outcome.

Only the named study investigators will have access to the record-level data, which will be stored securely in swipe-card-secured premises in the University of Oxford, in a password protected computer. No record-level data is being provided to a 3rd party and only aggregated data will be publicised/provided to 3rd parties.

The University will directly send NHS Digital a list of NHS numbers on the NHS Digital transferring system. An internal study number will identify subjects, and study details will not contain personal data such as names, NHS numbers or date of birth. The personal data that applies to a particular number would be kept locked separately away in the Division of Cardiovascular Medicine at the John Radcliffe Hospital.

The linking database will be kept on a high security password protected computer (to which only the study investigators will have access). Furthermore, the database computer will be kept in a swipe card-secured area of the Department (only authorized individuals have access to this area, and it is carefully controlled).

If applicable, information stored on laptop computers of the study investigators will contain additional password protection pertaining to relevant documents; this will be in addition to all computers being password protected. All data will not contain subject-identifiable material, and will be stored in a linked de-identified form.

The Investigators will be involved in reviewing drafts of the manuscripts, abstracts, press releases and any other publications arising from the study. No third parties will have access to the information as all analyses will be carried out within the University of Oxford, and no third organization will be involved.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

The applicant agrees to adhere to the Office for National Statistics terms and conditions as described in this agreement.

The data will only be used for the purposes described in this agreement.

No data will shared with 3rd parties.

No data will be used for commercial purposes.

OPtimising Treatment for Mild Systolic hypertension in the Elderly: a randomised controlled trial (OPTiMISE) — DARS-NIC-459340-M8R2R

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-07 – 2025-06 2023.02 — 2023.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Admitted Patient Care
  5. Civil Registrations of Death
  6. Hospital Episode Statistics Accident and Emergency (HES A and E)
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Yielded Benefits:

This is a new data request, so no benefits have yet been yielded.

Outputs:

All findings from the proposed research are intended to be published in peer-reviewed journals under an open-access license, with target journals including the British Medical Journal (BMJ), Journal of the American Medical Association (JAMA) Internal Medicine and Hypertension. Only aggregated data with small numbers suppressed in line with the HES Analysis Guide will be presented in published outputs. It is anticipated that the study findings will support better patient-centred management plans for the prevention of cardiovascular disease in older individuals and therefore will be available for the next iterations of the NICE hypertension and multi-morbidity guidelines.

The University of Oxford intend to present results at national scientific meetings (e.g. of the British and Irish Hypertension Society, Society for Academic Primary care, British Geriatrics Society) and international conferences (e.g., for the European Society of Cardiology, North American Primary Care Research Group). The University of Oxford will publish a summary of our findings on the study website (https://www.phctrials.ox.ac.uk/studies/optimise) and submit a final study report to the MHRA and ethics committee who provided approval for the study. Where appropriate, we will press release the results of the research in conjunction with their publication in scientific journals, and fully engage with any arising media inquiries that result. Social media (e.g. Twitter) will be used to draw attention to the work and stimulate debate, particularly when it is presented at conferences or published in the lay and scientific media.

Multiple channels of communication will be used to disseminate study findings including written feedback to study participants, plain English summaries, newsletters and community engagement events. We will work closely with our PPI representatives to ensure results are presented and disseminated in a patient friendly manner. An article discussing the issues raised by the research will be written for ‘The Conversation’, an online newspaper written by academics which is free and easy to read for the general public.

The University of Oxford will aim to present the findings of their analyses using these data at conferences in late 2022 and throughout 2023 and publish the final results in publications and online in early 2023.

Processing:

1. Participants who have consented to the OPTiMISE trial will have their data initially linked with the primary care data which is already held as part of ORCHID.
2. The University of Oxford will provide NHS Digital with a list of NHS numbers and date of births along with a unique Study ID for the OPTiMISE cohort.
3. A specific member of the University of Oxford IT team within the IT department will share the identifiers with NHS Digital, not the research team.
4. NHS Digital will send back to University of Oxford the pseudonymised, record level cohort data with Hospital Episode Statistics (HES), Admitted Patient Care (APC) and Accident & Emergency (A&E) data, Emergency Care Dataset (ECDS) data and mortality data included. Files will be sent securely back to University of Oxford via the Secure Electronic File Transfer System (SEFT).
5. University of Oxford will download and store the data within their secure ORCHID trusted research environment.
6. University of Oxford will process the pseudonymised data to meet the aims and objectives of the study (as detailed in ‘Objectives for Processing’). This will include matching the pseudonymised data from NHS Digital with the pseudonymised study data using the unique study ID. There will be no subsequent flows of data from the University of Oxford which has not already been suppressed in accordance with the small number suppression rules in the HES Analysis Guide.

Once data have been provided by NHS Digital, the University of Oxford will have no need to re-identify participants for the purpose of data processing. All patient identifiers are stored (securely and) separately from the main study database. Patient identifiers will be permanently destroyed at the earliest opportunity, in line with ethical and GDPR requirements and University policy.

The data will be controlled and processed by a group of substantive staff who are all based at the University of Oxford and under an employment contract. All staff are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Query Language (SQL) developers, Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) practice liaison officers, a project manager and a head of department. All staff will access NHS Digital data from secure workstations or secure laptops with encrypted drives within the group’s secure network. No data will be accessed outside of the location where the data is stored.

Analysis will be done by the clinical trials unit within the Nuffield department of Primary Care Health Sciences at the University of Oxford.

Improving outcomes for patients having shoulder replacements: guiding patient selection, evaluating cost-effectiveness and informing NHS provision — DARS-NIC-432598-Q6S0C

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-10 – 2024-09 2022.02 — 2023.01.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Outpatients
  5. Civil Registrations of Death - Secondary Care Cut
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)
  7. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

In this agreement, the University of Oxford requires Hospital Episode Statistics (HES) Admitted Patient Care (APC) and HES Outpatients (OP) data and linked Civil Registration (mortality) Secondary Care data for the purpose of a longitudinal, retrospective study to investigate temporal trends, geographic trends and variations in access for shoulder replacement surgery in the NHS. The study team wish to study the complications that follow surgery, and to predict the projected future burden of shoulder replacement surgery on the NHS which is crucial for service provision planning across the country for the next 25 years.

This study will be undertaken at the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS) at the University of Oxford. This study has been funded by the National Institute for Health Research (NIHR) through a Doctoral Fellowship Award and will attempt to answer key questions raised by patients, carers and researchers through the national 2015 James Lind Alliance Priority Setting Partnership. The study has also been endorsed by the National Director of Clinical Improvement for the NHS and the British Elbow and Shoulder Society (BESS). Further patient and public involvement through the Shoulder Research User Group (SHRUG) has reiterated the importance of this study to patients.

Shoulder pain is associated with increased health care utilisation and accounts for 20% of disability claims for musculoskeletal disorders. Degenerative shoulder osteoarthritis causes pain, functional limitation and disability and has an estimated prevalence between 4% and 26%. Patients with bilateral shoulder arthritis can rapidly lose function and be unable to self-care. Shoulder arthritis therefore leads to significant morbidity, particularly in an ageing population. Over 45,000 shoulder replacements were undertaken in the UK between 2012 and 2020.

Despite its high prevalence, there is ongoing treatment uncertainty with no high-quality evidence to guide the choice of the different shoulder replacements that are marketed. An evidence review conducted in 2009 (American Academy of Orthopaedic Surgeons) was published but unable to identify any strong evidence to support any of their 16 recommendations on shoulder replacement surgery. A 2010 Cochrane review reporting the effectiveness of different surgeries for shoulder arthritis determined that the overall lack of evidence precluded any conclusions being drawn about the benefit and safety of shoulder replacement surgery. In 2020, another Cochrane Review confirmed an ongoing lack of high-quality evidence on the topic of shoulder replacements. The 2020 NICE guideline on hip, knee and shoulder replacements further highlights the need for high-quality evidence to inform the surgical management of shoulder osteoarthritis and the need for clinical and cost-effectiveness comparisons between different types of shoulder replacements. With improving shoulder replacement outcomes being a priority for patients, there is an urgent need for better evidence and service planning in the NHS.

This project is aligned with the National Health Service (NHS) agenda. The NHS Improvement (NHSI) Getting It Right First Time (GIRFT) programme is dedicated to improving patient outcomes at a reduced cost to the NHS, by reducing regional variation in practice guided by evidence-based care. While other joint replacement procedures are undergoing service provision changes, much better evidence is now needed before any acceptable and effective national guidance for shoulder replacements can be made. Through this proposed project, researchers at the University of Oxford will gain an improved understanding of the burden of shoulder replacement surgery on the NHS now and in the future by analysing temporal trends, geographic trends, and any variations in access to shoulder replacement surgery based on population demographics.

This proposed project will form part of a larger research agenda on improving the outcomes of patients having shoulder replacements that will also include analysis of data from the National Joint Registry (NJR). This agreement containing the request for HES and Mortality data will specifically address one Work Package of the larger research project, namely the current and future burden shoulder replacement surgery on the NHS, including costs of shoulder replacement surgery and an analysis of any geographical variations or inequity of access.

While data from the National Joint Registry (NJR) collected as a part of the larger research project will provide useful surgery-specific information over a limited timescale, the HES and mortality data requested in this agreement will represent a more comprehensive dataset of NHS secondary care in England and enable a long-term follow up of patients having shoulder replacements allowing an assessment of complications, further surgery, as well as changes in practice, regional provision per population and any variations in access per population demographic. This will all inform future NHS service provision of shoulder replacements for maximum benefit to all patients and society.

The requested pseudonymised, record-level HES and mortality data will enable the research team to fulfil its aims and address patient and healthcare information needs. The NDORMS study team will explore how the change in service provision (number of surgeons and hospitals) corresponds to the demand for shoulder replacements. Trends in associated healthcare costs will be estimated through HES Admitted Patient Care as well as HES Outpatients data. Civil Registration (Mortality) data will enable analysis of the association between surgery and mortality and its temporal and geographic variations, including equality of access across England and across different patient groups.

NDORM’s lawful basis for processing data under GDPR has been reviewed and been assessed as acceptable. The University of Oxford process data under Article 6(1)(e): "processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller" as they are a Public Authority.

Additionally, the University of Oxford process the Special Category Health Data under Article 9(2)(j): "processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject" as the data are required for historical research purposes in the public interest. This research is in the public interest as there is very little high-quality evidence available to inform shoulder replacement service provision and workforce planning.

The University of Oxford is the sole data controller who also processes data. When the results of the study are made available, the study group will work closely with British Elbow and Shoulder Society (BESS) and NHSI GIRFT to improve translation of the study results into national policy. No record level data processing will be undertaken by these groups. All outputs will be aggregated with small number suppression applied as per the HES analysis guide.

This study will be funded by the NIHR who will publish summary details of the study on their website but will not be involved in data processing or decisions about data analysis.

Expected Benefits:

The University of Oxford hopes that this study informs NHS commissioners and healthcare professionals about the likely future burden of shoulder replacements on the NHS both in terms of cost and workforce planning. Key information about the geographic variation in surgical outcomes should help inform patient-choice and decision making as well as highlight modifiable organisational factors that will be useful to NHS commissioners to improve the service provision of shoulder replacements. NDORMS hope to work closely with NHSI so that the evidence from the temporal and geographic analysis of trends using HES data translates to improved provision.

This study forms part of a larger research agenda to improve the outcomes of UK patients having shoulder replacements as part of a surgical trainee’s doctoral thesis at NDORMS. Together with the current study, this overarching project aims to provide patients and clinicians with long overdue evidence to inform shared decision-making around shoulder replacement surgery with the aim of improving patient outcomes. It hopes to provide answers to key research questions raised by patients and the public through the James Lind Alliance Priority Setting Partnership (JLA PSP) and recent Cochrane and NICE evidence reviews.

The target date for the above outputs and dissemination that is expected to translate to measurable benefit is 36 months from receipt of the data.

Outputs:

Throughout this project the University of Oxford aims to actively engage with key stakeholders including NHS managers, professional bodies and patients and the public for results interpretation and dissemination. The research team at NDORMS has strong national collaborations that expect to facilitate effective dissemination of the research outputs to researchers, scientists and healthcare policymakers:

1. NHSI/Getting It Right First Time (GIRFT): A Professor of Orthopaedics (co-applicant on the study) advises GIRFT and has previously authored the new recommendations for provision of elbow replacement surgery in the NHS. The NHS National Director of Clinical Improvement fully supports this study so it is hoped it will gain high-level attention, enabling the results to directly translate to service provision changes on a national scale.

2. British Elbow and Shoulder Society (BESS): A Professor of Orthopaedic (co-applicant on the study) is President Elect for BESS and hopes to be able to facilitate the updating and authorship of BESS national guidelines depending on the results of the study.

3. National Institute for Health and Care Excellence (NICE): NDORMS expects to update NICE on any important findings which have the potential to translate to national change in clinical practice.

4. National Joint Registry (NJR): Two co-applicants on this study (a Professor of Orthopaedics and a Senior Research Fellow in Medical Statistics and lead data analyst for the NJR) work closely with the NJR. Dissemination to surgeons and the public will be supported by the NJR who reference important research projects in their annual report, NJR symposium at the British Orthopaedic Association, and through NJR patient information.

5. NIHR Oxford Biomedical Research Centre: Dissemination through the press, media and charities.

Researchers also hope to present the study findings at the below national and international conferences in the form of podium and poster presentations:

1. British Orthopaedic Association (BOA): This is the largest Orthopaedic conference in the UK and it is expected provide NDORMS with a platform to present the study results to all British Orthopaedic surgeons. This meeting is particularly well attended by Orthopaedic trainees and offers an excellent opportunity to create maximum impact on future consultant surgeons.

2. British Elbow and Shoulder Society (BESS): NDORMS hopes to disseminate the results of the study through BESS to all British shoulder surgeons in the form of conference presentations at the annual scientific meeting.

3. European Shoulder and Elbow Society (SECEC): Dissemination to shoulder surgeons on an international level

All outputs will adhere to the HES analysis guide with data being shown in aggregate form only with small numbers suppressed as per the HES analysis guidance.

Patient and Public Involvement (PPI):
NDORMS recognises the importance of meaningful PPI involvement and patients have been involved at all stages of this project. The importance of this study was identified and prioritised by patients and the public through their participation at the 2015 James Lind Alliance Priority Setting Partnership on shoulder surgery. NDORMS has already worked with patients from both the North (Shoulder Research User Group) and South (Oxford) of England to formulate this study plan including the larger research agenda on shoulder replacements. The study team have worked with the PPI Manager at the NIHR Oxford Biomedical Research Centre to identify patient representatives. The study team are setting up a patient advisory group for this study and a patient expert from the NICE Guidelines Joint Replacement Committee has already joined. The study team have collaborated with the PPI Senior Research Officer at the NIHR Research Design Services to make plans for effective dissemination of the study results so that they are easily accessible and interpretable to the wider patient community and to the public.

The study team plan to disseminate the study findings through scientific publications at peer-reviewed journals. These publications are expected to be open-access to maximise dissemination to the target audience of researchers, scientists, patients and the public. Open-access fees have been secured in the NIHR funding for this project. NDORMS hope to work with the new BESS Expert Patient Group to co-produce patient-friendly summaries including patient perspectives of the project results and infographics. NDORMS expect to publish a full and complete account of that research in the NIHR Health Services and Delivery Research Journal, ensuring the research is reported fully, and publicly available via the NIHR Journals Library website and Europe PubMed Central. A webpage is also expected to be developed within the NDORMs website for this study in order to improve dissemination of the results to the public.

Processing:

The University of Oxford will not be providing any patient data to NHS Digital but will provide NHS Digital with a list of OPCS codes for data minimisation. NHS Digital will link HES APC and HES OP data to Civil Registration Mortality data, preparing a pseudonymised, case-level dataset. This dataset will be transferred to the University of Oxford via Secure Electronic File Transfer Service (SEFT) and securely stored and processed as described below. Based on historical data and the projected number of shoulder replacements over the coming year (2021) the study team are expecting the resultant data extract cohort size to contain approximately 75,000 procedures (1998-2021).

The data requested is as detailed below – one drop of record level pseudonymised data:
HES APC data spanning the years 1998/1999 to 2020/2021,
HES OP data spanning the years 2003/2004 to 2020/2021,
Civil Registration (Deaths) Secondary Care Cut linked to the HES data spanning 1998/1999 to 2020/2021

DATA MINIMISATION
NDORMS has considered data minimisation and has taken the necessary measures to ensure the requested data is fully justified and limited to the required cohort. Details of these are outlined below:

- Datasets and linkages: The study is focused on patients who have had a shoulder replacement. The data required are limited to only hospital inpatient and outpatient episodes and mortality records for adult patients aged 18 years and over who have had a shoulder replacement since 1998 identified using the OPCS procedure codes code assigned to the hospital episode. The study team will provide a list of operation codes (OPCS) to ensure a minimised, yet sufficient cohort of patients are identified. The datasets requested are to be pseudonymised as this will enable the research questions to be answered least intrusively.

Civil Registration Mortality data linkage is required for two reasons. First, it is crucial to know whether a patient is still alive when undertaking survival analysis in such a longitudinal study. Second, it is important to identify the mortality rate following shoulder replacement or following a direct complication of shoulder replacement surgery. Both the cause of death as well as the date of death is therefore required, and the 23-year follow-up will enable researchers to produce the most accurate estimate of shoulder replacement burden and projected future burden to the NHS.

- Years and filtering: Complications after shoulder surgery including revision surgery for failing implants can occur many years after the index procedure, and the 23-year follow-up data requested will allow these events to be accurately captured. In order to most accurately analyse the temporal trends in shoulder replacement surgery, The University of Oxford are requesting long-term data covering 23 years. This will enable researchers to identify trends that occurred over a number of years which may correspond to changes in practice or the introduction of national guidelines. Having long term data is also critical to the production of the most accurate estimate of shoulder replacement burden and projected future burden to the NHS over the next 25 years.

Temporal trends spanning a number of years will also allow researchers to best forecast future costs and burden on the NHS. National (England only) data is required to identify geographic variation in the demand and provision of shoulder replacement surgery and to investigate whether deprivation has an influence on patients’ outcomes following shoulder replacement. It also helps to target the expansion of healthcare resources to the areas of greatest need in future.

- Episodes and fields: The study team require details of all the data subjects’ episodes of inpatient and outpatient care before the episode where they had their shoulder replacement (excepting Maternal episodes/birth episodes are not required as they are not relevant to this study) in order to gain a better understanding about their past medical history which may contain important information about risk factors for complications and revision surgery. Limiting previous episodes for the data subjects based on ICD codes may introduce bias and prevent the identification of important associations between risk factors and outcomes, so it is necessary to include all prior episodes. There is limited high-quality evidence to be able to confidently identify which risk factors are important predictors of outcome following shoulder replacement. It follows therefore that all previous patient episodes and code sets are required in order to ensure all true risk factors and associations are highlighted, and to prevent inadvertently discarding risk factors due to assumption. Furthermore, certain comorbidities may have been identified in patient episodes that may not be directly related to their shoulder replacement episode (e.g. medical comorbidities identified during a patient’s attendance for appendectomy). All subsequent hospital episodes for the data subjects are also required to ensure all inpatient and outpatient events that may be associated with the shoulder replacement procedure including revision surgery, hospital appointments and other treatments (however long after the index operation) are accurately captured and their costs accounted for to reflect the true burden of shoulder replacements.

DATA ACCESS
Once the pseudonymised data has been received by the University of Oxford from NHS Digital:
- The HES and Civil Registration Mortality datasets will be held on a password protected University of Oxford Computer on an encrypted drive in the Secure Data Room at the NDORMS Botnar Research Centre. NDORMS holds an up to date NHS Data Security and Protection Toolkit which provides data security assurance for processing and storing NHS data. Data will be encrypted to AES-256 standard as per IG07 NDORMS Confidential Data Storage and Destruction Policy.

All data will be processed only by substantive employees of University of Oxford. Access to the data will be restricted to named individuals working on the project and based at the NDORMS Botnar Research Centre who have received suitable training and will only access the data for the purposes described in this agreement. Those accessing NHS Digital data at NDORMS are required to take the University wide annual information security awareness module which is mandatory for all staff and students, and undergo an induction to the secure data room with the Information Governance Manager.

DATA ANALYSIS:
NDORMS will carry out statistical analysis to model the change in volume and secondary care costs of shoulder replacements over the 23-year period provided by the NHS Digital HES data. Correlations between variables will also be investigated such as disease prevalence and patient demographics. Geographic variations in outcome will be explored across hospital trusts and Clinical Commissioning Groups and the influence of these factors on a variety of outcomes (such as length of hospital stay, waiting times, revision and complications) will be highlighted. Variations in access to shoulder replacement surgery across different geographic area, different patient cohorts including levels of deprivation will be reported. Surgical volume will be projected for the following 25 years by applying age- and sex-standardised shoulder replacement rates to national (England only) population forecasts, a method previously applied to the projection of cataract surgery growth in Canada. This will be contrasted with different scenarios of projected growth in the service provision in England based on the analysis of observed trends from the NHS Digital HES data.

At the end of the study, the data will be safely held in a password protected University Computer at the Botnar Research Centre for 60 months and, in that time, it will be assessed only to answer questions arising from the publication and other publicity. The interim expected timeframe for completion of the data processing, production and dissemination of the outputs is 36 months, with a further 36 months retention of data after this to respond to changes based on peer review comments from journals and from funding bodies. An active data sharing agreement will be held with NHS Digital during this full data retention period.

All data will be processed only by substantive employees of University of Oxford who have been appropriately trained in data protection and confidentiality.

Data will not be linked to any other record level data. No attempts will be made to re-identify any individual from the data being supplied.

In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide.

UK Prospective Diabetes Study (UKPDS) Legacy Study: long-term follow-up of participants into electronic health records — DARS-NIC-265261-W7P8W

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7); Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2021-01 – 2024-01 2021.10 — 2022.12.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Critical Care
  6. Hospital Episode Statistics Outpatients
  7. Civil Registrations of Death - Secondary Care Cut
  8. Hospital Episode Statistics Accident and Emergency (HES A and E)
  9. Hospital Episode Statistics Admitted Patient Care (HES APC)
  10. Hospital Episode Statistics Critical Care (HES Critical Care)
  11. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Identifiable

Objectives:

The purpose of this application is to link participants in the UK Prospective Diabetes Study (UKPDS) trial to all death and hospitalisation health records in order to measure the effect of the treatments in this study on death, major medical illnesses, and costs of treatment.

The use of the data requested in this agreement is in accordance with Article 6(1)e as processing is necessary for a task carried out in the public interest. The aim of the study is to provide reliable evidence about the very long-term effects of blood pressure and glucose-lowering treatments on important health outcomes in people with diabetes. This promotes the public interest aiming to improve the treatment of estimated 5 million people with diabetes by the year 2025. Further details can be found on the UKPDS website (https://www.dtu.ox.ac.uk/OurTrials/UKPDSLegacy)

Processing of the data is in accordance with Article 9(2)(j) exemption, i.e. that the processing of the data is necessary for scientific research. The scientific aim of the study is to provide reliable evidence about the very long-term effects of blood pressure and glucose-lowering treatments on important health outcomes. This will help to inform people with diabetes about the long term consequence of blood pressure lowering and glucose lowering treatment, so they can make better decisions about their care. Further details can be found on the UKPDS website (https://www.dtu.ox.ac.uk/OurTrials/UKPDSLegacy)

The research team have taken the opinion of the South East Scotland Research Ethics Service (18/SS/0127), who have granted approval to the study in its current form, and of the Confidentiality Advisory Group (CAG) (18/CAG/0182).

The University of Oxford propose to link participants in the trial to their health data held within hospitalisation and death records curated by NHS Digital. By doing so, The University of Oxford will be able to determine the effects of higher versus lower blood pressure and glucose on future health and health care resource use. The University of Oxford will compare the incidence of major disease in different arms of the trial, in participants with different baseline factors (both clinical and genetic), and with difference disease occurrence during follow-up.

The UKPDS was a randomised, multi-centre trial of glucose-lowering and antihypertensive therapies in 5,102 patients with newly diagnosed type 2 diabetes that ran in 23 clinical centres for twenty years from 1977 to 1997.

UKPDS has been a major project, that has influenced diabetes guidelines in the UK and around the world (www.dtu.ox.ac.uk/ukpds). Both the Health Economic Research Unit and the Diabetes Trials Unit have a strong research interest in determining the effects of treatments for diabetes, and have published many influential studies.

The UKPDS trial investigators would therefore now like to evaluate the effects of the randomised treatments on dementia and other measures of long-term health. Therefore, the University of Oxford propose the extended follow up of all UKPDS participants into Electronic Health Records and other routinely collected health data.

The purpose of the project is to:

1. To determine whether participants randomly allocated to tight, rather than less tight, blood pressure control have a lower risk of dementia.
2. To determine whether participants randomly allocated to intensive, rather than conventional, glucose control have a lower risk of dementia.
3. To determine whether tight blood pressure control or intensive glucose control reduces the long-term risk of major vascular diseases in diabetes.
4. To determine whether tight blood pressure control or intensive glucose control reduces long-term health resource use and total burden of disease in diabetes.
5. To investigate use of health care resources in secondary care by patients with diabetes.

University of Oxford decided against requesting Mental Health data because it was not available for such a long time, and varied in coverage over the potential period of follow up. It was therefore determined that HES and mortality data will hold enough dementia data for the purposes highlighted above.

The study’s purpose is to examine the effect of baseline clinical variables on major health events, including major vascular events (including, but not limited to strokes of different types and myocardial infarction), cancers, renal disease and dementia. In order to ascertain these events, chiefly though ICD-10 coding. ICD-10 consists of a tabular list of diseases, the study team propose that it accesses hospital admission, and death records. The study team have found in previous work that the majority of cases of chronic disease (including dementia) can be found in admitted patient care, and death records. Data is needed on individuals in order to adjust for differing factors at baseline. The chief comparison will be between participants allocated to blood pressure and glucose lowering regimens and participants allocated to control regimens.


The University of Oxford propose that the linkage of individual participants by their identifying information (name, NHS number, date of birth, sex) should be performed by NHS Digital. The University of Oxford propose that NHS Digital return data to the university at the Nuffield Department of Population Health at the University of Oxford with each participant’s trial identity number with data from the linkage, i.e. a pseudonymised level of data.

The study team propose that to obtain data from each participant from the time they began to take part in the trial (the first participant was randomised in 1977) to the date of linkage. This will allow them to: (i) compare the occurrence of events recorded by the study during follow up with events recorded by Electronic Health Records; (ii) compare the very long-term incidence of major disease by randomised treatments and baseline factors. Further data releases will allow the study team to continue follow up into the extremely long term.

Participants were resident and recruited from across the UK, who may have moved between nations since recruitment, and therefore the data held will be linked across the country.

Linking participants to their data held by NHS Digital is the least intrusive way of achieving the stated purposes; in fact there is no other way that this could be performed without leading to considerable bias in the assessment of important outcomes. The University of Oxford believe that re-approaching participants for further consent would lead to potentially very large biases in ascertainment of major health conditions (because of non-responder biases particularly amongst those in poorest health, or have died), potentially lead to distress, and therefore have sought permission from the Health Research Authority (HRA) CAG for this linkage. The University of Oxford propose to link only to those datasets that contain information on medical diagnoses.

The Data Controller and Processor will be the University of Oxford. The Primary Investigator is employed by The University of Oxford. All processing of NHS Digital data will be within the University of Oxford. Analyses will be performed within the University of Oxford department the Nuffield Department of Population Health, by researchers within that department and researchers with contracts with that department. Advice on analysis and manuscript will be provided by researchers within the Diabetes Trials Unit. The project is funded by the Nuffield Department of Population Health.

The funders of the study and individual outside the study team will only have access to tabular data with small numbers suppressed. This so that people who wish to meta-analyse studies, who are currently not predictable (it may be no-one), are able to do so. The type of data that would be shared would be very similar to what would be in a published paper. Sharing this level of data is very important for openness of the scientific endeavour and would suppress small numbers.

Yielded Benefits:

The UK Prospective Diabetes Study (UKPDS) was a landmark randomised, multicentre trial of glycaemic therapies in 5,102 patients with newly diagnosed type 2 diabetes. It ran for twenty years (1977 to 1997) in 23 UK clinical sites and showed conclusively that the complications of type 2 diabetes, previously often regarded as inevitable, could be reduced by improving blood glucose and/or blood pressure control. The study has led to 118 manuscripts as of December 2020, covering many aspects of diabetes care (https://www.dtu.ox.ac.uk/ukpds/) The key benefits for patients with type 2 diabetes was to demonstrate that lower blood pressure and more intensive glucose control were of benefit. These treatments are the cornerstone of modern diabetes practice.

Outputs:

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide

The University of Oxford expect at least 3 publications to address each of the following questions:
1. To determine whether participants randomly allocated to tight, rather than less tight, blood pressure control have a lower risk of dementia.
2. To determine whether participants randomly allocated to intensive, rather than conventional, glucose control have a lower risk of dementia.
3. To determine whether tight blood pressure control or intensive glucose control reduces the long-term risk of major vascular diseases in diabetes
4. To determine whether tight blood pressure control or intensive glucose control reduces long-term health resource use and total burden of disease in diabetes
5. To investigate use of health care resources in secondary care by patients with diabetes

Once data is received, the University of Oxford expect that it will take between 2 and 3 years to deliver these analyses. The UKPDS trial investigators will publish these outputs in major clinical journals (e.g., Lancet, BMJ, Stroke etc.) and present them in international meetings by study end, target 2 to 3 years after a full dataset is received. It is anticipated these would contribute to national guidelines on reducing risk in people with diabetes, and will be communicated to charities (e.g., Diabetes UK) that are active in giving advice to people with diabetes.

The data will be aggregated with small number suppression in accordance with the HES analysis guide. The University of Oxford will not present data on individual participants. however, will present actual and modelled data in graphical and tabular format in line with the HES analysis guidelines on suppression.

The Diabetes Trials Unit and NDPH contribute widely to health policy, particularly in the area of vascular risk prevention. They contribute to debate with academic papers, conference participation, lectures to the public and advice to government (including NHS Digital). The University of Oxford will share all outputs through all of the listed channels: website and newsletters, open lectures and talks, exhibition at public events, posters, press/media engagement and other public promotion of the research, stakeholder mailing list.

Processing:

The Nuffield Department of Population Health (NDPH), University of Oxford will transfer participant identifiers with linked trial ID numbers to NHS Digital through a secure route approved by the receiving bodies. The entire UKPDS cohort (5102) will be transferred, in case of relocation of Scottish participants to England. The University of Oxford will receive data back to the Nuffield Department of Population Health in an encrypted format via NHS Digital encrypted transfer solution. The data will be encrypted during receiving, storage and processing. Each participant will be identified by trial identifier only at this stage, not with name, date of birth etc. The University of Oxford will construct a dataset from the original UKPDS trial dataset with covariates for this analysis, where each participant is identified only by the anonymised trial identifier, including baseline clinical, genetic, and event-based data. Data on individual participants held in the Nuffield Department of Population Health will be linked to data on the same individual provided by NHS Digital. Analyses will be performed with these data to achieve the stated scientific aims of estimating the effects of treatment in the UKPDS on major health outcomes, and health economic outcomes. All analyses will be performed using pseudo-anonymised trial identifiers.

All data will be transferred, handled and processed in agreement with the NHS Digital Data Sharing Framework Contract. Data will be received by the NDPH, University of Oxford. Using existing ICD-10 code lists for different clinical phenotypes, the study team will define the date and the nature of disease events for each participant. The study team will link the list of processed disease outcomes with existing datasets of baseline clinical, genetic and biomarkers data, and the occurrence of disease events within trial. Data are pseudonymised prior to analysis.

The Nuffield Department of Population Health, University of Oxford will link this dataset with the information received from NHS Digital with pseudonymised trial identifiers.

NDPH has successfully acquired analysed and appropriately stored data from HES for previous large long-term studies such as HPS2-THRIVE and HPS3-REVEAL. NDPH researchers are experienced in handling confidential and participant sensitive data and have appropriate training in Information Governance.

The NDPH servers are protected against unauthorised external access by an appropriate strength firewall. Access to patient identifiable information is protected by the appropriate authentication procedures (user IDs and passwords). Authentication is only given to personnel with a need to access the required data. Only personnel involved in the long-term follow-up study for UKPDS (processing and analysing data) will have access to this data, which will be members of the statistical and health economics teams NDPH has a Corporate Level Security Policy that has been fully adopted by management and will apply fully to the long-term follow-up study. The data protection Registration Number is Z575783X. NDPH investigators are fully aligned with all data management and security policies.

Identifiers will need to be retained whilst linkages are made between UKPDS datasets (the University of Oxford anticipate this will take up to a year) before all data are identified primarily with the study ID, in order to pseudo-anonymise the long-term follow-up dataset. We anticipate this will not be necessary, but if there are linkage problems, or inconsistencies in the data provided, the identifiers may need to be provided again to NHS Digital.

The study team will link data from individuals to existing trial databases, which hold information on the baseline clinical, genetic, biochemical, and Health Economic characteristics of participants, and in-trial health events.

Data processing will only be carried out by substantive employees of the data processor(s) and or data controller who have been appropriately trained in data protection and confidentiality.

No data will be stored at premises which are owned by an organisation which is not named in the agreement. All information is stored securely by University of Oxford and is kept confidential. Access to the computer database is by unique combinations of usernames and passwords and only authorised study personnel can access information about participants. The building is secure with authorised swipe card access only. No individuals will be identified in any study reports.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)”

There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.

Data will only be accessed and processed by substantive employees of University of Oxford and will not be accessed or processed by any other third parties not mentioned in this agreement

CPinBOSS Study - Cerebral Palsy in the British Orthopaedic Surgery Surveillance Study — DARS-NIC-324368-Q0H5T

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2021-05 – 2024-05 2022.11 — 2022.11.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The Cerebral Palsy in the British Orthopaedic Surgery Surveillance Study (CPinBOSS), funded by Action Medical Research (AMR), has been running since July 2019. This agreement requests HES data from NHS Digital for case ascertainment purposes. HES data is required to ensure that no potential cases that should be included in the study are missed. AMR will not have access to NHS Digital's Hospital Episode Statistics (HES) data/collected data from the study or specify any aims or objectives of the study. All people living with cerebral palsy, aged between 5-16 years, that have been referred for Single Event Multi Level Surgery (SEMLS) by either the treating clinicians or gait lab teams will be entered onto a database, forming the service evaluation aspect of the trial. The aim of the study is to undertake a national surveillance of this surgical activity encompassing all NHS Trusts in England. All of these patients and data are to come from participating NHS Trusts, which have appropriate Research & Development (R&D) and Sponsor approvals to participate within CPinBOSS. University of Oxford holds the data collected and only members of the CPinBOSS study team (all substantive employees of Oxford University) will have access to this database. The database will not be shared with any other institutions.

SEMLS is a surgical intervention that involves a minimum of two surgical procedures (bony or soft tissue) undertaken at a minimum of two different levels (e.g. hip and knee or thigh and calf) with the objectives to improve walking function within cerebral palsy patients. SEMLS has evolved over the past 30 years to replace repeated episodes of limited surgery. There are major differences between the Trusts that perform SEMLS in terms of patient selection and the choice of the specific surgical interventions. The primary objective of CPinBOSS is to identify the total number of patients that are eligible for SEMLS across all Hospitals in England, i.e. the incidence of children with cerebral palsy who fulfil the criteria for this type of surgery and to look at the variation in the surgeons’ criteria in selecting children for surgery by analysing the children’s clinical characteristics.

SEMLS operation would typically take a whole operating day of a surgical team. Therefore, any given surgical team is unlikely to be undertaking more than 4-5 such operations per month at the very maximum. The data collected from the recruiting NHS Trusts thus far support this estimate. With this in mind, it is highly unlikely that overwhelmingly large numbers will be involved. With the small numbers involved per centre it is expected that case ascertainment will be straightforward through comparison of HES and local PI submitted data.

This research was recently prioritised as one of the top-10 research priorities in children’s orthopaedics in a Delphi consensus amongst the British Society for Children’s Orthopaedic Surgery (BSCOS) members. The Delphi technique is a well-established approach to answering a research question through the identification of a consensus view across subject experts. This research was also prioritised in the top three topics at a recent James Lind Alliance Priorities Setting Partnership on paediatric lower limb surgery. The CP Cohort study is similar to the successful British Orthopaedic Surgery Surveillance Study (BOSS study), previously delivered in association with the BSCOS, confirming the feasibility of utilising this network for patient recruitment. The study design of CPinBOSS, including case ascertainment through HES data, followed the example of the BOSS study, which has now been completed successfully.

To undertake this national surveillance study, University of Oxford reached out to all NHS Hospitals nationally and invited participation by all clinical teams undertaking this type of surgery for children with cerebral palsy. A total of 24 NHS Trusts confirmed they undertake such surgery and were invited to recruit for the study. CPinBOSS has 19 NHS Trusts open for recruitment at the time of application (with a further 5 Trusts in current setup) across England. The recruitment period is from July 2019 – March 2021 with 2 years follow-up period. HES data is requested to provide case ascertainment, i.e. ensure that no cases are missed. It is particularly important for the case ascertainment to be national in order to capture cases undertaken in Trusts that have not formally declared this activity and are not recruiting for the study. This will enable the CPinBOSS research team to confidently report that CPinBOSS has captured national activity data with reasonable accuracy. If there are centres undertaking small volume activity and are not engaged with the clinical community, this would constitute important information for a national surveillance / service evaluation.

As the main objective of the study is to describe the incidence of the treatment across England , it is essential that University of Oxford do not miss any patients during the recruitment period. To ensure that University of Oxford have a full representative sample external sources will be used to check case ascertainment. Diagnostic CP codes will be searched within the Hospital Episode Statistics for England, the Patient Episode Database for Wales and the Scottish Morbidity Record and Cerebral Palsy Integrated Pathway Scotland (CPIPS) data (http://apcp.csp.org.uk/publications/cerebral-palsy-integratedpathway-scotland-cpips-dvd). The surgeon leads in hospitals with potential missed or duplicate cases will be contacted for confirmation. Only anonymised data will be reviewed.

HES data is requested for the recruitment period of the CPinBOSS study (July 2019 - Mar 2021) to ensure that University of Oxford have recruited all patients eligible for SEMLS. There are clear diagnostic (ICD) codes for diplegic cerebral palsy, these codes will be utilised to monitor hospital episodes throughout the study, which will be identified using the procedure codes provided.

The purpose of applying for HES data is to cross reference hospital admission for these patients with the information collected through the study. This will ensure that all cases of SEMLS are captured across England. In turn, this will contribute to the development of a comprehensive dataset which will reflect what is happening across the country with this patient population. Ensuring that University of Oxford capture all national activity in this clinical field and establishing the incidence of the condition is the central purpose of this study and cannot be achieved without the HES data. It is only with the cross referencing between data collected in the study with HES data that University of Oxford can ascertain complete case collection at national level.

University of Oxford are not seeking personal identifiable data, the request is for pseudonymised data. The data that is being sought will be utilised to identify NHS Trusts that have performed SEMLS over the specific recruitment period. The study team can then cross-reference with the recruitment statistics for CPinBOSS and identify if patients have not been included in the study. For example, the Oxford-based CPinBOSS Research group receive the HES data report indicating that in the first quarter of 2021 Hospital Trust X have undertaken 6 SEMLS operations. Trust X have provided the CPinBOSS research team data on 5 cases of SEMLS treated during the same period. The Study Coordinator of CPinBOSS contact the local PI at Trust X and inform them of the discrepancy in numbers, encouraging the PI to double check that no cases have been missed. No patient identifiable information is exchanged and only the total number of cases is discussed. There are then two potential outcomes: 1. The local PI at Trust X confirms that an extra case has been done but not included in the data provided to CPinBOSS. It is left with the local PI to encourage the local research team to upload the data of the additional case. The CPinBOSS team is no further involved with any chasing. No patient identifiable data are exchanged. 2. The local PI at Trust X confirms that NO extra case has been treated. The CPinBOSS team will then have no further involvement with this discrepancy. No patient identifiable data is exchanged.
Personal data will not be shared with the trusts in order to carry out this processing. Only counts will be shared.

All HES data will be held for 2 years post the end of the study (March 2025) so that research publications can be completed. It should be clarified here that a SEMLS operation would typically take a whole operating day of a surgical team. Therefore, any given surgical team is unlikely to be undertaking more than 4-5 such operations per month at the very maximum. The data collected from the recruiting NHS Trusts thus far support this estimate. With this in mind, it is highly unlikely that overwhelmingly large numbers will be involved. With the small numbers involved per centre it is expected that case ascertainment will be straightforward through comparison of HES and local PI submitted data.

University of Oxford and the CPinBOSS research team will conduct research following the General Data Protection Regulations (GDPR). Specifically, Article 6 1 (e) - Public Task and Article 9 2 (j) Archiving, Research and Statistics. Processing of the HES data is necessary for the research project to be conducted and will benefit the cerebral palsy population following dissemination of the peer reviewed published results, in line with Article 6 (e). In accordance with Article 9 (j) the research and statistical analysis is proportionate to the aim of the study and will respect the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

All data received from NHS Digital will be stored and managed by the University of Oxford (data processor and controller) and analysed by the trial statistician, a member of University of Oxford based at the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), on secure, password protected servers in a locked university building within NDORMS.

CPinBOSS is funded by Action Medical Research (https://action.org.uk/).

Expected Benefits:

The total number of SEML surgeries that are performed on a yearly basis in the UK with children with cerebral palsy is unknown and there has been no large scale data collection on this. CPinBOSS is aiming to answer this primary question through a service evaluation whilst recruiting all NHS Trusts that perform SEMLS across the UK. The primary purpose of the study is to describe the incidence of the condition through identifying all the children treated nationally over a period of 18 months. This aim cannot be achieved with data collection alone as this would rely only on individual sites/hospitals entering data voluntarily. This is likely to lead to selective reporting that would affect the reliability and credibility of the study. It is hoped that cross referencing the data collected directly from the hospitals by the research team to those recorded in HES would ensure that University of Oxford do not miss cases and that the collected data truly represent the English activity over 18 months. This data sharing agreement will allow the research team to identify whether patients are being missed and not enrolled in the CPinBOSS study. This would facilitate chasing sites to report any unreported cases.

CPinBOSS is primarily a service evaluation with the primary outcome of identifying the total number of cerebral palsy patients that undergo Single-Event Multi-Level Surgery across the UK. The CPinBOSS research team have opened 19 recruiting NHS Trusts across England to report the total number of operations performed on cerebral palsy patients that meet the study inclusion criteria. Within the service evaluation there is a nested consented cohort where patients are approached to consent to be identified by the CPinBOSS research team. The patients that are recruited for the cohort are approached and consented directly by the research nurses and local PIs at the hospitals. The Oxford research team are not involved in the consent process. The patients are seen at either the gait lab or in clinic and then are approached by the local PI/research nurses and invited to consent to CPinBOSS cohort. This is different from the dataset that will be provided by the DARS team. There will be no transfer of personal identifiable data to/from the local hospitals or NHS Digital. It will just be the total number of operations performed over a specific period at that NHS Trust/hospital which will be discussed between the local site and the CPinBOSS research team.

CPinBOSS is not altering the care of the patients at the local NHS Trust as the only difference between the consented cohort and the service evaluation is that parents/guardians and children complete a consent/assent form, baseline patient reported outcome measures (PROMS), and follow-up PROMS at 1 and 2 years. It is hoped that this will allow the research team to identify whether the patients have improved their walking and mobility functions post-surgery and whether they are happy with the overall treatment and care they received. The patients that are identified via HES data will be included within the service evaluation and not be approached for the consented cohort. This is because the research team would not have received baseline PROMS prior to surgery.

The secondary objectives are to review the regional variation in total number of operations and to describe the clinical indication and surgeon decision making in the surgical management of these patients. It is hoped this will enable the research team to answer these objectively and provide recommendations for best practice, agreed standards and prioritizing future research.

It is hoped that publishing papers in high impact peer-reviewed journals will increase the evidence base around SEMLS within the CP population. There is little known about the management of these patients across England and it is hoped that this research project and the anticipated published results will help to increase knowledge and promote future research within this field.

CPinBOSS also aims to instruct policy and to produce agreed frameworks on the management of all CP patients across the UK that have been referred for SEMLS. Currently, there are no agreed standards in the care and management of these patients. This is why this HES application is so essential for the research team to achieve its goals in providing agreed policies that would significantly benefit the patients and to standardise practice within the UK. It is hoped this will result in a more agreed and suitable patient management pathway so that patients will receive the best possible treatment with the most up-to-date research supporting this.

Outputs:

All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide.

The primary output from this HES application is to double check and provide case ascertainment that University of Oxford have recruited all cerebral palsy patients (aged 5-16 years with GMFCS levels I - III) that have had SEML surgery over the recruitment period (Jul 2019 - Mar 2021). This will be analysed by the statistician and reported back to the trial management team. The level of data received from NHS Digital will be pseudonymised data which will reduce the risk of identifying patients.

The data will be written up into a high impact peer-reviewed research papers, such as the British Medical Journal or the Bone Joint Journal, whilst being presented at National and International conference following the completion of the study.

The aim will be to present the project at the British Society for Children's Orthopaedic Surgery and The European Paediatric Orthopaedic Society conferences. This will enable the research team to provide an update on the total number of SEML surgery performed over the recruitment period.

The data gained from CPinBOSS and HES will be utilised to inform and instruct policy, guidelines and frameworks on how patients with Cerebral Palsy are have their conditions managed across all Trusts within England. There is a current lack of coherence between Trusts and one of the major goals of this research is to inform policy, standardise treatment and care across the UK. This policy decision making will take place through the professional body BSCOS and its educational committee. BSCOS will then produce guidance/policy on best practice in this area by setting agreed standards for SEMLS treatment within the CP population that would emulate the practices of the centres that produce the best results. This study will also help to inform feasibility and design of future trials. However, should clinical trials not be feasible, this study will provide definitive prospective comparison of conventional vs minimally invasive SEMLS vs natural history that should have major impact on clinical practice.

Prior to the final scientific write ups of the trial, results will be communicated through the CPinBOSS website, aimed at paediatric orthopaedic surgeons treating children with cerebral palsy as well as paediatricians and physiotherapists. Newsletters will be published during the recruitment period and can be found here: https://www.ndorms.ox.ac.uk/clinical-trials/current-trials-and-studies/cpinboss-study. The results will also be presented at British Society for Children’s Orthopaedic Surgery conference in March 2021, along with further national and international meetings. The CPinBOSS study team will liaise with the parent/patient organisations which have been engaged throughout the conception and design of this study (STEPS, Action Cerebral Palsy) to produce lay summaries and infographics for the wide dissemination of the results to this group of children and their families.

Processing:

This data application is trying to answer a specific question, how many cerebral palsy patients have SEML surgery across England, and the wider project including the whole of the UK. The data sought relates to specific lower limb surgeries that have been performed on patients with cerebral palsy aged between 5-16 years old with Gross Motor Function Classification System (GMFCS) levels 1-3. The GMFCS system is a 5-level classification that differentiates children with cerebral palsy based on the child's current gross motor abilities, limitations in gross motor function, and need for assistive technology and wheeled mobility.

The data applied for are specific products relating to type of surgery (multiple ICD codes), NHS Trust of where the operations are performed and the date of the operations. Due to SEMLS comprising of multiple lower limb surgeries and that there are no specific ICD codes for SEMLS, the application includes a large range of operations. The statistician and the Chief Investigator, both based at University of Oxford will be able to identify if the patients have received the specific type of surgery (SEMLS) based on this minimal dataset.

The data applied for is for record level data of Hospital Episode Statistics Admitted Patient Care, which includes the following:
• Date of admission – To identify when the potential patients who underwent multi-level surgery can be easily identified by the local hospital/Trust.
• Primary & secondary diagnosis codes – To allow the research team to confirm the patients meet the inclusion criteria for this study and they have diplegic Cerebral Palsy. The research team will then be able to contact the local site team to enquire whether a patient was missed during the recruitment phase of CPinBOSS.
• Date of operation and status - To identify when the missed SEMLS patients were admitted so local site clinicians can identify these patients.
• Total number of procedures per episode – To allow the research team to confirm the patients actually underwent Multi-Level Surgery. For the purpose of the CPinBOSS study the research team have defined SEMLS as the intervention that involves a minimum of two surgical procedures (bony or soft tissue) undertaken at a minimum of two different levels (e.g. hip and knee or thigh and calf). This field will facilitate whether patients meet this definition so should be included within the study.
• Duration of the episode and the type – To allow the research team to confirm the patients are indeed undergoing SEMLS
• What hospital/Trust performed the operation – To identify which Trust/hospital the operations were performed for the research team to contact and chase for details. This will also allow for a total number of operations performed per site.
• Patient data including Age – To ensure patients meet the inclusion criteria for CPinBOSS (5 – 16 years old). Patients that fall outside of this age range will not be required within the CPinBOSS study.
• Ethnicity & Sex– To ensure that the patients that undergo SEMLS are representative of the general population and there is not selection bias based on specific ethnicity or sex.
• Socio-economic including Index of Multiple Deprivation – To ensure the patients that undergo SEMLS are representative of the general population and that there is not selection bias based on socio-economic status. This can be used to identify whether only a certain population is operated on.

Demographic data are requested to ascertain that the sample is representative of the general population and that patient selection is not biased by demographics, in other words that surgery is not predetermined/biased based on a specific ethnicities or sex of patients. The data request has been minimised and is targeted to a specific population that has lower limb surgery. This population includes children, aged 5-16 years old, with cerebral palsy (GMFCS levels 1-3) that had lower limb surgery, within England, over the course of the recruitment period of CPinBOSS (July 2019 to March 2021).

The data application applies for a one-way data flow (i.e. from NHS Digital to University of Oxford). All data received from NHS Digital will be stored and managed by the University of Oxford (data processor and controller – data stored on University of Oxford servers only and these are backed up daily) ) and analysed by the trial statistician, a member of University of Oxford based at the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), on secure, password protected servers in a locked university building within NDORMS. All members of the CPinBOSS team have appropriate Good Clinical Practice (GCP) certificates and are appropriately trained in data protection and confidentiality. The Chief Investigator (CI) will oversee the whole project and the statistical analysis ready for dissemination. The data will be held for 2 years post end of the study for publication purposes.

Once the data is processed and provided to the research team, the statistician will identify the sites that have performed SEMLS and the total number of patients operated on during the previous quarter. This will provide the research team with in-depth knowledge of total number of SEML surgeries conducted at different hospitals across the UK. The research team cross-check number of patients recruited by each site to the HES data to identify whether the CPinBOSS trial has captured all patients that have had SEMLS over the recruitment period. Without the HES data University of Oxford cannot ensure that a full national representation of the incidence of this condition is collected.

There will be no attempt made to reidentify the patients from the data supplied by NHS digital under this agreement.

If the figures are different between the numbers that the Trust has specified and the numbers coming from HES, it would highlight potential missingness to the designated individual Trust identifying patients for the study. Based on the minimal dataset provided by HES it is likely that the treating clinicians, would be able to identify if the case is truly missing, or if it is a coding error. If truly missing, then the CPinBOSS team will prompt the local Trust team to enter the case details. If a coding error, the Trust team would be asked to highlight this to the study team. At no time would the study team (other than the individual's treating clinicians) be able to identify the individual. This would allow for a more detailed dataset and able to identify all patients fulfilling the inclusion criteria at participating sites across the England. This will ensure that the study result offers a reliable estimate of eligible participants, and ensures that the dataset represents the true sample of participants - to ensure that the results are widely generalisable, without bias emerging through missingness.

Security Assurance from University of Oxford Information Governance Team:
• As described in the Data Security and Protection toolkit, a list of all systems for storing or processing NHS Digital Data are on the asset register which is monitored regularly by the Information Governance Manager and The Research Centre IT Manager. The University of Oxford statutes include regulations relating to the use of Information Technology systems.
• Appropriate information security controls are implemented to protect all IT facilities, technologies and services used to access, process and store University information. The IT security baseline consists of approximately 80 specific requirements covering the following domains: Access control, System Acquisition and Development, Change Management, Incident Management, Monitoring and Logging, Network Security, Operational Security and Vulnerability management.
• The data from NHS Digital will be processed and stored safely and securely as per the Data Security and Protection Toolkit. Oxford University has a comprehensive Information Security Policy and all members of NDORMs are expected to abide by the departmental Information Security Policies

The data from NHS Digital will not be stored on cloud solutions at any time.

The department has a comprehensive policy and procedure for reporting breaches

Data will be processed and stored within University of Oxford servers, which are backed up daily. No data is transferred off site at any time.

The HOME Study — DARS-NIC-113964-G3J0C

Opt outs honoured: No, Yes (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c); Informed Patient consent to permit the receipt, processing and release of data by NHS Digital, Health and Social Care Act 2012 – s261(2)(c); Other-S261(5)(d), Health and Social Care Act 2012 - s261(5)(d); Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c); Informed Patient consent to permit the receipt, processing and release of data by NHS Digital; Other-s261(5)d, Health and Social Care Act 2012 - s261(5)(d); Health and Social Care Act 2012 – s261(2)(c); Informed Patient consent to permit the receipt, processing and release of data by NHS Digital; Other-S261(2)(d), Health and Social Care Act 2012 - s261(5)(d); Health and Social Care Act 2012 – s261(2)(c); Informed Patient consent to permit the receipt, processing and release of data by NHS Digital

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2021-07 – 2024-07 2022.03 — 2022.10.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  2. Civil Registration - Deaths
  3. Emergency Care Data Set (ECDS)
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Hospital Episode Statistics Critical Care
  7. Hospital Episode Statistics Outpatients
  8. Mental Health Services Data Set
  9. Civil Registrations of Death
  10. Hospital Episode Statistics Accident and Emergency (HES A and E)
  11. Hospital Episode Statistics Admitted Patient Care (HES APC)
  12. Hospital Episode Statistics Critical Care (HES Critical Care)
  13. Hospital Episode Statistics Outpatients (HES OP)
  14. Mental Health Services Data Set (MHSDS)

Type of data: Anonymised - ICO Code Compliant

Objectives:

BACKGROUND – THE HOME STUDY:
NHS general hospitals have more than two million unplanned admissions of people aged 65 and older every year. These patients typically spend more time in hospital than those aged under 65. Prolonged hospital stays are known to be detrimental to older people and known to be caused in part by lack of attention to psychiatric problems such as delirium, dementia, and depression as well as psychological issues such as minor cognitive impairment or anxiety that may slow patients’ discharge from hospital. The University of Oxford Psychological Medicine Research group has developed a new approach to the identification and management of psychological problems (called Proactive Liaison Psychiatry or Proactive Psychological Medicine, PLP/PPM) which aims to reduce the time that older people spend in acute general hospital wards.

The HOME Study is a two-arm parallel-group randomised controlled trial. It aims to determine whether adding PLP/PPM to usual care reduces the time spent by older patients in acute hospital wards in the month (30 days) after randomisation (primary outcome), when compared with usual care alone. A number of secondary outcomes, including patients’ views of their length of time in hospital, their quality of life, their secondary healthcare use in the year post-randomisation and deaths will also be evaluated. The HOME Study will also determine the cost-effectiveness of adding PLP/PPM to usual care.

Participants in The HOME Study are adults aged 65 or over, who were admitted non-electively to a general hospital in Oxford, Exeter or Cambridge between May 2018 and March 2020. Recruitment to The HOME Study has now closed. Informed consent (or consultee agreement, in accordance with the Mental Capacity Act 2005, for patients who lacked capacity to consent) was obtained for trial participation.

AIM AND PURPOSE OF THIS AGREEMENT:
The aim of this agreement is to access the 'routine data' that participants have consented to the researchers using in order to complete The HOME Study.

The ‘routine data’ required are participants’ healthcare use in the year prior to recruitment, data on time spent in hospital in the month post-recruitment (trial primary outcome), healthcare use in the year post-recruitment (NHS secondary care resource use is a trial secondary outcome), and information on deaths (trial secondary outcome). These data are from the Hospital Episode Statistics (HES) Accident and Emergency, Admitted Patient Care, Critical Care and Outpatients datasets; the Emergency Care Dataset; the Mental Health Services dataset and the Civil Registration (Deaths) dataset.

These pseudonymised, record level data are the minimum required to analyse the secondary healthcare use and deaths of participants in The HOME Study, comparing the outcomes of participants allocated to PLP/PPM with those allocated to usual care. There are no alternative, less intrusive ways of achieving this purpose. It is important to receive the NHS Digital data described above as participants are likely to have received healthcare (and died) in different settings from those where they had their initial acute admission.

The data requested are limited to The HOME Study participants only and those variables required to address the study aims. As the aim is to collect data on specific individuals who are taking part in the study, the use of anonymised data is not feasible. The number of years requested and geographical spread of the data requested are defined by the HOME Study participants’ dates of randomisation and locations respectively.

ORGANISATIONS:
The University of Oxford (the study Sponsor) is the Data Controller responsible for determining the purpose and manner in which any personal data collected for clinical research are, or are to be, processed for this study.

The University of Oxford, the University of York and London School of Hygiene and Tropical Medicine are data processors for this study; researchers in these organisations will conduct statistical and health economic analyses.

The University of Oxford is a ‘public authority’, as defined in the Data Protection Act 2018, with a principal object of the organisation being research and its dissemination. The processing of identifiable personal data, including special category data, is necessary to carry out medical research that serves the public interest. The legal basis for processing personal data is: Article 6(1)e of the GDPR, ‘processing is necessary for the performance of a task carried out in the public interest’; and Article 9(2) j of the GDPR ‘processing is necessary for archiving purposes in the public interest, scientific or historical research purposes’.
The processing of sensitive personal data by The HOME Study researchers is in the public interest as it will provide information to guide doctors’ decisions about the care of patients and to guide policy makers’ decisions about NHS service provision. The processing is of medical data about particular individuals and will be related to their involvement in the randomised trial.

A number of other organisations are involved in the study but not in the processing any data disseminated under this agreement nor do they carry out any data controllership activities. These are: Oxford University Hospitals NHS Foundation Trust, Devon Partnership NHS Trust, Royal Devon and Exeter NHS Foundation Trust, Cambridge University Hospitals NHS Foundation Trust, Cambridgeshire and Peterborough NHS Foundation Trust (patient recruitment); University of Exeter, University College London, University of Nottingham, University of Manchester, University of Birmingham, Worcestershire Acute Hospitals NHS Trust (collaborators).

FUNDING:
The study is funded by the National Institute for Health Research Health Services and Delivery Research Programme. The funder has no role in the design or conduct of the study, and will not be processing or accessing any data.

Expected Benefits:

The dissemination of the data will allow the completion of The HOME Study, an NIHR-funded trial which is expected to have a large impact on the provision of psychiatric care for older people admitted to general hospitals in the UK and internationally.

Acute NHS hospitals have more than two million unplanned admissions of people aged 65 and older every year. The greater length of stay of older patients means that these admissions account for most of the available emergency bed days. The UK Department of Health set out a policy to shift care from hospitals to community settings. But despite this, the last decade has seen a large increase in emergency admissions, the majority of those being of people aged over 65, a trend likely to continue as the population ages.

Prolonged hospital stays are known to be detrimental to older people and known to be caused in part by lack of attention to psychiatric problems. The HOME Study aims to determine the effectiveness and cost-effectiveness of Proactive Liaison Psychiatry / Proactive Psychological Medicine (PLP/PPM) which is a new way of delivering psychiatric care for older general hospital inpatients that aims to address this problem of prolonged hospital stays.

The dissemination of the findings of The HOME Study is in the public interest due to the large benefits that this research could have for patient care. The trial results are expected to shape the decisions that are made about NHS investment in liaison psychiatry services. If the PLP/PPM intervention is effective and cost-effective, this model of care rolled out across the UK could improve the lives of the large number of older people admitted to NHS general hospitals every year, as well as saving NHS costs.

The use of NHS Digital data is fundamental to the achievement of the scientific aims of The HOME Study. The study protocol and analysis plan included the use of these data and all participants have agreed to their NHS healthcare data being used in this way.

The expected benefits include both a major contribution to our knowledge of how best to care for older patients in general hospitals, published in peer-reviewed journals, as well as information that could directly enable commissioners and policy makers to make decisions about NHS care. The knowledge that will be gained is expected to inform NICE guidance as well as the Royal College of Psychiatrists Psychiatric Liaison Accreditation Network system, which promotes the development of high quality, evidence-based, liaison psychiatry services and is linked to the Care Quality Commission’s new inspection regimen.

Outputs:

Over the year following receipt of the data (by the end of 2022), the findings of The HOME Study are expected to be published and disseminated as papers, reports and conference presentations.

The research is anticipated to be published in high impact peer-reviewed journals and presented at national and international conferences including those held by the Royal College of Psychiatrists in the UK, by the Academy of Consultation-Liaison Psychiatry in the USA, and the European Association of Psychosomatic Medicine in Europe.

It is hoped that the trial results will shape the NHS investment in liaison psychiatry services and will also inform the Royal College of Psychiatrists Psychiatric Liaison Accreditation Network system, which promotes the development of high quality, evidence-based, liaison psychiatry services and is linked to the Care Quality Commission’s new inspection regimen.

The trial is expected to also have major international impact. It is anticipated that the findings will be used by healthcare policy makers worldwide, in particular in the USA, due to the current substantial interest in developing liaison psychiatry services, including proactive service models, to meet the needs of older medical inpatients with multimorbidity.

The PLP/PPM intervention manual is intended to be made freely available to the NHS. If the trial results favour PLP/PPM we anticipate that the manualised intervention will form a framework for liaison psychiatry provision nationally.

A process evaluation-based commissioning and implementation guide is expected to provide key recommendations to service providers and purchasers, and form the basis for commissioning and quality assurance of services.

It is planned that the results will be made available to participants and the public on the study website. The HOME Study has a dedicated Patient and Public Involvement (PPI) panel, made up of people who have personal experience of being an older general hospital inpatient or being a caregiver for an older general hospital inpatient. The PPI panel members were actively involved in the development of the PLP/PPM intervention and the trial procedures as well as in training HOME Study research staff. The panel will meet with the research team to discuss the study findings and assist in their interpretation. They will also advise the team on how to best disseminate the findings and ensure that the results are clearly described.

The researchers intend to actively work with the University of Oxford communications team and the Science Media Centre (London) for assistance with effective dissemination of results via the press and social media.

The study team will also, when reviewing the results of the analysis, consider whether any change in individual facility visiting policies could impact the study, during and post the Covid-19 pandemic.

All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

The University of Oxford will provide identifiers (NHS number, date of birth, sex, name), a unique study ID and the participant’s date of recruitment to NHS Digital for consented participants in The HOME Study via a Secure Electronic File Transfer (SEFT).

The pseudonymised data requested from NHS Digital are from the Hospital Episode Statistics (HES) Accident and Emergency, Admitted Patient Care, Critical Care and Outpatients datasets; the Emergency Care Dataset; the Mental Health Services dataset (MHSDS) and the Civil Registration (Deaths) dataset, covering the period from May 2017 to March 2021. HES and MHSDS data will be minimised to the year prior to and the year post recruitment for each study participant.

The study manager at the University of Oxford holds the identifiable information for all members of the cohort, and will receive the NHS Digital data. The study manager has disseminated existing trial data (including participant study ID, date of birth and sex) for cohort members, obtained with consent/consultee declaration from their medical records and participant/proxy reports, to the relevant statisticians and health economists at the University of Oxford, University of York, and the London School of Hygiene and Tropical Medicine.

The study manager will disseminate subsets of NHS Digital data to the relevant statisticians and health economists at the University of Oxford, University of York and the London School of Hygiene and Tropical Medicine to complete the requisite analysis. There will be no requirement or attempt by data analysts at these organisations to re-identify individuals. Analysts will not be provided with participants’ names, NHS numbers or contact details. Existing trial data may be linked with NHS Digital data by analysts using the unique study ID where relevant to ensure participant information is complete and accurate for data analysis purposes.

The data requested will be used in the following ways:

Healthcare use (admissions, outpatient visits, Accident and Emergency attendances) in the year prior to randomisation and ethnicity – to describe trial participants at the time of their recruitment to the study.

Number of days spent as an inpatient in a general hospital in the month (30 days) post-randomisation – to compare the outcomes of participants allocated to PLP/PPM with those allocated to usual care. This is the trial’s primary outcome.

Healthcare use (admissions, outpatient visits, Accident and Emergency attendances) in the year after randomisation- to compare the outcomes of participants allocated to PLP/PPM with those allocated to usual care and to determine the cost-effectiveness of PLP/PPM compared with usual care.

Deaths - to compare the outcomes of participants allocated to PLP/PPM with those allocated to usual care.

Statisticians at the London School of Hygiene and Tropical Medicine will conduct the analyses that describe trial participants at the time of their recruitment to the study and compare the outcomes of participants allocated to PLP/PPM with those allocated to usual care. Health economists at the University of York will conduct the cost-effectiveness analysis.

The data will be stored as follows:

The University of Oxford will store the data on Oxford University’s Medical Science Division IT’s High Compliance system (HCS). This is a service for Clinical Trials Units (CTUs) and Medical Sciences Division Departments or Units which need to access applications securely, and manipulate and store very sensitive data. The HCS is a controlled environment within which sensitive data can be manipulated and de-classified for further processing.

The London School of Hygiene and Tropical Medicine will store the data on the Secure Data Server which can only be accessed at London School of Hygiene and Tropical Medicine. The data will be accessible only to named HOME Study researchers who have authorisation from the applicant.

The University of York will store and access the data on the Safe Haven. The data will be accessible only to named HOME Study researchers who have authorisation from the applicant.

Data will only be accessed and processed by substantive employees of the University of Oxford, The University of York and the London School of Hygiene and Tropical Medicine, and will not be accessed or processed by any other third parties not mentioned in this agreement. Data will only be accessed for the purposes of HOME Study analyses.

The data will be safely held in an encrypted form on the University of Oxford Medical Science Division’s High Availability Novell network for 5 years.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

ATEMPT: Antihypertensive Treatment in Elderly Multimorbid Patients (Pilot Study) — DARS-NIC-414909-M5W6W

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: , Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-05 – 2025-05 2022.09 — 2022.09.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care
  4. Civil Registrations of Death - Secondary Care Cut
  5. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Expected Benefits:

An expected benefit of the ATEMPT pilot study aims to be an improved understanding of how to best manage blood pressure (BP) in older patients, in the presence of many underlying health problems, in particular when BP is not very high, and the effectiveness and safety of changing the number of prescribed antihypertensive drugs.

An additional benefit hope to be to understand the acceptability and tolerability of the intervention (using patient-reported outcomes) and to rule out any major excess harms (risk of serious adverse events) of managing BP in this way.

The findings from this pilot study are intended to provide the feasibility required to inform the planning of a larger, multinational, home-based study to assess the effect of treatment changes on patient-important outcomes. This trial could impact the treatment regime of millions of patients in the UK. The study is designed to minimise the burden of participation to patients. There is no need for clinic attendance. Participation and follow-up will take place at home using a bespoke IT system with much of the data collected remotely.

The experience of using bespoke IT-enabled systems to remotely recruit and monitor participants will, if shown to be effective, be considered for use in the recruitment and study management of other research trials. This could provide the means for other researchers to not only streamline research processes but also include participants in trials who historically are reluctant or unable to participate in research trials due to the demands made of them to attend research visits. For instance, research suggests that the vast amount of research findings are based on studies that have included participants in close proximity to specialised centres, men and those who have fewer comorbidities. This leaves a gap in research for the majority of the population in the UK to whom research findings are being applied. This study hopes to not only encourage participation of such patients but to assess the extent to which conduct of trials can be made more efficient and hence affordable.

Outputs:

The research agenda, plan of investigation and monitoring of the execution of the ATEMPT trial is overseen by a trial steering committee. The trial steering committee is made up of professional members including a Professor of Ageing and Stroke Medicine, a Professor of Cardiology, a GP plus two PPI members, individuals who are able to contribute to the wider public perspective. The main trial results from the ATEMPT Pilot Study are expected in 2022 with a publication towards the end of that year.

The results aim to be disseminated widely, including presentation at relevant conferences such as the European Society of Cardiology annual meeting and publication in an open-access, high-impact medical journal such as the European Journal of Cardiology. Further academic papers (including a protocol paper and results of remote recruitment and management of the trial) will be published in open-access, high impact, peer-reviewed journals and on the trial website.

A non-technical summary of the main study findings will be provided to participants and other interested groups and published on the study website (https://atempt.wrh.ox.ac.uk/).

All outputs will be aggregated with small number suppression applied (as per the HES analysis Guide).

The findings from this pilot study aim to be used to inform and plan an adequately powered major, multi-national Randomised Controlled Trial to start late 2022/early 2023. Additionally, the experience gained from utilising IT-enabled systems to remotely recruit and monitor participants will be evaluated with a view to expanding the use of the software to manage other research trials within the department and wider University. The online system for the ATEMPT trial has been developed in conjunction with members of the public aged 65 years or older in order to ensure that it is as simple and easy to use as possible.

Processing:

METHODOLOGY
1. The University of Oxford will send NHS Digital a cohort of approximately 221 consented individual records via Secure Electronic File Transfer service (SEFT). These specific identifiers will be provided according to when the study participant was consented:
> Cohort participant consented between 19 December 2020 to 24 May 2021 will provide the NHS Number only (approx 67 records), along with Study ID, date of consent and withdrawal date (if applicable).
> Cohort participant consented between 02 July 2021 to present will provide name, postcode, and date of birth (approx 154 records), along with Study ID, date of consent and withdrawal date (if applicable).

This information will be requested in one dissemination of five years and 3 months of data (2017 up to end June 2022).

2. NHS Digital will use the cohort identifiers to identify and extract relevant data from Hospital Episode Statistics (HES) Admitted Patient Care (APC) and Civil Registrations (Deaths) Secondary Care Cut. NHS Digital will then remove all identifiers, leaving the Study ID.

3. NHS Digital will disseminate the record-level pseudonymised files to the University of Oxford via SEFT.

The record-level pseudonymised data from NHS Digital will be stored in the ATEMPT study database and not shared with any other organisations. The Personal Identifiable Data (PID) data the study collected from participants will be stored separately to the study data and the NHS Digital record level pseudonymised data within the study database. Whilst record-level pseudonymised data will be provided by NHS Digital, while the University of Oxford hold the identifiers for the cohort, the data is considered by NHS Digital to be potentially identifiable.

The study team makes every effort to ensure the record-level data from NHS Digital will remain pseudonymised, including using the Pseudo-Study ID to link with the ATEMPT study data. However, the Study Team point out that individuals would be re-identified if it was in the participant's interest, for example, in the case of an adverse event and for safety monitoring purposes. Re-identification would be on an individual basis and data shared only with the study participant.

Data is stored securely by the University of Oxford in a high compliance system (HCS), managed and owned by the University of Oxford, suitable for storing personal and special category data, and data can only be accessed by the ATEMPT Study Team members, who are substantive members of the University of Oxford plus one consultant under an appropriate contract with the University of Oxford, who have authorisation to access the data for the purposes described and have been appropriately trained in data protection and confidentiality.

Statistical analysis of the data will be performed using an appropriate statistical package. This will be carried out either directly in person or remotely via a University of Oxford owned remote device connected to the University's HCS, which requires a username, password and secure two-factor authenticator (Virtual Private Network or VPN). All data analysis will be conducted within the confines of the University’s secure server, and will not be downloaded to remote devices for storage or processing.

The record-level data released by NHS Digital will not be shared with any other organisation or used for any other purpose other than those stated in this agreement. NHS Digital data is not being matched or linked to publicly available data, nor being linked to other data sets held by University of Oxford which are not directly related to the ATEMPT study. The data received from NHS Digital will only be linked to data in the ATEMPT study database.

VIRTUS Holdco Ltd do not access data held under this agreement as they only supply the building for storage of back-up tapes. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. They are therefore not considered a Data Processor.

HES DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, you must make sure that:
· National-level figures only may be presented unrounded, without small number suppression
· cell values from 1 to 7 (inclusive) are suppressed at a sub-national level to prevent possible identification of individuals from small counts within the table.
· Zeros (0) do not need to be suppressed.
· All other counts will be rounded to the nearest 5.
Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

MR1460 - OxValve - Survival following a diagnosis of Valvular Heart Disease in a primary care population (OxValve-Survive) — DARS-NIC-135294-P7L0F

Opt outs honoured: No - consent provided by participants of research study, No - data flow is not identifiable, No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (NHS Trust)

Sensitive: Sensitive

When:DSA runs 2019-07 – 2022-07 2018.10 — 2022.09.

Access method: One-Off, Ongoing

Data-controller type: OXFORD UNIVERSITY HOSPITALS NHS FOUNDATION TRUST

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Civil Registration - Deaths
  5. Demographics
  6. Civil Registrations of Death

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

The main function of the heart is to pump blood around the body. There are four main valves in the heart which ensure the blood travels in the right direction. If the valves become narrowed or leaky, this can mean the heart functions less efficiently.

Valvular heart disease (VHD) occurs when one or more valves does not form properly before birth (congenital) or if they are damaged (acquired) during life. In the developing world, infections such as rheumatic fever are still prevalent and can cause valve damage. In the UK and other developed countries, the most common cause of VHD is degeneration - wear and tear - over time.

When the heart valves don’t work properly, the heart muscle may need to work harder to cope. If valves become narrowed (stenosis), more pressure is needed to force the blood through them, and if they become leaky (regurgitation), more blood flows back into the heart chamber and needs to be pumped out again.

Over time, VHD can cause the heart to stop working properly. Some people may experience symptoms such as breathlessness, chest pain or passing out, while for others, problems with their valves will not cause them any difficulties. The treatment for severe VHD is surgery but this has risks. Identifying people who need to have an operation to deal with symptoms, or prevent future problems, and are well enough to have the procedure, is important.

The burden of VHD in the community population was poorly understood and therefore a cardiology team at the Oxford University Hospital NHS Foundation Trust embarked on finding out how common VHD was in the older population. In 2009, the team started the OxValve study with the aim of screening people age 65 years and over from primary care to determine how many participants had VHD. The study received ethical approval from the Southampton and South West Hampshire Research Ethics Committee (REC ref. no. 09/H0502/58) under consent versions 1 to 7 which was used to recruit 4,009 participants in total between 2009 and May 2016. Each participant underwent detailed examination including echocardiography to establish the presence, and severity, of VHD.

The findings of the first 2,500 participants were reported in the European Heart Journal in 2016. VHD was found in 1,269 participants (51% of the cohort). Most VHD was mild with only 159 participants having a new diagnosis of clinically significant disease (12.5% of those with VHD, 6.4% of the OxValve cohort). The cohort is currently undergoing a 5 year follow up where participants are asked if they are willing to be rescreened.

The long-term outlook for people with VHD is not fully understood. It is not known how long people with VHD, detected at screening, live for and whether they die from heart-related problems or something else. The OxValve-Survive study aims to report the survival rates of people in the OxValve cohort with and without VHD. The study will provide estimates of one, five and ten year survival, and the cause of death.

The cardiology team at Oxford University Hospital NHS Foundation Trust are in working partnership with the Nuffield Department of Primary Care Health Sciences (NDPCHS) at the University of Oxford working with the primary care team at NDPCHS which is leading on the primary care theme of the OxValve programme. Only individuals at the NDPCHS will do the data linkage and analysis for the data received from NHS Digital. The reason for this is that NDPCHS have expertise in survival analysis and experience with mortality linkage. The original OxValve team (at Oxford University Hospitals NHS Foundation Trust) will not be involved in processing the data for this purpose and will have no access to the data in its raw form. Oxford University Hospitals NHS Foundation Trust will only have access to aggregated reports with small numbers suppressed in line with the HES Analysis Guide.

Yielded Benefits:

The findings have been presented at the British Society of Cardiology conference. The OxValve study (at NDPCHS) are currently drafting a manuscript for submission to a peer-reviewed journal.

Expected Benefits:

The number of people with VHD in the community population of the UK was previously unknown. OxValve has given reliable prevalence estimates and is following participants up. However, the number of people in the cohort who have died, and their cause of death, remains unknown. This is important information to understand the natural trajectory of the disease and whether VHD found at screening is associated with higher mortality, or not.

A better understanding of prognosis could help inform patients, clinicians and commissioners. The limited data on survival for people with VHD can make discussions on outlook between patients and clinicians more challenging. Accurate mortality data linked to a well-phenotyped cohort could improve clinicians understanding of likely survival rates and causes of death for people with VHD. Commissioners of healthcare are also likely to be interested in the findings to allow them to provide appropriate surgical and palliative care services for this population.

Identification of risk factors for death in people with VHD may allow targeted treatment of modifiable risk factors. The findings from the study are likely to be relevant to other European countries where the prevalence VHD and risk factors for death are likely to be comparable.

Further scientific benefits include the contribution of the project to future systematic reviews and meta-analyses of risk factors for the prognosis of VHD. The findings of the study may also lead to future randomized controlled trials of treatments, and of interventions aimed to target risk factors, to improve the prognosis of these patients.

Outputs:

The OxValve-Survive study will report the one and five year survival rates of participants with and without VHD, and report the most common causes of death.

The findings will be presented at a relevant conference such as the Annual Scientific Meeting of the Society for Academic Primary Care or the British Cardiovascular Society Annual Conference. The choice of conference will depend on the timing of completion of the statistical analyses and deadline for submission of the abstract. Dissemination of the findings of the project at either of these meetings, will inform frontline clinicians that interact with these patients on a daily basis. This project will help to provide an evidence base to inform decisions that are likely to improve the quality of care for patients with VHD in the UK and similar countries.

The findings of this project will also be published in a peer reviewed scientific journal approximately one year after receiving the mortality data i.e., before the end of 2019. Target journals will include the British Medical Journal, European Heart Journal and the British Journal of General Practice. Depending on obtaining the necessary funding, the aim will be to publish open-access.

The findings of this project will also be disseminated through the OxValve study website, the Nuffield Department of Primary Care Health Sciences website, and through relevant social media channels. Through these platforms, clinicians, academics, media, patients, and the public will be reached.


All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide. ONS disclosure rules will be followed.

Processing:

The original OxValve study dataset is held at Oxford University Hospital NHS Foundation Trust. A copy of the full OxValve dataset is also held by NDPCHS at the University of Oxford and this dataset will be linked with the civil registration mortality data via NHS Digital. This contains the data of individuals who consented to participate in the study from 2009 onwards. Individuals recruited in the first year using consent materials version 1.1 did not give sufficient consent for their personal data to be shared with a body such as NHS Digital for the purpose of accessing their mortality data and no data will be requested about these individuals unless they provided additional consent subsequently.

The primary care team at NDPCHS based at University of Oxford will send NHS Digital; name, date of birth, NHS number, and the pseudonymised study ID for all participants who gave sufficiently informed consent. NHS Digital will match and flag the cohort and will return Mortality data (including Date and Cause of death) linked to the study ID. This data will be linked into the main OxValve study database at NDPCHS which only contains the clinical data (i.e. information collected at the screening appointment such as outcomes of ECGs, blood tests and self-reporting information). OxValve identifiers are stored separately. The data will not be linked with any other data and only the linkages described above are permitted under this Agreement.

The data will be stored on a restricted access network drive, with access restricted by password to the authorised user of the data only. Both the PC and network drive are on a secure part of the main University network with EAL4+ compliant perimeter firewalls. The wider University network is monitored and secured by the University OxCERT team. The local network and PCs are operated under the departments Information Security and Information Governance policies.

The data will be used exclusively for the purposes of the study specified hereby at University of Oxford only. The data will not be made accessible to any other 3rd parties, including Oxford University Hospitals NHS Foundation Trust.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

The Data will only be used for the purposes described in this Agreement.

EMPA-KIDNEY (The Study of Heart and Kidney Protection With Empagliflozin) — DARS-NIC-449860-L0D6W

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: Yes (Academic)

Sensitive: Sensitive

When:DSA runs 2022-05 – 2023-05 2022.06 — 2022.07.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Demographics

Type of data: Identifiable

Yielded Benefits:

This is a new Data Sharing Agreement. No data has yet been disseminated and there are as yet no yielded benefits.

Outputs:

The results of this research would be presented at relevant scientific meetings (e.g., the World Congress in Nephrology), in peer-reviewed journals, and as such should influence clinical practice. The main results paper will be submitted to the world’s leading medical journals (e.g., the Lancet and the New England Journal of Medicine (NEJM)). Lay summaries of important results will be provided on www.empakidney.org following appropriate review by ethics committees (where relevant). The REC committee includes lay members. If time allows (there are very short timelines between getting results and needing to distribute these), the PPI group will be involved in reviewing these.

The NDPH contributes widely to health policy, particularly in the area of vascular risk prevention. It contributes to debate with academic papers, conference participation, lectures to the public and advice to government (including NHS Digital).

The EMPA-KIDNEY study team will share outputs via the following listed channels:

- Study website https://www.empakidney.org/
- Open lectures and talks
- Posters
- Press/media engagement and other public promotion of the research (e.g. via the Nuffield Department of Population Health website (https://www.ndph.ox.ac.uk/), or Twitter account (@oxford_ndph).

The University of Oxford aims to issue the first main publication of results by end 2022.

Participants are kept informed about the study via newsletters, Participant Information Leaflets and the study website https://www.empakidney.org/.

All outputs will only contain results in highly aggregated format and as statistical summaries and measures of association. Reports will be in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

Processing:

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by ‘Personnel’ (as defined within the Data Sharing Framework Contract i.e., employees, agents and contractors of the Data Recipient who may have access to that data).

The list of identifiers that the EMPA-KIDNEY study team at the University of Oxford will send to NHS Digital are as follows:

• Study ID (pseudonymised)
• NHS Number
• Date of birth
• Postcode
• Surname
• Forename
• Sex

The data product the EMPA-KIDNEY study team have requested are as follows:

• Demographics (Study ID, Fact of death, Formal Date of Death, Informal Date of Death, NHS Number, Date of birth)

The data being requested includes historic data starting from 1st February 2019 to present to be received by the EMPA-KIDNEY study team as soon as possible, and then one additional drop of the latest data to be received on 11th July 2022.

NHS Digital will return the study ID and the following identifiers to the EMPA-KIDNEY study team for the purposes of validating linkage. This enables the study team to ensure that the linkage process is robust and accurate. These identifiers will not be used for analysis:

• NHS Number
• Date of Birth

The University of Oxford will retain the data until sites have confirmed any deaths that the EMPA-KIDNEY study team report to them. Identifiers received from NHSD will be destroyed after validation of deaths. NDPH will not be destroying the identifiers held directly from participants.

The data will be transferred from NHS Digital to the Data Controller’s (NDPH, University of Oxford) NHS DSP Toolkit compliant environment via the secure electronic transfer system (SEFT). All data will be transferred, handled and processed in agreement with the NHS Digital Data Sharing Framework Contract, and will be subject to Fair Processing requirements. No NHS Digital data will be transferred to BI.

The data received from NHS Digital will be used as follows:

• Information on deaths will be cross-checked with the trial database. If ‘new’ deaths are identified (i.e., deaths not previously reported by the site), the fact and date of death will be reported to sites to assist them with identifying deceased participants and find medical records relating to their death held locally.

• NHS Digital death data will not be entered into the trial database or used for analysis. In the event that an unreported death is identified, the site responsible for the participant will be prompted to check their records (which include access to the NHS Spine) and to report the death into the study database via the web-based system as they would do routinely for deaths reported in other ways (e.g., via a relative or other healthcare provider).

The EMPA-KIDNEY study team request linkage only to the dataset that contains relevant information on deaths, minimised to the cohort recruited during the period of 1st February 2019 to 11th July 2022. Filters can not be applied to the Demographic data set to minimise data from 1st February 2019, however the University of Oxford is only requesting details of deaths for participants who consented after that date. No other data fields are required for participants who are still alive.

All processing of data will be performed within the Nuffield Department of Population Health at the University of Oxford within an NHS DSP Toolkit compliant environment. No identifiable data will be shared other than with associated researchers working on this project, all of whom are substantive employees of the Nuffield Department of Population Health at the University of Oxford.

Access to patient identifiable information is protected by the appropriate authentication procedures (user IDs and passwords). Authentication is only given to personnel with a legitimate need to access the required data. NDPH has a Corporate Level Security Policy that has been fully adopted by management and will apply fully to this study.

Researchers will not link the NHS Digital death data to other datasets.

As part of the consent form, participants explicitly agree to the collection, storage, processing, transfer and use of their personal data as explained in the EMPA-KIDNEY Participant Information Leaflet.

NDPH researchers are experienced in handling confidential and participant sensitive data and have appropriate training in information governance. The NDPH servers are protected against unauthorised external access by an appropriate strength firewall.

All information is stored securely by the University of Oxford and is kept confidential. Access to the computer database is by unique combinations of usernames and passwords and only authorised study personnel can access information about participants. All authorised study personnel are substantive employees of the University of Oxford. The building is secure with authorised swipe card access only. There will be no attempts made to identify participants in any study reports.

EMPA-KIDNEY participants have consented for their personal data (i.e., their name, address, date of birth and medical information) to be accessed by the EMPA-KIDNEY study team, and for these details to be stored securely within the Nuffield Department of Population Health at the University of Oxford.

As detailed in the study documentation, participants give consent for their data to be shared with other parties including central registries, BI, and regulatory authorities. This data sharing will not include the NHS Digital data being requested in this Agreement.

Models of Resilience – Covid-19 and Non-Covid-19 Contexts — DARS-NIC-378657-B8F3K

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', , Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-06 – 2024-06 2021.12 — 2022.06.

Access method: Ongoing

Data-controller type: UNIVERSITY OF BIRMINGHAM

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. Emergency Care Data Set (ECDS)
  3. HES:Civil Registration (Deaths) bridge
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Hospital Episode Statistics Critical Care
  7. Hospital Episode Statistics Outpatients
  8. Civil Registrations of Death - Secondary Care Cut
  9. Hospital Episode Statistics Accident and Emergency (HES A and E)
  10. Hospital Episode Statistics Admitted Patient Care (HES APC)
  11. Hospital Episode Statistics Critical Care (HES Critical Care)
  12. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Birmingham is requesting data from NHS Digital in order to help them to determine the impact of hospital-level variation in organisational and clinical approaches to acute care delivery at the hospital/community interface during waves of COVID 19 (e.g., prescribing strategies, staff redeployment, integrated community care planning, etc.) on indicators of healthcare resilience such as (a) operational outcomes (e.g. acute care flow, discharge rates), (b) clinical outcomes for COVID-19 related conditions (e.g. mortality, readmission, rates of pulmonary embolism), and (c) clinical outcomes for non-COVID-19 health conditions (e.g. rates of new onset heart failure, stroke). The data requested will make it possible to study five comparative periods of analysis: (i) Pre-COVID-19, no winter pressures, (ii) Pre-COVID-19, winter pressures, (iii) COVID-19 outbreak peaks, (iv) Post-COVID-19 peaks, and (v) Concurrence of COVID-19 and winter pressures (season 2020-2021).

The surge of COVID-19 has had a profound impact on the management and delivery of acute healthcare. To tackle the epidemic, trusts have redesigned organisational models with changes in processes of assessment and care delivery, redeployment of staff, new pathways of care, and different prescribing strategies. These changes have been implemented to provide a rapid increase in acute care assessment and treatment capacity across a system of care for patients with COVID-19-related symptoms, whilst also trying to maintain delivery of care for patients with non-COVID-19 healthcare needs.

The purpose of this agreement is to determine the optimal design of the acute care interface with the community, by correlating hospital-level care delivery approaches elicited by the Society for Acute Medicine Benchmarking Audit data (SAMBA) and hospital and patient outcomes from HES data before, during, and after the COVID-19 periods.

The data requested will support the achievement of the aim of the project through the construction and analysis of indicators of hospital and healthcare resilience, which is defined as (1) the ability to deliver acute care for COVID-19, and (2) the ability to provide standard care for non-COVID-19-related conditions that can present with acute complications. Examples of resilience indicators include readmission rates, length of stay, mortality, intensive care unit admission rates, number of specialist visits, number of elective and emergency hospital admissions (for COVID-19), rates of heart failure (for non-COVID-19-related conditions).
The datasets from NHS Digital will allow the University of Oxford (University of Birmingham's sole Data Processor) to construct indicators of hospital resilience for COVID-19, and non-COVID-19-related conditions that can evolve and develop complications that require acute care (such as, e.g., heart failure, stroke, cancer) by:
- Following patients across different types of health services that they use before, during, and after COVID-19 outbreak periods;
- Accounting for multiple episodes of hospital attendance/admission and study readmissions for COVID-19 and non-COVID-19-related symptoms;
- Estimate out-of-hospital mortality for patients using data from the Civil Registry (Deaths) - Secondary Cut.
The requested data (years 2018 to 2021) will allow the data processor (University of Oxford) to study five comparative periods of analysis:
(i) Pre-COVID-19, no winter pressures
(ii) Pre-COVID-19, winter pressures
(iii) COVID-19 outbreak peaks
(iv) Post-COVID-19 peaks
(v) Possible interactions between COVID-19 and winter pressures (season 2020-2021).
Due to the novel setting and disease that this project studies, and the as yet unknown COVID-19 and non-COVID-19-related medical complications that the current pandemic may cause, there is a major exploratory element to this study. The uncertainty related to the object of investigation requires access to multiple sources of data such as HES critical care, A&E, Outpatients and Inpatients, emergency care (ECDS), as well as the civil registry of deaths (secondary cut). The data processor, the University of Oxford, will use the pseudonymised code provided by NHS Digital to follow patients across the different NHS Digital products that are requested in this agreement.
The University of Oxford will use the hospital code in HES to complement the analysis with information at the hospital and catchment area level from publicly available datasets and the Society for Acute Medicine's SAMBA survey of practice, which provides information regarding the size and staffing organisation of each acute medical department in the UK, alongside strategies for care delivery as well as methods of interaction with community care providers. In particular, the project will use SAMBA data from the 2018 and 2019 Winter version, and the 2020 COVID-SAMBA survey.
The Society for Acute Medicine (SAM) is the national representative organisation for acute health care staff. Formed in 2000, the Society now has over 1000 affiliates, the majority of which are doctors training or specialising in acute medicine. SAM delivers annual SAMBA audits to assess acute medicine approaches and the sharing of good practices. These are England-wide surveys at the hospital level and, in the UK, they are recognised by the Healthcare Quality Improvement Partnership.

The study that is subject of this agreement is part of a broader project, which has three operational tiers:
(i) The first part includes literature reviews, engagement with stakeholders and a survey of healthcare delivery practices of UK acute medicine units at the hospital level, based on the Society for Acute Medicine Benchmarking Audit (SAMBA). This part of the project will not use NHS Digital data.
The Principle Investigator (PI) of the overall project is an active member of the SAM (Society for Acute Medicine) network, has delivered three previous national surveys through the SAMBA network, and has published peer reviewed papers analysing key points from previous audits.
(ii) The second part of the project is the empirical analysis of hospital resilience based on the NHS Digital data that the University of Birmingham (Data Controller) is requesting in this agreement. This part will rely on developing quantitative econometric analyses of indicators of healthcare resilience for COVID-19 and non-COVID-19 diseases with acute complications constructed from the HES data. Examples of indicators of healthcare resilience include mortality rates, readmission rates, rates of pulmonary embolism, average length of stay in intensive care units, rates of new onset heart failure or stroke, rates of A&E attendances and emergency admissions for heart attack and stroke/transient ischaemic attack (TI), during and after the first COVID-19 wave.
Hospitals will be grouped by common approaches to organisation of care from the SAMBA survey (see (i) above). The trust/hospital/deliverer-level variables that describe care delivery approaches elicited from SAMBA will constitute the main explanatory variables. The analyses will control also for patients' demographics and comorbidities, and data on pre-COVID-19 organisational practices and healthcare needs of the patients and of the population in the trust/hospital/deliverer catchment area. The analysis will deliver aggregate-level results that do not identify individuals, and the publications will not identify hospitals. All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide.
(iii) The third part of the overall project will develop a qualitative study to learn about healthcare seeking behaviour among patients with non-COVID-19 severe disease. For example, this part of the project will develop focus groups to understand the reasons behind the reorganisation/postponement and delay of diagnoses (e.g., for cancer-related screenings and the screening and treatment of heart failure). This final part of the project will also include qualitative work based on site visits (or remote interviews) in well performing systems of care, to understand how novel structures and organisational contexts were successfully implemented and embedded. This part of the study will not involve analyses of NHS Digital data nor any linkage to NHS Digital data.

The analysis will control for underlying health conditions, healthcare needs, and characteristics of the population in acute care units and in their catchment areas. Information on different care delivery approaches at the hospital level will be elicited from a national survey of organisation and delivery of acute care, the Society for Acute Medicine Benchmarking Audit (SAMBA). The SAMBA dataset is described below. Importantly, SAMBA contains information at the hospital level and does not entail patient-level linkages.

The findings from this programme of research will enable policy makers within the Department of Health and Social Care and NHS England to determine how best hospitals and community systems should organise and deliver care during and after waves of COVID-19.

The GDPR legal basis for processing data for this research comes under Article 6(1)E – "task in the public interest" The data processing will provide evidence to help (a) policymakers make evidence-based policy decisions, (b) hospital managers to develop evidence-based decisions on the organisation of acute medical services, and (c) acute care clinicians to understand which practices have improved the resilience of acute care services.
The public interest that justifies the processing of this data relates to the improvements that can be made to health-care provision within the NHS as a result of the findings. The University of Birmingham is proposing to process data under point (j) of Article 9(2).

The 2020 version of SAMBA for COVID-19 (COVID-SAMBA) collects hospital-level information about variations in organisational and care delivery approaches during the COVID-19 outbreak, such as the degree of integration across acute/community healthcare providers (e.g., discussion of guidelines and common planning for the referral and management of patients with ambulance services, primary care providers, and care homes), novel care pathways (e.g. prescription and patient screening strategies, staff redeployment), and novel structures/systems of care (e.g. home-based hospitalisation).
With regards to the analysis for which the University of Birmingham is requesting access to NHS Digital data, the SAMBA surveys will provide information at the hospital level on care delivery approaches. SAMBA data will be linked to HES data using hospital site codes and not at the patient level.

After the onset of the current pandemic, the Department for Health and Social Care (DHSC) asked the project team to analyse pressures as a consequence of COVID-19, as this is an overwhelming national priority in acute care. In particular, following the research focus commissioned by the DHSC, this project defines the concept of hospital resilience as the ability to meet the acute healthcare needs of the population during COVID-19. The researchers will assess which organisational and care delivery practices are associated with improved healthcare delivery performance.

Other parts of the study, which are not based on the requested data and do not include data analysis, involve literature reviews, consultations with stakeholders, health professionals and patients, and qualitative work in a sample of acute hospitals. The University of Birmingham’s data processor, the University of Oxford, will process the NHS Digital data received and conduct a quantitative analysis for this project.

The University of Birmingham holds the main NIHR research contract for the overall study and has entered into an honorary contract with the Chief Investigator (CI). The CI will formulate hypotheses to be tested and help to interpret the findings of the overall study. Hence, the University of Birmingham is the Data Controller. It will not, however, be involved in processing the data. In its capacity as the University of Birmingham’s data processor, the University Oxford team will hold and process the NHS Digital data. The University of Birmingham are determining the means and purpose of the processing of the personal data and the University of Oxford are providing their expertise as the data processor but have no role in determining the means and purpose of the processing. The University of Warwick, where the CI now resides, will not be involved in any decisions about the data nor the analysis of the data.

The University of Leicester employs the researchers undertaking the qualitative component of the wider study, that is the third part of the study as described above. The University of Leicester team will not access, process nor control the data.

Department for Health and Social Care (DHSC) has no role in the conduct of the study. It is providing the funding (through the NIHR) and will receive the outputs. It is not involved in deciding which analyses should or should not be conducted.
The overall project, including the collection of SAMBA data and the cross-mapping of SAMBA with HES data, received ethical approval.

Since the study is not an evaluation of a specific intervention, the research approach is not based on a distinction between treated and control groups. Rather, the empirical design relies on correlations between hospital-level care delivery approaches and health outcomes. More specifically, the analysis will correlate indicators based on patient clinical information, mortality data from civil death registry with hospital-level indicators that identify relevant elements in the organisation of acute care delivery during and after COVID-19 outbreaks, elicited from the SAMBA survey.
As the data processor on behalf of the University of Birmingham, Oxford will inform the analysis using data from all attendances at A&E specialist or outpatient clinics or admissions between January 2018 and September 2021. This project requires information on all patients attending/admitted to the hospital, with information on the referral status, the cause of attendance/admission, inpatient/outpatient visits and outcomes, the length of stay, and the clinical health outcome for each episode/service use. The analysis will be conducted with pseudonymised data and no individual patient data will be released.
The purpose of this project is to understand which acute care delivery approaches developed and implemented before, during and after COVID-19 outbreaks translate into better acute care and health outcomes for the population, and to identify the practices best able to make hospitals more resilient when there is an outbreak of a disease such as COVID-19 or the winter flu. Combining SAMBA and HES data will allow the data processor, the University of Oxford, to achieve this aim. While SAMBA contains all the information relating to the processes of care implemented by English hospitals, HES data make it possible to investigate how these processes affect patients and hospitals.
This project requires data from the following data sets:
Emergency Care Data Set (ECDS)
Hospital Episode Statistics Accident and Emergency (HESA&E), non sensitive data
Hospital Episode Statistics Admitted Patient Care (HESAP), non sensitive data
Hospital Episode Statistics Critical Care (HESCC), non sensitive data
Hospital Episode Statistics Outpatients (HESO)
HES: Civil Registration (Deaths) - Secondary Care Cut link
The ECDS data requested is not currently within the TRE dat offering and thus this request can not at this point in time be fulfilled by the NHS Digital TRE service.

Using the pseudonymised identifiers provided by NHS Digital to bridge the products requested, the data analysis will connect patient's admission episodes across the HES products (inpatient, outpatient, critical care) and with (i) readmissions, and (ii) out-of hospital mortality (through the Death Civil Registry). As the data processor, the University of Oxford will analyse this information also in conjunction with hospital-level care delivery approaches from the Survey of Acute Medicine Benchmark Audit (COVID-SAMBA and 2019, 2020 SAMBA - please see point 4 of this section and the attached documents for a description) and with aggregate metrics of general health and population characteristics in the acute department's catchment area from publicly available data sources.

Due to the as yet unexplored and as yet unknown context of a novel disease outbreak, and because this project studies how COVID-19-related care as well as non-COVID-19-related conditions relate to different healthcare provision approaches, information on all symptoms and causes of hospital admission is necessary. As features of acute illness are often non-specific (e.g. confusion, generalised functional decline, reduced mobility among older adults), the project requires all available health information without restriction to specific conditions. In addition, there is no guidance yet as to which groups of patients have had fewer admissions due to COVID-19 and its overall effect on hospitals' ability to deliver care: therefore looking at all hospital admissions is the most inclusive and correct approach.
Hospital Episode Statistics Accident and Emergency data will allow the data processor, the University of Oxford, to identify whether patients that attend A&E are discharged or admitted, and to classify the cause of attendance (COVID or non-COVID related).
HES A&E (and the ECDS, once a code will be developed), HES-Outpatient, HES-Inpatient, HES-Critical Care will make it possible to:
- Follow patients that attend A&E/ the hospital/ trust in the subsequent stage (i.e., inpatient / outpatient / discharged), record their process of admission and outcome (e.g., length of stay and clinical health outcome);
- Control for the utilisation of primary care before and after an acute illness that requires A&E attendance or
inpatient/outpatient admission;
- Construct and correlate indicators of acute care resilience with organisational changes and care delivery practices during and after COVID-19 outbreaks (from the SAMBA hospital-level data).
Civil Registration Deaths - Secondary Cut will allow the data processor at the University of Oxford to link attending/admitted patients with out-of-hospital mortality outcomes.
In particular, the University of Birmingham is requesting the following groups of variables:
- Admissions - Period of care (e.g., method, source, date, waiting time) to control for different circumstances and procedures of admission in the analysis of the correlation between hospital-level acute care delivery approaches and average health outcomes, and group patients’ health outcomes by heterogeneous characteristics;
- Augmented/critical care period variables, with information such as time, period, outcome, source, discharge, status, intensive care, high dependency of patient’s admission episodes, to construct outcomes for the analysis (e.g., average time in intensive care, mortality, probability of high dependency case), controlling for further clinical and admission characteristics;
- Clinical information with date of operation, cause of admission, primary and additional diagnosis codes, operation status, and durations, to control for these elements in the analysis, construct health outcomes by specific circumstances/causes/etc. of admission, and duration of the episode(s);
- Clinical information regarding patient classification and consultant/treatment specialty, and Practitioner/Referring organisation codes, to categorise patients’ health outcomes according to specific treatment groups either by own classification or consultant specialty or practitioner;
- Diagnosis codes and Alcohol Attributable Fraction;
- Discharge dates and methods (and flags), to control for length of admissions and cross-validate precision of the duration, and study time lags between readiness for discharge and actual discharge, and their trends before, during, and after peaks of acute care activity;
- Episodes and spells (Period of care) data, such as dates, durations, types, ward types, and Patient Pathway information, to form groups of similar episodes and to control for such characteristics in the analysis of the correlation between care delivery approaches and health, mortality, and readmission outcomes;
- Geographical codes (e.g., CCG, area, region, site code of GP practice, treatment, residence areas, ONS electoral ward codes), Healthcare resource groups (HRG), Organisation codes/information, and Socio-economic indicators (location-based IMD indexes), to control for/group health outcomes by locations, and associate health outcomes to other local-level information from publicly available data at the trust/catchment area level;
- Patient demographic data, to group patients by categories or control for patient characteristics in the empirical analysis of the correlation between hospital-level care delivery approaches and indicators of health care resilience from patient health outcomes;
- System Data to verify validity of assignment of patient/CDS/SUS codes.
The specification of a COVID-19 diagnosis for patients will be based on the ICD-10 code.
This project only requires pseudonymised data, because the analysis will follow patients in the different services/units. The analysis requires patient level records to analyse health outcomes by different patterns of use of the healthcare services and to be able to group/control for demographic characteristics, waiting times, diagnosis, procedures, etc. Furthermore, patient record data will allow the empirical estimations to follow patients/episodes of care across the various NHS Digital products such as, e.g., deaths registry data, outpatients, etc., to measure healthcare outcomes, before, during and after the pandemic. The University of Birmingham does not request any identifiable or "high risk" variable, and the estimation outcomes and findings of this project will be produced solely in aggregate form, with small numbers suppressed in line with the HES analysis guide.

Nonetheless, the results of the quantitative analyses will only be included in the study outputs and communicated at an aggregate level. There will be no way to identify individual or critically small/selected groups of people from the results of the study all outputs will be aggregated in line with the HES analysis guide. The estimations will only deliver coefficients of correlation between care delivery practices and aggregate categories of health outcomes and indicators (e.g., total A&E admissions, mortality rate, total admissions in cardiology, ICU admissions, average length of stay by non-identifiable demographic characteristics such as age groups).
This data request is limited to the years between 2018 and 2021 inclusive.
This will allow the University of Birmingham to study five comparative periods of analysis:
Pre-COVID-19, no winter pressures (2018-2019, spring-summer)
Pre-COVID-19, winter pressures (2018-2019, winter)
COVID-19 outbreak peaks (2019-2020 winter and spring)
Post-COVID-19 peaks (e.g., July-August 2020)
Possible interactions between COVID-19 and winter pressures in the winter season of 2020-2021.

The quantitative analysis will compare the outcomes of patients in different hospitals and acute care units across England and, as such, it needs data concerning all English hospitals.
There exists no possibility other than via HES to construct and analyse variables that are based on following patients across different units of care, multiple episodes of admission, and out-of-hospital mortality at the hospital/acute care unit aggregate level. This project requires patient-level information also to account for patients' demographic characteristics, and prevalence of as yet not know preconditions and co-morbidities in the reference population that may contribute to determining the success and failure of hospital/acute care unit care delivery organisational approaches and practices in terms of both COVID-19 and non-COVID-19 related care.

The University of Birmingham has minimised the request in the time dimension. In particular, the required data is limited to the years between 2018 and 2021, ending with the release of September 2021.
Due to the exploratory nature of the project and as yet unknown consequences of COVID-19 and care delivery approaches during the current pandemic, the request is not restricted to specific health conditions and causes of admission. The aim of this proposal makes it necessary to request and explore individual-level data because this study is the first of its kind, and the context of the COVID-19 pandemic is as yet unexplored. This analysis will request and explore all possible conditions, causes of admission, and demographic characteristics. It is not possible to pre-aggregate and request health outcomes at the hospital level. This is required to understand the pathways of each individual in the use of the health system, in response to the COVID-19 pandemic, and to group outcomes by (or control for) demographic characteristics, waiting times, diagnosis, and procedures in the analysis.

The ethnic category variable is requested because there is evidence that people from BAME communities are the most affected by the COVID-19 pandemic and the analysis needs to control for this factor. This project requires only pseudonymised data and the request does not include any identifiable or "high risk" variable. The results of the quantitative analyses will only be communicated and included in the study outputs at an aggregate level, further suppressing critically small/selected groups of people.

The request is further minimised by excluding data concerning maternity and psychiatry.

The University of Birmingham is the sole Data Controller. University of Birmingham are determining the means and purpose of the processing of the personal data and the University of Oxford are providing their expertise as the data processor but have no role in determining the means and purpose of the processing. The University of Oxford operates under specific protocols for processing of data directed by the University of Birmingham.

The University of Warwick is not carrying out joint data controllership activities, in light of the Chief Investigator holding an honorary contract with the University of Birmingham, but being a substantive employee of the University of Warwick. The University of Birmingham will remain the only Data Controller, according to its original contract with DSHC and NIHR . University of Leicester employs the researchers undertaking the qualitative component of the wider study. They are not involved in the NHS Digital data processing.

The Department of Health and Social Care (DHSC) is the commissioner of this project. DHSC has no direct influence over the analysis performed and will have access to a final report of the findings but not the data used. The project funder is National Institute fir Health Research (NIHR).

Expected Benefits:

The anticipated evidence produced by this research is hoped will be directly relevant to
a) patients and NHS beneficiaries,
b) policymakers, planners and decision-makers, and
c) health providers, managers and practitioners.

The study hopes to produce findings on what changes in the organisational and cultural approach of hospitals are associated with better coping with Covid-19. These are hoped will be relevant for the development of policy, the organization of NHS acute medical services and the management of patients with COVID-19 and of patients with other conditions during national or local increases in numbers of COVID-19 patients. The dissemination of the anticipated study findings is hoped will enable the NHS to take measures to improve patient care based on evidence gathered on the topics studied.

The project and its dissemination strategy is designed to rapidly inform the Funder (DHSC) and engage in ongoing debates and policy reviews. The University of Birmingham and its project partners have worked with the Patient and Public Involvement (PPI) panel group, study Steering Group and the Funder to agree an engagement and dissemination plan at the start of the project, with activities running throughout its course. The anticipated outputs from the study are centred on informing policy and acute service provision. The University of Birmingham and its team will use its varied professional networks and professional social media presence to raise awareness of the outcomes of this study and maximise engagement with its findings. The external stakeholder group of this project, comprising representatives from the Royal College of Emergency Medicine, the Society for Acute Medicine, NHS Providers and Care England, will consider the anticipated research findings and where it is hoped these will inform potential service improvement or further resources that could help service provision.

It is hoped that the study will identify which organisational and healthcare delivery approaches minimise the impact of COVID-19 in the community, and will identify which practices support the ability to deliver routine care in COVID-19 times. The two focuses of this research project benefit the public interest because they may lead to improved health outcomes, via adoption by the healthcare community. It is hoped that the short-term findings on clinical strategies and organisational approaches associated with high performance in “peak 1” of COVID-19 will inform policy for acute hospitals and acute community providers for any subsequent outbreaks, whether these outbreaks are national or more localised.

Medium term benefits are hoped will be the identification of strategies to maintain ‘business as usual’ healthcare for both acute non-COVID-19 illnesses and serious longer term disease.
Both sets of results will be available to policymakers and health care providers and their guidelines will benefit the public interest and the community.

This project has been solicited by the Department of Health and Social Care (DHSC), to understand how the current pandemic is affecting the delivery of acute care and the delivery of routine care for conditions that may develop into acute complications. By investigating which care delivery approaches entail a better performance for patients with COVID-19 as well as non-COVID-19-related conditions, this project it is hoped will be able to directly inform policy and treatment for future waves of COVID-19, and similar pervasive public health emergencies, and to inform development of new standards of care delivery. The anticipated project outputs and results are hoped will directly feed into policymakers’ decisions. The project team will share the results also with the academic, scientific, and general communities with help from professional networks and by drawing on the team’s personal networks.

The project dissemination plan includes the following list of activities and tentative timeline:

AUTUMN – WINTER 2021:
- Main interim report (draft stage): findings of the COVID-19 related research analysis
- PPI panel meeting
- External Stakeholder Group meeting

WINTER 2021:
- Journal article, first draft: results of the COVID-19 SAMBA questionnaire findings
- Journal article, first draft: results of the quantitative analysis of hospital resilience

SPRING 2022:
- External Stakeholder Group meeting: presentation of the interim results
- PPI panel meeting: presentation of the interim results
- Workshop: presentation of the interim results
- Paper articles: submission to scientific/academic journals

AUTUMN 2022-SPRING 2023
- Final analyses and report writing
- External Stakeholder Group meeting, with a press release
- PPI panel meeting
- End of project dissemination meeting with a press release.
- Press coverage: blog articles, social media-based dissemination activities

It is hoped that with the help of Funder, advisers and stakeholders this project will make findings available to DHSC, NHS England, NHS Acute Trusts and professional organisations so that they can use them to inform their decision-making. The plans for dissemination are set out above.

The University of Birmingham hopes that the findings of this project should lead to improved decision-making by policy-makers, NHS managers and clinicians. While it is not certain in advance of conducting the study what specific decisions will be made as a result, the findings of this project will lead to improvements in the organization and management of acute medical care that will in turn lead to improved quality of care for patients and improved outcomes.

There is potential for large numbers of patients with acute medical conditions to benefit from improvements to their care based on evidence provided by this study. There is also potential for efficiency if improved care leads to better outcomes, including fewer emergency re-admissions and fewer patients experiencing deterioration of their condition resulting in need for more intense and costly treatment. The benefits will accrue to NHS acute services and ultimately to patients.

The benefits could be monitored through future surveys and future analyses of HES and other data sets, if DHSC decides to conduct or fund such monitoring. The University of Birmingham envisages that benefits will start to accrue soon after dissemination of the findings. This may depend on the specifics of the findings and on decisions by DHSC and NHS managers and clinicians informed by the findings.

The study does not support a PhD/post graduate research study.

Outputs:

Outputs from the study will include:
(a) Tables of HES-based information aggregated at hospital level with any small numbers suppressed (if there are any), such as number of admissions in period t of patients with condition X;
(b) Correlation or regression coefficients from analyses of hospital level data, such as correlation between operational practice X and proportion of patients with COVID-19 who died within 28 days; and
(c) Possibly a composite resilience index for each hospital calculated as a weighted sum of some of the hospital level data.
The project team will disseminate the research findings to patients, clinicians, professional bodies, and policy makers, and publish the aggregate results of the study in academic journals. The project will produce reports for the Department of Health and Social Care and communicate findings through webinars and conference presentations.


The results of this study will consist of the coefficient of correlation (or effect size) between an organisational or healthcare delivery practice and aggregate outcomes such as:

i. Operational outcomes (e.g. acute care flow, discharge rates);

ii. Indicators of healthcare resilience based on clinical outcomes for patients with COVID-19, e.g.:
• Mortality rates,
• Readmission rates,
• Rates of pulmonary embolism,
• Probability of readmission for suspected COVID-19,
• Average length of stay in intensive care unit;

iii. Indicators of healthcare resilience based on clinical outcomes for patients who do not have COVID-19, e.g:
• Rates of new onset heart failure or stroke,
• Total numbers and rates of A&E attendances and emergency admissions for heart attack and stroke/TI, during and after the first COVID-19 wave.

The researchers will not publish any disaggregated data or information about single individuals or critically small and identifiable groups of individuals. The University of Oxford will ensure that discrete variables cannot be used (either alone or in combination) to identify an individual. Tabulations and summaries of outcomes that may contain very small sample numbers in some cells will not be reported. Tables and other outputs will not be published in a form where the level of geography would threaten the confidentiality of the data.

The project team will disseminate the research findings to patients, clinicians, professional bodies and policy makers, as well as publish in academic journals. The evidence produced by this research will be directly relevant to:

A. Policymakers, planners and decision-makers;
B. Health providers, managers and practitioners.

The dissemination activities are designed with the goal of informing and supporting health and care policy through developing evidence that is crafted and presented with the policy user in mind, rigorous and authoritative, and timely.
The dissemination activities will include a one-day conference for key stakeholders at the end of the project, seeking their responses to study results. The project will ensure that a range of relevant organisations are included at the conference, such as professional societies, CCGs, service users, and carers. This event will be press released.

The project will inform practice at local and national level, leveraging the national roles of co-applicants and collaborators to ensure a wide dissemination to policy makers, relevant Policy Research Units, and professional societies. The project will disseminate findings of hypotheses of health system resilience through practice networks, professional societies and ALBs.
The project will raise public awareness by producing lay summaries of the results in accessible formats, including through webinars and blog entries, which will ensure a broad dissemination thanks to the extensive resonance of the network of universities and stakeholders involved in the project.

The project team will leverage the national roles and visibility of its co-applicants, collaborators, and funding partner to ensure a wide dissemination of the products of the research to policy makers in ALBs (NHS Improvement, Getting It Right First Time, Health Education England) as well as relevant Policy Research Units (Commissioning, Older people and Frailty) and professional societies (British Geriatrics Society, Society for Acute Medicine). The project team will disseminate the findings of this exploration of best practices in acute care delivery and health system resilience in COVID-19 times through practice networks, professional societies and ALBs (Arms Length Bodies)

To raise public awareness, this project will produce a summary of the results in an accessible format with the help of the PPI Panel and distribute it to a range of stakeholders, e.g. the NHS, commissioning groups, policymakers and service users. The University of Birmingham and its data processor, the University of Oxford, will ensure that the research is synthesised and communicated in a meaningful and clear way, such that the results of this study can be employed by all beneficiaries in practice to deliver real healthcare benefits.

The results and outputs of this project do not involve the development of tools, technologies, algorithms, or any similar instruments that may entail issues related to data and knowledge ownership, management, rights, and access.

Target date for the preliminary analysis of acute care delivery during COVID-19 outbreaks: late Summer 2021
Target date for the preliminary analysis of acute care delivery during COVID-19 outbreaks and winter pressures (possibly occurring in winter 2020-2021): Autumn 2021 - Winter 2021/22
Target date for the final analyses, report writing, end of project dissemination meeting, and press release/press coverage: Winter 2022-Spring 2023.

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract, i.e.: employees, agents and contractors of the Data Recipient who may have access to that data)”

No data is flowing into NHS Digital. The analysis will employ the requested data solely in its pseudonymised form. The ethnicity data flowing is not identifiable but is a sensitive field. The research team will not publish any individual-level or identifiable information, with patient level HES data used solely to produce a range of aggregate variables for each hospital and to produce information for healthcare resilience indicators. The results of the analyses will be disseminated in aggregate form (e.g., the mean value of a clinical outcome and its standard deviation), with small numbers suppressed in line with the HES analysis guide and the publications will not identify hospitals by name.

The organisation responsible for data processing is the University of Oxford. As the University of Birmingham’s data processor, the University of Oxford will analyse the correlation between hospital-level care delivery approach variables (from the COVID-SAMBA data) and HES-based indicators of healthcare resilience (e.g. readmission rates, mortality for COVID-19 related symptoms, length of stay in Intensive Care Units (ICU), etc.).

This project will develop a dashboard of indicators at the hospital level including information relating to care delivery approaches (from the SAMBA survey) and aggregate baseline acute health and frailty outcomes. These measures will be correlated with healthcare resilience indicators from the NHS Digital data using site-specific codes (i.e., hospital identifiers). As the University of Birmingham’s data processor, the University of Oxford will process that data. It will not link the requested NHS Digital data with any other data at individual patient level. The analysis will be based solely on information at hospital level derived from the requested HES data and hospital level information from other data sources, in particular with SAMBA survey data, but this will not involve any linkage at patient level.

HES data will be used exclusively in its pseudonymised form. The analysis will follow patients across the requested NHS Digital datasets using only pseudonymised codes, such as the Encrypted HESID. The data will not be linked to any other data about individual patients.

As the University of Birmingham’s data processor, the University of Oxford will add to the analyses at hospital level the SAMBA data, which is collected at hospital level from a survey of clinical practice, without any patient data. The project will use COVID-SAMBA and 2019, 2020 regular SAMBA datasets. In addition, the project will add site-level information from a range of publicly available data for hospitals, Commissioners of Health and Social Care and local authorities, using site codes.
The datasets are:
- Office for National Statistics (ONS) data (population aged 65+, IMD of area, rurality index), https://www.ons.gov.uk/;
- NHS workforce statistics (hospital staff, community staff, primary care staff) by CCG, https://digital.nhs.uk/data-and-information/publications/statistical/nhs-workforce-statistics ;
- NHS Digital NHS Outcome Framework (https://digital.nhs.uk/data-and-information/publications/statistical/nhs-outcomes-framework) ;
- Adult Social Care Outcome Framework measures https://digital.nhs.uk/data-and-information/publications/statistical/adult-social-care-outcomes-framework-ascof ;
- Skills for Care data on adult social care staff by LA, https://www.skillsforcare.org.uk/adult-social-care-workforce-data/Workforce-intelligence/publications/Data-and-publications.aspx;
Care Quality Commission (CQC) data on ratings of hospitals, https://www.cqc.org.uk/about-us/transparency/using-cqc-data; and
- NHS England SitRep data on hospital performance, closures, and bed pressures, https://www.england.nhs.uk/statistics/statistical-work-areas/winter-daily-sitreps/ .

The datasets include only variables that are aggregated at the hospital level or catchment areas and there is no identification of any patient.

There is no requirement for the study to re-identify individuals for this project and the University of Birmingham and its data processor, the University of Oxford, confirm that no attempts will be made to re-identify individuals.

As the University of Birmingham’s data processor, the University of Oxford will process the data received. This team resides at the University of Oxford, Nuffield Department of Primary Care Health Sciences (NDPCHS). All researchers and staff at the University of Oxford follow specific protocols for the protection and confidentiality of the data. All team members are also subject to training on these requirements initial upon start at the Department and annually thereafter. This team will retain the data on a secure, network server and limit access to only those researchers approved to access it via an encrypted remote desktop application.

QResearch-Oxford Data Linkage Project — DARS-NIC-240279-Y2V2N

Opt outs honoured: No - data flow is not identifiable, No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: Yes (Academic)

Sensitive: Non Sensitive, and Non-Sensitive, and Sensitive

When:DSA runs 2019-02 – 2020-09 2019.07 — 2022.06.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Critical Care
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Outpatients
  5. Civil Registration - Deaths
  6. Emergency Care Data Set (ECDS)
  7. Civil Registration (Deaths) - Secondary Care Cut
  8. HES-ID to MPS-ID HES Accident and Emergency
  9. HES-ID to MPS-ID HES Admitted Patient Care
  10. HES-ID to MPS-ID HES Outpatients
  11. Civil Registrations of Death - Secondary Care Cut
  12. Hospital Episode Statistics Accident and Emergency (HES A and E)
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Hospital Episode Statistics Critical Care (HES Critical Care)
  15. Hospital Episode Statistics Outpatients (HES OP)
  16. Civil Registrations of Death

Type of data: Anonymised - ICO Code Compliant

Objectives:

QResearch is a database of linked medical records that has been used and continues to be used by a variety of research projects undertaken by UK universities, from reviewing the safety of antidepressant medicines to studying factors to predict variations in survival rates for cancer patients.

QResearch has also been used to develop and validate risk prediction algorithms such as QRISK2. QRISK2 can be used by clinicians to calculate an individual’s risk of a heart attack or stroke taking account of their individual risk factors such as age, sex, ethnicity, clinical values and diagnoses. The research describing the derivation and validation of QRISK2 has been published in the BMJ (2008) and the software implementing QRISK2 is available as open and closed source software. QRISK2 is recommended by NICE as the risk score for use in its guidance on lipid modification (2014) and it is also recommended for use in the NHS Health Check.

The HES and mortality data are requested to link to the existing QResearch database so that it can be used for medical research. The QResearch database consists of the coded pseudonymised electronic health records from primary care patients registered with approximately 1,500 general practices spread throughout the UK.

QResearch is a not for profit collaboration originally between the University of Nottingham and Egton Medical Information Systems (EMIS) but the University of Nottingham’s roles and responsibilities are being transferred to the University of Oxford. Strategic decisions about the GP data are taken by a Management Board representing the interests of EMIS and the University of Oxford. The University of Oxford is the sole data controller for the datasets which are linked to QResearch (deaths, cancer and hospital data) and the single point of access to the data.

The database is widely used for medical research into the causes of disease, its natural history, treatment and outcomes. QResearch was started in 2003 in order to improve access for research to primary care data and will continue for the foreseeable future.

In addition to coded data from the GP electronic record, the QResearch database also contains the linked cause of death derived from the death certificate data which was originally supplied directly by the Office of National Statistics (ONS) but NHS Digital has since assumed ownership for this data, and cancer registration data supplied directly by Public Health England, following approval by Trent MREC and Secretary of State for Health. From October 2018, new mortality data (referred to as Civil Registration data) will be supplied by NHS Digital. Any mortality originally supplied by ONS data will be considered data supplied by NHS Digital and only NHS Digital can approve ongoing access to this data and its use for specific purposes.

The data linkages for QResearch were extended in 2011 to include additional health information from secondary care including HES. The additional linked HES data enables researchers to analyse additional information on patient characteristics, treatment and outcomes which will improve the epidemiological analyses of studies since the data will be more complete. Without the data linkage research studies may under-estimate the risk and benefits associated with interventions such as prescribed medicines. For example, QResearch data linked to HES data is being used to undertake an assessment of different types of direct anticoagulant medication which is prescribed in primary care to reduce risk of stroke and manage thrombosis. Adverse effects from anticoagulants include major haemorrhage which can be life threatening or life ending. Haemorrhage can affect the brain, gastrointestinal tract, urinary track or other parts of the body. The primary care data provides information on the prescriptions issued and the linked HES data provides information on haemorrhage which is serious enough to require hospital admission. Another example is a recent study looking at safety of the oral contraceptive pill. The primary care data provide information on exposure to the medication and the linked HES data provides information on thrombosis. These are just two examples of projects which can only be done using the linked data. The results help identify and quantify the risks and benefits associated with different types of medication, used in different patients, at different doses over time because of the outcomes. The results help doctors and patients make better decisions and increase the evidence base to inform guideline development and policy.

The patient level data linked to QResearch is only accessed by academics employed by University of Oxford, as well as authorised individuals employed by the University of Nottingham. In all cases, data can only be accessed on site at the University of Oxford. However, the researchers involved in a given project (contributing to the research question, design, interpretation and writing of the paper for publication but not handling the data) may be employed by other UK universities. The HES and mortality data stay on site at the University of Oxford and are only handled by University of Oxford staff, the data processor contracted to the University of Oxford (Dancing House Consulting) and authorised researchers employed by the University of Nottingham. The University of Oxford may have a collaborator at another university on the project team advising on clinical aspects or interpretation of findings, but they will not receive any data. In addition, the external researcher may initiate a project but the University of Oxford has sole autonomy for determining the purposes for which the HES and/or civil registration data will be processed and analysis will be done by University of Oxford staff with the data located at the University of Oxford. Data will not be used for any solely commercial purposes and all applications for the use of HES and/or mortality linked data are subject to a governance process explained in the Processing Activities section.

Only University of Oxford staff, their data processor, Dancing House Consulting, and authorised researchers employed by the University of Nottingham will have access to HES and/or mortality record level data and external researchers will only have access to tabular outputs. Record level data are not shared with researchers outside of the University of Oxford. Small numbers are suppressed in line with the HES Analysis Guide.

Research undertaken using the extended database continues to be processed using the existing arrangements with respect to scientific review and annual reports to Trent MREC. Research has to be peer reviewed, original, hypothesis driven or hypothesis testing, intended for publication in an academic peer reviewed journal.

All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.

Yielded Benefits:

The results of research undertaken continues to result in new knowledge and understanding regarding disease epidemiology, health inequalities, drug safety, methods of identifying patients at high risk of serious illnesses. Every year new research is published in high impact international research journals such as the British Medical Journal and the British Journal of General Practice. The research is ongoing with target dates for individual projects rather than one overall target date. A complete list of research papers using QResearch database is published at http://www.qresearch.org/SitePages/publications.aspx There are many benefits arising from this research - some examples are listed here. QRISK, which the applicant continues to develop and enhance, has become the preferred cardiovascular risk assessment tool used across the NHS. It is implemented in every GP practice, used extensively in NHS Health Checks, and a variant is used for the NHS Choices 'Heart Age' tool. It was recognised as an outstanding impact case study in the Research Assessment Exercise in 2014. Use of QRISK2 has led to targeted interventions to reduce CVD risk as shown in NHS health check research published in BMJ Open in 2016. In response to nationally identified NHS needs, the applicant has developed & updated a suite of risk prediction tools to identify patients at high risk of an adverse condition for intervention to improve outcomes. Many of these tools are recommended in policy, NICE guidelines & widely implemented in clinical practice. Examples include three risk assessment tools known as QFracture, QDiabetes and QAdmissions. 1. The QFracture tool which assesses risk of fracture has been recommended in NICE guidelines on fracture prevention (August 2012). It is the preferred tool in the NICE quality standard (2016) & SIGN in Scotland. It was included as a quality indicator within the GP Quality and Outcomes Framework in 2013/4. The tool is integrated in over 4,300 GP practices. It helps identify patients who have a high risk of fracture who can then be offered interventions to reduce their risk of a fracture. This is especially important for elderly patients for whom a osteoporotic fracture can be life changing or life limiting. 2. QDiabetes is recommended by 2012 NICE guidance on diabetes prevention & used to identify patients for the national Diabetes Prevention Programme for interventions to reduce risk of type 2 diabetes. Interventions to reduce diabetes risk will have benefits for the individual patient who may otherwise have developed diabetes. Reducing the incidence of diabetes is also likely to have a wider benefit for the health system given the high work load and costs associated with caring for people with diabetes. 3. Research on identifying patients at high risk of emergency hospital admissions led to the development of the QAdmissions risk assessment tool. This tool is recommended by 2016 NICE guidance on co-morbidity & is used to delivery NHS England's unplanned admissions Designated Enhanced Service by identifying those at high risk of emergency admissions for targeted interventions to reduce their risk of having an emergency admission. This is important since emergency admissions are distressing for the patient and their families but also put strain on the NHS. It will also help GP practices to identify frail older patients as required by the new changes to the 2017 GP contract. Research into the early diagnosis of cancer was awarded the 2012 Royal College of General Practitioners (RCGP) paper of the year category. It also led to implementation of new risk assessment tool in over 4300 GP practices to improve early diagnosis of cancer, in partnership with Macmillan Cancer Support. It also led to professor Hippisley-Cox becoming an expert witness to the All Party Parliamentary Group on Pancreatic Cancer (2012, 2017) which produced high profile recommendations on how to improve early diagnosis of pancreatic cancer. Patients who are diagnosed with cancer at an earlier stage have a better chance of accessing treatment which is capable of improving survival and quality of life. Research on the safety of antidepressants has been published in the British Medical Journal and research on how it could be used to improve prescribing decisions for antidepressants in primary care is supported as part of the new NIHR funded Biomedical Research Centre in Nottingham (2017-2022).

Expected Benefits:

The results of research undertaken continues to result in new knowledge and understanding regarding disease epidemiology, health inequalities, drug safety, methods of identifying patients at high risk of serious illnesses. Every year new research is published in high impact international research journals such as the British Medical Journal and the British Journal of General Practice. The research is ongoing with target dates for individual projects rather than one overall target date.

A complete list of research papers using QResearch database is published at http://www.qresearch.org/SitePages/publications.aspx

Research arising for the QResearch database including the linked data has been used to inform national policy. For example, research findings have been included in NICE guidelines on fragility fracture, diabetes, suspected cancer and lipid modification. Research findings have informed the NHS Health Checks programme and Department of Health guidelines on health checks.

Examples of research include assessment of the safety of antidepressant drugs and novel anticoagulants; investigation of potential links between diabetes drugs and cancer; quantification of the risk of thrombosis associated with various types of the oral contraceptive pill.

Outputs:

The outputs are research papers which are published in peer reviewer academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by with press releases from the relevant organisations and highlighted on social media.

Examples of conferences include the annual academic conference for the Society of Academic Primary Care ( next due July 2018) and the NIHR School for Primary Care Research (Sept 2017); international conferences such as the North American Primary Care Research Group (NAPCRG- US Nov 2018); the biannual conferences of the EMIS National User Group (a national education and research charity representing the GP practices who contribute data to QResearch Sept 2017, Feb 2018, Sept 2018 etc); annual conferences run by cancer charities such as Macmillan Cancer Support and Pancreatic Cancer UK; local and regional conferences run by the Nottingham Biomedical Research Centre (Dec 2017).

Results are also shared with policy makers and NICE guideline committees on a regular basis via their stakeholder consultations in order to support development of relevant guidelines. For example,
• The results of recent research on cardiovascular risk in people with severe mental health illness were shared in August 2017 with the guideline development group for guideline CG178 entitled “The Psychosis and schizophrenia in adults: prevention and management”.
• The results of work on unplanned admissions was shared with the NICE guideline on multi-morbidity [NG56] to inform its review and update process. This guideline was updated in September 2016 and can be found here. https://www.nice.org.uk/guidance/ng56

• Research on risk assessment for diabetes has fed into recently published NICE guideline on prevention of diabetes (PH38, September 2017) and the update to the “NHS Health Checks best Practice Guidance” published by Public Health England in February 2017.

• The recent research to update QRISK3 was shared at meetings with the British Heart Foundation and Public Health England as well with the National Directors of Cardiovascular Disease (Huon Grey and Matt Kearney) and at meetings of Expert Scientific Advisory Group which oversees the NHS Health Checks program and which is chaired by John Newton (PHE). QRISK3 will be implemented in the NHS from 2018 and will continue to be updated on regular basis to ensure that the tool gives the most accurate estimation of risk possible.

• Planned research on the risks and benefits of HRT are targeted at the recent NICE guideline on HRT at the next review in 2019. Patient representatives have been involved with the development of the research question and the grant application and will advise on the research as it progresses.

The results of two studies published in the BMJ which described enhanced methods to estimate risk of bleeding (QBleed) and stroke (QStroke) have informed NICE's decision to update their guidelines on atrial fibrillation [CG180]. For more details please see the information published on NICE's website in Sept 2017 on assessment of bleeding and stroke risk https://www.nice.org.uk/guidance/cg180/resources/surveillance-report-2017--atrial-fibrillation-management-2014-nice-guideline-cg180-4597399263/chapter/Surveillance-decision

Results have been shared with the Parliamentary Enquiry into Pancreatic Cancer (JHC attended as an expert witness in 2017).
Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.

The results tables within the papers will only contain statistical information with cell counts of > 5, being suppressed in line with the ICO code on anonymisation. Outputs will contain aggregate level data with small numbers suppressed in line with the HES analysis guide.

No indicators are produced which show performance of an organisation – indeed the identity of the GP practices contributing to QResearch are not shared with any third party.

Processing:

The data has been stored on secure servers at the University of Nottingham. These servers hold only the QResearch data and are not connected to any other servers within the University of Nottingham. Data on the servers are backed up on tapes which also contain only QResearch data.

This Data Sharing Agreement grants permission for controllership of this data to transfer to the University of Oxford and, as determined by the University of Oxford, for the servers and back up tapes to be physically transported to a server room in the University of Oxford. The servers and back up tapes will be transported separately by secure couriers. Once relocated within the University of Oxford, the University of Oxford will be the sole data controller for the data. From the point when the servers and back up tapes are removed from the University of Nottingham, the University of Nottingham will not hold any copies of the data.

Prior to the transfer of the QResearch database, a number of researchers substantively employed by the University of Nottingham were processing the data for the purposes of research projects under the controllership of the Principal Investigator who was then employed by the University of Nottingham but has since transferred to the University of Oxford. Under the continuing controllership of the Principal Investigator, these individuals will be permitted to continue to process the data to complete their research projects. The Principal Investigator may utilise substantive employees of the University of Nottingham in future research projects with an appropriate data processing agreement in place between the respective organisations and/or under honorary contracts or secondment agreements which NHS Digital has confirmed are acceptable before access is granted.

EMIS process the GP data from the original data controllers (GP practices) and sends it to the University of Oxford.

EMIS is not able to access or process any GP data once it is located at the University of Oxford.

EMIS is neither a data processor nor a data controller for the data provided by NHS Digital under this Agreement. EMIS is not able to access the HES data under any circumstances. EMIS has given permission for the GP data it supplies to be linked with the data from NHS Digital for purposes determined by the Principal Investigator at the University of Oxford.

Before providing data to the University of Oxford, NHS Digital use the Open Pseudonymiser tool to pseudonymise the HES data. NHS Digital retains the salt key for this pseudonymisation, meaning that the University of Oxford are unable to re-identify the data but as described below they are able to link with GP data that was pseudonymised using the same Open Pseudonymiser tool. The University of Oxford will not be provided with a copy of the pseudonymisation salt.

NHS Digital provide the pseudonymised data to the University of Oxford which is then linked to the QResearch database at individual patient level using a pseudonymised version of the NHS number which has been supplied in both GP data and the HES data. The data linkage is undertaken by an employee of the University of Oxford. No data items which would identify the data subjects are received by QResearch as the data is pseudonymised-at-source and at NHS Digital. Date of birth is rounded to year of birth before receipt by the University of Oxford.

The resulting data are then used for undertaking primary research. The linked data are only accessed by approved research staff with substantive contracts employed by University of Oxford, the contracted data processor (Dancing House Consulting) and authorised researchers employed by the University of Nottingham. Data is only processed on site on secure servers at the University of Oxford. No individual level data will be shared or stored outside the University of Oxford or supplied to any third party.

Applications for HES and/or civil registration data linked to QResearch GP data are restricted to academics employed by University of Oxford to undertake research. At least one member of the research team must be a medically qualified academic registered with the General Medical Council who signs the guarantee. Eligibility of applications is assessed according to the following criteria.
• You agree NOT to attempt to identify patient(s) or practice(s)?
• You undertake to provide a copy of the final report of the project and copies of any publications within one year of the project completion?
• You agree NOT to release the data to any third party including the funder, sponsor or other such body?
• You agree not to use the data for any other project except that which is expressly described in your protocol
• Do you have a statistician on the project team who has contributed to the design of the study and will advise on the analysis?
• Is the research a benefit to the UK Health and Social care system
All applications are reviewed by the QResearch Scientific Committee, which is overseen by the QResearch Advisory Board (which includes patients and general practice representatives). If an application does not meet the above criteria it would mean that application would be rejected and the data would not be shared. Details of the Scientific Committee and Advisory Board terms of reference and membership are published on the QResearch website, along with Advisory Board minutes.

Researchers originate a research question or hypothesis; write an outline protocol; and contact QResearch to discuss the feasibility of undertaking the study. If the study is feasible, QResearch will give a broad estimate of the costs of providing the analysis and will provide a letter to accompany any application for funding. The researcher then secures the necessary funding and completes the QResearch application form, including a detailed protocol and data specification. This application is sent for scientific review and feedback is given to the researcher. The researcher makes any necessary modifications to the protocol and approval is obtained, the researcher is given a timescale for the analysis. Once the researcher has the analysis, they have to approve it within one month of receipt.

As described in the section above, the QResearch database is also linked to mortality and cancer registration data. The database was first linked to ONS mortality data in 2007 and cancer data in 2011 (subsequently supplied by Public Health England since 2015). The data fields received from mortality data are: pseudonymised NHS number; year of birth, date of death; ICD10 cause of death. The cancer data includes pseudonymised NHS number; sex; year of birth; date of death; diagnosis date; cancer site and type; cancer stage and grade; cancer behaviour; cancer diagnosed only on death certificate; cancer treatment (surgery, hormone, chemotherapy, other).

In theory it would be possible to link additional datasets to the QResearch database though this would require consultation with the QResearch advisory board, the ethics committee, the confidentiality advisory group. It would also require amendment to the data sharing agreement with NHS Digital. There is no requirement to re-identify individuals from the data and no attempts will ever be made to do this.

The data processor Dancing House Consulting undertakes IT consultancy on behalf of the data controller, including administration of data backups, database administration, and secure destruction of data. Dancing House Consulting do not undertake data linkage or analysis of the data.

All outputs are restricted to aggregate data with small numbers supressed in line with the HES Analysis Guide.
Regular reviews against the ICO code on anonymisation (2012) will be undertaken to ensure that the data remain anonymised and all appropriate controls are in place to minimise any risk of re-identification.

The data from NHS Digital will not be used for any other purpose other than that outlined in this Agreement.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

MR360 - Early Breast Cancer Trialists' Collaborative Group — DARS-NIC-148204-7B1XT

Opt outs honoured: Yes (Excuses: Does not include the flow of confidential data, , Section 251 NHS Act 2006, )

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2019-11 – 2020-03 2016.04 — 2022.06.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Flagging Current Status Report
  4. MRIS - Members and Postings Report
  5. Cancer Registration Data
  6. Civil Registration - Deaths
  7. Demographics
  8. Civil Registrations of Death

Type of data: Identifiable

Objectives:

The data supplied by the NHSIC to Clinical Trial Service Unit (CTSU) will be used only for the approved Medical Research project MR360.

Yielded Benefits:

The first collaboration produced clear evidence of a modest but real effect, in at least some women, of adjuvant hormonal and cytotoxic therapy on five year mortality, and gave statistically stable evaluations of the effects of treatment on recurrence free survival in different types of patient. The results of this first cycle of the overview have already altered routine clinical practice in the UK and elsewhere.

Expected Benefits:

In any future application, the applicant will be required to provide details of the expected benefits resulting from the study.

Outputs:

No new outputs will be produced under this Data Sharing Agreement.

In any future application, the applicant will be required to provide details of the outputs that were produced and disseminated by the study as well as details of any future outputs planned.

Processing:

Under this Agreement, the data may be securely stored but not otherwise processed. No new data will be provided by NHS Digital under this Agreement.

The study data, including data provided by NHS Digital under previous agreements, are currently held by the University of Oxford. Under this interim extension all devices containing data will be securely locked away in a locked cabinet at the University of Oxford storage address specified in this Agreement.

The following provides background on the processing activities undertaken for the original study:

Identifying data on approximately 2,850 patients from 14 clinical trials was shared with ONS to carry out the linkage between the study data and civil registration data. Participants records were ‘flagged’ with the Office for National Statistics (ONS). ONS notified the study team at the University of Oxford of participants’ deaths (date and cause) and cancer events when they occurred. The ‘flagging for long-term follow up’ service transferred from ONS to the HSCIC in 2008. Data was last supplied in November 2016.

How general practice team composition and climate relate to quality, effectiveness and human resource costs: a mixed methods study in England. — DARS-NIC-344271-Q5X0S

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2021-08 – 2024-08 2022.02 — 2022.02.

Access method: One-Off

Data-controller type: ROYAL COLLEGE OF GENERAL PRACTITIONERS, UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Accident and Emergency (HES A and E)
  4. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

Background:
The British National Health Service (NHS) is a primary care led system with general practitioners (GPs) being the first point of contact for citizens with non-emergency health care needs. GPs have traditionally worked in practices, led by partners (or a sole partner), employing a team of staff (nurses, care assistants, receptionists, managers) and liaising with other community services. They coordinate care for local people who register with their practice. The sector is currently facing financial and other pressures that threaten the patient experience. Increases in the number of older people, conditions related to social or economic determinations of health , rising expectations of access and quality of medical care of the general public and transfer of some tasks previously undertaken in hospitals to primary care have added significantly to the general practice workload. Simultaneously, recruitment and retention problems have reduced the number of GPs per capita, and shortages of primary and community nurses have exacerbated staffing problems. The number of qualifying doctors choosing general practice has gradually declined over the last decade, whilst increasing numbers of GPs have left practice, with many opting to work abroad.

Concerns about recruitment and retention have coincided with a period of rapid change in the organisation of general practice. Over time, practices have become larger and incorporated a wider range of staff. In September 2016, the BMA reported 7,613 GP practices in England, a decline of 8% since 2006.
Recently, new organisational forms (e.g. ‘super-practices’, federations, and integrated models of primary and community-based care), and different ownership and contractual models (e.g. Alternative Provider Medical Services) of general practice have developed. In this challenging and changing situation, research is required to produce evidence that will enable primary care commissioners and GP practice managers to make resource allocation decisions that will ensure the workforce is effectively and efficiently deployed, and high quality care is maintained. Whilst it is clear that practices are becoming increasingly multidisciplinary, with a wider range of staff involved in direct patient care representing more varied roles, identifying the optimal mix of professionals is complex. Historically workforce planning has been unidisciplinary, but promotion of workforce flexibilities for care delivery relies on a range of disciplines and requires a different approach to workforce planning.
Workforce is the largest single component of healthcare expenditure and the size and composition of the workforce affects performance and outcomes for patients. The ability of health care systems to provide safe, high-quality, effective, and patient-centred services depends on sufficient, well-motivated, and appropriately skilled personnel operating within service delivery models that optimise their performance.

Problems have been highlighted by the Health Foundation regarding national workforce policy in the English NHS concluding that “Workforce is a relatively neglected area of policy which is often pursued as an afterthought, with important clinical, operational and financial impacts on the front line”. However, a number of recent policy proposals (e.g. the NHS Five Year Forward View, and the GP Forward View) have specifically addressed general practice workforce issues. Moreover, developments driven locally by general practices, Clinical Commissioning Groups and community health service providers have led to changes in the practice organisation and structure. In addition, there have been a number of national reviews of the primary care workforce which have had an influence on policy and practice.
Evidence explaining why this research is needed now.

Aside from calling for increased investment and extended use of technology, recent workforce challenges in general practice have been approached in two ways: different ways of working (e.g. skill mix changes, task shifting, role substitution), and organisational changes. As a result, extended use of mid-level practitioners (advanced nurses, paramedics, pharmacists, physiotherapists) and the introduction of new roles (physician’s associates) is becoming more widespread. New collaborative forms of general practice and integrated models involving hospital-based specialists are also emerging (‘super practices’, networks and federations; and polyclinics and multispecialty providers, respectively).

Aim:
The overall aim of this study is to explore how team composition and climate affect quality of care, clinical outcomes (effectiveness) and human resource costs in England, in order to inform practice management and commissioning decisions. The workforce configurations in general practices are highly variable and there is a lack of evidence about what skill mixes and staff deployments generate the best outcomes for patients and savings for health care economies. In addition, evidence on how the micro-level team climate (trust, relationships, processes, etc) relates to quality is not strong.
Study objectives are:
1. Description of policy context; delivery models; practice level variability in skill mix and human resource costs for general practice
2. Exploration of the factors associated with practice performance in terms of quality of care, in particular, the role of skill mix and human resource costs
3. Exploration of impact of role substitution on practices costs and quality of care
4. Conduct patient level modelling of associations between skill mix and clinical effectiveness and implications for costs
5. Examination of how team working affects quality of care and effectiveness through focus groups with service users, a staff survey in a sample of GP practices and practice based case studies

To complete this research, the research team will obtain fully pseudonymised data from the Royal College of General Practice (RCGP) Research Surveillance Centre (RSC). In addition to the pseudonymised primary care medical records, the research team will need to link the RCGP RSC primary care data with secondary Hospital Episode Statistics (HES) Accident and Emergency records for the primary care data cohort.

These data are being requested by the University of Oxford in the performance of a task in the public interest Article 6(1)(e) (EU GDPR, "Lawfulness of processing") i.e. “processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller”; requested by the National Institute of Health Research to investigate work force and skill mix in GP primary care services, as part of their Health Services and Delivery Research (HS&DR) Programme which aims to produce rigorous, relevant evidence to improve the quality, accessibility and organisation of health services.
The processing required is in accordance with Article 9(2)(j) (EU GDPR, "Processing of special categories of personal data") with regards to the processing being necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law.

Patients who are cared for in general practice surgeries will interact with a wide range of staff, including administrative staff, nurses, healthcare assistants, physiotherapists as well as doctors. How the staff work together has a significant effect on how well a patient is treated and how their medical conditions are managed. Patients who become unwell often attend hospital Accident and Emergency departments and may be admitted for care to hospital as in-patients.
In order to measure how well or poorly general practices are managing the health of their patients, data about how often patients attend hospital accident and emergency departments due to serious medical conditions and how many of a practice’s patients become hospital inpatients. General practice's achievement are measured in the Quality Outcome Framework (QOF) against a scorecard of evidence-based indicators. These indicators span four domains: clinical, organisational, patient experience and additional services. In addition the study will use Emergency hospitalisations for ambulatory care sensitive conditions (ACSC) as the measure of effectiveness, and markers for performance globally as well as in the NHS (Tian Y, Dixon A, Gao H. Emergency hospital admissions for ambulatory care sensitive conditions: identifying the potential for reductions. The Kings Fund, Data Briefing 2012 & World Health Organisation. Assessing health services delivery performance with hospitalizations for ambulatory care sensitive conditions, working document WHO Europe, April 2016).

NHS Digital can provide the Hospital Episode Statistics about Accident and Emergency and Admitted Patient Care (in patient) data, to allow the research team to measure both the clinical and financial impact of the way general practice staff work together to provide patient care.

The study is part of a national program of research funded by the National Institute of Health Research related to Health Services and Delivery Research (HS&DR) Programme and more specifically to the aspect of workforce and skill mix in GP services. The study is part of an ongoing digest of NIHR funded projects (https://www.journalslibrary.nihr.ac.uk/hsdr/#/) aimed to provide evidence to help implement the response to the 2015 Roland Commission’s vision to provide challenging and fulfilling careers for health professionals while delivering a high standard of care.

This study requires secondary (the Hospital Episode Statistics) data and will form the basis of the quantitative assessment of clinical efficacy of primary care and the related cost of clinical outcomes of variation of care, when combined with patients’ medical records from primary care.

500 general practices, comprising the Royal College of General Practice (RCGP) Research Surveillance Centre (RSC) research network will be analysed. This analysis will use a multilevel logistic regression model for the likelihood of hospital admission testing for cross-level interactions between practice characteristics and skill mix profile and emergency admission into secondary care. The registered patients from practices will form the level 1 data, comprising data from secondary care:
• Hospital Episode Statistics Admitted Patient Care
• Hospital Episode Statistics Accident and Emergency
and primary care data from the RCGP RSC database for the year 2019 (1/1/2019 to 31/12/2019).
These data will provide both clinical outcome data and facilitate the calculation of the cost of secondary care.
The data will be pseudonymised and the primary care and secondary care data will be linked and combined with practice level data:
Workforce:
- Total FTE care staff per head of practice population
- Ratio of care staff FTE to total practice FTE
- Ratio of GP FTE to total practice FTE
- Proportion of care staff FTE that are temporary (locum, bank)/ mid level (physician’s associate, advanced nurse)
- Staff turnover, vacancies
Practice Characteristics:
- List size
- Age/ sex distribution of practice population (e.g. % over 75)
- Morbidity (clinical registers
- Region, urban / rural
- Index of multiple deprivations
- Contract type, practice payments
- Type of practice (traditional /new)
Quality indicators:
QOF clinical summary score
CQC inspection rating
GPPS patient experience indicators

When analysed, these data will be used to establish the practice level factors which are associated with patient outcomes / indicators of clinical effectiveness, controlling for patient demographic and comorbidity status, and other practice characteristics which may confound the relationship.

Hospital Episode Statistics about Accident and Emergency and Admitted Patient Care will form the basis of outcome measures of clinical effectiveness : Emergency hospitalisations for ambulatory care sensitive conditions (ACSC) will be the measure of effectiveness used in the analysis. Hospitalisations for ACSCs present a significant burden upon healthcare systems and adjusted rates are used as markers for performance globally as well as in the NHS . ASCS have been described as those conditions where it is possible, to a large extent, to prevent acute exacerbations and reduce the need for hospitalizations through strong primary health care-based services delivery, and are indicators used within the NHS Outcomes Framework (http://content.digital.nhs.uk/nhsof ). Whilst the levels of hospital admissions for select ACSC appear to be decreasing or stabilising over time, there remains wide variation in hospitalisation rates. ACSC are a suitable proxy for primary care clinical effectiveness, and individual conditions will be selected from the Kings Fund categorisation:
- Vaccine preventable: influenza and pneumonia
- Acute (dehydration and gastroenteritis, pyelonephritis, perforated or bleeding ulcer, cellulitis, pelvic inflammatory disease, ENT infections, dental conditions, convulsions/ epilepsy, gangrene)
- Chronic (asthma, congenital heart failure, diabetes complications, COPD, angina, iron deficiency anaemia, hypertension.

To establish the relevant factors determining the current performance of primary care, the most recent stable information has been sought, namely data for 2019.
Regional variation of both healthcare provision and outcomes is well established and to match the geographical spread of the primary care data sources, England wide hospital data will be required in creating a nationally representative dataset.
In order to obtain robust statistical models, hierarchical analyses require patient level will necessary to control for patient characteristics.
Variables have been defined to utilise minimal potential identifiers. Study variables have been specified in formats that will reduce the risk of any inadvertent identification through combinations of variables. Data requested has been limited to that directly relevant to the main outcomes of interest. The study team are not requesting NHS number; this will be pseudonymised using a non-reversible hashing algorithm.

The University of Oxford and the Royal College of General Practitioners are joint data controllers for this study. The University of Oxford is the sole Data Processor. The RCGP RSC has its secure data and analytics hub at University of Oxford, who will manage data governance, encryption and access. The RCGP, has an interest specifically in this study and the use of the data collected due to the nature of the study and therefore has engaged as a joint controller undertaking the relevant activities as a controller along side Oxford. More generally the RCGP does not act as controller of the data used in the research undertaken with the collected data. The RCGP research surveillance centre provides its network general practices with posters which are displayed in the public areas of the practices’ premises (poster provided), patients are informed of the use of their data for both surveillance and research and are provided with a patient leaflet (leaflet provided) and provided with the link to the RCGP RSC transparency statement https://clininf.eu/index.php/transparency-statement/, they are also informed of their right to opt out of their data being used for research and planning (https://digital.nhs.uk/services/national-data-opt-out).
The University of Oxford has a contract with the RCGP to provide this surveillance, quality improvement and research platform. The University of Oxford is identified as a processor of personal data for the Royal College of General Practitioners (RCGP).

Wellbeing (formally Apollo Medical Software Solutions), an approved third-party provider, has formal service agreements and service specifications with RCGP RSC and with individual participating GP practices to conduct data collection and secure web transfer. Each unique patient within the RCGP RSC database is pseudonymised at source before data is extracted from individual practices using a computer generated patient ID created by Wellbeing Software Solutions. This pseudonymisation of records includes production of a hashed NHS number using pseudonymisation algorithm (SHA-512).

The service RCGP use is their secure extraction service:
Wellbeing SQL is a data extraction software that will extract any and all data from the GP practice in a consented, appropriate manner. It allows practices to share information in an anonymised format to third party organisations, who may amalgamate data from multiple practices and apply business intelligence or risk stratification to assist the individual practice, local CCG or PCT. There are regular letters that go out to all practices, a monthly newsletter, and a weekly email.

The National Institute of Health Research have funded this research as part of the Health Services and Delivery Research (HS&DR) Programme (NIHR Funding award ID 17/08/34).


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Expected Benefits:

The findings will produce evidence about what skill mix configurations work best in primary care, and what opportunities exist for substitution of tasks between different health practitioners in order to reduce costs whilst maintaining or improving outcomes. The study will generate quantitative economic models, indicating key characteristics which drive costs and quality. These models will be corroborated by the detailed qualitative parts of the overall, complex, concurrent, parallel, multistage, mixed methods design, with embedded survey and intensive case studies, including patient surveys. The detailed technical economic models will then be interpreted by a working group comprising recommendations and ‘priority action points’. The targeted recommendations and ‘priority action points’ will be more readily interpretable by GP partners, managers and commissioners and will enable them to make staffing decisions based on comprehensive evidence based policy that will ensure that the limited available human resources can be deployed in a way that maximises patient benefit. Identifying efficient workforce configurations will enable more patients to be treated effectively at the same or lower costs. This will benefit the population who are service users, through improved access to more timely care, and tax payers (funders of the NHS).The findings will produce evidence about what skill mix configurations work best in primary care, and what opportunities exist for substitution of tasks between different health practitioners in order to reduce costs whilst maintaining or improving outcomes. The study will generate quantitative economic models, indicating key characteristics which drive costs and quality. These models will be corroborated by the detailed qualitative parts of the overall, complex, concurrent, parallel, multistage, mixed methods design, with embedded survey and intensive case studies, including patient surveys. The detailed technical economic models will then be interpreted by a working group comprising recommendations and ‘priority action points’. The targeted recommendations and ‘priority action points’ will be more readily interpretable by GP partners, managers and commissioners and will enable them to make staffing decisions based on comprehensive evidence based policy that will ensure that the limited available human resources can be deployed in a way that maximises patient benefit. Identifying efficient workforce configurations will enable more patients to be treated effectively at the same efficiently allocated. Overall this will contribute to the smooth running of the NHS in the future, and its sustainability.

The research will also provide information on the relative efficiency of new models of primary care, and whether new staff roles, and new ways of using existing staff, are associated with improvements in patient outcomes or savings in costs. Findings will also indicate how team working and relationships relate to patient outcomes and experiences and staff wellbeing and job satisfaction, providing further guidance about how to foster productive team working environments.
The identification of the changes in how health care is delivered in primary care in terms of roles, will allow for planning of the recruitment of the health care workforce across all specialties and with sufficient staff to provide sufficient training to do the work that is needed in primary care.

In line with the overall stated goals of the HS&DR Programme, this research will produce evidence on the workforce factors associated with quality care provided by general practice. This evidence will form the basis of evolving models of care, informing policy as to how the NHS might improve delivery of services , by developing statistical models that identify key GP workforce characteristics associated with both clinical effectiveness and cost of care. These models will be evaluated at various stages of the study to validate the models’ interpretations in the context of the qualitative evidence, building on the strengths of the mixed methods approach for investigating complex processes in health care. Practice workforce characteristic will be complied from the freely available NHS Digital Primary Care Workforce Minimum Dataset and supplemented by data from the Quality Outcome Framework process and data from the both the Royal College General Practitioners Research Surveillance Centre database and Workforce costs for practices will be examined in relation to the total payments received (NHS Digital Annual Payments Review). The cost of care data required for economic analysis will be estimated using a top down approach with national unit costs (Curtis L, Burns A. Unit Costs of Health and Social Care 2016, Personal Social Services Research Unit, University of Kent, Canterbury. 2016) applied to the direct FTE cost of each staff role by practice. Workforce costs for practices will be examined in relation to the total payments received (NHS Digital Annual Payments Review).

The statistical models based on the primary and secondary (Hospital Episode Statistics Accident and Emergency) care data, will identify the key characteristics of general practices organization and workforce that drive quality of care, facilitating the development of specific policies and planning for the NHS.
There is a detailed dissemination strategy to delivery throughout the project, led by a member of the research team, who is both a senior academic with expertise in Primary Care epidemiology and an active clinician). The plan will ensure results are shared and have impact. Input will be provided by part of the research team engaging directly with GP primary care practitioners, commissioners and service users to develop implementation recommendations, the Service User Panel and Study Steering Group.
To ensure that the outputs inform practice and thereby maximise benefit to patients and the NHS, the dissemination strategy will use a knowledge management framework, creating information at macro (health system), meso (health region/ locality) and micro (individual provider/ practice) levels.

The study outputs will have direct benefit to commissioners and strategic policy makers. Commissioning, policy development and implementation are complex processes. The outputs of this study will have the potential to contribute to these processes, ultimately improving the workforce effectiveness at the practice level through staffing policy and training.

Both economic analysis and investigation of the factors contributing to clinical effectiveness are major aspects of the proposed study. Findings will be disseminated to all stakeholders, both service users, clinicians and administrators at the 10 workshops and policy briefings and conferences. As one of the specified target audiences includes NHS England, there is potential to inform future policy at this level, in line with the NIHR’s remit. Such changes in policy regarding the future conformation of the GP practice workforce has the potential to improvement care quality outcomes and reduce cost of treatment throughout primary care , at the national level .
The benefits will be accrued at several levels of the primary healthcare system; the funder, the NIHR will gain insight into how workforce dynamics in general practice relate to clinical outcomes and from these insights commissioners will have statistical models which can form the basis of a workforce planning toolkit, to be utilized in the nationwide planning of primary healthcare services, to the advantage of the nation as a whole.

The study team will measure clinical effectiveness using adjusted hospitalization rates for ambulatory care sensitive conditions, which are well established markers for performance within the NHS. While the study will deliver its findings within 36 months and the project does not provide for implementation evaluation, the use of routinely used metrics will facilitate the on-going monitoring of clinical performance as defined within the research framework.
The epidemiological analysis of the primary care and linked HES data is expected to be completed within 27 months. The analysis will provide insight into the factors associated with clinical effectiveness However as the study employs a mixed methods approach, the synthesis of the quantitative epidemiological analysis with the qualitative patient and healthcare professional findings will be finalised and disseminated from month 34 to 36.

Specifically, the findings will produce evidence about what skill mix configurations work best in primary care, and what opportunities exist for substitution of tasks between different health practitioners in order to reduce costs whilst maintaining or improving outcomes. This will enable GP partners, managers and commissioners to make staffing decisions that will ensure that the limited available human resources can be deployed in a way that maximises patient benefit. Identifying efficient workforce configurations will enable more patients to be treated effectively at the same or lower costs. This will benefit the population who are service users, through improved access to more timely care, and tax payers (funders of the NHS), because the NHS budget will be more efficiently allocated. Overall this will contribute to the smooth running of the NHS in the future, and its sustainability.

The research will also provide information on the relative efficiency of new models of primary care, and whether new staff roles, and new ways of using existing staff, are associated with improvements in patient outcomes or savings in costs. Findings will also indicate how team working and relationships relate to patient outcomes and experiences and staff wellbeing and job satisfaction, providing further guidance about how to foster productive team working environments.

Outputs:

The study follows a mixed methods design. The findings from the quantitative analysis of the data from NHS Digital data - the hospital data (accident and emergency, in-patient data) and civil registration deaths, will be combined with the practice level database and patient level data from primary care in the RCGP RSC database and an economic regression qualitative using a synthesised using a convergent parallel mixed methods design (Cresswell JW, Plano Clark VL. Designing and Conducting Mixed Methods Research. Thousand Oaks, CA: Sage Publications, Inc., 2011).

To ensure that the outputs inform practice and thereby maximise benefit to patients and the NHS, the dissemination strategy will use a knowledge management framework (de Lusignan S, Pritchard K, Chan T. A knowledge-management model for clinical practice. Journal of Postgraduate Medicine 2002; 48(4): 297-303), creating information at macro (health system), meso (health region/ locality) and micro (individual provider/ practice) levels.

The knowledge translation literature indicates that new information is most effectively disseminated using multiple approaches and ideally face-to-face. In addition to maintaining a project website and giving written and online feedback to study participants, activities will include:

Reports – a study report (planned delivery month 33) will be delivered to the funder, the NIHR. This report will detail all the methods, results and conclusions, including patient and public involvement.

Patient and public involvement has been formalised by the establishment of a Service User Panel (SUP), a form of public patient involvement (PI) advisory group. It will comprise 10 members recruited from different types of practices (traditional and new models, in varied socio-economic-ethnic areas in Kent and Surrey) and will meet four times per year to provide the perspective of patients and the public on issues within the research. The advisory group will be asked to assist with preparing information sheets for participants, focus group topics, patient survey questions, statements for the implementation guideline development process and dissemination materials for lay audiences. The SUP will receive training for their role and full information about the project at the first meeting and will be involved in the knowledge transfer process. Members will be reimbursed for their attendance at meetings, and contributing to research activity, for reasonable travel expenses and time commitments at National Standards for Public Involvement rates.

The NIHR study report the format will conform to the guidance given by the NIHR.

Submissions to peer reviewed journals – research papers will be submitted to lead journals relating to health service and delivery research, health economics and primary care medicine. These research papers will be written and submitted within the year following the end of the study.

Presentations - ten interactive workshops across England on implementation of good practice recommendations developed. These workshops will involve Commissioners and NHS managers- GPs, GP consortia, and other primary care providers- Dept. of Health, NHS Digital, National Institute for Care Excellence (NICE), Care Quality Commission, Health Education England - Royal College General Practitioners (RCGP), Royal College Nursing (RCN), British Medical Association and its Local Medical Committees; other groups dependent on skill mix e.g. Faculty of Physicians Associates (FPA), Royal College of Physicians

Conferences

Patient/public guide (developed with input from the SUP – to help patients and public appraise the pros and cons of skill mix in primary care; targeted at practices PPI group members; lay members of CCGs/STPs; national patient groups/charities

Press releases and policy briefings disseminated through links with key organisations

Social media (LinkedIn® & Twitter®) with associated infographics at key milestones

Massive open online course (MOOC) Webinar, video (YouTube®), multimedia evidence summaries

All data reported in the study outputs will be at the aggregate level with small number suppressed in line with HES analysis guide for quantitative analyses.

Implementation recommendations:
Qualitative research, comprising findings from all aspects of the work will be brought together in a consensus forming process involving GPs, professionals, commissioners and service users in order to produce implementation recommendations that are relevant and workable throughout the NHS .
The consensus forming process will employ the Nominal Group Technique (McMillan, S. S., King, M., & Tully, M. P. 2016. How to use the nominal group and Delphi techniques. International journal of clinical pharmacy, 38(3), 655–662. https://doi.org/10.1007/s11096-016-0257-x) to synthesise findings and elicit consensus among experts on implementation recommendations. The method facilitates the generation of ideas in relation to problems, solutions, or both, and is based on the premise that accurate and reliable assessment is best achieved by consulting a panel of experts and accepting group consensus. Development sessions attended by the members of the research team, Service User Panel and Professionals and Commissioners Panel will establish key learning from the research and identify Knowledge Transfer Topics. Consensus-building workshops with commissioners, healthcare professionals in general practice and service-user representatives (experts) will to consider the Knowledge Transfer Topics and will develop recommendations and ‘priority action points’ that will support practice management and commissioning decisions related to the GP workforce composition and team functioning.
Stakeholders will be recruited to the to the Nominal Group Technique based workshops, so as to ensure that there is good geographical coverage and that different types of practices and a variety of socio-economic and ethnic areas are represented.
The recruitment use two processes
1) an open invitation to commissioners, GPs, other professionals in General Practice and service users) will be publicised via the project website, social media and targeted communications.
2) partnerships will be formed with national networks, such as the Clinical Research Networks, the Primary Care Collaboratives, RCGP and other influential groups, to support recruitment.
These two approaches are expected to be supplemented by the snowballing technique and will thus increase participation rates, with members of the team and individuals who have participated in the research during the two-year period circulating invitations to their contacts. A nominal financial recruitment incentive will be offered to each stakeholder taking part in the workshop, and participant travel expenses will be reimbursed.

a) Patient and carer focus groups
b) Survey of team members in a representative sample of general practices
c) Case studies in 12 general practices

The recommendations from the Nominal Group Technique will inform short term staffing decisions and longer term training plans at practice, regional and national levels.
They will be disseminated through multiple means including interactive workshops, policy briefings and presentations to the relevant audiences.

The workshops lead by a senior primary care researcher will initiate discussion on how to implement good practice recommendations with Commissioners and NHS managers (e.g. Clinical Commissioning Groups, Sustainability and Transformation Plan areas, NHS England), GPs, GP consortia, and other primary care providers, external statutory organisations (e.g. Dept. of Health, NHS Digital, National Institute for Care Excellence (NICE), Care Quality Commission, Health Education England), external non-statutory bodies: Royal College General Practitioners (RCGP), Royal College Nursing (RCN), British Medical Association and its Local Medical Committees; other groups dependent on skill mix e.g. Faculty of Physicians Associates (FPA), Royal College of Physicians.

Policy briefings and press releases will be disseminated to Commissioners and NHS managers (e.g. Clinical Commissioning Groups, Sustainability and Transformation Plan areas, NHS England), through links with key organizations: external statutory organisations (e.g. Dept. of Health, NHS Digital, National Institute for Care Excellence (NICE), Care Quality Commission, Health Education England), external non-statutory bodies: Royal College General Practitioners (RCGP), Royal College Nursing (RCN), British Medical Association and its Local Medical Committees; other groups dependent on skill mix e.g. Faculty of Physicians Associates (FPA), Royal College of Physicians, academia, especially primary care academia through RCGP, conferences and Society of Academic Primary Care (SAPC). The briefing documents will be high level summaries of the key findings of the study, written in a less technical style.

Publications are planned; to report the clinical efficiency and economic evaluation findings, in conjunction with the qualitative research findings - within a year of the end of the study in journals such as the Health Services and Delivery Research (ISSN: 2050-4357).

Statistical mixed effects models of clinical effectiveness and estimation of care costs (and savings) at the practice level and more widely at higher levels of the NHS will be published in the appropriate journals to share findings with the various audiences identified by the dissemination team.

Due to information governance restriction patient and staff level data will not be shared. However all findings will be shared, and publishing in journals offering open access will be sought, aggregated with small numbers suppressed in line with HES analysis guide.

All reporting and wider dissemination activities are scheduled to be completed by the end of September 2021.

Outputs will be produced that meet the needs of six key audiences:

• Commissioners and NHS managers (e.g. Clinical Commissioning Groups, Sustainability and Transformation Plan areas, NHS England). They will be involved in ten interactive workshops based on implementation of good practice recommendations. Press releases and policy briefing will be targeted at this group along with peer reviewed journal articles.
The benefits of the evidence the study will produce are closely aligned with the aims of the funder, NIHR HS&DR to produce evidence on the quality, accessibility and organisation of health services and how the NHS might improve delivery of service. Use of the NHS Digital data will enable the development of statistical models exploring the key determinates of health outcomes of primary care and associated costs, allowing for the inclusion of both individual patient characteristics and the characteristics of their specific GP surgery’s health care teams characteristics responsible for delivery their care.

• GPs, GP consortia, and other primary care providers. They will be involved in ten interactive workshops based on implementation of good practice recommendations and will also benefit from social media, webinar and peer reviewed journal articles. The study findings and their implications will be presented in the workshops and it is hoped that the interaction between the researchers and the GP community will mean that findings and implications of the research can be explored in a supportive and collaborative environment.

• Patients and the public. A Patient/public guide (developed with input from the patient advisory group) will be provided– to help patients and public appraise the pros and cons of skill mix in primary care. Specifically practices PPI group members; lay members of CCGs/STPs; national patient groups/charities will be made aware of this resource. Additionally, social media, webinar and peer reviewed journal articles will be available to further inform.
The benefits of public involvement is an intrinsic part of citizenship, public accountability and transparency and can lead to empowering people who use health and social care services, providing a route to influencing change and improvement in issues which concern people most.

• External statutory organisations (e.g. Dept. of Health, NHS Digital, National Institute for Care Excellence (NICE), Care Quality Commission, Health Education England). These bodies will be invited to attend ten interactive workshops based on implementation of good practice recommendations. Press releases and policy briefing will be targeted at this group and they will also benefit from social media, webinar and peer reviewed journal articles.
This audience, while varied in its make-up, have broad remits in terms of planning and providing health services and also the generation of process and outcome data and its synthesis. By presenting new models of the interaction of GP team composition and climate and outcomes of quality and effectiveness of care, costs, the aim is to refine the co-ordination of the work of these organisations.

• External non-statutory bodies: Royal College General Practitioners (RCGP), Royal College Nursing (RCN), British Medical Association and its Local Medical Committees; other groups dependent on skill mix e.g. Faculty of Physicians Associates (FPA), Royal College of Physicians. These bodies will be invited to attend ten interactive workshops based on implementation of good practice recommendations. Press releases and policy briefing will be targeted at this group and they will also benefit from social media, webinar and peer reviewed journal articles. It is essential that the bodies representing the GP workforce are appraised of the findings of the study, if policy change is to be effective. Engaging with the representatives of the workers delivering change and explaining the study findings and their implications, can only help to initiate change within the body of healthcare professionals required, in response to the new insights the study findings will provide. It is expected that findings will include the degree of variation within primary care, of modes of multi-disciplinary working and it is thus essential the professional bodies can contribute to any strategic planning at the earliest opportunity while be appraised of the complexity of the totality of the system. These workshops will ensure the new findings can be explained in an interactive fashion ensuring details can be explored in a supportive and collaborative environment.

• Academia, especially primary care academia through RCGP, conferences and Society of Academic Primary Care (SAPC) . Academic researchers and societies will be key targets for peer reviewed journal articles generated by the study team and they will also have available the widely disseminated press releases and policy briefings, social media and webinar. The dissemination of research findings and the subsequent discourse is a well established aspect of modern science and will be key to establishing the validity of the findings, promoted the evidence and to initiate further work in the field.

• Ten interactive workshops across England on implementation of good practice recommendations developed as part of the study. The audiences will comprise: commissioners and NHS managers (e.g. Clinical Commissioning Groups, Sustainability and Transformation Plan areas, NHS England), GPs, GP consortia, and other primary care providers , external statutory organisations (e.g. Dept. of Health, NHS Digital, National Institute for Care Excellence (NICE), Care Quality Commission, Health Education England), and external non-statutory bodies (e.g. Royal College General Practitioners, Royal College Nursing, British Medical Association and its local medical committees; other groups dependent on skill mix e.g. Faculty of Physicians Associates, Royal College of Physicians)
• Patient/public guide (developed with input from the SUP)– to help patients and public appraise the pros and cons of skill mix in primary care; targeted at practices PPI group members; lay members of CCGs/STPs; national patient groups/charities (skill mix to deliver quality)
• Press releases and policy briefings disseminated through links with key organisations : commissioners and NHS managers, external statutory organisations, external non-statutory bodies, academia
• Social media (Linked in & Twitter) with associated infographics at key milestones (All)
• Massive open online course (MOOC) webinar, video (Youtube), multimedia evidence summaries
• Publications, including full NIHR report, articles for professional and academic journals, conference presentations

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by "Personnel" (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

The RCGP RSC is based at the University of Oxford. The University of Oxford has a contract with the RCGP to provide this surveillance, quality improvement and research platform. The University of Oxford is identified as a processor of personal data for the Royal College of General Practitioners (RCGP).

The hashing of identifiable data for the Clinical Informatics and outcomes Research Group at the University of Oxford is conducted by the Salt Service of the University of Oxford Central IT team, so that the holder of the pseudonymised data is separated from the service that holds the non-reversible hash key. This avoids pseudonymised data becoming identifiable data.

The SALT methodology rationale will be as follows
1) Wellbeing Software Solutions, an approved third-party provider, has formal service agreements and service specifications with RCGP Research Surveillance Centre and with individual participating GP practices to conduct data collection and secure web transfer.
2) Each unique patient within the RCGP RSC databank is pseudonymised at source before data is extracted from individual practices using a computer-generated patient identifier created by Wellbeing Software Solutions.
3) This pseudonymisation of records includes production of a hashed NHS number using pseudonymisation algorithm (SHA-512).
4) An encryption salt is held by a designated staff member of the University of Oxford Medical Science Division who is not a member of the ORCHID staff.
5) When a data linkage is required to the data extracted by Wellbeing Software Solutions in the RGCP RSC databank, the encryption salt holder sends the encryption salt to the data provider (in this case it is NHS Digital)
6) NHS Digital will hash personal identifiers (in the data requested by ORCHID) using a hashing algorithm. NHS Digital will use the same pseudonymisation algorithm (SHA-512)
7) To make this key unique, an encryption salt is added at the end of the NHS number (e.g. NHS number= 12345678 ; SALT (held by someone other than ORCHID staff) = bob. So, hashing would take place using the SHA2-512 algorithm by 12345678bob = return pseudonymised data.
The encryption salt is one-way.
8) The member of staff who holds the encryption SALT is not a member of the research team working on the data provided by the RGCP or NHS Digital.
9) Therefore the researchers do not have the means available to ‘un-hash’ the data provided.

NHS Digital will hash their NHS numbers using the same pseudonymisation algorithm (SHA-512). NHS Digital will undertake data linkage via the hashed NHS numbers in both sets of data. This process has been used for previous projects linking different sets of data, and the linkage has been successful. Records for each study participant containing information from HES, together with hashed NHS numbers will be sent to the University of Oxford.

There will be no subsequent flows of data from the University of Oxford.

In this agreement the University of Oxford will act as a joint data controller with the RCGP. University of Oxford will process the data.

University of Oxford have requested 41 fields of the dataset HES APC, including the codes present in

General practices within the RCGP RSC network have been involved in disease surveillance for over 50 years. Over this period practices have had feedback about their data quality and many practices have been computerised since the late 1990s, allowing long-term outcomes to be studied.
Wellbeing Software Solutions has formal service agreements and service specifications with RCGP RSC and with individual participating GP practices to conduct data collection and secure web transfer.

Each unique patient within the RCGP RSC database is pseudonymised at source before data is extracted from individual practices using a computer generated patient ID created by Wellbeing Software Solutions. This pseudonymistion of records includes production of a hashed NHS number using pseudonymisation algorithm (SHA-512).

Pseudonymised record-level HES data will be processed and stored at the University of Oxford. Patient level databases are held in the database server within the Research Group's secure network. The Research Group's dedicated secure network is sited behind a firewall within the University's network. It is a standalone, independent network, all in-bounded connections are block, but out-bounded connections are allowed. All staff members of the research group working within the team base work from secure workstations or secure laptops with encrypted drive. Only substantive employees of the University of Oxford will have access to the data and only for the purposes described in this document. The data will be used solely for the study titled "How general practice team composition and climate relate to quality, effectiveness and human resource costs: a mixed methods study in England".

The University of Oxford will send the hashed NHS numbers to NHS Digital. The following flow of hashed NHS numbers will be undertaken.

University of Oxford will identify the study patients for the cohort above from primary care records in the RCGP RSC practices and send the hashed NHS numbers of the cohort under study to NHS Digital to link to HES/ Civil registration data. No other GP data will be sent to NHS Digital.

The process of linkage is as follows:
• NHS Digital will hash their NHS numbers using the same pseudonymisation algorithm (SHA-512) as used by the RCGP.
• NHS Digital will undertake data linkage via the hashed NHS numbers in both sets of data. This process has been used for previous projects linking different sets of data, and the linkage has been successful
• NHS digital extract all HES records for which there are matched primary care records
• NHS digital will send the extract of HES records with the hashed NHS number to the University of Oxford
• University of Oxford will link the HES records together with GP data from the primary care records from RCGP RSC practices with the same hashed NHS numbers
Records for each study participant will when fully linked contain information from HES together with information from RCGP RSC primary care practices.

Each unique patient within the RCGP RSC database is pseudonymised at source before data is extracted from individual practices using a computer-generated patient ID. The University of Oxford holds no identifiable data and only hashed NHS number. Combining/ linking data from University of Oxford for this project will not lead to or increase the risk of pseudonymised data becoming identifiable data. Linkage of two non-confidential datasets does not create a confidential dataset.

Only pseudonymised data with direct patient identifiers removed will be used. The research team will not seek individual patient identifiers; where required, data linkage will be achieved through ‘hashing’ algorithms to generate non-identifiable, unique IDs from identifiable data; as a further protection, non-reversible, pseudonymised ID numbers held be database organisations will be converted to unique study IDs, the keys to which will not be accessible to the research team; and, when using these data small numbers in reporting will be suppressed and the presentation of data that can potentially be used to reveal identities will be avoided. Data extracts and aggregate analyses will be pseudonymised/anonymised as described.

All data processing is carried out by staff with contracts with the University of Oxford. All staff have received Information Governance training on an annual basis and have all passed the NHS Information Governance on-line test for the current year.

Access to the data will limited to researchers with substantive employee contracts with the University of Oxford. All researchers will be required to complete training and sign the relevant agreements to be able to access the data on the University of Oxford secure environment. No individual-level study data can leave this environment, and all aggregated results data is reviewed prior to export.

All data transferred from the secure, “safe haven” computing environment, undergoes a statistical control process, where the aggregated data are assessed in order that no patients can be identified by inference, such as reporting rare diseases or operations conducted at a specific time or location. Practice level identification is also avoided by ensuring the granularity of the analyses reported are at the highest level possible while providing meaningful scientific insights.

The Research Group has conducted a risk assessment of the physical security of the offices and servers where patient level data is kept. The Research Group of Department of Clinical and Experimental Medicine at the University of Oxford has worked with routinely collected healthcare data in a number of research and evaluation projects over the last 15 years. The Research Group works within the Research and Information Governance team at the University of Oxford.

No data is stored outside of the secure computer system hosted at the University of Oxford.

All outputs will be scrutinized by a lead senior academic with the Service User Panel and the Study Steering Group before the output is disseminated. The study has a set up a working group, the dissemination of findings team specifically for this purpose.

The dynamics of frailty in older people: modelling impact on health care demand and outcomes to inform service planning and commissioning — DARS-NIC-353126-Y1S5F

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d), Health and Social Care Act 2012 – s261(2)(a)

Purposes: Yes, No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-02 – 2024-02 2022.01 — 2022.01.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD, UNIVERSITY OF SOUTHAMPTON

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Critical Care
  5. Hospital Episode Statistics Outpatients
  6. Civil Registrations of Death
  7. Hospital Episode Statistics Accident and Emergency (HES A and E)
  8. Hospital Episode Statistics Admitted Patient Care (HES APC)
  9. Hospital Episode Statistics Critical Care (HES Critical Care)
  10. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

STUDY AIMS AND PURPOSE:
Frailty has emerged as a significant issue for the National Health Service (NHS) in recent years. Frailty is associated with outcomes including unplanned admission, transfer to residential care and high levels of service use. As the population ages, the frailty becomes more common, and associated demand for health care increases. Where there are limited NHS resources but increasing demand, planning delivery of appropriate services to support people with frailty will be key to providing cost-effective, quality care for older people. However, detailed information about how many people develop frailty over a certain time, how common frailty is in different groups of people, how it progresses and how it impacts on need for health care is still lacking. We need this information to be able to plan, commission and delivery services for older people who are at risk of developing frailty, or who already have frailty.

To be able to do this, we need to explore the trends of frailty development and progression within large populations and understand the impact of frailty on patients and their use of NHS services. A useful tool, the electronic Frailty Index (eFI) has recently been introduced to the NHS. This tool uses data in the patients primary care medical record and looks for 36 different ‘deficits’ (e.g., clinical conditions or diagnoses, laboratory tests, limitations to mobility) which are used to calculate a score. A low score indicates that patients are ‘fit’, and higher scores indicate patients may have mild frailty, moderate frailty or severe frailty. The worse the frailty becomes, the more at-risk patients are from poor outcomes, as people are more likely to find it difficult to deal with small changes in their health or circumstances, so the effects of getting ill are worse than for other people.

Until recently, it was difficult for General Practitioners (GPs) to provide care for frail older people because it was hard to identify people who were frail without an assessment by a consultant. This meant that frail older people were not always receiving the care they needed. However, GPs can use the information from the eFI to improve care for patients with moderate and severe frailty.

University of Southampton have access to a pseudonymised extract of all individuals aged 50 years and above between 2006 and 2017 from the primary care records of participating RCGP RSC practices. An eFI score for each individual for each calendar year they are present in the cohort has been calculated from the RCGP RSC primary care data. The eFI score is then categorised into fit, mild, moderate and severe based on the cut-offs provided in Clegg (2016). Given the number of years individuals may be present in the dataset, it is likely the eFI category will vary during their follow-up time; University of Southamptons preliminary analyses of the existing primary care data (RCGP dataset) confirms this is the case. The data extract requested from NHS Digital will be pseudonymised and linked to the existing pseudonymised primary care data as per the processes described in section 5b. This linked dataset will allow University of Southampton to explore the relationship between frailty transitions and outcomes without having to identify individuals.

The request is for primary care data from RCGP RSC, including all relevant codes for the 36 variables used in calculating eFI. There is no use of the eFI scores coded within GP systems, which would not have been available for the years being requested. The eFI scores are generated from routinely collected primary care data and use Read or CTV3 codes, as specified in the method by Clegg (2016), which allows calculation of eFI for all ages (Read code algorithm). This method has been applied to retrospective primary care data to generate information on each of the 36 eFI deficits. The requested data will be linked to our pseudonymised primary care records using the processes described. This will allow University of Southampton to utilise the primary-care derived eFI scores to explore the relationship between frailty and secondary and urgent care use.

Within the primary care record, which are used to calculate the eFI score, the eFI uses clinical diagnoses which have already been made and recorded by GPs using Read or CTV3 codes in the patients’ records. No prospective clinical assessments or diagnoses are therefore required for the proposed work. No clinical diagnoses are being carried out for this study. The eFI is not the same as a clinical diagnosis of frailty, its development was based on the recognised cumulative deficit framework devised by Rockwood. The intention is to use eFI scores as a measure of potential frailty or frailty associated burden at population level, not as a clinical diagnostic tool. By diagnoses, it is meant existing diagnostic codes held by RCGP RSC.

Therefore, the overarching aim of this study is to explore trends in development and progression of frailty, and the dynamics of frailty related healthcare demand, outcomes, and costs in the older general practice population, to inform the development of guidelines and tools to facilitate commissioning and service development for this patient group.

SPECIFIC STUDY OBJECTIVES AND RELATED WORKSTREAMS:
The study objectives are:
1. Identification of incidence and prevalence of frailty states in an ageing population (50 years and over)
2. Identification of frailty trajectories and transitions in severity in the older population over time
3. Exploration of drivers of progression of frailty, including clinical, socioeconomic, and demographic factors
4. Examination of the impact of frailty on service use, costs, and pathways of care
5. Exploration of the relationship between frailty status, socio-economic factors, practice factors and service use and outcomes (mortality, unplanned admissions, residential care use)
6. Prediction of trends in frailty, modelling of health and care demand and costs over time and in different service contexts
Workstreams:
To fulfil the above objectives, the project is divided into the following workstreams, of which workstreams 1 and 4 are relevant to this data request. There are two main aims for the project Workstream to which this data request relates. They are:
- the identification of key variables capable of predicting frailty development
- progression and assessment of the relationship between frailty status and key clinical outcomes (including mortality and unplanned admissions).
These analyses will then be used to inform the simulation modelling being conducted in Workstream 4.
This application relates to the linkage of HES and mortality data from NHS Digital to primary care data provided by RCGP RSC within Workstream 1 of the study. There is no data linkage between Hospital Episode Statistics (HES) and mortality data and SAIL.

• Workstream 1: statistical modelling of population trends, incidence and prevalence of frailty, stratification of frailty and related outcomes, resource use and costs – this data request specifically relates to providing secondary and urgent care service use data as a component of this workstream.
• Workstream 2: validation of the population model
• Workstream 3: stakeholder engagement.
• Workstream 4: simulation modelling to explore impact of different service and demographic scenarios on population trends, service demand and costs in the future – the analysis of data provided under this data request will inform this workstream, no further data is required for workstream 4.
The data requested under this application will provide the necessary hospital outcomes and mortality data to be able to fulfil Workstream 1, and the results of analyses in Workstream 1 will inform the simulation modelling in Workstream 4.

WHICH DATA IS BEING REQUESTED?
This study will use electronic data which is recorded during the routine care of NHS patients, where explicit consent has not been gained from participants. To be able to fulfil the aims of the study, healthcare data on an ageing cohort over a 12-year period will be needed, so that health outcomes can be explored over the medium to long term. We will use data which has already been collected (‘retrospective data’), as it would not be possible to do a large-scale representative study prospectively.

The dataset requested is minimised to a pre-defined cohort of approximately 2.2 million patients from the Royal College of GPs Research Surveillance Centre (RCGP RSC) dataset. The RCGP RSC dataset is an electronic health record (EHR) that collates routinely recorded primary care data from a population of 3 million nationwide from more than 400 GP practices. We are only requesting variables which are needed for analysis of our defined outcomes, in appropriate formats to minimise potential identifiers and reduce the risk of any inadvertent identification through combinations of variables. The RCGP Research Surveillance Centre team at University of Oxford and the study team at University of Southampton are requesting a unique study identifier (ID) only; NHS Digital data will be pseudonymised using a non-reversible hashing algorithm. The RCGP Research Surveillance Centre team will link the NHS Digital data to their primary care data (RCGP RSC dataset) using the pseudonymised Identifier.

To conduct this component of the research (Workstream 1), the research team from University of Southampton will work on a pseudonymised RCGP RSC data extract, linked to pseudonymised NHS Digital HES and Civil Registration Deaths data/Mortality data to determine the outcomes specified in this application. In total, for this workstream, the University of Southampton will obtain fully de-identified, pseudonymised data extracts from the following databanks:

• Royal College of General Practitioners Research Surveillance Centre (RCGP RSC) dataset: this primary care dataset will include demographic data, residence, long-term conditions diagnoses, frailty index domains, prescriptions, primary care service events

The primary care RCGP RSC dataset comprises the baseline characteristics of the patients and primary healthcare contacts over this period, in addition to frailty scores, the main predictor of interest in this study. Secondary care attendances and their outcomes (outpatient appointments, Accident and Emergency (A&E) visits, hospital admissions, critical care admissions) and deaths are key study outcomes of interest to understand how attendances and healthcare use varies between people with different frailty states. It is therefore important to have individual-level data to be able to analyse changes in healthcare use over the cohort period and examine predictors of secondary care use and deaths, hence the request for pseudonymised Hospital Episode Statistics (HES) and Civil Registration Deaths data/Mortality data, which will be linked to the RCGP RSC primary care dataset only.

For this study, the research team will need to link the de-identified RCGP RSC data extract with data on secondary care Hospital Episode Statistics (HES) and Civil Registration Deaths data/Mortality data. HES and mortality data are therefore being requested in the performance of a task in the public interest - Article 6(1)(e) i.e. processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller, and Article 9(2)(j) with regards to the processing being necessary for achieving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law. The public interest function of the proposed data linkage is evidenced in the acceptance of this study within the RCGP Research Surveillance Centre portfolio and its funding by the NIHR, where it is a part of their established programme of research in relation to management of frailty.

ROLE OF THE FUNDER AND OTHER ORGANISATIONS:
This project has been funded by the National Institute of Health Research (Health Services & Delivery Research funding stream, grant number 16/116/43) which commenced in March 2019 and is due to conclude in February 2022. NIHR are the funding body only, they will not determine the aims and objectives of this project nor will they have access to NHS Digital data.

As the main study is funded by the NIHR, an independent Study Steering Committee (SSC) comprising academics, service commissioners, public health experts and Public Patient Involvement (PPI) representatives provides oversight on behalf of NIHR. The SSC is independent of the study and their remit is to ensure that the project is delivered in line with the agreed protocol. The National Clinical Director for Older People and Person-Centred Integrated Care at NHS England is a member of the Study Steering Committee; the Director provides the NHS England perspective on commissioning of services for older people and guidance on dissemination and implementation of study findings.

The other organisations involved in the wider project with advisory roles include Southampton University Hospitals NHS Trust, Southern Health Foundation Trust, the University of Oxford, the University of Leeds, and public contributors. No staff from these organisations will have access to NHS Digital data. The Stakeholder Engagement Group (SEG) comprises a wide range of stakeholders, including representatives from service providers, commissioners, clinical experts, health, social care and voluntary organisation and patients/carers. The SEG role is to advise on the development of the simulation model and the scenarios to be tested by the simulation in Workstream 3 of the funded project.

DATA CONTROLLERS AND DATA PROCESSORS:
In this agreement, the University of Oxford and the University of Southampton are the joint Data Controllers. University of Oxford makes decisions about the processes for data processing and access. University of Southampton are data controllers as they are dictating the analysis that is being done.

The University of Oxford and University of Southampton are Data Processors. The RCGP RSC dataset is stored and managed at the University of Oxford. The University of Oxford has a contract with the RCGP to provide this surveillance, quality improvement and research platform. Under the 2018 Data Protection Act, the University of Oxford is identified as a processor of personal data for the Royal College of General Practitioners (RCGP). The RCGP Research Surveillance Centre has its secure data and analytics hub at University of Oxford, who will manage data governance, encryption, and access. NHS Digital data will be released to University of Oxford who will be carrying out the linkage with their primary care dataset before making the linked data available to University of Southampton. University of Southampton are Data Processor because University of Southampton staff will access NHS Digital data and carry out data analysis on the University of Oxford secure remote server.

DATA ANALYSIS METHODS AND USE OF THE RESULTS:
This study will explore the incidence and prevalence, development, and impact of frailty within the population using retrospective data from the RCGP Research Surveillance Centre databank. The eFI tool will be utilised to stratify a cohort of people aged 50 and over present in the database between 2006 and 2017 inclusive into fit, mild, moderate, and severe frailty groups. Data will be extracted on frailty status, health care use, and outcomes for the subsequent years, and the team at University of Southampton will calculate key service use costs from the linked RCGP RSC dataset and NHS Digital HES and mortality data. Outcomes will include mortality, unplanned hospital admission, A&E attendance, and GP appointments.

The RCGP RSC dataset will provide data on socio-economic factors, practice size and location and residence. The research team at University of Southampton will use the eFI to stratify the RCGP RSC dataset cohort by severity of frailty and explore frailty status over time, determining incidence, prevalence, and progression of frailty. The University of Southampton research team will use descriptive statistics to estimate baseline prevalence, burden of frailty and transition rates between frailty states in population aged 50 and over.
The research team at the University of Southampton will use the RCGP RSC dataset to examine the relationships between factors such as age, deprivation, ethnicity, location, and comorbidities of individuals in relation to development of, and deterioration in, frailty status. The epidemiology of frailty will also be described, calculating prevalence, incidence and describing trajectories of decline. Relationships between demographics, practice characteristics, outcomes, service use and costs will be explored for frailty (eFI score) strata (robust, mild, moderate, and severe). The influence of frailty on outcomes, service use and costs will be explored. With the linked HES and mortality data, the University of Southampton team will also explore the relationship between frailty and secondary care outcomes and costs and mortality. Multi-state models (models which take account of the ‘level’ of frailty a patient has at any one time – i.e. fit, mild, moderate or severe) will be used to determine what clinical, demographic, and socio-economic variables are able to stratify frailty progression. Time-dependent Cox models will be used to examine the relationship between frailty state and key binary clinical outcomes (including mortality and service use). Mixed-effects negative binomial models will be used to examine the relationship between frailty state and count based clinical outcomes, such as the number of A&E attendances and unplanned hospitalisations.

The research team at the University of Southampton will use results from these analyses to inform development of guidelines for service commissioners, developed in partnership with experts in service delivery, commissioning and the study PPI representatives through stakeholder engagement. The key clinical, demographic and socio-economic drivers that are identified as significant predictors of frailty progression and/or associated with outcomes or service use patterns of interest will also be used to inform the development of a prototype simulation model. The simulation model will use a System Dynamics (SD) based approach to explore the development and impact of frailty in the population and likely future scenarios over a 12-year timeframe. SD is a computer simulation modelling approach whose purpose is to analyse changes over time in complex, interacting systems and is ideally suited for health and care systems. The statistical analyses will be used to stratify the SD model and to inform potential ‘what if’ scenarios for simulation developed with the Stakeholder Engagement Group.

WHAT WILL THE SIMULATION MODEL DO?
An SD model consists of stocks (accumulations) of material, and flows between them, analogous to a series of water tanks connected by pipes. The rate of flow along each pipe is governed by valves that can be turned up or down. A stock-flow model will be developed, depicting patient transitions between different states. In this case, the “material” is frail patients, and the stocks are the numbers of patients in different health and social care states. These states will be further broken down by those characteristics identified in Workstream 1 as significantly impacting on demand for services, or strongly associated with specific outcomes. Potential candidate characteristics include age, gender, long-term condition (LTC) diagnoses and Index of Multiple Deprivation (IMD) scores.

The model does not follow individual patients, but uses the results obtained in Workstream 1 to calculate monthly transition probabilities between states (stocks). The model will use data from Workstream 1 to capture the key clinical and demographic differences that influence these transitions, as well as information about the costs and outcomes associated with each state. Data from Workstream 1 will be used to populate the simulation model to enable accurate simulation of population trends, service use and costs.
The anticipated time horizon for running the model is ten years (2018-2027). This length of time is required to capture fully the population dynamics and the evolution of frailty. While the demographic predictions thus derived will be robust, it is recognised that any cost calculations more than two or three years into the future can only be indicative, given that service delivery modalities and health and social care organisational structures are unlikely to remain fixed for the whole period.

Moreover, there is bound to be considerable local variation. The simulation model can easily take this into account by modifying the relevant parameters. The key benefit of using simulation is that a wide range of “what-if” scenarios can be tested and compared, including demographic trends and changes to prevalence and progression rates, in addition to service delivery scenarios developed with the SEG in Workstream 3. The model outputs, which will enable comparison between scenarios, will include:
• The number of patients, and proportion of the population, in each stock over time
• Demand for services over time, aggregated or broken down by patient category
• A range of health outcome measures, aggregated or broken down by patient category
• Mortality, total or cumulative, aggregated or broken down by patient category

To develop the simulation model to allow prediction of future trends and population health burden, retrospective analysis of a number of years of population-level data is required. As frailty is a slowly developing condition and is much more prevalent in the oldest old, this study requires analysis of transitions in frailty states and health outcomes for a large ageing cohort on an individual level over at least a 10-year period. This will allow the study to capture transitions in frailty development and important health outcomes during this period.

In line with the public interest basis for this request, the data requested from NHS Digital is to provide additional longitudinal data required for delivery of this National Institute of Health Research (NIHR) funded project, specifically linked hospital outpatient, emergency department, health economic and mortality data for a cohort of primary care patients identified from the RCGP RSC dataset. The simulation modelling study will be at population level (England) for which a representative cohort has been obtained from RCGP Research Surveillance Centre. This cohort primary care data covers a range of geographical areas, urban and rural locations, and the range of deprivation levels. This data request is for linked NHS Digital HES and Civil Registration Deaths data/Mortality data, so necessarily covers the same geographical range as the primary care data.

Expected Benefits:

HOW DOES SHARING THIS DATA BENEFIT HEALTHCARE PROVISION?
The clinical management of frailty will become increasingly important as the population ages, with prevalence of frailty rising from 10% of people aged over 65, to up to 50% in those aged over 85. Despite the scale of this patient group, research indicates that half of patients with frailty are not receiving effective health care interventions. In Fit for Frailty Part 2 (British Geriatric Society, 2015), it is noted that there is potential for significant harm to frail patients if they receive inappropriate interventions. However, many services across the health and care system do not take adequate account of individuals’ frailty and so opportunities to improve quality of care are missed. Attention to the needs of older people living with frailty could, therefore, be more effective in reducing acute bed use and improving quality of care than focusing on those at high risk of admission. At the individual patient level, guidance for patient management exists and there is general agreement about the features of good quality care. There are, however, gaps in the evidence relating to the organisation and delivery of interventions and services to optimise provision of high-quality individualised patient management across the frail older population. The improved understanding of population needs offered by this study hopes to inform appropriate service planning and delivery, giving direct benefit for patients through provision of timely and appropriate care.

This study, with its emphasis on whole-system population dynamics of frailty, will explore the issues around population need, service configurations and clinical interventions highlighted above. Data from Workstream 1 (including the shared data) will be analysed and the results used to inform the simulation model in Workstream 4. A strength of the simulation modelling approach is that it allows for identification of different trajectories of care and key transition points, projection of future demand and rapid testing of the impact of different service configuration scenarios to aid decision-making. The proposed study hopes to impact on patient care directly, for example, by identifying features of people with frailty who are more likely to have adverse outcomes, identifying risk factors for frailty progression and informing targeted prevention through identification of trajectories of frailty, so enabling better targeting of interventions and services. Indirect impact may also be important, for example, through allowing commissioners to understand different care trajectories, and therefore the likely scale and nature of service demand, or service providers to identify cost-effective approaches for their specific population and facilitating the integration of health and social care.

The study outputs may have a direct benefit for commissioners; commissioning is a complex cycle involving assessment and understanding of population health needs, planning services to meet those needs, procuring appropriate and cost-effective services, and monitoring their delivery and impact. The outputs of this study has the potential to contribute at each of these stages but may have most impact in relation to assessment of population health needs. The planning stage of the commissioning cycle is often limited by a lack of reliable data on demand, particularly data which allows for forward projections; this study will address this need in relation to older people with frailty. The simulation modelling approach proposed in this study is particularly well-positioned to support commissioning, with its recent shifts towards more local commissioning, joint working and context specific (or ‘place-based’) commissioning and a focus on integrated systems of care. Integrated care organisations and commissioners may need to become more focused on needs of patients with multiple morbidity and functional problems (consistent with the presenting problems encountered in frailty) rather than disease-specific approaches.

The study team anticipate that realisable benefits from the proposed work will include guidance for commissioners and service providers on service configurations and the development of a customisable simulation model for local exploration of service demand and configurations.

The immediate project outputs from Workstreams 1 and 4 are the statistical and economic analyses, algorithms and simulation model, which will form the core of guidance for NHS commissioners and planners to aid resource planning in relation to frailty.

SPECIFIC OUTPUTS AND DISSEMINATION:
The study team will use a range of dissemination approaches to reach the various target audiences for this research. The dissemination strategy will be guided by study PPI representatives and other key stakeholders on the SEG, including carer organisations and Age UK. The study team, SEG and collaborators include senior stakeholders relevant to development of frailty services and use of the eFI, including from provider Trusts, NHS England (NHSE) Older People Team and CCGs. The study team will use their established networks to share findings with leaders in implementation and commissioning of frailty services. The team will work with the study PPI lead and SEG to plan dissemination to NHS staff ‘on the ground’ and the local and wider body of patient/carers, with a focus on making the results ‘accessible’ to the wider public, both in writing and verbally, through presentations at workshops/team meetings/to patient groups. The study team will run a dissemination planning event, to which NHS commissioners and frailty leaders will be invited, to review findings, consider their implications and implementation and explore key messages and strategies for dissemination. The study team will use their established formal social media networks to promote project outputs, and for dissemination. The team will share the results of the study with the public and staff in the relevant health, local and third sectors a public/patient friendly way by use of infographics, using plain English, and via use of local and national media and social media. In addition, the study team will summarise the findings of the work via professional journals (e.g. the Health Service Journal (HSJ)) and health service networks and professional organisations (Health Services Research Network, British Geriatrics Society).

In addition to the above, the core study team will lead on other study outputs, including academic journal papers. They will submit abstracts for oral and poster presentations at a minimum of two national and one international conference focusing on care of older people and aiming for the widest possible audience. They will submit at least two academic papers to high impact open access journals. These will be focused on the dynamics of frailty within the population and the impact of frailty on health care demand and outcomes. This analyses from Workstream 1 will provide data on incidence and prevalence of frailty, stratified by severity, in a typical older, primary care population, and the associated outcomes including emergency department use, hospitalisation and deaths. The long-term impact of frailty on outcomes and service demand and costs will be modelled. The simulation model could allow local and regional service planners and commissioners to explore a range of scenarios relevance to their specific contexts, so aiding decisions on service commissioning and design. The study team will collate the outputs of the study into a commissioning toolkit, comprising guidance on drivers of frailty-related demand and outputs from the Workstream 4 simulation model that can be used for prediction of future demand and exploration of different scenarios. The simulation model could be capable of adaptation for exploration of different service and demographic contexts. The simulation model algorithms may also be transferable to modelling of other chronic conditions that are common within the ageing population.

The study team will produce a final research report for NIHR detailing the work undertaken and results alongside an abstract, executive summary and technical appendices. The executive summary will be suitable for use as a briefing paper for NHS managers and commissioners. In addition, they will prepare a short Powerpoint presentation to present the main findings to NHS organisations. The slides will be made available, alongside the full report, on the HS&DR programme web pages and, where possible, as additional linked material with other publications. They will also work closely with the University communications team and ensure that members of the study team are given appropriate support and training in handling enquiries from the media.

i) Development of guidance and commissioning toolkit for service providers and commissioners to inform planning over a 15 year+ period
ii) Development of a simulation model that may allow service planners and commissioners to explore scenarios and trends tailored to local and regional populations
iii) Future development of the simulation model of population trends into a workforce planning tool
iv) Future adaptation of the simulation model algorithms to explore health care demand and mitigation scenarios in relation to other conditions within the ageing population

Better understanding of the development and dynamics of frailty over time could facilitate service and workforce planning and commissioning. Outputs of the study will include guidance for commissioners, a simulation model to facilitate prediction of service demand associated with frailty and the potential for development of these resources into a workforce planning toolkit. The simulation model architecture, and the know-how relating to populating and operationalising the model may be transferable to prediction of demand for other populations and conditions with a high population prevalence (e.g., dementia, obesity, mental health problems). As the models are based on national-level data, the application of results and the ability to adapt the model to geographical locations means that the impact may be nationwide within the UK, and the information may also be adapted on an international level.

HOW THE BENEFITS WILL BE ACHIEVED, AND TIMELINES
The study team (including researchers at the University of Oxford and Southampton) will achieve the benefit, working together with the NIHR to ensure appropriate dissemination and with third parties such as NHS Commissioners to realise the benefits.

The Stakeholder Engagement Group (SEG) includes representation from local Strategic Transformation Partnership (STP), including from Clinical Commissioning Groups (CCGs), local authorities, and provider organisations, in addition to national commissioning representatives. The SEG also includes the PPI lead, PPI representatives from the Ageing & Dementia PPI panel and representation from third sector organisations, including Age UK. This will ensure that the results from the analyses and simulation model are discussed with the right people to make the appropriate changes to the healthcare system.

The study outputs will be monitored by the independent Study Steering Committee (SSC) according to the study Gannt chart, publication plan and dissemination activities. For example, milestones such as simulation model production, analysis of scenarios, commissioning guidance and toolkit and dissemination and implementation events will all be reviewed by the SSC.

Epidemiological analysis of the primary care and linked HES/mortality data is expected to be complete within 9 months of data delivery, enabling provision of aggregate data to inform the simulation model and scenario development. The simulation model and related outputs including scenarios is projected to complete by the end of 2022.

Outputs:

There will be several outputs by the end of the study. The target groups and individuals for the outputs will include:
• academic
• scientific
• professional
• policy makers (both political and professional) involved in deciding future health policies

The main report will be delivered by 30th March 2022 delivered to the study funder and academic papers and seminars will be delivered in the following year.

The immediate project outputs will be:
• statistical and economic analyses - in the form of aggregate data tables, graphs, reports and submissions to peer reviewed journals, with any small numbers suppressed (in line with the HES Analysis Guide)
• oral and poster presentations at a minimum of two national and one international conference focusing on care of older people and aiming for the widest possible audience. The research team will submit at least two academic papers to high impact open access journals.
• Guidance for providers/commissioners
• Algorithms, simulation model and interactive dashboard for simulation

These outputs will form the core of guidance for NHS commissioners and planners to aid resource planning in relation to frailty. Study Patient and Public Involvement (PPI) representatives, drawn from the core study team and the School of Health Sciences Ageing & Dementia Research PPI Panel at the University of Southampton, will advise on dissemination and implementation through the SEG events and a study dissemination planning event.

The study team, Study Engagement Group and collaborators includes senior stakeholders relevant to development of frailty services and use of the electronic Frailty Index (eFI), including from provider Trusts, National Health Service England (NHSE) Older People Team and Clinical Commissioning Groups (CCGs).

The study team will use the established networks to share findings with leaders in implementation and commissioning of frailty services nationally. The team will work with the study PPI lead and SEG (including the Age UK representative) to plan dissemination to NHS staff 'on the ground' and also the local and wider body of patient/carers, with a focus on making the results 'accessible' to the wider public, both in writing and verbally, through presentations at workshops/team meetings/to patient groups. The study team will run a dissemination planning event, to which NHS commissioners and frailty leaders will be invited, to review findings, consider their implications and implementation and explore key messages and strategies for dissemination.

Processing:

As per the definition of ‘controller’ in the General Data Protection Regulation (1), both University of Southampton and the RCGP RSC research group based at the University of Oxford determine the purposes and means of the processing of personal data. The Principal Investigator (PI) at University of Southampton determines the study aims and objectives, the personal data that will be processed and the analyses that will be carried out. The University of Southampton staff working on Workstream 1 will also have access to the pseudonymised, linked primary care, HES and mortality data provided by RCGP RSC. In this case, University of Southampton are controllers in that they determine why the personal data are processed. The RCGP Research Surveillance Centre based at the University of Oxford determines the means of processing the data and approves its purpose; the University of Oxford therefore has oversight of study aims and objectives via the RCGP Research Surveillance Centre. University of Southampton and the University of Oxford are therefore joint Data Controllers.

Data flow into NHS Digital will consist of hashed identifiers for the study cohort (adults aged 50 and above registered with an RCGP practice at any year from 2006 to 2017 inclusive). The hashing of identifiable data for the Clinical Informatics and outcomes Research Group (RCGP Research Surveillance Centre) is conducted by the Salt Service of the University of Oxford Central IT team, so that the holder of the pseudonymised data is separated from the service that holds the non-reversible hash key. This avoids pseudonymised data becoming identifiable data.

NHS Digital will hash their NHS numbers using the same pseudonymisation algorithm (SHA-512). NHS Digital will undertake data linkage via the hashed NHS numbers in both sets of data. This process has been used for previous projects linking different sets of data, and the linkage has been successful. Records for each study participant containing information from HES and mortality data, together with hashed NHS numbers will be sent to the University of Oxford.

All individual-level data will then be stored and analysed at the University of Oxford. There will be no subsequent flows of individual level data from the University of Oxford. Aggregate analyses will be shared with the wider study team and used in dissemination of the research.

Apollo Medical Software Solutions, an approved third-party provider, has formal service agreements and service specifications with RCGP Research Surveillance Centre and with individual participating GP practices to conduct data collection and secure web transfer. (Copies of these formal agreements and technical details were shared with NHS Digital in the last IGTK assessment and were deemed satisfactory and are available to legitimate requests).

Each unique patient within the RCGP RSC databank is de-identified at source before data is extracted from individual practices using a computer-generated patient identifier created by Apollo Medical Software Solutions. This de-identification of records includes production of a hashed NHS number using pseudonymisation algorithm (SHA-512).

Pseudonymised record-level HES data will be processed and stored at the University of Oxford. Patient level databases (such as this study’s RCGP RSC dataset) are held in the database server within the RCGP Research Surveillance Centre Research Group's secure network. The Research Group's dedicated secure network is sited behind a firewall within the University's network. It is a standalone, independent network, all in-bounded connections are block, but out-bounded connections are allowed. All staff members of the research group working within the team base work from secure workstations or secure laptops with encrypted drive. Only substantive employees of the University of Oxford will have access to the data and only for the purposes described in this document. The data will be used solely for the "Dynamics of frailty in older people" study.

The University of Oxford will send the hashed NHS numbers to NHS Digital. The following flow of hashed NHS numbers will be undertaken.

The study group is the cohort of patients aged 50 years and over in registered in RCGP Research Surveillance Centre network practices 2006. University of Oxford will identify the study patients for the cohort above from primary care records in the RCGP Research Surveillance Centre practices and send the hashed NHS numbers of the cohort under study to NHS Digital to link to HES/ Civil Registration Data (CRD).

No other GP data will be sent to NHS Digital.

The process of linkage is as follows:
• University of Oxford’s senior SQL developer will submit the cohort to NHS Digital, with hashed NHS numbers using the pseudonymisation algorithm SHA-512
• NHS Digital will hash their NHS numbers using the same pseudonymisation algorithm (SHA-512) as used by the RCGP Research Surveillance Centre.
• NHS Digital will undertake data linkage via the hashed NHS numbers in both sets of data. This process has been used for previous projects linking different sets of data, and the linkage has been successful
• NHS digital extract all HES and CRD records for which there are matched primary care records.
• NHS digital will send the extract of HES and CRD records with the hashed NHS number to the University of Oxford.
• University of Oxford will link the HES and CRD records together with GP data from the primary care records from RCGP Research Surveillance Centre network practices with the same hashed NHS numbers.
• Records for each study participant will when fully linked contain information from HES and CRD, together with information from RCGP Research Surveillance Centre network primary care practices.

Each unique patient within the RCGP RSC dataset is de-identified at source before data is extracted from individual practices using a computer-generated patient ID. The University of Oxford holds no identifiable data and only hashed NHS number.

Only pseudonymised data with direct patient identifiers removed will be used. The research team will not seek individual patient identifiers; where required, data linkage will be achieved through ‘hashing’ algorithms to generate non-identifiable, unique IDs from identifiable data. As a further protection, non-reversible, pseudonymised ID numbers held be database organisations will be converted to unique study IDs, the keys to which will not be accessible to the research team; and, when using these data the research team will suppress small numbers in reporting and avoid the presentation of data that can potentially be used to reveal identities. Data extracts and aggregate analyses will be pseudonymised as described.

All data processing will be carried out by staff employed by the University of Oxford. Data analysis will be carried by staff employed by the University of Southampton and the University of Oxford. All staff have received Information Governance training on an annual basis and have all passed the NHS Information Governance on-line test for the current year.

Access to the data will limited to either:
1) Researchers with substantive employee contracts with the University of Oxford
2) Senior researchers from the University of Southampton. Southampton researchers will be required to complete training and sign the relevant agreements to be able to access the data on the University of Oxford secure environment. No individual-level study data can leave this environment, and all aggregated results data is reviewed prior to export.

The Research Group at the University of Oxford has conducted a risk assessment of the physical security of the offices and servers where patient level data is kept. The Research Group of Department of Clinical and Experimental Medicine at the University of Oxford has worked with routinely collected healthcare data in several research and evaluation projects over the last 15 years. The Research Group works within the Research and Information Governance team at the University of Oxford.

No data is stored outside of the secure computer system hosted at the University of Oxford.

National Core Studies - Data and Connectivity: COVID-19 Vaccines Pharmacovigilance (DaC-VaP) — DARS-NIC-431355-B1L8W

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-07 – 2022-07 2021.10 — 2021.12.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. COVID-19 Hospitalization in England Surveillance System
  3. COVID-19 Second Generation Surveillance System
  4. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  5. COVID-19 Vaccination Adverse Reactions
  6. COVID-19 Vaccination Status
  7. Diagnostic Imaging Dataset
  8. Emergency Care Data Set (ECDS)
  9. Mental Health Services Data Set
  10. MSDS (Maternity Services Data Set)
  11. Secondary Uses Service Payment By Results Accident & Emergency
  12. Secondary Uses Service Payment By Results Episodes
  13. Secondary Uses Service Payment By Results Outpatients
  14. Secondary Uses Service Payment By Results Spells
  15. MSDS (Maternity Services Data Set) v1.5
  16. Civil Registrations of Death - Secondary Care Cut
  17. COVID-19 Second Generation Surveillance System (SGSS)
  18. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  19. Diagnostic Imaging Data Set (DID)
  20. Maternity Services Data Set (MSDS) v1.5
  21. Mental Health Services Data Set (MHSDS)
  22. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

OVERALL AIM
This application is part of the urgent public health study that is funded by HDRUK to investigate the pharmacovigilance of the COVID-19 vaccine.

The purpose of this application is to link data held by NHS digital to support the University of Oxford to conduct observational epidemiological studies that inform the national public health response to COVID-19 and importantly the COVID-19 vaccine. The RCGP RSC dataset includes individual patient level up-to-date primary care data which can be easily queried. Primary care/general practice data is rich in terms of diagnosis and information about the process of care. For example, the database contains the following variables for each patient (where present)

Specifically, the objectives are to: measure variation in vaccine uptake in relation to a)population characteristics; b) assess vaccine effectiveness (VE) against infection, transmission, severe outcomes, and deaths; and c) identify the risk of adverse events following immunisation (AEIs).

The “outcome” measures of vaccine effectiveness are:
- Incidences of vaccine preventable disease (VPD) – e.g. COVID-19, influenza etc.
- Hospital admission – usually within 28 days of suffering from the index VPD
- Intensive care admission
- Death, again usually within 28 days of the index date of the VPD

Real time information will be provided to Public Health England (PHE), and through them to the Joint Committee for Immunisation and Vaccination (JCVI) and SAGE. The requirement varies with the stage and impact of any VPD.

The study involves COVID-19 vaccine pharmacovigilance across England, Wales, Scotland and Northern Ireland, where each of the nations do their own analyses within their secure environment. The University of Edinburgh will liaise with each of the analyses leads in the four nations.

The study team are requesting to utilise all the datasets coming into the University of Oxford secure environment as part of the MAINROUTE (DARS-NIC-381683-R6R6K) agreement.
The datasets included are:
- Detailed demographic and risk factor data.
- COVID-19 appointments: information on whether or not a virology swab was taken and the outcome of the swab
- Non-COVID-19 appointments
- Detailed data for the 32 conditions monitored by RCGP RSC on behalf of PHE
- Vaccination status: date of vaccination, type of vaccination
- Co-morbid conditions
- Medication which may be associated with better or adverse outcomes.
- Test results
- Referrals made
- A&E visits
- Inpatient appointments, including critical care
- Secondary Uses Services Payment by Results (SUS)

Datasets that are requested to flow under this agreement are:

- COVID-19 Second Generation Surveillance System (SGSS) – (Pillar 1)
- COVID-19 UK Non-hospital Antigen Testing Results (Pillar2)
- Civil Registrations (Deaths)– Secondary Care Cut
- Mortality data
- Maternity Services Data Set (MSDS)
- Covid-19 vaccination status and adverse effects following vaccination

The impact of infection on pregnancy (including the need for intervention), and the impact of infection on infants in the months of life (if their mother is not immune) are really important. For example, if mothers are not immune to RSV or influenza – then there are no antibodies crossing the placenta to protect the young infant. Hence vaccine uptake in pregnancy and linkage to infant outcomes are a very important part of our academic work. Capturing vaccine exposure in pregnancy is important. As no trial to date has included pregnant women this type of study is the only opportunity to explore safety and effectiveness in pregnant women and their babies.


The same pseudonymisation algorithm will be applied to all data involved in this study (and any other studies) so the researchers can draw scientific conclusions for a study population.

The University of Oxford is the sole data controller for processing the data that is mentioned within this agreement. Some of the data which will be accessed under this agreement will be data which is already in the hands of University of Oxford under a different agreement DARS-NIC-381683 for which University of Oxford operate as a Data processor for on behalf of Pubic Health England (PHE) and the Royal Collage of GPs (RCGP). This agreement will also flow new data sets (such as the COVID-19 vaccine data) which are not currently held by the Data Controller and these datasets are only for use by the Data Controller (University of Oxford) for the purposes set out in this data sharing agreement.

University of Oxford – The University are a data processor for the surveillance activities it undertakes for PHE In addition to surveillance, there is an agreement between PHE and Oxford to use the data collected for surveillance activities for further research studies, for which University of Oxford will be the data controller. the work being undertaking under this agreement falls in the further research area which is under University of Oxford control.

University of Edinburgh - This study is part of urgent public health studies and funded by the HDRUK Data and National Connectivity Studies, Rapid Funding Call. Edinburgh applied for the funding on behalf of University of Oxford as they are managing the home nations response. Each of the home nations are taking control of the work within their regions and so for England the University of Oxford are the sole Data controller with their own ethical approval in place for this work. The University of Edinburgh do not make any decisions about the means by which the personal data are being processed under this agreement.

The data will only be processed by University of Oxford. Analysts at University of Edinburgh may gain access to outputs which will be aggerated with small numbers suppressed in line with the HES analysis guide.

The GDPR Lawful basis for processing the requested data under this agreement are;

Article 6(1)(e) (Public Task processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller).

Article 9(2)(j) (processing is necessary for reasons of public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interest of the data subject.

Only the named Data Controller and Processor have permission to access the record level data provided under this agreement. The size of the cohort is 25,428,392 individuals.

The DaCVAP and AstraZeneca (AZ) programme of work are different analyses over different time periods, using different datasets and range of data sources. The results will hopefully be compatible and comparable but quite different. Achieving similar results from different lines of enquiry is an important part of science – particularly in epidemiologal studies like this where we identify associations, rather than measure direct causation.

The main difference between the DaCVAP study and the AZ programme is the nature of the analysis. The DaCVAP study looks to report the relative risk (how much more likely the event is), whereas the AZ analysis will provide the rate of these events. The former may say that an event is two or three times more common, the latter is that the rate in the unvaccinated group is 1 per million and that in the vaccinated group 2 pear million (these rates are just illustrative and not based on analysis).

In greater detail: The AZ approach is that of a cohort study and therefore utilises the entire RCGP ORCHID cohort and eventually, in phase 2, the wider English cohort available in NHS Digital. The DaCVAp study is a nested case control study and, for each case utilises up to 10 controls (people in RCGP ORCHID who have not, by index date - event date of the case - have not experienced an event of interest). Post-hoc confirmatory analysis will be carried out via a self-controlled case series model. The cohort, AZ approach, allows for the calculation of incidence rates (absolute risk) as well as relative risk, furthermore it allows for a wider set of modelling techniques, namely AI ensemble and compartmental, mathematical modelling to be implemented. There are additionally differences in the variables, time periods and matching approaches between the studies. DaCVAP also coordinates a distributed analysis across the four UK devolved nations, whereas our AZ study is just with English data.

Expected Benefits:

Analyses conducted under HDRUK-funded DaC-VaP will lead to a better understanding of the characteristics of patients being tested for COVID-19 and the associations between demographics, comorbidity and medications on the likelihood of developing COVID-19 post COVID-19 vaccinations and subsequent complications, if any. The major benefit of this study is to see differences between various demographic characteristics, especially ethnicity.

Moreover, the study will establish the safety of COVID-19 vaccination and its effectiveness to reduce COVID-19 infections. Analyses will also establish if COVID-19 vaccine will have an impact on other flu-like illness. All these will benefit public health and will inform them about the benefits of the COVID-19 vaccine.

Furthermore, the study will support COVID-19 vaccine surveillance.

Outputs:

Specific Outputs for this study are:
• To measure the outcome of the COVID-19 vaccine
• To look at risk of COVID-19 infections, hospitalisations and deaths post vaccination
• To track the impact of COVID-19 vaccination in terms of visual descriptions (dashboards) of the number and rates of patients vaccinated.
• Subgroups of data will be identified to enable display of vaccination by GP practice, region, age group, gender, and ethnicity
• Furthermore, ability to track number of patients receiving one or both of the COVID-19 vaccine dose, vaccine brand and categorise by age group, gender, ethnicity.
• To establish differences in the vaccine effectiveness between the different brands of vaccine and different doses

A protocol of the study design will be published (already submitted to The Lancet) as well as publish papers in international journals. A number of publications are expected across each of the 4 nations as well as one for the harmonised analyses

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Patient and Public Involvement and Engagement (PPIE) members have been involved since the beginning of this project. Research proposal for the Wales analysis has also been reviewed by members of the public. Their contribution includes defining research questions, interpretation, and dissemination of study findings. The PPI and study team did a survey around vaccine emotions due to the high media discussion around the Oxford –AZ COVID-19 safety. The PPI group showed high confidence in vaccine safety and felt strongly that the media attention could be a political issue (EU and UK). They do have concerns about the long term impact of COVID-19 (Long COVID). The PPI have further raised the potential need of COVID-19 booster doses and also making the vaccine mandatory for work and/or travel.

Processing:

Flows of data:
- Data are extracted from practices that are members of the Royal College of General Practitioners (RCGP RSC) Research and Surveillance Network by Wellbeing. The University of Oxford subcontracts with Wellbeing to do this as part its contractual responsibilities.
- The University of Oxford will provide NHS digital with a list of pseudonymised NHS numbers and pseudonymised date of birth for the cohort monthly.
- NHS Digital will link the cohort to the requested datasets and send pseudonymised linked datasets securely back to University of Oxford.
- University of Oxford will store the data on the secure network.
- University of Oxford will process and aggregate pseudonymised data to produce approved reports for surveillance (as part of the National surveillance process); and for the purpose of COVID-19 vaccine pharmacovigilance and quality improvement.

No identifiable data items will be passed into or out of NHS Digital

SALTING METHODLOGY:
The University of Oxford will follow a salting method in a manner that all the data will be non-identifiable. The process is as follows:
1. An encryption salt is held by a designated staff member of the University of Oxford Medical Science Division who is not a member of the ORCHID staff.
2. When a data linkage is required, the encryption salt holder sends the encryption salt to the data provider (NHS D)
3. The data provider will hash personal identifiers (in the data requested by ORCHID) using a hashing algorithm
4. The hashing algorithm is SHA2-512.
5. To make this key unique, an encryption salt is added at the end of the NHS number (e.g. NHS number= 12345678 ; SALT (held by someone other than ORCHID staff) = bob. So, hashing would take place using the SHA2-512 alogrithm by 12345678bob = return pseudonymised data)

The data is controlled and processed by a group of staff who are all based at the University of Oxford; all are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Language Query (SQL) developers, practice liaison officers, a project manager and a head of department. The team work from secure workstations or secure laptops with encrypted drives within the group’s secure network.
Data will only be accessed by individuals within the University of Oxford who have authorisation that are substantive employees of University of Oxford. The authorisation process includes: (1) Contractual requirement to follow IG principles; (2) Using the email registered with Human Resources to complete IG training and to return the certificate; (3) Staff email is authorised by the IT department for one year to access the secure network and staff computers are configured to allow this; (4) At any point the project managers or Head can have access to the secure network turned off. There is special authorisation to have access to the main database.

The additional linkages will be added to the data that the University of Oxford already receives from the RCGP RSC network practices and PHE reference laboratories.

This process for previous projects linking different sets of data, and the linkage has been successful, provided both parties use the same pseudonymisation algorithm (SHA-512).

There will be no requirement nor attempt to re-identify individuals from the data. The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

The use of national data is needed as the University of Oxford are a national surveillance centre and the cohort are from across England and Wales.

The use of pseudonymised NHS numbers are essential as the request to link to the data that the University of Oxford already received from the RCGP RSC network general practices and PHE reference laboratories.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

R15 - The Platform Randomised trial of INterventions against COVID-19 in older peoPLE (PRINCIPLE) trial — DARS-NIC-373132-D3Y7P

Opt outs honoured: No - consent provided by participants of research study, No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2020-11 – 2021-10 2020.11 — 2021.10.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Secondary Uses Service Payment By Results Spells
  2. Secondary Uses Service Payment By Results Episodes
  3. Secondary Uses Service Payment By Results Outpatients
  4. COVID-19 Hospitalization in England Surveillance System
  5. Secondary Uses Service Payment By Results Accident & Emergency
  6. Civil Registration - Deaths
  7. Secondary Uses Service Payment By Results Accident & Emergency
  8. Civil Registrations of Death

Type of data: Identifiable

Objectives:

University of Oxford are running the Platform Randomised trial of INterventions against COVID-19 In older people (PRINCIPLE) Trial.

COVID-19 disproportionately affects people over 50 years old with comorbidities and those over 65 years old. The infection causes considerable morbidity and mortality in this population group in particular, and is having a devastating effect on people's health, and society in the UK and internationally. So far, there are no specific treatments for COVID-19 that have been proven in rigorous clinical trials to be effective. Most cases are being managed in the community. It is essential that we urgently identify interventions that may favourably modify progression of the infection. An ideal intervention would be one that is safe, with few side-effects, helps prevent disease progression, and can be administered in the community using existing NHS processes and capability.

Setting up a bespoke randomised controlled trial for each potential intervention that might become available will be inefficient. The University of Oxford therefore propose establishing a platform, randomised controlled trial in primary care that can be rapidly deployed to evaluate low risk interventions for high risk people. Using an efficient open clinical trial design, with procedures embedded in existing health service structures and capabilities as afar as possible, our trial aims to give a rapid answer about the effectiveness of trial treatments in modifying the disease course. The goal is to prevent disease progression such that affected individuals will recover sooner, but critically, avoid the need for hospital admission. The platform trial will be flexible in that it will operate under a master protocol that will allow the addition of further interventions into the trial while the trial is already in progress, should such suitable interventions become available for this kind of evaluation.(5) This means that a new trial does not need to be started afresh each time an additional suitable intervention becomes available, and it also means that existing controls can be used efficiently to give rapid answers about the effectiveness of new interventions. This is particularly important as new candidate interventions are being considered on a regular basis.

The trial will be implemented in the first instance by the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) general practices. This is one of Europe's oldest sentinel systems. RCGP RSC has produced a weekly report of influenza, respiratory and other infections in primary care for over 50 years. RCGP RSC works closely with Public Health England (PHE). More information at: www.rcgp.org.uk/rsc. The RCGP RSC Network has over 500 practices, including 100 practices currently swabbing patients with suspected COVID-19 in partnership with Public Health England (PHE).

Trial aspects will be managed by the UK Clinical Research Collaboration Registered University of Oxford Primary Care and Vaccines Clinical Trials Unit.

The trail participants will be consented into the trial and will be made up of Patients ≥50-64 years with comorbidities, and aged ≥65 with or without comorbidity presenting within 7 days since onset of symptoms with a new continuous cough and/or high temperature during time of prevalent COVID-19 infections. Recruitment has commenced and at the time of writing approx. 1500 patients are enrolled. A sperate agreement is in place with NHS Digital to aid and boost recruitment of individuals into the trial.

Primary objective of PRINCIPLE - To assess effectiveness of trial treatments in reducing the need for hospital admission or death, for patients aged ≥50 years with comorbidity, and aged ≥65 with or without comorbidity and suspected COVID-19 infection during time of prevalent COVID-19 infections.

Primary objective outcome measures: Hospital admission or mortality related to suspected COVID-19.

Secondary objectives - To explore whether trial treatment reduces
1) Duration of severe symptoms
2) Time taken to self-report recovery
3) Contacts with the health services
4) Consumption of antibiotics
5) Hospital assessment without admission
6) Oxygen administration
7) Intensive Care Unit admission
8) Mechanical ventilation
9) To determine if effects are specific to those with the infections syndrome but who test positive for COVID-19
10) Duration of hospital admission

Secondary objective outcome measures:
1-2 Patient report on day they feel to have recovered (Daily online symptoms score. Telephone call or text day 7, 14 and 28 if data not being received online).
3. Contacts with health services reported by patients and captured by reports of patients linked medical records where the practice is a member of RSC (GP notes review through RCGP RSC network after 28 days and linkages to HES/ECDS/SUS/CHESS)
4. Bi-weekly reports from participants primary care medical records (RSC)
5-8 and 10 patient report/carer report/linked medical records from primary care and hospital care (HES/SUS/MORTALITY/CHESS/RSC data linkage after 28 days where patients have been assessed in hospital)
9. Swab results for COVID-19 will indicate an “Intention to Treat Infected” group within the overall cohort for sub analysis from national laboratory infrastructure (RSC/SGSS)

Organisations Involved
The University of Oxford are the sole data controller for this request.

Public Health England (PHE)

For the purposes of the PRINCILE trial PHE do not hold any data controllership responsibilities. However members of the statistical team are based at PHE working under the direction of the data controller and are therefore lusted as data processors.

Royal Collage of General Practitioners (RCGP)

For the purpose of the PRINCIPLE trial RCGP are not a data controller. The RCGP are joint data controllers for the RCGP RSC collected data which is being linked to the cohort data. The RCGP play no role in determining the means by which or the purpose for which the data will be processed for the PRINCIPLE trial.

University of Surrey

The RCGP Research Surveillance Centre (RCGP RSC) was based at the University of Surrey, but is in the process of transferring to Oxford. Data being shared for the PRINCIPLE trial will be sent to Surrey so that the data they hold on the RCGP RSC for the consented cohort can be linked to the PRINCIPLE cohort. The RCGP RSC is a growing network of over 1200 GP surgeries based in England. University of Surrey are data processors

The University of Surrey acts as Data Processor on behalf of the Data Controller for the PRINCIPLE trial (Oxford). An existing secure network at the University of Oxford is progressively housing the RCGP RSC data. This data collection is known as (ORCHID secure). This process is underway and due to be completed by early 2021, at which stage all these data will all be held on the Oxford secure network.

University of Surrey are a joint data processor they currently host the RCGP RSC Database for which the trial participants data will also be linked with. The RCGP RSC dataset includes individual patient level up-to-date primary and secondary care data which can be easily queried. Primary care/general practice data is rich in terms of diagnosis and information about the process of care. For example, the database contains the following variables for each patient (where present):

• Detailed demographic and risk factor data.
• COVID-19 appointments: including information on whether or not a virology swab was taken and the outcome of the swab
• Non-COVID-19 appointments.
• Detailed data for the 32 conditions monitored by RCGP RSC on behalf of PHE
• Vaccination status: date of vaccination, type of vaccination
• Co-morbid conditions
• Medication which may be associated with better or adverse outcomes.
• Test results
• Referrals made
• A & E visits
• Inpatient appointments, including critical care
• Outpatient appointments
• Mortality data (if applicable).

Expected Benefits:

There is an urgent need to report the data from the >1,500 patients who have joined the trial. The results may have immediate impact on management of suspected COVID-19 infection and this study rightly has urgent public health status.

The extracted data will identify whether there is undetected community transmission of COVID-19. For cases of COVID-19 PRINCIPLE will report the effectiveness of different treatments given early in the disease on health outcomes. For cases of COVID-19 the associations between demographics, comorbidity and medications on the likelihood of developing COVID-19 and subsequent complications (e.g. hospitalisation, admission to an intensive care unit, death).

For PRINCIPLE linked data allows the primary and secondary objectives of the trial to be achieved as detailed in the previous "objective" section. It also allows validation and enhancement of sociodemographic and comorbidity data for PRINCIPLE participants

Outputs:

Specific outputs for this trial are:

PRINCIPLE will publish the results of each CTIMP investigated in open-access journals with summary reports made publicly available through the study website (https://www.principletrial.org/).

PRINCIPLE will work with patient and public representatives to ensure that such reports are communicated in an appropriate manner for a lay audience. The Investigators will be involved in reviewing drafts of the manuscripts, abstracts, press releases and any other publications arising from the study. Authors will acknowledge that the study was funded by UKRI/NIHR and any other funding that is secured. Authorship will be determined in accordance with the ICMJE guidelines and other contributors will be acknowledged. All outputs are expected to be submitted by the end of 2022.

Guidance how to manage cases of COVID-19 on presentation to primary care or other community services will be produced.




Processing:

Participants who have consented to the PRINCIPLE Trial will have their data initially linked with the primary care data which is already held as part of the Royal College of General Practitioners (RCGP RSC) Research and Surveillance Network database.

• The University of Surrey, on behalf of the University of Oxford for the PRINCIPLE trial, will provide NHS Digital with a list of NHS numbers and date of births along with a unique Study ID for the PRINCIPLE cohort. A specific University of Surrey IT team within the IT department will share the identifiers with NHS D not the research team.

• NHS Digital will send back to University of Surrey the linked cohort data with SUS/CHESS and Mortality data included.

• University of Surrey will store the data on the secure network researchers will then analyse a pseudonymised data to produce outputs for the PRINCPLE Study.

The data is controlled and processed by a group of staff who are all based at the University of Surrey; all are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Language Query (SQL) developers, RCGP RSC practice liaison officers, a project manager and a head of department. The team work from secure workstations or secure laptops with encrypted drives within the group’s secure network. These same processes are replicated in Oxford.

The general practices in the RCGP RSC take virology swabs and serology samples to know if someone has a COVID-19 or a range of other infections, including influenza. These results are being passed back to the patients GP for their clinical care. However, a pseudonymised copy will go to the RCGP RSC. The COVID-19 status will be shared with the PRINCIPLE trial team (who also pseudonymise NHS number to allow this linkage).

NHS Digital data being accessed by a statistician in the USA will be aggregated with small numbers suppressed. All record level data will be held and stored within England and Wales.

RAPid Testing fOR Covid-19 (RAPTOR-C19). — DARS-NIC-396119-C8W3W

Opt outs honoured: No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-02 – 2022-02 2021.06 — 2021.06.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. COVID-19 Hospitalization in England Surveillance System
  3. COVID-19 Second Generation Surveillance System
  4. Civil Registrations of Death
  5. COVID-19 Second Generation Surveillance System (SGSS)
  6. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Type of data: Identifiable

Objectives:

RAPID COMMUNITY POINT-OF-CARE TESTING FOR COVID-19 (RAPTOR-C19) is a study being run by the University of Oxford.

The NHS urgently needs quick, accurate rapid diagnostic tests to diagnose people with coronavirus or to confirm that people do not have the infection. Point-of-care Tests (POCTs) can be used in community settings where there is no easy access to a specialist laboratory. They provide quick results that allow people to get immediate advice about self-isolation and treatment, potentially blocking further spread of infection in the community. Companies are quickly developing new rapid diagnostic tests, but we do not know how well they work. Some tests give a result like a pregnancy test by using a drop of blood from a finger prick. Others use saliva, or a swab to collect a sample from the nose or throat.

Companies check tests work in their laboratories, but usually tests do not work as well when used in the field with real patients. Accurate rapid diagnostic tests are important so that people are not falsely reassured when they are infected, and are not wrongly diagnosed when they are not really infected.

The University team manages a national surveillance system with a network of community settings including GP practices from all over England that report directly to the Department of Health and Social Care about a wide range of infections. These GP practices have been testing for coronavirus since January 2020 with samples sent for laboratory tests. In this study, practices in the network will quickly compare new POCTs for coronavirus with laboratory tests so we can see how good the new tests are in a coordinated and efficient way. National COVID-19 Test centres may also support the research project.
There are currently no rapid diagnostic tests that have been evaluated as fit-for-purpose in NHS primary care that aim to identify whether adults are currently, or have been, infected by COVID-19. The UK and wider world is in the midst of the 2019 novel coronavirus (SARS-CoV-2) pandemic. Accurate diagnosis of infection, identification of immunity and monitoring the clinical progression of infection are of paramount importance to our response, and for all of these diagnostics are central. Widespread population testing has proven difficult in western countries and has been limited by test availability, diagnostic test sensitivity, human resources and long turnaround times (up to 72 hours). This has limited our ability to
control the spread of infection and to develop effective clinical pathways to enable early social isolation of infected patients, early treatment for those most at risk and early return to work for those with resolved infection and potential immunity.

POCTs can be used in the community where there is no easy access to a specialist laboratory, in locations such as NHS general practices. POCTs provide quick results that allow people to get immediate advice about self-isolation and treatment, potentially blocking further spread of infection in the community. In-context evaluation of POCTs in the community is important as test accuracy can vary based on the prevalence of disease in the population tested. “In-context” in this case means “in the clinical environment that the test is to be used”, for example, RAPTOR is evaluating tests for use in general practice, in general practice. This is an important process as tests perform differently (either more or less accurate) when used in different settings / environments / contexts.

The severity of the COVID-19 disease in the community is much lower than in hospital patients. Symptomatic acutely unwell hospitalised patient are likely to have higher viral loads that are easier to detect, and may be undergoing invasive procedures to collect samples from the lower respiratory tract, that have a higher yield. Testing only severe patients introduces spectrum bias, and biases the results to overestimate test performance. It is important to diagnose hospital patients, but from a public health point of view the most concerning patients are ambulatory outpatients, who may spread the virus much further in the community if falsely reassured. Evaluations of COVID-19 POCTs are therefore required in each clinical setting. Community based POCTs may lead to additional public health impacts such as reducing onward household transmission of COVID-19, improving surveillance of NHS and social care staff, accurate prevalence estimates, and understanding of COVID-19 transmission dynamics in the population.

RAPTOR-C19 will provide the community testbed to the COVID-19 National DiagnOstic Research and Evaluation Platform (CONDOR). It should be noted that CONDOR will not contain any NHS Digital data.

RAPID COMMUNITY POINT-OF-CARE TESTING FOR COVID-19 (RAPTOR-C19)

Aim - to assess the diagnostic accuracy of multiple current and emerging point-of-care tests (POCTs) for active or past COVID-19 infection in the community setting.

It is estimated that up to 10,000 patients will be recruited for the trial (approximately 1,500 patients per test).

Specific objectives - RAPTOR-C19 will incorporate a series of prospective observational parallel diagnostic accuracy studies of COVID-19 POCTs against laboratory and composite reference standards in patients with suspected current or past COVID-19 attending RCGP RSC general practices. Because the current reference tests are imperfect, the RAPTOR-C19 protocol allows “standard” and “enhanced” diagnostic accuracy studies for active and past infection:

• Standard diagnostic accuracy of POCTs for active COVID-19 infection with reference to Public Health England (PHE) reference standard virology testing.
• Standard diagnostic accuracy of POCTs for past COVID-19 infection with reference to PHE reference standard serology testing.
• Enhanced diagnostic accuracy of POCTs for active COVID-19 infection assessed against a composite reference standard using multiple tests data, linked Electronic Health Records (EHR) data, and patient reported outcomes data
• Enhanced diagnostic accuracy of POCTs for past COVID-19 infection assessed against a composite reference standard using multiple tests data, linked EHRs, and patient reported outcomes data

Composite reference standards - An assumption of standard diagnostic accuracy studies is that the reference standard is infallible. This constrains the performance of the index test to the performance of the reference standard and assumes every time the tests get different results the reference is correct and the index is incorrect. In reality, the reference standard is unlikely to be perfect, so we will undertake further analyses using composite reference standards. Composite reference standard 1 will be designed to minimise false negatives (FNs), and composite reference standard 2 will be designed minimise false positives (FPs).

For example, for POCTs for current infection:
1. A positive composite reference standard to minimise the impact of a FN PHE reference test result for current infection at visit one / increase sensitivity will also include:
i. paired PHE antibody testing suggesting active infection at visit one (positive Immunoglobulin G (IgM)) and past infection at visit two (positive Immunoglobulin G (IgG)), or
ii. EHRs showing a confirmed COVID-19 diagnosis (in another setting), such as a 111 contact, COVID-19 hospital related admission or death in the following 28 days, or
iii. a positive household contacts within 14 days identified via RCGP-RSC

2. A positive composite reference standard to minimise the impact of a FP PHE reference test result for current infection at visit one / increase specificity will also include:
i. at least two positive PHE reference tests for current infection, or
ii. paired PHE antibody testing suggesting active infection: visit one (positive for IgM) and visit two (positive IgG), or
iii. linked EHRs showing a 111 contact for COVID-19, COVID-19 hospital admission, or death

For POCTs for past infection:
1. A positive composite reference standard to minimise the impact of a FN PHE reference test result for past infection at visit one / increase sensitivity will also include:
i. positive visit two IgG positive PHE antibody tests, or
ii. linked EHRs showing a confirmed past COVID-19 diagnosis (in another setting), such as positive PHE test for active COVID-19 infection, a 111 contact for COVID-19, hospital COVID-19 related admission, or
iii. a previous household COVID-19 contact identified via RCGP-RSC

2. A positive composite reference standard to minimise the impact of a FP PHE reference test result for past infection at visit one / increase specificity will also include:
i. Paired PHE serology: visit one (positive IgG) and visit two (positive IgG), or
ii. linked EHRs showing a 111 contact for COVID-19, COVID-19 hospital admission

Linkage to the CHESS, SGSS, and the Civil Registration of Deaths datasets will allow clinical information about SARS-CoV-2 to be captured from outside of the primary care setting prior to and following the date of RAPTOR point of care test evaluation. These data will allow the RAPTOR team to construct a composite reference standard to identify occasions where the laboratory SARS-CoV-2 test used as the primary reference standard is likely to have been a false negative or false positive. Civil Registration of Deaths is required as CHESS only captures COVID death in hospital and there is the need to identify any COVID mortality (in hospital and in the community) within 28 days of recruitment to use in the composite reference standard.

Organisations Involved

The University of Oxford are the sole data controller for this request.

Public Health England (PHE)

For the purposes of the RAPTOR trial PHE do not hold any data controllership responsibilities. However members of the statistical team are based at PHE working under the direction of the data controller and are therefore listed as data processors.

Royal Collage of General Practitioners (RCGP)

For the purpose of the RAPTOR trial RCGP are not a data controller. The RCGP are joint data controllers for the RCGP RSC collected data which is being linked to the cohort data. The RCGP play no role in determining the means by which or the purpose for which the data will be processed for the RAPTOR trial.

University of Surrey

The RCGP Research Surveillance Centre (RCGP RSC) was based at the University of Surrey, but is in the process of transferring to Oxford. Data being shared for the RAPTOR trial will be sent to Surrey so that the data they hold on the RCGP RSC for the consented cohort can be linked to the RAPTOR cohort. The RCGP RSC is a growing network of over 1200 GP surgeries based in England. University of Surrey are data processors

The University of Surrey acts as Data Processor on behalf of the Data Controller for the RAPTOR trial (Oxford). An existing secure network at the University of Oxford is progressively housing the RCGP RSC data. This data collection is known as (ORCHID secure). This process is underway and due to be completed by early 2021, at which stage all these data will all be held on the Oxford secure network. Further information relating to ORCHID can be found here: JPH - The Oxford Royal College of General Practitioners Clinical Informatics Digital Hub: Protocol to Develop Extended COVID-19 Surveillance and Trial Platforms | de Lusignan | JMIR Public Health and Surveillance

University of Surrey currently host the RCGP RSC Database for which the trial participants data will also be linked with. The RCGP RSC dataset includes individual patient level up-to-date primary and secondary care data which can be easily queried. Primary care/general practice data is rich in terms of diagnosis and information about the process of care. For example, the database contains the following variables for each patient (where present):

• Detailed demographic and risk factor data.
• COVID-19 appointments: including information on whether or not a virology swab was taken and the outcome of the swab
• Non-COVID-19 appointments.
• Detailed data for the 32 conditions monitored by RCGP RSC on behalf of PHE
• Vaccination status: date of vaccination, type of vaccination
• Co-morbid conditions
• Medication which may be associated with better or adverse outcomes.
• Test results
• Referrals made
• A & E visits
• Inpatient appointments, including critical care
• Outpatient appointments
• Mortality data (if applicable).

The RAPTOR-C19 study (IRAS ref 284320) was approved by the North West - Liverpool Central Research Ethics Committee (ref 20/NW/0282) on June 10th 2020. Participants give individual patient consent for RAPTOR-C19 to access their medical records data.

Note that current funding for the study is until June 2021, but the end date could be later than this depending on whether test continue to require evaluation and further funding is secured.

Expected Benefits:

For RAPTOR-C19 linked data allows the development of an enhanced reference standard to overcome imperfections in laboratory tests for COVID-19, thereby providing more accurate estimates of diagnostic accuracy. It also allows validation and enhancement of sociodemographic and comorbidity data for RAPTOR-C19 participants.

Outputs:

Specific outputs for this trial are:

• RAPTOR-C19 will publish the results of each POCT evaluation in open-access journals, the protocol on the study website (https://www.condor-platform.org/condor_workstreams/raptor) and registries, and summary reports which can be made publicly available through e.g. the websites of the study and of the NIHR Community Healthcare MIC (https://www.community.healthcare.mic.nihr.ac.uk/). RAPTOR-C19 will work with patient and public representatives to ensure that such reports are communicated in an appropriate manner for a lay audience. The Investigators will be involved in reviewing drafts of the manuscripts, abstracts, press releases and any other publications arising from the study. Authors will acknowledge that the study was funded by UKRI-MRC and any other funding that is secured. Authorship will be determined in accordance with the ICMJE guidelines and other contributors will be acknowledged. All outputs are expected to be submitted by the end of 2021.

Findings from this trial will contribute to the main outputs of the RCGP RSC.

The NIHR Community Healthcare MedTech and In vitro Diagnostics Co-operative and CONDOR have PPI groups feeding into the RAPTOR-C19 study. They have contributed to the development of the RAPTOR-C19 protocol, have commented on the relevance and acceptability of research questions and methods, they have assisted in the development of patient facing materials, and continue to advise on the public dissemination of results.

Processing:

Participants who have consented to the RAPTOR Trial will have their data initially linked with the primary care data which is already held as part of the Royal College of General Practitioners (RCGP RSC) Research and Surveillance Network database.

• The University of Surrey, on behalf of the University of Oxford for the RAPTOR trial, will provide NHS Digital with a list of NHS numbers and date of births along with a unique Study ID for the RAPTOR cohort. A specific University of Surrey IT team within the IT department will share the identifiers with NHS D not the research team.

• NHS Digital will send back to University of Surrey the linked cohort data.

• University of Surrey will store the data on the secure network researchers will then analyse a pseudonymised data to produce outputs for the RAPTOR Study.

The data is controlled and processed by a group of staff who are all based at the University of Surrey; all are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Language Query (SQL) developers, RCGP RSC practice liaison officers, a project manager and a head of department. The team work from secure workstations or secure laptops with encrypted drives within the group’s secure network. These same processes are replicated in Oxford.

The general practices in the RCGP RSC take virology swabs and serology samples to know if someone has a COVID-19 or a range of other infections, including influenza. These results are being passed back to the patients GP for their clinical care. However, a pseudonymised copy will go to the RCGP RSC. The COVID-19 status will be shared with the RAPTOR trial team (who also pseudonymise NHS number to allow this linkage).

All record level data will be held and stored within England and Wales.

ATEMPT: Antihypertensive Treatment in Elderly Multimorbid Patients (Pilot Study) — DARS-NIC-311182-F5W4X

Opt outs honoured: Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2021-04 – 2022-04 2021.06 — 2021.06.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Demographics

Type of data: Identifiable

Expected Benefits:

This data application will enable an eligible group of potential participants to be identified and recruited into the ATEMPT clinical trial (pilot).

It is hoped that the results from the ATEMPT trial will be relevant for the management of hypertension in older people with multimorbidity or polypharmacy, a patient group for whom currently the treatment effects of pharmacological blood pressure (BP) reduction remains uncertain. These patients have been underrepresented or excluded in previous research, thus, leaving an important gap in our understanding of treatment effects. One key reason for the existing gap in evidence is the challenge of recruiting sufficiently large numbers of older and multimorbid patients into clinical trials. This pilot study aims to address this challenge by recruiting approximately 200 participants aged 65 or over who have at least 3 long-term health conditions or are taking at least 5 medications in addition to any being taken to manage blood pressure.

The findings from this pilot study are intended to provide the feasibility required to inform the planning of a larger, multi-national, home-based study to assess the effect of treatment changes on patient-important outcomes. This trial could impact the treatment regime of millions of patients in the UK.

The study is designed to minimise the burden of participation to patients. There is no need for clinic attendance. Participation and follow-up will take place at home using a bespoke IT system with much of the data collected remotely.

The experience of using bespoke IT-enabled systems to remotely recruit and monitor participants will, if shown to be effective, be considered for use in the recruitment and study management of other research trials. This could provide the means for other researchers to not only streamline research processes but also include participants in trials who historically are reluctant or unable to participate in research trials due to the demands made of them to attend research visits. For instance, research suggests that the vast amount of research findings are based on studies that have included participants in close proximity to specialised centres, men, and those who have fewer comorbidities. This leaves a gap in research for the majority of the population in the UK to whom research findings are being applied. This study should not only encourage participation of such patients but will assess the extent to which conduct of trials can be made more efficient and hence affordable.

Outputs:

The research agenda, plan of investigation and monitoring of the execution of the ATEMPT trial is overseen by a trial steering committee. Members of a patient group, or individuals able to contribute to the wider public perspective are involved in the committee and review public-facing outputs.

The main trial results from the ATEMPT Pilot Study are expected in 2022 with a publication towards the end of that year.

The results will be disseminated widely, including presentation at relevant conferences such as the European Society of Cardiology annual meeting and publication in an open-access, high-impact medical journal such as the European Journal of Cardiology. Further academic papers (including a protocol paper and results of remote recruitment and management of the trial) will be published in open-access, high impact, peer-reviewed journals and on the trial website.

A non-technical summary of the main study findings will be provided to participants and other interested groups and published on the study website.

The data will be de-identified at the end of the study and only anonymised results will be used in publications.

The findings from this pilot study will be used to inform and plan an adequately powered major, multinational Randomised Controlled Trial. Additionally, the experience gained from utilising IT-enabled systems to remotely recruit and monitor participants will be evaluated with a view to expanding the use of the software to manage other research trials within the department and wider University. The online system for the ATEMPT trial has been developed in conjunction with members of the public aged 65 years or older in order to ensure that it is as simple and easy to use as possible.

Processing:

NHS digital will extract the details of patients that are aged 65 and older, residing in the Thames Valley (specific postcodes provided) with at least 3 co-morbidities diagnosed in the 5 years prior to the search, excluding those with a previous diagnosis of heart failure (ICD code I50). Patients who are deceased would be excluded. This information will be requested in up to 2 batches based on subsets of postcodes. If enrolment targets are met before the second batch of demographics data have been disseminated, the University of Oxford will inform NHS Digital as soon as possible, halting the production and dissemination of personal details which are no longer required.

NHS Digital will provide to the University of Oxford a file containing the following identifying data for potentially eligible participants within the specified postcodes for a given request: Name, address, gender, and date of birth. The University will then undertake further work to ascertain eligibility. The data will be stored in the ATEMPT pre-screening database.

The University will write to the potential participants inviting them to take part in the trial. In order to efficiently print and mail invitation letters, batches of personal data (name and address) will be sent securely to CFH Docmail Ltd who will process these data in order to print and post the invitation letters. The letters will be sent out gradually in smaller batches across one month, enabling the study team to stop sending letters as soon as there are enough participants enrolled on the study. Data is retained by CFH Docmail for one month after an invitation letter is mailed to a participant at which point the data is deleted. The University of Oxford may send one reminder to those who have not responded within that timescale.

The potential participants will be able to use a website address provided in the letter to find out more about the trial and a unique access code to log in and register their interest. The name and address of those consenting to take part will be copied to the ATEMPT study database at the point of e-consent and then participant name, address and other identifiable information will be collected directly from the participant.

At the end of enrolment the University of Oxford will delete data of all individuals not taking part in the trial. Participants who have provided their consent for taking part in the trial will have their identifiable information sent to NHS Digital under a new data sharing agreement to obtain Hospital Episode Statistics data for participants (safety data). Given identifiable information will be provided under consent for the subsequent agreement, all NHS Digital data provided using s251 approval for this original agreement will be deleted at the end of enrolment.

The ATEMPT pre-screening database and ATEMPT study database are not linked to any other databases. Data is stored securely by the University of Oxford in a high compliance system (HCS) suitable for storing personal and special category data, and data can only be accessed by study team members with a level of access based on their role. The HCS is accessed remotely on a university device and requires a unique username and password and two factor authentication. Data is not being matched to publicly available data. The data received from NHS Digital will only be accessed by individuals in the ATEMPT Study Team who have authorisation to access the data for the purposes described, all of whom are substantive employees of the University of Oxford and have been appropriately trained in data protection and confidentiality.

Where names and addresses are transferred to CFH Docmail to print and mail invitation letters, only CFH Docmail staff with appropriate authorisation and who need to access the data in order to fulfil their job role are allowed access to the data. These staff are all appropriately trained in data protection and confidentiality. They are required to sign a confidentiality agreement on an annual basis and are subject to refresher training and updates relating to data protection, GDPR and confidentiality on a regular basis, at least once a year. Data access at CFH Docmail is arranged by Security Group membership and Access Control Lists. Only restricted authorised production personnel can access compiled files. CFH Docmail have two employed data protection officers who would be responsible for the investigation and response to any data breach.

During the pandemic, where feasible, CFH staff are currently working from home and accessing their infrastructure via a secure VPN. The VPN is configured to provide users with the same access that they would have if they were on the cabled CFH Docmail internal network and is secured on an individual basis, with two factor authentication being required.

Comparing COVID-19 Vaccine Schedule Combinations – Stage 2 (Com-COV2) — DARS-NIC-448303-Z7H5R

Opt outs honoured: No - consent provided by participants of research study (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2021-03 – 2022-03 2021.04 — 2021.05.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Permission to Contact

Type of data: Identifiable

Objectives:

This Data Sharing Agreement authorises the use of information voluntarily provided to NHS Digital by individuals who have given permission to be contacted about potential participation in COVID-19 vaccine clinical trials. The data will be processed on behalf of the data controller, University of Oxford, by NHS Digital as a data processor for the purpose of supporting recruitment to participate in a COVID-19 vaccine trial being run by University of Oxford.

The following provides background to the Permission to Contact (PtC) Service:

NHS Digital has agreed to work in partnership with the National Institute of Health Research (NIHR) to build and host a first of type online Permission to Contact (PtC) Service on nhs.uk where members of the public can register their details and give their permission to be contacted by researchers working on NIHR approved UK coronavirus vaccine trials about participating in those trials. This PtC Service, which is called “Sign Up to be Contacted about Coronavirus Vaccine Studies” on the nhs.uk website was launched as a national service on 20th July 2020.

This Service enables participants to:
• Provide permission for NHS Digital to share an individual’s details provided through the Service with the researchers undertaking COVID-19 UK vaccine trials for the purposes of researchers contacting that individual about taking part in those trials.
• Provide their permission to be contacted by NHS Digital about progress and outcomes from CV19 vaccine studies and in relation to the development of the PtC Service, including to inform them of opportunities to participate in other types of health research.

The data collected from individuals who sign up includes sufficient information to achieve the following purposes:
• Matching potentially eligible participants to eligibility criteria provided by the vaccine trials for their specific studies. This data will comprise of age, sex, geographic locations, type of employment, and a number health question e.g. about whether they have long-term health conditions.
• Providing relevant details of potentially eligible participants which have been obtained through the Service to researchers. This will allow the researchers to contact the participants with a view to discussing their taking part in a trial and if so, to obtain their further permission to take part in the trial.
• NHS Digital will provide access to the information obtained from individuals through the Service via the existing Data Access Request Service (DARS) process available to researchers working on UK COVID-19 vaccine trials sponsored by the National Institute of Health Research. The Service will only provide researchers with the data collected directly from individuals themselves through the Service.

The contact details will be used to invite potentially eligible individuals to undertake an eligibility assessment and, if eligible, to give informed consent to participate in this trial. NHS Digital, as data processor acting on behalf of University of Oxford, will be sending the email to eligible participants.

This request relates specifically to a vaccine trial. A single-blind, randomised, phase II UK multi-centre study to determine reactogenicity and immunogenicity of heterologous prime/boost COVID-19 vaccine schedules – Stage 2.

A total of 1050 (+ up to additional 10%) participants will be enrolled, all of whom will have had their first dose of COVID-19 vaccine in the community as part of the NHS vaccine roll-out programme. Participants will be evenly divided by prime vaccine type (525 per prime vaccine group). Within these vaccine groups participants will be enrolled into either an Immunology cohort who will have more visits (n=150 in total, 75 from each vaccine prime group) or a General cohort (n=900 in total, 450 from each vaccine prime group).

The initial mailout will aim for around four / five times the number of potential participants to be recruited and therefore the estimate is for around 5,250 individuals to be contacted.

Although this application relates to the combining of commercial vaccines, there is no commercial element specifically attached to this application itself, the purpose of which is about influencing national vaccine rollout strategy. Although results may influences the manner in which the commercial firms role out vaccines in future, this application relates solely to an academic exercise.

Although AstraZeneca, Pfeizer, Moderna and Novavax have allowed the use of their vaccines for this trial, they have no responsibilities as to how the trial is conducted and therefore University of Oxford remain the sole Data Controller for this application.

Expected Benefits:

The primary benefit of using the data will be to recruit participants for the clinical study/trial in a manner which:
• Enables individuals to volunteer in advance to participate in COVID-19 vaccine trials as an alternative to other potentially more intrusive mechanisms, e.g. sharing data with researchers about individuals under section 251 consents or COPI notices, which although lawful is initially less transparent.
• Allows researchers to identify a suitable cohort and recruit them quickly into the vaccine trials – thus reducing the overall time to recruit into the trials and to accelerate the delivery of an effective vaccine to treat individuals to manage the COVID-19 outbreak and to save lives.
• Reduces burden on research staff in identifying and contacting potential clinical trial participants.
• Supports the Vaccines Taskforce objectives to drive forward, expedite and coordinate efforts to research and then produce a coronavirus vaccine and make sure one is made available to the public as quickly as possible.

Outputs:

The information from NHS Digital will be used to facilitate contact with individuals who are potentially eligible and who have indicated willingness to potentially participate in studies/trials of COVID-19 vaccines.

This is expected to result in individuals entering the trials screening process with a view to them participating in the trial with fully informed consent.

The main results from this trial are expected to inform development of a safe and effective multiple vaccine combination against COVID 19.

Processing:

NHS Digital will extract a list of patients meeting the following criteria, where that criteria can be ascertained using the PtC registry:

INCLUSION CRITERIA:

- Participant is willing and able to give written informed consent for participation in the trial
- Male or Female, aged 50 years or above and in good health as determined by a trial clinician
Participants may have well controlled or mild-moderate comorbidity
- Has received one dose of the prime/boost schedules being studied via the UK COVID-19 vaccination
programme at a timing to allow boost dose given in the trial to fall between D56-84 post-prime.
Evidence of this will be gathered from medical history and/or medical records.
- Female participants of childbearing potential must be willing to ensure that they or their partner use
effective contraception from enrolment continuously until 3 months after
boost immunisation. See Section 12.13.1 for definition of child bearing potential
- In the Investigator’s opinion, is able and willing to comply with all trial requirements
- Willing to allow their General Practitioner and consultant, if appropriate, to be notified of
participation in the trial
- Willing to allow investigators to discuss the volunteer’s medical history with their General
Practitioner and access all medical records when relevant to study procedures
- Agreement to refrain from blood donation during the course of the study

EXCLUSION CRITERIA:

Receipt of any vaccine (licensed or investigational) within 30 days before enrolment (one week for licensed seasonal influenza vaccine or pneumococcal vaccine)
- Previous receipt of two or more COVID-19 vaccine doses
- Prior or planned receipt of an investigational or licensed vaccine or product likely to impact on interpretation of the trial data (e.g. Adenovirus vectored vaccines other than ChAdOx1 nCoV-19)
- Administration of immunoglobulins and/or any blood products within the three months preceding the planned administration of the vaccines
- Any confirmed or suspected immunosuppressive or immunodeficient state; asplenia; recurrent severe infections and use of immunosuppressant medication within the past 6 months, except topical steroids or short-term oral steroids (course lasting ≤14 days)
- History of anaphylaxis, allergic disease or reactions likely to be exacerbated by any component of study vaccines (e.g. hypersensitivity to the active substance or any of the SmPC-listed ingredients of
the Pfizer vaccine), as specified in the UK Immunisation ‘Green Book’ COVID-19 vaccine chapter 14a
- Pregnancy, lactation or willingness/intention to become pregnant within 3 months post boost vaccine
- Malignancy requiring receipt of immunosuppressive chemotherapy or radiotherapy for treatment of solid organ cancer/haematological malignancy within the 6 months prior to enrolment. (Presence of
basal cell carcinoma of the skin, cervical carcinoma in situ, prostate cancer under observation and breast cancer on hormone therapy as secondary prophylaxis are not excluded).
- Bleeding disorder (e.g. factor deficiency, coagulopathy or platelet disorder), or prior history of significant bleeding or bruising following IM injections or venepuncture
- Continuous use of anticoagulants, such as coumarins and related anticoagulants (i.e. warfarin) or novel oral anticoagulants (i.e. apixaban, rivaroxaban, dabigatran and edoxaban)
- Suspected or known current alcohol or drug dependency
- Any other significant disease, disorder or finding which may significantly increase the risk to the volunteer because of participation in the study, affect the ability of the volunteer to participate in the study or impair interpretation of the study data
- Severe and/or uncontrolled cardiovascular disease, respiratory disease, gastrointestinal disease, liver disease, renal disease, rheumatological disease, endocrine disorder and neurological illness (mild/moderate well controlled comorbidities are allowed)
- History of active or previous auto-immune neurological disorders (e.g. multiple sclerosis, Guillain-Barre syndrome, transverse myelitis). Bell’s palsy will not be an exclusion criterion
- History of laboratory confirmed COVID-19 prior to enrolment (e.g. history of SARS-CoV-2 detection by PCR or antibody to SARS-CoV-2)
- Significant renal or hepatic impairment
- Scheduled elective surgery requiring overnight admission and/or general anaesthetic during the trial
- Participant with life expectancy of less than 6 months
- Participants who have participated in another research trial involving an investigational product in the past 12 weeks
- Insufficient level of English language to undertake all study requirements in opinion of the Investigators.

The inclusion and exclusion criteria noted above is based on the information provided by cohort members on the permission to contact dataset (where it can be obtained from this dataset), and is not collected from other NHS data sources. Some of the above inclusion and exclusion criteria will be used by the sites during the Screening phase.

NHS Digital will identify all individuals within the PtC dataset meeting the relevant criteria and will extract their names, email addresses and postcodes.

It is not known in advance how many individuals meeting the above criteria will have records in the PtC dataset. The number may be amended and the process may be repeated depending on the level of response. In the event of the trial not achieving a suitable balance in recruited participants, such as an uneven ratio of males to females, subsequent mail outs may restrict the required criteria to a greater degree than previously, for example, only requesting details for male participants as opposed to both males and females. This could encompass any part of the criteria, such as age, gender, ethnicity or location and various others, depending on how the recruitment progresses.

NHS Digital will write to the individuals in the subset inviting them to participate within the trial using ethically approved text provided by University of Oxford. The email will remind the individuals of the background of the permission to contact programme and give them the opportunity to state that they do not wish to be contacted again. The email will also direct volunteers to NIHR’s Be Part of Research website to access study information and regional contact information. Individuals will not be contacted multiple times under this Agreement and NHS Digital will record the fact that the individuals have been contacted to ensure compliance with the maximum number of contacts outlined as part of consent. Furthermore, in order to ensure that NHS Digital are able to update the register with which participants are registered with an active trial, and therefore prevent them from being invited to any further trials, NHS Digital will be provided with regular updates of those registered participants who have consented. This sharing of information is built into the Permission to Contact signing up information and will also be added to the trial consent and participant information.

Individual trial recruitment sites will supply NHS Digital with details of those who have signed up to take part in their trial so that NHS Digital can suitably capture this information within the Permission To Contact registry. All data that flows to NHS Digital in this context falls under the controllership of the data controller, regardless of whether they themselves are specifically involved in the processing of that data as it flows to NHS Digital. For this agreement there may be flows from each individual site. Once the data is received at NHS Digital then NHS Digital become controller for that data in their existing role as controller of the Permission To Contact Registry.

Due to the nature of trial recruitment sites, they often only become confirmed as sites very close to recruitment, and so NHS Digital will leave the responsibility with the lead site / data controller to appointment data processors themselves under their own due diligence. This practice aligns with their obligations under GDPR as a data controller and the emphasis will be on the lead site / data controller to appoint appropriate data processors on their behalf. Ordinarily NHS Digital would carry out these checks, but attempting to do so for this service would cause unnecessary delay to the initial application, as well as potentially multiple and costly amendments thereafter. Therefore all recruitment sites / data processors and their processing activities will be covered under a suitable processing agreement between themselves and the lead site / data controller which does not require NHS Digital’s inclusion. Specific details of recruitment sites, such as key contact, location, will therefore not be made known to NHS Digital unless there is a specific reason to do so.

No other processing of the data will take place and the data will not be linked with information from any other sources.

University of Oxford will not have access to any of the data being disseminated by NHS Digital under this agreement.

Comparing COVID-19 Vaccine Schedule Combinations (Com-COV) — DARS-NIC-428459-V7Q8M

Opt outs honoured: No - consent provided by participants of research study (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2021-01 – 2022-01 2021.01 — 2021.05.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Permission to Contact

Type of data: Identifiable

Objectives:

This Data Sharing Agreement authorises the use of information voluntarily provided to NHS Digital by individuals who have given permission to be contacted about potential participation in COVID-19 vaccine clinical trials. The data will be processed on behalf of the data controller, University of Oxford, by NHS Digital as a data processor for the purpose of supporting recruitment to participate in a COVID-19 vaccine trial being run by University of Oxford.

The following provides background to the Permission to Contact (PtC) Service:

NHS Digital has agreed to work in partnership with the National Institute of Health Research (NIHR) to build and host a first of type online Permission to Contact (PtC) Service on nhs.uk where members of the public can register their details and give their permission to be contacted by researchers working on NIHR approved UK coronavirus vaccine trials about participating in those trials. This PtC Service, which is called “Sign Up to be Contacted about Coronavirus Vaccine Studies” on the nhs.uk website was launched as a national service on 20th July 2020.

This Service enables participants to:
• Provide permission for NHS Digital to share an individual’s details provided through the Service with the researchers undertaking COVID-19 UK vaccine trials for the purposes of researchers contacting that individual about taking part in those trials.
• Provide their permission to be contacted by NHS Digital about progress and outcomes from CV19 vaccine studies and in relation to the development of the PtC Service, including to inform them of opportunities to participate in other types of health research.

The data collected from individuals who sign up includes sufficient information to achieve the following purposes:
• Matching potentially eligible participants to eligibility criteria provided by the vaccine trials for their specific studies. This data will comprise of age, sex, geographic locations, type of employment, and a number health question e.g. about whether they have long-term health conditions.
• Providing relevant details of potentially eligible participants which have been obtained through the Service to researchers. This will allow the researchers to contact the participants with a view to discussing their taking part in a trial and if so, to obtain their further permission to take part in the trial.
• NHS Digital will provide access to the information obtained from individuals through the Service via the existing Data Access Request Service (DARS) process available to researchers working on UK COVID-19 vaccine trials sponsored by the National Institute of Health Research. The Service will only provide researchers with the data collected directly from individuals themselves through the Service.

The contact details will be used to invite potentially eligible individuals to undertake an eligibility assessment and, if eligible, to give informed consent to participate in this trial. NHS Digital, as data processor acting on behalf of University of Oxford, will be sending the email to eligible participants.

This request relates specifically to a vaccine trial. This is a Single-blind, randomised prime-boost vaccine administration study comparing COVID19 vaccine schedule combinations.

On the 2nd December 2020 the MHRA granted emergency authorisation for a vaccine against COVID-19, ‘COVID-19 mRNA Vaccine BNT162b2’. This was the first in what are expected to be multiple vaccines approved for use against COVID-19. . Most of these are expected to be approved as a two-dose regimen, using the same vaccine for both the initial (prime) and subsequent (boost) dose. There are likely to be significant logistical challenges immunising large portions of the population. There would be significant advantages to having flexible immunisation programmes whereby the second vaccine dose is not necessarily the same as the first dose. Accordingly, this study will determine the safety as well as the immune responses to a variety of combinations of prime/boost schedules for candidate COVID-19 vaccines that are potentially to be deployed in the UK. The vaccines to be studied in this protocol will primarily be determined by those made available to the Department of Health and Social Care (DHSC) for population use, but for the purposes of this articular application, the aim is to recruit participants to test combinations of ChAdOx1 nCOV-19 (developed by University of Oxford / AstraZeneca) and BNT162b2 (developed by Pfeizer).

The primary objective is to determine whether the immune response in COVID seronegative participants to immunisation with heterologous prime/boost COVID-19 vaccines regimens (boosted at D28) is non-inferior to that observed following immunisation with approved homologous prime-boost regimens (boosted at D28).

The secondary objectives are to determine whether the immune response in COVID seronegative participants to immunisation with heterologous prime/boost COVID-19 vaccines regimens across all dosing intervals is non-inferior to that observed following immunisation with approved homologous prime-boost regimens, and the reactogenicity and safety of heterologous & homologous prime/boost schedules of COVID-19 vaccines.

The aim for this application is to recruit a total of total of 820 participants, consisting of an Immunology cohort receiving their booster vaccine dose after 28 days (n=100) and a General cohort (n=720). Half of the general cohort participants (N-360) will receive their booster vaccine after 28 days, and half will receive their booster vaccine after 84 days.

Within the immunology cohort participants will be randomised 1:1:1:1 to the following arms receiving their booster vaccine dose after 28 days:
• Prime ChAdOx1 nCOV-19, Boost ChAdOx1 nCOV-19
• Prime ChAdOx1 nCOV-19, Boost BNT162b2
• Prime BNT162b2, Boost BNT162b2
• Prime BNT162b2, Boost ChAdOx1 nCOV-
Within the general cohort participants will be randomised 1:1:1:1:1:1:1:1 to the following arms:
• Prime ChAdOx1 nCOV-19, Boost ChAdOx1 nCOV-19 28 day boost
• Prime ChAdOx1 nCOV-19, Boost BNT162b2 28 day boost
• Prime BNT162b2, Boost BNT162b2 28 day boost
• Prime BNT162b2, Boost ChAdOx1 nCOV-19 28 day boost
• Prime ChAdOx1 nCOV-19, Boost ChAdOx1 nCOV-19 84 day boost
• Prime ChAdOx1 nCOV-19, Boost BNT162b2 84 day boost
• Prime BNT162b2, Boost BNT162b2 84 day boost
• Prime BNT162b2, Boost ChAdOx1 nCOV-19 84 day boost

There will therefore be a sum total of 205 participants receiving each different permutation of vaccine, 25 of whom will be in the Immunology cohort with booster vaccine dose after 28 days, 90 in the General Cohort with booster vaccine dose after 28 days and 90 in the General Cohort with booster vaccine dose after 84 days.

The initial mailout will aim for around four / five times the number of potential participants to be recruited and therefore the estimate is for around 4,100 individuals to be contacted.

Although this application relates to the combining of two commercial vaccines, there is no commercial element specifically attached to this application itself, the purpose of which is about influencing national vaccine rollout strategy. Although results may influences the manner in which the commercial firms role out vaccines in future, this application relates solely to an academic exercise.

Although AstraZeneca and Pfeizer have allowed the use of their vaccines for this trial, they have no responsibilities as to how the trial is conducted and therefore University of Oxford remain the sole Data Controller for this application.

Expected Benefits:

The primary benefit of using the data will be to recruit participants for the clinical study/trial in a manner which:
• Enables individuals to volunteer in advance to participate in COVID-19 vaccine trials as an alternative to other potentially more intrusive mechanisms, e.g. sharing data with researchers about individuals under section 251 consents or COPI notices, which although lawful is initially less transparent.
• Allows researchers to identify a suitable cohort and recruit them quickly into the vaccine trials – thus reducing the overall time to recruit into the trials and to accelerate the delivery of an effective vaccine to treat individuals to manage the COVID-19 outbreak and to save lives.
• Reduces burden on research staff in identifying and contacting potential clinical trial participants.
• Supports the Vaccines Taskforce objectives to drive forward, expedite and coordinate efforts to research and then produce a coronavirus vaccine and make sure one is made available to the public as quickly as possible.

Outputs:

The information from NHS Digital will be used to facilitate contact with individuals who are potentially eligible and who have indicated willingness to potentially participate in studies/trials of COVID-19 vaccines.

This is expected to result in individuals entering the trials screening process with a view to them participating in the trial with fully informed consent.

The main results from this trial are expected to inform development of a safe and effective multiple vaccine combination against COVID 19.

Processing:

NHS Digital will extract a list of patients meeting the following criteria, where that criteria can be ascertained using the PtC registry:

INCLUSION CRITERIA:

1. Participant is willing and able to give written informed consent for participation in the trial.

2. Male or Female, aged 50 years or above and in good health as determined by a trial clinician Participants may have well
controlled or mild-moderate comorbidity.

3. Female participants of childbearing potential must be willing to ensure that they or their partner use effective contraception from 1 month prior to first immunisation continuously until 3 months after boost immunisation.

4. In the Investigator’s opinion, is able and willing to comply with all trial requirements.

5. Willing to allow their General Practitioner and consultant, if appropriate, to be notified of participation in the trial.

6. Willing to allow investigators to discuss the volunteer’s medical history with their General Practitioner and access all medical records when relevant to study procedures.

7. Agreement to refrain from blood donation during the course of the study

EXCLUSION CRITERIA:

The participant may not enter the trial if ANY of the following apply:

1. Receipt of any vaccine (licensed or investigational) other than the study intervention within 30 days before and after each study vaccination (one week for licensed seasonal influenza vaccine or pneumococcal vaccine).

2. Prior or planned receipt of an investigational or licensed vaccine or product likely to impact on interpretation of the trial data (e.g. Adenovirus vectored vaccines, any coronavirus vaccines).

3. Administration of immunoglobulins and/or any blood products within the three months preceding the planned administration of the vaccines.

4. Any confirmed or suspected immunosuppressive or immunodeficient state; asplenia; recurrent severe infections and use of immunosuppressant medication within the past 6 months, except topical steroids or short-term oral steroids (course lasting ≤14 days).

5. History of allergic disease or reactions likely to be exacerbated by any component of the study vaccines.

6. Any history of angioedema.

7. Any history of anaphylaxis or if they have been advised to carry an adrenaline auto-injector.

8. Pregnancy, lactation or willingness/intention to become pregnant within 3 months post boost vaccine.

9. Current diagnosis of or treatment for cancer (except basal cell carcinoma of the skin and cervical carcinoma in situ).

10. History of serious psychiatric condition likely to affect participation in the study.

11. Bleeding disorder (e.g. factor deficiency, coagulopathy or platelet disorder), or prior history of significant bleeding or bruising following IM injections or venepuncture.

12. Continuous use of anticoagulants, such as coumarins and related anticoagulants (i.e. warfarin) or novel oral anticoagulants (i.e. apixaban, rivaroxaban, dabigatran and edoxaban).

13. Suspected or known current alcohol or drug dependency.

14. Any other significant disease, disorder or finding which may significantly increase the risk to the volunteer because of
participation in the study, affect the ability of the volunteer to participate in the study or impair interpretation of the study data.

15. Severe and/or uncontrolled cardiovascular disease, respiratory disease, gastrointestinal disease, liver disease, renal disease, endocrine disorder and neurological illness (mild/moderate well .controlled comorbidities are allowed).

16. History of active or previous auto-immune neurological disorders (e.g. multiple sclerosis, GuillainBarre syndrome, transverse myelitis). Bell’s palsy will not be an exclusion criterion

17. History of laboratory confirmed COVID-19 prior to enrolment (history of SARS-CoV-2 detection by PCR or antibody to
SARS-CoV-2).

18. Significant renal or hepatic impairment.

19. Scheduled elective surgery during the trial.

20. Participant with life expectancy of less than 6 months.

21. Participants who have participated in another research trial involving an investigational product in the past 12 weeks.

22. Insufficient level of English language to undertake all study requirements in opinion of the Investigators.

The inclusion and exclusion criteria noted above is based on the information provided by cohort members on the permission to contact dataset (where it can be obtained from this dataset), and is not collected from other NHS data sources. Some of the above inclusion and exclusion criteria will be used by the sites during the Screening phase.

NHS Digital will identify all individuals within the PtC dataset meeting the relevant criteria and will extract their names, email addresses and postcodes.

It is not known in advance how many individuals meeting the above criteria will have records in the PtC dataset. The number may be amended and the process may be repeated depending on the level of response. In the event of the trial not achieving a suitable balance in recruited participants, such as an uneven ratio of males to females, subsequent mail outs may restrict the required criteria to a greater degree than previously, for example, only requesting details for male participants as opposed to both males and females. This could encompass any part of the criteria, such as age, gender, ethnicity or location and various others, depending on how the recruitment progresses.

NHS Digital will write to the individuals in the subset inviting them to participate within the trial using ethically approved text provided by University of Oxford. The email will remind the individuals of the background of the permission to contact programme and give them the opportunity to state that they do not wish to be contacted again. The email will also direct volunteers to NIHR’s Be Part of Research website to access study information and regional contact information. Individuals will not be contacted multiple times under this Agreement and NHS Digital will record the fact that the individuals have been contacted to ensure compliance with the maximum number of contacts outlined as part of consent. Furthermore, in order to ensure that NHS Digital are able to update the register with which participants are registered with an active trial, and therefore prevent them from being invited to any further trials, NHS Digital will be provided with regular updates of those registered participants who have consented. This sharing of information is built into the Permission to Contact signing up information and will also be added to the trial consent and participant information (see supporting document SD3 for further details).

Individual trial recruitment sites will supply NHS Digital with details of those who have signed up to take part in their trial so that NHS Digital can suitably capture this information within the Permission To Contact registry. All data that flows to NHS Digital in this context falls under the controllership of the data controller, regardless of whether they themselves are specifically involved in the processing of that data as it flows to NHS Digital. For this agreement there may be flows from each individual site. Once the data is received at NHS Digital then NHS Digital become controller for that data in their existing role as controller of the Permission To Contact Registry.

Due to the nature of trial recruitment sites, they often only become confirmed as sites very close to recruitment, and so NHS Digital will leave the responsibility with the lead site / data controller to appointment data processors themselves under their own due diligence. This practice aligns with their obligations under GDPR as a data controller and the emphasis will be on the lead site / data controller to appoint appropriate data processors on their behalf. Ordinarily NHS Digital would carry out these checks, but attempting to do so for this service would cause unnecessary delay to the initial application, as well as potentially multiple and costly amendments thereafter. Therefore all recruitment sites / data processors and their processing activities will be covered under a suitable processing agreement between themselves and the lead site / data controller which does not require NHS Digital’s inclusion. Specific details of recruitment sites, such as key contact, location, will therefore not be made known to NHS Digital unless there is a specific reason to do so.

No other processing of the data will take place and the data will not be linked with information from any other sources.

University of Oxford will not have access to any of the data being disseminated by NHS Digital under this agreement.

D27 - QResearch COVID-19 linkage — DARS-NIC-375354-G8V1H

Opt outs honoured: No - data flow is not identifiable, No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: Yes (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2020-04 – 2020-09 2020.06 — 2021.03.

Access method: Ongoing

Data-controller type: INTENSIVE CARE NATIONAL AUDIT & RESEARCH CENTRE (ICNARC), UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Outpatients
  2. Hospital Episode Statistics Critical Care
  3. Hospital Episode Statistics Admitted Patient Care
  4. Civil Registration - Deaths
  5. Civil Registration (Deaths) - Secondary Care Cut
  6. Hospital Episode Statistics Accident and Emergency
  7. Civil Registrations of Death - Secondary Care Cut
  8. Hospital Episode Statistics Accident and Emergency (HES A and E)
  9. Hospital Episode Statistics Admitted Patient Care (HES APC)
  10. Hospital Episode Statistics Critical Care (HES Critical Care)
  11. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

This agreement specifically relates to QResearch COVID-19 research projects undertaken in relation to the 2020 pandemic. Under this agreement QResearch data linked to NHS Digital data will be used solely for the purpose of research into COVID-19. Other QResearch uses of NHS Digital data are covered by a separate data sharing agreement (DARS-NIC-240279-Y2V2N).

QResearch is a database of linked medical records that has been used and continues to be used by a variety of research projects undertaken by UK universities, from reviewing the safety of antidepressant medicines to studying factors to predict variations in survival rates for cancer patients.

Monthly HES and mortality data are requested to link to the existing QResearch database so that it can be used for medical research. The QResearch database consists of the coded pseudonymised electronic health records from primary care patients registered with approximately 1,500 general practices spread throughout the UK.

QResearch was originally a not for profit collaboration originally between the University of Nottingham and Egton Medical Information Systems (EMIS) but the University of Nottingham’s roles and responsibilities have since been transferred to the University of Oxford. Strategic decisions about the GP data are taken by a Management Board representing the interests of EMIS and the University of Oxford. The University of Oxford is the sole data controller for the datasets which are linked to QResearch (deaths, cancer and hospital data) and the single point of access to the data, with ICNARC as joint data controller for COVID-19 projects using linked ICNARC data.

In addition to coded data from the GP electronic record, the QResearch database also contains the linked cause of death derived from the death certificate data which was originally supplied directly by the Office of National Statistics (ONS) but NHS Digital has since assumed ownership for this data, and cancer registration data supplied directly by Public Health England, following approval by Trent MREC and Secretary of State for Health. From October 2018, new mortality data (referred to as Civil Registration data) will be supplied by NHS Digital. Any mortality originally supplied by ONS data will be considered data supplied by NHS Digital and only NHS Digital can approve ongoing access to this data and its use for specific purposes.

The data linkages for QResearch were extended in 2011 to include additional health information from secondary care including HES. This agreement grants additional permission to link NHS Digital data to an existing database of data from 185 intensive care units nationally which has the clinical data for all those admitted with severe disease requiring ventilation. This is known as the Intensive Care National Audit and Research Centre (ICNARC) database and the COVID-19 testing database held by PHE. ICNARC will be a joint data controller (along with the University of Oxford) solely for COVID-19 projects involving the use of this linked data, and not for any other purposes.

The patient level data linked to QResearch is only accessed by academics employed by University of Oxford, as well as authorised individuals employed by the University of Nottingham. In all cases, data can only be accessed on site at the University of Oxford. However, the researchers involved in a given project (contributing to the research question, design, interpretation and writing of the paper for publication but not handling the data) may be employed by other UK universities. The HES and mortality data stay on site at the University of Oxford and are only handled by University of Oxford staff, ICNARC where they are a joint data controller, the data processor contracted to the University of Oxford (Dancing House Consulting) and authorised researchers employed by the University of Nottingham. The University of Oxford may have a collaborator at another university on the project team advising on clinical aspects or interpretation of findings, but they will not receive any data. In addition, the external researcher may initiate a COVID-19 project but the University of Oxford has sole autonomy for determining the purposes for which the HES and/or civil registration data will be processed and analysis will be done by University of Oxford staff with the data located at the University of Oxford. The sole exception to this is for COVID-19 projects using linked ICNARC data, for which ICNARC will be a joint data controller. For these COVID-19 projects ICNARC statisticians will have a role in the design, analysis and interpretation of the data under the overall direction of University of Oxford, and they will be co-authors on arising papers. ICNARC will not be involved in any decisions regarding other research projects which do not use their ITU data. Data will not be used for any solely commercial purposes and all applications for the use of HES and/or mortality linked data are subject to a governance process explained in the Processing Activities section.

Only University of Oxford staff, their data processor, Dancing House Consulting, ICNARC, and authorised researchers employed by the University of Nottingham will have access to HES and/or mortality record level data. External researchers will only have access to tabular outputs that are aggregate with small numbers suppressed in line with the HES Analysis Guide. Record level data are not shared with researchers outside of the University of Oxford.

Research undertaken using the extended database continues to be processed using the existing arrangements with respect to scientific review and annual reports to Trent MREC. Research has to be peer reviewed, original, hypothesis driven or hypothesis testing, intended for publication in an academic peer reviewed journal.

All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.

Expected Benefits:

This data linkage with ICNARC seeks to match against data on prior long-term medication and chronic disease, information contained in the QResearch databases derived from the de-identified general practice health records. The aim is to provide useful knowledge that patients, GPs and intensive care doctors can use to reduce the risk of severe COVID-19 infection within this pandemic.

Specifically it will help research to understand whether drugs commonly taken for chronic conditions such as hypertension or diabetes may exacerbate or reduce the severity of COVID-19 disease. It is hoped this study will be able to identify alternative drugs for patients with chronic conditions, as well as possible drugs to treat COVID-19; and recognise high-risk patients in primary care.

Around 14 percent of the adult population in England take anti-hypertensive medications, and around five percent receive medication to treat diabetes. The prevalence increases with age, making usage particularly common in those at risk of for severe COVID-19 infections. In many cases drugs from a different class could be used instead. If these drugs are increasing the risk of severe infection, they represent one of the few modifiable risk factors for severe COVID-19 infection. Medical and research communities need rapid large-scale accumulation of data on the outcomes of patients who develop COVID-19 infection whilst taking these drugs to allow appropriate risk assessment and clinical decision making for these patient groups. Other drugs in common use in primary care patients are believed to have anti-viral activity to COVID-19, such as hydroxychloroquine, used in rheumatoid arthritis, and lopinavir-ritonavir, used in the treatment of HIV.

There are also immune-suppressive therapies that may either increase the risk of severe illness by preventing the body’s response to infection, or attenuate the hyperinflammation syndrome associated with COVID-19 disease, so preventing severe disease.

The incidence of severe disease in patient groups taking these medications urgently needs to be established to guide both their management and investigation of COVID-19 treatment strategies.

ICNARC is already providing up-to-date information on the admission characteristics and outcomes of all patients with severe COVID-19 infection treated on an ICU in England, Wales and Northern Ireland.

Outputs:

The outputs are research papers which are published in peer reviewer academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by with press releases from the relevant organisations and highlighted on social media.

Results are also shared with policy makers and NICE guideline committees on a regular basis via their stakeholder consultations in order to support development of relevant guidelines.

Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.

The results tables within the papers will only contain statistical information with cell counts of > 5, being suppressed in line with the ICO code on anonymisation. Outputs will only contain aggregate level data with small numbers suppressed in line with the HES analysis guide.

No indicators are produced which show performance of an organisation – indeed the identity of the GP practices contributing to QResearch are not shared with any third party.

Processing:

Under this agreement, primary care data from The Phoenix Partnership (TPP) from general practices which use the SytmOne computer system will be included in QResearch linkage in addition to data from EMIS practices. This will give a larger population of patients and enable more coverage of patients who subsequently go into hospital and onto Intensive Treatment Unit (ITU) with and without COVID-19.

EMIS and TPP process the GP data from the original data controllers (GP practices) and sends it to the University of Oxford. EMIS and TPP are not able to access or process any GP data once it is located at the University of Oxford.

EMIS and TPP are neither a data processor nor a data controller for the data provided by NHS Digital under this Agreement. EMIS and TPP are not able to access the HES data under any circumstances. EMIS and TPP have given permission for the GP data it supplies to be linked with the data from NHS Digital for purposes determined by the Principal Investigator at the University of Oxford.

Before providing data to the University of Oxford, NHS Digital use the Open Pseudonymiser tool to pseudonymise the HES data. NHS Digital retains the salt key for this pseudonymisation, meaning that the University of Oxford are unable to re-identify the data but as described below they are able to link with GP data that was pseudonymised using the same Open Pseudonymiser tool. The University of Oxford will not be provided with a copy of the pseudonymisation salt.

NHS Digital provide the pseudonymised data to the University of Oxford which is then linked to the QResearch database at individual patient level using a pseudonymised version of the NHS number which has been supplied in both GP data and the HES data. The data linkage is undertaken by an employee of the University of Oxford. No data items which would identify the data subjects are received by QResearch as the data is pseudonymised-at-source and at NHS Digital. Date of birth is rounded to year of birth before receipt by the University of Oxford.

The resulting data are then used for undertaking primary research relating to COVID-19. The linked data are only accessed by approved research staff with substantive contracts employed by University of Oxford, the contracted data processor (Dancing House Consulting), ICNARC (for COVID-19 projects using linked ICNARC data) and authorised researchers employed by the University of Nottingham. Data is only processed on site on secure servers at the University of Oxford. No individual level data will be shared or stored outside the University of Oxford or supplied to any third party.

Applications for HES and/or civil registration data linked to QResearch GP data are restricted to academics employed by University of Oxford to undertake research. At least one member of the research team must be a medically qualified academic registered with the General Medical Council who signs the guarantee. Eligibility of applications is assessed according to the following criteria.
• You agree NOT to attempt to identify patient(s) or practice(s)?
• You undertake to provide a copy of the final report of the project and copies of any publications within one year of the project completion?
• You agree NOT to release the data to any third party including the funder, sponsor or other such body?
• You agree not to use the data for any other project except that which is expressly described in your protocol
• Do you have a statistician on the project team who has contributed to the design of the study and will advise on the analysis?
• Is the research a benefit to the UK Health and Social care system
All applications are reviewed by the QResearch Scientific Committee, which is overseen by the QResearch Advisory Board (which includes patients and general practice representatives). If an application does not meet the above criteria it would mean that application would be rejected and the data would not be shared. Details of the Scientific Committee and Advisory Board terms of reference and membership are published on the QResearch website, along with Advisory Board minutes.

Researchers originate a research question or hypothesis; write an outline protocol; and contact QResearch to discuss the feasibility of undertaking the study. If the study is feasible, QResearch will give a broad estimate of the costs of providing the analysis and will provide a letter to accompany any application for funding. The researcher then secures the necessary funding and completes the QResearch application form, including a detailed protocol and data specification. This application is sent for scientific review and feedback is given to the researcher. The researcher makes any necessary modifications to the protocol and approval is obtained, the researcher is given a timescale for the analysis. Once the researcher has the analysis, they have to approve it within one month of receipt.

As described in the section above, the QResearch database is also linked to mortality and cancer registration data. The database was first linked to ONS mortality data in 2007 and cancer data in 2011 (subsequently supplied by Public Health England since 2015). The data fields received from mortality data are: pseudonymised NHS number; year of birth, date of death; ICD10 cause of death. The cancer data includes pseudonymised NHS number; sex; year of birth; date of death; diagnosis date; cancer site and type; cancer stage and grade; cancer behaviour; cancer diagnosed only on death certificate; cancer treatment (surgery, hormone, chemotherapy, other).

To enable COVID-19 research, data will also be linked to the ICNARC database and the COVID-19 testing database held by PHE. No other data linkage is permitted without further amendment to the data sharing agreement with NHS Digital. There is no requirement to re-identify individuals from the data and no attempts will ever be made to do this.

The data processor Dancing House Consulting undertakes IT consultancy on behalf of the data controller, including administration of data backups, database administration, and secure destruction of data. Dancing House Consulting do not undertake data linkage or analysis of the data.

All outputs are restricted to aggregate data with small numbers supressed in line with the HES Analysis Guide.

Regular reviews against the ICO code on anonymisation (2012) will be undertaken to ensure that the data remain anonymised and all appropriate controls are in place to minimise any risk of re-identification.

The data from NHS Digital will not be used for any other purpose other than that outlined in this Agreement, and the specific QResearch projects outlined within the data sharing agreement DARS-NIC-240279-Y2V2N while that agreement remains active.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

MR1164 - The Asymptomatic Carotid Surgery Trial (ACST-2) — DARS-NIC-10123-M5K5H

Opt outs honoured: No - consent provided by participants of research study, No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-04 – 2022-01 2019.06 — 2021.03.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Demographics
  5. Civil Registration - Deaths
  6. MRIS - Members and Postings Report
  7. Civil Registrations of Death

Type of data: Identifiable

Objectives:

The University of Oxford requires identifiable data for the Asymptomatic Carotid Surgery Trial (ACST-2); a large international multi-centre randomized clinical trial comparing carotid endarterectomy (CEA) and carotid artery stenting (CAS) for stroke prevention. ACST-2 is designed to reliably compare the long-term stroke risk of all patients randomized to CEA with those randomised to CAS. To do this, all patients are followed-up 1 month after the procedure by an independent neurologist (to record any procedural complications) and thereafter, follow-up is achieved via annual questionnaires, supplemented with cause-specific civil registry mortality data. The UK is the only country to benefit from mortality data sourced from NHS Digital but all other countries in the trial use the same patient information and questionnaires. The University of Oxford is the coordinating centre and collate all of the data for this international study.

The proposed data processing is in line with Article 6(1)(e) ‘processing is necessary for the performance of a task carried out in the public interest’. Identifiable record level data from central registries provide reports of fatal stroke and also inter-current mortality to allow appropriate censoring of the trial population. This data is the smallest amount that is necessary to answer the research question.

ACST-2 will complete recruitment in 2019-2020 with a major report (describing initial hazards of surgery and 4-year follow-up) envisaged in 2021. Follow-up (exclusively questionnaire and registry-based) will continue until 2025 (thereby ensuring a minimum follow-up of 5 years), with a final report in 2025-2026 (median follow-up of ~10 years). The data are reviewed annually by the independent Data Monitoring Committee (iDMC), comprising expert members who are independent of the trial. Their role is to ensure trial participants are not exposed to excess hazards due to their participation in ACST-2 by reviewing unblinded aggregate trial data. Unblinded aggregate data is pooled data that is broken down by treatment allocation only, prepared as a report and given to the iDMC. The iDMC does not have access to patient level data. Public interest is in line with Article 9(2)(j) ‘processing is necessary for scientific or historical research purposes’.

The trial was started in 2008 at St George’s Hospital, London before moving to the University of Oxford in 2011. The University of Oxford is now the sole data controller. St George’s University of London has no ongoing involvement with the project and is not accessing any data. The trial was supported by the NIHR HTA and the BUPA Foundation and more recently secure long-term funding has been provided by The Nuffield Department of Population Health. It will be the largest trial of a carotid procedure ever completed. Currently 3134 participants have been recruited across 33 countries with the aim of recruiting 3600 by the end of 2019 / early 2020.

England is currently the second largest recruiting country, with 426 patients randomised from 23 hospitals to date. The results of the first ACST trial (which compared CEA with medical therapy) changed clinical practice worldwide and the University of Oxford expects the results of ACST-2 to be similarly impactful in the UK and beyond.

The MRIS Cohort Event Notification and Cause of Death data that is provided by NHS Digital is critical in informing the study’s endpoints from both a safety and efficacy viewpoint as well as the primary short term and long-term objectives.

The information requested from NHS Digital is to help the trial achieve its primary goals, namely the comparison of the peri-procedural risks (myocardial infarction [MI], stroke and death within 30 days of procedure and the longer term objective of preventing stroke, especially disabling of fatal strokes over the period of follow up (with major reports at 4 and 10 years median follow-up). NHS Digital data is also used to help avoid contacting the relatives of recently deceased patients, which would be intrusive and cause significant additional distress.

The study will compare:
1) Peri-procedural risks (myocardial infarction [MI], stroke and death;
2) Long-term (>5 years) prevention of stroke, particularly disabling or fatal stroke.
3) Procedural and stroke-related healthcare costs and;
4) Evaluate quality of life.

The University of Oxford will be the sole data processor. The only organisation that will have access to the data that is supplied by NHS Digital will be the designated personnel at the Clinical Trials Service Unit and the ACST-2 data team within the University of Oxford.

The information provided by participants at the point of consent and randomisation as well as each year when they return their annual questionnaires will be used to describe the risks and benefits of not only the surgical procedures but the co-morbidities and the long term use of medications to prevent future strokes.

Yielded Benefits:

The trial is ongoing.

Expected Benefits:

The ACST-2 study is a stroke prevention study enrolling asymptomatic patients across over 20 countries in Europe (including the UK), North and South America and Asia, to compare the early safety and long-term efficacy of CEA v CAS. There are approximately 200,000 procedures in Europe and US per annum, half of which are CEA, half CAS.

ACST-2 will be the largest-ever trial of a vascular surgical procedure and its results will be impactful. If it shows that CEA is superior to CAS, large numbers of patients (who currently undergo CAS) may switch to CEA. Alternatively, if the long-term results of both procedures are comparable, patients and doctors have a choice, and many patients may prefer a less invasive stent over surgery. If CEA is better than CAS, 100,000 patients will directly benefit by avoiding an inferior procedure. If CEA is equal in outcome to CAS then it becomes a patient/doctor choice and many patients may chose minimally invasive option of CAS. Either way, results may be impactful worldwide and will likely change practice.

The impact of ACST-2 will be tracked via national registries of vascular procedures. Practice changed worldwide following ACST-1 within 1-2 years, and University of Oxford expect ACST-2 to be similarly impactful once the 10-year follow up is reported in 2025-26.

Outputs:

Interim unblinded results are provided to the independent Data Monitoring Committee (DMC) annually. These reports are prepared by the trial statistician and data manager. There are no patient identifiable information contained in the report, which is circulated by email. This committee can advise the Trial Steering Committee (TSC) if there is proof ‘beyond reasonable doubt’ that one procedure is better than the other. In such circumstances, the TSC may choose to end the trial prematurely.

Two major reports are planned: It is expected that ACST-2 will complete recruitment in 2019-2020 with a major report (describing initial hazards of surgery and 4-year follow-up) envisaged in 2021. Follow-up (exclusively questionnaire and registry-based) will continue until 2025 (thereby ensuring a minimum follow-up of 5 years), with a final report in 2025-2026 (median follow-up of ~10 years).

Until then, the Principal Investigators will give trial updates at meetings of various learned societies aimed at raising the trial profile and encouraging recruitment. No patient identifiable data will be shared in such talks.

The ACST-2 have been involved in disseminating information to the general public through various means including engaging with Social Media, the UK Stroke Forum and the Oxford Biomedical Research Centre. The ACST-2 Trial Steering Committee includes lay members who have been present at the meetings throughout the course of the trial. The University of Oxford will continue to use these platforms not only to share information about the trial, but the disease process and Stroke.

All published outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

It is necessary for the University of Oxford to use NHS Digital to follow-up patients and receive information relating to mortality so that the study has access to the correct survival status and cause of death of trial participants. The data supplied by NHS Digital will be used with other sources of event information to assess the long-term safety and efficacy of CEA and CAS.

a) The Clinical Trials Service Unit (CTSU) securely transfers a file of identifying information including NHS Number, Date of Birth and Postcode plus Unique Study ID to NHS Digital.
b) NHS Digital will flag the participants and link the data to Civil Registry mortality data.
c) NHS Digital will return identifiable linked data in MRIS Cohort Event Notification reports and Cause of Death reports. The data will include the Unique Study ID, date of birth, gender, name, NHS number, date and cause of death of those participants who have died.
d) CTSU stores the data on a server based at CTSU, which can be only accessed by CTSU staff at the University of Oxford.
e) CTSU will extract a subset of the data containing/comprised of those patients who have died and make this available to the ACST-2 Trial Manager within the same organisation via encrypted email.

Data will only be accessed by individuals within CTSU and ACST-2 who have authorisation from the data controller to access the data for the purpose(s) described, all of whom are substantive employees of University of Oxford.

The data will be linked at record level with the trial data.

All contact data for the participants are held securely on a database at the Clinical Trials Service Unit and all paper documents are kept in a locked office to which only ACST-2 staff have access.

The patient-identifiable data will not be made available to any third parties, including the worldwide collaborators.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

The Data will only be used for the purposes described in this Agreement.

No data will be shared with third parties.

For clarification, NHS Digital will not supply information about cancer notifications for the purpose of this trial.

Patient outcomes and NHS costs following primary hip and knee replacement surgery — DARS-NIC-172121-G0Z1H

Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251, Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2018-07 – 2021-03 2018.06 — 2021.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Patient Reported Outcome Measures (Linkable to HES)
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford’s Big Health Data Group (BHDG) is undertaking two distinct research studies that require data from the National Joint Registry (NJR) linked with Hospital Episode Statistics (HES) and Patient Reported Outcome Measures (PROMs) data from NHS Digital.

The BHDG has received the linked data under a separate Data Sharing Agreement (ref: DARS-NIC-366845-Q1F0Q) for the purposes of two unrelated studies called STAR and ATLAS respectively. This data will be reused for two further studies called UKSAFE and UTMoST respectively.

Although the Principal Investigators of the studies are different, the same individuals (statisticians and a health economist), all of whom are substantive employees of the University of Oxford, will undertake both the UK SAFE and UTMoST studies at the Botnar Research Centre at the Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS).


UK SAFE- EVIDENCE BASED COST-EFFECTIVE HIP AND KNEE ARTHROPLASTY FOLLOW-UP CARE PATHWAYS

Most people now understand the need for a cost-effective NHS but seek reassurance that this will not reduce the standard of care. This is particularly true of older people, who are the group most likely to be affected by this research.

This research seeks to demonstrate that good aftercare is not necessarily expensive, in terms of time and money on the part of both the patient and hospital staff, and that individual patient-centred follow-up can better identify potential problems in a timely fashion, to the benefit of all concerned.

Total joint replacement provides considerable improvement in quality of life to people suffering with severe joint damage and in 2013 over 150,000 total hip and knee replacements were conducted. Due to increasing ageing and obesity in the UK population, this number is likely to increase each year. Sometimes, problems can develop with the replaced joint over time and a small percentage of people require further surgery. Because joint failure is not always associated with symptoms, follow-up care is provided to ensure that problems are identified as early as possible.

Providing this care for everyone in the years after their surgery is extremely expensive and the NHS is under increasing pressure to reduce its costs. Many hospitals have dramatically reduced the amount of follow-up provided and some provide no follow-up at all. There is very little research evidence to determine whether not providing follow-up care may be causing harm to people by missing the opportunity to pick up a problem with a replaced joint before serious damage occurs.

UK SAFE is a wider program of research funded by the NIHR Health Services & Delivery Research (HS&DR) and managed by the Leeds Biomedical Research Centre that covers four work packages. The principal investigator for the UK SAFE study is at University of Leeds. The investigator at the University of Oxford was a co-applicant on the grant and is leading work package 2a which will be using data from the NJR-HES-PROMS. This work package is being completed solely by the team at University of Oxford and University of Oxford is the sole data controller. The University of Oxford has sole autonomy for work package 2a and, as co-applicant on the grant, independently determined the purpose for and the means of data processing. Leeds BRC cannot direct or instruct any purpose or means for processing the data.

This study will enable University of Oxford’s BHDG to look at the routine data from the National Joint Registry on a large group of people admitted for revision surgery. Using PROMs data, the study will look at how people came to be admitted to hospital for revision surgery, their symptoms and previous hospital visits and then compare for those who needed emergency surgery, with those who have more timely revision surgery. This will help to understand when people are most likely to develop problems with their joint replacement and to identify whether some are more likely to develop problems than others.

It is vital that a decision to stop providing follow-up is not made just to save costs to the NHS, but is based on precise evidence, which includes understanding potential benefit and harm to people.

This NIHR funded project is designed to address how to improve productivity within NHS services; ensure that the right care is delivered in the right settings; develop new, innovative ways of developing health care and allocating spending more rationally. The areas of research that the study will address will help identify mechanisms to close the NHS funding gap whilst ensuring that the interests of patients remain protected and that the standard of service provision is not compromised as prioritised by Monitor.
At the end of the study an expert panel, including individuals who have undergone joint replacement, will consider the results to develop guidelines about how follow-up should be conducted to ensure no harm is caused.


UTMoST- RISK-BENEFIT AND COSTS OF UNICOMPARTMENTAL (COMPARED TO TOTAL) KNEE REPLACEMENT FOR PATIENTS WITH MULTIPLE CO-MORBIDITIES: A NON-RANDOMISED STUDY, AND DIFFERENT NOVEL APPROACHES TO MINIMISE CONFOUNDING

Surgical randomised controlled trials (RCTs) are the gold standard in research methodology. However, despite recent evidence suggesting that surgical RCTs are both safe and useful, they remain uncommon for a number of reasons, including costs, time, ethical concerns, surgeon equipoise, and feasibility.

Non-randomised studies relying on routinely collected data, could offer an efficient alternative for the comparative assessment of surgical interventions in the National Health Service (NHS). In addition, these studies offer results which are potentially generalizable to the whole population of real world NHS patients (regardless of comorbidities or age) including patients who would have been excluded in RCTs, and they can be conducted at a much lower cost as well as within a shorter time. However, observational studies are limited by confounding and related bias due to the non-random allocation of treatment alternatives.

The University of Oxford is currently running a larger and very expansive randomised controlled trial called TOPKAT. This NIHR HTA-funded RCT is a multi-centre randomised trial to measure the clinical effectiveness and cost effectiveness of total and partial knee replacement for medial compartmental osteoarthritis. Because of its restrictive eligibility criteria, the TOPKAT RCT involves comparatively healthier participants rather than patients with more severe comorbidities. For this reason, it is unclear whether the findings of TOPKAT will have external validity to the large number of patients with multiple co-morbidities (1 in 6 according to National Joint Registry data).

The University of Oxfords BHDG will replicate TOPKAT by analysing the association between unicompartmental knee replacement (UKR) (compared to total knee replacement (TKR)) and post-operative patient reported outcomes (PROMs) amongst participants in the National Joint Registry (NJR) eligible for TOPKAT (ASA grade <3 - ASA is the physical status classification system for assessing the fitness of patients before surgery) using different analytical methods and then test for a difference between the obtained estimates and TOPKAT. If validated, the same method will be used to study the benefits (PROMs), risks (revision, complications), mortality, costs and cost-effectiveness of UKR (compared to TKR) amongst NJR participants not eligible for TOPKAT (ASA 3+).

The UTMoST project will complement the results of the NIHR HTA-funded TOPKAT RCT, where unicompartmental (UKR) is compared to total knee replacement (TKR). The UTMoST will assess the risks, benefits and costs of these two alternative surgical procedures amongst the NHS patients with multiple co-morbidities who were not eligible for TOPKAT according to the listed inclusion/exclusion criteria. The study will have a clear impact on and benefits for the public and the NHS, as well as for clinical research funders including NIHR by providing information on the comparative risks, benefits (patient-reported outcomes), and cost of partial and total knee replacement for patients with multiple co-morbid conditions.

Expected Benefits:

UK SAFE- EVIDENCE BASED COST-EFFECTIVE HIP AND KNEE ARTHROPLASTY FOLLOW-UP CARE PATHWAYS

Upon completion, this research will have major immediate effect on national NHS planning and budgeting and patient well-being. The outputs will be evidence-based support for timing of follow- up and identification of the most cost-effective follow-up model. This fits directly within the NHS framework for improving outcomes from elective procedures. Rationalising current diversity of follow-up practices should enable substantial savings for the NHS. Novel follow-up strategies, such as creating a rapid access pathway after joint replacement for symptomatic patients will be examined. It is envisaged outputs to be readily applicable to the wider NHS, not only hip and knee but also other joint replacements.

The impact will be to reduce the burden on patients and the NHS in terms of outpatient visits and clinical tests that do not add benefit, while optimising detection of potential problems. From an NHS perspective, this work will provide NHS managers with economic and clinical information on arthroplasty follow-up to inform service planning and delivery, and the role of arthroplasty practitioners in this service; provide orthopaedic surgeons with guidance on follow-up, including patient and economic considerations of factors involved; produce arthroplasty follow-up guidelines for adoption by the relevant specialist societies and inclusion with information for their members. From a patient perspective, this work will help to inform patients about follow-up practice and empower them to make choices about future healthcare relating to their joint arthroplasty.

At the end of the project, a policy document will be created with support of the relevant societies, NHS England, CCGs and patient representation. It is anticipated that this will include a stratification algorithm to determine appropriate follow-up for an individual patient, taking into account, for example, implant type and patient factors, and that recommended follow-up pathways for hip may differ to those for knee. This advisory document will be disseminated to all stakeholders, including orthopaedic surgeons, arthroplasty surveillance professionals and NHS managers. With the committed support of these key organisations, the applicant anticipates that these guidelines will be positively received and that implementation will be widespread. It is the BDHG’s ambition that the recommended follow-up pathway/s defined by this programme of work will be adopted for all hip and knee replacement patients in the UK and internationally.

The target date is 36 months following receipt of data.


UTMoST- RISK-BENEFIT AND COSTS OF UNICOMPARTMENTAL (COMPARED TO TOTAL) KNEE REPLACEMENT FOR PATIENTS WITH MULTIPLE CO-MORBIDITIES: A NON-RANDOMISED STUDY, AND DIFFERENT NOVEL APPROACHES TO MINIMISE CONFOUNDING

This study will have clear impact on and benefits for both the public and the NHS, as well as for clinical research funders including NIHR by:

- Providing information on the comparative risks, benefit (patient-reported outcomes), and cost of partial and total knee replacement for patients with multiple co-morbid conditions.

If, as expected, UKR is safer, as effective, less costly, and thus more cost-effective than TKR for this specific patient group, it might become the first line surgical solution for severe knee arthritis in multi-morbid patients. The BDHG would then inform NICE and the Medicine and Healthcare products Regulatory Authority (MHRA) of the findings with the aim to impact on future guidelines for the treatment of severe knee arthritis. Depending on the study results, the BDHG would –if relevant- produce UK guidance documents and information leaflets for patients and health care professionals in both primary and secondary care involved in this area.

- Informing on the usefulness of efficient studies using routinely collected (non-randomised) data for the evaluation of surgical alternatives in the NHS to complement randomized studies.

If some or all of the proposed pharmaco-epidemiological analytical methods are able to replicate the findings from an ongoing surgical RCT, these could be used in the future to provide information on the comparative risk-benefit and cost-effectiveness of surgical options for patients typically under-represented in (or even excluded from) randomized studies. This would typically include a growing proportion of the UK population: the elderly and multi-morbid patients.

The target date is 48 months following access to data.

Outputs:

UK SAFE- EVIDENCE BASED COST-EFFECTIVE HIP AND KNEE ARTHROPLASTY FOLLOW-UP CARE PATHWAYS

This project will deliver the first research-supported, best-for-patient, joint-specific, cost-effective recommendations for follow-up care, providing a gold standard for clinical excellence, and follow-up advice for patients, surgeons, purchasers and health services. Value is not limited to the UK, but has massive global potential.

Nationally, the outputs, in the form of an executive summary statement of the agreed pathway/s will be disseminated through appropriate NHS Networks, the NHS England Elective Orthopaedics Sub- committee, the NHS Institute for Innovation and Improvement and professional societies. Dissemination will be key to developing a culture of ‘finding the best way of doing something and doing it everywhere’ to significantly reduce wastage of clinical resources and optimise NHS spend.

The University of Oxford have support of the British Hip Society (BHS), British Orthopaedic Association (BOA), British Association for Surgery of the Knee (BASK), NHS England, Arthroplasty Care Practitioners Association (ACPA), the National Joint Registry and three Leeds-based CCGs for this research and for dissemination activities. The University of Oxford will put forward the consensus statement to each society’s AGM for adoption as a resolution.

Internationally, dissemination platforms are already in place through the International Society of Arthroplasty Registers (ISAR) and the European Federation of National Associations of Orthopaedics and Traumatology (EFORT).

Overall findings and findings from individual work-packages will be disseminated through a variety of media. Abstracts will be submitted to major British and international orthopaedic conferences, and separate relevant meetings, including the Health Economics Study Group and Exploiting Existing Data for Health Research conference. The University of Oxford will look to present at the NIHR Methodology Conference and NHS Management conferences and events. Manuscripts will be submitted to appropriate peer-reviewed journals, including general medical, orthopaedic and management journals.

Patient dissemination will be supported through the Leeds Musculoskeletal Biomedical Research Unit (LMBRU) PPI forum and website and the strong ties with Arthritis Care of the applicant within the University. The BDHG will hold a PPI conference at the end of the study. The BDHG will encourage their PPI representatives to be involved in presentations, with support from research staff, and they will help to ensure conference material is appropriate. Working with the lay representatives, the BDHG will write a lay summary for publication in a patient publication such as The Patient or Inspire.

The target date is 36 months following receipt of data.


UTMoST- RISK-BENEFIT AND COSTS OF UNICOMPARTMENTAL (COMPARED TO TOTAL) KNEE REPLACEMENT FOR PATIENTS WITH MULTIPLE CO-MORBIDITIES: A NON-RANDOMISED STUDY, AND DIFFERENT NOVEL APPROACHES TO MINIMISE CONFOUNDING

The University of Oxford will write a thorough report of the research at the end of the project to be included in the NIHR HTA Journal. In addition, the University will publish at least two papers in national and/or international scientific journals to report key findings. In order to increase the impact and accessibility of the findings, they will be published in open access journal(s) when possible.

The results will also be presented at national (British Orthopaedic Association, British Society of Rheumatology, or similar) and international (American Association of Orthopaedic Surgeons, American College of Rheumatology, or similar) scientific conferences, preferably in the format of oral presentation/s.

The University of Oxford will discuss the results (including risk-benefit and cost-effectiveness evaluation/s) with relevant panels at NICE to make them available for future health technology assessments.

The University of Oxford will also disseminate the findings to the public. A Public Patient Involvement (PPI) co-investigator will help to design materials such as leaflets for this purpose, which will be distributed in key places/events like surgeries, hospitals and meetings organised by charities. The PI will present the results in meetings with both local and regional patient groups (such as the NJR patient Network), and charities such as National Rheumatoid Arthritis Society (NRAS) and Arthritis Care will be involved in this stage to ensure the public are reached in an effective and respectful way.

Finally, the results will be disseminated through the media when possible – local radio, charity magazines, etc.- following advice from departmental Outreach and Communications officers, as well as resources available through the Oxford NIHR Biomedical Research Centre network.

The target date is 36 months following access to data.

Processing:

NDORMS will forward to NHS Digital via a Secure Electronic File Transfer (SEFT) account from their current dataset and NHS Digital will reidentify them, apply objections and return a cleaned list of HESIDs. NDORMS can then extract only the data linked to those HESIDs thereby applying current patient objections.

The linked NJR, HES and PROMS datasets are held on a password protected University Computer on an encrypted drive at the Botnar Research Centre, Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS).

Access to the data is restricted to the statisticians and health economists who are substantive employees of the University of Oxford and based at the Botnar Research Centre and who will work collaboratively on both the UK SAFE and UTMoST studies.

The BHDG has received pseudonymised HES and PROMS data under a separate Data Sharing Agreement (ref: DARS-NIC-366845-Q1F0Q) which are linked with pseudnoymised NJR data for the purposes of two unrelated studies called STAR and ATLAS respectively. The BHDG will take copies of some that data to reuse them for the purposes of the UK SAFE and UTMoST studies respectively. The detailed process to do this is as follows:

1. From the dataset that the University of Oxford is authorised to hold and process under the Data Sharing Agreement DARS-NIC-366845-Q1F0Q, the encrypted HESIDs will be extracted and supplied to NHS Digital.
2. NHS Digital will decrypt those IDs to identify the individuals.
3. NHS Digital will apply national patient opt-outs to this list of patients. The data of any individual who has registered a Type 2 objection/patient opt out since the data was supplied under DARS-NIC-366845-Q1F0Q will be removed.
4. NHS Digital will remove all identifiers; re-encrypt the HESIDs using the same encryption key as for DARS-NIC-366845-Q1F0Q, and provide the list of HESIDs, as pseudo-anonymised data, to the University of Oxford.
5. The University of Oxford would extract a copy of the linked HES, PROMS and NJR supplied under DARS-NIC-366845-Q1F0Q for all individuals whose data is included in the output file from NHS Digital. The resulting dataset will be stored separately from the dataset supplied under DARS-NIC-366845-Q1F0Q with access controls ensuring the two will not be linked or accessed together.

The same fields of data are required for both studies and the knee replacement data will be used in both but the hip replacement data will only be used for UK SAFE. The data will be used exclusively for the purposes of the specified studies. The data will not be made accessible to any third parties. At the end of the studies, the data will be safely held in a password protected University Computer at the Botnar Research Centre, for further 5 years, and accessed only to answer questions arising from the publication and other publicity if required.

Only individuals, substantively employed by the University of Oxford, will have access to the data. The processing of the requested data will be carried out in the course of its legitimate activities by a University of Oxford research team which has a longstanding experience in orthopaedic outcomes.

All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. No record level data falling under this agreement will be shared with any third-party.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract – i.e. employees, agents and contractors of the Data Recipient who may have access to that data.

RECOVERY Trial - Communications to Participants DSA — DARS-NIC-405749-N7T3M

Opt outs honoured: No - consent provided by participants of research study, No (Excuses: Consent (Reasonable Expectation))

Legal basis: Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2020-11 – 2023-11 2020.12 — 2021.01.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Demographics
  2. Mailing - Cohort - Non-aggregate (Comms & Recruitment)

Type of data: Identifiable

Objectives:

BACKGROUND:
The RECOVERY trial, coordinated by Oxford University, is a national clinical trial aimed at identifying treatments that may be beneficial for people hospitalised with suspected or confirmed COVID-19 (Corona Virus).

In 2019 a novel coronavirus-induced disease (COVID-19) emerged in Wuhan, China. A month later the Chinese Center for Disease Control and Prevention identified a new betacoronavirus (SARS [Severe Acute Respiratory Syndrome] coronavirus 2, or SARS-CoV-2) as the aetiological (causing or contributing to the development of a disease or condition) agent. The clinical manifestations of COVID-19 range from asymptomatic infection or mild, transient symptoms to severe viral pneumonia with respiratory failure. As many patients do not progress to severe disease the overall case fatality rate per infected individual is low, but hospitals in areas with significant community transmission experienced a major increase in the number of hospitalized pneumonia patients, and the frequency of severe disease in hospitalised patients was recorded as high as 30%. The progression from prodrome (an early symptom indicating the onset of a disease or illness - in this case usually fever, fatigue and cough) to severe pneumonia requiring oxygen support or mechanical ventilation often takes one to two weeks after the onset of symptoms. The kinetics of viral replication in the respiratory tract are not well characterized, but this relatively slow progression provides a potential time window in which antiviral therapies could influence the course of disease. The RECOVERY Trial aims to compare several different treatments that may be useful for patients with COVID-19. These treatments have been recommended by the expert panel that advises the Chief Medical Officer (CMO) in England.

TRANSPARENCY/PARTICIPANTS:
The Health Research Authority (HRA) details in their Research Transparency Strategy that ‘Informing Participants’ is one of the four elements of research transparency, stating that it is a good practice requirement that people who have taken part in a research project are thanked for their contribution and told about what it helped the researchers to find out, where appropriate. Furthermore, the UK Policy Framework for Health and Social Care Research says: “Information about the findings of the research [should be] available, in a suitable format and timely manner, to those who took part in it, unless otherwise justified.” This approach is also supported by the National Institute of Health Research (NIHR) and United Kingdom Research and Innovation (UKRI) who are funders of the RECOVERY trial.

There has been recurring feedback from patient panels that people would like to hear about the results of the trials in which they participated. Such feedback has been received from members of panels that are coordinated by the Nuffield Department of Population Health at Oxford University.

To this end, the RECOVERY trial team are looking to send a series of updates to participants to make them aware of the trial results to which they have contributed. An agreement is therefore being put in place with NHS Digital to facilitate this (the subject of this agreement)

Traditionally, the trials units within the University of Oxford’s Nuffield Department of Population Health have collected patient contact details including addresses and would therefore have been able to communicate directly with trial participants. However, due to the requirement to recruit people into the trial quickly whilst minimising impact on frontline workers, participant addresses have not been captured in this instance. Given the short duration of the study intervention for RECOVERY (10 day treatment period), direct to participant communications systems have not been established, in contrast to the department’s longer-term cardiovascular trials where the treatment period can be as long as 5 years. Consequently, the RECOVERY trial team are looking for support from NHS Digital through the NHS DigiTrials service to determine the addresses of trial participants using the cohort details provided by Oxford University, and contact participants, by letter, on their behalf.

Whilst there has been considerable media coverage of the results of the trial, the RECOVERY team would like to thank participants directly for their contribution and ensure that they are aware of the trial results, as well as inviting participants to support future public engagement and involvement by becoming part of a RECOVERY-specific participant panel. This panel will provide feedback on future communications and ensure that the trial team are aware of the needs and concerns of existing and future participants. The letters will also provide an opportunity to remind participants that information about how their data are handled is available on the trial website.

RECOVERY wishes to inform its surviving participants (or parents/guardians of child participants) of the results to date from the RECOVERY trial. This is considered best practice and Nuffield Department of Public Health has always done this at the end of its trials before. Because RECOVERY has generated results already (but the trial is still ongoing) the team wish to inform participants throughout the course of the trial. The RECOVERY team would also like to take the opportunity to give participants the opportunity to opt out of such communications in the future, or to receive them electronically (rather than by mail). The team also keen to involve participants in the development of RECOVERY and other trials, so would allow participants to volunteer for this if they are interested, as well as thanking them for their participation in the trial.

The RECOVERY database has a unique participant ID for each participant, linked to their NHS number.
This linkage has been validated already as it is used to collect outcome data from NHS Digital for the trial, so NHS Digital can also link from participant ID to NHS number.

RECOVERY would create a list of participant IDs (excluding anyone RECOVERY knows to have withdrawn consent for all forms of follow-up) and provide this securely to NHS Digital using existing secure data transfer methods. This list would indicate whether the participant should receive the adult letter, or whether the parent/guardian letter should be sent to their parent or guardian.

This list of Participant ID's will be compared against the existing cohort that NHS Digital receives for the main RECOVERY Trial Data Sharing Agreement on a weekly basis (under DARS-NIC-365354).

NHS Digital would perform a vital status check and remove any additional participants known to have died (whom RECOVERY may not have been aware of due to the intermittent nature of the vital status update that RECOVERY receives).

NHS Digital would then retrieve the address for the remaining participants and provide this to APS Group - a marketing service group that is a recognized and trusted provider of NHS Services. They are used frequently to co-ordinate mail outs for NHS Bodies.
APS Group would have the template letters and would merge address details onto the letter prior to mailing it out.
NHS Digital would also return the final list of participant IDs who will be mailed a newsletter to the RECOVERY team.

NHS Digital would store the final list of recipients, but would not use it for any future mailings which would begin with RECOVERY providing a new list of participant IDs.

Each mailing would include information for participants who wish to opt out of future mailings. This information will also be on the trial website and included in the privacy notice. Participants will be able to write, telephone or e-mail their intention to the RECOVERY team who would flag their record accordingly in the database.

Any such participants would be removed from the list of participant IDs that RECOVERY send to NHS Digital for any subsequent mailing (along with those who have died, withdrawn consent for follow-up or elected to receive communications electronically).

Ethical approval of these communications will be handled directly by the RECOVERY trial, who have engaged with the Chair of the Cambridge East Research Ethics Committee (REC) (trial ref 20/EE/0101). The outcome of this engagement was that it would be sufficient for the ethics committee to approve a template and/or the 'boundaries' within which the communication would work. After that, each letter does not need to be approved, though the RECOVERY trial will send a copy for their records.The RECOVERY trial team will seek feedback from the existing Nuffield Department of Population Health and NHS DigiTrials public panels to ensure that the communications are appropriate to lay audiences, prior to review by the research ethics committee. These panels have already been involved in reviewing other RECOVERY-related materials.

The University of Oxford relies on the General Data Protection Regulation (GDPR) Article 6 (1) (e), to carry out its public task and for processing special categories of data (including health information); and GDPR Article 9.2(j), for archiving, research and statistics.

Yielded Benefits:

By the end of July 2020, the RECOVERY trial had successfully established over 175 sites across the UK and recruited over 11,000 participants treated in hospital for COVID-19. The data linkage already established to received SUS+ and other data is providing important information to the Data Monitoring Committee on a weekly basis about patients' recovery (i.e. discharge from hospital), in-hospital death and procedures required. Provision of complete and reliable data to the DMC through May and early June 2020 is critical to allow robust assessment of the effects of the the trial treatments with a major contribution to these data expected from analysis of the routine health care data requested under this agreement. On Thursday 4 June, in response to a request from the UK Medicines and Healthcare Products Regulatory Agency (MHRA), the independent Data Monitoring Committee conducted a further review of the data. The DMC recommended the chief investigators review the unblinded data on the hydroxychloroquine arm of the trial. The results included a total of 1542 patients randomised to hydroxychloroquine compared with 3132 patients randomised to usual care alone. There was no significant difference in the primary endpoint of 28-day mortality (25.7% hydroxychloroquine vs. 23.5% usual care; hazard ratio 1.11 [95% confidence interval 0.98-1.26]; p=0.10). There was also no evidence of beneficial effects on hospital stay duration or other outcomes. These results were released to the public and on the 15 July 2020, the U.S. Food and Drug Administration (FDA) revoked the emergency use authorization (EUA) that allowed for chloroquine phosphate and hydroxychloroquine sulfate donated to the Strategic National Stockpile to be used to treat certain hospitalized patients with COVID-19 when a clinical trial was unavailable, or participation in a clinical trial was not feasible. This result has major implications for countries around the world who were planning to scale manufacturing of these drugs in order to treat COVID patients. On 8 June 2020, recruitment to the dexamethasone arm was halted since, in the view of the trial Steering Committee, sufficient patients had been enrolled to establish whether or not the drug had a meaningful benefit. On 16 June 2020, preliminary results were released. A total of 2104 patients were randomised to receive dexamethasone 6 mg once per day (either by mouth or by intravenous injection) for ten days and were compared with 4321 patients randomised to usual care alone. Among the patients who received usual care alone, 28-day mortality was highest in those who required ventilation (41%), intermediate in those patients who required oxygen only (25%), and lowest among those who did not require any respiratory intervention (13%). Dexamethasone reduced deaths by one-third in ventilated patients (rate ratio 0.65 [95% confidence interval 0.48 to 0.88]; p=0.0003) and by one fifth in other patients receiving oxygen only (0.80 [0.67 to 0.96]; p=0.0021). There was no benefit among those patients who did not require respiratory support (1.22 [0.86 to 1.75]; p=0.14). Based on these results, 1 death would be prevented by treatment of around 8 ventilated patients or around 25 patients requiring oxygen alone. On the 16 June 2020, on the basis of these results, the MHRA issued an alert to health care providers in the UK recommending the use of dexamethasone in hospitalised patients with COVID who require oxygen or ventilation. In addition dexamethasone has also been added to the government’s parallel export list, which bans companies from buying medicines meant for UK patients and selling them on for a higher price in another country. A recent analysis estimates that treatment with Dexamethasone may save between 4,000 and 27,000 lives in the UK by January 20201 (depending on the number of COVID-19 cases during Q3-4 2020) and potentially over half a million lives worldwide (https://www.medrxiv.org/content/10.1101/2020.07.29.20164269v1). Without the results from RECOVERY the effectiveness of this treatment would not be known. A paper was recently published in the New England Journal of Medicine entitled "Dexamethasone in Hospitalized Patients with Covid-19 — Preliminary Report" (17/07/2020) detailing the results. The above demonstrates that the RECOVERY Trial is a fast paced moving trial with plenty to communicate to participants about updates and ongoing work.

Expected Benefits:

Keeping participants informed of results of trials they are involved with is a high priority according to the Health Research Authority and is best practice. Participants frequently request information about the outcome of trials in which they have participated and being able to share information without the RECOVERY team needing to process contact details is a key benefit. Whilst there has been considerable media coverage of the results of the trial, the RECOVERY team would like to thank participants directly for their contribution and ensure that they are aware of the trial results.

RECOVERY will use this process throughout the trial period (which includes follow-up for 10 years). We hope that by communicating regularly with participants, we will help to keep them engaged with the work of RECOVERY and make it clear that participants are partners in the research.

The communications will also provide an opportunity to invite participants to support future public engagement and involvement by becoming part of a RECOVERY-specific participant panel. This panel will provide feedback on future communications and ensure that the trial team are aware of the needs and concerns of existing and future participants. The letters will also provide an opportunity to remind participants that information about how their data are handled is available on the trial website.

Outputs:

The key immediate output will be a file of participant IDs, names and addresses which would be passed to APS to generate the mailings.

APS are an approved mailing house with the relevant NHS Digital approvals.

The ultimate output of this data processing will be participants being mailed a letter to inform them about the results to date from the RECOVERY trial. This data processing is for this single element of the much larger RECOVERY trial so other outputs such as results presentations and publications would not be expected as a result of this specific process.

The RECOVERY trial has a separate DSA for other data that are being processed that would generate these more traditional outputs. However, the process of securely sending the study results to trial participants described in this application will be an exemplar of good practice, which will encourage other researchers to provide similar information to their trial participants.

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e: employees, agents and contractors of the Data Recipient who may have access to that data).

Proposed Method
Oxford University already provide cohort details to facilitate data minimisation for the data sets included in their existing Data Sharing Agreement (DARS-NIC-365354).
Participants who have already withdrawn consent for collection of long-term health care data are removed from the cohort prior to submitting to NHS Digital. NHS Digital would be extracting this existing cohort information and using the Master Patient Service (MPS) to locate the correlating patient addresses and check vital status prior to generating the mailings. This cohort information will be provided in a list format to APS Group. They will co-ordinate the mail out of specific letters.

The communications would consist of letters tailored to specific audiences. Additional analysis would be needed to split the cohort into the following groups for different letters:
1. Parents or guardians of children
2. Surviving adult participants.

Sample communications that will be reviewed by public panels and an ethics committee prior to sending have been provided by Oxford University. The date of birth of participants will be provided by Oxford University so that it is clear which letter should be sent.

NHS Digital would be using an established contract with a mailing provider (APS Group) to fulfil the communications. The APS Group are also used by NHS England and NHS Improvement.

Ideally the first round of communications would take place in October, providing a summary of the results to date. Further rounds of communication would be required as and when new information becomes available.

Data will come into the APS Group Customer Communications Management Platform which is hosted in the Normanton data centre, This solution is segregated from all APS GroupBusiness As Usual functional system by physical network segregation. Access to this solution is via Named AD accounts and two factor authentication and is on a needs only basis. All data received into this solution is via Secure File Transfer Protocol and in accordance with any data sharing agreement in place with the client. Normally APS Group would expect this data to arrive encrypted. Once received the data is transferred to the processing platform where any agreed processing will take place. Data is encrypted at rest using PGP when not being processed. Any data in this platform is deleted as a standard after 30 days or in accordance with any processing agreement. Once processed the data will be sent to the appropriate output engine within APS Group production.

All APS sites and data centres are protected by 24/7 CCTV, Named badge access control which limits access to only those areas required

All APS Group networks are segmented using Vlans and where required for security these vlans prevent access, data flow, external access etc, our secure production site maintains a fully secure network in accordance with this. APS Tests all its networks internally and externally on a monthly basis for vulnerabilities

Handling follow up queries
The letter provides email, postal and telephone details for follow up enquiries. Email enquiries would be directed to the RECOVERY trial’s existing generic email address and handled by the Oxford-based coordinating centre, and telephone enquiries would be handled by MessageDirect – a contact centre that is currently being used for trial communications. MessageDirect would not receive any information from the RECOVERY trial or NHS Digital about trial participants and will handle enquiries as instructed.

A 'return to sender' address will need to be included on the letters. When letters are unable to be delivered to the participant address provided by NHS Digital - they will be returned to NHS Digital where they will be shredded.

The delivery of major trauma care in England - impact and effectiveness following a whole system reorganisation. — DARS-NIC-177392-B8T1Z

Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251, Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2018-08 – 2021-07 2018.10 — 2020.09.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Critical Care
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Outpatients
  4. Hospital Episode Statistics Accident and Emergency
  5. HES:Civil Registration (Deaths) bridge
  6. Civil Registration (Deaths) - Secondary Care Cut
  7. Civil Registration - Deaths
  8. Civil Registrations of Death - Secondary Care Cut
  9. Hospital Episode Statistics Accident and Emergency (HES A and E)
  10. Hospital Episode Statistics Admitted Patient Care (HES APC)
  11. Hospital Episode Statistics Critical Care (HES Critical Care)
  12. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The Big Health Data Group (which is part of the University of Oxford) requires data from NHS Digital for the purpose of determining the clinical and cost-effectiveness of reorganisation of trauma care services into Regional Trauma Networks (RTNs) and Major Trauma Centres (MTCs).

Trauma is the leading cause of mortality under the age of 45 years and a significant cause of short and long-term morbidity. Every year 12,500 people die from trauma in England & Wales.

There is some international evidence that inclusive trauma systems within designated major trauma centres (MTCs) may reduce mortality for severely injured patients. Following the international trend, Regional Trauma Networks (RTNs) were established in England in 2012, each with one or more dedicated specialist hub hospitals or Major Trauma Centres (MTCs). This restructuring required considerable financial investment by the NHS, however it is not known whether this has resulted in improved care for severely injured patients.

The reconfiguration of major trauma services has been associated with very substantial changes to hospital case-mix, clinical processes and workload. Some limited observational data suggest that there has been a reduction in mortality following reorganisation. However, despite being in place for almost five years, there is substantial variation in the way MTCs in England are structured and organised.

Providers agree that information-sharing up to now has been ineffective and that they do not know how best to provide services and almost certainly, the existing variations in services between MTCs lead to variations in health outcomes.

Open fracture of the lower limb is a unique tracer condition for trauma services organisation. It can be diagnosed at the point of injury and has clear within-network bypass pathways testing triage and bypass systems with RTNs. Specialist surgical associations and National Institute for Health Care and Excellence (NICE) have issued widely agreed best practice guidance for the management of these severe injuries (NG37 & BOAST4) which requires these patients to be immediately transferred to the care of specialist trauma multidisciplinary teams provided exclusively by MTCs. The Trauma Audit and Research Network (TARN) collects the key performance indicators for this care pathway now reporting centre-level compliance with these standards. Effective, timely treatment reduces complications and length of stay and failed initial treatment very often mandates revision surgery; all outcomes recorded in Hospital Episode statistics (HES).

The objective of this study is to explore variation in outcomes following major trauma and link this to the variations in service structures already operating across England to inform planning for future services in the devolved countries. The results can improve major trauma services by learning from variation that exists in our current systems. Crucially, the system in England may soon be replicated in other UK countries.

Expected Benefits:

Open fracture is a major societal burden: nearly 7000 people sustain open fractures in the UK every year. (Performance Comparison: Trauma Care. (2016)).

In and out of hospital care and societal costs are substantial even in the least injured patients. TARN reported outcomes from the MTC22 collaborative from 646 of the most severe type of open fracture of the tibia in the last annual reporting cycle (in press Young et al 2017).

The biggest single observational study of these most severe injuries (Bosse, M. J. et al. An analysis of outcomes of reconstruction or amputation after leg-threatening injuries. N. Engl. J. Med. 347, 1924–1931 (2002)) estimated that 40% of patients had persisting severe disability; only half returned to work and US healthcare costs (2002 USD) were $163,000 if the limb can be salvaged and more than $500,000 if amputation is required. This was a fraction of the subsequent personal and societal cost.

Determining the effectiveness of components of the service will reduce the costs to the NHS by reducing variability and maximise patients’ functional recovery and quality of life following open fracture. This programme of work will be considered by the Major Trauma Clinical Reference Group which advises NHS England on the services that should be commissioned for major trauma. This programme will produce new economic models for MTCs effectiveness, capable of informing commissioning decisions and modelling considerations for updates to NICE Major Trauma Guidance (NG40). Major trauma: service delivery. www.nice.org.uk (2016). Available at: https://www.nice.org.uk/guidance/ng40. (Accessed: 16 February 2017)

The University of Oxford will also be able to provide evidence for the utility of the national audit of trauma, generating high impact research findings from this dataset. This was a research priority identified by NICE in same guideline (NG40). Major trauma: service delivery. www.nice.org.uk (2016). Available at: https://www.nice.org.uk/guidance/ng40. (Accessed: 16 February 2017)

The University of Oxford will feedback to each of the centres their individual centre performance, in terms of cost and clinical outcomes; but crucially set within the context of the national picture across the 22 MTCs. This will allow local hospital staff and management to identify areas of good practice and those which may be improved. This will facilitate hospitals to take up evidence-based best practice in major trauma service delivery for the first time, reducing the unwarranted variability in outcomes across England.

Outputs:

At the conclusion of this study the University of Oxford will have provided the most robust evidence available to establish the clinical and cost effectiveness of MTCs in England and current recommendations for care for these injuries. The study team will be able to recommend service design considerations for better outcomes for patients sustaining open fractures of the lower limb.

The study team will deliver customised reports for the following organisations:
• NICE
• The 22 Major Trauma Centres
• NHS England
• Central Commissioning - Clinical Reference Group Major Trauma

These will be in addition to publications in peer-reviewed journals and at national conferences. A final and full research report detailing all the work undertaken and supporting technical appendices, an abstract and an executive summary will be provided at the end of the study. A set of PowerPoint slides will be provided presenting the main findings from the research for use of members of the research team and others in disseminating research findings to the NHS. The study team will publish a full and complete account of that research in the NIHR HS&DR Journal, ensuring the research is reported fully, and publicly available via the NIHR Journals Library website and Europe PubMed Central.

Target date: End of March 2023

Processing:

The Trauma Audit and Research Network (TARN) is hosted by the University of Manchester. TARN will generate a cohort from the year 2000 to present of all patients with an open fracture recorded in the database. A file of unique TARN ID patient identifiers (pseudonymised) along with the NHS number, date of birth, gender and postcode will be sent from the University of Manchester to NHS Digital. The cohort is expected to include approximately 100,000 patients.

NHS Digital will link HES data and mortality data (date and cause of death) for each patient identified in the TARN cohort using the matching data file (containing NHS number, date of birth, gender and postcode) to the unique TARN identifier. The HES and mortality data will be at patient level and pseudonymised. NHS Digital will destroy the linkage file once linkage is achieved. The pseudonymised HES and mortality data with the linked TARN ID will be sent to the University of Oxford.

TARN will send pseudonymised patient-level TARN non-sensitive data for all patients identified in the cohort with the linked TARN ID to the University of Oxford

University of Oxford will link the pseudonymised datasets received from NHS Digital and University of Manchester using the unique TARN identifier to yield a non-identifiable patient-level dataset linking TARN and HES data for all patients with an open fracture identified within the cohort. The data will not be linked to any other data and only the linkages described are permitted under this Agreement.

University of Oxford will analyse the dataset to:

1. estimate the clinical effectiveness and impact on costs to the NHS of the reorganisation of services into RTNs & MTCs in 2012.
2. estimate the cost-effectiveness of the organisation of MTCs according to their level of compliance with BOAST4 guidance and their models of care.
3. explore the influence of components of the BOAST4 care pathway and service structures on the clinical effectiveness of MTCs.
4. provide evidence as to whether the introduction of new surgical standards and centralisation of services has led to improved patient outcomes compared with the previous models of care.

All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. No record level data falling under this agreement will be shared with any third-party.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract – i.e. employees, agents and contractors of the Data Recipient who may have access to that data.

MR1471 (MR865 & MR850) - HEALTH OF CIVIL SERVANTS — DARS-NIC-148044-RGS7W

Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2018-10 – 2020-09 2016.04 — 2020.07.

Access method: Ongoing, One-Off

Data-controller type: LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE, UNIVERSITY COLLEGE LONDON (UCL), UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Bespoke
  4. Civil Registration - Deaths
  5. Demographics
  6. Cancer Registration Data
  7. MRIS - Flagging Current Status Report
  8. Civil Registrations of Death

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

The objectives of the Whitehall resurvey are to quantify reliably the relevance of blood lipids, markers of inflammation and nutrition and genetic markers, for cardiovascular and non-cardiovascular mortality in older people. This resurvey in 1997 of over 5500 older men (mean age 77 years) with questionnaires and blood samples who participated in the 1970 Whitehall study, involves over 3300 deaths over a 14-15 year follow-up period in the subset with complete data. The study has already contributed reports on vascular and non-vascular mortality in relation to blood lipids, biomarkers of inflammation, phospholipid fatty acids and cystatin C. Work is ongoing on reports mortality in relation to 25-hydroxy-vitamin D, smoking and alcohol consumption.

Yielded Benefits:

The study already made a major contribution to the identification of cardiovascular risk factors in middle aged men in the UK. The study confirmed the importance of smoking, elevated blood cholesterol, elevated blood pressure and diabetes for heart disease death rates in lower compared with upper employment grades which were not fully explained by established risk factors. The access to lifestyle and medical information in both middle and old age allowed assessment of prolonged differences in such risk factors for life expectancy and causes of death in old age. The study has provided unique data on causes of death in old age in relation to very prolonged differences in cardiovascular risk factors and socioeconomic circumstances in middle and old age. These reports will guide public health policy on the provision of health services to reduce the risks of death and disability in older people in the UK and elsewhere. The study will highlight the importance of modifiable risk factors for avoidable disability in old age using information collected in both middle and old age. Influence on guidelines for the management of hypertension and blood lipids: The 2002 report of the Prospective Studies Collaboration report on blood pressure and stroke and heart disease (Lewington et al, Lancet 2002), included the Whitehall data and was also based on the methodology to correct for regression dilution bias developed in the Whitehall and Framingham studies (Clarke et al, Am J Epidemiol 1999). Likewise, the 2007 report of the Prospective Studies Collaboration report on blood cholesterol and stroke and heart disease (Lewington et al, Lancet 2007), included the Whitehall data and was also based on the methodology to correct for regression dilution bias developed in the Whitehall and Framingham studies. These reports influenced JNC7 Guidelines on the Detection and Treatment of Hypertension in the USA and NICE guidelines for the management of hypertension and blood lipids in the UK in addition to the European Society of Cardiology reports on prevention of heart disease (Piepolo 2016) and detection and management of blood lipids (Capetano, 2016) and American Heart Association reports for prevention of heart disease over the last 15 years. References for benefits of study Lewington S, Clarke R, Quizilbash N, Peto R, Collins R for the Prospective Studies Collaboration. Age-specific relevance of usual blood pressure to vascular mortality: One million adults in 61 prospective studies. Lancet. 2002;360:1903-1913. Lewington S, Whitlock G, Clarke R, Sherliker P, Emberson J, Halsey J, Qizilbash N, Peto R, Collins R on behalf of the Prospective Studies Collaboration. Blood cholesterol and vascular mortality by age, sex and blood pressure: a meta-analysis of individual participant data from 61 prospective studies with 55,000 vascular deaths. Lancet. 2007;370:1829-1839. Piepolo MF, Hoes AW, Agewal S, Albus C, Brotons C, Catapano AL, Cooney MT. 2016 guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J 2016; 37 (29): 2315-81. Catapano AL, Graham I, De Backer G, Wiklund O, Chapman MJ, Drexel H, Hoes AW, Jennings CS, Landmesser U, Pedersen TR, Reiner Ž, Riccardi G, Taskinen MR, Tokgozoglu L, Verschuren WM, Vlachopoulos C, Wood DA, Zamorano JL. 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias: The Task Force for the Management of Dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS). Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). Eur Heart J 2016;37: 2999-3058.

Expected Benefits:

The study will conduct medical research into the causes of death in this sample of the UK population. It is anticipated that the results of the planned analysis will be published in peer review medical journals. The results from this study have helped to inform UK response to the epidemic of deaths from heart disease and stroke in 1970’s and 1980’s and the extent to which mortality from both of these diseases have declined thereafter.

Anonymised data from this study were incorporated in the Prospective Studies Collaboration meta-analysis which guided public health policy on detection and treatment of elevated blood pressure and of elevated cholesterol levels in the UK and worldwide. Data from the resurvey on blood lipids and CHD mortality have helped to clarify the relevance of lipids for prediction of death from vascular disease in old age.

Lastly, data on blood levels of vitamin D (25(OH)D) in this study have guided policy on the relevance of vitamin D and specifically for testing for vitamin D for prediction of vascular and non-vascular causes of death in the UK. The study will generate a series of scientific publications on the causes of mortality, particularly focusing on determinants of cardiovascular disease in old age in relation to cardiovascular risk factors measured in middle and old age. It will also generate reports on cardiovascular and non-vascular causes of death in relation to socioeconomic circumstances measured in both middle and old age.

As well as peer-reviewed scientific publications, the University of Oxford will also communicate with NHS and other organisations (Food Standards Agency) or Public Health England where outputs from the study will provide information needed for health strategies using up-to-date evidence on effects of cardiovascular risk factors on risk of death. This will improve provision of health care delivery and health services in response to demands on health and social care in the present and the future.

Outputs:

The chief aim of the study is to assess mortality risks in old age in relation to cardiovascular risk factors measured in middle and old age, and assess life expectancy and lifetime risks of cardiovascular risk factors measured in middle and old age.

All outputs and publications contain only aggregated data with small numbers suppressed in line with HES Analysis Guide.

The results of analyses of the Whitehall study have been presented at national and international meetings, including the Society of Social Medicine and the European Society of Cardiology and American Heart Association annual scientific sessions. The results of planned analyses will be submitted for publication and some may also be presented at national and international meetings. Likewise, results of some analyses will be posted on the Nuffield Department of Population Health (a department within the University of Oxford) website. The target time frame for publication of the results of the planned analyses is during 2018-2020.

Examples of publications are:
Underestimation of risk associations due to regression dilution in long-term follow-up of prospective studies.
Clarke R, Shipley M, Collins R, Marmot M, Peto R.
Am J Epidemiol. 1999;150:341-353.

Re-survey of the Whitehall study of London civil servants: changes in risk factors for cardiovascular disease during 29 years of follow-up.
Clarke R, Breeze E, Youngman L, Sherliker P, Bell P, Shah S, Shipley M, Collins R, Leon D, Marmot M, Fletcher A.
J Cardiovasc Risk. 2000;7:251-257.

Socioeconomic disadvantage persists into old age: self-reported morbidity in a 29 year follow-up of the Whitehall Study.
Breeze E, Fletcher AE, Leon DA, Marmot MG, Clarke R, Shipley MJ.
Am J Publ Health. 2001;91:277-283.

Cause-specific mortality in relation to body mass index in middle age in old age.
Breeze E, Clarke R, Shipley MJ, Marmot MG, Fletcher AE.
Int J Epidemiol. 2006;35:169-178.

Cholesterol fractions and apolipoproteins as risk factors for heart disease mortality in older men.
Clarke R, Emberson J, Armitage J, Shipley M, Clark S, Linksted P , Fletcher A, Collins R.
Arch Intern Med. 2007;167:1373-1378.

Survival in relation to angina symptoms and diagnosis among men aged 70-90 years: the Whitehall Study.
Clarke R, Shipley M, Breeze E, Collins R, Marmot M, Halsey J, Fletcher A, Hemingway H.
Eur J Cardiovasc Prev Rehabil. 2007;14:280-286.

Life expectancy in relation to cardiovascular risk factors: 38 year follow-up of 19000 men in the Whitehall Study.
Clarke R, Emberson J, Fletcher A, Breeze E, Marmot M, Shipley M J.
BMJ. 2009;339:b3513. doi: 104136/bmj.63513

Risk factors for pancreatic cancer mortality: extended follow-up of the original Whitehall Study.
Batty GB, Kivimaki M, Morrison D, Huxley R, Smith GD, Clarke R, Marmot M, Shipley MJ.
Cancer Epidemiol Biomarkers Prev. 2009;18:673-675.

Plasma phospholipid fatty acids and CHD in older men: Whitehall study of London civil servants.
Clarke R, Shipley M, Armitage J, Collins R, Harris W.
Br J Nutr. 2009; 102:279-284.

Whitehall Study Authors’ reply.
Clarke R, Shipley MJ.
BMJ. 2009;339:b5097.

Height loss and future coronary heart disease in London: the Whitehall II study.
Batty GD, Shipley MJ, Gunnell D, Smith GD, Ferrie JE, Clarke R, Marmot MG, Kivimaki M.
J Epidemiol Comm Health. 2011;65:461-464.

Modifiable risk factors for prostate cancer mortality in London: forty years of follow-up in the Whitehall study.
Batty GD, Kivimäki M, Clarke R, Davey Smith G, Shipley MJ.
Cancer Causes Control. 2011;22:311-318.

Vitamin D and risk of death from vascular and non-vascular causes in the Whitehall study and meta-analyses of 12,000 deaths.
Tomson J, Emberson J, Hill M, Gordon A, Armitage J, Shipley M, Collins R, Clarke R.
Eur Heart J. 2013;34:1365-74

Processing:

The cohorts were flagged by NHS Digital under an earlier data sharing agreement (DARS-NIC-148044-RGS7W-v0.0). NHS Digital will provide updates on participant events, including removals and re-entries to NHS Registration, cancer registrations and deaths including cause of death details. Participants in the Whitehall study were flagged for mortality and cancer registration at the Office for National Statistics (England), which provided the date (mm/yyyy) and cause (including International Classification of Disease (ICD) codes) of all deaths. Cause-specific mortality is coded using ICD-9 up to August 2002 and ICD-10 subsequently. In the past, mortality data and cancer registration data were provided electronically at 3-monthly intervals to the London School of Hygiene and Tropical Medicine. The data were sent to University of Oxford by encrypted email. The University of Oxford incorporated these data into the Whitehall database but in summer 2018 the data provided by NHS Digital was securely destroyed.

The participants in this study have agreed to prolonged follow-up via central registries via patient consent, with the patient information sheet and consent form making reference to the fact that information about health and lifestyle and causes of death could be collected for medical research purposes. Due to the age of the consent involved, Section 251 support was also obtained to cover the continued use of identifiable data. All data on the study will be stored in secure electronic files at University of Oxford. Pseudonymised copies of the linked study data will be sent at periodic intervals by secure email using password encrypted files to named researchers at LSHTM and UCL to maintain the 3-way collaboration for supervision of the study.

The Whitehall study database held by the University of Oxford contains identifiable data for the study participants, including date of birth and name if this was provided by participants in response to questionnaires. The data disseminated by NHS Digital will be in a pseudonymised format using a Study ID, but once received by the University of Oxford the data will be combined with the identifiable study data already held. For the purposes of this agreement the data disseminated by NHS Digital is therefore considered to be identifiable. A senior statistician at the Clinical Trial Service Unit (CTSU) links the data, using study ID, with the study participants questionnaire records. All subsequent analyses use only subsets of the pseudonymised data. All such subsets are customised for specific analyses intended for specific purposes.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract, i.e. employees, agents and contractors of the Data Recipient who may have access to that data). The study will not share any data supplied by NHS Digital with any other institution or individual outside the study of the University of Oxford, London School of Hygiene, or UCL.

pre-DIRECT - All cause mortality within 12 months following hip fracture — DARS-NIC-144057-G4S0Q

Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251, Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-08 – 2020-08 2019.01 — 2020.07.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Critical Care
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Outpatients
  5. Civil Registration - Deaths
  6. HES:Civil Registration (Deaths) bridge
  7. Civil Registration (Deaths) - Secondary Care Cut
  8. Civil Registrations of Death - Secondary Care Cut
  9. Hospital Episode Statistics Accident and Emergency (HES A and E)
  10. Hospital Episode Statistics Admitted Patient Care (HES APC)
  11. Hospital Episode Statistics Critical Care (HES Critical Care)
  12. Hospital Episode Statistics Outpatients (HES OP)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires HES and Civil Registration (mortality) data for the purpose of the ‘pre-DIRECT’ study which aims to investigate the causes of death’s in patients with hip fracture. The mortality is very high, up to 30% at 12-months following hip fracture. In 2013 there were more than 61,000 hip fractures across England, Wales and Northern Ireland. There has been much research into the rates of mortality after hip fracture but systematic large-scale analysis of the causes of mortality is lacking.

In order to improve the care and management of patients it is important to understand the causes behind the high mortality rates. It is proposed that analysing the causes of death in patients with hip fracture will elucidate the reasons for such high mortality rates. This study aims to identify trends in the cause of death for patients who die in the first year following their hip fracture. By analysing the case mix included in the data, groups of patients who are at risk from particular causes of mortality in the year following the hip fracture will be identified. Further research could then investigate appropriate follow-up and preventative strategies that are targeted to reduce the risk for these patients.

The study will involve several organisations and will take place over a one-year period once the data are available for analysis at the University of Oxford.

This study will involve several organisations. The University of Oxford will receive, process and analyse the data and subsequently publish the findings. The Falls and Fragility Fracture Audit Programme (FFFAP), part of the national audit programme of the Healthcare Quality Improvement Partnership (HQIP), will provide a list of all hip fractures sustained in the UK over the last ten years.

The study will take place over a one-year period once the data is available for analysis at the University of Oxford.

The study is funded by grant income and underpinned by support from the Musculoskeletal theme of Biomedical Research Centre (BRC) and The Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS) and sponsored by the University of Oxford. NDORMS sits within the Medical Sciences Division of the University of Oxford.

NHS Digital will act as a trusted third party to securely link all datasets and send the University of Oxford an pseudonymised dataset for the analyses.

Yielded Benefits:

Due to delays in production of the data no yielded benefits have been achieved. If the University of Oxford are awarded a 12 month extension to access the data all expected measurable benefits are expected to be achieved.

Expected Benefits:

As part of the Falls and Fragility Fracture Audit Programme (FFFAP) within the Clinical Effectiveness and Evaluation Unit at the RCP, the NHFD has now developed into a comprehensive quality improvement initiative and includes several elements which will be supported through this work:
• a framework to support local and national audit work
• an infrastructure for service evaluation and research work
• a resource of specialist information, expertise and networking

The data processing under this Agreement will support:
• The first understanding anywhere in the world of cause-specific mortality following hip fracture. There are no published reports of the contribution of different types of disease and illness to the overall mortality associated with hip fracture.
• The development of clinical solutions within service design and delivery to specifically target the important causes of mortality after hip fracture.
• Generating unique specialist information which can be used across the NHS and the world to enhance expertise.

With these data it is hoped that the following will be achieved:

• Calculation of absolute mortality hazard risk after hip fracture
• Calculation of sub-group adjusted hazard risk after hip fracture
• Absolute proportion of mortality attributed to different major system dysfunction
Targets for further prospective research to reduce cause-specific mortality. For example, if it is found that the most common cause of mortality is a myocardial infarction (heart attack) then the publication of this finding may prompt further research into the follow-up cardiology care offered to patients with hip fracture. Case mix analysis from the study may even demonstrate more specific groups at risk from heart disease allowing follow-up care to become more targeted.

Outputs:

Within 12 months of receiving the data the following will be produced:

1. Peer-reviewed publication of UK hip fracture mortality risk and cause of death

2. Peer to peer dissemination of findings through (inter)national conferences:
• British Orthopaedic Association
• International Fragility Fracture Network
• Orthopaedic Trauma Society of Great Britain and Ireland

The purpose of these publications and presentations is to disseminate the project’s findings to the clinical community and raise discussion on how the results might influence the design of services provided to patients suffering a hip fracture.

Processing:

The Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences (NDORMS, University of Oxford) will use data from National Hip Fracture Database (NHFD) , which is contained within the FFFAP, in relation to patients over 60 years of age undergoing hip fracture surgery. The following personal identifiers will be provided to NHS Digital from NHFD for linkage to HES data and date of death and cause of death, : NHS numbers, date of birth, gender, postcode and unique NHFD identifier. NHS Digital will transfer a pseudonymised NHFD dataset to NDORMS for analysis, along with age, gender and clinical data.

NDORMS require data about patients over 60 years of age undergoing hip fracture surgery from the Falls and Fragility Fracture Audit Programme (FFFAP) linked with HES and civil registration mortality data. HQIP is the data controller for FFFAP data and Crown Informatics is their data processor. NDORMS only requires pseudonymised data. To facilitate the linkage of the data sets, the following will occur:
1. Crown Informatics will send NHS Number, Date of Birth, full postcode and FFFAP ID (a study ID for the Falls and Fragility Fracture Audit Programme) to NHS Digital;
2. NHS Digital will extract the HES and mortality data linked to the cohorts whose identifiers were supplied by Crown Informatics;
3. NHS Digital will create a separate HES extract of individuals who had hospital episodes with specific ICD10 and OPCS codes indicating a fall or fracture whose identifiers were not included in the cohort whose identifiers were supplied by Crown Informatics;
4. NHS Digital will disseminate both extracts to the University of Oxford as pseudonymised data. The linked extract will also contain the FFFAP ID supplied by Crown Informatics.
5. Crown Informatics will send pseudonymised data from National Hip Fracture database (NHFD) and FFFAP ID to NDORMS.
6. NDORMS will use the FFFAP ID to combine the FFFAP data and the linked HES and mortality data.

Civil Registration Mortality data is required to be able to explore variation in patient demographics which might explain differences in causes of death in the hip fracture population. Previous studies have reported that age, sex and fracture type are all predictors of mortality in other international hip fracture populations.

NDORMS require dates of death in order to be able to explore the trends in the data across the ten-year life of the NHFD. Without these dates they would not be able to explore secular trend in mortality, which has been marked in the wider UK population. It is clinically important to be able to understand if trends seen in mortality are those seen in the UK population generally or if there are specific challenges in the hip fracture population.

Validation of hip fracture diagnosis:

Linked HES data will allow NDORMS to assess the validity of hip fracture diagnosis and assess case ascertainment within the NHFD. Hip fracture patients can be identified in HES using search strings dependent upon International Classification of Diseases (ICD) or Office of Population Censuses and Surveys (OPCS) coding or both. Considering NHFD audit data as the gold standard, NDORMS will compare hip fracture events in NHFD to HES, searched using each candidate search string, by calculating sensitivity, specificity, positive and negative predictive values. Events in HES will not be counted if the event is present in both datasets but with more than a 60-day interval.

Ascertainment of outcome:

The linkage with Civil Registration Mortality data will provide information on cause and date of death. With ~65,000 hip fractures being entered the NHFD each year and an overall all-cause mortality rate of 6.7% at 30-days; the NHFD is the largest national dataset available to estimate such information. Major groupings of mortality, such as venous thromboembolism (VTE), stroke, infection that exist within the data will be assessed and all cause and cause specific mortality rates over time will be reported using survival analyses. Variation across the hospitals using mixed effects regression models will be reported and explored.

All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. No record level data falling under this agreement will be shared with any third-party.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract – i.e. employees, agents and contractors of the Data Recipient who may have access to that data.

An evaluation of knee arthroplasty fixation in an evolving challenging population — DARS-NIC-316443-V5Z4Y

Opt outs honoured: Yes - patient objections upheld, No - data flow is not identifiable, Yes, No (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-11 – 2022-11 2020.06 — 2020.06.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration - Deaths
  3. HES:Civil Registration (Deaths) bridge
  4. Patient Reported Outcome Measures (Linkable to HES)
  5. Civil Registration (Deaths) - Secondary Care Cut
  6. Civil Registrations of Death - Secondary Care Cut
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant, Identifiable

Objectives:

The University of Oxford requires HES admitted patient care dataset (HES APC), mortality and PROMS data for a cohort identified from the National Joint Registry (NJR) for the purpose of an evaluation of knee arthroplasty fixation in an evolving challenging population.

Background:
Over 100,000 primary knee replacements are performed annually in the United Kingdom for end stage knee osteoarthritis of which 95.1% use cemented fixation and 4.9% are cementless (4.9%). The number of knee replacements conducted is expected to increase six-fold by 2030 although this statistic has been questioned by academics. The complication rate following surgery is reported to be up to 11% with younger and obese patients having double the rates of implant failure. Furthermore, up to 20% of patients report clinically significant persistent pain and dissatisfaction with their knee replacements. Worryingly the number of revision procedures has increased by 95% in recent years and have worse outcomes than primary knee surgery despite costing over 10 times more. The commonest causes for revision include aseptic loosening, pain and infection.

Cemented knee replacement surgery is currently the gold standard and provides immediate fixation but has many associated problems including cement embolisms, late implant loosening and complex revision surgery. Furthermore, preliminary studies suggest that thermal necrosis of surrounding structures from cement polymerisation may be linked to acute and chronic pain.

Importantly patient demographics undergoing knee replacement surgery are changing with more obese or younger and active patients requiring surgery. These new demographics have created new challenges given cemented implants have higher failure rates in these groups with the under 65 age group expected to represent the majority of cases by 2030. Additionally, given the rise in life expectancy there is an increasing need for implants to provide a more physiological long-term fixation with current concerns that cemented implants will not last.

Cementless implants currently form under 5% of all primary knee replacements. However, cementless fixation may offer a solution and has many advantages including the elimination of bone cement interface for failure, no thermal necrosis from cement polymerisation and no third body wear from retained or fragmented cement. It is also well recognised that cementless knee replacement surgery has shorter operative times meaning reduced times under anaesthesia, reduced intraoperative blood loss and infection risk all of which reduce the chances of postoperative complications, potentially reducing morbidity and mortality.

There is currently no consensus on which fixation type is best overall and certainly not for population subgroups based on age or body mass index. The majority of studies, which compare outcomes for cemented and cementless knee replacement, have been limited by relatively small numbers of patients.

By analysing linked data from HES and the NJR plus linked fields from the mortality and PROMS datasets, the question of which fixation method is superior overall and for subsets of patients and implant types can be answered. An analysis which propensity matches for patient demographics and surgical caseload is needed to allow for an accurate comparison due to selection bias with younger, healthier fitter patients being more likely to receive cementless implants. Furthermore, this data will allow for comprehensive cost benefit analysis for all implant types to be conducted. These results will then help guide research to improve cementless fixation outcomes.

The study team will use routinely collected data to answer the questions outlined and not only help deliver more patient specific care and improve outcomes but guide surgical provision for healthcare providers and help patients make more informed decisions.

The study team's project is justified by article 6(1)(e) of the GDPR as this data linkage and processing is needed in the public interest to help decide whether cemented or cementless knee replacements are better from a clinical or cost effectiveness perspective, overall and then in different subgroups of the population. The study team's project is justified by article 9(2)(j) of the GDPR as it is in the public interest to know which knee replacements work best for patients to help improve health and social care. This will help develop better care in the NHS and perhaps the world. Only anonymised results will be published. The National Joint Registry and NHS Digital also have systems by which patients can dissent to their data being used. The study team will only be using data for those patients who have not dissented. The study team have full ethical approval and clinical advisory group approval for this project.

The legal basis for the flow of HQIP data from the NJR to NHS Digital is GDPR Articles 6(1)(e) and 9(2)(i) and the duty of confidence is met through support under section 251 of the NHS Act 2006.

Cohort identification:
The data subjects are all patients who have had cemented or cementless knee replacements and have been registered on the NJR between April 2003 to December 2018. All subjects will be over the age of 40 years at the time of their latest hospital episode.

The treatment group will be the patients who have received cementless knee replacements and the control group will be the patients who have received cemented knee replacements.

Data required:
For the cohort described above, data is needed from the HES Admitted Patient Care (APC), Civil Registrations Deaths and Patient Reported Outcome Measures (PROMs) data sets.

For the cohort, NHS Digital would provide a one-off report of linked HES APC, Mortality and PROMs data for the knee replacement cohort provided by NJR. This would provide information on revisions/reoperations, mortality, PROM scores, mortality, length of inpatient stay, costs of admission and patient demographics (comorbidities, BMI, age, gender).

To evaluate the performance of knee replacements the study team need data on the knee status (reoperation, revised, unrevised, death), time to event data, readmissions, length of hospital stay, medical complications, patient reported outcome measures. To allow a fair comparison of cemented and cementless replacements the study team need to match patients on implant factors (component size, knee implant design, year of implantation, bearing type), patient factors (gender, age, BMI), surgical factors (Primary diagnosis, ASA grade, thromboprophylaxis, surgeon’s grade and caseload, bearing type bone graft) and comorbidities (from both HES APC and PROMs datasets). For health economic analyses the study team require PROM scores, EQ-5D scores, HRG codes and OPCS codes for procedures undertaken.

To clarify some of the terminology above:
- The American Society of Anaesthesiologists (ASA) score is a subjective assessment of a patient’s overall health that is based on five classes.
- For information on the EQ-5D score, see: https://digital.nhs.uk/data-and-information/publications/statistical/patient-reported-outcome-measures-proms/patient-reported-outcome-measures-proms-in-england-2011-2012-special-topic-eq-5d-index-analysis.
- Healthcare Resource Groups (HRGs) are standard groupings of clinically similar treatments which use common levels of healthcare resource.
- OPCS codes are operating procedure codes.

The NJR dataset is needed for identifying the cohort and information pertaining to the knee replacement implanted.

Mortality data is needed to perform any survival analysis and is no longer provided by the National Joint Registry. The HRG and OPCS codes of subsequent episodes are essential for any health economic analyses and is only available through HES APC. PROMs data is needed to evaluate the pain and functional outcomes of patients.

The years of HES data requested begins 5 years prior (1997/98) to when the National Joint Registry started collecting data on knee replacements (2003) and finishes with the latest available data at point of production. The HES APC is needed for information on reoperations, mortality and revision. Additionally, HES APC data offers more details on patient demographics such as BMI, gender, Age and comorbidities. The HES-PROMs linked data will provide information on functional outcomes, health economic analyses, and the matching of comparable records to compare outcomes of cemented vs cementless knee replacements.

The NJR will send identifiable data to NHS Digital to allow the data linkage to take place - specifically the NHS number, Date of Birth, Surname, Postcode and Sex. The data (except sex) is not needed for the study team's analysis. CAG and REC have issued support for these items for the purposes of data linkage. The study team only require pseudonymised data to perform analyses.

Data minimisation reasoning:

The study team are only requesting HES data relevant to assessing the outcomes of primary knee replacements for patients over 40 at the time of their latest hospital episode and have limited the data requested to the cohort described. Data is not required for patients who were under 40 years of age when they had knee replacement surgery. However, because the date of surgery can not be determined via the OPCS codes, all patients who had surgery under the age of 40 can not be eliminated from the HES data. The amount of data will be reduced by excluding individuals who were under the age of 40 at the date of their most recent episode in hospital. These data will be removed and excluded entirely.

The study team are requesting data for the years ranging from 1997/98 to the latest available data in 2019/20. The study team will not receive episodes relating specifically to: maternity, alcohol, psychiatry, patient pathway and most geographical fields. The study team have only requested a one off dataset and the study team will not require further data on the data subjects in the future for the purpose of this study.

The University of Oxford had initially tried to limit the data requested to 5 years prior to the date of surgery and by providing a list of OPCS codes to NHS Digital. However, this has created two significant issues.
1) There are known issues with the way knee replacements are coded. Around a quarter of the knee replacements recorded in the NJR data would not be identified if the data extract was limited to only include specific OPCS codes.
Additionally, there is a study published by Middleton et al (2018) which has shown a significant problem with the coding of knee replacement procedures. Therefore, all hospital records (excluding maternity, fetal, alcohol and psychiatry episodes) are needed to prevent this problem.
2) The full set of HES records are needed (excluding maternity, fetal, alcohol and psychiatry episodes) to accurately profile the patients' past medical history. For example, a patient can present for knee trauma/arthroscopy/meniscal injury 10 years before they have a knee replacement and this needs to be factored into the analysis. As these factors affect the underlying indication of knee replacement surgery, limiting this information can mislead the analysis by mixing different surgical indications and lead to erroneous results.

The study team require all pre and post-operative HES episodes (excluding maternity, fetal, alcohol and psychiatry fields) to monitor the knee replacement outcomes over time. Outcomes include revisions, reoperations, medical complications and mortality.

Regarding PROMs data, the study team have only requested the Oxford Knee Score and EQ-5D scores which are needed to assess the outcomes of cemented and cementless knee replacements. This is important to assess the functional outcomes and to perform health economic analyses. The study team have also requested access to PROMs comorbidity data, this is needed for matching of cementless and cemented records in a fair way - i.e. matching records with similar comorbidities. This is assessed by a comorbidity index score and the PROMs comorbidity data will also help assess the quality of reported comorbidities in the HES APC data. PROMs data for the data requested has only been collected from 2009/10 hence the time period in the data requested.

The study team require mortality data to be able to compare mortality between cemented and cementless knee replacements. Dates of deaths are essential for any implant survival analysis.

Deprivation indices are needed for propensity matching comparative groups as this can influence patient outcomes. HRG codes and length of stay are essential for health economic comparisons of cemented and cementless knee replacements.

The study team require data from across England so that the study is adequately powered to compared cemented and cementless knee replacements overall and then to allow appropriate subgroup analyses in different strata of the population (i.e. different age groups etc). Including all regions in England will help by having a mixture of patients with different demographics to allow subgroup analyses. Only data which is needed to assess the objectives outlined above has been requested.

The study team have considered possible methodologies and determined there is no viable alternative method for answering this question. To run a clinical trial is impractical as one would need approximately 10 years follow up and would require an unmanageable sample size to have the same impact as this proposed project. The data available from NHS Digital is not available from the NJR. There are no less intrusive methods of performing the study analysis.

Noting that NHS Digital has previously supplied HES data linked with NJR data for other studies related to knee replacements under separate Data Sharing Agreements, the University of Oxford has considered and ruled out the approach of reusing that data for this study. A new dataset is needed given the applicant needs information on the most recent knee replacements given implant designs are constantly improving in a dynamic implant market. Also, by obtaining information on the newer cementless designs, this will allow comparison to older designs. This project is substantially different to any other NJR-HES linked data projects.

The study team require and have applied for approval for NJR data to release for this specific research purpose. Confirmation of NJR approval will be required prior to the release of this data.

References
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[1] Middleton R, Wilson HA, Alvand A, Abram SG, Bottomley N, Jackson W, Price A. Outcome-based commissioning of knee arthroplasty in the NHS: system error in a national monitoring programme and the unintended consequences on achieving the Best Practice Tariff. Bone Joint J. 2018 Dec;100(12):1572-8.


Data analysis plan:
Data only on primary knee replacements will be sought from 1997/98 to the latest available HES data with data only requested necessary to evaluate knee replacement outcomes. Linked data from Northgate Public services and NHS Digital, will be stored in a secure room in a CCTV monitored, card protected university research building. All analysis will be conducted on a fully encrypted computer. This will ensure that the data will be kept safe and secure.

The study team will propensity match replacement groups based on various factors including gender, age, BMI, primary diagnosis, ASA grade, thromboprophylaxis, surgeon’s grade and caseload, implant component size, bearing type and the use of bone graft.

Using the combined NJR/HES/PROMs/mortality dataset the study team will;
I. Calculate the implant and patient survival of the cemented and cementless implants respectively using Kaplan Meier analysis and compare groups using the log rank test to see which has a superior long-term survival. This comparison requires comorbidity analysis.
II. Analyse mechanisms of implant failure by reporting the incidence of mechanisms of failure.
III. Compare patients early, midterm and long-term PROMs from the cemented and cementless groups. This comparison requires comorbidity analysis.
IV. Determine the incidence of serious medical complications following surgery including thromboembolism (pulmonary embolism or deep vein thrombosis), blood loss and transfusions, myocardial infraction, stroke and mortality. The study team will compare these rates between groups using multivariate analyses.
V. Conduct subgroup analysis on different patient subgroups and implant types.
VI. Conduct cost effective analysis for the propensity matched cemented and cementless groups using a lifetime Markov model.

Data Controller statement:
The University of Oxford is the sole data controller and processor, given the University of Oxford are solely determining, through the study team, the way the data is being processed. Northgate Public Services are providing the NJR dataset and identifiers for the cohort only, but not taking further part in the research. The University of Oxford is the data controller responsible for determining the purpose for all data flows described and will be the data controller for the data received.

Linkage process:
Northgate Public Services will send the study team de-identified data on all patients who have had a knee replacement from April 2003-December 2018 with an NJR ID number (which is not patient identifiable) on an encrypted device. They will simultaneously send their identifiable patient data (NHS Number, Date of Birth, Surname, Sex, Postcode) to NHS Digital and ask them to link the HES dataset (inpatient data, patient reported outcome measures and mortality data) to the NJR dataset and then remove any patient identifiers prior to sending anything to the study team. NHS Digital will then only send the study team de-identified data which would include the NJR ID and linked HES inpatient data. The study team will then be able to merge the datasets obtained from NHS Digital to the previously received dataset from Northgate Public Services using the NJR IDs (which are de-identified). The linked dataset will then be analysed by the study team in the University of Oxford.

Funding:
The Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at the University of Oxford is the sole data controller and will receive, process and analyse the data and subsequently publish the findings. The NJR is part of the national audit programme of the Healthcare Quality Improvement Partnership (HQIP) and is managed by Northgate Public Services Ltd – which will provide the cohort of identifiers to NHS Digital for the data request.

The project has been instigated and is being undertaken by a substantive employee of the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at the University of Oxford. This individual has an employment contract with the University of Oxford and is a Royal College of Surgeons (RCS)/NJR Fellow which allows the individual to undertake work in their home institution, but their salary funding is provided by the RCS. Therefore, RCS is providing funding for the person who will undertake the work but is not providing funding specifically for the purpose of this work and has not determined that it should be undertaken. The purpose of the investigation has been determined solely and entirely by employees of the University of Oxford. Objectives of the work are focused on informing knowledge in the field of knee replacement care delivery within the NHS to meet recognised needs. The purpose of the work has received external review by the NJR Research Sub-Committee as part of the approvals process to undertake the work, as it includes the use of NJR data. Such review ensures that the proposed work falls within the NJRs thematic areas of interest.

Assessment of how the data will be processed to meet the proposed purpose has been undertaken by the senior team members (University of Oxford employees), who have extensive experience in the field.

Expected Benefits:

This is the first study aiming to compare the outcomes of cemented and cementless knee replacements. This has never been done before using registry data for all knee replacements and is much needed given no one knows how they compare in different subgroups of the population. The results from this study may help to change practice throughout the United Kingdom to help develop more clinically and cost effective patient specific care.

This research study will help guide which fixation method is superior clinically and from a cost effectiveness perspective both overall and in different subgroups of the population. This will help to provide more patient specific care which should help improve clinical outcomes and reduce expensive revision surgery. By comparing all the available implant designs and population subgroups patients will have increased awareness of options being offered allowing for more informed consent for surgery. The study team will aim to achieve all the above by October 2021.

The results from this work will most likely help to develop NICE guidelines on whether patients should have cemented or cementless knee replacements for different patient demographics. This will help to develop guidelines promoting more patient specific care for patients. This could not only change practice in the United Kingdom but could have worldwide effects on Orthopaedic practice.

The study team will look to achieve benefits through the strategy mentioned throughout the output section.

Although it is difficult to know exactly how much money this project will save the NHS, preliminary data on Unicompartmental Knee Replacements from a separate project of has suggested a 20% reduction in revision rate in cementless replacements.

Given the price of a revision total knee replacement (TKR) ranges between £10,000 to £30,000. A primary TKR costs approximately £6000). 5070 revisions were performed in 2017. Therefore, a reduction of 20% would equate to 1,014 less knee replacement revisions. This could equate to a saving of at least £10,000,000 per year.

Outputs:

The results from this research will be disseminated both to the Academic world and to patients. Each will be discussed in turn.


Academic world dissemination
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The results from this study will be submitted to prominent peer reviewed journals and conferences.
Journals which the study team plan to submit the findings to will include; The Lancet, The BMJ, Journal of Bone and Joint Surgery. Conferences the study team will submit this work to will include the American Academy of Orthopaedic Surgeons, the EFORT congress meeting and the British Orthopaedic Association meeting. The results will also be put on the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences website.

To maximise the impact of the study research the study team will monitor for conferences with themes on using big data to help change clinical practice. The study team will always try to select high impact journals first with wide authorship. Additionally, the study team have a twitter account to help share the publication to enhance the altmetric score for published articles.

The results will not identify individuals and contain only data in aggregate form (tabulations and figures showing analysis results at the minimum level of detail required) in line with the HES Analysis Guide relating to the data being shared under this Agreement. In the year following receipt of the data the following reports, analyses and presentations are planned:

Specific data Analyses and papers include:

1. A comparison of the clinical outcomes of cemented and cementless knee replacements. This will also involve comparing total and unicompartmental knee replacements (Target date for completion June 2020).

2. An analysis of the mechanisms of failure of cemented and cementless knee replacements (Target date for completion October 2020).

3. A comparison of early and late cementless knee replacements (Target date for completion January 2021).

4. A cost effectiveness comparison of cemented and cementless knee replacements (Target date for completion October 2021).



Dissemination of results to patients
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The study team have already established a patient focus group in Oxford who helped the research team devise their research protocol. The focus group felt that studies comparing fixation were essential and important to patients and they helped the study team determine the outcome measures relevant to patients. This patient focus group will meet on a six monthly basis to discuss the results of the work and offer ideas to help direct the research. Additionally, they will offer suggestions on how best to disseminate the results of the study to other patients.

The study team also intend to run a research open day in the Nuffield Orthopaedic Centre in which members of the public can come to ask questions about the study teams current research and our future directions.

Finally, the study team have a twitter account @OOEC which will be used to tweet summaries of the results. This will be accessible to all twitter members including patients and the general public. They will also be able to message the twitter account for any questions they have regarding the research. The study team have a designated individual who regularly checks the account and currently has 10.2K followers.


Processing:

The National Joint Registry for England, Wales, Northern Ireland and the Isle of Man (NJR) which was established in April 2003 collects information on all knee replacement operations and is now the world’s largest replacement register with over two million joint procedures recorded.

Northgate Public Services will send the study team pseudonymised data on all patients who have had a knee replacement from April 2003-December 2018 with an NJR ID (which is not patient identifying) on an encrypted device.

Northgate Public Services will separately send their identifying patient data (NHS No, Date of Birth, Surname, Sex Postcode) to NHS Digital to be linked with the HES dataset and subsequently with Patient Reported Outcomes Measures (PROMS) and Civil Registration Mortality data.

NHS Digital will then only send the study team pseudonymised linked data which would include the NJR ID and linked HES APC, PROMs and mortality data. The study team will then be able to link the datasets obtained from NHS Digital to the dataset received from Northgate Public Services using the NJR IDs (which are pseudonymised).

The study team will implement the data analysis plan after the data linkage.

Data will be stored on a secure server in the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science which can only be accessed on location. Access to the pseudonymised data will be restricted to the named individuals within the research group who have authorisation from the Principal Investigators to access the data for the purposes described, all of whom are substantive employees or students of the University of Oxford. The study team will link the NJR dataset and HES dataset using the NJR IDs. The University of Oxford will not link the data further and the only data linkages are those described in this Agreement.

Data processing will only be performed by substantive employees of the data controller who have been appropriately trained in data protection and confidentiality. Data can only be accessed in a secure room for which access is limited to those with permission to analyse the data. Additionally, anyone accessing the secure room will need to have completed the mandatory information governance modules.

This Data Sharing Agreement does not permit data to be made available to any third parties except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide, unless a third party has received separate approval from NHS Digital to receive the data covered by this Agreement.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purpose of that use) by 'Personnel' (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Receipt who may have access to the data).

Associations between frailty, implant and outcomes after primary knee replacement — DARS-NIC-238613-D3W0L

Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld, No, Yes (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-02 – 2022-01 2019.07 — 2020.05.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Patient Reported Outcome Measures (Linkable to HES)
  2. Civil Registration - Deaths
  3. HES:Civil Registration (Deaths) bridge
  4. Hospital Episode Statistics Admitted Patient Care
  5. Civil Registration (Deaths) - Secondary Care Cut
  6. Civil Registrations of Death - Secondary Care Cut
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires Hospital Episode Statistics (HES), Patient Reported Outcome Measures (PROMs) and Civil Registration (mortality) data for the purpose of an investigation to determine associations between surgical and patient factors on outcome following primary knee replacement, the proposed work would be undertaken by individuals from the Big Health Data Group, of the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, at the University of Oxford. The work requires the HES, PROMS and mortality data controlled by NHS Digital to be linked to National Joint Registry (NJR) data - for which HQIP is the data controller - and would be supplied by HQIP’s data processor, Northgate Information Solutions. All data accessible to the team at the University of Oxford will be pseudonymised. Northgate Information Solutions will have no access to NHS Digital data under this Agreement.

The work will investigate factors relevant in the delivery of knee arthroplasty care and consists of two work packages:
- Package 1 addresses surgical factors (implant choice and surgical strategy) important in knee arthroplasty outcomes.
- Package 2 will investigate the role of patient frailty in knee arthroplasty outcomes.

The outcomes of interest are similar for both work packages (patient reported outcome measures, quality of life measures, mortality, revisions, re-operations and health care resources usage), and would be addressable using the same data request.

This data will be used for work in the public interest and will add to the existing knowledge base for knee arthroplasty, to better inform patients, clinicians and commissioners.

Knee replacement is one of the most common surgical procedures in the UK, with more than 800,000 performed over the last 9 years. Whilst the majority of patients experience improvements in pain, function and quality of life, there remain a group (estimated at 10-25%) who are dissatisfied after their knee replacement. It is important to better understand which patients are likely to benefit, those who may not experience a positive outcome, and potential avenues to improve success after primary knee replacement. This knowledge would feed into the shared decision pathway to surgery, in which the potential benefit and risk of the procedure are core components.

The importance of ongoing investigation in the field is recognised. There is public interest from patients undergoing knee arthroplasty to greater understand the value of the surgical procedure. This interest has been formalised. For example, the James Lind Alliance Priority Setting Partnership - which is made up of patients, carers and clinicians - identified areas of ongoing interest for knee replacement. These include identifying factors to improve post-operative outcomes, deciding what implants result in optimum outcomes and determining which patients are more likely to do well after knee replacement. The National Joint Registry is currently responsible for monitoring knee replacements, and commonly collaborates with external groups to investigate outcomes of arthroplasty and relies on GDPR Article 6(1)(e) as the lawful basis to do this.

Knee replacement involves the implantation of artificial materials into the knee to replaced damaged surfaces, with the aim of reducing pain and improving function. This proposal concerns the investigation of medical devices. Given the number of these devices used, and the demand for this surgery, it is important to understand the impact of such procedures as part of care delivery.


The work described in this Agreement would add to the knowledge base around primary knee replacement. This will differ from existing pieces of work in two ways:

Firstly, the use of patient frailty as the independent variable in the assessment of outcome after knee replacement is novel. Existing pieces of work that explore the influence of patient health on outcome have done so using specific co-morbidities or co-morbidity indices (for example the Charlson Co-morbidity Index and the American Society of Anaesthesiologists grading). Frailty is a more recently developed concept, and considers patient health status in a more holistic way (through the consideration of additional facets of health such as psychological and social needs). Systems to assess patient frailty have been developed, and been shown to be valuable predictors in determining mortality and post-operative complications in existing studies. The value of frailty as an assessment tool has also been recognised by NHS England, and its assessment in primary care is now mandatory, to identify opportunities to intervene and optimise patient care. Assessment of how frailty influences outcome after knee replacement has not yet been done in the UK using these national datasets.

Secondly, existing pieces of work in the field of joint arthroplasty often report only a particular type of outcome (for example revision rate, patient reported outcome measures or complication rates). Such an approach can make interpretation of outcomes after surgery difficult, in that ‘success’ of surgery depends on the outcome being used, and the criteria for success. In addition, the reporting of isolated outcomes from different cohorts makes subsequent comparisons more difficult. A major strength of this work (made possible by the linkage of a data held by the National Joint Registry and NHS Digital), is that for each aspect of knee replacement care being assessed, different categories of outcome (implant survival, patient reported outcome, medical/surgical complications) will be reported. Reporting multi-modal outcome in this way will give a more comprehensive assessment of primary knee replacement surgery than has been available to date.

The Clinical Trials and Research Governance Department of the University of Oxford have reviewed and approved both work packages. Section 251 approval has been granted for the flow of identifying data from the NJR to NHSD for the purposes of data linkage. Both work packages have been reviewed by the NJR/HQIP and approved. No patient identifying information will be accessible to the study team at the University of Oxford, with the data being received from NHS Digital being pseudonymised prior to release.

The data subjects are individuals who have undergone primary knee replacement, as recorded in the NJR, since 2003. To determine the outcomes of these individuals requires the combined dataset comprised of data from the NJR, HES Admitted Patient Care (APC), mortality and PROMS. The NJR dataset contains detailed information pertaining to the surgical care of the individual at the time of surgery (anaesthetic grade and body mass index of patient, seniority of operating surgeon, implant details, use of cement), as well as recorded instances of revision (where the knee prosthesis has components added, removed or exchanged) and the indication for this. The use of HES APC and mortality register data is required to characterise patient groups, and to identify instances of health care input not captured by the NJR (for example re-operations to the knee, complications such as stroke, myocardial infarction or venous thromboembolism, and to capture out of hospital deaths not recorded in HES). The PROMs dataset provides critical information on the outcome of surgery from the patient perspective (using validated joint specific outcome questionnaires and quality of life questionnaires).

The data request is for records pertaining to patients identified by the NJR from 2003 onwards. Such data is required to investigate the outcomes of interest (see work package descriptions), which can only be captured by long term follow-up. NJR and HES data fields will also be required to control for confounding variables such as age, gender, deprivation and ethnicity when determining associations between treatment and outcomes. There are no practicable alternatives to this data request, given the number of records involved and retrospective nature of the work. With regards to data minimization, Northgate Information Solutions will provide to NHS Digital a restricted list of identifying details for the eligible patients from the NJR dataset, for subsequent linkage to the NHS Digital controlled datasets. As such no patients beyond those receiving primary knee replacement as recorded in the NJR will be included. Further to this, the data fields requested from each data set are limited to those required for analysis (to characterise patient groups, to control for confounding variables, to determine outcomes).

The Big Health Data Group at University of Oxford is the sole data controller and will receive, process and analyse the data and subsequently publish the findings. The NJR is part of the national audit programme of the Healthcare Quality Improvement Partnership (HQIP) and is managed by Northgate Information Solutions – HQIP’s data processor for this purpose - which will provide a list of all knee replacement as recorded in the NJR since 2003.

The project has been instigated and is being undertaken by a substantive employee of the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at the University of Oxford. This individual has an employment contract with the University of Oxford and is a Royal College of Surgeons (RCS)/NJR Fellow which allows him to undertake work in his home institution but his salary funding is provided by the RCS. Therefore, RCS is providing funding for the person who will undertake the work but is not providing funding specifically for the purpose of this work and has not determined that it should be undertaken. The purpose of the investigation has been determined solely and entirely by employees of the University of Oxford. Objectives of the work are focused on informing knowledge in the field of knee replacement care delivery within the NHS to meet recognised needs. The purpose of the work has received external review by the NJR Sub-Committee as part of the approvals process to undertake the work, as it includes the use of NJR data. Such review ensures that the proposed work falls within the NJRs thematic areas of interest.

Assessment of how the data will be processed to meet the proposed purpose has been undertaken by the senior team members (University of Oxford employees), who have extensive experience in the field.


Work Package 1:

Work package 1 aims to inform on surgical factors and implant factors that may affect patient outcomes following primary knee replacement (these represent points 3, 4 and 17 identified by the James Lind Alliance Priority Setting Partnership as important questions for patients needing knee replacement for osteoarthritis). CAG support under 18/CAG/0144 has been obtained for this work package.

The surgical factor of interest in work package 1 is the choice of surgical strategy, with regards to how much of the knee to replace, if disease is isolated to one area. One strategy is to perform total knee replacement (TKR) for all patients, the other is to perform unicompartmental knee replacement (UKR) where possible. UKR has been shown to provide faster recovery, higher patient reported outcomes, lower complication rates and greater economic benefit, but higher revision rates, when compared to TKR (an evidence base made up from randomised controlled trials, large registries and multiple cohort studies). In clinical practice patients referred for orthopaedic treatment will demonstrate varying patterns of knee arthritis, but it is estimated that 25-45% of patients would be appropriate for unicompartmental knee replacement. Despite this the NJR recorded level of UKR use has remained at 7-10%, suggesting underutilisation, with concerns around high revision rates likely a driver. Prior work has compared the outcomes of TKR to UKR, or the outcomes of UKR between high- and low-volume centre. This work will investigate whether UKR or TKR based surgical strategies provide benefits to the patient group as a whole, and better reflect practice in the NHS. Case-mix adjustments will be performed prior to determining associations between surgical strategy and outcomes of interest.

The second component of work package 1 is an investigation of the influence of knee replacement design on outcomes after primary total knee replacement. The 2018 NJR Report lists 67 different knee replacement systems as used in primary knee replacement during 2017, comprised of multiple systems across different manufacturers. Knee replacement systems demonstrate particular design philosophies (e.g. cruciate retaining, posterior stabilised, medial pivot etc.), aimed at improving outcomes. However, it is unclear to date what difference such changes make. To this end this component of the work would assess outcomes between 4 over-arching design principles in knee replacement (medial-pivot, gender specific, high-flexion and cementation choices in primary knee replacement), following case-mix adjustment.

Outcomes of interest for both components of work package 1 are change in Oxford Knee Score (a validated joint specific patient reported outcome measure) at 6-months, satisfaction after primary total knee replacement at 6 months, revision rates at 5 and 9 years, adverse events and mortality at 90-days and 1-year. Regression analysis techniques will be used to determine associations between implant type and the outcomes of interest.


Work package 2:

Work package 2 focuses on the influence of the patient on their outcome following primary knee replacement. The majority of patients receiving primary knee replacement are over the age of 60, with some degree of co-morbidity. It is appreciated that some health conditions are associated with less positive outcomes following joint replacement. Prior work has investigated the role of specific co-morbidities or used grading systems (such as the American Society of Anaesthesiologists grade - ASA) or co-morbidity indices (such as the Charlson Co-morbidity Index). However, such methods do not consider the patient in holistic manner. The concept of frailty has been developed to provide a more global assessment of patient health, and considers not only physical disease, but also psychological and social aspects relevant to patient care. Frailty measures have been found to be predictive of mortality, hospitalisation and nursing home measures. Further, when used in the hospital setting, frailty has been shown to be as good as, or better than, grading systems such as ASA in predicting mortality or poor outcomes after surgery. The value of frailty as an assessment tool has been recognised by NHS England, with assessment now routinely performed in primary care to identify vulnerable individuals. Given the high level of demand for knee replacement, and an aging population with complex health care needs, improved understanding of the interactions between frailty and outcomes after knee replacement is of value in the shared decision-making process. Such knowledge is recognised to be of value by the James Lind Alliance Patient Priority Setting Partnership (points 3 and 11 for hip and knee replacement).

Work package 2 will investigate associations between patient frailty and post-operative outcomes after primary knee replacement. Frailty will be determined using a validated frailty index, using International Classification of Diseases codes contained with HES records. Associations with outcomes after knee replacement will then be determined, after case-mix adjustment, between patients classified as being fit, mildly frail, moderately frail or severely frail. CAG support under 18/CAG/0143 has been obtained for this work package.

Outcomes of interest are change in quality of life (as measured by the EQ-5D utility index) at 6 months, change in Oxford Knee Score at 6 months, revision rates at 5 and 9 years, adverse events and mortality at 90-days and 1-year. Regression analysis techniques will be used to determine associations between implant type and the outcomes of interest. A health economics analysis will be performed to determine how frailty affects the cost of care delivery for primary knee replacement. If frailty is found to be a more predictive measure of outcome than existing measures, it would represent a valuable addition to the decision-making process for knee replacement surgery. As frailty is now routinely assessed in primary care, such information could be included in referrals for specialty care. For this purpose, information on all HES episodes for eligible patients is required.

Expected Benefits:

The need for further understanding of factors influencing outcome following knee replacement is well recognised, and is highlighted in the James Lind Alliance Patient Priority Setting Partnership for Hip and Knee Osteoarthritis.

Specifically the planned work would address the areas of need concerning modifiable factors pre-, peri- and post-operatively that can influence outcome; identifying pre-operative predictors of success; identifying characteristics of individuals who benefit from knee replacement and those who do not and what is the best implant/prosthesis for best/safest outcomes.

If frailty is identified as a more specific predictor of outcome than current measures, it would demonstrate additional value to the now required assessment of frailty in primary care. Such information could then be included in referral pathways, and to improve the shared decision-making process for knee replacement.

Greater clarity as to the role of implant type would inform surgeons when it comes to selecting the implant for use, and to the NHS as a purchaser of implants. Similarly, an improved understanding of surgical strategy on both patient-oriented outcomes (quality of life, risks and complications) and health economics have the potential to support a wider change of practice in the NHS.

Outputs:

Data processing will result in a number of outputs, as detailed below. It is not expected that any outputs will result in small numbers (defined as ≤5), given the size of the population. However, if this is found to occur for any output, HES analysis guidance will be followed, with suppression of such numbers (as detailed in 6.1 of HES analysis guide).

Dissemination of results/outputs:

The work will inform on key areas directly relevant to patient care in knee arthroplasty. The assessment of patient frailty is already recognised as important in primary care. As the majority of patients receiving knee replacement are over 60, with varying levels of co-morbidity, understanding the influence of frailty on outcomes after surgery would be immediately informative in the shared decision making process. The advantages and disadvantages of unicompartmental and total knee replacement have been discussed previously, this work is novel in that it will determine the outcomes for patient populations treated at centres with differing strategies for knee replacement. This has the potential to directly influence surgical decision-making and delivery of surgical care. Finally, the consideration of different knee replacement designs will expand on the annual NJR report, by reporting a wider range of outcomes. Such findings will inform on the performance of knee replacements in current use.

Reports of findings will be submitted for publication in relevant academic journals, for dissemination to clinicians and researchers. It is anticipated that there will be three major publications from the submitted data (addressing frailty, reconstructive strategy and implant design in primary knee replacement respectively). These publications would be submitted for publication within 18 months of data receipt, and publication within 24 months.

Findings will also be disseminated via presentation at orthopaedic conferences (for example those held by the British Association for Surgery of the Knee and British Orthopaedic Association) and may be in the form of oral or poster presentation. Such conferences represent an important method of disseminating new findings to clinicians and researchers. Such findings can be presented in advance of formal publication in academic journals, again with a target of submission to relevant meetings within 18 months of data receipt.

In addition to the above, a formal report of the work will be submitted to the National Joint Registry and Royal College of Surgeons of England, as part of the standard arrangements which allow an RCS/NJR Fellow to support the work. Neither the RCS nor Northgate Information Solutions will have access to the data, nor a role in the analysis or interpretation. These reports can then subsequently be published on either the NJR or RCS websites, and included in annual reports (for example the RCS annual report of Fellows activities) made available on their public facing websites. These reports will be submitted at the end of 2019.


Communication of results/outputs:

Both the National Joint Registry and Royal College of Surgeons are key bodies in the communication of new results relevant to health care delivery in England (this includes both clinicians, healthcare managers and policy makers). As mentioned above, reports of the work will be submitted to both the NJR and RCS at the end of the first year after data receipt.

As the work will inform knowledge in areas identified as important to patients (as detailed in the James Lind Alliance Patient Priority Setting Partnership for Hip & Knee Osteoarthritis), the findings of the work will be discussed with the NJR, for consideration of patient review through the NJR patient network.

In addition to the above, results of the work will be added to the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS) web pages for the project (to be created as part of the CAG approval requirements). In addition, NDORMS manage the institutional social media platform, on which recent findings by groups are announced.

Processing:

The proposed work consists of 3 data flows

1. On behalf of HQIP, Northgate Information Solutions will transfer to NHS Digital the NHS number, date of birth, gender and postcode, paired with a unique identifier for each eligible patient from the NJR, for the purpose of linkage to NHS Digital held data sets;
2. Northgate Information Solutions will transfer to the Big Health Data Group (BHDG) pseudonymised records of eligible individuals;
3. NHS Digital would will transfer to the BHDG the linked HES,/ PROMs and mortality record level data, with the accompanying unique NJR identifier received in step 1. Above.

On receipt of the NJR/HQIP and NHS Digital data sets, the BHDG would will be responsible for linking the two data sources, using the NJR unique identifier. The resulting pseudonymised record level dataset would be used in the proposed investigations. There will be no attempt to re-identify individuals from the dataset, and results will be presented at aggregate level with small numbers suppressed in line with the HES Analysis Guide . Within the BHDG, data would be stored in a secure environment (data will be stored on an encrypted password protected drive and kept within a data safe).

Learning From Patients (2): Developing a National Resource for Hip Fracture Research — DARS-NIC-149784-H9K6B

Opt outs honoured: N, Y, No - data flow is not identifiable, No, Yes (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2018-04 – 2020-12 2018.06 — 2020.05.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The National Hip Fracture Database (NHFD) is a clinically led, web-based audit of hip fracture care that grew out of collaboration between the British Orthopaedic Association and the British Geriatrics Society and is now managed by the Royal College of Physicians (RCP) and commissioned by Healthcare Quality Improvement Partnership (HQIP).

The NHFD currently provides statistics on hospital performance outcomes but does not capture all variables to account for patient case mix, for example any patient who has a pre-existing health condition such as diabetes or heart attack.

The University of Oxford requires access to pseudonymised record level HES data linked with NHFD data plus vital status indicators for the purpose of a project which aims to:
1. Develop an improved risk adjustment model for the NHFD using data linkage and prospective collection of additional variables.
2. Use the new risk adjustment model to compare hip fracture patient outcomes between the UK, US, and Australia to identify opportunities for improving care.
3. Demonstrate the feasibility of using the enriched NHFD dataset to answer specific health policy questions that could inform future research priorities and health service planning.

This is a standalone PhD study undertaken by a researcher who holds a UCB-Oxford Prize Fellowship in Biomedical Research and is employed by University of Oxford and supported by a researcher from Yale University. UCB is a global biopharmaceutical company. The study aims to improve the case mix adjustment model to collect co-morbidities and enrich the data held in the NHFD. No data will be shared with UCB.

There are 70,000 hip fractures every year in the United Kingdom at a total cost exceeding £2 billion. Mortality is high, with 8.5% of patients dying within 30 days of admission. The NHFD captures data from 95% of hip fractures treated in England, Wales, and Northern Ireland; and is the largest comparable registry in the world. The NHFD exists primarily to drive quality improvement and has been used infrequently for research.

The NHFD reports NHS hospital outcomes (e.g. mortality) that are adjusted for differences in patient case mix using statistical techniques, such as multivariable regression. This is important because some hospitals might treat patients that are - for example - older and sicker than other hospitals. If statistical techniques are not used to "adjust" outcomes, then a hospital with older patients might appear to be worse than one with a younger population, even though it is actually providing better care. However, these models have been developed based on limited fields available within the dataset, such as age and pre-morbid mobility. It is possible that additional variables could have greater predictive value for outcomes reported by the NHFD. The majority of hip fractures occur in older adults and so it is likely that co-morbid diseases affect patient outcomes. Although the NHFD includes American Society of Anaesthesiologists (ASA) score (which is a measure of overall "sickness" on a scale from 1-5), other validated co-morbidity measures (such as the Charlson and Elixhauser indices, which convert each patient's diagnoses into a single numeric score) cannot be calculated because the NHFD does not record individual comorbidity diagnoses. Inadequate risk adjustment could result in failure to identify poorly performing hospitals and/or unfair attribution of poor outcomes to hospitals with unfavourable case mixes.

One of the three components of this project is to investigate the effect of the Best Practice Tariff (BPT) on hip fracture outcomes. The BPT is an initiative that was launched in April 2010 and provides additional payments to hospitals that meet defined quality criteria when treating patients with hip fractures, such as providing assessment by a senior orthogeriatrician and an operation within 36 hours. The National Hip Fracture Database (NHFD) was already in existence when the BPT was introduced and was chosen as the vehicle for determining which cases should attract the additional payment. One consequence was that this financial incentive dramatically increased the proportion of cases captured by the NHFD once the BPT was introduced. This creates an obvious problem for using the NHFD to evaluate the BPT as any change in outcomes might simply reflect differences in the cases being reported by individual hospitals. A solution is to use an external dataset (such as HES APC) that was capturing cases before and after the BPT was introduced and that is independent of the NHFD. The University of Oxford intend to use this dataset to undertake an interrupted time series “natural experiment” to look for any changes in outcome that came about after the BPT was introduced.

The aim of processing these data is to improve the NHFD risk adjustment model and develop this comprehensive national registry into a valuable resource for hip fracture research.

Expected Benefits:

The two changes likely to occur as a result of this project are:

(1) Revision of the existing risk adjustment model within the NHFD and;
(2) Refinement of the variables collected by the NHFD for case mix adjustment.

These changes will bring a number of benefits for patients and commissioning organisations. In particular, it will improve the ability of the NHFD to fulfil a key audit role, which is to identify hospitals with worse-than-expected and better-than-expected hip fracture outcomes. Suboptimal risk adjustment may lead to hospitals with worse case mix being inappropriately highlighted as providing poor care and - conversely - failure to identify some hospitals that provide sub-standard care but that benefit from treating "fitter" patients. This will help drive quality of care for older adults with hip fractures. It will also open up the NHFD as a tool for hip fracture researchers studying factors associated with hip fracture outcomes. The project will achieve this final outcome in a number of ways, i.e. by (1) showcasing the value of the NHFD to the clinical research community, (2) describing the degree to which the variables in the existing NHFD can predict mortality, i.e. so increasing researcher confidence in their ability to risk adjust hip fracture outcomes.

The risk adjustment model in the existing NHFD could be improved in time for the next annual report in 2018. If optimal risk adjustment requires the collection of new variables, this could take place from 2019.

Outputs:

This project will principally be reported in a doctoral thesis by the researcher (DPhil in Musculoskeletal Sciences) and this is intended for submission to the University of Oxford in late 2018. The findings from objective 1 (improving the NHFD risk adjustment model) will be communicated directly to the Healthcare Quality Improvement Partnership (HQIP) which commissions the Royal College of Physicians to manage the National Hip Fracture Database (NHFD). This is anticipated to occur in the latter half of 2018 and in time for a revised case mix adjustment algorithm to be incorporated into the NHFD 2018 annual report. If additional variables are required for collection in future iterations of the NHFD, this could happen as early as 2019.

The case mix adjustment data will be presented in a research methods paper that is likely to appear in an open access journal. This will provide a reference point for other research papers using the NHFD and needing to justify their statistical approach to risk adjustment. This will be submitted for publication in advance of the doctoral thesis submission in 2018.

The other papers (e.g. international benchmarking and health service research projects) will be submitted for publication in peer-reviewed journals that will depend on the study findings. The target journals are usually the Bone & Joint Journal (for findings that are applicable to orthopaedic surgeons) and the British Medical Journal (in the case of findings that are of interest to a broad clinical audience). These are intended for submission in early 2019. The University anticipate presenting all available results for each project at the British Orthopaedic Association Annual Congress 2019.

All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

This study will mainly focus on a cohort of patients originally identified from the National Hip Fracture Database (NHFD), all of whom are aged >60 and have been treated for a hip fracture at a hospital in England. The University of Oxford has previously received an extract of HES data linked to this cohort under a separate Data Sharing Agreement (ref DARS-NIC-61090-T9Y0G) for the purpose of an unrelated study. The University of Oxford will take a copy of some of that data to reuse it for this purpose. The detailed process to do this is as follows:

1. From the dataset that the University of Oxford is authorised to hold and process under the Data Sharing Agreement DARS-NIC-61090-T9Y0G, the encrypted HESIDs will be extracted and supplied to NHS Digital along with the date of the hip fracture for each individual patient.
2. NHS Digital will decrypt those IDs to identify the individuals and extract linked ONS mortality data (date of death) which NHS Digital will use to calculate vital status at 30, 60, 90 and 365 days post-date of hip fracture.
3. NHS Digital will apply Type 2 patient objections to this list of patients. The data of any individual who has registered a Type 2 objection since the data was supplied under DARS-NIC-61090-T9Y0G will be removed.
4. NHS Digital will remove all identifiers and the date of death; re-encrypt the HESIDs using the same encryption key as for DARS-NIC-61090-T9Y0G, and disseminate the data, as pseudo-anonymised data, to the University of Oxford.
5. The University of Oxford would extract a copy of the linked HES and NHFD data (but not the linked ONS mortality data) supplied under DARS-NIC-61090-T9Y0G for all individuals whose data is included in the output file from NHS Digital. This data would be linked with the mortality indicators supplied and the resulting dataset will be stored separately from the dataset supplied under DARS-NIC-61090-T9Y0G with access controls ensuring the two will not be linked or accessed together.
6. In addition, NHS Digital will produce a new unlinked pseudonymised extract of HES data for which Type 2 patient objections will not be applied. This will be an extract of patients with a record of hip fracture (ICD-10 S72.0*, S72.1*, S72.2*) fracture between 1st January 2000 and the latest possible date with age >=60 at the time of diagnosis. For each patient, vital status at 30, 60, 90 and 365 days post-admission will be calculated. This will be supplied to the University of Oxford. This will be used as external validation of the Hip Fracture Best Practice Tariff work, as this initiative might itself also influence reporting of cases to the NHFD. The University of Oxford will not attempt to link this data with any other dataset.

The University of Oxford will then hold two separate datasets: one NHFD-HES with vital status indicators under this Data Sharing Agreement and a second as NHFD-HES-ONS with date of death under the Agreement DARS-NIC-61090-T9Y0G.

The respective datasets will only be used for the projects authorised under their respective Data Sharing Agreements. The two datasets will be stored on separate hardware-encrypted hard drives that can only be accessed by physically entering a passcode onto the device itself. This will mean that the datasets will be physically separated (i.e. on separate devices) and accessed using different passcodes. As well as being separated in space, the datasets will also be separated in time as they will not be accessed simultaneously.

The researcher from the University of Oxford has previously undertaken analyses directly from these hard drives so that data does not have to be stored on a single computer or network. If it does become necessary to transfer a dataset to a University of Oxford computer (e.g. because of the size or analysis complexity), this will only be done temporarily while the dataset is being worked on. It will be returned to the appropriate hard drive at the end of the day to mitigate the risk of "cross contamination" between the two datasets.

The linked mortality data provided under Data Sharing Agreement DARS-NIC-61090-T9Y0G will not be copied, linked or used in any way for the purpose of this project under this Data Sharing Agreement.

The datasets will be stored on encrypted hard drives in a locked safe in the Botnar Secure Computing Room, which is an access-controlled facility within the Botnar Research Centre. The Botnar is one of three facilities run by the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS) at the University of Oxford. It is based on the Nuffield Orthopaedic Centre site, which is operated by Oxford University Hospitals NHS Foundation Trust. In addition to access controls, there is CCTV in the building and 24/7 security. Data will only be analysed within the Botnar Secure Computing room on computers that are not connected to any external network. Security within the room is regularly audited by the Information Governance Manager and the computers are kept up-to-date with anti-virus software.

The Kadoorie Centre for Critical Care Research is a second site operated by NDORMS and will serve as a secondary processing location for analysing derived (i.e. less sensitive) data. This data will only include fields that are required for the analyses being undertaken at any one time. Sensitive variables (e.g. individual diagnoses) will be recoded (e.g. to Charlson co-morbidity score). Data at the Kadoorie Centre will be stored on an encrypted hard drive in a locked filing cabinet in a secure office. This room requires two levels of swipe card access and a physical key to open the door itself. Data will be analysed on a computer that is not connected to any external network and analyses will be undertaken using the encrypted hard drive rather than by transferring data to the computer itself. This will mean that no sensitive data will be stored on the computer hard drive overnight.

Data will only be transported occasionally between the Botnar Secure Computing Room and the Kadoorie Centre. When such transfers do occur, it will always be a direct journey and the data will always be stored on an AES-256 encrypted hard drive.

Data from the NHFD and NHS Digital will only be stored and accessed at the University of Oxford. It will not be linked to any datasets other than the NHFD. There will be no requirement nor attempt to re-identify individuals from the data by the research team.

The members of the research team are all directly employed or working under appropriate supervision on behalf of University of Oxford. All researchers who will have access to the data are subject to the same policies, procedures and sanctions as substantive employees. Supporting the research team will be one individual on secondment from the University of Yale in the USA. This individual will work under an honorary contract with the University of Oxford and will only access the data on site at the University of Oxford under the same conditions as substantive employees of the University of Oxford described above.

All organisations party to this agreement will comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract – i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

The data will only be used for the purposes described in this Agreement. The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

For clarification, comparisons of hip fracture patient outcomes between the UK, US and Australia will be undertaken using the new risk adjustment model produced as a result of processing the data covered by this Agreement. The data will not be shared with third parties in the UK, US or Australia. As above, only data in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide will be available to any third parties.

The role of patient factors, surgical factors and hospital factors upon patient outcomes and NHS costs in the treatment of upper limb musculoskeletal injuries and infections: spatial and longitudinal analysis of routine data — DARS-NIC-295342-W3Z6L

Opt outs honoured: No - data flow is not identifiable, No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2020-01 – 2023-01 2020.02 — 2020.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration - Deaths
  3. HES:Civil Registration (Deaths) bridge
  4. Civil Registration (Deaths) - Secondary Care Cut
  5. Civil Registrations of Death - Secondary Care Cut
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires HES Admitted Patient Care linked to mortality data for the purpose of a retrospective longitudinal study to investigate the trends in surgery undertaken for the treatment of upper limb injuries and infections, and the complications that follow surgery. This study is being undertaken at the Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS) within the University of Oxford.

Upper limb injuries and infections are common and can affect the short and long-term social and occupational function. Emergency conditions (i.e.; hand fractures, dog/cat bites, infections) often need surgery as soon as possible to prevent complications, e.g.; nerve damage, prevent spread of infection to other parts of the body and prevent damage to joint surfaces that lead to post traumatic arthritis.

The complexity of these emergency conditions often requires treatment in dedicated units, especially when the hand is affected. Hand injuries are common, accounting for up to 30% of Emergency Department attendances. Upper limb injuries in general are thought to affect the young, male, working population most commonly, with the majority of injuries sustained either at work or during sport. The prevalence of these injuries among the young, working-age population means they have significant marked economic impact. These costs take into consideration both direct healthcare costs and loss of productivity. Infections of the upper limb can occur in all age groups and are similarly debilitating. Less is known about the incidences and outcomes of upper limb infections. By understanding the burden of surgery needed to treat upper limb injuries and infections on the National Health Service (NHS) and observing temporal and geographic trends, services can be better planned. In addition, understanding injury patterns and risk factors for infections allows targeted preventative strategies to be considered. Lastly, analysis of upper limb injury and infection burden allows clinical research to be directed towards better understanding and managing the most prevalent and impactful conditions.

The research group at NDORMS recently performed and published an analysis of HES data for hand trauma (see https://www.ncbi.nlm.nih.gov/pubmed/?term=Manley+AND+wormald). Researchers used publicly available HES data which is published on line and found that the absolute number of hand injuries per year was 33,948 in 1998–1999 and 59,830 in 2014–2015, a 76% increase. The incidence of hand injuries also increased in this period from 70 to 110 injuries per 100,000 population, a 57% increase. Hand injuries themselves can broadly be divided into fractures and soft tissues injuries. Soft tissue injuries can then be further divided into tendon, muscle, nerve and vessel injuries. Hand injuries also encompass amputation of the hand or digits and soft tissue finger-tip injuries, which usually involve injury to the nail apparatus.

This new study has been founded as a result of the success of this paper.

Despite the commonality of upper limb injuries and infections, there is significant on-going debate and research regarding best management. This is an area of interest to a number of leading research groups in the UK, all of which would benefit from further in-depth analysis of HES data. Additionally, a number of other common hand injuries have been identified as targets for further clinical research by the NIHR, including digital nerve injury (NIHR HTA call for research, 2018) and hand flexor tendon injury (NIHR HTA call for research, 2019). Previous analysis of non-patient level HES data by researchers at NDORMS demonstrates increasing trends in upper limb trauma surgery. NDORMS researchers will use a HES dataset of patients treated for upper limb injuries and infections over the past 20+ years. This pseudonymised, individual case-level data will allow researchers to look carefully at the patient and surgical factors which comprise the scope of upper limb emergencies in England, as well as specific factors that may contribute to differences in outcomes.

The analysis of routinely collected observational data may be limited by the quality of data collection and coding (Kuhn & Mallon 2016). However, the major benefit of HES data is that it represents a comprehensive dataset of NHS Secondary Care in England. It explicitly avoids the problem of selective reporting to a purpose designed research database since reporting of all NHS funded cases is mandated. Whilst technical detail on procedures may be lacking, the research team expect sufficient granularity to inform temporal trends and analysis of patient and hospital factors associated with treatment failure, as identified by repeated need for admitted hospital care.

NDORMS will also focus on variation in outcomes of specific patient groups (e.g. old and frail with comorbidities and obese) and present evidence as to whether the introduction of new surgical innovations (e.g. minimally invasive surgery), and centralisation of services, has led to improved patient outcomes. Civil Registration Mortality data for the patients selected will enable analysis of associations between surgery and death rates.

The researchers require data for processing under General Data Protection Regulation Article 9 (2) (j) and Article 6 (1) (e). The researchers believe that this research is in the public interest as currently there is very little high level evidence available to counsel patients who sustain upper limb injuries and infections on what their outcome is likely to be. The research will investigate geographical trends in injury incidence that will assist in workforce planning and the provision of surgical services. Temporal trends over 22 years will also enable researchers to investigate if any differences in outcome are due to patient factors (past medical history, age) or healthcare factors (admission to hospital).

This study focuses on patients who have sustained upper limb injuries and infections. The data required are limited to only hospital inpatient episodes and mortality records for individuals who had an inpatient care episode since 1997 due to an upper limb information or injury (identified using the ICD code assigned to the hospital episode) which resulted in non-elective surgery (identified using the OPCS code assigned to the hospital episode). Both criteria must apply for an individual to be included in the cohort.

The University of Oxford requires details of all of the data subjects' episodes of inpatient care before the episode due to the upper limb injury in order to gain as full an understanding as possible of their past medical history to see if the individuals have risk factors for infection/complications. All prior and subsequent hospital episodes for the data subjects are required regardless of diagnosis and/or procedure because the study is looking at comorbidities which potentially impact on risks of upper limb injury or adverse outcomes following surgery. It is not feasible to limit the types of previous hospital episodes to specific ICD codes which are presumed to be more likely to be related to risk factors for surgical outcomes as this would bias the findings of the study and could potentially result in failure to identify previously undetected links between certain conditions in past medical history and risk of specific outcomes following surgery. Due to the lack of existing evidence surrounding the role of comorbidities in this research area, it is not advantageous or appropriate to further select a subgroup of patients with certain co-morbidities. Less data than what has been requested would limit the usefulness of the study and be impact the results for informing future patient care.

Details of all inpatient hospital episodes after the individual’s upper limb infection or injury are required to see if they had a complication, or needed further surgery to deal with sequelae of infection or injury (i.e.. develop joint contracture, post traumatic arthritis).

National data is required in order for the results to be generalisable and because one of the main aims of this study is to investigate geographical and temporal trends in the management and outcomes of upper limb injury and infection. For example, the study will investigate links between deprivation and comorbidity and the propensity to incur the injury or infection with a view to recommending targeted prevention programmes in specific areas to reduce the risks of injury and of adverse outcomes post-surgery.

The study team requires both adult and children’s injuries in the extract so will want to include paediatric episodes. Paediatric trauma is as common as adult trauma so excluding this group is non-sensical. The long-term outcome for children with upper limb trauma or infection is potentially even more relevant.

It is specifically desirable not to narrow the cohort by demographics such as age as to do so would introduce bias to the findings of the study. Undertaking a retrospective analysis which includes the very young and very old is advantageous as such groups tend to be excluded from clinical trials. This study will involve focus on variation in outcomes of specific patient groups such as these. Maternal episodes/birth episodes will not be required as they will not be relevant.

In addition to HES APC data, civil registration mortality data would be used to enable risk factor association studies and survival analysis to be undertaken. In this retrospective longitudinal study, the ability to recognise whether a patient is still alive is key to undertaking survival analysis. Civil registration data enables researchers to identify the outcome of patients who sustain polytraumatic injuries (upper limb trauma in association with life threatening injuries elsewhere in the body at the same time) and to identify the true risk of complications following isolated upper limb trauma and infections. This is why knowing both the date of death and the cause of death are key. Requesting the full 22 years of mortality data enables researchers to undertake a long term follow up study that does not occur after clinical trials due to cost and time constraints, and therefore there is a paucity of evidence into long term complications.

The University of Oxford is requesting 22 years of HES and Civil Registry mortality data. Enabling researchers to follow patients up for a long time retrospectively will allow clinicians to be better informed when counselling patients in the future, at the point of surgery, about their options, the risk of them having complications, needing further surgery and long term prognosis. Some complications only occur after many years, and therefore the longer follow up possible the better, as they need to know when and why people died, in order to know if the death was associated with the injury (polytrauma). The date of death will enable researchers to accurately censor the patients within the survival analysis when investigating the true rate of complications (i.e. someone who has died cannot sustain a complication). Researchers want to be able to look at long term complications (post traumatic arthritis, joint contracture etc) which they cannot do if they only have access to mortality data within a certain time period after the event.

National data enables researchers to undertake geographical analysis of the burden of hand trauma and to compare outcomes across England. This enables researchers to identify where greater resources are needed. One of the ways of doing this would be to do an interrupted time series, where statistically one compares the rate of surgery/complications before and after, e.g. introduction of a policy. As this data is observational rather than true research data, further studies, such as interrupted time series’, are needed to identify whether changes in trends over time are due to changes in policy/ hospital factors, or due to patient factors (e.g. ageing population). Having 22 years of data enables researchers to be able to generate a better picture of whether these trends are likely to be due to patient or health system factors.

There is nowhere else in the world that has this length of follow up. There is no current evidence that enables patients to be counselled. Analysis of this data would add a very large body of evidence to counsel patients at the time of consent.

The University of Oxford has considered data minimisation and has taken steps to ensure the data requested is justified and limited to specified upper limb conditions, injuries and procedures. The study team will provide a list of diagnosis and operation codes which relate to upper limb skeletal conditions. Efforts have been made to ensure procedure codes have been combined where possible, e.g. excision of bone/hand, excision of bone/thumb, etc, instead of just excision of bone which may not relate to the upper limb. The research team have produced a tight list of OPCS and ICD fields that restrict the request to only these specific upper limb surgeries.

The interventions that this study wishes to look at have been in use for well over 20 years, and as such the study would like to look specifically at the changes over time in their usage, for example in response to key papers, guidelines, changes in policy.

The University of Oxford is the sole data controller and also processes the data for this study. No other organisations process the data for this purpose. When results are available, an advisory role would be taken by the British Society of Surgery for the Hand BSSH research committee but no data processing would be undertaken by them and all decisions about data analysis would remain with the university. The BSSH would advise about how best to disseminate the results to both healthcare providers and to patients, having recently undertaken a priority setting partnership with patients through the James Lind Alliance (https://www.bssh.ac.uk/patients/bssh_james_lind_alliance_partnership.aspx).


Study Aims

The main aims of this study are:

1. Investigation of the variation in surgical treatments, revision rates and mortality rates in upper limb injuries. Investigation of spatial and retrospective longitudinal trends in mortality will also be studied.

There is substantial debate on an international level regarding how best to treat some of the most common upper limb injuries, including hand, wrist and forearm fractures in adults and children, hand tendon injuries and digital nerve injuries. The key debate for most injuries is whether they should be managed operatively or non-operatively, and within that which interventions are most beneficial. NDORMS wish to investigate these interventions and their outcome in terms of further morbidity and cost.

2. Geographical and temporal trends in management and outcome

Having identified the types of surgical intervention undertaken, NDORMS will investigate whether there are temporal or geographical trends associated with intervention type, compared to geographical and temporal trends in injury prevalence. NDORMS will investigate this comparing patient demographics within regions and over time, and produce maps highlighting these trends. NDORMS will also produce maps highlighting variation in length of stay, readmission complication and re-operation rates across the country as proxy measurements for patient outcome.

3. Assessment of access to care & care costs

Statistical analysis of national data from the HES admissions database will allow identification of hospital organisation and surgical factors that may explain geographical variations in patient outcomes of surgery, after adjustment for patient level case-mix. In this study researchers aim to identify whether the different ways that hospitals organise services for patients presenting with upper limb injuries can lead to improved patient outcomes, and postulate reasons why outcomes may vary between hospitals or regions. NDORMS will investigate whether these differences cause a variation in access to care, due to disease prevalence, or due to variation in management and how these factors influence the cost of patient care. Greater understanding of trends in how these interventions are being used and the outcomes following them will enable NDORMS to propose changes that will influence health service provision and workforce planning.

This dataset has the unique and exciting opportunity of exploring the changes that have occurred in disease presentation, development, treatment and outcome over an extensive time period. Studies that have follow up of this duration have not been previously undertaken in this country, and undertaking research using routinely collected NHS data will enable researchers to better understand how to care for patients with upper limb injuries. Long term follow-up of operative and non-operative interventions allows evaluation of their impact in terms of further morbidity and need for further intervention. Analysis of long term outcomes are vital in order to determine which interventions should continue to be used; evidence that is not available elsewhere.

Alignment with NHS agenda:

In the NHS, patients can choose which hospital they want to have their surgery in. Information on access to treatments and the outcomes of surgery between different hospitals would help patients in making their decision. Outcomes of surgery may vary across different regions and hospitals. Any such differences might be explained by a hospital treating more complex and sicker patients, but could also be explained by the surgical techniques employed in different centres, or centralisation of care into specialist high volume hospitals. Knowledge of this upper limb trauma, injury and complications would inform the development of an NHS Improvement clinical outcome dashboard for trauma. Previous work using elective HES data has informed a similar dashboard for hand conditions, currently being piloted across five sites with national roll-out in 2020. The Chief Investigator has worked on this dashboard with the NHS National Clinical Improvement Programme and has an ongoing collaboration with this group (https://gettingitrightfirsttime.co.uk/ncip/). These dashboards can aid NHS managers and clinicians in changing and optimising service organisation to reduce any variations in outcomes.

The national audit into the orthopaedic surgical procedures called Getting It Right First Time (GIRFT) was launched in 2013. Initial results released in March 2015 found large variations in practice, and have called for better research into the timing and types of procedures undertaken. Better understanding of regional and temporal variations in procedures, and which surgical procedures have the best outcomes would improve the quality of patient care in the UK, reduce costs for the NHS and more importantly provide better patient information to inform shared treatment decision making.

Expected Benefits:

Benefit

The study will inform patients, NHS managers, commissioners and health professionals of the NHS costs and patient outcomes and cost-effectiveness associated with the treatment of upper limb injuries, and the key elements that are most clinically and cost effective. It will provide patients with information on variation in outcomes of surgery to inform patient choice and decision-making. NDORMS will work alongside charities and learned societies to disseminate the findings of this study using established platforms that include social media such as Twitter and a study website, as more patients are now turning to these resources for information about planned surgery. NDORMS will provide evidence of modifiable hospital organisational factors that can explain unwarranted geographical variation in patient outcomes of surgery. This can be used to inform healthcare organisations of factors identified as improving patient outcome and both local and national level, and can be used by clinicians and policy makers to inform healthcare policy.

Impact

The exploration of current trends in procedures undertaken, in temporal and geographical variation in operation numbers and type, mismatch of prevalence and surgery rates, and of outcomes will enable NDORMS to understand more about the current management of upper limb conditions and how to improve NHS services nationwide. NDORMS will explore variations found to identify whether differences in the way hospitals or regions organise their services, such as specialist surgeons, use of new surgical techniques, or centralising care into specialist hospitals, can explain any observed variations. Similarly, understanding the variation in outcomes following a range of procedures enables greater knowledge of which interventions should continue to be funded. Knowledge of these factors would inform changes that can be made to the way services are organised and provided, leading to better access for patients and helping to standardise evidenced based care and patient pathways across the UK. The target date for output and dissemination to produce measurable benefit is 24 months from receipt of data.

Outputs:

Throughout all stages of this project, NDORMS will engage with key stakeholders including NHS managers, healthcare professionals, patients and the public for interpretation, dissemination and direct communication of the main findings. This will be facilitated through collaboration with the James Lind Alliance, support of specialist societies, and Patient and Public Involvement (PPI) representation. A Professor of Plastic Surgery at University of Oxford is a named co-applicant on this study and the leader of the BSSH research committee. He will assist in interpreting results and with the national dissemination of findings. This project has also been informed by results from the recent James Lind Alliance (JLA) Priority Setting Partnership (PSP) for surgery for common hand and wrist conditions, carried out in association with the British Society of Surgery for the Hand (BSSH). NDORMS shoulder and elbow, and hand and wrist applicants both have national roles and collaborations that provide excellent access and influence to disseminate the study findings nationally and internationally through the following societies and funded research centres:

1. British Society for Surgery of the Hand (BSSH)- Dissemination to all British hand surgeons and hand therapists. Presentation at the biannual National Congress.

2. British Association for Plastic, Reconstructive and Aesthetic Surgery (BAPRAS) - Dissemination to all British plastic surgeons, hand surgeons and hand therapists. Presentation at the biannual National Congress.

3. British Orthopaedic Association (BOA) - Dissemination to all British orthopaedic surgeons, hand surgeons and hand therapists. Presentation at the biannual National Congress.

4. NIHR Oxford Biomedical Research Unit/Centre – Dissemination to all linked patient and local GP networks

5. Internationally NDORMS will disseminate through peer review publications and via presentations at the Federation of European Societies for Surgery of the Hand (FESSH)

One of the NDORMS professors using this data has written national guidelines for NICE and the specialist societies on managing many shoulder conditions including authoring national commissioning guidelines.

A senior researcher on this study, who is an employee of the University of Oxford will use the aggregated, anonymised results generated from this study to influence practice nationwide. BSSH is in the process of gaining accreditation from NICE for guideline development and NDORMS anticipate this to be in place by the time the results of this work are published.

Working with and informing all stakeholders will remain an important part of NDORMS dissemination plans. NDORMS recognise the importance of meaningful PPI involvement and have worked collaboratively with the PPI Officer at NIHR Research Design Service (RDS) to identify individuals to become involved, and NDORMS Director of Patient Involvement at the Oxford NIHR BRC. NDORMS have identified three lay people who understand the needs and problems of upper limb conditions. Through their involvement and recommendations regarding the dissemination of findings, NDORMS will ensure results are readily available and interpretable to the wider patient and public community.

NDORMS shall disseminate findings in peer-reviewed journals, at national and international conferences, and inform learned societies that include the British Orthopaedic Association, The British Shoulder and Elbow Society (BESS), British Society for Surgery of the Hand (BSSH). NDORMS will work alongside charities and learned societies to disseminate the findings of this study using established platforms that include social media such as Twitter and a study website, as more patients are now turning to these resources for information about planned surgery.

Based on the findings NDORMS will write scientific papers for submission to high quality peer-reviewed journals. NDORMS will also present findings to professionals at conferences and meetings, will develop Plain English summaries of findings for communication to patients and members of the public. All outputs will adhere to the HES analysis guide so that data is only shown in aggregate form with small numbers supressed. NDORMS will publish a full and complete account of that research in the NIHR HS&DR Journal, ensuring the research is reported fully, and publicly available via the NIHR Journals Library website and Europe PubMed Central. A webpage will be developed within the NDORMS website specifically for this study in order to further transmit the results to the public. This study aims to capture the attention of patients and the public by presenting the long term results of surgery for upper limb conditions in the UK not previously undertaken, and to also present the potential reasons why there may be variation in outcomes following surgery. Previous PPI work has shown that variation in disease progression, and outcome following intervention is of particular interest to patients and the public.

The University of Oxford has employed a post-doctoral research fellow, who is a specialist data scientist, to undertake the analyses described above, as well as undertake a separate analysis looking at the epidemiology of surgical site infection following upper limb trauma in adults and children. This will form part of his DPhil at the University of Oxford in collaboration with the Chief Investigator of this research project.

The interim expected timeframe for completion of the data processing, production and dissemination of the outputs would be 24 months, with a further 36 months retention of data after this to respond to changes based on peer-review comments from journals and from funding bodies.

Processing:

The University of Oxford is requesting patient level pseudonymised HES Admitted Patient Care and Civil Registry mortality data from NHS Digital. The University of Oxford have requested patient demographic factors (e.g. age, sex, ethnicity, deprivation index); episode factors (e.g. date of admission/surgery/pseudonymised consultant code/HRG); healthcare provision (CCG/waiting times) and data relating to the injury/infection itself (OPCS/ICD codes).

The University of Oxford will not be providing any data to NHS Digital, but just requesting all episodes of care for patients who have an episode containing pre-determined OPCS and ICD codes associated with upper limb injuries and infections. The University of Oxford has requested HES APC data be linked to Civil Registry mortality data to enable survival analysis and will not link this data to any other datasets.

Upon receiving the data from NHS Digital, a senior data manager with experience in managing HES datasets will process the raw data into smaller extracts. Smaller extracts will be made available for analysis based upon disease pathology and surgical intervention undertaken. This will enable the separate research questions defined by the aims of the study to be answered.

NDORMS will provide data at the small area level presented as maps to describe variation in outcomes, before and after accounting for these organisational and surgical factors. All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Statistical analyses (multilevel regression modelling) of HES data will assess the association of surgical factors on patient outcomes of surgery, adjusting for patient case-mix. Further statistical analyses (random intercept models) will explore geographical variation in outcomes across hospital trusts and Clinical Commissioning Groups. Geographical Information Systems will be used to produce maps depicting variation in outcomes, and graphically display the influence these factors have on explaining such variation.

NDORMS will then use a natural experimental study design to specifically examine the impact that the new treatments have had on NHS resource use, NHS costs and patient outcomes (based upon length of stay, complications, readmission, further surgical intervention including revision surgery). Interrupted time series analysis will examine changes in secular trends in outcomes and NHS costs before and after the introduction of the new treatments. There will be a focus on the benefit of the new treatments to specific patient groups such as frail older people with complex co-morbid conditions. An economic evaluation will describe the hospital NHS costs, patient health related quality of life and cost effectiveness that reflect the new treatments for upper limb conditions. The predominant method of limiting the data requested is through the study of selected upper limb conditions only, and through only selecting certain procedures. Due to the lack of existing evidence surrounding the role of comorbidities in this research area, it is not advantageous or appropriate to further select a subgroup of patients with certain co-morbidities.

A cost-effectiveness analysis will be performed to estimate the economic burden of conservative and surgical care in relation to trends in outcome, adjusting for socioeconomic status and case-mix. This is largely unexplored to date and essential for further studies potentially exploring the cost-effectiveness of the surgical intervention.

Once data has been disseminated to the study;

- The HES and Civil Registration Mortality datasets will be held on a password protected University Computer on an encrypted drive at the Botnar Research Centre, Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS).

- The data will be managed by a researcher based at the Botnar Research Centre Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS) University of Oxford.

- The data will be used exclusively for the purpose of this project.

- At the end of the study, the data will be safely held in a password protected University Computer at the Botnar Research Centre for 60 months and, in that time, it will be assessed only to answer questions arising from the publication and other publicity. The interim expected timeframe for completion of the data processing, production and dissemination of the outputs would be 24 months, with a further 36 months retention of data after this to respond to changes based on peer-review comments from journals and from funding bodies.

All data will be processed only by substantive employees of University of Oxford who have been appropriately trained in data protection and confidentiality.

Data will not be linked to any other record level data. No attempts will be made to identify any individual from the data being supplied. No data will be onwardly shared.

MR126 - Study of Cancer in Vegetarians — DARS-NIC-148267-W26RZ

Opt outs honoured: N, Yes - patient objections upheld, Yes (Excuses: Section 251, Section 251 NHS Act 2006)

Legal basis: Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2019-04 – 2020-09 2017.09 — 2020.01.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Members and Postings Report

Type of data: Identifiable, Anonymised - ICO Code Compliant

Objectives:

The data supplied by the NHS Digital to University of Oxford will be used only for the approved Medical Research project MR126.

The Oxford Vegetarian Study (OVS), also known as the Study of Cancer in Vegetarians, was designed in 1980, and the 11,040 participants were recruited through the Vegetarian Society, media and by word of mouth between 1980 and 1984. Participants implicitly consented to the study by voluntarily completing and returning the questionnaire.

The aim of the study is to investigate the long-term health of vegetarians and comparable non-vegetarians, examining cancer risk and mortality. The design is an observational cohort, based on recruiting healthy volunteer participants and following their long-term health through linkage to NHS information on incident cancers and causes of death.

Participants in the study were immediately flagged for cancers and deaths with the Office for National Statistics (ONS) Record linkage for supplying information for the Study of Cancer in Vegetarians (Ref: MR126). Deaths and cancer information was approved via ONS to supply this information from 1980 to 2013.
In November/ December 2015 the study received Ethics (NHS REC) and Section 251 (CAG) approval.

There have been 1108 incident cancers (to 31/12/2012) and 1955 deaths (to 31/3/2014) in the cohort. Analysis of the cohort has led to many publications, as recently as 2014, in peer reviewed journals such as the British Medical Journal and British Journal of Cancer.

Data was initially collected by questionnaires on diet and lifestyle, returned by post in 1980-1984. The OVS is supported by a grant from the Medical Research Council (MRC) (“Health of Vegetarians”).
The study is needed to improve understanding of the effects of diet on health and thus inform advice to governments, health professionals and the public about dietary choices to maximise the potential for long-term good health.

The study is on-going and funding is in place until 2020. As outlined in the specific outputs analysis of the data will continue into 2018 and the research findings will be presented in 2019.

Yielded Benefits:

As this is a long term longitudinal cohort study it will take many years to reach the final endpoints (death and cancer incidence).

Expected Benefits:

The aim of the study is to improve information on diet in relation to the risk of cancer and cardiovascular disease and offers potential for improvements in public health in the UK. The results are published in peer-reviewed publications and presented at conferences, and are also reported through national media.

University of Oxford research relates directly to the health of 1.2 million people in the UK who follow vegetarian diets (NHS 2014). The long-term effects on cancer of a vegetarian diet are not well understood, and little is known about the health effects of a vegan diet. Our previous research has demonstrated lower risks of obesity (50%), heart disease (30%), stomach cancer (60%) and haematological cancers (36%) in vegetarians compared with non-vegetarians (Key and Davey 1996, Crowe et al 2013, Key et al 2009, 2014), and further study is likely to reveal other associations between diet and cancer risk. As well as peer-reviewed scientific publications, where appropriate, University of Oxford will also communicate with the NHS and other organisations such as the National Cancer Intelligence Network within Public Health England and other health providers in the UK, where the outputs from the study will provide information to underpin their health advice to the public.

For example: The PI of this study sits on the Scientific Advisory Committee on Nutrition (SACN) which reports to Public Health England and other UK government organisations. Conclusions from this committee are used to formulate government and NHS policy on diet and thus reduce the risk of disease and the burden on the NHS. In a current SACN update, the fortification of the UK food supply for folic acid to prevent neural tube defects included a key piece of evidence including data from the Oxford Vegetarian Study, related to the safety of folic acid with respect to cancer risk. (https://www.gov.uk/government/consultations/consultation-on-draft-sacn-update-on-folic-acid).

Future work will look at heart disease (further analyses with more data), death from stroke and risk of prostate cancer, as well as the protective impact of vegetarian diets in preventing the development of obesity.

In the planned new analyses of ischaemic heart disease and stroke, the study will use their data on diet to estimate the impacts on health of replacing energy (calories) from red and processed meat with energy from plant foods which can be used to replace these foods, such as legumes (beans, peas and lentils) and nuts.

The NHS Choices website (http://www.nhs.uk/Livewell/Vegetarianhealth/Pages/Vegetarianhealthqanda.aspx#what) states that “a vegetarian diet can be very healthy” and reports on an NHS patient who comments “I feel much healthier on a vegan diet”, but includes few specific statements about the benefits. The research will provide the robust information needed to include more specific facts and advice on the NHS website and thus enable the public to improve their health and reduce the burden on the NHS.

As well as peer-reviewed scientific publications, where appropriate, University of Oxford will also communicate with the NHS and other organisations such as the National Cancer Intelligence Network within Public Health England where the outputs from the study will provide information to underpin their health advice to the public.

This study will directly benefit health care through the NHS by providing clinicians and other NHS health care professionals with up-to-date evidence-based guidance on the effects of diet on cancer and the risk of death. This will improve clinical health care and inform planners and policy makers to address demands on health and social care in the present and future.

The robust, reliable knowledge on vegetarian diets and risk of chronic disease will provide the evidence to underpin the judgements made by decision-makers on the future direction of NHS policy in relation to dietary advice, thus acting as an enabler. For example, the NHS reported in 2013 that a vegetarian diet brings a range of health benefits and is linked to longer lifespan (12% in risk of death from any cause, see http://www.nhs.uk/news/2013/06June/Pages/Vegetarian-diet-linked-to-longer-lifespan.aspx). This NHS assessment noted that the study concerned had a relatively short follow-up of six years, this is quite short to address how dietary patterns might affect the risk of death.

In University of Oxford analyses, there is a follow-up of over thirty years which will provide the NHS with much more reliable information on the long-term health of people following a vegetarian diet. This reliable evidence will be available in publications in late 2017 and 2018, enabling updating of NHS sources during 2018.

In the link http://www.nhs.uk/news/2013/01january/pages/does-a-veggie-diet-lead-to-a-healthier-heart.aspx
The researchers concluded that vegetarians had a 32% lower risk of IHD than non-vegetarians, and that this is likely due to “reduced levels of well-established risk factors for IHD, such as non-HDL cholesterol concentrations and systolic blood pressure”. This large and impressive prospective cohort study suggests that a vegetarian diet may benefit your heart; reducing the risk of IHD. This was a well-conducted, large long-term study that suggests there are heart healthy benefits to a vegetarian diet. The NHS will be able to continue to use University of Oxford data to update their websites accessible to the general public.

This NHS provided advice, based on OVS data, to their stakeholders. This will enable commissioners to implement appropriate policies in relation to diet, thus reducing the financial burden of dietary related diseases.

More recently one of the named researchers attended the inaugural workshop of the Cancer and Nutrition NIHR infrastructure collaboration http://cancerandnutrition.nihr.ac.uk/wp-content/uploads/2016/06/Cancer-Nutrition-Full-Report-FINAL_03-06-16.pdf . OVS and EPIC will be part of this initiative. The Cancer and Nutrition NIHR infrastructure collaboration will improve cancer prevention and care for clinicians and patients.

Selected publications:
Appleby PN, Crowe FL, Bradbury KE, Travis RC, Key TJ. Mortality in vegetarians and comparable nonvegetarians in the United Kingdom. Am J Clin Nutr 2016;103:218-30.
Key TJ, Appleby PN, Crowe FL, Bradbury KE, Schmidt JA, Travis RC. Cancer in British vegetarians: updated analyses of 4998 incident cancers in a cohort of 32,491 meat eaters, 8612 fish eaters, 18,298 vegetarians, and 2246 vegans. Am J Clin Nutr 2014;100 Suppl 1:378S-85S.
San Joaquin MA, Appleby PN, Key TJ. Nutrition, lifestyle and colorectal cancer incidence: a prospective investigation of 10998 vegetarians and non-vegetarians in the United Kingdom. Br J Cancer 2004;90:118-21.

Outputs:

Publications are produced on an ongoing basis, all outputs and publications contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide. Examples of publications are:

Plasma lipids and lipoprotein cholesterol concentrations in people with different diets in Britain.
Thorogood M, Carter R, Benfield L, McPherson K, Mann JI.
British Medical Journal 1987;295:351-353.

Relationship of body mass index, weight and height to plasma lipid levels in people with different diets in Britain.
Thorogood M, McPherson K, Mann J.
Community Medicine 1989;11:230-233.

Dietary intake and plasma lipid levels: lessons from a study of the diet of health conscious groups.
Thorogood M, Roe L, McPherson K, Mann J,
British Medical Journal 1990;300:1297-1301.
(h:\docs\ovs\dietary_intake_and_plasma_lipid_levels.pdf)

Testosterone, sex hormone-binding globulin, calculated free testosterone, and oestradiol in male vegans and omnivores.
Key TJA, Roe L, Thorogood M, Moore JW, Clark GG, Wang DY.
British Journal of Nutrition 1990;64:111-119.

Asymptomatic hypothyroidism and hypercholesterolaemia.
Ball MJ, Griffiths D, Thorogood M.
Journal of the Royal Society of Medicine 1991;84:527-529.

Risk of death from cancer and ischaemic heart disease in meat and non-meat eaters.
Thorogood M, Mann J, Appleby P, McPherson K.
British Medical Journal 1994;308:1667-1671.
(h:\docs\ovs\risk_of_death_BMJ1994.html)

Emergency appendicectomy and meat consumption in the UK.
Appleby P, Thorogood M, McPherson K, Mann J.
Journal of Epidemiology and Community Health 1995;49:594-596.

Results are disseminated in peer-reviewed open-access papers in research journals, and related presentations to national and international colleagues, including clinicians.

This study currently has funding to follow up patients until 2020.

The data is processed only by one named researcher within the Cancer Epidemiology Unit (CEU). For all of these outputs, data is aggregated with small numbers suppressed in line with the HES analysis guidance.

Future anticipated work using ONS mortality and cancer registry data:
The Medical Research Council Grant MR/M012190/1 "Health of vegetarians" specifies a programme of research on the associations of vegetarian diets and related nutritional factors with the incidence of common diseases.

In 2017 and 2018 the study will analyse:
• the relationships of vegetarian diets with the risk for death from ischaemic heart disease, extending previous published research on this topic with larger numbers of cases and examining the extent to which the effects of a vegetarian diet may be explained by the consumption of saturated and polyunsaturated fatty acids, fruit and vegetables and dietary fibre; the intent is to complete this manuscript in late 2017 and to submit it to the BMJ.
• In parallel, analyses commencing later in 2017 will examine the associations of vegetarian diets with risk of death from stroke, it was suggested that vegetarians had a somewhat higher risk of stroke than meat-eaters, but the number of cases was too small for robust analyses; with the new current linkage combined with data from EPIC – Oxford, it is expected that approximately 2000 cases of stroke which will provide sufficient power to conduct reliable analyses, and to explore the possible roles of protein and vitamin B12 in determining stroke risk in vegetarians. The intent is to submit this manuscript in 2018 to the journal Circulation.
• In analyses of prostate cancer, the study will report on the risk in relation to vegetarian diets and submit to the British Journal of Cancer, and present the results at the conference of Urologists stated below.

Conferences
University of Oxford plan to present research findings at the following conferences:
• 2017 – Nutritional Society UK Symposium
• 2017 – European Association of Urologists
• 2018 – 7th International Congress on Vegetarian Nutrition, Loma Linda, California
• 2018 – NCIN Conference
• 2019 – NCIN Conference

Processing:

The participants in the study are already flagged on the NHS Digital system, therefore the customer does not need to send in the cohort again.

NHS Digital provides quarterly updates on participant events including removals and re-entries to NHS registration, cancer registrations and deaths, including cause of death details. The future extracts provided will be pseudonymised and will not be linked to the Identifiable data held in any way.

NHS Digital will provide University of Oxford with month and year and causes of deaths and month and year and diagnosis of cancer and a unique study id.

The Senior Statistician within the Cancer Epidemiology Unit (CEU) at the University of Oxford links the data, using Study ID, with study participants’ pseudonymised questionnaire records. All subsequent analyses use only subsets of the pseudonymised data. All such subsets are customised according to the characteristics relevant to the specific analysis containing only the minimum data required for the specific purpose.

Various types of analyses are undertaken on an on-going basis for the overarching purpose of assessing cancer incidence and overall mortality. The data will be held only at the Cancer Epidemiology Unit at the University of Oxford. The datasets will be pseudonymised as described above before statistical analyses are undertaken.

The study will not share any data supplied by NHS Digital with any other institution or individual outside of the study team at Oxford University (i.e. the named users within this agreement).

All users of the data are substantive employees of the University of Oxford.

All processing of ONS data will be in line with ONS standard terms and conditions.

Data supplied by NHS Digital and existing data will be kept in separate electronic files linked by a numerical, anonymous subject identifier. Lifestyle/dietary data required for analysis will be extracted from the relevant data files (which do not contain subject names, NHS numbers or full dates of birth) and merged with the data supplied by NHS Digital using the subject identifier, without having recourse to any identifiable data.

MR1113 - Study of Heart and Renal Protection (SHARP) Post-trial — DARS-NIC-147782-0D7TX

Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251, Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2018-01 – 2020-12 2017.06 — 2019.09.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Members and Postings Report
  4. Hospital Episode Statistics Admitted Patient Care
  5. MRIS - Scottish NHS / Registration
  6. MRIS - Flagging Current Status Report
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Identifiable

Objectives:

SHARP was a large-scale randomised controlled trial involving almost 9500 volunteers aged 40 or over which assessed the effects of lowering LDL-cholesterol in participants with chronic kidney disease (CKD). Patients with CKD are at high risk of substantial cardiovascular mortality and morbidity, and there is a great public need for reliable medical evidence regarding effective therapies for this group of patients. SHARP’s key objective was the assessment of the effect of the combination of simvastatin 20mg and ezetimibe 10mg daily versus placebo on the time to a first ‘major atherosclerotic event’ (MAE) (defined as non-fatal myocardial infarction or coronary death, non-haemorrhagic stroke or revascularisation). Between 2003 and 2006, 9438 patients were randomised world-wide (of which 1987 were from 65 UK centres). The final study visits occurred in August 2010, resulting in a median follow-up of 4.9 years. The main results were published last year (The Lancet 2011; 377: 2181-92) and showed a highly significant 17% reduction in the risk of developing MAEs (95% confidence interval 0.74-0.94, p=0.0022). The study Sponsor was the University of Oxford.

All 1987 UK patients in this randomised trial gave their consent for follow-up of their health by our coordinating centre at the University of Oxford.

A further 5 year follow-up study of SHARP survivors is planned. Such extended follow-up will be imperative to answer the following questions:

• Whether the benefits seen in the main results persists in future years
• Whether the study treatment has any effect on renal disease progression i.e. whether statins are reno-protective in the longer term
• Whether there is any latent safety signal (e.g. effect on cancer, since it has previously been suggested that one of the study drugs - ezetimibe - might be associated with an increased risk of cancer) that did not emerge during the trial’s initial follow-up period
• Whether the intervention is cost-effective (long-term health economic analyses)

Yielded Benefits:

Results from the main SHARP study (as published in 2011; Lancet 2011; 377: 2181–92) showed that In SHARP, allocation to the combination of simvastatin 20 mg plus ezetimibe 10 mg (simvastatin/ezetimibe) safely reduced major atherosclerotic events (MAEs), defined as non-fatal MI or coronary death, non-haemorrhagic stroke, or any arterial revascularization procedure, by 17% (95% confidence interval [CI] 6–26%; p = 0.0021) in a wide range of patients with chronic kidney disease (CKD). The SHARP post-trial follow-up project is ongoing; the data have not been extensively analysed to date pending receipt of an updated dataset which will contain HES data, which will make the results much more informative.

Expected Benefits:

The aim of the SHARP PTFU project is to carry out extended follow-up of SHARP participants to determine whether, in the longer-term:
(i) the beneficial effects in reducing the risk of heart attacks, strokes and operations to open blocked arteries seen in SHARP persist;
(ii) there is any protective effect on the kidneys;
(iii) any hazardous effects (such as cancer) emerge.

Expected benefits:

Researchers/health and social care;
- Generation of knowledge relevant to clinical guidelines and practice
- Increased awareness of the potential for routinely collected data to augment existing understanding and knowledge of a therapeutic area

Patients:
- Increased knowledge which will be used to inform healthcare decisions leading to improved safety and quality of patient care

Outputs:

Results of the analyses will be presented at relevant scientific meetings, and in peer reviewed journals. Specific conferences or journals can not be named as it is not possible to predict where the material may be accepted. However, these will be targeted to ensure that the results are disseminated widely among the clinical trials community.
The results of these analyses will also be posted on the SHARP website (http://www.sharpinfo.org/) in a similar manner to multiple previous SHARP-related publications.

The target time frame for publication of the results of analyses is 2020-2021.

Processing:

The CTSU at the University of Oxford previously sent a cohort of participants in the SHARP study to NHS Digital prior to the end of the main SHARP study for flagging and MRIS data. 1759 participants in England and Wales were flagged in this way.

Subsequent to this, the CTSU received MRIS registry data corresponding to deaths and cancers in relation to these 1759 participants. This data is currently held on secure servers within the University's Nuffield Department of Population Health (of which CTSU is a part). However, this data is does not include any HES outcomes. The SHARP 'within trial' registry data is required so as to make biological sense of the 'post-trial' data. For the purpose of cohort maintenance and cohort reconciliation, an updated dataset (with data capture commencing from 2002/3) comprising HES data, mortality and cancer outcomes is required for the SHARP PTFU project.

NHS Digital still holds the cohort data consisting of 1759 participants and will link this in a one-off extract with MRIS mortality, cancer and HES Admitted Patient Care data. It is believed that the data which was previously disseminated by MRIS is incomplete for the post-trial period as some deaths and other events have been identified as occurring but not reported. At the request of the University of Oxford, NHS Digital will provide all available MRIS mortality and cancer data for the cohort for the purpose of the SHARP PTFU project. On receipt of the new data, the University of Oxford will link it to the existing SHARP database and any duplicates with records already held will be destroyed in a secure manner and the remaining records used to fill any gaps in data coverage. The University of Oxford will confirm destruction of the duplicate data by returning a completed Certificate of Data Destruction.

The data is stored securely on a database within the CTSU. Access to the database will be restricted to study investigators and authorised personnel. Analysis will be performed by appropriately qualified clinicians and statisticians.

The CTSU also separately shares the participants' identifying details with the UKRR so that UKRR can return to the CTSU linked data which it routinely collects from 71 adult and 13 paediatric renal centres. CTSU separately receives data from NHS Digital and UKRR. Each dataset is added to CTSU SHARP PTFU database and linked with the existing data in that database. Through this process, the data from UKRR and the data from NHS Digital are linked by virtue of a common SHARP unique participant identifier. No linkage of the two datasets is undertaken outside of the CTSU SHAPR PTFU database (i.e. the datasets will not be linked externally and then imported as combined data).

The data from NHS Digital will not be linked in any other way or with any other datasets beyond those described above.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

No data will be shared with 3rd parties.

The Data will only be used for the purposes described in this agreement.

MR376 - Ischaemic Stroke and Transient Ischaemic attacks (TIA) — DARS-NIC-33234-C0V1D

Opt outs honoured: Yes - patient objections upheld, No - data flow is not identifiable (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-11 – 2020-10 2018.10 — 2019.03.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. MRIS - Flagging Current Status Report

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires mortality data for the purpose of a research study referred to as ‘Ischaemic Stroke and Transient Ischaemic Attacks’ (TIA).

Transient ischaemic attack, or TIA, occurs when there is interruption to the blood supply to the brain. Patients can have slurred speech, weakness on one side and problems with vision but symptoms resolve fully within 24 hours. The long-term outcome for patients following a TIA is not fully understood.

The TIA cohort study was carried out by the University of Oxford in the 1980s as part of the Oxford Community Stroke Project (OCSP) and an Oxford cohort study of hospital referred patients with TIA. The OCSP was a population-based study of the incidence of first ever TIA in a population of 105,000 people in Oxfordshire, UK, that ran from 1981 to 1986. The hospital referred cohort was recruited during the same period from patients referred from the remaining population of Oxfordshire that was not covered by the OCSP and included both first ever and recurrent TIA. Both studies involved a consecutive series of patients.

A total of 290 participants were recruited (between 1981 and 1986) to the TIA cohort for the purpose of this study. The aim was to enable the study team to report who had died between the time of the study assessment and the present, and the date and cause of death.

The TIA cohort team is now based at the Nuffield Department of Primary Care Health Sciences at the University of Oxford. The team are currently working on a study called TIA-Survive which explores the long-term outcomes of the original study participants.

TIA-Survive will continue to link the information provided by participants at study visits with NHS Digital’s civil registration data to report the survival rates, and cause of death, for the whole cohort. This work would determine how long people live for following a diagnosis of TIA, and whether they die from stroke-related problems or something else, to help doctors and patients understand more about the condition.

Yielded Benefits:

The only publication to date from the study was published in 2003. The paper was published in the Journal of Neurology, Neurosurgery and Psychiatry and titled 'Long term risks of stroke, myocardial infarction, and vascular death in "low risk" patients with a non-recent transient ischaemic attack'. The paper has been downloaded a total of 3,712 times and has been cited 23 times. This work has added to understanding of the long-term cardiovascular risks in people with a history of TIA. Since 2003, the national stroke strategy, published by the Department of Health in 2007, has aimed to improve outcomes for people with stroke by raising awareness of symptoms and includes earlier diagnosis and management of people with TIA.

Expected Benefits:

Linking mortality data will allow the scientific community to understand more about the impact of TIA on longevity, and the reasons why people died. This type of epidemiological research is important for public understanding of TIA and how things may have improved over time. Prognostic research is important for patients to understand survival times following a vascular event, to clinicians looking after them to enable evidence-based discussions about treatment and outlook and to NHS commissioners to ensure there are appropriate healthcare services for people with TIA.

The updated linking mortality data will allow the University of Oxford to report the survival of the entire cohort. The participants were recruited in the 1980s and well-phenotyped. Outcome data from this period is lacking. Accurate survival rates following a TIA diagnosis, and cause of death, will improve the University of Oxford’s understanding of the pathophysiology of this condition.

Outputs:

The University of Oxford will use the linked civil registration mortality data to report the long-term survival of participants in the cohort. This analysis should take 3 months to complete following receipt of the linked data from NHS Digital. The initial findings from the study will be presented in an abstract for submission to the Society for Academic Primary Care Annual Scientific Meeting in July 2019. The University of Oxford team will also write up the findings into a paper and submit to a peer-reviewed journal for publication such as the European Heart Journal or Stroke. The team hope to have successfully published the work by September 2019. The target audience will be cardiologists, stroke physicians and family doctors caring for patients with TIA and policymakers responsible for planning TIA and stroke services. The team will also work with their patient and public involvement (PPI) representatives to disseminate the findings to the public through PPI newsletters, charity websites and social media when the paper is published.

Following the original study, a paper was published in the Journal of Neurology, Neurosurgery and Psychiatry in 2003 titled 'Long term risks of stroke, myocardial infarction, and vascular death in "low risk" patients with a non-recent transient ischaemic attack'. This is the only output so far from this cohort which is why it is important to report the mortality figures.

Processing:

Prior to 2008, a minimum amount of identifiable data (name, date of birth, NHS number) was shared with ONS to carry out the linkage between the study data and civil registration data. 290 participants records were ‘flagged’ with the Office for National Statistics (ONS) in 1991. ONS notified the study team at the University of Oxford’s Childhood Cancer Research Group (CCRG) of participants’ deaths (date and cause) when they occurred. As soon as the date and cause of death was linked with the participants’ study information, any data that could be used to directly identify individuals (name, date of birth, NHS number) was removed. The ‘flagging for long-term follow up’ service transferred from ONS to the HSCIC in 2008. There are currently 288 individuals from the cohort still flagged on NHS Digital’s system. Data was last supplied in March 2014.

To address the common law duty of confidentially, the University of Oxford have destroyed all fields that NHS Digital have classed as identifiable. This includes identifying details in both the data that NHS Digital (including any predecessor organisations) has provided the University of Oxford and fields that the University of Oxford have obtained from other sources. Only pseudonymised data is now held at the University of Oxford and the University has no means of reidentifying the individuals.

NHS Digital as a trusted party will retain the cohort identifiers as provided under historic Agreements. Under this Agreement pseudonymised Mortality data (including date and cause of death) will be disseminated to the University of Oxford linked via a pseudonymised study ID. No identifiable data is sent to the University of Oxford.

The TIA-Survive project will report the survival rates, and cause of death, for the whole cohort. This work will determine how long people live for following a diagnosis of TIA, and whether they die from stroke-related problems or something else, to help doctors and patients understand more about the condition.

Tracking the Impact of Gestational Age on Health, Educational and Economic outcomes: a Longitudinal Record Linkage Study (TIGAR) — DARS-NIC-09637-Y8T1N

Opt outs honoured: Yes - patient objections upheld (Excuses: Section 251, Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-08 – 2021-07 2018.10 — 2018.12.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Oxford requires a pseudonymised extract of HES data which has previously been linked with birth registration data by City, University of London for a separate project. The University of Oxford require the linked data for part of the analyses required for the TIGAR study (Tracking the Impact of Gestational Age on Health, Educational and Economic outcomes: a Longitudinal Record Linkage Study) which is being conducted by a multidisciplinary team of researchers, led by the National Perinatal Epidemiology Unit (NPEU) at the University of Oxford.

The overall purpose of the TIGAR study is to investigate the effect of gestational age on health, educational and economic outcomes up to age 11 years. The intention is that subject to obtaining the necessary approvals, the data can be linked with education data. However, approval to perform that linkage is not granted under this Data Sharing Agreement. In lieu of the necessary approvals, the University of Oxford will use an extract of the linked HES and birth registration data for the investigation of the effect of gestational age on health and economic outcomes only. The rest of this application refers to the health and economic analyses only.

The organisations involved in this study are ONS (data processor) and the University of Oxford.

The linked data which is stored at ONS includes data from birth registrations, NN4B (National Number for Babies), HES (birth records and subsequent hospital admissions) and a variable that includes the age at death in months for those children who have died. Under another Data Sharing Agreement (DARS-NIC-10094-P6P4B) selected researchers from the TIGAR study team have had access to the linked data, including identifiers, at the secure ONS SRS facilities (previously known as ‘VML’) in order to check the matching between birth registration and HES data. Once this process is complete and a ‘clean linked dataset’ has been produced, the University of Oxford would receive a pseudonymised extract of data which will be analysed (i.e. statistical analyses for health and economic aspects of the study) at the secure ONS SRS facilities for the purposes of statistical analyses, the results of which would be disseminated at conferences and published in journal articles.

The reason for undertaking the work described is that it forms part of the TIGAR study. TIGAR is being funded by the UK Medical Research Council. It is being led by the NPEU, University of Oxford. TIGAR has had input from the support group 'BLISS for babies born too soon, too small, too sick' and the National Childbirth trust. Two Patient and Public Involvement Groups provide patients’ and parents’ perspectives on all aspects of the project (including the health and economic aspects described here) and will help guide the dissemination of the findings. An Advisory Group of experts (academic, clinical, support group) has also given input on the statistical and health economic analysis plan for the pseudonymised data which is being requested in this application.

The rationale for the TIGAR study is as follows. A typical full term pregnancy lasts about 40 weeks and babies born before 37 weeks of pregnancy are classified as preterm. Preterm birth (PTB) is a major cause of long term loss of human potential. Most preterm babies survive and do very well in the long term, but as a group they have an increased risk of health and neurodevelopmental problems in childhood and adulthood. Even babies who are born just a few weeks early may have more challenges in childhood than those who are born after a full term pregnancy.

Detailed information is needed on the typical health trajectories of children who have been born preterm. This will be used to inform clinical guidelines on which groups of preterm babies should be routinely followed up after birth. It will also be used to prepare health professionals for the type of difficulties preterm children may have as they are growing up and what support they may need. Information is also needed to facilitate the counselling of parents about the types of challenges that preterm children may have later in life – this will help parents be more prepared about what to expect in the future and when to seek help from professionals. Finally, information on the costs associated with prematurity will be used by organisations who plan or deliver health services – this will help ensure that preterm children who need help are identified and given support.

Studies of long term health outcomes following PTB need to be based on large numbers. There have been several large studies of the long term effects of PTB, but their findings may not be generalizable to the current UK population. There is a need for a large UK study to assess the health and economic outcomes, across the whole gestational age spectrum, in a population-based cohort of babies born in the 21st century.

The specific objectives of the TIGAR study (in relation to health and cost outcomes only) are:
1. To estimate the effect of gestational age, across the full spectrum, on hospital admissions in children up to age 11 years. (This will be done by analysis of a pseudonymised extract of the linked data at the ONS SRS).
2. To describe the trajectory of these outcomes in different gestational age-groups of children using ‘growth curve modelling’ methods. (This will be done by analysis of a pseudonymised extract of the linked data at the ONS SRS).
3. To determine whether these effects vary according to markers of socio-economic deprivation and whether there is a gestational age threshold beyond which the impact of gestational age is outweighed by the effects of socio-economic factors. (This will be done by analysis of a pseudonymised extract of the linked data at the ONS SRS).
4. To estimate the economic costs for hospital services in different gestational age-groups during the first 11 years of life, and the incremental costs associated with varying levels of prematurity. (This will be done by analysis of a pseudonymised extract of the linked data at the ONS SRS).

Yielded Benefits:

A good start to the analysis of this large and complex data has been made, but the analysis is still in progress and the papers are not yet complete. The yielded benefits will accrue after publication and dissemination of the findings.

Expected Benefits:

The beneficiaries of the research will be:

i) Children born before full-term and the parents and families who care for them.

ii) Those who provide obstetric, neonatal or paediatric care to those affected by birth before full-term.

iii) Other stakeholders who support families affected by birth before full-term. Stakeholders such as ‘Bliss’ (a charity that supports those affected by preterm birth) have already been identified and Bliss has agreed to support the project. The University of Oxford will use their networks to identify a wider group of stakeholders in health, who can provide input to the project (via the two advisory groups) and ensure that they benefit from the research.

iv) Those involved in resource planning, policy and service provision (such as neonatal and paediatric healthcare services, public health services) and the development of interventions in terms of populations targeted and the content and timing of delivery (for example, whether it is important to focus on children born very preterm, or socially deprived preterm children). This includes services at a national (e.g. NHS) and local level.

For i)-iv) it is difficult to estimate what the exact benefits will be and when they will occur as this will depend on what the results show. However, possible examples might be that particular groups of pregnant women are advised to have induction of labour because the baby is not growing as well as it should be, or that particular groups of premature babies should be routinely followed-up and assessed by doctors and other health professionals. The pathway for putting in practice any findings or recommendations to change clinical practice would be the inclusion of the results in national clinical guidelines such as NICE and the Royal College of Obstetrics and Gynaecology Greentop Guidelines. The relevant charities such as those who support parents of premature babies may also add this new information to their website.

Outputs:

The specific outputs from the pseudonymised extract of the linked database will be scientific papers, conference presentations, and a lay summary/report:

The scientific papers and conference presentations will be aimed at the clinicians who provide obstetric, neonatal or paediatric care to those affected by birth before full-term. Results will also be disseminated to those involved in resource planning, policy and service provision and the development of interventions in terms of populations targeted and the content and timing of delivery. This includes services at a national (e.g. NHS) and local level.

The conferences will be chosen depending on what the key findings are and to which target audience. They will be most relevant in order to maximise the potential benefits of the research. Possible conferences include the European Congress of Perinatal Medicine (targeting obstetricians and neonatologists), the European Society for Paediatric Research (targeting paediatricians and those involved in child follow-up) and the Society for Social Medicine (targeting researchers in public health, epidemiology and health economics).

• The lay summary will be disseminated to families affected by birth before full-term using Patient and Public Involvement (PPI) groups (parents, National Childbirth Trust (NCT) representatives) and other stakeholders such as ‘Bliss’ (a charity that supports those affected by preterm birth).

It is expected that the first paper will be drafted and submitted for publication in late 2018 / early 2019, with further papers published between 2018 and 2020, assuming that we have access to the pseudonymised data is received in the summer of 2018.

The scientific papers will be published in Open Access journals and the report and lay summary will be freely available as pdf documents which can be downloaded from the TIGAR website (www.npeu.ox.ac.uk/tigar). When each paper is published, information will be posted on the NPEU website (https://www.npeu.ox.ac.uk/) and the TIGAR team will liaise with the University of Oxford Press Office to help disseminate to a wider audience via media interviews, etc. Finally, input will be sought from the TIGAR Advisory Group and PPI groups regarding other methods of dissemination, particularly targeting those who would be most interested in the findings.

All of the above outputs will contain only aggregate level data with small numbers suppressed in line with the HES analysis guide.

Processing:

Under a separate Data Sharing Agreement (ref: DARS-NIC-10094-P6P4B) birth registration data for all births in England and Wales in 2005-2007 have already been linked with the NN4B and HES maternity datasets by two of the TIGAR co-investigators. As part of an NIHR-funded project, they have updated this dataset to include births in 2008-2012 and linkage to subsequent HES data about admissions of the children to hospital for in-patient or day case care (data from 2004-05 to 2014-15). This is the 'master' dataset referred to as 'Baby Cohort'.

In order to apply the latest national opt-outs, it will be necessary for the following steps to take place before access is granted:
1. ONS will supply a list of pseudonymised HESIDs for all individuals born in 2005 or 2006 from the data it currently holds (under Agreement DARS- NIC-10094-P6P4B) to NHS Digital;
2. NHS Digital will decrypt these IDs to reidentify the individuals and apply the latest national opt-outs;
3. NHS Digital will re-encrypt the IDs using the same encryption (pseudonymisation) key as before and supply to ONS a list of pseudo-HESIDs omitting the IDs of any individual who has registered a national opt-out.
4. ONS will extract the pseudonymised data linked with the returned pseudonymised HESIDs only and make that data available for the researchers from the University of Oxford to access within the SRS. This will include all HES episodes from 2004/05 to 2014/15 for any individual born in 2005 or 2006 whose pseudonymised HESID was in the file returned by NHS Digital.
5. ONS will create two unique pseudo-new identifiers (e.g. random numbers) for each child. These are known as tigarid and linkid. One of the pseudo-IDs (linkid) is intended for use by ONS to facilitate future data linkages and the other (tigarid) will facilitate future linkages with the extract being supplied under this Agreement. No additional data linkages are authorised under this Data Sharing Agreement and a separate application would be made to NHS Digital to undertake further linkage if/when required.

This pseudonymised extract of the data will be released for analysis within the ONS SRS facilities. This extract will be analysed by the TIGAR team at the ONS SRS in order to achieve the specific objectives described above.

The data will only be accessed by individuals within the TIGAR study team for the purposes described, all of whom are substantive employees of the University of Oxford.

All organisations party to this Agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract - i.e. employees, agents and contractors of the Data Recipient who may have access to that data).

MR1447 - Long-term follow-up of Asymptomatic Carotid Surgery Trial (ACST-1) — DARS-NIC-78397-Z1F1Q

Opt outs honoured: Y, N (Excuses: Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2019-02 – 2022-01 2017.09 — 2018.09.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Mental Health and Learning Disabilities Data Set
  2. Hospital Episode Statistics Accident and Emergency
  3. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  4. Hospital Episode Statistics Outpatients
  5. Mental Health Minimum Data Set
  6. Hospital Episode Statistics Admitted Patient Care
  7. MRIS - Flagging Current Status Report
  8. MRIS - Cause of Death Report
  9. MRIS - Bespoke
  10. Hospital Episode Statistics Accident and Emergency (HES A and E)
  11. Hospital Episode Statistics Admitted Patient Care (HES APC)
  12. Hospital Episode Statistics Outpatients (HES OP)
  13. Mental Health and Learning Disabilities Data Set (MHLDDS)
  14. Mental Health Minimum Data Set (MHMDS)

Type of data: Identifiable

Objectives:

Stroke is the third leading cause of disability and premature death worldwide, Around 20% of all strokes are caused by narrowing of carotid arteries, when fatty deposits break off from such lesions and lodge in the brain, thereby causing a stroke and over 80% of these carotid related strokes occur without warning. ACST-1 showed that preventative surgery to remove carotid narrowing (carotid endarterectomy) halves the risk of stroke up to 10-years following a successful procedure and these operations are performed widely worldwide (around 200,000 per year in US and Europe). There is a strong association between carotid stenosis and dementia, but (unlike the link between carotid disease and stroke) it is not clear if this association is causal, and whether carotid surgery could also prevent cognitive decline. Determination of causality requires randomised evidence, and this is the purpose of this study.

ACST-1 (ISRCTN26156392), randomly allocated 3120 participants with asymptomatic narrowing of the carotid artery to carotid surgery (endarterectomy) plus best medical therapy or to best medical therapy alone. Procedural complications (i.e. those occurring within 1 month) were recorded by surgeons collaborating in the trial, and thereafter participants informed the trial coordinators of any late strokes by means of an annual postal questionnaire, the last of which was mailed in 2008. Cause specific mortality was also provided by ONS for the 1069 UK participants. The relationship between carotid disease and dementia was not well recognised when ACST-1 was designed in the early 1990s, nor was dementia the major public health priority that it now is. Accordingly, ACST-1 did not routinely collect information on cognitive decline. However, this trial provides a unique opportunity to reliably assess the effect of carotid surgery on dementia. This question is also being assessed (at considerable expense) by a similar trial currently underway in North America (CREST-2), but meaningful results may only emerge in around 10 years’ time.

This work will be conducted by the MRC Population Health Research Unit, Clinical Trial Service Unit (CTSU), Nuffield Department of Population Health, which is based at the University of Oxford. The aim of the Unit is to generate and disseminate reliable evidence from observational epidemiology and from randomised trials that leads to practicable methods of avoiding premature death and disability. Prevention of premature vascular death and morbidity is a major focus of CTSU’s work, and the effects of drugs such as statins and aspirin on dementia are currently being investigated (led by members of CTSU). Consequently, the proposed study fits within an established research program, and the required specialist skills and knowledge exist at CTSU.

Whilst CTSU have data on stroke rates at up to 10-years post-surgery, CTSU did not collect information on incident dementia during ACST-1 follow-up which ended in 2008, and CTSU have no information on any health outcomes after 2008. Indirect follow-up via routinely collected health records is necessary to assess rates of dementia in this cohort of participants thereby allowing a complete and unbiased follow-up of the UK ACST-1 participants.

The data held prior to 2008 does not contain information on incident dementia. The CTSU seeks data on dementia from before this date as well as after to answer an additional question on whether patients who had carotid surgery (endarterectomy) in the original cohort also had a lower risk of contracting dementia.

Dementia is an insidious process which takes a number of years (usually decades) to develop which is why if only a short time was requested CTSU would miss potential dementia and stroke diagnoses. The risk of stroke and dementia increases with age which is why this is such an important study in a high-risk elderly cohort. CTSU know that the 5 and 10 year results of ACST-1 trial highlighted the benefit of carotid endarterectomy however CTSU do not know the longer term and potentially enhanced benefits seen at >20 years post-intervention. Data on incident dementia is required going back to as early as possible for this reason.

ACST-1 Long-term follow-up study is funded by an Alzheimer’s Society project grant and also by core funding from the Clinical Trial Service Unit (CTSU), University of Oxford.

Yielded Benefits:

Preliminary dementia diagnosis and methodology data presented at the Alzheimer's Society Annual Meeting in 22-23 May 2018 Long-term (15 year) stroke risk/outcome for ACST-1; long-term persistence of the early benefits presented at the European Cardiology Congress, Munich August 2018 Publications not finalised as yet as analyses still ongoing.

Expected Benefits:

The ACST-1 trial showed that early carotid surgery prevents future fatal and disabling strokes for at least 10 years. This finding changed clinical practice worldwide, with rates of asymptomatic carotid intervention rising sharply in the UK and Europe. However, due to improvements in medical therapy (chiefly better lipid-lowering drugs) there is renewed uncertainty about the benefits of preventative carotid surgery and rates of intervention are falling (particularly in the UK). If this study shows an additional benefit of carotid surgery on dementia risk (NB: Statins do not protect against dementia in several very large randomised trials), then rates of carotid intervention may rise again, thereby preventing large numbers of strokes and also helping to prevent dementia. Rates may rise once advisory boards have been notified. This is common practice in any change of medical practice. E.g. NICE, and the Royal College of Surgeons will need to be involved to advise on the best treatment dependent on results.

CTSU know that at 5 and 10 years, carotid endarterectomy reduces stroke (Lancet 2004, 2010). However CTSU do not know whether it still reduces stroke rates in the longer-term (e.g. median 22 years). In addition, no other large randomized controlled trial has investigated whether this type of surgery reduces the rate of dementia with results within the next year. No other surgical study has looked at dementia. This is the first and CTSU have a large cohort. There are other surgical studies looking at dementia but their results will not be available for a number of years. The ACST-1 trial 5, and 10 year results (Lancet 2004, 2010) showed that surgery reduced the risk of stroke at 5 and 10 years after the operation substantially and changed medical practice worldwide. CTSU anticipate that the results of this long-term study will have a similar impact.

Dementia develops over many years, and intervention may take a long time to have an effect so long-term follow-up is vital. The ACST-1 trial has >15 years of follow up and is therefore uniquely placed to help answer the question of whether increased rates of carotid intervention prevent large numbers of strokes and help prevent dementia. It may be able to detect an effect of carotid intervention on dementia more reliably than any previous study. The study is funded by a grant from the Alzheimer’s Society who supports this research question as part of their emphasis on dementia prevention and also by the University of Oxford as sponsor*, the Clinical Trials Service Unit and the Nuffield Dept. of Population Health.

*'Sponsor' in this context means the legal establishment which:
• takes legal responsibility for initiation and management of the study;
• provides insurance for the study;
• is required for all clinical research not just trials
• is not necessarily the funder. Many funding bodies are unable to provide Sponsorship.

Outputs:

All outputs will consist of aggregate data only with small numbers suppressed in line with the HES analysis guide.

Results of the analyses will be presented at relevant international scientific meetings 2018-2019. The results of this analysis will be posted on the ACST-1 section of website www.acst-2.org in a similar manner to multiple previous ACST-1-related publications and will also be available through the ISRCTN registry. The target time frame for publication of the results of analyses is 2018-2020.

If ACST-1 can reliably demonstrate that carotid intervention (carotid endarterectomy or carotid stenting) in middle age leads to a reduction in the risk of dementia, stroke or death in the longer term this may increase the number of carotid interventions performed and help patients make better decisions about their treatment. The outcome of the research will inform clinicians and patients about potential preventative treatment pathways. Any change in medical practice will need to be discussed with advisory boards (eg, NICE) but patients will be informed of the outcome in discussions with their doctor. Alzheimer’s Society have provided CTSU a lay network monitors and CTSU will be taking on their advice with regard to disseminating this information into the public forum.

The results will be presented during 2018 at international scientific meetings and published in a prominent peer-reviewed medical journal by 2019. The results of the research will be disseminated in leading peer-reviewed, high impact-factor journals and conferences including the American Heart Association, UK Stroke Forum, European Society of Cardiology, European Society for Vascular Surgery and the European Stroke Organisation Conference.

Processing:

The data supplied to NHS Digital by CTSU for each participant will be: unique ACST-1 trial Identifier (ID); first and last name; date of birth, and NHS number. The data will be in an encrypted format via the Oxford secure data transfer system.

The data received back from NHS Digital will include the ACST-1 trial ID, date of birth (as provided by CTSU), gender, and outcomes of potential relevance (e.g. strokes and dementia) from the following datasets: HES Admitted Patient Care, HES Outpatients, and A&E, Mental Health, and Date of Death (obtained from demographics). The data will be securely transferred to the secure database at Clinical Trial Service Unit (CTSU), Richard Doll Building, University of Oxford. Upon receipt, these data will be entered into the existing ACST-1 trial database, and hence will remain identifiable. However, access to this database is tightly restricted, and any outputs are aggregated and entirely non-identifiable.

Date of birth is required back from NHS Digital in order apply a two-fold validation of the individual records by linking participants in the original trial dataset with their health recorded in the hospital episode statistics. This is due to policy at CTSU to employ rigorous data-checking procedures for all imported data. By doing this, CTSU can have higher confidence that matching of data is accurate.

The ACST-1 trial has a study specific database that is password protected and held securely on one University drive only. The ACST-1 database contains detail from the original ASCT-1 study where members are archived according to the original paper consent forms and records. These records include full name and date of birth but these are the only identifiable data contained within the ACST-1 database. The identifiable HES data will be stored in an encrypted TrueCrypt container where all such access will be granted on the instruction of the Information Asset Owner for ACST-1. The database with imported NHS Digital information will be modified and only Trial ID and age will be used in the database for analysis. Pseudonymised data (with exception to date of death) will only be available for analysis. Access is routinely reviewed and revoked when the team member leaves ACST-1. Only personnel substantively employed by the University of Oxford and are involved in this long-term follow-up study for ACST-1 study (processing and analysing data) will have access to this data.

The data received will be combined with existing information on rates of stroke, other vascular disease and death (obtained previously up to 2008) and used to compare rates of dementia (and also stroke) amongst participants originally allocated to undergo carotid surgery versus those managed with medical therapy alone (i.e. intention-to-treat analyses).

The ACST-1 study team shall not make the data provided by NHS Digital available to any third party or allow use of the data by or on behalf of any third party or for any purpose other than those described, in whole or in part or as linked data within the ACST-1 database.

Total hip arthroplasty versus hemiarthroplasty for independently mobile older adults with an intracapsular hip fracture. — DARS-NIC-61090-T9Y0G

Opt outs honoured: Y (Excuses: Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(7)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2018-11 – 2020-10 2017.12 — 2018.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Office for National Statistics Mortality Data
  3. Bridge file: Hospital Episode Statistics to Mortality Data from the Office of National Statistics
  4. Civil Registration (Deaths) - Secondary Care Cut
  5. HES:Civil Registration (Deaths) bridge
  6. Civil Registrations of Death - Secondary Care Cut
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

This study aims to examine a guideline published by the National Institute for Health and Clinical Excellence (NICE) with regards treatment of patients with hip fractures.

There are 70,000 hip fractures every year in the United Kingdom at a total cost exceeding £2 billion. Mortality is high, with 8.5% of patients dying within 30 days of admission and 30% within a year. Many surviving patients are unable to continue living independently and 4.5 million patients are disabled worldwide as a consequence of hip fracture every year.

Two thirds of hip fractures are displaced, i.e. there is separation of the bony fragments, and these are usually treated with arthroplasty (joint replacement). There are broadly two arthroplasty options: total hip arthroplasty (THA) in which both the femoral head and acetabulum are replaced and hemiarthroplasty (HA) in which only the femoral head is replaced.

There have been a number of small, randomised controlled trials that compared THA to HA. When taken together, they suggest that THA is associated with better functional outcomes, fewer wound infections, and reduced need for secondary procedures. However, THA is a longer operation, more complex, and has a significantly higher risk of subsequent dislocation (9% versus 3%). THA is also a more specialised operation that might not be within the skillset of every orthopaedic surgeon treating patients with hip fractures. Despite the existing evidence base, one recent survey found that 73% of orthopaedic surgeons prefer HA to THA.

The National Institute for Health and Clinical Excellence (NICE) has elected to reserve THA for the fittest patients as they are more likely to survive a prolonged operation and gain the most from its enhanced functional properties. NICE recommend that patients with displaced hip fractures should be treated with arthroplasty and THA offered to patients who:

• Could walk independently before the fracture;
• Are not cognitively impaired and;
• Are medically fit for anaesthesia and the procedure.

Despite this guidance, the NICE criteria are not universally applied throughout the NHS. In particular, there is evidence that surgeons incorporate other considerations (including patient age and admission at the weekend) into their decision-making. The University of Oxford have previously shown that this leads to considerable variation across the country in terms of which treatment is offered to patients with hip fracture.

In this study, the University will use linked NHS datasets (the National Hip Fracture Database and Hospital Episode Statistics) to test two related hypotheses:

1. THA is associated with better outcomes than HA for independently mobile older adults with hip fractures, i.e. patients satisfying the criteria proposed by NICE.
2. Patients that receive an operation that is non-compliant with NICE guidance (i.e. HA despite being eligible for THA or THA despite being ineligible) will have worse outcomes than those receiving NICE-compliant treatment.

The data requested from NHS Digital are necessary to (a) aid risk adjustment by enriching the NHFD with details of patients' co-morbidities and (b) provide data about re-admission to hospital and re-operation for patients in the NHFD cohort.

Yielded Benefits:

The data for this study were only received in February 2018 and, although it has been analysed, it has not yet been published.

Expected Benefits:

The University anticipate the findings of the study informing the next iterations of NICE Clinical Guideline [CG124] "Hip fracture: management", the British Orthopaedic Association (BOA) Standards for Trauma 1, and the BOA/British Geriatric Society Blue Book: "Care of patients with a fragility fractures”. These are all due for revision in, or shortly after, 2017. The findings of the study should therefore begin having an impact on the health status of patients (by ensuring they are offered the most appropriate operation) within two years. This is clearly important to ensure that patients are being offered the most effective choice of operation after a broken hip.

Importantly, once the NHFD-HES data linkage has been established, this resource could be used to address other important clinical questions aimed at improving outcomes for older adults with hip fractures. Any further use of the resource would result in amendment requests to NHS Digital

Outputs:

The University anticipate presenting the results at the British Orthopaedic Association Annual Congress 2018 and publishing in a journal that is most likely to reach the broadest possible audience of UK orthopaedic surgeons, e.g. the Bone & Joint Journal. The findings will also be communicated directly to the guideline teams at the National Institute for Health and Clinical Excellence (NICE), British Geriatric Society (BGS), and British Orthopaedic Association.

If it is found that compliance with this NICE guideline benefits patients, the study will advocate for greater compliance among orthopaedic surgeons and wider access to THA among hip fracture patients. If the findings suggest that THA makes little difference to patient outcomes, the study will suggest that this guideline be reconsidered by NICE.

The study ultimately hopes to influence the advice provided to clinicians as part of NICE Clinical Guideline [CG124] "Hip fracture: management", the British Orthopaedic Association (BOA) Standards for Trauma 1, and the BOA/British Geriatric Society Blue Book: "Care of patients with a fragility fractures”.

All outputs will be aggregated with small numbers suppressed in line with the HES Analysis guide.

Processing:

In this study, the University will use linked NHS datasets, the National Hip Fracture Database from the Healthcare Quality Improvement Programme and Hospital Episode Statistics from NHS Digital.

Individual NHS trusts send patient-identifiable information to the Falls and Fragility Fracture Audit Programme (FFFAP, which is run by the Royal College of Physicians [RCP] on behalf of the Healthcare Quality Improvement Programme [HQIP]) to populate the National Hip Fracture Database (NHFD). The NHFD data is processed by Crown Informatics Ltd on behalf of the FFFAP.

Crown Informatics will provide NHS Digital with a list of NHS numbers along with date of birth, postcode, gender (injury date) and a unique ID number from patients that are included within the National Hip Fracture Database (NHFD).

These patients will all have been aged >60 and treated for a hip fracture at a hospital in England from 2011 onwards. Although the NHFD has existed since 2007, data quality improved with the introduction of the Hip Fracture Best Practice Tariff in 2012. The University have therefore opted to restrict their data request to the period from 2011 onwards.

NHS Digital will link these records stored within the Hospital Episode Statistics (HES) admissions file and return pseudonymised HES data and the date of death and the study ID to Crown Informatics. This will include admissions before the hip fracture (as patient co-morbidities will be used for risk adjustment) and afterwards (as re-admission, re-operation, and health service utilisation) will be used as outcome measures. All data analyses will be undertaken using the linked NHFD-HES-ONS dataset.

Crown Informatics will add relevant non identifiable data from the National Hip Fracture Database to the linked database and remove the unique ID. This data (linked pseudo HES+Date of death+NHFD) is then supplied to the University of Oxford for analysis.

Data from the NHFD and NHS Digital will only be stored and accessed by the researchers at the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at the University of Oxford. It will not be linked to any other datasets. It will not be shared with any 3rd parties. The data will only be used for the purposes stated in this agreement.

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

All ONS terms and conditions described in the special conditions section of this agreement will be adhered to .

The role of patient factors, surgical factors and hospital factors upon patient outcomes and NHS costs in the treatment of upper limb musculoskeletal conditions: spatial and longitudinal analysis of routine data. — DARS-NIC-29827-Q8Z7Q

Opt outs honoured: Y (Excuses: Consent (Reasonable Expectation), Does not include the flow of confidential data)

Legal basis: Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2019-01 – 2022-01 2017.12 — 2018.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Office for National Statistics Mortality Data
  2. Hospital Episode Statistics Admitted Patient Care
  3. Bridge file: Hospital Episode Statistics to Mortality Data from the Office of National Statistics
  4. Civil Registration (Deaths) - Secondary Care Cut
  5. HES:Civil Registration (Deaths) bridge
  6. Civil Registrations of Death - Secondary Care Cut
  7. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

Musculoskeletal conditions of the upper limb (arm) are a significant disease burden, affecting all age groups including the working population. Prevalence of conditions affecting the hand such as osteoarthritis and carpal tunnel syndrome are estimated at between 15-36% of the population, causing pain, numbness and loss of function. Shoulder osteoarthritis prevalence is estimated to be as high as 32% in those over 60 years, which stands to increase as the UK population ages. Research also has shown that approximately 20% of the population present to their GP to discuss a musculoskeletal condition each year, with NHS spending totalling over £5 billion annually on musculoskeletal conditions. There has been little research exploring national trends in treatment, outcome or access to care in upper limb musculoskeletal conditions in the UK, and Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS), at University of Oxford believe that research in this field is vital for patients, clinicians and the NHS alike in order to improve patient care, patient information and patient pathways.

Around 5300 shoulder replacement operations now take place each year in the UK and this number is expected to increase, including revision (re-do) surgery. Elbow replacement surgery is rarer with only a few hundred cases per year, but revision rates are thought to be potentially very high and the costs even higher. It is currently difficult to estimate the considerable number of surgeries undertaken for hand and wrist arthritis, as this data is not yet collected into any national database.

Some forms of upper limb arthritis can develop following joint dislocation or injury to the soft tissues. Shoulder rotator cuff tendon tears and joint instability following shoulder joint dislocation are common injuries that may contribute to the development of osteoarthritis. Surgery to repair rotator cuff muscles and to stabilize the shoulder following dislocation seems to be rapidly increasing in recent years. Investigation of the use of these new procedures, and whether they have an impact upon the development of arthritis in later life is not yet known.

In the hand, dupuytrens disease is disorder of the connective tissue (soft tissue) of the hand causing a progressive significant deformity and reduced ability to use the hand. There are a variety of treatment options, ranging from splinting the affected finger, to local injections to break down the abnormal tissue, to surgery to remove it. It is thought that availability of treatment options available varies across the UK. There is an increasing trend in patients being diagnosed with the condition.

Compression of nerves in the arm is very common, and this is called nerve entrapment conditions. Carpal tunnel syndrome and cubital tunnel syndrome being the most common and treatment remains varied, with some patients undergoing local steroid injection and splinting of the affected area, and others proceeding to surgery to stop compression of the nerve. Previous evidence has suggested some nerve entrapment conditions may be related to obesity and diabetes, and therefore the number of patients suffering with the condition is expected to increase. There are some links suggesting development of nerve compression during pregnancy. The interaction between surgery to treat arthritis, and the development of a nerve entrapment condition is not yet understood.

This study aims to investigate the impact of treatment for the most prevalent upper limb conditions and will include investigation of surgical treatment trends, revision surgery trends (in particular upper limb joint replacement surgery) and current resource demands in treating these common conditions. These conditions include osteo- and rheumatoid arthritis of the upper limb joints, shoulder rotator cuff (muscle) tendinopathies and tears, Frozen shoulder, shoulder joint instability (joint dislocation), Dupuytren’s contracture of the hand, and nerve entrapment (nerve compression) syndromes.

AIMS
The main aims of this study are:

1. Investigation of the variation in surgical treatments, revision rates and mortality rates in upper limb conditions
A large variety of new surgical techniques coupled with a rapid expansion of surgical implants mean that many different options exist in the surgical treatment of upper limb conditions. Newer innovative surgical options might enable patients to undergo less invasive surgery with reduced recovery time and improved return of function. Some new techniques aim to prevent disease recurrence or progression. NDORMS wish to investigate these surgical techniques, and the impact upon the need for further interventions following these procedures.

2. Geographical and temporal trends in management and outcome
Having identified the types of surgical intervention undertaken, NDORMS will investigate whether there are temporal or geographical trends associated with intervention type, compared to geographical and temporal trends in disease prevalence. NDORMS will investigate this comparing patient demographics within regions and over time, and produce maps highlighting these trends. NDORMS will also produce maps highlighting variation in length of stay, readmission complication and revision rates across the country as proxy measurements for patient outcome.

3. Assessment of access to care & care costs
Statistical analysis of national data from the HES admissions database will allow identification of hospital organisation and surgical factors that may explain geographical variations in patient outcomes of surgery, after adjustment for patient level case-mix. In this study we aim to identify whether the different ways that hospitals organise services for patients presenting with upper limb conditions can lead to improved patient outcomes, and postulate reasons why outcomes may vary between hospitals or regions. NDORMS will investigate whether these differences cause a variation in access to care, due to disease prevalence, or due to variation in management and how these factors influence the cost of patient care. Greater understanding of trends in how these interventions are being used and the outcomes following them will enable NDORMS to propose changes that will influence health service provision and workforce planning.

This dataset has the unique and exciting opportunity of exploring the changes that have occurred in disease presentation, development, treatment and outcome over an extensive time period. Studies that have follow up of this duration have not been previously undertaken in this country, and undertaking research using routinely collected NHS data will enable us to better understand how to care for patients with upper limb conditions . Long term follow up of surgical interventions allows evaluation of the impact of new techniques and devices, and especially the effect of new implants upon implants failure rates. Analysis of long term outcomes are vital in order to determine which implants and interventions should continue to be used; evidence that is not available elsewhere.

Patient focused priorities for research
NDORMS have recently run a successful James Lind Alliance Priority Setting Partnership (non-profit making initiative to identify and prioritise uncertainties and questions about the effects of treatments) for “Surgery for Common Shoulder Conditions” which brought together patients, carers and clinicians to set the ongoing treatment uncertainties with regards to surgery for common shoulder conditions. These results are now published and highlight research questions that are important for UK patients. This application will help address some of these questions Including; Which shoulder replacement type operation should be undertaken in different patient groups. Due to the short term NJR data this is currently not answerable but HES data over a longer period of time will allow for a separate and much more detailed data interrogation, potentially answering this question and negating the need for an expensive national surgical trial.

Appreciating that the James Lind Alliance Priority Setting Partnership for “Common Hand conditions” is currently underway in the UK but has not yet reported, NDORMS have lead a regional patient and public engagement project in hand surgery. This study has emphasized that improving patient selection for surgery, timing of surgery and type of surgical management undertaken is seen as a priority. NDORMS study will help answer or contribute further important information to those trying to answer these treatment uncertainties.

Alignment with NHS agenda
In the NHS, patients can choose which hospital they want to have their surgery in. Information on access to treatments and the outcomes of surgery between different hospitals would help patients in making their decision. Outcomes of surgery may vary across different regions and hospitals. Any such differences might be explained by a hospital treating more complex and sicker patients, but could also be explained by the surgical techniques employed in different centres, or centralization of care into specialist high volume hospitals. Knowledge of this would inform dashboards and aid NHS managers and clinicians in changing and optimising service organisation to reduce any variations in outcomes.

The national audit into the orthopaedic surgical procedures called Getting It Right First Time (GIRFT) was launched in 2013. Initial results released in March 2015 found large variations in practice, and have called for better research into the timing and types of procedures undertaken. Better understanding of regional and temporal variations in procedures, and which surgical procedures have the best outcomes would improve the quality of patient care in the UK, reduce costs for the NHS and more importantly provide better patient information to inform shared treatment decision making.

This dataset has the unique and exciting opportunity of exploring the changes that have occurred in disease presentation, development, treatment and outcome over an extensive time period. Studies that have follow up of this duration have not been previously undertaken in this country, and undertaking research using routinely collected NHS data will enable the study to better understand how to care for patients with upper limb conditions . Long term follow up of surgical interventions allows evaluation of the impact of new techniques and devices, and especially the effect of new implants upon implants failure rates. Analysis of long term outcomes are vital in order to determine which implants and interventions should continue to be used; evidence that is not available elsewhere.

The predominant method of limiting the data requested is through the study of selected upper limb conditions only, and through only selecting certain procedures. Due to the lack of existing evidence surrounding the role of comorbidities in this research area, it is not advantageous or appropriate to further select a subgroup of patients with certain co-morbidities .

The NJR data for shoulder replacement only began in 2012, and the elbow data began this year. There is no other source available to evaluate implants and procedures used for hand and wrist conditions. Over the time that HES data has been collected, there has been a rapid evolution of the implants available for these procedures, which have yet to be evaluated. The importance of long term data has been shown in other areas of orthopaedics, especially in hip surgical research where metal on metal hip replacements have since been shown to have higher long term failure rate than other implants. A lack of long term data surrounding complications associated with these new implants to treat hip osteoarthritis led to patients undergoing procedures that have since been withdrawn due to excess morbidity associated with their use. This work aims to identify implants and procedures with higher rates of complications using the long term data available in HES APC, to optimise future patient care and prevent harm. This data will not be available in other sources for many years, and therefore this emphasises the real value of the long term data available through using HES to prevent future harm, and why we have specifically chosen to use this dataset for this work.

The hand, wrist and elbow procedures that this study wish to look at have been in use for well over 20 years, and as such the study would like to look specifically at the changes over time in their usage, for example in response to key papers, guidelines, changes in policy. Releasing less data than this would limit the usefulness of the study and the results that we would be able to make to inform future patient care.

Yielded Benefits:

Expected Benefits:

BENEFIT
The study will inform patients, NHS managers, commissioners and health professionals of the NHS costs and patient outcomes and cost-effectiveness associated with the treatment of upper limb conditions, and the key elements that are most clinically and cost effective. It will provide patients with information on variation in outcomes of surgery to inform patient choice and decision-making. NDORMS will work alongside charities and learned societies to disseminate the findings of this study using established platforms that include social media such as Twitter and a study website, as more patients are now turning to these resources for information about planned surgery. NDORMS will provide evidence of modifiable hospital organisational factors that can explain unwarranted geographical variation in patient outcomes of surgery. This can be used to inform healthcare organisations of factors identified as improving patient outcome and both local and national level, and can be used by clinicians and policy makers to inform healthcare policy .

IMPACT
The exploration of current trends in procedures undertaken, in temporal and geographical variation in operation numbers and type, mismatch of prevalence and surgery rates, and of outcomes will enable NDORMS to understand more about the current management of upper limb conditions and how to improve NHS services nationwide. NDORMS will explore variations found to identify whether differences in the way hospitals or regions organise their services, such as specialist surgeons, use of new surgical techniques, or centralising care into specialist hospitals, can explain any observed variations. Similarly, understanding the variation in outcomes following a range of procedures enables greater knowledge of which interventions should continue to be funded. Knowledge of these factors would inform changes that can be made to the way services are organized and provided, leading to better access for patients and helping to standardise evidenced based care and patient pathways across the UK. The target date for output and dissemination to produce measurable benefit is 24 months from receipt of data.

Outputs:

DISSEMINATION PLANS
Throughout all stages of this project, NDORMS will engage with key stakeholders including NHS managers, healthcare professionals, patients and the public for interpretation, dissemination and direct communication of the main findings. This will be facilitated through collaboration with the James Lind Alliance, support of specialist societies, and Patient and Public Involvement (PPI) representation. A Professor of Orthopaedic Surgery at the University of Oxford and a Professor of Plastic Surgery at Oxford University Hospitals NHS trust are named co-applicants on this study and will assist in interpreting and the national dissemination of findings. This project has also been informed by results from the recent James Lind Alliance (JLA) Priority Setting Partnership (PSP) for surgery for common shoulder conditions, carried out within the Oxford NIHR Musculoskeletal BRU and supported by the British Shoulder and Elbow Society (BESS) and the British Orthopaedic Association (BOA). NDORMS shoulder and elbow, and hand and wrist applicants both have national roles and collaborations that provide excellent access and influence to disseminate the study findings nationally and internationally through the following societies and funded research centres:
1. British Elbow and Shoulder Society (BESS) – Dissemination to all British shoulder surgeons and shoulder physiotherapists. Presentation at the National Congress.
2. British Society for Surgery of the Hand (BSSH)- Dissemination to all British hand surgeons and hand therapists. Presentation at the biannual National Congress.
3. NIHR Oxford Biomedical Research Unit/Centre – Dissemination to all linked patient and local GP networks
4. ARUK Centre of Excellence (CoE) for Sports and Exercise Medicine – Dissemination to all patients and professional sporting bodies linked to this CoE.
5. Internationally NDORMS will disseminate through peer review publications and via presentations at the European Shoulder and Elbow Society (SECEC) and the Federation of European Societies for Surgery of the Hand (FESSH)

One of the NDORMS professors using this data has written national guidelines for NICE and the specialist societies on managing many shoulder conditions including authoring national commissioning guidelines. This study will allow evidence-based updating of these guidelines will be able to influence these as an Executive Council member of BESS and the BESS Quality Outcomes Lead.

Dominic Furness, a senior researcher on the application, is a member of the British Society for Surgery of the Hand (BSSH) Research Committee, and will use the aggregated, anonymised results generated from this study to influence practice nationwide. BSSH is in the process of gaining accreditation from NICE for guideline development and NDORMS anticipate this to be in place by the time the results of this work are published.

Working with and informing all stakeholders will remain an important part of NDORMS dissemination plans. NDORMS recognize the importance of meaningful PPI involvement and have worked collaboratively with the PPI Officer at NIHR Research Design Service (RDS) to identify individuals to become involved, and NDORMS Director of Patient Involvement at the Oxford NIHR BRC. NDORMS have identified three lay people who understand the needs and problems of upper limb conditions. Through their involvement and recommendations regarding the dissemination of findings, NDORMS will ensure results are readily available and interpretable to the wider patient and public community.

NDORMS shall disseminate findings in peer-reviewed journals, at national and international conferences, and inform learned societies that include the British Orthopaedic Association, The British Shoulder and Elbow Society (BESS), British Society for Surgery of the Hand (BSSH), Arthritis Research UK, rheumatology (British Society for Rheumatology), care of the elderly (British Society of Geriatrics). NDORMS will work alongside charities and learned societies to disseminate the findings of this study using established platforms that include social media such as Twitter and a study website, as more patients are now turning to these resources for information about planned surgery.

Based on the findings NDORMS will write scientific papers for submission to high quality peer-reviewed journals. NDORMS will also present findings to professionals at conferences and meetings, will develop Plain English summaries of findings for communication to patients and members of the public . All outputs will adhere to HES analysis guide so that data is only shown in aggregate form with small numbers supressed. NDORMS will publish a full and complete account of that research in the NIHR HS&DR Journal, ensuring the research is reported fully, and publicly available via the NIHR Journals Library website and Europe PubMed Central. A webpage will be developed within the NDORMS website specifically for this study in order to further transmit the results to the public. This study aims to capture the attention of patients and the public by presenting the long term results of surgery for upper limb conditions in the UK not previously undertaken, and to also present the potential reasons why there may be variation in outcomes following surgery. Previous PPI work has shown that variation in disease progression, and outcome following intervention is of particular interest to patients and the public.

The target date is 24-months following receipt of the data.

Processing:

Upon receiving the data from NHS Digital, a senior data manager with experience in managing HES datasets will process the raw data into smaller extracts. Smaller extracts will be made available for analysis based upon disease pathology and surgical intervention undertaken. This will enable the separate research questions defined by the aims of the study to be answered.

NDORMS will provide data at the small area level presented as maps to describe variation in outcomes, before and after accounting for these organisational and surgical factors. All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide. All processing of ONS data will be in line with ONS standard conditions. NDORMS will also focus on variation in outcomes of specific patient groups (old and frail with co-morbidities and obese) and present evidence as to whether the introduction of new surgical innovations (e.g. minimally invasive surgery), and centralisation of services, has led to improved patient outcomes. ONS mortality data for the patients selected will enable analysis of associations between surgery and death rates. Investigation of spatial and longitudinal trends in mortality will also be studied .

Multilevel regression modeling of HES data will assess the association of surgical factors on patient outcomes of surgery, adjusting for patient case-mix. Random intercept models will explore geographical variation in outcomes across hospital trusts and Clinical Commissioning Groups. Geographical Information Systems will be used to produce maps depicting variation in outcomes, and graphically display the influence these factors have on explaining such variation.

NDORMS will then use a natural experimental study design to specifically examine the impact that the new treatments have had on NHS resource use, NHS costs and patient outcomes (based upon length of stay, complications, readmission, further surgical intervention including revision surgery). Interrupted time series analysis will examine changes in secular trends in outcomes and NHS costs before and after the introduction of the new treatments. There will be a focus on the benefit of the new treatments to specific patient groups such as frail older people with complex co-morbid conditions. An economic evaluation will describe the hospital NHS costs, patient health related quality of life and cost effectiveness that reflect the new treatments for upper limb conditions. The predominant method of limiting the data requested is through the study of selected upper limb conditions only, and through only selecting certain procedures. Due to the lack of existing evidence surrounding the role of comorbidities in this research area, it is not advantageous or appropriate to further select a subgroup of patients with certain co-morbidities .

A cost-effectiveness analysis will be performed to estimate the economic burden of conservative and surgical care in relation to trends in outcome, adjusting for socioeconomic status and case-mix. This is largely unexplored to date and essential for further studies potentially exploring the cost-effectiveness of the surgical intervention.

Once data has been disseminated to the study;

- The HES datasets will be held on a password protected University Computer on an encrypted drive at the Botnar Research Centre, Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS).

- Only authorised users where they hold Approved researcher status for the ONS data will have access to the data, these users will change their password every 90 days, according to the IG guidelines of the Big Health Data Group (BHDG).

- The data will be managed by a statistician based at the Botnar Research Centre Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS) University of Oxford.

- The data will be used exclusively for the purpose of this project

- At the end of the study, the data will be safely held in a password protected University Computer at the Botnar Research Centre, for further 36 months, and assessed only to answer questions arising from the publication and other publicity.

All processing of ONS data is in accordance with standard ONS terms and conditions.

All data will be processed only by substantive employees of University of Oxford.

Data will not be linked to any other record level data, no attempts will be made to identify any individual from the data being supplied, and there will be no onward disclosure of record level data.

MR1407 - Study of Heart and Renal Protection (SHARP) Intrial — DARS-NIC-13172-S1S3F

Opt outs honoured: Y (Excuses: Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2018-05 – 2021-05 2017.06 — 2017.11.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. MRIS - Cause of Death Report
  3. MRIS - Flagging Current Status Report
  4. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Identifiable

Objectives:

The Clinical Trial Service Unit has extensive experience in developing and running large-scale streamlined randomized trials, many of which have significantly changed clinical practice and majorly influenced national and international guidelines. One of these trials was the Study of Heart and Renal Protection (SHARP), which is the largest trial to date worldwide in patients with chronic kidney disease (CKD), and involved >9000 participants.

The SHARP trial was carried out in 18 countries with 1,987 people in the United Kingdom being randomized. It assessed the effect of lowering LDL cholesterol with a combination of simvastatin 20mg plus ezetimibe 10mg versus a matching placebo on serious vascular disease (e.g. heart attacks, strokes) and renal disease (e.g. starting dialysis) events. Participants were followed regularly in study clinics, with all serious adverse events being recorded. Those events which were pre-specified as study outcomes were confirmed by central review of hospital notes by study doctors. This process is referred to as clinical adjudication.

Such outcome measure adjudication is typically seen as the ‘gold standard’ for assessment of study outcomes. However it is very resource intensive and expensive, and took a team of trained clinicians two years to complete for the SHARP trial. Such increasing cost of research is a contemporary major issue for all researchers conducting trials. If it can be demonstrated that reports from routine healthcare data-sets are complete and reliable compared with nurse reported events and/or the final adjudicated outcomes, future trials could be designed which follow-up participants solely through routine healthcare data.

There are examples where routinely collected healthcare data has been compared to study outcomes previously and they have demonstrated that using routinely collected data to record study outcomes can be reliable which could greatly simplify future trial design, and as such benefit patients and the public. However, there are limited such examples in people with renal disease, where complex disease presentations make some researchers doubt the reliability and therefore utility of routinely collected healthcare data. Moreover, people with chronic kidney disease – who have substantially increased morbidity and mortality compared with the general population - are often excluded from large randomized trials. Consequently, in renal disease, there is a mismatch between high clinical need and levels of evidence on which to base clinical care.

There is, therefore, a particular need to develop novel ways of conducting affordable trials of both old and new treatments in this patient group. An example is the NIHR-funded SIMPLIFIED trial http://www.phpc.cam.ac.uk/pcu/research/research-projects-list/other-projects/simplified/) which is assessing the effect of high-dose native vitamin D versus standard of care in dialysis patients. The primary outcome is all-cause mortality, however such a trial could become much more informative if the value of routinely collected hospitalisation data can be confirmed by this proposed study, and so the effect of high dose vitamin D on other non-fatal outcomes such as vascular disease, can be tested. The SHARP trial dataset is in a unique position to validate such methods for both SIMPLIFIED and other future renal trials.

This project seeks to obtain all relevant registry associated outcomes from healthcare data sources at NHS Digital so as to compare the outcome data collected and adjudicated during SHARP with those collected as part of routine practice. To ensure the completeness of the comparison, in addition to hospital episode statistics (HES), all relevant death and cancers data are also requested.

Methods:
This study aims to compare the validity of registry data with both the nurse-led reporting of adverse events, as well as clinically adjudicated outcomes. The main focus will be on non-fatal outcomes (where there is more doubt of validity) derived from registry data including:
• major cardiac events
• stroke and its subtypes
• revascularisation procedures
• end-stage renal disease events
• admissions with acute kidney injury and
• a range of infections including opportunistic infections unique to immunosuppressed transplant recipients and more common infections
This will involve an evaluation of the specificity and sensitivity of registry data derived outcomes, looking at both the occurrence of events and the time frame in which they occurred. Results of the original trial will be compared against replicated results using registry data derived outcomes.

Yielded Benefits:

Project ongoing.

Expected Benefits:

Clinical trials are a pivotal part of evidence-based medicine but their rising costs are problematic and hampering research. If this project’s results indicate that routinely collected healthcare data is as robust as clinical adjudication, this would potentially result in very substantial efficiency savings for future trials as;

1, Collection of trial events and trial event adjudication (which requires training and employment of skilled staff) will be greatly streamlined
2. The need for trial participants to attend study clinics (which can be onerous and expensive if travel costs are not reimbursed) may be reduced

This in turn will enable such future research to be conducted on a greatly reduced budget, which is vital given the limited funding that national and charity funding bodies can typically offer.

This may be particularly important for trials of generic drugs in common conditions (e.g. aspirin in cancer prevention) which do not currently attract industry funding.

Such methodological research is becoming increasingly important to the efficiency, design and data collection strategies of future trials and studies, and hence will be of benefit to public health at home and abroad.

In summary, expected benefits include;

Researchers/health and social care;
1. reduced costs
2. Greater efficiency leading to increased throughput of research and associated enhancement of evidence based medicine, with impact upon national clinical guidelines
3. Increased awareness of the potential for routinely collected data to augment existing understanding and knowledge of a therapeutic area

Patients;
1. Reduction in the demands upon trial participants in terms of time and inconvenience in attending study visits
2. Increased knowledge which will be used to inform healthcare decisions leading to improved quality of patient care

Outputs:

Results of the analyses will be presented at relevant international scientific meetings, such as the International Clinical Trials Methodology Conference and in peer reviewed journals, e.g. Clinical Trials, CJASN (Clinical Journal of the American Society of Nephrology) and NDT (Nephrology Dialysis Transplantation). These will be targeted to ensure that the results are disseminated widely among the clinical trials community, including the MRC Hub for Trial Methodology Research and UK Kidney Research Consortium Clinical Trial Network.

The results of these analyses will be posted on the SHARP website (http://www.sharpinfo.org/) in a similar manner to multiple previous SHARP-related publications.

The target time frame for publication of the results of analyses is 2019-2021.

Processing:

The data will be accessed only by substantive employees of Oxford University and only for the purposes described in this document.

NHSDigital already hold the cohort data and will link this in a one off extract with mortality, cancer and HES data

Data supplied by NHS Digital will be psuedonymised HES data, identifiable mortality and cancer data all supplied with a study ID. The researchers will compare the NHS Digital data with the existing SHARP trial analysis database which includes:
• Unique study Patient ID
• Clinical data on clinical events
• Laboratory results
• Study treatment

The data supplied for the purpose described in this document will not be linked to the data being held for the post trial follow up held under Data Sharing Agreement NIC 147782.

University of Oxford will adhere to the Office for National Statistics standard terms and conditions as described in the special conditions in the Data Sharing Agreement.

Knee Arthroscopy and Knee Arthroplasty - Rates of Surgery, Outcomes, Complications — DARS-NIC-68703-R4Y6C

Opt outs honoured: N, Y (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2018-11 – 2020-11 2017.06 — 2017.08.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Office for National Statistics Mortality Data (linkable to HES)
  3. Civil Registration (Deaths) - Secondary Care Cut
  4. HES:Civil Registration (Deaths) bridge
  5. Civil Registrations of Death - Secondary Care Cut
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The purpose of this application is to support a University of Oxford’s Big Health Data Group (BHDG) study of knee arthroscopy surgery.

The study will require HES Inpatient and ONS mortality data.

The study will be performed by employees of the University of Oxford at the Botnar Research Centre, Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS).

Knee arthroscopy is a very commonly performed procedure and around 150,000 knee arthroscopies are performed in England every year. Despite the frequency with which the procedure is performed, data on the risks and complications associated with the procedure is limited.

In relatively small cohort studies, arthroscopic surgical procedures such as meniscectomy and anterior cruciate ligament (ACL) reconstruction have been shown to be associated with the subsequent development of osteoarthritis. There is also high-level evidence to suggest that many arthroscopic procedures (such as knee washout and meniscectomy) are ineffective if performed on patients with osteoarthritis. These patients may be more appropriately managed with other interventions such as physiotherapy or knee replacement.

Data demonstrates the number of knee arthroscopies performed each year is rising, especially in older age groups and a key objective of the proposal is to investigate the historical trends in arthroscopy practice and the factors underlying this. It is highly likely that knee arthroscopy is being over-performed. This study proposes to determine the rate of complications (such a venous thromboembolism, stroke, heart attack, death) that occurs following knee arthroscopy. The study also propose to investigate the association of the procedure with a diagnosis of osteoarthritis and with further procedures such as repeat arthroscopy or knee replacement. For patients subsequently undergoing knee replacement the study wishes to determine if previous knee arthroscopy is associated with any subsequent complications. The study will compare patients undergoing early joint replacement after arthroscopy (e.g. within 90 days) to those undergoing later joint replacement (e.g. after 2 years). The study will compare the outcomes of all knee replacement patients previously undergoing knee arthroscopy to those not previously undergoing knee arthroscopy. For this the study the University of Oxford require all inpatient and ONS data for all knee replacement (total or uni-compartment) patients.

The role of arthroscopic treatment in the management of early osteoarthritis has been highlighted as a Top 10 research priority in the recently published James Lind Alliance (JLA) Priority Setting Partnership on Early Osteoarthritis. The James Lind Alliance (JLA) is a non-profit making NIHR supported initiative which brings patients, carers and clinicians together in Priority Setting Partnerships (PSPs) to identify and prioritise the Top 10 uncertainties, or 'unanswered questions', about the effects of treatments that they agree are most important.

This study aims to inform on the complications, short and long term outcome of knee arthroscopy surgery. The study will also investigate the number of cases being performed in patients with osteoarthritis – a group that evidence suggests are less likely to benefit from arthroscopy. The association with total knee replacement will be investigated and any impact on complications of total knee replacement determined. Finally, the study will report in detail on the trends in rates of knee arthroscopic procedures and how these have varied over time along with geographic variation.

The data years requested are required for the analysis of the following: trends in the rates of certain procedures (e.g. with publication of evidence) and coding of index procedures, trends in the rates of complications (and changes with changing practice), and trends in associations between procedures – such as knee arthroscopy followed by total knee replacement and any complications or compromised outcome that may be associated with this. This information will be of value to patients, the public and to health care professionals: informing on the pictures of changing surgical practice, the risks of current practice with comparison to previous practice and a review of how practice has changed in response to the publication of guidelines (for example, from the National Institute for Health and Care Excellence, NICE).

The study has minimised the data requested during the time-period as much as possible by limiting to defined OPCS index procedure codes and specific ICD-10 codes (osteoarthritis, meniscal tears, ligament rupture). It is not possible to reduce the data further without compromising the ability to analyse trends in complications and associations between knee arthroscopy and knee replacement which is a key output of the project.

Surgical practice has changed considerably over the time-period requested – for example, reduced rates of knee ‘washout’ (e.g. OPCS W852, often performed to treat osteoarthritis in the 1990s) but increased rates of ‘meniscectomy’ (e.g. W822) beyond 2002. It is important to explore the demographics and population rates of these procedures and to investigate factors underlying these changes. There is the possibility that patients with osteoarthritis previously underwent washout but may now be undergoing a meniscal procedure – and therefore subsequently being at high risk of requiring a total knee replacement soon afterwards. The association between changing practice such as this and complications and repeat surgery rates is currently unknown and would benefit health care practice. Much of the evidence against knee washout was published around 1999-2002 and therefore this data period is required to investigate treatment practice before publication of this evidence, the transition period include the rate of change in practice, and the subsequent period which seems to include some increase in the rate of alternative surgical procedures for the degenerative knee with osteoarthritis.

Other past trends of interest include the rate of cruciate ligament reconstruction and developing osteoarthritis or requiring total knee replacement. The delay between ligament injury, reconstructive surgery, and development of symptomatic osteoarthritis could easily be 15-20+ years and this period of data follow up is therefore required to investigate time to a diagnosis of osteoarthritis and time to total knee replacement. The association of meniscal surgery with a diagnosis of osteoarthritis and requiring total knee replacement later in life will also be explored.

Yielded Benefits:

Several publications in high impact journals and contributed to the ongoing development of a national treatment guideline for arthroscopic meniscal surgery. 1. Abram SGF, Judge A, Beard DJ, Wilson HA, Price AJ. Temporal trends and regional variation in the rate of arthroscopic knee surgery in England: analysis of over 1.7 million procedures between 1997 and 2017. Has practice changed in response to new evidence? Br J Sports Med 2018; : bjsports-2018-099414. 2. Abram SGF, Judge A, Beard DJ, Price AJ. Adverse outcomes after arthroscopic partial meniscectomy: a study of 700 000 procedures in the national Hospital Episode Statistics database for England. Lancet 2018; published online Sept 24. DOI:10.1016/S0140-6736(18)31771-9. 3. Abram SGF, Beard DJ, Price AJ. National consensus on the definition, investigation, and classification of meniscal lesions of the knee. Knee 2018; 25: 834–40.

Expected Benefits:

The dissemination of the findings of this study is intended to benefit health care by rigorously reporting the rate complications and outcome of knee arthroscopy. It is highly likely that for many patients currently undergoing knee arthroscopy, the procedure may not be beneficial – for example, when performed on a background of advanced osteoarthritis. It is important to investigate the association of knee arthroscopy procedures with a diagnosis of osteoarthritis and knee replacement surgery, complications and outcome of any subsequent knee replacement.

The study aims to improve health practice, reducing rates of unnecessary surgery by disseminating findings on the rate of complications of the procedure in different populations of patients. We will determine predictors of outcome through multiple variable regression analysis.

Trends in the rate of surgery in groups of patients categorised by age and diagnosis of osteoarthritis will be determined and highlighted. Geographic variation will also be determined and publicised.

The study will provide evidence on identifying patients who are highly likely to progress to require a joint replacement at an early stage and determine if the outcome of their knee replacement may be compromised by the prior knee arthroscopy.

The information will inform patients and surgeons and the aim is to improve health practice and reduce rates of knee arthroscopy when this is unlikely to be beneficial. The study outputs will also inform NHS managers, commissioners and other health professionals of the outcomes and predictors of outcome of knee arthroscopy. This will encourage a change in practice where necessary, for example due to geographic variation or inappropriately high rates of surgery for patients with osteoarthritis. The study outputs may provide commissioners with evidence of any factors that can explain unwarranted geographical variation in knee arthroscopy surgery.

The target date is 18-24 months following receipt of the data.

Outputs:

The main output of this study will be a summary of post-operative complications of knee arthroscopy in the short and long term. Independent predictors of complications and repeat surgery such as knee replacement will be identified from the results of the regression model. Outcomes of knee replacement after knee arthroscopy will be compared to those without prior knee arthroscopy. Association of knee arthroscopy with a ICD-10 diagnosis of osteoarthritis will be investigated and analysed in context of any subsequent knee replacement.

Based on the findings of the study, we will write a scientific paper for submission to high quality peer-reviewed journals (for example, previous work from the group has been published in the BMJ, The Lancet). The study also aims to present findings to professionals at conferences and meetings.

The specific UK conferences to submit findings of this research to are: the British Orthopaedic Association (BOA) and the British Association for Surgery of Knee (BASK). International dissemination will also be sought, through journal publication and conferences such as the American Academy of Orthopaedic Surgeons (AAOS) and European Federation of National Associations of Orthopaedics and Traumatology (EFORT).

The study will develop Plain English summaries of findings for communication to patients and members of the public - these will be freely available and published on the NDORMS website (ndorms.ox.ac.uk). The findings may also be presented at established patient and public engagement events. The proposed analysis plan and outputs has been reviewed and approved by an established patient and public involvement (PPI) group.

All outputs will adhere to the HES analysis guide so that data is only shown in aggregate form with small numbers suppressed.

The target date for just the publications is 18-months following receipt of the data.

Key project outputs:

1. The rate of serious complications following knee arthroscopy (including comparison of groups by diagnosis and the arthroscopic procedure performed).

2. The rate of knee arthroscopy in patients with osteoarthritis / ligament rupture / meniscal tears.

3. The rate of progression to osteoarthritis in patients without osteoarthritis (after arthroscopy; after diagnosis of ligament rupture; after diagnosis of meniscal tear).

4. The rate of knee replacement surgery after knee arthroscopy (and time points).

5. The complications of total knee replacement and predictors including comparison of those previously undergoing arthroscopy to matched controls.

6. Trends in the rates of arthroscopic procedures (historical trends and factors underlying this)

7. Geographic variation in the rates of arthroscopic procedures and associated knee replacement procedures.

All outputs will be controlled for factors such as patient demographic, co-morbidity, and other surgical procedures with regression analysis.

Processing:

The University of Oxford requires details of all hospital episodes for the patients who have had knee arthroscopy as the study will explore potential links between surgery and subsequent health issues that are not necessarily specific to the knee (e.g. venous thromboembolism, stroke, heart attack, hospital acquired infection). In addition, the same data is required for all total or uni-compartment knee replacement patients – to investigate outcomes in this group, comparing those having undergone a prior knee arthroscopy to all others. Finally, data on patients with a diagnosis (ICD-10) of osteoarthritis, meniscal tear or knee ligament rupture is required to analyse the overall rate of surgery in these groups and rate of complications in matched groups undergoing or not undergoing surgery.

The only identifier being disseminated to University of Oxford will be Date of Death.

The datasets will be held on a password protected and encrypted drive at the Botnar Research Centre, Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS). Access to the data will be restricted to members of the research team employed by the University of Oxford and based at the Botnar Research Centre. The data will be used exclusively for the purposes of the specified study. The data will not be made accessible to any third parties. At the end of the study, the data will be safely held on a password protected and encrypted drive at the Botnar Research Centre, for further 5 years, and accessed only to answer questions arising from the publication and other publicity if required.

Simple descriptive statistics will be used to report trends in the rate of surgery and overall rates of complications. Regression analysis will be used to identify predictors of complications (e.g. venous thromboembolism) or further surgery (e.g. knee replacement). The data on all knee replacements will be used to compare the outcome of patients previously undergoing knee arthroscopy to those not having undergone knee arthroscopy. These groups will be carefully matched for any potentially confounding factors. Missing data will be handled using multiple imputation methods. Geographical Information Systems will be used to produce maps depicting variation in the rates of knee arthroscopy in different sub-populations (e.g. patients with osteoarthritis) and to depict any variation in the rate of complications and further surgery.

Project 104 — DARS-NIC-366845-Q1F0Q

Opt outs honoured: N

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Non Sensitive

When:2017.03 — 2017.05.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Patient Reported Outcome Measures (Linkable to HES)

Type of data:

Objectives:

The University of Oxford’s Big Health Data Group (BHDG) is undertaking two distinct research studies that require data from the National Joint Registry (NJR) linked with Hospital Episode Statistics (HES) and Patient Reported Outcome Measures (PROMs) data from NHS Digital.

The same individuals, all of whom are substantive employees of the University of Oxford, will undertake both studies at the Botnar Research Centre at the Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS).

STUDY 1: STAR - POST SURGICAL PREDICTORS OF CHRONIC PAIN AFTER TKR
The main reason that people undergo knee replacement is to alleviate pain. However it is recognised that around 20% of patients experience long-term post-surgical pain. The potential value of identifying patients at risk of long-term pain and targeting interventions is clear, but existing models have low predictive power, particularly for pain related outcomes. Given the difficulties around pre-operative prediction of long-term pain, it is important to consider post-operative factors.

An operation itself is an important risk factor for long-term pain, and factors relating to the operation and early recovery may be of greater importance than pre-surgical factors. In the context of major orthopaedic surgery, interventions targeting post-operative determinants of outcomes are likely to be more beneficial than pre-surgical interventions. Research is required into the post-operative determinants of long-term outcomes after total knee replacement. Achieving a better understanding of post-operative factors associated with the development and persistence of pain after surgery will inform future development of interventions that can either reduce the incidence of this kind of pain or that will provide more effective management for pain.

Analysis will take place from HES-PROMS data linked to data from the National Joint Registry (NJR), data to see if any of these issues after surgery predict who will experience long-term pain.

WIDER PROGRAMME OF RESEARCH
This study is part of a NHS National Institute for Health Research (NIHR) Programme Grant for Applied Research (PGfAR) (RP-PG-0613-20001 Chronic pain after total knee replacement: better post-operative prevention and management). The NIHR provide the framework through which the Department of Health position, maintain and manage the research, research staff and research infrastructure of the NHS in England as a national research facility. Within this five year programme of research there are six work packages:

1. Synthesise evidence about the effectiveness of interventions for chronic pain after knee replacement and other surgeries and identify post-surgical predictors of chronic pain after knee replacement.
2. Characterise the long-term trajectory of chronic pain including pain characteristics, disability and resource use up to five years after knee replacement.
3. Finalise an assessment process and a care pathway for patients with chronic pain after knee replacement.
4. Evaluate the clinical and cost-effectiveness of a new care pathway for patients with chronic pain after knee replacement.
5. Identify reasons for non-use of services and provide recommendations.
6. Make recommendations about best-practice care for patients with chronic pain after knee replacement and evaluate implementation of these.


STUDY 2: ATLAS - THE ROLE OF HOSPITAL ORGANISATION, SURGICAL FACTORS AND THE ENHANCED RECOVERY PATHWAY ON PATIENT OUTCOMES AND NHS COSTS FOLLOWING PRIMARY HIP AND KNEE REPLACEMENT SURGERY
Osteoarthritis is a leading cause of pain and disability. Many people with severe hip or knee pain caused by osteoarthritis have an operation called total joint replacement. This involves replacing the painful hip or knee joint with an artificial joint. Over 150,000 hip and knee replacement operations take place each year in the NHS and this number is expected to increase.

In the NHS patients can choose which hospital they want to have their surgery in. Information on the outcomes of surgery between different hospitals would help patients in making their decision. Outcomes of surgery will vary across different hospitals and areas of the country. This may be explained by a hospital treating more complex and sicker patients, and this must be accounted for. However, differences in patient outcomes could also be explained by how hospitals organised their services, such as bed availability, numbers of operating theatres and specialist surgeons, using new surgical techniques, or centralising care into specialist high volume hospitals. Knowledge of this would help NHS managers to change the way services are organised and reduce variation in outcomes between hospitals.

A new patient pathway for hip and knee replacement called enhanced recovery has been introduced in NHS and private hospitals. It is hoped this will benefit patients, through patient education before and after surgery, that includes making changes around the home, exercises to strengthen the joint and changes to diet, to help reduce the risk of complications and speed up a patient’s recovery time. For patients in whom it is suitable, they will further benefit by being able to return home earlier to continue their recuperation at home with appropriate support. This in turn will benefit the hospital by freeing up space for other patients on the waiting list. However, hospitals organise enhanced recovery services in different ways and it is unclear which way is best.

In this study University of Oxford will identify whether the different ways that hospitals organise services for hip and knee replacement patients can lead to improved patient outcomes, and explain why outcomes vary between hospitals. University of Oxford will produce maps highlighting how outcomes of surgery vary across the country and exploring organisational processes in the way enhanced recovery has been implemented across different hospital settings. The department will look at whether the introduction of enhanced recovery has improved patient outcomes and the potential cost saving to the NHS.

Statistical analysis of national linked data from the NJR/HES/PROMs databases will allow identification of hospital organisation and surgical factors that explain geographical variations in patient outcomes of surgery, after adjustment for patient level case-mix. University of Oxford will provide data at the small area level presented as maps to describe variation in outcomes, before and after accounting for these organisational and surgical factors. Focus will be on variation in outcomes of specific patient groups (old and frail with co-morbidities and obese) and provide evidence as to whether the introduction of new surgical innovations (e.g. minimally invasive surgery), and centralisation of services, has led to improved patient outcomes.

The project will then use a natural experimental study design to specifically examine the impact that the new enhanced recovery treatment pathway has had on NHS resource use, NHS costs and patient outcomes (PROMs, length of stay, complications, readmission). Interrupted time series analysis will examine changes in secular trends in outcomes and NHS costs before and after the introduction of the new treatment pathway. There will be a focus on the benefit of the new enhanced recovery pathway to specific patient groups such as frail older people with complex co-morbid conditions. An economic evaluation will describe the hospital NHS costs, patient health related quality of life and cost effectiveness that reflect the new treatment pathway for hip/knee replacement surgery.

Expected Benefits:

STUDY 1: STAR POST SURGICAL PREDICTORS OF CHRONIC PAIN AFTER PRIMARY TOTAL KNEE REPLACEMENT SURGERY

The dissemination of the findings of this study is intended to benefit health care by improving understanding of the reasons why patients suffer long-term pain after knee replacement and therefore how best to prevent or manage it.

The study aims to provide crucial pieces of information to aid this understanding, as identification of post-operative factors associated with long-term pain is expected to pave the way for the development of interventions to prevent and manage this kind of pain.

First, by providing evidence about how to proactively identify patients who are most likely to go on to experience long-term pain following surgery, the study is a building block in the development and evaluation of interventions targeted to these patients. Such interventions may help to prevent the development of long-term pain and therefore reduce incidence in the population as a whole. Second, as the study will identify post-operative factors contributing to the development of long-term pain, interventions that address pain could be put in place earlier in the pain trajectory, as pain emerges rather than once it starts to become persistent. When interventions for pain take place earlier, then they are more likely to be successful than interventions that take place once pain has become persistent with more impact on general and psychological wellbeing.

BENEFITS AS PART OF THE WIDER MAIN PROGRAMME GRANT

Findings from this work will be communicated in the context of the wider main programme of research of which this forms a part. The programme as a whole aims to provide guidance about better care for people with long-term pain after total knee replacement, and this guidance will be developed in the final phase of the programme, which is due for completion in August 2020.

The Programme has been designed to deliver improvements to services and patient well-being within one to three years of its completion. In addition to activities described above, the Programme contains activities designed to have impact.

Total knee replacement is a common elective procedure in the NHS. Although usually conducted to relieve pain associated with osteoarthritis, it is now known that 20% of people who have this surgery will have moderate to severe pain afterwards. It is also known that people with chronic pain after knee replacement are not provided with adequate care, that they may find it hard to cope and that services are not well-placed to help them.

While it would be ideal to identify who is at risk before they have surgery,-it is known that an operation is itself a risk factor for chronic pain. It is a priority for the Programme to find out how to look at the period after surgery to see if this can help in future identification and intervention for people at risk of chronic pain. Alongside this an aim is to address the pressing needs of patients who are unfortunate enough to have pain after surgery, and this will be done by evaluating an intervention.

Many people with chronic pain do not seek help, and that this is particularly evident among older people. However, it is not known why this is the case in relation to chronic pain after knee replacement, or what is needed to ensure better engagement with services. The Programme therefore includes research about why people do not use services. This will enable development of recommendations to encourage better engagement between health services and these individuals. An understanding of individuals’ decisions about use of healthcare will be contextualised in their previous experiences of service use. This will mean that recommendations will be developed for healthcare professionals and providers as well as individuals with pain and their families, carers or friends.

STUDY 2: ATLAS - THE ROLE OF HOSPITAL ORGANISATION, SURGICAL FACTORS AND THE ENHANCED RECOVERY PATHWAY ON PATIENT OUTCOMES AND NHS COSTS FOLLOWING PRIMARY HIP AND KNEE REPLACEMENT SURGERY

The study outputs will inform patients, NHS managers, commissioners and health professionals of the NHS costs about patient outcomes and cost-effectiveness associated with the enhanced recovery treatment pathway and the key elements that are most clinically and cost effective. It will provide patients with information on variation in outcomes of surgery to inform patient choice and decision-making. The study outputs will provide commissioners with evidence of modifiable hospital organisational factors that can explain unwarranted geographical variation in patient outcomes of surgery.

The maps highlighting how patient outcomes of hip/knee replacement vary across different hospitals and clinical commissioning groups would be informative to patients in making a choice of where to have surgery. The study will identify whether differences in the way hospitals organise their services, such as bed availability, numbers of operating theatres and specialist surgeons, using new surgical techniques, or centralising care into specialist hospitals, can explain why such variation exists. Knowledge of this would inform NHS managers of changes that can be made to the way services are organised, that lead to improved patient outcomes, and reduce unwarranted variation in outcomes between hospitals.

The study will provide evidence of the clinical and cost-effectiveness of the new enhanced recovery pathway for hip/knee replacement surgery. The study will identify which elements and ways of organising these services are best in terms of NHS cost and improved patient outcomes. The future benefit to patients will be through improving and standardising their care before, during and after surgery, helping reduce the risk of complications and speeding up their recovery time. NHS managers will benefit through knowledge of the best ways to organise enhanced recovery services that lead to improved patient outcomes.

The target date is 24-months following receipt of the data.

Outputs:

STUDY 1: STAR POST SURGICAL PREDICTORS OF CHRONIC PAIN AFTER PRIMARY TOTAL KNEE REPLACEMENT SURGERY

The STAR study sits within work package 1.
The main output of this study will be a summary of post-operative predictors of long-term post-surgical pain from the results of the regression model. Based on the findings, the BHDG will write a scientific paper for submission to high quality peer-reviewed journals. Currently the plan is to submit this paper to the Journal of Rheumatology to the BHDG also aims to present findings to professionals at conferences and meetings.

The specific conferences to submit findings of this research to are: the British Pain Society and the British Orthopaedic Association. The BHDG will develop Plain English summaries of findings for communication to patients and members of the public. These will be developed working with patients and Arthritis Care who are members of the research programme team of which this study forms part.

All outputs will adhere to the HES analysis guide so that data is only shown in aggregate form with small numbers supressed.

The target date for just the publications is 12-months following receipt of the data.

This study will additionally contribute to the broader outputs of the main programme. Work Package 6 includes dissemination activities to maximise impact of the Programme on care for patients with chronic pain after total knee replacement. Outputs will include robust evidence about best assessment, referral and management options. The study will host a workshop, present at conferences, publish articles and disseminate to professionals, patients and the public.

The study team will host a dissemination workshop with invited delegates to share findings of the Programme. The workshop will engage with healthcare professionals to disseminate and discuss findings and ensure maximum diffusion into practice. At the workshop it is aimed to introduce a web-based information resource to professionals, which will be refined on the basis of their feedback.

The study team will disseminate at two international conferences, engaging audiences interested in pain and in orthopaedics: the International Association for the Study of Pain (World Pain Congress) and the European Federation of National Associations of Orthopaedics and Traumatology. National conferences will be chosen to ensure that findings reach clinicians specialising in pain and orthopaedics as well as methodologists. It is aimed to maximise exposure of findings and efficiency of the budget by submitting more than one presentation to each conference. Conferences will include: British Pain Society; the British Orthopaedic Association; the Society for Social Medicine; MRC Network of Hubs for Trials Methodology Research Clinical Trials Methodology Conference.

The study team has developed a list of proposed publications from each Work Package.

The study will work in partnership with patients and Arthritis Care to develop accessible, evidence-based information. These resources will be disseminated through press releases, a web-based resource, written information, and other appropriate outlets. The study will ensure that communication is clear, and that there is the chance for a two-way flow of information between the research team, patients and members of the public.

Engagement with the public and patients will also take place through web-material and social media hosted at the University of Bristol, including podcasts and Twitter. All participants in WPs 2-6 will receive feedback on study findings, developed in partnership with patients. Other avenues (e.g. YouTube, provision of downloadable summaries of findings) will be discussed with patients in the PPI group to ensure that results and recommendation reach audiences who may benefit most: for instance those people living with long-term pain who have yet to receive support.

STUDY 2: ATLAS
THE ROLE OF HOSPITAL ORGANISATION, SURGICAL FACTORS AND THE ENHANCED RECOVERY PATHWAY ON PATIENT OUTCOMES AND NHS COSTS FOLLOWING PRIMARY HIP AND KNEE REPLACEMENT SURGERY

The study team will produce maps highlighting how patient outcomes of hip/knee replacement vary across different hospitals and clinical commissioning groups.

Throughout all stages of this project,-the study group will engage with key stakeholders including NHS managers, healthcare professionals, patients and the public for interpretation, dissemination and direct communication of findings. This will be facilitated through involvement of NHS management, collaboration with the James Lind Alliance, support of learned societies, and PPI representation. Based on the findings, an aim is to write scientific papers for submission to high quality peer-reviewed journals. The three key papers will be:
1. Determinants of geographical variation in patient outcomes of hip and knee replacement surgery
2. A Natural experimental study to evaluate the impact of enhanced recovery on trends in patient outcomes of hip and knee replacement surgery
3. Cost effectiveness of the enhanced recovery pathway for hip and knee replacement

The journals the studies aim to publish in are: Lancet, British Medical Journal, Arthritis and Rheumatology, Osteoarthritis and Cartilage. So either general medical journals, or a more specific rheumatology or Orthopaedic journal depending on where they ultimately get accepted.

Other aims are to present findings to professionals at conferences and meetings and to develop Plain English summaries of findings for communication to patients and members of the public. The health professionals will broadly be Rheumatologists, Orthopaedic surgeons. GPs, physiotherapist, nurses. Specific conferences are: British Society for Rheumatology (BSR), British Orthopaedic Association (BOA), Osteoarthritis Research Society International (OARSI).

All outputs will adhere to HES analysis guide so that data is only shown in aggregate form with small numbers supressed. It is planned to publish a full and complete account of that research in the NIHR HS&DR Journal, ensuring the research is reported fully, and publicly available via the NIHR Journals Library website and Europe PubMed Central.

The target date is 24-months following receipt of the data.

This project is informed by results from the recent James Lind Alliance (JLA) Priority Setting Partnership (PSP) for Hip/Knee Replacement, carried out within the Oxford NIHR Musculoskeletal BRU and supported by the Oxford NIHR Biomedical Research Centre (BRC). Two of the co-applicants on this study were members of the partnership, which is also supported by the BRC Director of patient involvement and who has been working with the JLA since it began in 2004.

University of Oxford recognize the importance of meaningful Patient and Public Involvement (PPI) and have worked collaboratively with the PPI Officer at NIHR Research Design Service (RDS) to identify individuals to become involved, and the Director of Patient Involvement at the Oxford NIHR BRC. The study team identified two lay people who understand the needs and problems of hip and knee replacement patients. Through their involvement, the study has listened to their ideas regarding the dissemination of findings so they are readily available and interpretable to the wider patient and public community.

It is planned to disseminate findings in peer-reviewed journals, at national and international conferences, and inform learned societies that include the British Orthopaedic Association, The British Association for Surgery of the Knee (BASK), Arthritis Research UK, rheumatology (British Society for Rheumatology), geriatrics (British Society of Geriatrics). University of Oxford will work alongside charities and learned societies to disseminate the findings of this study using established platforms that include social media such as Twitter and a study website, as more patients are now turning to these resources for information about planned surgery.

Processing:

Northgate Information Solutions will provide patient identifiers (NHS number, date of birth, gender and postcode) plus a unique NJR patient identifier (pseudonymised) for individuals whose records are held in the National Joint Registry (NJR). NHS Digital will link the data to HES admitted patient care and PROMS data.

NHS Digital will perform this linkage by first matching NJR identifiers (and associated unique NJR pseudonymised patient identifier), to HES/PROMS identifiers. A file containing NJR identifiable fields, unique NJR pseudonymised patient identifier, identifiable HES/PROMS fields with associated pseudonymised records will be created.

The BHDG requires details of all hospital episodes for the patients who have had hip or knee replacement surgery (identified from the NJR data) as both studies will explore potential links between surgery and subsequent health issues that are not necessarily specific to the knee or hip (e.g. hospital acquired infection).

All identifiers will then be removed to produce a pseudonmyised linked extract of HES/PROMS records, with each record having the associated unique NJR pseudonmyised patient identifier.

The BHDG will receive from NHS Digital patient level pseudonymised data only, i.e. the linked HES/PROMS data with the unique NJR patient identifier.

The unique pseudonymised NJR patient identifier will allow the BHDG to further link patient level pseudonymised NHS Digital data to pseudonymised NJR records which the BHDG will receive separately from Northgate Information Solutions.

The linked NJR, HES and PROMS datasets will be held on a password protected University Computer on an encrypted drive at the Botnar Research Centre, Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS). Access to the data will be restricted to two statisticians, both of whom are substantive employees of the University of Oxford and based at the Botnar Research Centre, who will work collaboratively on both studies. The same fields of data are required for both studies and the knee replacement data will be used in both but the hip replacement data will only be used for ATLAS. The data will be used exclusively for the purposes of the specified studies. The data will not be made accessible to any third parties. At the end of the studies, the data will be safely held in a password protected University Computer at the Botnar Research Centre, for further 5 years, and accessed only to answer questions arising from the publication and other publicity if required.

STUDY 1: STAR - POST SURGICAL PREDICTORS OF CHRONIC PAIN AFTER PRIMARY TOTAL KNEE REPLACEMENT SURGERY

The analysis of the linked datasets aims to identify post-operative predictors of long-term pain. Outcome will be assessed using the Oxford Knee Score (OKS) collected pre- and six months post-operatively in the PROMs database. The ‘OKS pain component’ provides a measure of chronic pain following surgery. Information on post-operative predictors within the NJR dataset includes intraoperative events (fracture, tendon avulsion, ligament injury) and revision surgery. Linkage to HES provides additional post-operative predictors, including readmission, reoperation, length of hospital stay, and medical complications.

Regression modelling will be used to identify post-operative predictors of chronic pain. Linearity of continuous predictors will be assessed using fractional polynomial regression modelling and linear splines. Missing data will be handled using multiple imputation methods.

STUDY 2: ATLAS - THE ROLE OF HOSPITAL ORGANISATION, SURGICAL FACTORS AND THE ENHANCED RECOVERY PATHWAY ON PATIENT OUTCOMES AND NHS COSTS FOLLOWING PRIMARY HIP AND KNEE REPLACEMENT SURGERY

VARIATION IN OUTCOMES:
Multilevel regression modelling of HES/NJR/PROM linked data will describe the association of hospital organisation, surgical factors and the enhanced recovery pathway on patient outcomes of surgery, adjusting for patient case-mix. Random intercept models will explore geographical variation in outcomes across hospital trusts and Clinical Commissioning Groups. Geographical Information Systems will be used to produce maps depicting variation in outcomes, and graphically display the influence these factors have on explaining such variation.

ENHANCED RECOVERY:
A disease specific Markov model will simulate the costs and health-related quality of life of hip/knee replacement patients before and after introduction of the pathway. A cost-effectiveness analysis will be performed using outcome measures such as Quality-Adjusted Life Years gained. Interrupted time series analysis will be used to evaluate the impact of change in service delivery on trends in rates of outcomes, adjusting for socioeconomic status and case-mix.

Project 105 — DARS-NIC-148436-W4NL6

Opt outs honoured: N

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Purposes: ()

Sensitive: Sensitive, and Non Sensitive

When:2016.04 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration

Type of data:

Objectives:

A randomised controlled trial of iodine supplementation in preterm infants (I2S2)

Primary research question: Does iodide supplementation of extreme preterm infants change neurodevelopmental outcome at 2 years corrected age?

Secondary research question: What is the relationship between supplementation, blood levels of thyroid hormones, illness, drug usage, other events of postnatal period and neurodevelopment? Specifically includes
-Collection of blood levels of T4, TSH and TBG on day 7, 14, 28 and 34 weeks corrected age will confirm the efficacy of iodide supplementation; and will distinguish between transient hypothyroxinaemia, transient hypothyroidism and transient hyperthyrotropinaemia.

If this work shows benefit to the supplemented neonates there will be worldwide clinical support for iodide supplementation for preterm infants. The study hopes to achieve iodide sufficiency in parentally fed infants, ensuring that the nutrition is adequate for development. In addition, the current iodide recommendation of 1mcg/kg/day extends to term infants and children up to 15 kg and they are also likely to benefit.

Project 106 — DARS-NIC-148435-2T54S

Opt outs honoured: N

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Purposes: ()

Sensitive: Sensitive

When:2016.04 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Members and Postings Report
  5. MRIS - Personal Demographics Service

Type of data:

Objectives:

Data supplied will be used by Clinical Trials Service Unit (CTSU) for the approved Medical research Project, ASCEND - ( Study Of Cardiovascular Events In Diabetes).

Expected Benefits:

To be completed by applicant

Outputs:

To be completed by applicant

Processing:

To be completed by applicant

Project 107 — DARS-NIC-148456-2YZGZ

Opt outs honoured: N

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c)

Purposes: ()

Sensitive: Non Sensitive, and Sensitive

When:2017.09 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report

Type of data:

Objectives:

The data supplied by the NHSIC to University of Oxford will be used only for the approved Medical Research Project MR767

Project 108 — DARS-NIC-148137-YQCFB

Opt outs honoured: Y

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive

When:2016.09 — 2016.11.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Scottish NHS / Registration
  2. MRIS - Cohort Event Notification Report

Type of data:

Objectives:

The data supplied will be used only for the approved medical research project - MR240: FERTILITY STUDY

Project 109 — DARS-NIC-148171-LGV0V

Opt outs honoured: Y, N

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive, and Non Sensitive

When:2016.04 — 2016.11.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report

Type of data:

Objectives:

The data supplied to the Clinical Trial Service Unit (CTSU) will be used only for the approved medical research project - MR200 Leukaemia Trials (CLL2)

Project 110 — DARS-NIC-358191-T5P4G

Opt outs honoured: N

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Non Sensitive, and Sensitive

When:2016.04 — 2016.11.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Patient Reported Outcome Measures

Type of data:

Objectives:


Sponsorship:
The National PROMs data is requested as part of a DPhil research project with the title ‘Missing data in Patient Reported Outcome Measures’. The DPhil project is funded by the Medical Research Council (MRC) and the Nuffield Department of Population Health at the University of Oxford. The MRC’s mission statement (http://www.mrc.ac.uk/about/mission/?nav=sidebar) is described as follows:
“The heart of our mission is to improve human health through world-class medical research. To achieve this, we support research across the biomedical spectrum, from fundamental lab-based science to clinical trials, and in all major disease areas. We work closely with the NHS and the UK Health Departments to deliver our mission, and give a high priority to research that is likely to make a real difference to clinical practice and the health of the population.”
By receiving this prestigious funding, the proposed project is recognised by the funders to have a beneficial impact on clinical practices and the health outcomes of the population.

Support from relevant groups in health and social care:
Through the receipt of funding by the MRC and Department of Population Health, University of Oxford, the project is directly supported by those groups. More precisely, senior academics from the Health Economics Research Centre, the Health Services Research Unit and the National Perinatal Epidemiology Unit are directly supervising the project.
The proposed project is a methodological study looking at the handling, analyses and reporting of missing data in PROMs. The issue of missing data in clinical research has been recognised as important, and is attracting continued interest from researchers, as well as funding and regulatory bodies including the UK NHS National Co-ordinating Centre for Research on Methodology, the Food and Drug Administration (FDA) and European Medicines Agency (EMA). Indeed, the FDA specifically stipulates that the treatment of missing data in clinical trials is a crucial issue and should be given a higher priority by the sponsors of statistical research. The NHS has also signalled explicit interest in research regarding missing data, by commissioning a report on the subject (Carpenter JR and Kenward MG (2008). Missing data in clinical trials – a practical guide. National Health Service Coordinating Centre for Research Methodology: Birmingham. Downloadable from http://www.haps.bham.ac.uk/publichealth/methodology/docs/invitations/Final_Report_RM04_JH17_mk.pdf.)
Similarly, the www.networks.nhs.uk/ webpage provides a wealth of information on missing data methodology and current research and best practice, demonstrating the NHS’s recognition of the relevance of this research and an interest of developing it further.
The pharmaceutical industry and health care providers (including health insurers) have been involved in research on missing data, including the funding of research and provision of data.
Inadequate analyses of data with missing observations can lead to biased and insufficiently powered results from clinical studies. This can prevent clinicians and health authorities, including those in the UK health and social care system, from making appropriate health care decisions, and may even lead to inferior interventions being accepted or recommended.
The research aims to create a better understanding of missing data within clinical research and aims to provide guidelines on how to deal with, and report, studies which contain missing data. To do this the researcher will specifically consider a single case study – that of PROMS data. By focussing specifically on missing data in PROMs, this work will expand the current research in an area that has not received as much attention as broader missing data research.

How does this work fit into a broader research project:
The DPhil project in the remit of which this data is requested is looking at the handling, analysis and reporting of missing PROMs outcome data. By means of a systematic review of the currently literature (in the process of being published in a peer reviewed journal, this research has also been presented on numerous occasions as stated elsewhere in this application), the project has confirmed deficits in the current practice of handling, analysing and reporting missing outcome data. The requested data will contribute to the second objective of the DPhil, i.e. using real data sets to better understand pattern in missing PROMs. Furthermore, the data will be used in simulation studies to address the third objective of the DPhil, i.e. to investigate the best way to analyse studies with missing data. Results from those two objectives will then be used to investigate different sensitivity analysis scenarios, and to consolidate guidance and methodology around the handling, analysis and reporting of missing PROMs outcome data.
In conclusion, this research project will contribute to the more robust and reliable analysis of studies with missing data, and will therefore contribute to improving health care within the UK and other countries.

Expected Benefits:


Patient reported outcome measures (PROMs) have increasingly gained prominence in the NHS for routine care and research in recent years particularly in areas, such as hip or knee replacement, hernia repair, to assess the effects of surgery and other interventions on health and quality of life. They form an important addition to long term clinical outcomes, which are not able to capture patients’ perceptions of their individual experiences outcomes with regards, to the results of an intervention or disease burden.
However, as the use of PROMs within the NHS is still relatively new, more research is needed in this area to better understand and interpret results used for clinical decision making.
A particularly important area for research is the occurrence of missing data within PROMs, as they rely on participants to be able and willing to complete the relevant questionnaires, and are therefore often subject missing data. It is unclear what the impact of missing data may be, which means that the available PROMs data may not be representative of the general population, and conclusions based on this data may not be appropriate for the wider population – for example, if more patients with poor outcomes were much more likely to not provide feedback.
The proposed work focusses on identifying factors that influence non-compliance with PROMs to create a better understanding of the available data and improve the results drawn from it to avoid reducing the likelihood of routine analysis and studies producing biased and misleading results. In line with the interest expressed by the NHS and other health care providers, regulators and funding bodies (as stated in the section labelled ‘purpose’), this work will help the NHS to choose effective and cost-effective treatments, and target available resources on the most appropriate treatments backed by the most robust research methodology. By contributing to the implementation of the most robust methodology and health research used, amongst others in clinical trials, this research aids the decision making with regards to which treatments are most effective for certain disease areas and patient populations. Thereby, this research will contribute to policy changes (changes in medication or interventions supported and financed by the NHS). This means that by having better evidence to choose the most effective and cost-effective treatments, the NHS will save money otherwise spent on less effective interventions.
This will result in better treatment for participants, because as a result of this work, patients will be more likely to receive the best interventions available, which will maximise their health and wellbeing though more robust research and evidence. They can also be more certain of the decision-making process underlying their treatment choices. Through less uncertainty around the results of clinical studies, new treatments will also be implemented more quickly into routine care, which means that patients can receive novel interventions and medication sooner.
Outputs are to be published in peer reviewed, open-access journals by April 2017. Thereby, results and conclusions will be freely accessible to researchers, NHS staff and decision makers and the public alike. The researcher will liaise with NHS England and the NHS Outcomes Framework for additional opportunities to present and discuss their work. Through the open-access publications and targeted presentations as described above, outputs are expected to impact on the current practice of handling, analysis and reporting clinical research in the presence of missing data thereafter. Past presentations of this work have been described above.

Outputs:


The outputs from this research will provide relevant information in their own right, and also contribute to simulation models of the PhD project statistical modelling of data.
Clear plans to communicate the potential and athe outcomes of the work:
Results from this research project in the field of missing data methodology will be published in relevant peer-reviewed, open-access journals reaching a wide audience including health care professionals, NHS staff and decision maker, statisticians and methodologists working in clinical trials and health research more generally.
Findings will also be presented at relevant local, national and international conferences aimed at a wide range of audiences, as described above. In particular, NHS and health care conferences will be targeted, such as the National PROMs Summit, and a short summary of the research aimed specifically at NHS staff will be submitted to the Health Services Journal. Also, the researcher will liaise with NHS England and the NHS Outcomes Framework for additional opportunities to present and discuss their work.
In addition, the researcher has established close links with local clinical trial teams, researchers and health professionals (including consultants, chief investigators and research nurses within the NHS) to whom the initial research aims have been described and findings will be presented on a regular basis. By contributing to and co-designing research with these groups and patient representatives, research outputs can be implemented into future and ongoing clinical trials and research projects where appropriate.
To date, presentations on the topic of missing data arising from the broader research have been delivered at various meetings including the following: Oxford Research Network Conference, Musculoskeletal Study days held at the Oxford University NHS trust and the Thames Valley Clinical Research Network Meetings (Oxford University Hospital Trust).
Any published information will be restricted to summary statistics (i.e. means, medians, standard deviations/ 95% Confidence intervals or ranges), as well as to the reporting of the results from statistical models (logistic regression and similar).
Under no circumstances will individual patient level data or any patient information that could be used to identify individual patients be published.
Outputs are expected to be published within the next two years, i.e. before April 2017.

Processing:


All processing is secured in line with the system level security policy.
The project is being supervised by HERC which is a research group with the University of Oxford so the data is controlled by HERC. The University Data Protection policy applies to the project http://www.admin.ox.ac.uk/councilsec/compliance/dataprotection/policy/ . This policy equally applies to staff, students and visitors and states:
“A failure to comply with the provisions of the Act may render the University, or in certain circumstances the individuals involved, liable to prosecution as well as giving rise to civil liabilities. Individuals are encouraged to familiarise themselves with the general aspects of Data Protection contained in the University's guidelines to the Act, referred to above and with any specific measurements recommended by the University or their Department relevant to the particular nature of their work.”
More precisely, failure comply with the University Data Protection policy can lead to students being expelled http://www.admin.ox.ac.uk/statutes/352-051b.shtml#_Toc28142348 and staff being dismissed from office http://www.admin.ox.ac.uk/statutes/353-051a.shtml#_Toc28073905 as part of the disciplinary measures.
The merged dataset will be used to explore in detail the rates of missing questionnaires and the rates of missing items within the different questionnaires. It aims to investigate the characteristics of patients with missing data, compared to those without any missing data in their questionnaires. Statistical models will be used to model the relationship between patient characteristics and the completeness of their PROMs data.
Furthermore, the project will look at a number of simulation models based on the dataset to assess the performance of different models dealing with missing data in PROMs, and to compare them to each other. The simulation models will also assess the impact of different missing data assumptions (data is missing completely at random, missing at random or missing not at random) on the results and interpretation of statistical models.
The customer has requested a copy of the National PROMs dataset. As the project is specifically looking at missing data, it is important that the data the customer receives will be the original data, in which none of the items for the Oxford Knee Scores (OKS), Oxford Hip Scores (OHS) and EQ-5D (PROMS data field) have been imputed.
The customer requests the HES data for all patients having undergone any hip and knee replacements or operations (i.e. not just for those that can be linked with the PROMs data) starting from 2009. From these patients, only HES data for episodes relating to hip and knee operations/ replacements is requested.

MR261 - ISIS 2:STREPTOKINASE ASPIRIN AFTER MYOCARDIAL INFARCT — DARS-NIC-148130-46N08

Opt outs honoured: Y, N (Excuses: Does not include the flow of confidential data, , , Section 251 NHS Act 2006)

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(7), Other-The data was disseminated with support under the Health and Social Care Act 2001 section 60 to process the data without informed consent. This legislation is no longer active and the University of Oxford is required to confirm how future processing of the data will comply with the common law duty of confidentiality., Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Sensitive

When:DSA runs 2016-09 – 2020-01 2016.04 — 2016.11.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Flagging Current Status Report
  5. MRIS - Members and Postings Report

Type of data: Identifiable

Objectives:

The data supplied by the NHSIC to Clinical Trail Service Unit will be used only for the approved Medical Research project MR261.

Yielded Benefits:

Expected Benefits:

In any future application, the applicant will be required to provide details of the actual benefits achieved as a result of the study.

Outputs:

No new outputs will be produced under this Data Sharing Agreement.

In any future application, the applicant will be required to provide details of the outputs that were produced and disseminated by the study as well as details of any future outputs planned.

Processing:

Under this Agreement, the data may be securely stored but not otherwise processed. No new data will be provided by NHS Digital under this Agreement.

The study data, including data provided by NHS Digital under previous agreements, are currently held by the University of Oxford. Under this interim extension all devices containing data will be securely locked away in a locked cabinet at the University of Oxford storage address specified in this Agreement.

The following provides background on the processing activities undertaken for the original study:

Identifiable data was shared with ONS to carry out the linkage between the study data and civil registration data. Participants records were ‘flagged’ with the Office for National Statistics (ONS). ONS notified the study team at the University of Oxford of participants’ deaths (date and cause) and cancer events when they occurred. The ‘flagging for long-term follow up’ service transferred from ONS to the HSCIC in 2008.

MR1146 & MR1194 - Audit of the effect of age at the first invitation for Breast Screening in the NHSBSP — DARS-NIC-147940-WVXJF

Opt outs honoured: Y (Excuses: Section 251 NHS Act 2006)

Legal basis: Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Other-This data was disseminated on behalf of ONS under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007. For the purpose of this Data Sharing Agreement it may be retained under section 261(7) of the Health and Social Care Act 2012., Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2016-10 – 2020-04 2016.04 — 2016.11.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Personal Demographics Service
  5. MRIS - Flagging Current Status Report
  6. MRIS - Members and Postings Report

Type of data: Identifiable

Objectives:

The purpose of the audit is to establish whether the age women are when first invited for routine mammogram by the NHS Breast Screening programme affects mortality from breast cancer.
The finding of this audit will inform screening policy and practice regarding the age at first routine mammogram.
The findings of this audit will inform screening policy and practice regarding the age at first routine mammogram. They will, therefore, have the potential to reduce the risk of dying from breast cancer. The audit will contribute to the NHSBSP's ongoing mission to provide as effect a service as possible.

Yielded Benefits:

In any future application, the applicant will be required to provide details of the actual benefits achieved as a result of the study.

Expected Benefits:

In any future application, the applicant will be required to provide details of the expected benefits resulting from the study.

Outputs:

No new outputs will be produced under this Data Sharing Agreement.

In any future application, the applicant will be required to provide details of the outputs that were produced and disseminated by the study as well as details of any future outputs planned.

Processing:

Under this Agreement, the data may be securely stored but not otherwise processed. No new data will be provided by NHS Digital under this Agreement.

The study data, including data provided by NHS Digital under previous agreements, are currently held by the University of Oxford. Under this interim extension all devices containing data will be securely locked away in a locked cabinet at the University of Oxford storage address specified in this Agreement.

The following provides background on the processing activities undertaken for the original study:

The audit used data from the NHS Central Register (NHSCR) and the National Health Application and Infrastructure Services (NHAIS) systems. The study cohort was identified from NHAIS system as: all women born in 1945-1948 inclusive, who were alive and on the NHAIS system in England and Wales on 1st January of the year in which they turned 50. In the first instance, the study was piloted on the 1945 cohort i.e. women born in 1945 who were alive and on the NHAIS system in England and Wales on 1st January 1995.

The University of Oxford provided to ONS a list of women containing the following data items

a) date of birth

b) NHS number

c) name

d) address

e) health authority

The following data was returned originally by ONS and subsequently (from 2008 onwards) by NHS Digital:

a) cancer registration, type and date

b) death, cause and date

Project 113 — DARS-NIC-147808-3F9FR

Opt outs honoured: Y

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive

When:2016.04 — 2016.11.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report
  3. MRIS - Scottish NHS / Registration

Type of data:

Objectives:

To relate mortality from a wide range of specific diseases and the incidence of cancer to smoking habits and to characterize the effects of stopping smoking.

Project 114 — DARS-NIC-10496-Z3F9B

Opt outs honoured: Y

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive

When:2016.04 — 2016.08.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Office for National Statistics Mortality Data

Type of data:

Objectives:

This is a research study aiming to establish the proportion of patients dying over the course of a year in Oxfordshire who are assessed by the Oxfordshire Out of Hours (OOH) service in the 4 weeks prior to their death. The study also aims to evaluate whether there are clinical and demographic features which could help distinguish patient subgroups at higher risk of death within 4 weeks of contact with the OOH service.

Expected Benefits:

The provision of primary care services outside core contracted hours is fundamental to the operation of the NHS. On a national scale it is clear that out of hours care is an area of significant challenge, and a current focus for quality improvement; the 2014 Urgent Care Commission report ‘Urgent and important: the future for urgent care in a 24/7 NHS' issued a direct ‘call to action’ for improvement in out of hours primary care provision. If Out of hours primary care is a fertile research area, then end of life care is even more so. ‘Actions for End of Life Care’ (NHS England, 2014) clearly establishes improving end of life care as a key goal for the NHS.

The contribution of out of hours primary care to end of life care is currently unknown. It is not known how many patients who have contact with OOH services die shortly after, and it is not known whether these deaths were expected or not. This study seeks to address those questions. In doing so the study is expected to contribute to improvements in healthcare in the following ways:

- By providing crucial background information for further research to enable the development of out of hours primary care services that are better able to meet the needs of people at end of life in the community.

- Identifying particular subgroups at risk of death has direct implications for patient safety and service design. Detailed analysis of the results, including use of deprivation indices might provide the basis for targeted local interventions in particular patient groups.

- This study benefits from having direct links to the service it is based upon. A co-investigator on the study is the clinical lead for Urgent Care at Oxford Health NHS Foundation Trust (who runs the Oxfordshire OOH service). Having management so closely integrated within the study team provides an immediate route for dissemination of the findings of the study, for their discussion, and for changes to be identified and made if necessary.

- The two nominated users have previously done research involving the Oxfordshire OOH service, results of which we have shared and discussed with clinicians working at the service at Research and Development meetings. These meetings informed the design of this study in its early stages. Study findings would be discussed in future meetings to share findings, and discuss how service change might result from these.

- The aim is to publish the results of this study in appropriate peer reviewed journals, and to present findings at conferences. This contributes to a growing evidence base around out of hours primary care, and, through national collaboration may help to inform and understand regional variation in the UK.

- Already underway is the process of setting up a local patient public involvement group (PPI) group for out of hours primary care (none currently exists). Results of the study would be shared with this group, and used as a basis for discussion of further research, and to gather service user views on how the results of the study could change local services.

Outputs:

When data processing is complete, the aim is to have established the proportion of patients who died over the course of a year in Oxfordshire who had seen the Oxfordshire OOH service in the 4 weeks prior to their death. Multivariable logistic regression will have been used to see whether any particularly high risk patient subgroups can be identified (hence the need for causes of death).

Oxford University aim to have completed the study (including preparation of manuscripts for publication) within one year of receipt of data from the HSCIC/ONS. The findings will be published in academic journals such as the British Medical Journal (BMJ) and the British Journal of General Practice (BJGP) and shared with colleagues at conferences. A report will be written for the study funder, and this will be held in their archives. On completion of the study, the funder (Oxford Radcliffe Hospitals Charitable Funds charity) may report a summary of the study on their website.

Outputs from this study (online, for the funder, and any others) will not include personal data and will only use aggregated data, with any small numbers supressed in line with the HES Analysis Guide.

This data will not be used for any commercial purpose at any point.

Processing:

Mortality data provided by the HSCIC/ONS will be linked to OOH records for Oxfordshire held by the Oxford Health NHS Foundation Trust. Linkage will be performed by cross-referencing NHS numbers between the two data sets. Only employees of the University of Oxford will process the data at the Trust, before the data is transferred to the University. In this way, it can be established what proportion of people who died in Oxfordshire during the study period were seen by the OOH service in the 4 weeks prior to their death. This will identify the study population (patients who saw OOH services within 4 weeks of their death). Data from patients who died in Oxfordshire during the study period but who had not been seen by the OOH service within four weeks of their death will be securely disposed of at this point as this information plays no further part in the study.

Data to be collected, together with an explanation of why this information is required, is detailed below.
NHS numbers - required in initial HSCIC dataset to enable linkage with OOH dataset to establish proportion of patients dying in Oxfordshire who had seen the OOH service within 4 weeks of their death.
Date of death - required to establish 4 week period prior to death.
Cause of death - required for subgroup analysis seeking to establish any patient groups who might be at high risk of death following OOH contact.
Date of birth (month and year) - Age of patient required for demographics/risk profiling.
Postcode - District level postcode required for deprivation scoring.
Gender - For demographics/risk profiling.

This will form a dataset of all patients who had died in Oxfordshire between 1st January 2015 and 31st December 2015 and who had contacted the Oxfordshire Out of Hours service within four weeks of their death. This is the study population of interest. To minimise the use of identifiable data, study data will be pseudonymised at this point by replacing NHS numbers with a unique study number. Following pseudonymisation, data will be transferred to the Department of Primary Care Health Sciences at the University of Oxford for further analysis via secure electronic file transfer (SEFT). This subsequent analysis will include Multivariable logistic regression analyses with the data of patients who did die within four weeks of contact with the Oxfordshire OOH service, to identify any particular groups at particularly high risk of death.

Project 115 — DARS-NIC-148220-FSJM5

Opt outs honoured: N

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Purposes: ()

Sensitive: Sensitive

When:2016.04 — 2016.08.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report

Type of data:

Objectives:

The 3C Study is investigating two possible strategies that could improve the lifespan of kidney transplants: firstly, is Campath-based induction treatment superior to standard basilixmab-based treatment; secondly, is sirolimus-based maintenance treatment superior to standard tacrolimusbased treatment. Although the primary outcomes of the study are relatively short-term, there is considerable scientific interest in the long-term (i.e. 5-20 year) outcomes from this study. In particular, there is uncertainty about the safety of such treatments with malignancy being one complication of transplantation that often occurs late.

Project 116 — DARS-NIC-183082-K3CPB

Opt outs honoured: Y, N

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Purposes: ()

Sensitive: Non Sensitive, and Sensitive

When:2016.04 — 2016.08.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report

Type of data:

Objectives:

SIFT is a multi-centre randomised controlled trial to assess whether the speed of increasing milk feed volumes in very preterm (<32 weeks) or very low birth weight (<1,500 g) infants has any effect on survival without moderate or severe disability at 24 months of age corrected for prematurity. The primary objective is to assess and compare the effects of a fast (30 ml/kg/day) and a slow (18 ml/kg/day) increase in milk feed volumes on survival of very preterm (<32 weeks) or VLBW (<1,500 g) infants without moderate or severe disability at 24 months of age corrected for prematurity.

The secondary objective is to assess and compare the effects of a fast (30 ml/kg/day) and a slow (18 ml/kg/day) increase in milk feed volumes on survival of very preterm (<32 weeks) or VLBW (<1,500 g) infants with respect to:
• Incidence of microbiologically-confirmed or clinically suspected lateonset invasive infection from trial entry until hospital discharge
• Incidence of necrotising enterocolitis (NEC) [Bell stage 2 or 3] from trial entry until hospital discharge
• Time taken to reach full milk feeds (tolerating 150 ml/kg/day for 3 consecutive days)
• Growth (weight and head circumference) at hospital discharge
• Duration of parenteral feeding before hospital discharge
• Length of time in intensive care
• Length of hospital stay

In addition to this, the data will be used to ensure that the questionnaire sent to parents at 24 months of age will not go to parents who have lost their child or no longer live in the UK. Given the potential emotional impact of being contacted by SIFT in error on parents who have lost their child, this is very important information for SIFT to acquire.