NHS Digital Data Release Register - reformatted

University Of Oxford projects

2638 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.

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

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

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

Purposes: (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2021-07-09 — 2021-09-08

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

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.


Improving outcomes for patients having shoulder replacements: guiding patient selection, evaluating cost-effectiveness and informing NHS provision — DARS-NIC-432598-Q6S0C

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

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

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-10-01 — 2024-09-30

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

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.


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: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

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

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-03-23 — 2021-08-31

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

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).


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: Anonymised - ICO Code Compliant, Yes (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'.

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:2021.11 — 2021.11. DSA runs 2021-09-15 — 2023-09-14

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)

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.


Investigating a vaccine against COVID-19 — DARS-NIC-396423-H4Z6Z

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

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

Purposes: (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2020-08-20 — 2020-12-31

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Permission to Contact

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: Anonymised - ICO Code Compliant (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: (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2020-05-27 — 2020-09-30

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Shielded Patient List

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.


Revision Hip and Knee Replacements: Evaluation of Clinical, Psychological and Surgical Outcomes — DARS-NIC-380650-K4F6X

Opt outs honoured: Anonymised - ICO Code Compliant (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'.

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-12 — 2024-05-05

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)

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.


Models of Resilience – Covid-19 and Non-Covid-19 Contexts — DARS-NIC-378657-B8F3K

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

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

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-06-24 — 2024-06-23

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

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.


The short and long-term cardiovascular consequences of critical illness: The C3 Study — DARS-NIC-352725-V1X2R

Opt outs honoured: Anonymised - ICO Code Compliant (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'.

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-17 — 2024-05-16

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

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.


CPinBOSS Study - Cerebral Palsy in the British Orthopaedic Surgery Surveillance Study — DARS-NIC-324368-Q0H5T

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

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

Purposes: (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2021-05-13 — 2024-05-12

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

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.


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: Identifiable (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: (Academic)

Sensitive: Sensitive

When:DSA runs 2019-10-11 — 2021-10-10

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

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: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: (Academic)

Sensitive: Sensitive

When:DSA runs 2019-08-01 — 2024-07-31

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

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.


The HOME Study — DARS-NIC-113964-G3J0C

Opt outs honoured: Anonymised - ICO Code Compliant (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

Purposes: (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2021-07-29 — 2024-07-28

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

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).


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, Anonymised - ICO Code Compliant, No (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: (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:2021.04 — 2021.11. DSA runs 2021-02-14 — 2024-02-13

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

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.





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, Identifiable, Anonymised - ICO Code Compliant, Yes, No (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: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2020.11 — 2021.11. DSA runs 2020-11-05 — 2021-05-04

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)

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.


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, Identifiable, Anonymised - ICO Code Compliant, No (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)

Purposes: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2020.06 — 2021.11. DSA runs 2020-06-01 — 2020-09-25

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

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)

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).


R1 (D09) - Data support to COVID-19 RCT — DARS-NIC-365354-R3M0Q

Opt outs honoured: No - consent provided by participants of research study, Identifiable, Anonymised - ICO Code Compliant, No (Consent (Reasonable Expectation))

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

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:2020.05 — 2021.11. DSA runs 2020-03-31 — 2023-03-30

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

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

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.


QResearch-Oxford Data Linkage Project — DARS-NIC-240279-Y2V2N

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (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'

Purposes: (Academic)

Sensitive: Non Sensitive, and Non-Sensitive, and Sensitive

When:2019.07 — 2021.11. DSA runs 2019-02-01 — 2020-09-25

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

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).


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, Identifiable, Yes (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'.

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:2018.10 — 2021.11. DSA runs 2018-10-01 — 2020-06-30

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

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.


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, Identifiable, Anonymised - ICO Code Compliant, Yes, No (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: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2018.10 — 2021.11. DSA runs 2019-12-18 — 2022-12-17

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

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.


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, Anonymised - ICO Code Compliant, No (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)

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2017.09 — 2021.11. DSA runs 2019-10-01 — 2022-09-30

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

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, Identifiable, Anonymised - ICO Code Compliant, No (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: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2017.06 — 2021.11. DSA runs 2020-05-21 — 2021-07-26

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

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

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.


National Core Studies - Data and Connectivity: COVID-19 Vaccines Pharmacovigilance (DaC-VaP) — DARS-NIC-431355-B1L8W

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable, No (Does not include the flow of confidential data)

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

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:2021.10 — 2021.10. DSA runs 2021-07-13 — 2022-07-12

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

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, Identifiable, No (Consent (Reasonable Expectation))

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

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2020.11 — 2021.10. DSA runs 2020-11-10 — 2021-10-09

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

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.


MR1247 - Evaluating the age extension of the NHS Breast Screening Programme — DARS-NIC-147931-DT25Y

Opt outs honoured: Yes - patient objections upheld, Identifiable, Anonymised - ICO Code Compliant, Yes, No (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)

Purposes: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2016.05 — 2021.10. DSA runs 2011-05-25 — 2026-05-24

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

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.


MR779: ASCEND (A Study of Cardiovascular Events iN Diabetes) — DARS-NIC-302994-C2Q2Y

Opt outs honoured: No - consent provided by participants of research study, Identifiable, Anonymised - ICO Code Compliant, No (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: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2017.09 — 2021.09. DSA runs 2019-10-05 — 2022-10-04

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

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.


RAPid Testing fOR Covid-19 (RAPTOR-C19). — DARS-NIC-396119-C8W3W

Opt outs honoured: Identifiable, No (Consent (Reasonable Expectation))

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

Purposes: (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:2021.06 — 2021.06. DSA runs 2021-02-08 — 2022-02-07

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

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: Identifiable, Yes (Section 251 NHS Act 2006)

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

Purposes: (Academic)

Sensitive: Non-Sensitive

When:2021.06 — 2021.06. DSA runs 2021-04-29 — 2022-04-28

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Demographics

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, Identifiable (Consent (Reasonable Expectation))

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

Purposes: (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:2021.04 — 2021.05. DSA runs 2021-03-23 — 2022-03-22

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Permission to Contact

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.


The Oxford Risk Factors And Non Invasive Imaging Study (ORFAN) Arm 4 — DARS-NIC-409610-J6L1F

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant (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'.

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2021.03 — 2021.05. DSA runs 2021-03-25 — 2024-03-24

Access method: One-Off

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

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.


Comparing COVID-19 Vaccine Schedule Combinations (Com-COV) — DARS-NIC-428459-V7Q8M

Opt outs honoured: No - consent provided by participants of research study, Identifiable (Consent (Reasonable Expectation))

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

Purposes: (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:2021.01 — 2021.05. DSA runs 2021-01-29 — 2022-01-28

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Permission to Contact

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.


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, Identifiable, Yes (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'.

Purposes: (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:2017.06 — 2021.04. DSA runs 2017-04-01 — 2020-03-31

Access method: Ongoing

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP)

Sublicensing allowed: No

Datasets:

  1. Birth Notification Data

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).


D27 - QResearch COVID-19 linkage — DARS-NIC-375354-G8V1H

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (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)

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2020.06 — 2021.03. DSA runs 2020-04-27 — 2020-09-25

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

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, Identifiable, No (Consent (Reasonable Expectation))

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

Purposes: (Academic)

Sensitive: Sensitive

When:2019.06 — 2021.03. DSA runs 2019-04-21 — 2022-01-20

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

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.


MR1134 - The Oxford Monitoring System for Attempted Suicide: Mortality following Deliberate Self-harm — DARS-NIC-147957-4444C

Opt outs honoured: Yes - patient objections upheld, Y, Anonymised - ICO Code Compliant, Identifiable, Yes (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(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'.

Purposes: (Academic)

Sensitive: Sensitive

When:2019.02 — 2021.03. DSA runs 2018-08-01 — 2021-07-31

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

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).


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, Identifiable, Anonymised - ICO Code Compliant, No (Consent (Reasonable Expectation))

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

Purposes: (NHS Trust)

Sensitive: Sensitive

When:2018.10 — 2021.03. DSA runs 2019-07-23 — 2022-07-22

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

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.


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, Identifiable, Anonymised - ICO Code Compliant, No (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: (Academic)

Sensitive: Sensitive

When:2017.09 — 2021.03. DSA runs 2019-02-01 — 2022-01-31

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

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


Patient outcomes and NHS costs following primary hip and knee replacement surgery — DARS-NIC-172121-G0Z1H

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Yes (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: (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:2018.06 — 2021.02. DSA runs 2018-07-01 — 2021-03-30

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)

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, Identifiable, No (Consent (Reasonable Expectation))

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

Purposes: (Academic)

Sensitive: Sensitive

When:2020.12 — 2021.01. DSA runs 2020-11-27 — 2023-11-26

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Demographics

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 Oxford Heart Vessels and Fat (ox-HVF) Cohort — DARS-NIC-392669-T1F8B

Opt outs honoured: No - consent provided by participants of research study, Identifiable, No (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: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2017.12 — 2020.10. DSA runs 2019-11-02 — 2020-10-31

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

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.


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, Anonymised - ICO Code Compliant, Yes (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'.

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2018.10 — 2020.09. DSA runs 2018-08-01 — 2021-07-31

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

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.


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, Identifiable, Yes (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: (Academic)

Sensitive: Sensitive, and Non Sensitive

When:2017.09 — 2020.09. DSA runs 2019-03-01 — 2020-10-02

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

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).


MR1471 (MR865 & MR850) - HEALTH OF CIVIL SERVANTS — DARS-NIC-148044-RGS7W

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Identifiable, Yes (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'.

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2016.04 — 2020.07. DSA runs 2018-10-01 — 2020-09-30

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

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, Anonymised - ICO Code Compliant, Yes (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'

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2019.01 — 2020.07. DSA runs 2019-08-28 — 2020-08-27

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

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, Anonymised - ICO Code Compliant, Identifiable, Yes, No (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)

Purposes: (Academic)

Sensitive: Sensitive

When:2020.06 — 2020.06. DSA runs 2019-11-11 — 2022-11-10

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

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, Anonymised - ICO Code Compliant, No, Yes (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)

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2019.07 — 2020.05. DSA runs 2019-02-01 — 2022-01-31

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

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, Anonymised - ICO Code Compliant, No, Yes (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)

Purposes: (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:2018.06 — 2020.05. DSA runs 2018-04-01 — 2020-12-31

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

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.


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 study, Identifiable, Yes, 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'.

Purposes: (Academic)

Sensitive: Sensitive

When:2016.06 — 2020.03. DSA runs 2011-04-08 — 2021-12-09

Access method: 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. MRIS - Personal Demographics Service

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:


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, Anonymised - ICO Code Compliant, No (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)

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2020.02 — 2020.02. DSA runs 2020-01-02 — 2023-01-01

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

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, Identifiable, Anonymised - ICO Code Compliant, Yes (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'.

Purposes: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2017.09 — 2020.01. DSA runs 2019-04-15 — 2020-09-30

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

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, Identifiable, Yes (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'.

Purposes: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2017.06 — 2019.09. DSA runs 2018-01-01 — 2020-12-31

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

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, Anonymised - ICO Code Compliant (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)

Purposes: (Academic)

Sensitive: Sensitive

When:2018.10 — 2019.03. DSA runs 2019-11-01 — 2020-10-31

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

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, Anonymised - ICO Code Compliant (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)

Purposes: (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:2018.10 — 2018.12. DSA runs 2019-08-01 — 2021-07-31

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

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, Identifiable (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)

Purposes: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2017.09 — 2018.09. DSA runs 2019-02-01 — 2022-01-31

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

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, Anonymised - ICO Code Compliant (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: (Academic)

Sensitive: Non Sensitive, and Sensitive, and Non-Sensitive

When:2017.12 — 2018.02. DSA runs 2018-11-01 — 2020-10-31

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

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, Anonymised - ICO Code Compliant (Consent (Reasonable Expectation))

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)

Purposes: (Academic)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:2017.12 — 2018.02. DSA runs 2019-01-09 — 2022-01-08

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

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