NHS Digital Data Release Register - reformatted

University Of Oxford projects

4934 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.

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

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-02-12 — 2026-02-11

Access method: Ongoing

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

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

There are no control subjects.

All analyses will be carried out on pseudonymised datasets.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Expected Benefits:

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

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

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

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

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

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

Outputs:

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

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

The following outputs hope to be developed:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Processing:

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

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

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

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

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

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

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

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

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

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

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

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

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


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

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable (Section 251 NHS Act 2006)

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

Purposes: Yes (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2024-02-01 — 2024-07-31

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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


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

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


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

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


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

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

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

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

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

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

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

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

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

Expected Benefits:

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

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

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

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

Outputs:

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

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

Processing:

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

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

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

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

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

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

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

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

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

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

The Data will not leave England at any time.

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

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


European Prospective Investigation into Cancer and Nutrition (EPIC) - Oxford ( ODR1516_018 ) — DARS-NIC-656754-C6S5Q

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-10-23 — 2024-10-19

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations

Objectives:

The University of Oxford requires data from NHS England for the purpose of the EPIC-Oxford study - a nationwide longitudinal cohort study of 60,642 men and women aged 20 and above who were recruited between 1993 and 1999 from throughout the UK.

The study was designed to examine the effects of diet on long-term health, with a specific focus on vegetarians. 50% of the participants do not eat meat, with large numbers following lacto-vegetarian and vegan diets, and EPIC-Oxford is the only large prospective study in the world with dietary data and stored blood samples for a large number of vegetarians together with linkage for the whole cohort to medical records covering cancer diagnoses, hospitalisations and causes of death.

EPIC’s research on the long-term health of vegetarians is unique in the world and is supported by grants from the MRC (“Health of Vegetarians”), the Wellcome Trust (“Livestock, Environment and People”), Cancer Research UK (Aetiology of prostate cancer”) and the World Cancer Research Fund (“Cancer risk in vegetarians”). All this research funded by competitively awarded grants from government and charities, which is focused mainly on cardiovascular diseases, cancer, bone and joint health, and gastro-intestinal diseases, is completely dependent on continued ability to link the whole EPIC-Oxford cohort with the records from HES.

The study is needed to improve understanding of the effects of diet on health and thus inform advice to governments, health professionals and the public about dietary choices to maximise the potential for long-term good health. Further aims include examining the roles of other lifestyle factors (including shift-work) and of endogenous hormones in relation to health.

The study’s overall aim is to provide reliable evidence on choices people can make in adult life to help increase their chances of staying healthy into old age. The aim of the scientific research is to reliably inform the public and health providers and regulators about the statistical findings on risk factors including diet and lifestyle and environmental factors and risk of cancer and other medical conditions.

The data controller is the University of Oxford, and all data is processed in the Nuffield Department of Population Health (NDPH) at the University of Oxford. The University of Oxford is the sole data processor.

All data collected is processed lawfully under GDPR Article 6(1)(e) as a public task in the public interest and under Article 9(2)(j) (‘research’). The use of ‘Article 6(1)e – processing is necessary for the performance of a task carried out in the public interest’ for research purposes is justified as:
•The study is directly related to population health risks and diet which is in the public interest.
•The University of Oxford is a ‘public authority’ as defined in the Data Protection Act 2018.
•Statute 1(3) of the ‘Statutes of the University of Oxford’ states that “The principal objects of the University are the advancement of learning by teaching and research and its dissemination by every means.” (http://www.admin.ox.ac.uk/statutes/1086-120.shtml).
The condition for processing special category personal data is met by the use of ‘Article 9(2)j - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes’ as, in line with the University’s principle objectives previously indicated, the University will be undertaking processing in line with the research protocol stated in this application. The research protocol has received due consideration for its public interest through peer review by a public funder, appropriate ethics committee review and supporting evidence of which is included as part of this application.

Participants were recruited into EPIC-Oxford through; GP practices; through the memberships of the Vegetarian Society and the Vegan Society and through health food shops and magazines. Participants are both male and female and aged 20 or over at recruitment. They were initially asked to complete a questionnaire about their diet and lifestyle, family history, a food frequency questionnaire and to donate a blood sample at recruitment between 1993 and 1999. All surviving participants also provided written consent to follow up their medical records at this time. Participants who were recruited via GP Practices were also asked for blood pressure and anthropometric measurements. Follow up questionnaires asking about diet, lifestyle and health were sent to all surviving participants approximately 5, 10 and 15 years after recruitment. Following recruitment, all surviving participants were also asked to complete a 7-day food diary to record all food consumed in one week.

When EPIC Oxford commenced in 1993 the records available were for cancer registrations and causes of death. Linkage to data from HES became possible after the completion of the recruitment to EPIC-Oxford, and linkage to HES was first established in 2008.

The following datasets are processed by the study and disseminated under two DARS agreements:

DARS-NIC-148322

-Demographics
-Civil Registrations of Death
-MRIS - Cohort Event Notification Report
-MRIS - Flagging Current Status Report
-Hospital Episode Statistics Admitted Patient Care (HES APC)
-MRIS - Cause of Death Report
-MRIS - Members and Postings Report
-Cancer Registration Data


DARS-NIC-656754

-NDRS Cancer Registration data


There are currently 60,642 EPIC-Oxford participants flagged at NHS England. The HES data required is record level pseudonymised data where the date fields only contain month and year. All morbidities and events are required since recruitment to the study in order to have a full record of cancers and deaths for the primary endpoint and to be able to exclude any co-morbidities and confounding variables from the analysis. A complete history of fact, cause and place of death including text fields are required to have a complete history of mortality for each participant to be able to conduct full analysis of the data and to exclude any confounding co-morbidities to produce accurate and reliable results.

Linkage to data for information on detailed NDRS cancer diagnoses and treatment is needed in order to examine the relationships of dietary, lifestyle and other potential risk factors with subsequent health. The aim is to contribute to knowledge of the epidemiology and aetiology of cancers. The priority endpoints which will be studied until 30/04/2026 and beyond are cancers of the breast, prostate, ovary, endometrium, thyroid and colorectum. Without the linked data provided by the NCRAS datasets, EPIC-Oxford researchers will not be able to fully understand the complete burden of the diseases of interest within the cohort. A complete history of the cancer diagnoses, as well as hospital admissions and fact and cause of death, is required to have a comprehensive documentation of conditions for each participant to be able to conduct full analysis of the data and also to exclude any confounding co-morbidities to produce accurate and reliable results.

The pathological and diagnostic data from the cancer outcomes dataset requested in this application will be used in epidemiological analyses of dietary, hormonal and other environmental and biological factors in relation to cancer risk and will also enable the study team to subdivide cancer types according to pathological features of the cancers. Some of the tumour sites being investigated are breast, prostate, ovarian, thyroid and endometrial cancer. The study team aim to expand our collection of data on tumours, allowing the for more tumour characteristics on more types of cancer, at lower cost. The study team require more detailed information on tumour characteristics to enable the study team to conduct further analyses of diet and other risk factors in relation to the incidence of sub-types of cancer, such as prostate cancers subdivided by TNM stage and Gleason score, and breast cancers subdivided by hormone receptor status.

Participants were recruited from England, Wales, Scotland and Northern Ireland, and may have moved since randomisation so coverage of England and Wales for cancer diagnosis and deaths and England for HES is crucial to follow-up all participants. Approval also exists for these data to be collected in Scotland (cancer, death and hospital admissions) and Wales (for hospital admissions only). It would be complicated, costly and burdensome to collect this information any other way, and full coverage of the cohort would not be achieved. The data has been restricted to cohort participants, with the minimum amount of information necessary to answer the research question e.g. only month and year provided for date fields for HES data. NHS England data is necessary because it provides the key mechanism for researchers to work on diseases that are of interest, and the mechanism to exclude any potentially confounding co-morbidities in these datasets. Under this Agreement HES data will be re-supplied for the whole cohort for the period 1997/98 to 2015/16 and new data supplied from 2016/17 up to the latest available. This is because the HES data (supplied under DARS-NIC-148322) is on the basis of participant informed consent rather than the previous CAG Section 251 support, which required national data opt-outs to be supplied.

The priority endpoints which will be studied over the next five years are ischaemic heart disease, stroke, fractures, joint disorders, digestive tract disorders and cancers of the breast, prostate and colorectum. Without the linked data provided by NHS England EPIC-Oxford researchers will not be able to fully understand the full burden of the diseases of interest within the cohort.

Study participants’ records were linked electronically to Hospital Episode Statistics for information on cause-specific hospital admissions, for example cancer diagnoses, cardiovascular disease, joint replacements and fractures. This was to examine the relationships between dietary, lifestyle and other potential risk factors with subsequent health. The aim is to contribute to knowledge of the epidemiology and aetiology of common diseases and other causes of hospital admissions. One of the primary outcomes is cause of mortality so continued receipt of this data will be required in the future.
The collection of these data provides minimal risk of harm to the participants.

Follow-up in a cohort study needs to be as complete as possible. This is to avoid both unnecessary reduction in size of the cohort (which reduces statistical power of data analyses), and loss-to-follow-up bias (which can cause misleading research results). To produce scientifically valid results, it is essential that the whole EPIC-Oxford cohort can be linked with information from medical records. If linkage was not complete there would be a high risk of the results being biased by showing falsely low rates of disease in some dietary groups.

EPIC-Oxford is committed to ensuring participants continue to be kept aware of progress and developments in the study, and to obtain their opinions on current and proposed research and how their data is being used in the study. The unanimous consensus of the study participant panel is that they strongly support the study’s aims and the research that is currently taking place and the future plans. The panel feel that they had been made aware at recruitment that they had signed up to a long term cohort study and they expected their health records to be followed up over many years. The investigators have not changed the scope of the study since the original participant information sheet and protocol were approved initially in 1993 and a further review by the Ethics committee and CAG took place in 2018. It was always intended that the cohort be followed up for diet and cancer risk and other chronic illnesses.

Updates to the protocol have expanded some of these groups, all within the scope of the original objectives. The participants are also aware that the study would run for a further 10 years.

EPIC-Oxford is an independent study with its own research aims with the University of Oxford acting as the sole data controller. From the initial set-up, the study is also part of a larger collaboration called EPIC-Europe. EPIC-Europe is a collaboration between 23 centres in 10 European countries with a total of 521000 participants. The aims of EPIC-Europe are broadly the same as EPIC-Oxford, to study the effects of diet and lifestyle and environmental factors on cancer and other chronic illnesses. The centres involved and the numbers of participants in each country details can be found at the EPIC-Europe web site (https://epic.iarc.fr/). EPIC-Europe is conducting a large number of analyses on the associations of diet with cancer risk, with a focus on the most common cancers such as cancers of the stomach, colorectum (large bowel), breast, prostate and lung. So far, research has focused on the role of fruit and vegetables, dietary fibre, meat, fish, dairy products and alcohol intake, as well as dietary-related factors such as obesity and physical activity, on cancer risk. More details of the findings from EPIC-Europe are found in the EPIC-Europe publications listed on the EPIC Europe website. This will be the focus of a separate data sharing application for EPIC Europe (DARS-NIC-340646-C8Z6J).

This nationwide cohort study was designed to examine the effects of diet on long-term health. All EPIC-Oxford participants provided written informed consent at recruitment to the study in the 1990s. When the study first commenced the records available were for cancer registrations and causes of death. Linkage to data from HES became possible after the completion of the recruitment to EPIC-Oxford, and linkage to HES was established in 2008.

The EPIC-Oxford study team has engaged with the EPIC participant panel by asking them ‘Given the time that has elapsed is it still reasonably expected that the study team are collecting hospital data as part of their medical records’. The participant panel were explicitly asked if they would expect ‘their medical records’ to cover HES data. The panel were also asked whether they felt that the consent given when enrolling into the study met their reasonable expectation that all medical records including deaths, cancer diagnosis and hospital admissions were part of their medical record.

The panel declared that it was and still is their expectation that hospital data, as well as data on cancers and deaths will be received by the EPIC-Oxford researchers as part of their medical record. The patient group ultimately feel that processing of the data is in line with the reasonable expectations of participants who consented to participate in the study.
The participant panel also contribute ideas for disseminating the results of EPIC-Oxford to the study participants e.g via vegetarian society and vegan society publications which the investigators are now looking into.

The national data opt-out does not apply where explicit consent has been obtained from the patient for the specific purpose.

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

Yielded Benefits:

Obesity, ischaemic heart disease and diabetes are diet-related diseases which put an enormous burden on the health of people in the UK and on the NHS. EPIC-Oxford has shown that, compared with meat-eaters, vegetarians are less likely to be obese (BMJ 1996 Sep 28;313(7060):816-7.), have lower blood cholesterol and a 22% lower risk of ischaemic heart disease (BMJ. 2019 Sep 4;366:l4897.), and a 37% lower risk of diabetes (Nutr Diabetes 2019 Feb 25;9(1):7.). These findings have not only been published in scientific journals and presented at conferences, both scientific and with a lay audience, but have received enormous media interest. For example, the findings on the low risk of ischaemic heart disease in vegetarians, which were published in the BMJ with an accompanying editorial, had an Altmetric score of 2533 which is in the 99th percentile of outputs, with coverage by 132 news outlets worldwide including the BBC and all the major UK newspapers; it is therefore very likely that the findings were read by millions of people in the UK, providing this reliable information direct to the public to increase knowledge and support beneficial dietary changes which in turn will reduce the associated work and cost to the NHS of diet-related ill-health. Findings from EPIC-Oxford have also provided important evidence used by Public Health England’s Scientific Advisory Committee on Nutrition (SACN) in its expert evaluations of nutritional impacts on health, which underpin government policy through the Department of Health. For example, results from EPIC-Oxford together with EPIC-Europe on the relationship of folic acid with the risk of prostate cancer were part of the evidence considered in SACN’s report on folic acid, while other results from EPIC were evaluated in SACN’s review of carbohydrates. The SACN reports recommended folic acid fortification of the food supply, decreases in the recommended intake of free sugars, and increases in the recommended intake of dietary fibre for the UK population, thus having direct impacts on nutritional policy and the future health of the public

Expected Benefits:

Diet has been identified as the number one cause for the burden of disease worldwide, and by providing new evidence on the impact of diet on health, EPIC-Oxford expect to contribute to reducing the work and cost to the NHS of diet-related ill-health.

The aim of EPIC-Oxford is to provide high quality information on the relationships of diet with long-term health, with a focus on the health of vegetarians and vegans. Although much is already known about diet and health, important questions remain, and in particular it is essential to gain a deeper understanding of the health impacts of “plant-based diets” which are increasingly being recommended as part of strategies to combat climate change and for other environmental reasons. EPIC-Oxford is unique in the world in having a large cohort in which 50% of participants do not eat meat, with long follow-up, a biobank, and linkage to medical records to provide complete and objective follow-up.

Publications from EPIC-Oxford constitute a very substantial proportion of the world literature on the long-term health of vegetarians; the only other comparable prospective study is based in California, but this has no biobank or comprehensive linkage to electronic medical records. Based on the research from EPIC-Oxford and other studies, it is now well-established that vegetarian diets are compatible with good long-term health, and this research underpins the ability of the NHS to provide advice supporting healthy eating as a vegetarian; the NHS could not give such advice without the evidence to support the healthiness of vegetarian diets

Outputs:

Diet has been identified as the number one cause for the burden of disease worldwide, and by providing new evidence on the impact of diet on health EPIC-Oxford will contribute to reducing the work and cost to the NHS of diet-related ill-health. The aim of EPIC-Oxford is to improve information on diet in relation to the risk of cancer and other chronic diseases, which offers huge potential for improvements in public health in the UK. The results are published in peer-reviewed publications and presented at conferences, and are also reported through national media.

A major focus of research in EPIC-Oxford is the long-term health of vegetarians and vegans, and this research relates directly to the health of the more than 1.2 million people in the UK who follow vegetarian diets (NHS 2014). The long-term effects on health of a vegetarian diet are not well understood, and little is known about the health effects of a vegan diet. The earlier research in EPIC-Oxford has demonstrated lower risks of ischaemic heart disease, stomach cancer and perhaps haematological cancers in vegetarians compared with non-vegetarians, but understanding of these relationships is incomplete and much further research is needed to assess both the potential beneficial effects of a vegetarian diet and also possible hazards associated with low intakes of some nutrients, such as protein, long-chain n-3 fatty acids, vitamin B12, vitamin D and calcium (particularly in vegans). As well as peer-reviewed scientific publications, the EPIC-Oxford website (www.epic-oxford.org) is used to describe all findings, with lay summaries of findings when appropriate, copies of abstracts, and links to pdfs of full papers. The website provides information both for study participants and for a wider audience in the UK and worldwide and where appropriate findings will also be communicated to the NHS because the research will provide information to underpin their advice, e.g. as on their website: http://www.nhs.uk/Livewell/Vegetarianhealth/Pages/Goingvegetarian.aspx

During 2019 the study team have published four papers on the health of participants in EPIC-Oxford. In a paper in the BMJ, the study reported for the first time ever on the risk of stroke in vegetarians, and found that vegetarians had a higher risk for stroke than meat-eaters, although this was counter-balanced by a lower risk for ischaemic heart disease https://www.bmj.com/content/366/bmj.l4897.long. This paper was published with a linked editorial in the BMJ https://www.bmj.com/content/366/bmj.l5272 and a detailed commentary on the NHS website https://www.nhs.uk/news/food-and-diet/vegetarian-diet-linked-lower-risk-heart-disease-higher-risk-stroke/, as well as articles in 122 news outlets worldwide and widespread media coverage giving an Altmetric score of 2515, which is in the top 1% of all outputs https://bmj.altmetric.com/details/65924701.

Selected publications in 2019
Tong TYN, Appleby PN, Bradbury KE, Perez-Cornago A, Travis RC, Clarke R, Key TJ. Risks of ischaemic heart disease and stroke in meat eaters, fish eaters, and vegetarians over 18 years of follow-up: results from the prospective EPIC-Oxford study. BMJ. 2019 Sep 4;366:l4897.
Knuppel A, Papier K, Key TJ, Travis RC. EAT-Lancet score and major health outcomes: the EPIC-Oxford study. Lancet. 2019 Jul 20;394(10194):213-214.
Papier K, Appleby PN, Fensom GK, Knuppel A, Perez-Cornago A, Schmidt JA, Tong TYN, Key TJ. Vegetarian diets and risk of hospitalisation or death with diabetes in British adults: results from the EPIC-Oxford study. Nutr Diabetes. 2019 Feb 25;9(1):7.
Papier K, Tong TY, Appleby PN, Bradbury KE, Fensom GK, Knuppel A, Perez-Cornago A, Schmidt JA, Travis RC, Key TJ. Comparison of major protein-source foods and other food groups in meat-eaters and non-meat-eaters in the EPIC-Oxford Cohort. Nutrients. 2019 Apr 11;11(4). pii: E824.

The data used from NHS England combined with EPIC Oxford data demonstrates the benefits of the research being in the public interest. The public are able to choose whether their diet choices may affect their health, particularly in heart disease and stroke.

In the Lancet the study reported analyses in EPIC-Oxford on mortality in relation to compliance with the EAT-Lancet dietary score, showing beneficial associations for ischaemic heart disease and diabetes, but no association with stroke and no clear association with mortality. Other 2019 papers reported that vegetarians have a 37% lower risk of diabetes than meat-eaters, and that non-meat-eaters have higher intakes of high-protein meat alternatives (soya, legumes, pulses, nuts, seeds) and other plant-based foods (whole grains, vegetables, fruits) and lower intakes of refined grains, fried foods, alcohol and sugar-sweetened beverages than meat-eaters.

EPIC-Oxford research findings presented to clinicians, policymakers and other academics at conferences (listed below) and via the press as described above will directly benefit health care through the NHS by providing clinicians and other NHS health care professionals with up-to-date evidence-based guidance on the effects of diet on long term health and the risk of death. This will improve clinical health care and inform planners and policy makers to address demands on health and social care in the present and the future.

Examples of recent findings through the linkage of HES data is a recent high profile publication in the BMJ looking at the risks of ischaemic heart disease and stroke in meat eaters, fish eaters, and vegetarians over 18 years of follow-up https://www.ncbi.nlm.nih.gov/pubmed/31484644. This was a newsworthy article and reached a wide audience via the press https://www.bbc.co.uk/news/health-49579820 , with reports in 122 news outlets throughout the world https://bmj.altmetric.com/details/65924701/news. Earlier this year a study paper on diabetes showed that this risk of this disease is much lower in vegetarians than in meat eaters https://www.nature.com/articles/s41387-019-0074-0. Altogether, this research provides more information for government policy makers to advise the general public on eating a healthy diet.

Target publications for 2021/2023 are:

Vegetarian diets and risk of bone fractures: analyses during 2020, publish 2021
Target journal: BMC Medicine

Vegetarian diets and risk of joint disorders: analyses during 2020, publish 2021
Target journal: Rheumatology
Target conference: Society for Social Medicine and Population Health Annual Scientific Meeting, Cambridge 2020

Vitamin B12 and risk of haemorrhagic stroke: analyses during 2021, publish 2022
Target journal: European Heart Journal
Target conference: European Society of Cardiology Congress 2021

Vegetarian diets and risk of digestive tract disorders: analyses during 2021, publish 2022
Target journal: Gut
Target conference: Nutrition Society Summer Symposium, 2021

Diet and risk of cancers of the breast, prostate and colorectum: analyses 2020-2022, publish 2023
Target journal: British Journal of Cancer
Target conference: National Cancer Research Institute Conference 2022

All information regarding collection, processing and storage of participant data including details of participant panel discussions mentioned previously are on the EPIC –Oxford website at www.EPIC-Oxford.org . This website is updated regularly with publications, contains annual newsletters and details of participant panel meetings ensuring that participants are fully informed of how their data are being used. The website also contains details of how participants may opt-out of the study and contact details for the study team, who receive regular e-mails, letters and telephone messages from study participants to update their contact details, or report an illness or a death. Study participants also contact the EPIC-Oxford team about EPIC-Oxford research findings they see in the national press and online.
The website also regularly publishes results from research in EPIC-Oxford, including on diseases for which the information comes from HES (such as ischemic heart disease, stroke and fractures), and information on these scientific publications is included on the study website. Results are also described in EPIC-Oxford newsletters and have been covered by national media (online and print), and is covered by the Nuffield Department of Population Health website www.ndph.ox.ac.uk . Information regarding publications is also tweeted by the wider Twitter handle for the Nuffield Department of Population Health (@Oxford_NDPH).

Processing:

The identifying information shared with NHS England included names, dates of birth, NHS Number, gender, address and postcode. NHS England retains this information and consequently, there is no requirement for further data to flow from EPIC-Oxford to NHS England unless a participant has moved to England from Scotland and requires to be flagged, or a participant has withdrawn from the study and requires to be removed from the flagged cohort whereupon no further data about this participant will be supplied from NHS England.

A complete history of the cancer diagnoses, hospital admissions and fact and cause of death are required to have a complete history of conditions for each participant to be able to conduct full analysis of the data and to exclude any confounding co-morbidities to produce accurate and reliable results.

NHS England send identifying Demographic, Civil Registration mortality and Cancer data back to University of Oxford including supplied date of birth, Supplied Gender, Supplied Member Number, Cause of Death text and cancer registration details. Cause of death text is important because it enables researchers to determine whether or not the ICD codes provided refer to diseases/conditions that were on the causal pathway. Cancer registration number is important because it enables researchers to correctly identify which cancer is to be deleted in the event of a cancelled cancer; cancer site and morphology (type) data are essential and cancer anniversary year is required to check on the date of diagnosis. Supplied gender and date of birth are necessary for checking that the data really do refer to the participant identified by the member number.

The HES data provided by NHS England is pseudonymised record level data and the participants are not re-identified.

The Demographic, Civil Registration mortality and Cancer Data is held separately from the HES data, When an analysis file is created the fields are merged using a pseudonymised ID into a file containing no other identifying information. During this process there will be no attempt to re-identify any individuals who are taking part in the study.

These data from NHS England provide the study with the most accurate and cost-effective method of participant follow-up. Using any other means would be laborious and costly, and the results would not be as accurate or comprehensive than those that are collected centrally at NHS England.

The data is received from NHS England by a single named Statistician, who processes the files, storing the data, and creating an updated events data file from which analysis files for researchers and other statisticians who work on the study are generated. The analysis files contain the minimum of individual level data required to answer the research question, and are pseudonymised, containing no identifiable data. During this process there will be no attempt to re-identify any individuals who are taking part in the study.

Two named EPIC-Oxford Statisticians have access to the main administrative database, which includes identifiable information on participants (allowing for linkage to health-related records) and is located and maintained separately from the research database (which contains all the data of analysis files for researchers but no data from which any participant could be identified).

1. HES data and identifying Demographic, Civil Registration mortality and Cancer data are downloaded from the NHS England server to Oxford by a named statistician.
2. Pseudonymised NHS England data including event dates and particulars are stored in events databases in NDPH at the University of Oxford, with access limited to named individuals. These databases do not contain participant identifying information (name, date of birth, NHS number, gender, and postcode).
3. Identifying participant information linked to the study ID numbers are stored separately to the dataset for use in analysis and are held only for administrative purposes and for use in facilitating ongoing data linkage.
4. Data files for analysis by epidemiologists, statisticians and students are created by the named statisticians, merging data from the events databases with baseline, follow-up and biological data provided by participants as required.
5. The analysis dataset contains full date of death for individuals whose deaths were reported. These data files contain only pseudonymised data (gender, month and year of birth, month and year of any events, but no names or other identifiable data), and contain the minimum amount of data required to answer the research question. The analysis dataset (containing the study participant’s linked records from the sources specified above) will not be re-linked with the identifiers. All subsequent analyses use only subsets of the pseudonymised data. All such subsets are customised according to the characteristics relevant to the specific analysis, containing only the minimum data required for the specific purpose.
6. Data files for analysis are retained in a secure location on the server only for as long as necessary, for example, to answer questions from journal correspondents and commentators on published papers, and in order to re-run analyses as required.

The research questions and analyses are overseen by the Chief and Principal Investigators of EPIC Oxford who are employees of the University of Oxford and apply for funding to use these data in accordance with the protocol for the benefit of the public to be able to make choices regarding their diet and lifestyle and their risk of cancer or other chronic illnesses.

The datasets will be pseudonymised as described above before statistical analyses are undertaken. Various types of analyses are undertaken on an ongoing basis for the overarching purpose of assessing cancer incidence, health risks and overall mortality. The data will be held only at the NDPH at the University of Oxford. The data will only be accessed by authorised members of the EPIC-Oxford study team of epidemiologists and statisticians, all of whom are substantive employees of the University of Oxford, or non-contractual DPhil and MSc students who complete a University Research Services form agreeing to terms and conditions of the project, grant and relevant sections of the latest Data Sharing Agreement with NHS England. These are filed in the Research Coordinators office with signed copies sent to the Director of Research Services at University of Oxford. Every member of staff working on these data receives an IG induction and made aware of the terms of use of these data. The staff and students also complete an MRC course on Research and GDPR and confidentiality https://byglearning.co.uk/mrcrsc-lms/course/index.php?categoryid=1 for which a certificate with the appropriate pass mark needs to be submitted before access to data is authorised. The data will only be used for the objectives of the study as described within the Data Sharing Agreement. The EPIC-Oxford study will not share any data supplied by NHS England with any other institution or individual outside of the study team at Oxford University.

The IT security measures in the NDPH include:
• Access control: controlling access to resources using a default “deny-all” policy, user, authentication and policies to commission and decommission access on receipt of the appropriate permissions
• Boundary control: configuration and management of a perimeter firewall and interior firewalls within the network, monitoring, DDOS and other attack mitigation,
• Secure storage: NHS England -supplied data is stored on a dedicated, access-controlled server which facilitates encryption-at-rest and prompt data deletion.

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

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


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

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2023-09-20 — 2026-09-19

Access method: One-Off

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

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Yielded Benefits:

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

Expected Benefits:

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

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

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

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

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

Outputs:

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

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

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

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

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

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

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

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

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

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

Processing:

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

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

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

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

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

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

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

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

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

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

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

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

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

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


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

Type of data: information not disclosed for TRE projects

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

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

Purposes: Yes (Academic)

Sensitive: Sensitive

When:DSA runs 2023-01-26 — 2026-01-25 2023.05 — 2024.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Vital Status and updated contact details for trial participants:

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

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

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

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

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

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

Expected Benefits:

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

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

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

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

Outputs:

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

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

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

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

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

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

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

Processing:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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


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

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable, Anonymised - ICO Code Compliant (Consent (Reasonable Expectation))

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

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2023-01-13 — 2029-12-31

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Yielded Benefits:

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

Expected Benefits:

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

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

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

Outputs:

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

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

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

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

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

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

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

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

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


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

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable (Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

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

Purposes: Yes (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2022-12-07 — 2024-12-06

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Expected Benefits:

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

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

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

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

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

Outputs:

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

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

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

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

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

Results will also be communicated directly to trial participants.

Processing:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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


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

Type of data: information not disclosed for TRE projects

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

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

Purposes: Yes (Academic)

Sensitive: Sensitive

When:DSA runs 2022-11-04 — 2023-11-03

Access method: One-Off

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

Sublicensing allowed: No

Datasets:

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

Expected Benefits:

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


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

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

Outputs:

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

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

Processing:

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

Proposed Methodology::

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

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

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

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

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

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

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


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

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable, No (Statutory exemption to flow confidential data without consent, Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006)

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

Purposes: No, Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-12-10 — 2022-03-31 2022.12 — 2024.03.

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

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Request to use SCR for consented participants:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Expected Benefits:

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

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

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

Outputs:

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

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

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

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

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

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

Processing:

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

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

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

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

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

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

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

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

• Summary Care Record (SCR) for consented participants:

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

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

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

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

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

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

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

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

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

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

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

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


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

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable

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

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2021-12-06 — 2022-12-05

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

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

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

Yielded Benefits:

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

Expected Benefits:

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

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

Outputs:

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

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

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

Processing:

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


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

Type of data: information not disclosed for TRE projects

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: Yes (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
  7. COVID-19 Second Generation Surveillance System (SGSS)
  8. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Objectives:

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

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

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

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

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

Expected Benefits:

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

Outputs:

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

Processing:

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

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

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

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

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


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

Type of data: information not disclosed for TRE projects

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: No (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
  12. Civil Registrations of Death - Secondary Care Cut
  13. COVID-19 Second Generation Surveillance System (SGSS)
  14. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  15. Diagnostic Imaging Data Set (DID)
  16. Mental Health Services Data Set (MHSDS)
  17. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Objectives:

Since the outbreak of COVID-19 in Wuhan, China, and the subsequent pandemic, Public Health England (PHE) has commissioned the Oxford- RCGP RSC, based at the University of Oxford, to incorporate the monitoring of COVID-19 into its virology surveillance scheme. A vital part of this work has been to monitor the number of suspected COVID-19 cases in the community and ultimately establish the effect of COVID-19 infection on hospitalisation as the outcome measure.

OVERALL AIM
Primary aim of the RECAP (Remote COVID-19 Assessment in Primary Care) project is to assist primary care providers to improve patient care and health outcomes. Most COVID-19 patients are diagnosed and managed remotely by GP’s. This helps reduce the burden on hospitals. However, due to the wide number of possible symptoms, it is hard to predict and diagnose COVID-19.

Through this project, we aim to develop and validate an early warning score for GPs based on data collected to a remote GP consultation and then link this to the outcomes such as hospital admissions as a measure of clinical deterioration.

The purpose of this application is to link data held by NHS digital to support the RCGP RSC to conduct observational epidemiological studies that inform the national public health response to COVID-19. The RCGP RSC dataset includes individual patient level up-to-date primary care data which can be easily queried. Primary care/general practice data is rich in terms of diagnosis and information about the process of care.

For the purpose of this study, datasets coming into ORCHID as part of the MAINROUTE study (DARS-NIC-381683-R6R6K) will also be utilised.

The datasets included are:
- Detailed demographic and risk factor data.
- COVID-19 appointments: information on whether or not a virology swab was taken and the outcome of the swab
- Non-COVID-19 appointments
- Detailed data for the 32 conditions monitored by RCGP RSC on behalf of PHE
- Co-morbid conditions
- Medication which may be associated with better or adverse outcomes.
- Test results
- Referrals made
- A&E visits
- Inpatient appointments, including critical care
- COVID-19 SARI Watch (Formerly CHESS)
- Mortality data (if applicable)

Additional datasets under DARS-NIC-431355-B1L8W will also be utilised:
- COVID-19 Second Generation Surveillance System (SGSS) – (Pillar 1)
- COVID-19 UK Non-hospital Antigen Testing Results (Pillar2)
- Civil Registrations (Deaths)– Secondary Care Cut

The GDPR Lawful basis for processing the requested data under this agreement are;

Imperial College London:
Since Imperial College are the sponsors of this study, they are joint data controllers.

All the data will flow into the secure environment at University of Oxford, thus are data controllers. Furthermore, only University of Oxford will be processing the data.

The data controllers for the processing being undertaken within this agreement are University for Oxford and Imperial Collage London who have together the joint responsibilities. Some of the data which will be accessed under this agreement will be data which is already in the hands of University of Oxford under a different agreement DARS-NIC-381683 for which University of Oxford operate as a Data processor for on behalf of Pubic Health England (PHE) and the Royal Collage of GPs (RCGP) and for DARS-NIC-431355-B1L8W where University of Oxford are a data controller for different purpose.

The lawful basis for processing the data are as follows:

Article 6(1)(e) (Public Task processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller).

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

Expected Benefits:

The RECAP (Remote COVID-19 Assessment in Primary Care) project aims to assist primary care providers to improve patient care and health outcomes. Most COVID-19 patients are diagnosed and managed remotely by GP’s. This helps reduce the burden on hospitals. However, due to the wide number of possible symptoms, it is hard to predict and diagnose COVID-19.

Through this project, an early warning score for GPs based on data collected to a remote GP consultation will be developed and validated which will then be linked to outcomes such as hospital admissions as a measure of clinical deterioration.

Outputs:

Specific Outputs for this study are:
• To track the impact of COVID-19, visual descriptions (dashboards) of the number and rates of patients presenting specific symptoms (primary care data), being tested for specific tests, hospitalisation outcomes confirming deterioration
• Subgroups of data will be identified to enable display by GP practice, region, age group, gender, and ethnicity.
• Establishing a risk score for the predictability of COVID-19 diagnosis.

Furthermore, articles will be published in international scientific journals.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Flows of data:
- Data are extracted from practices that are members of the Royal College of General Practitioners (RCGP RSC) Research and Surveillance Network by Wellbeing. The University of Oxford subcontracts with Apollo to do this as part its contractual responsibilities.
- The University of Oxford will provide NHS digital with a list of pseudonymised NHS numbers and pseudonymised date of birth for the cohort each quarter.
- NHS Digital will link the cohort to the requested datasets and send pseudonymised linked datasets securely back to University of Oxford.
- University of Oxford will store the data on the secure network.
- University of Oxford will process and aggregate pseudonymised data to produce approved reports for surveillance (as part of the National surveillance process); and for the purpose of COVID-19 vaccine pharmacovigilance and quality improvement.

No identifiable data items will be passed into or out of NHS Digital

SALTING METHODLOGY:
The University of Oxford will follow a salting method in a manner that all the data will be non-identifiable. The process is as follows:
1. An encryption salt is held by a designated staff member of the University of Oxford Medical Science Division who is not a member of the ORCHID staff.
2. When a data linkage is required, the encryption salt holder sends the encryption salt to the data provider (NHS Digital)
3. The data provider will hash personal identifiers (in the data requested by ORCHID) using a hashing algorithm
4. The hashing algorithm is SHA2-512.
5. To make this key unique, an encryption salt is added at the end of the NHS number (e.g. NHS number= 12345678 ; SALT (held by someone other than ORCHID staff) = bob. So, hashing would take place using the SHA2-512 alogrithm by 12345678bob = return pseudonymised data)

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

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

Only three SQL developers and one senior project manager can access the main database. Surveillance databases are
created for approved analyses once they have been agreed by the RCGP RSC approval committee. This agreed protocol
includes the list of variables required for the database. The SQL developers create separate databases for individual projects only including the required variables, for the required time interval.

The additional linkages will be added to the data that the University of Oxford already receives from the RCGP RSC network practices and PHE reference laboratories.

This process for previous projects linking different sets of data, and the linkage has been successful, provided both parties use the same pseudonymisation algorithm (SHA-512).

There will be no requirement nor attempt to re-identify individuals from the data. The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

The use of national data is needed as the University of Oxford are a national surveillance centre and the cohort are from across England and Wales.

The use of pseudonymised NHS numbers are essential as the request to link to the data that the University of Oxford already received from the RCGP RSC network general practices and PHE reference laboratories.

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


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

Type of data: information not disclosed for TRE projects

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

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

Purposes: Yes (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2020-08-20 — 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

Type of data: information not disclosed for TRE projects

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: No (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.


4CHILD - Four Counties Database of Cerebral Palsy, Vision Loss and Hearing Loss in Children (Berkshire, Buckinghamshire, Northamptonshire, Oxfordshire) — DARS-NIC-148239-M8RTP

Type of data: information not disclosed for TRE projects

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), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (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

Type of data: information not disclosed for TRE projects

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), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (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 Oxford Risk Factors And Non Invasive Imaging Study (ORFAN) Arm 4 — DARS-NIC-409610-J6L1F

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Yes (Section 251 NHS Act 2006)

Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

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

When:DSA runs 2021-03-25 — 2024-03-24 2021.03 — 2024.03.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Medicines dispensed in Primary Care (NHSBSA data)
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. COVID-19 Hospitalization in England Surveillance System
  4. Emergency Care Data Set (ECDS)
  5. HES:Civil Registration (Deaths) bridge
  6. Hospital Episode Statistics Accident and Emergency
  7. Hospital Episode Statistics Admitted Patient Care
  8. Hospital Episode Statistics Critical Care
  9. Hospital Episode Statistics Outpatients
  10. Civil Registrations of Death - Secondary Care Cut
  11. Hospital Episode Statistics Accident and Emergency (HES A and E)
  12. Hospital Episode Statistics Admitted Patient Care (HES APC)
  13. Hospital Episode Statistics Critical Care (HES Critical Care)
  14. Hospital Episode Statistics Outpatients (HES OP)
  15. Civil Registrations of Death

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.


PRINCIPLE: Platform Randomised trial of INterventions against COVID-19 In older peoPLE — DARS-NIC-411161-G4K7X

Type of data: information not disclosed for TRE projects

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

Purposes: No (Academic)

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

When:DSA runs 2020-11-05 — 2021-05-04 2020.11 — 2024.03.

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

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  2. COVID-19 Access to Summary Care Records
  3. Hospital Episode Statistics Critical Care
  4. Hospital Episode Statistics Admitted Patient Care
  5. Civil Registration - Deaths
  6. GPES Data for Pandemic Planning and Research (COVID-19)
  7. Medicines dispensed in Primary Care (NHSBSA data)
  8. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  9. Civil Registrations of Death
  10. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  11. Hospital Episode Statistics Admitted Patient Care (HES APC)
  12. Hospital Episode Statistics Critical Care (HES Critical Care)

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

Type of data: information not disclosed for TRE projects

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

Purposes: Yes (Academic)

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

When:DSA runs 2020-06-01 — 2020-09-25 2020.06 — 2024.03.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No, Yes

Datasets:

  1. SUS plus - Admitted Patient Care (beta version)
  2. Civil Registration - Deaths
  3. COVID-19 Second Generation Surveillance System
  4. COVID-19 Hospitalization in England Surveillance System
  5. COVID-19 Vaccination Adverse Reactions
  6. COVID-19 Vaccination Status
  7. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  8. Emergency Care Data Set (ECDS)
  9. Hospital Episode Statistics Accident and Emergency
  10. Hospital Episode Statistics Admitted Patient Care
  11. Hospital Episode Statistics Critical Care
  12. Hospital Episode Statistics Outpatients
  13. COVID-19 Therapeutics Programme Data Set’
  14. HES-ID to MPS-ID HES Accident and Emergency
  15. HES-ID to MPS-ID HES Admitted Patient Care
  16. HES-ID to MPS-ID HES Outpatients
  17. MSDS (Maternity Services Data Set) v1.5
  18. Civil Registrations of Death
  19. COVID-19 Second Generation Surveillance System (SGSS)
  20. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  21. Hospital Episode Statistics Accident and Emergency (HES A and E)
  22. Hospital Episode Statistics Admitted Patient Care (HES APC)
  23. Hospital Episode Statistics Critical Care (HES Critical Care)
  24. Hospital Episode Statistics Outpatients (HES OP)
  25. Maternity Services Data Set (MSDS) v1.5
  26. COVID-19 SGSS First Positives (Second Generation Surveillance System)
  27. COVID-19 Therapeutics Programme Data Set
  28. Maternity Services Data Set (MSDS) v2

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

Type of data: information not disclosed for TRE projects

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: No, Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2020-03-31 — 2023-03-30 2020.05 — 2024.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No, Yes

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. COVID-19 Hospitalization in England Surveillance System
  3. COVID-19 Second Generation Surveillance System
  4. Civil Registration - Deaths
  5. COVID-19 Second Generation Surveillance System (Beta version)
  6. SUS plus - Admitted Patient Care (beta version)
  7. GPES Data for Pandemic Planning and Research (COVID-19)
  8. Cancer Registration Data
  9. Medicines dispensed in Primary Care (NHSBSA data)
  10. Civil Registration (Deaths) - Secondary Care Cut
  11. HES-ID to MPS-ID HES Admitted Patient Care
  12. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  13. COVID-19 Vaccination Status
  14. Demographics
  15. Electronic Prescribing and Medicines Administration (EPMA) data in Secondary Care for COVID-19
  16. Emergency Care Data Set (ECDS)
  17. Hospital Episode Statistics Critical Care
  18. Civil Registrations of Death - Secondary Care Cut
  19. Hospital Episode Statistics Admitted Patient Care (HES APC)
  20. Civil Registrations of Death
  21. COVID-19 Second Generation Surveillance System (SGSS)
  22. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  23. COVID-19 Electronic Prescribing and Medicines Administration (ePMA) in Secondary Care
  24. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  25. Hospital Episode Statistics Critical Care (HES Critical Care)
  26. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Objectives:

This is a new application from the University of Oxford. University of Oxford request to use the NHS Digital Clinical Trials Service for access to data for a study entitled Randomised Evaluation of COVid-19 thERapY (RECOVERY).

In 2019 a novel coronavirus-induced disease (COVID-19) emerged in Wuhan, China. A month later the Chinese Center for Disease Control and Prevention identified a new betacoronavirus (SARS coronavirus 2, or SARS-CoV-2) as the aetiological (causing or contributing to the development of a disease or condition) agent. The clinical manifestations of COVID-19 range from asymptomatic infection or mild, transient symptoms to severe viral pneumonia with respiratory failure. As many patients do not progress to severe disease the overall case fatality rate per infected individual is low, but hospitals in areas with significant community transmission have experienced a major increase in the number of hospitalized pneumonia patients, and the frequency of severe disease in hospitalised patients can be as high as 30%. The progression from prodrome (an early symptom indicating the onset of a disease or illness - in this case usually fever, fatigue and cough) to severe pneumonia requiring oxygen support or mechanical ventilation often takes one to two weeks after the onset of symptoms. The kinetics of viral replication in the respiratory tract are not well characterized, but this relatively slow progression provides a potential time window in which antiviral therapies could influence the course of disease.

In early 2020, as the protocol for this trial was being developed, there were no approved treatments for COVID-19, a disease induced by the novel coronavirus SARS-CoV-2 that emerged in China in late 2019. The UK New and Emerging Respiratory Virus Threats Advisory Group (NERVTAG) advised that several possible treatments should be evaluated, including (but not limited to) Lopinavir-Ritonavir, Interferon β, and low-dose corticosteroids. These groups also advised that other treatments will soon emerge that require evaluation. A World Health Organization (WHO) expert group issued broadly similar advice. This trial allows reliable assessment of the effects of multiple different treatments (including re-purposed and novel drugs) on major outcomes in COVID-19.

This study aims to compare several different treatments that may be useful for patients with COVID-19. These treatments have been recommended by the expert panel that advises the Chief Medical Officer in England. Some are tablets and some are injections. Although these treatments show promise, nobody knows if any of them will turn out to be more effective in helping patients recover than the usual standard of care at hospitals (which all patients will receive).

The treatments, given in addition to the usual care at hospital, are: Lopinavir-Ritonavir (commonly used to treat HIV); dexathasone (a type of steroid, which is used in a range of conditions typically to reduce inflammation) and Hydroxychloroquine. Hydroxychloroquine, a derivative of chloroquine, has been used for many decades to treat malaria and rheumatological diseases. It has antiviral activity against SARS-CoV-2 in cell culture. As of 07/04/2020 - Azithromycin has been added as an arm to the trial (replacing a previous drug type called interferon beta). Azithromycin is a macrolide antibiotic. The macrolides inhibit the growth of bacteria and are often prescribed to treat rather common bacterial infections. Azithromycin has immunomodulatory properties that has shown benefit in inflammatory lung disease.

As of 16/04/2020 - a second randomisation arm has been added to the protocol.
This is for participants who meet certain simple physiological and inflammatory criteria - for example those in the cohort receiving oxygen therapy or oxygen saturations <92%) who can be randomised for a second time to receive either tocilizumab (an immunosuppressive drug, mainly for the treatment of rheumatoid arthritis) or control (both in addition to the treatment assigned at the first randomisation)

Other arms can be added if evidence emerges that there are suitable candidate therapeutics. Conversely, in some patient
populations, not all trial arms are appropriate (e.g. due to contraindications based on co-morbid conditions or concomitant medication); in some hospitals, not all treatment arms will be available (e.g. due to manufacturing and supply shortages); and at some times, not all treatment arms will be active (e.g. due to lack of relevant approvals and contractual agreements). Therefore,other treatments may be added to the protocol as time goes on and more information is gathered. This will not impact or change the level of data that is required from NHS Digital - as the cohort in the trial remains the same, regardless of what drug is being trialed.

Data from the trial will be regularly reviewed so that any effective treatment can be identified quickly and made available to all patients. The RECOVERY Trial team will constantly review information on new drugs and include promising ones in the trial.

Patients are eligible for the study if all of the following are true:

(i) Aged at least 18 years
(ii) Hospitalised
(iii) Proven SARS-CoV-2 infection.
(iv) Suspected SARS-Cov-2 infection. In general, SARS-CoV-2 infection should be suspected when a patient presents with
(i) typical symptoms (e.g. influenza-like illness with fever and muscle pain, or respiratory illness with cough and shortness of breath); and (ii) compatible chest X-ray findings (consolidation or ground-glass shadowing); and (iii) alternative causes have been considered unlikely or excluded (e.g. heart failure, influenza). However, the diagnosis remains a clinical one based on the opinion of the managing doctor.
(v) No medical history that might, in the opinion of the attending clinician, put the patient at significant risk if he/she were to participate in the trial

The anticipated scale of the epidemic is such that hospitals, and particularly intensive care facilities, may be massively overstretched. Under some models of pandemic spread, up to 50% of the adult population may fall sick over a period of 8-12 weeks, of whom around 10% may require hospitalisation. In this situation, even treatments with only a moderate impact on survival or on hospital resources could be worthwhile. Therefore, the focus of the COVID-19 Core Protocol is the impact of candidate treatments on mortality and on the need for hospitalisation or ventilation. Critically, the trial (and subsequent data collection) is designed to minimise the burden on front-line hospital staff working within an overstretched care system during a major epidemic. Eligibility criteria are therefore simple and trial processes (including paperwork) are minimised.

The primary objective is to provide reliable estimates of the effect of study treatments on in-hospital death (with subsidiary analyses of cause of death and death at various timepoints following discharge).

The secondary objectives are to assess the effects of study treatments on duration of hospital stay; the need for (and duration of) ventilation; and the need for renal replacement therapy.

Data from routine healthcare records (including linkage to medical databases held by organisations such as NHS Digital) and from relevant research studies (such as UK Biobank and Genomics England) will allow subsidiary analyses of the effect of the study treatments on particular non-fatal events (e.g. ascertained through linkage to Hospital Episode Statistics), the influence of pre-existing major co-morbidity (e.g. diabetes, heart disease, lung disease, hepatic insufficiency, severe depression, severe kidney impairment, immunosuppression), and longer-term outcomes (e.g. 6 month survival) as well as in particular sub-categories of patient (e.g. by genotype).

Follow-up information is to be collected on all study participants, irrespective of whether or not they complete the scheduled course of allocated study treatment. Study staff will seek Follow-up information through various means including medical staff, reviewing information from medical notes, routine healthcare systems, and registries.

The study team require the following information from NHS Digital:

- Prompt feed from SUS on hospital discharge
- Quarterly feed on HES data
- Quarterly feeds on civil registration data (death certificate information)

This study is supported by a grant to the University of Oxford from UK Research and Innovation/National Institute for Health Research (NIHR) and by core funding provided by NIHR Oxford Biomedical Research Centre, the Wellcome Trust, the Bill and Melinda Gates Foundation, Health Data Research UK, and the Medical Research Council Population Health Research Unit, and NIHR Clinical Trials Unit Support Funding.

The new trial has been classed as an Urgent Public Health Research Study. It is one of a round of projects to receive £10.5 million as part of the £20 million rapid research response funded by UK Research and Innovation, and by the Department of Health and Social Care through the National Institute for Health Research.

Yielded Benefits:

By the end of April 2020, the Recovery trial had successfully established over 160 sites across the UK and recruited over 8000 participants treated in hospital for Covid-19. The data linkage already established to received SUS+ and other data is providing important information to the Data Monitoring Committee on a weekly basis about patients' recovery (i.e. discharge from hospital), in-hospital death and procedures required. Provision of complete and reliable data to the DMC through May and early June 2020 is critical to allow robust assessment of the effects of the the trial treatments with a major contribution to these data expected from analysis of the routine health care data requested under this agreement.

Expected Benefits:

- improving the health of the whole population by sharing information and expertise, and identifying and preparing for future public health challenges/COVID-19 challenges

- researching, collecting and analysing data to improve understanding of this public health challenge, and come up with answers to public health problems arising from COVID-19

- providing reliable information on potential treatments for COVID-19 and potentially changing the standard of care that the NHS offers which could improve outcomes for many thousands of patients

Outputs:

COVID-19 is an emerging pathogen which presents a significant threat to the population in terms of increased morbidity and mortality, particularly among vulnerable groups such as those with pre-existing disease.

The primary objective is to provide reliable estimates of the effect of study treatments on in-hospital death (with subsidiary analyses of cause of death and death at various timepoints following discharge).

The secondary objectives are to assess the effects of study treatments on duration of hospital stay; the need for (and duration of) ventilation; and the need for renal replacement therapy.

The interim trial results will be monitored by an independent Data Monitoring Committee (DMC). The most important task for the DMC will be to assess whether the randomised comparisons in the study have provided evidence on mortality that is strong enough (with a range of uncertainty around the results that is narrow enough) to affect national and global treatment strategies. In such a circumstance, the DMC will inform the Trial Steering Committee who will make the results available to the public and amend the trial arms accordingly.

The data requested will be used to evaluate the efficacy and safety of the study treatments and will help shape the public health response. The rapid feed will be used to ensure that the trial Data Monitoring Committee have complete, up-to-date information on the major outcomes in the trial on which to base their decisions. If they find compelling evidence of efficacy or safety then that arm may be stopped and – if effective – added to standard care across the NHS.

All outputs produced will be in the form of aggregated reports with small number suppression applied.

Processing:

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

The University of Oxford will act as the trial Sponsor. The trial will be coordinated by a Central Coordinating Office within the Nuffield Department of Population Health staffed by members of the two registered clinical trials units – the Clinical Trial Service Unit and the National Perinatal Epidemiology Unit Clinical Trials Unit. Both of these units are at the University of Oxford. University of Oxford is the sole data controller for this piece of work. The data will be collected, analysed and published independently of the source of funding.

The initial proposal is to set up a feed of SUS APC data for the patients in a cohort list provided by University of Oxford. The process is as follows

• Details of the patient cohort (initial list and updates) to be emailed to a secure nhs.net account from another nhs.net account. It will be indicated that the email is in regards to the Oxford COVID-19 Study Trial. The initial list of patient identifiers will include study ID's and NHS numbers and date of birth.
• NHS Digital SUS team will report back any NHS Numbers which are not found in PDS (will do this for any new numbers that NHS Digital are sent as NHS Digital are sent them)
• Each week NHS Digital will provide a file of all records received by SUS for patients in the cohort (as updated with any new NHS Numbers)
• NHS Digital will send the extracts of data (baseline and deltas) to a MESH mailbox.
• The SUS APC extract will also include the date of death from PDS and the death status from PDS - this will all be sent as one extract in replacement of the Civil Registration Data Set for this iteration of the data sharing agreement.

Following on from the SUS APC dissemination - NHS Digital will do the following

• Link the cohort to Hospital Episode Statistics Data (HES) and provide back to University of Oxford

The linked data set will be sent back to Oxford via SEFT [Secure Electronic File Transfer System].


Further developments could include (and would be subject to approvals); the following:

• Automate the update of the patients in the cohort list
• Provide historic data for NHS numbers added to the cohort
• Use the Master Patient Service to try to identify the correct NHS Number based on patient name etc

All data shared under this agreement will be processed and stored in secure locations within England and Wales and will not be shared outside University of Oxford, other than in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.


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

Type of data: information not disclosed for TRE projects

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: No, Yes (Academic)

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

When:DSA runs 2019-10-05 — 2022-10-04 2017.09 — 2024.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Hospital Episode Statistics Critical Care
  5. Hospital Episode Statistics Outpatients
  6. Hospital Episode Statistics Accident and Emergency
  7. Hospital Episode Statistics Admitted Patient Care
  8. Civil Registration - Deaths
  9. Demographics
  10. Cancer Registration Data
  11. Emergency Care Data Set (ECDS)
  12. HES-ID to MPS-ID HES Accident and Emergency
  13. HES-ID to MPS-ID HES Admitted Patient Care
  14. HES-ID to MPS-ID HES Outpatients
  15. National Diabetes Audit
  16. Hospital Episode Statistics Accident and Emergency (HES A and E)
  17. Hospital Episode Statistics Admitted Patient Care (HES APC)
  18. Hospital Episode Statistics Critical Care (HES Critical Care)
  19. Hospital Episode Statistics Outpatients (HES OP)
  20. Civil Registrations of Death
  21. Diagnostic Imaging Data Set (DID)
  22. Medicines dispensed in Primary Care (NHSBSA data)
  23. Mental Health and Learning Disabilities Data Set (MHLDDS)
  24. Mental Health Minimum Data Set (MHMDS)
  25. Mental Health Services Data Set (MHSDS)

Objectives:

The aim of the British Heart Foundation (BHF)-funded ‘A Study of Cardiovascular Events iN Diabetes’ (ASCEND) randomised trial is to determine reliably whether aspirin (100mg daily or matching placebo) and/or supplementation with omega-3 fatty acids (1g capsule or matching placebo) safely prevents cardiovascular events and deaths in patients with diabetes, who do not already have clinically manifest arterial disease. Although aspirin is recommended for people with arterial disease, since it also causes bleeding, the balance of benefits and possible harms are not clear in this group with diabetes.

The study is funded by the British Heart Foundation and the packaged study treatment is provided free of charge by Bayer Pharma AG [100mg aspirin/matching placebo] and Abbott Products Operations AG [1g omega-3 capsule/matching placebo].

15,480 participants were randomized between June 2005 and July 2011 and median follow-up is currently ~4 years with a planned duration of at least 7 years. All serious adverse events (SAEs) are to be recorded among the randomised participants to allow detailed analyses of both the safety and efficacy of trial treatments. In order to reliably record and code reported SAEs during follow-up, as outlined within the study protocol, the team require clinical information about diagnoses and operations, including dates of occurrence. Access to electronic central records of hospital episodes will allow this complete and unbiased follow-up and appropriate intention-to-treat analyses.

The sensitive identifiable fields are required to ensure robust linkage to ensure that the records pertain to the correct participant, which is vital for the accuracy of the study data. The HES data will also provide additional confirmation of some participant reported events. The HES data relevant to the trial outcomes (heart attacks, strokes etc.) will be further followed up via GPs for additional information, and will be reviewed by study clinicians (who remain blind to treatment allocation) with the aim of confirming or refuting events.

Yielded Benefits:

For the on-treatment phase of the ASCEND study, the analyses have shown conclusively that aspirin reduces the risk of vascular events in primary prevention, as it does in people who already have cardiovascular disease, but these benefits are largely counter-balanced by the number of major bleeds caused by aspirin. This is an important finding with implications for many millions of people who have diabetes but have not yet had cardiovascular events. Previous clinical guidelines have varied in their recommendations about the use of aspirin for primary prevention because of a previous lack of clear evidence. The results of ASCEND now provide much needed clarity. The findings are likely to be widely incorporated into future guidelines for the prevention of cardiovascular events in people with diabetes both nationally and internationally. The World Health Organisation statistics detail 422 million people with diabetes in 2014, a rise of almost 400% since 1980. The prevalence of diabetes in the UK and global population is expected to continue to rise.

Expected Benefits:

ASCEND is a high profile trial (already widely referred to in international journals) whose results have the possibility of influencing national and international guidelines for the use of anti-platelet therapy in this very large patient group (currently at least 3M in the UK and over 300M worldwide). Access to the data requested will allow a complete and unbiased analysis of the benefits and hazards of allocation to aspirin and to omega-3 fish oils in the ASCEND study, thus enhancing the reliability of the study findings. The study results are expected in 2018 but any changes to treatment guidelines as a result of the ASCEND trial may take several years to emerge.

Outputs:

The main outputs from the research will be in the form of scientific reports of the results of the trial. If ASCEND can reliably demonstrate that aspirin and/or omega-3 FA safely reduce the risk of cardiovascular events, cancers and deaths in diabetic patients, without pre-existing occlusive arterial disease, this would be relevant to some hundreds of millions of people world-wide currently not receiving such therapy, and could save tens of thousands of lives each year. On the other hand, if the risks of serious bleeding outweigh or are similar in magnitude to the cardiovascular benefits in this group, then these risks could be avoided by the very large number of diabetic patients who are currently being treated with aspirin.

The results will be presented during 2018 at international scientific meetings and published in a prominent peer-reviewed medical journal within about a year. The arrangements are not yet finalised but the international meeting is likely to be one of: American Diabetes Association, European Society of Cardiology or the American Heart Association. The journal is likely to be The Lancet but again not finalised at this stage. In addition the BHF will play a role in the advertising and promotion of the results. The results are likely to be incorporated into an individual participant data meta-analysis of similar trials run by the Anti-thrombotic Trialists Collaboration.

All outputs will consist of aggregate data only with small numbers suppressed in line with HES analysis guide.

In addition to this the two pharmaceutical companies providing the medication and matching placebo for the study and some funds to cover the costs of packaging the treatment have an interest in seeing these treatments (aspirin and fish oils) properly evaluated in a large well run randomised trial. They will receive the same publically available results. If the study results show benefits for diabetic patients, the pharmaceutical companies may wish to use tabular data from the study to seek approval from the regulatory agencies for the marketing of these treatments to this group. The data provided would be aggregated with small numbers suppressed in line with the HES Analysis Guide.

If a submission is made to a regulatory agency, the Clinical Trial Service Unit at Oxford University would provide relevant information in the form of tabulations of numbers (for example: number of participants randomized, experiencing serious or other adverse events) with no individuals being identifiable in any submission. There would be considerable overlap between any tabulations provided to the companies and the published results, however the companies might ask for specific detail that were not considered necessary to publish. No participants will be identifiable in any information provided and the pharmaceutical companies do not have any influence in the research or the results. All data provided to the companies would be aggregate with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Information is collected routinely of the ~15,480 participants who were randomised between June 2005 and July 2011 by postal questionnaire however, over time, some participants stop returning questionnaires and this is more likely among people who have also stopped their study treatments. To minimise bias all participants need to be followed-up irrespective of whether they have been taking their study treatments and all events included in intention-to-treat analyses.

In order to comply with the EU Clinical trials directive, the data received will be transferred into the trial database by the person registered to receive data. The ASCEND trial database is study specific and is stored on an ASCEND specific server. The identifiable HSCIC data is stored in an encrypted TrueCrypt container to which access is granted on a "need to know" basis i.e. the level of access will depend on the staff role. All such access will be granted on the instruction of the Information Asset Owner for ASCEND. Access is routinely reviewed and revoked when the team member leaves ASCEND. The complete supplied HES data will need to be retained for 15 years (as per the ASCEND Protocol, section 2.4.6) as the team need to be able to trace all study medical events (some of which may be identified from HES data) back to source data to comply with the European Medicines Agency guidelines for good clinical practice and have this readily available during any Medicines and Healthcare Products Regulatory Agency (MHRA) inspection.

The ASCEND study team shall not, except as may be strictly necessary for carrying out the project, provide or otherwise make available the HES or ONS data to any third party or allow use of it or them by or on behalf of any third party, in whole or in part, whether by way of sale, resale, loan, transfer, hire or any other form of exploitation. This statement is intended to cover the situation where there may be a need to write to an individual participant’s GP for further clarification about a medical event or death to support the adjudication coding process undertaken by the study medical team. The event/death may have been supplied by ONS/HSICIC although the source of the event would not be supplied to the GP. Clinical trials involving Investigational Medicinal Products (IMPs) are legally required to comply with GCP which is regulated by the MHRA so this phrase also covers MHRA Good Clinical Practice inspections, during which an inspector may see an individual record with a medical event or death recorded which may have been supplied by ONS/HSCIC.

Cause of death data from the Office for National Statistics has been processed by NHS Digital through a separate Data Sharing Agreement and will be assessed separately when the agreement is due for review in March 2017.


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

Type of data: information not disclosed for TRE projects

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), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., National Health Service Act 2006 - s251 - 'Control of patient information'. ; Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. ; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

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

When:DSA runs 2011-05-25 — 2026-05-24 2016.05 — 2024.03.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. MRIS - Members and Postings Report
  5. Hospital Episode Statistics Admitted Patient Care
  6. MRIS - Scottish NHS / Registration
  7. Demographics
  8. Cancer Registration Data
  9. Civil Registration - Deaths
  10. MRIS - Personal Demographics Service
  11. MRIS - Bespoke
  12. HES-ID to MPS-ID HES Admitted Patient Care
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Civil Registrations of Death

Objectives:

Evaluating the age extension of the NHS Breast Screening Programme - Age Extension (AgeX) trial

The NHS Breast Screening Programme (NHSBSP) routinely invites women aged 50-70 years to come for three-yearly screening. Because of uncertainty about the effects of screening outside this age range, an England-wide cluster-randomised trial is under way to assess the risks and benefits of additional invitations for screening at ages 47 to 49 and, separately, after age 70 (currently 71-73).

Random allocation of small clusters of participants is used to determine (in a 50:50 ratio) which women are offered one additional screening invitation before age 50 and which are not, and which women are offered additional screening after age 70 and which are not. This trial will involve about 71 of the 81 breast screening units in England and will randomize at least two million women aged 47-49 and one million aged 71-73 to be invited for additional screening. Women will be followed up by routine electronic linkage to NHS and ONS mortality records to assess short-term and long-term effects of the additional screening on: patterns of investigation, detection and treatment of breast lesions; breast cancer incidence; breast cancer mortality; hospital admissions; and overall mortality.

The principal outcome for screening before age 50 and, separately, after age 70 will be breast cancer mortality, eventually subdivided by 5-year time periods (0-4, 5-9, 10-14 years, etc.) since random allocation. Subsidiary analyses will assess effects on other outcomes. The main results are expected in the mid-2020s.

When the main results of the trial are available results will be reported to the Advisory Committee on Breast Cancer Screening which oversees the NHSBSP and reports to government ministers. The NHSBSP sets the standards for the screening units and monitors performance through a national quality assurance network.

The data will be pseudonymised before analysis and will not be shared with any third parties.

The reason for this trial is to provide definitive evidence on an issue that has been the subject of controversy for over 15 years – specifically whether the harms of breast screening outweigh the benefits. Previous trials have evidenced the benefits without sufficiently evidencing the potential harms. Numerous claims and counter claims have been made and continue to be made emanating from such sources as patient groups, publications, scientific literature and in the media. The nature of the claims varies over time. For example, it may, at different times, be claimed that harms include increases in operations, hospital stays, related health episodes of specific types, etc. Such claims are typically varied with a lack of definitive supporting evidence.

This trial aims to amass and analyse sufficient evidence that will enable the final reports to provide definitive unequivocal evidence. Where such claims of harm have been made, the trial will investigate the validity and tailor the content of planned reports to provide responses. Due to the potentially wide variety of possible harms which might be attributed to screening, the trial requires wide ranging hospital episode data not restricted to specific types of episode.

The number of women involved in the trial is necessarily large in order to ensure that the findings of the trial are unequivocal. The sample size has been reviewed by numerous committees and accepted as being appropriate.

In terms of the number of years of data required, it is necessary to have data over such a long period because firstly, the screening programme currently offers women 7 screenings between the ages of 50 and 70 and the trial is investigating the effect of adding just one screen to the existing 7 routinely offered. Therefore the screening period is already more than 20 years and effects of screening are likely to become visible at least 10 years after the first screening. Secondly, it is essential for the trial design to have information on morbidity prior to randomization. It is well established that women with prior co-morbidities are less likely to attend for screening, when invited. It is stated explicitly in the protocol that groups of women will be excluded from the main analyses where there are known (on the basis of information collected before randomization) to be unlikely to accept an invitation for screening. It is therefore a fundamental requirement that the trial analyses HES data going back as far as is possible.

Yielded Benefits:

No benefits to date the study is due to be completed in the mid-2020s

Expected Benefits:

The aim of the trial is to assess reliably the risks and benefits of additional NHS invitations for breast screening before age 50 and, separately, after age 70. The results are expected to help determine future NHS policy on age at breast screening. The main results are not expected before the mid-2020s but interim results will be reviewed and the trial end date may be brought forward if the evidence is clear before then.

Public Health England will use the findings to inform government and influence policy. This will affect breast screening policy in the UK and influence policy in much of the rest of the world for decades after the results have published.

The benefits of interim analyses are that these will be used to monitor the protection and safety of trial participants in addition to feeding into the wider trial aims.

Outputs:

The primary output of the study will be findings disseminated by publications in peer-reviewed open-access journals and presented at medical conferences to academics, NHS national policy makers and on the web. The results are expected to help determine future NHS policy on breast cancer screening outside the 50-70 age group. The main results are not expected before the mid-2020s.

Outputs will include only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

As with any clinical trial, it is necessary to gather evidence incrementally throughout the course of the trial in order to check that the trial itself is not exposing participants to increased risk of harm or, conversely, to check for evidence of benefits. The trial end date is not fixed and may be brought forward if at any stage, sufficient evidence is obtained.

The outputs from the interim analyses will be annual reports to the Data Ethics and Monitoring Committee who may also request additional analyses within the scope of the clinical trial’s objectives if they identify the need. The Data Ethics and Monitoring Committee report any concerns about the trial or findings to the trial management group.

Processing:

To date, identifiable details have been supplied to NHS Digital (formerly known as HSCIC) in separate batches for flagging on NHS Digital's MIDAS system and NHS Digital has supplied periodic updates on deaths, cancers and exits from NHS registration. Approximately 2 million cohort members have been flagged to date with the number to rise to 2.5m.

Further batches of trial participants will be supplied as new participants are randomised into the trial on an ongoing basis.

In addition to the ongoing supply of notifications, NHS Digital will perform further linkage to Hospital Episode Statistics data and supply the linked data to the CEU.

All data received from NHS Digital is linked with trial participants’ records from the National Breast Screening System and PHE cancer outcome datasets.

The purpose for collecting the data is to assess the short-term and long-term effects of the additional screening on: patterns of investigation; detection and treatment of breast lesions; breast cancer incidence; breast cancer mortality; hospital admissions, and overall mortality.

The data will be held exclusively at the Cancer Epidemiology Unit (CEU) at the University of Oxford and used solely for the purpose of this project.

All data (core trial data, including personal details, flagging information, deaths, cancers, externally linked data, some admin data) is held in a central database. Several internal ID's exist so that data can be appropriately structured. No statistical analyses of the data are performed directly on this database. Direct access to the entire database is limited to the database manager. Access to personal identifiers is required to process externally linked data, and to prepare datasets for external linkage to HES, ONS, Cancer Registration, NHS Registration and NHS Screening records.

Pseudonymised analysis data is extracted from the database, either as database views or via text files. When accessing views directly, appropriate roles exist to limit access to the required view(s) only. Analysis datasets will have no individual level identifiers but may have a group identifier e.g. year recruited or site recruited. Analysis datasets will never contain any personally identifiable data e.g. name, NHS number etc. ONLY linkage datasets will require this information. If required year and month of birth will be used instead of full date of birth or death.


Epidemiological and health services research using routine NHS data: work programme of the Unit of Health-Care Epidemiology, Oxford University — DARS-NIC-315419-F3W7K

Type of data: information not disclosed for TRE projects

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

Purposes: No (Academic)

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

When:DSA runs 2019-10-01 — 2022-09-30 2017.09 — 2024.03.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Office for National Statistics Mortality Data (linkable to HES)
  3. Civil Registration - Deaths
  4. HES:Civil Registration (Deaths) bridge
  5. Civil Registration (Deaths) - Secondary Care Cut
  6. HES-ID to MPS-ID HES Admitted Patient Care
  7. Civil Registrations of Death - Secondary Care Cut
  8. Hospital Episode Statistics Admitted Patient Care (HES APC)

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.


MBRRACE-UK - Delivering the National Maternal, Newborn and Infant Clinical Outcome Review Programme - National Surveillance of Perinatal Deaths — DARS-NIC-359651-H3R1P

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable, Yes, No (Section 251 NHS Act 2006, , )

Legal basis: Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., , Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2017-04-01 — 2020-03-31 2017.06 — 2024.03.

Access method: Ongoing

Data-controller type: HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), HEALTHCARE QUALITY IMPROVEMENT PARTNERSHIP (HQIP), NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Birth Notification Data

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).


DART: The Integration and Analysis of Data using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases — DARS-NIC-668928-L9N5F

Type of data: information not disclosed for TRE projects

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

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

Purposes: Yes (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2023-10-26 — 2024-10-25 2024.02 — 2024.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

The University of Oxford requires access to NHS England Data for the purpose of the following research project:
DART (The Integration and Analysis of Data using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases)

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

DART is a study developing integrated diagnostics to enable the earlier diagnosis of lung cancer. This study, which began in 2020, aims to improve patient survival, yielding time and cost efficiencies to the NHS. The overall objective of the study is to link data from the Targeted Lung Health Checks (TLHC) programme, collected by the Lung Health Centres and sent to Oxford University Hospitals NHS Foundation Trust (OUH), with NHS England Data to better predict those who will benefit from lung cancer screening and to develop artificial intelligence systems that could improve understanding (through machine learning) of co-morbidities and confirm or improve standard clinical practices. Costs and survival will be summarised for groups of patients for various health states. It is anticipated that limited data will be received on secondary care resource use via the TLHC Programme. Based on initial inspections, this data will be fragmented, will cover a more limited follow-up period, and will not be available in detail for all participants in the TLHC programme. The Data requested from NHS England under this Agreement is expected to considerably enhance the study by providing less biased data and ensuring that missing secondary care resource use data is minimised.

Another objective of DART is to improve and enhance the existing evidence base on outcome prediction for patients with lung cancer. The requested Data will be used to identify patients with lung cancer who relapse or die; analyses using these Data will assess the efficacy of current and proposed clinical approaches.

OUH has been granted and funded for a Trusted Research Environment (TRE). The data from DART will be stored in this TRE, which will be managed in accordance with the relevant approvals from the Confidentiality Advisory Group (CAG), health Research Authority (HRA), and the Research and Development Department of the OUH. Access to the TRE for researchers will be governed by the above regulations and will require detailed applications and approval by the TRE Data Access Committee (TRE DAC). The NHS England data requested for DART will be stored in the DART section of the TRE.

DART has a total of nine work packages
• WP1 Leadership and Project Management
• WP2 Planning for, and management of Datasets, and Integration
• WP3 AI Model Validation on Lung Cancer Screening (LCS) data
• WP4 Digital Pathology AI and Radiomics Model Development and Validation
• WP5 Chronic obstructive pulmonary disease (COPD)/ Coronary artery disease (CAD) Model Development and Validation
• WP6 Primary Care/Population Health and Health Economics
• WP7 Integration of Blood Biomarkers
• WP8 Outcome prediction and new treatment paradigms
• WP9 Quality assurance: radiologist training and monitoring

The requested Data will be used in multiple DART work packages (WPs 4, 5, 6, 8) to further its overall aims:

> WP4: This WP relates to development of an artificial intelligence algorithm to diagnose lung cancer from digital pathology images. The HES data will enable ground truthing (a Gold Standard that can be used to compare and evaluate model results) of cancer diagnoses and for the algorithm to learn which of the cancers are fatal and incurable.

> WP5: This WP relates to lung cancer comorbidity, and to maximising the clinical information gathered during a single computerised tomography (CT) exam study of the chest, to allow for earlier treatment of patients who have underlying, unrecognised diseases or conditions such as Chronic Obstructive Pulmonary Disease (COPD) and Coronary Artery Disease (CAD). The aim of WP5 is to automate the identification of comorbid states (COPD and CAD) related to or caused by lung cancer, by developing and implementing machine learning models. The aim is to utilise all standard of care data captured during the lung cancer screening programme, if available through the normal course of clinical practice, to identify incidental findings that may be picked up in the TLHC patient cohort through the screening programme.

> WP6: The aim of half of WP6 is to assess whether the addition of an AI component to the Lung Cancer Screening Programme (LCSP) in England is cost-effective, compared to current practice. This is to be achieved by constructing a decision-analytic model to evaluate resource use, costs and health outcomes for patients in the LCSP over time, with and without the AI component in place. A specific type of model will be built – a state transition model – in which patients move between different lung cancer specific health states periodically over a time horizon of several years. By spending time in these health states, patients accrue costs and health outcomes. The requested HES-TLHC linked Data will be used to determine an appropriate cost for each health state, and the requested linked mortality Data will be used to inform estimates of survival outcomes in each health state. To achieve the former, the HES-TLHC linked Data will be combined with NHS Reference Costs to calculate the secondary care costs accrued by patients in specific health states.

> WP8: The aim of WP8 is to improve and enhance the existing evidence base on outcome prediction for patients with lung cancer. The aim is to identify predictors of unexpected (usually poor) outcome. This will require a wide spectrum of data that might help predict, for example, greater mortality, lower recurrence-free survival and overall survival than expected having accounted for all of the known factors that influence these (such as age, performance status and stage). This will be achieved by using the requested Data linked to TLHC data to identify patients with lung cancer who relapse or die. Analyses will be undertaken using this data to confirm the efficacy of current clinical approaches and suggest standardised approaches that may reduce unwarranted variation. The results of these analyses will also be used to challenge existing practice that does not meet the outcomes achieved in better services and suggest new paradigms of care by identifying novel markers of unexpected outcomes. WP6 and WP8 are necessarily linked: the model that will be constructed in WP6 will be adaptable such that the cost-effectiveness of standardised and new clinical approaches can be tested.

The other work packages will not use the NHS England data provided under this Agreement.

The following NHS England Data will be accessed:

> Hospital Episode Statistics; necessary for the analysis of the algorithms developed in WP5 to determine if they can detect and quantify clinically meaningful COPD and CAD from the Lung Cancer Screening CT scans, and the requested HES-TLHC linked Data will be used to determine if the AI algorithms developed relate to clinically important episodes. For WP6, HES Data is required for the cost-effectiveness analyses and the requested HES-TLHC linked Data will be used to determine an appropriate cost for each health state. For WP8, the HES data is required for the analysis of the algorithms developed in this work package to determine if they can determine whether and why, patients from the TLHC Lung Cancer Screening CT scans die from lung cancer and are not cured despite having early-stage disease. Specifically, the following HES Data is required:
- Admitted Patient Care - necessary to determine how often patients from the TLHC are admitted to hospital and whether it is due to COPD, CAD or lung cancer.
- Accident & Emergency - necessary to determine how often patients from the TLHC are seen in Emergency Departments, and whether it is due to COPD, CAD or lung cancer and to estimate costs associated with lung cancer treatment.
- Critical Care - necessary to determine how often patients from the TLHC are admitted to ICUs and whether it is due to COPD, CAD or lung cancer and to estimate costs associated with lung cancer treatment.
- Outpatients - necessary to determine how often patients from the TLHC are seen in OPs and whether it is due to COPD, CAD or lung cancer and to estimate costs associated with lung cancer treatment.
> Emergency Care Data Set (ECDS) – necessary to determine how often patients from the TLHC are seen in Emergency Departments, and whether it is due to COPD, CAD or lung cancer and to estimate costs associated with lung cancer treatment.
> Civil Registration Mortality - necessary to determine whether patients from the TLHC centres have died from COPD, CAD or lung cancer and because mortality Data will be used to inform estimates of survival outcomes associated with health states.
> Cancer Registration - necessary to determine who in the cohort has / has had cancer and who has died from it.

The level of the data will be:
> Identifiable – NHS number is required to link the NHS England Data to the TLHC data.

The data will be minimised as follows:
> Limited to a study cohort identified by Oxford University Hospitals NHS Foundation Trust (OUH) – approximately 300,000 participants of the TLHC programme
> Limited to data for episodes after the start date (individual specific; this will be the date the cohort member attended their screening). Cancer and deaths data will not be filtered in this way.
> Data access is minimised according to the research purpose within the TRE. This means that researchers within each distinct work package will have access only to the Data that they need.

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

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

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

Early detection and treatment of asymptomatic patients is crucial. Detecting lung cancer early when it is small and seen on a CT scan as a small nodule is currently recognised as the best way to do this. The ambition the DART study is to see if some of the aspects of lung cancer screening can be improved, which is expected to provide public healthcare benefits.

The funding is provided by Innovate UK, with in kind funding (non-monetary) from GE Healthcare (GEHC) and Roche Diagnostics Ltd. The funding is specifically for the component of the project described. Funding is in place until the end of March 2024.

OUH, GEHC, Optellum and Nottingham University Hospital NHS Foundation Trust (NUH) are processors acting under the instructions of the University of Oxford.

Microsoft Limited provides IT hosting services to OUH and will store the Data as contracted by OUH.

A Patient and Public Involvement and Engagement (PPIE) group assisted with the grant application and another PPIE group assisted with the programme design after the grant was received and has an on-going role in advising the project through quarterly meetings and ad hoc email/video calls as needed.

GEHC are a commercial organisation and a processor under this Data Sharing Agreement for the purpose described. They will be using the data obtained under this agreement, in combination with the data DART is obtaining from the Targeted Lung Health Checks, to develop and improve artificial intelligence algorithms to better predict respiratory conditions such as cardiac diseases and COPD.
GEHC make a considerable (over 1 million pounds) kind contribution to the project and, as a commercial company, would naturally expect a commercial gain and the publicity associated with participating in a prestigious project which has attracted Government and national media attention. The expected health and social care benefits of their contribution into the project outweigh any commercial gain they would receive from the project.

Alongside the University of Oxford academic team, Roche Diagnostics Ltd make an in-kind contribution of their expertise into WP4 and have loaned a Digital Pathology Scanner to DART (in Oxford) and provided a staff member to operate this. As a funder and commercial organisation, Roche Diagnostics reasonably expect a commercial return and to receive acknowledgement and publicity for their participation in the project. In turn, their contribution to the earlier detection of lung cancer far outweighs any likely commercial return.

Expected Benefits:

The requested Data will be used to undertake analyses that are expected to reveal:
• The cost-effectiveness of adding an AI component to the Lung Cancer Screening Programme in England, compared to current practice.
• The efficacy of (a) current clinical approaches to outcome prediction; (b) plausible standardised approaches to outcome prediction, and (c) potential new paradigms of care by identifying novel markers of outcomes.

It is expected that these findings will have the following benefits for patients in the English NHS, and the health sector overall:
• Lung cancer could be more accurately diagnosed, with enhanced prognostic information.
• The time to diagnosis for lung cancer could be reduced.
• The frequency of use of harmful invasive procedures in the diagnostic pathway could be reduced.
• Selection of patients for lung cancer screening could be improved, reducing the overall cost allocation for this.
• The assessment of risks from comorbidities could be improved.

The results of the planned analyses will be communicated directly to the National Screening Committee (NSC) by collaborators who also have a position on this committee, thus ensuring that the findings directly influence and optimise the implementation of the Lung Cancer Screening Programme. Results will be communicated to the NSC upon the completion of DART in March 2024, and are thus expected to begin to translate into direct patient benefit quickly. Around 48,000 people are diagnosed with lung cancer every year in the UK, so the potential health benefits and cost impacts could be significant.

Outputs:

The expected outputs of the processing will be:
> A report of findings to funding bodies (Innovate (part of UK Research and Innovation); Cancer Research UK (CRUK)): expected March 2024
> A summary of findings to relevant stakeholders (Innovate UK, CRUK, Roche, Optellum, GEHC): Expected March – May 2024
> Submissions to peer reviewed open-access journals: Specific target journals will be identified as the work progresses to ensure the study findings are communicated to appropriate audiences. Expected January – June 2024
> Presentations will also be given at national and international conferences relevant to lung cancer and screening

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

The outputs will be communicated to relevant recipients through the following dissemination channels:
> Journals
> The results of the planned analyses will be communicated directly to the National Screening Committee (NSC) upon the completion of DART in March 2024 by collaborators who also have a position on this committee
> Results will be shared with the staff at the TLHC centres and other operational staff involved in lung cancer screening
> DART Patient and Public Involvement and Engagement (PPIE) contributors, including the Roy Castle Lung Cancer Foundation, will be consulted to communicate findings to the general public and patients in an accessible way
> Results will be communicated to the National Screening Committee upon the completion of DART in March 2024
> National and International conferences

Outputs are expected throughout 2024.

Processing:

OUH will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Gender, Date of Birth, and a DART Study ID) for the cohort to be linked with NHS England Data.

NHS England will provide the relevant records from the HES APC, HES CC, HES OP, HES A&E, ECDS, Civil Registrations of Death, and Caner Registration Data datasets to OUH. The Data will:
> Contain directly identifying data items including NHS number which are required to link the NHS England Data to the lung health check data.

The Data will not be transferred to any other location.

The Data will be stored on servers at OUH. OUH also stores data on the TRE which runs on the Azure Cloud provided by Microsoft Limited.

The Data will be accessed onsite at the premises of OUH.

The record-level Data will also be accessed on the DART TRE by authorised personnel via remote access. The Data will remain on the servers at OUH and Microsoft Limited at all times.

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

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

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

Only aggregated data with small numbers suppressed can be exported from the TRE, via a secure Airlock Policy.

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

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

The Data will be linked at person record level with data from the TLHC programme. The Data will not be linked with any other data.

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

Analysts from the OUH, NUH and University of Oxford will analyse the data for the purposes described above.
Optellum and GEHC users will access the data for the purpose of developing AI tools to achieve the purpose described above.


MR1086 - The Oxford Vascular Study (consent cohort) — DARS-NIC-653950-W8D4Z

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-07-01 — 2025-06-30 2023.12 — 2024.02.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Demographics
  3. Civil Registrations of Death

Objectives:

The following provides background information on the purpose of the original study:

The Oxford Vascular Study (OxVasc) began in April 2002 to determine mortality, disability, psychological morbidity, cognitive decline and cost of care following stroke, transient ischaemic attack (TIA), Acute Coronary Syndrome (ACS) and acute peripheral vascular events in patients registered in one of eight GP practices in Oxfordshire.

ACS is the leading cause of death in the developed world, causing more than twice as many deaths as stroke. However, mortality data underestimates the burden of stroke. Stroke is the main cause of neurological disability in the developed world, and a common cause of dementia, depression, epilepsy, falls and fractures. The incidence, case fatality, longer term sequelae of stroke and ACS have never been measured in the same population at the same time. Comparison of OCSP (Oxford Community Stroke Project) and OXMIS (Oxford Myocardial Infarction Study) which took place in the early 1980s suggests that mortality due to stroke is lower than that due to ACS, but overall incidence is similar, and the total clinical instance of stroke may be greater. There are no data from the UK on recent time trends in age and sex specific incidence or disability rates for stroke and ACS. However, there have been major changes over the last 20 years in the life-style, primary and secondary prevention treatments and particularly in population demographics. A formal comparison would provide a firm basis on which local and national policy decisions about allocation of limited NHS funding for clinical services and limited governmental funding for medical research could be made.

OxVasc is one of a number of cohort studies funded by the National Institute for Health and Care Research (NIHR) to identify simple low cost interventions and to inform the development of clinical trials to improve the treatment outcomes of vascular disease in the short and long term. By recruiting all eligible participants from a defined population and following them up over a long period of time, OxVasc reduces recruitment bias so the results are more generalizable to the population as a whole and can identify whether the benefits of any intervention are maintained (e.g. sustained blood pressure monitoring and treatment, carotid surgery).

The GDPR legal bases for processing the data held under this Agreement are Article 6(1)(e) (processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller) and Article 9(2)(j) (processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes). This research into the health outcomes for people who have suffered from stroke or other vascular events is a task in the public interest under General Data Protection Regulation (GDPR) as it aims to improve care for all patients considering undergoing this type of process – informing clinicians and commissioners of variation and outcomes and complications to support work to improve and standardise treatment selection choices. The protocol has had appropriate ethics committee approval and CAG support (all documentary evidence is included in this application.

Since 2008, mortality and demographic data were supplied to the University of Oxford by ONS and subsequently the Health and Social Care Information Centre (which has since become NHS Digital) for the purpose of this research study. The overall aims of the study have not changed since 2002 and the benefits of a cohort study of this length and detail will continue to improve the public’s health through disease prevention, earlier disease diagnosis and better disease management. The study to date has had significant impacts (as described in the benefits section) and it is expected that further measurable benefits will be outputs that underpin NICE and other Department of Health strategies for detection, management and treatment of vascular disease.

The minimal information is requested under this agreement to meet the aims of the study and ensure integrity of study outputs, specifically:

Date of death-survival after vascular event to evaluate treatment interventions, natural history of disease and to stop further contact for follow up visits.
Place of normal residence and place of death-health economic analyses of recovery and use of assisted living/institutional care.
Cause of death (including ICD10 codes and free text) to establish underlying and contributing factors to death.

The University of Oxford previously flowed identifying information to NHS Digital for the purpose of list cleaning. The University of Oxford used the list cleaning service to provide a newsletter to participants. Upon receipt of the Demographics data, University of Oxford will destroy this data and provide a data destruction certificate to NHS Digital as it will no longer be required.

No attempt is made to contact families after the death of a participant notified to the study team through this process.

The analyses are determined by the Principal Investigator (PI) and the study statistician and performed by the University of Oxford research team to support the aims and objectives of the study. Ethical approval and grant funding from the Wellcome Trust and the NIHR Oxford Biomedical Research Centre have been granted for the study, for the same purposes as described in this Agreement.

The progress is evaluated annually and new analyses are added or completed based on findings to date and the length of time required to collect outcomes (cause of death) to determine the prognosis of different presentations of vascular disease and/or achieve statistical power to answer the research question. For example, mortality data is required to determine the outcome (disability or death) and time course of bleeding requiring medical attention in patients taking long-term antiplatelet treatment after acute vascular events. This is then used to estimate the age-specific numbers needed to treat to prevent upper gastrointestinal bleeding with routine proton-pump inhibitor co-prescription.

Not all of the work of the Oxford Vascular Study involve use of data on mortality obtained from NHS Digital but use of the data will be important in some analyses in order to determine firstly the impact of any treatment on survival and secondly the health economic value of any intervention e.g. prevention of recurrent stroke and subsequent health resource use.

The data subjects are patients registered in one of eight GP practices in Oxfordshire who have had a stroke, transient ischaemic attack (TIA), Acute Coronary Syndrome (ACS) or acute peripheral vascular events. These are the same practices (and associated demographic characteristics of the previous studies-OCSP/OXMIS) allowing valid comparisons over time. Since 2002, participants have been recruited from hospital, outpatients’ clinics or home following referral from a collaborating GP and interviewed by a researcher following written consent. Clinical information is gathered from participants about their health, medical history, family history and current treatment. The study team extract information about their vascular event and related conditions from health records for the duration of the study in order to follow up on participants health status. Regular face-to-face or telephone contact is maintained with participants and their GPs over the first two years and they are contacted again at five and ten years after entering the study. However, over this period participants may move out of Oxfordshire or register with a different GP. In order to achieve the study aims, accurate information on the date and cause of death of participants in the cohort to evaluate long term morbidity and mortality for the study population is required. For this reason, national data is required. Data will need to be shared at a record level as agreed between the University of Oxford and NHS Digital to flag and receive date and cause of death for each individual cohort member and in order to produce accurate matching. There is no alternative way to obtain all cause mortality data sufficiently robust to achieve the aims of the study. All results will be presented as aggregated data.

The earliest participants were recruited while the study was in a pilot phase and they were all asked to re-consent to participate in the full study when version 2 of the consent form (dated 28/12/2006) came into use. Under this Agreement, the University of Oxford is permitted to share with NHS Digital details of participants who have given consent using version 2 of the consent form or any subsequent version. The current Agreement does not permit the processing of data relating to any participant who was recruited using an earlier version - which did not include a declaration of consent for "information held by the NHS and records maintained by the General Register Office" to be used to maintain contact and follow up their health status - and did not re-consent using version 2 or a subsequent version. The data for these participants is to be obtained using section 251 support from the Confidential Advisory Group (CAG) under a separate Agreement, DARS-NIC-148369-8PPWK.

The University of Oxford is the sole data controller who also process the data supplied by NHS Digital under this Agreement. No other organisation determines the purpose for data processing or has any access to the data. Funding for OxVasc is provided by the Wellcome Trust and the NIHR Oxford Biomedical Research Centre. Past funding has been provided by the Stroke Association which is still acknowledged on some of the study outputs. The funders expect the Nuffield Department of Clinical Neurosciences to undertake research such as this but the funding body can not access data nor has a role in analysis or interpretation.

Yielded Benefits:

Expected Benefits:

The overall aims of the Oxford Vascular Study are to improve the public’s health through disease prevention, earlier disease diagnosis and better management of known risk factors. Results from the study to date have been used to underpin NICE guidelines and other Department of Health strategies (some of these benefits are described in yielded benefits to date) by providing evidence for ways to improve diagnosis of disease and how to effectively treat common risk factors such as high blood pressure.

The Oxford Vascular Study has ongoing funding from the Wellcome Trust and the NIHR to continue recruitment and complete follow up of the 25 year cohort. This will allow the study to continue providing new evidence to inform stroke prevention and vascular disease generally for the benefit of the population at large, with the continuing recruitment and long term follow up of OxVasc participants. These benefits fulfil the requirements necessary for data processing outlined in Article 6(1)(e).

The study also benefits the individual participants by providing:
1. Rapid assessment and treatment following TIA and minor stroke in order to identify the cause and provide treatment.
2. Ongoing assessment of vascular risk factors (BP, cholesterol), health care advice (smoking cessation, lifestyle advice) at follow up, enabling participants and the collaborating GP to improved secondary prevention of vascular disease.

Mortality data from NHS Digital also potentially reduces distress to participant’s relatives by attempting to contact them for follow up/information about circumstances of death.

The OxVasc study has been running for over 20 years, during which time many improvements in assessment/diagnosis and treatment of TIA, stroke and ischaemic heart diseases have been made. Analysis of morbidity and mortality over this time period is expected to provide additional insights into how further gains can be made in stroke prevention and care. An example of how long term cohort studies like OxVasc can direct further research is in stoke incidence in younger age groups, which appears to be increasing. A new study to better understand the role of treatable risk factors in young stroke patients which could potentially be informative for future clinical guidelines are now underway. (https://www.medicalresearchfoundation.org.uk/projects/contribution-of-the-presence-susceptibility-to-and-control-of-modifiable-vascular-risk-factor-in-young-stroke-and-tia-a-prospective-cohort-and-nested-case-control-study). This study is separate from the OxVasc study and does not use that data held under this Agreement, however, the new study builds on OxVasc research to improve treatment for young stroke victims.

Outputs:

The study overall has produced over 250 peer reviewed publications on incidence of disease, risk factor management, prognosis and outcomes. Peer-reviewed manuscripts on original research arising from the study are subject to the Wellcome Trust open access policy and are available to all free of charge on publication. A statement on data used and data sharing is provided in line with the individual publisher guidelines and the NIHR. The data received under this Agreement will continue to be used in the same way as previously outlined and is important for use in analyses of the effects of new/extended uses of primary and secondary prevention of vascular disease over a long period of time.

Research aims and findings from the Oxford Vascular Study are summarised on the study website (www.ndcn.ox.ac.uk/research/oxvasc) and presented at open days organised by the NIHR Oxford Biomedical Research Centre (BRC), Nuffield Department of Clinical Neurosciences and public involvement and engagement groups. Talks on OxVasc and related topics (e.g., high blood pressure, vascular dementia) are also available on YouTube (https://oxfordbrc.nihr.ac.uk/research-themes-overview/stroke-and-vascular-dementia/videos-stroke-and-vascular-dementia). Selected results of the study have been reported in the local, national and international press.

Participants are informed of progress with posters displayed with results of the study to date in the participating GP practices and the general information booklet which participants are given on entry to the study and updated yearly.

Yearly reports on the progress of this research have been given to the funders with all outputs and impacts for the previous year. Many of the outputs arising from the Oxford Vascular Study include data on mortality obtained from NHS Digital, often to corroborate information reported by hospitals, GPs and/or relatives of participants on cause of death. Data from NHS Digital provides the collated ICD10 codes, and these data continue to be important in some analyses together with the detailed clinical information collected from participants as part of the study. A statement regarding sharing of data collected from and about participants is available on the study website.

All outputs (presentations, posters, peer reviewed publications and oral presentations at conferences) report numbers at an aggregated level, with small numbers suppressed.

Processing:

The following provides background on the processing activities undertaken for the original study:

The study data, including data provided by NHS Digital under previous versions of this Agreement, are held by the University of Oxford. The data are stored electronically on University of Oxford central servers which are connected to the main University of Oxford’s network. At no time will sole employees of John Radcliffe Hospital have access to the data held on the server for University of Oxford.

Identifying details of participants have previously been supplied to ONS and subsequently NHS Digital so that their patient records could be flagged and mortality data could be reported to the study. The University of Oxford will flow identifiers (Surname, First name, NHS number, date of birth, study ID) to NHS Digital to update the cohort to flag participants recruited after 2018.

The data disseminated under this Agreement will only cover participants who have consented to this. Where section 251 support has been granted to meet the Common Law Duty of Confidentiality, the data for these participants is disseminated under a separate Agreement for this study: NIC-148369.

The following datasets are processed by the study:

i. Civil Registration Mortality data – details of participants’ deaths including date and cause;
ii. Demographics – details of embarkations or lost to follow up

Data received from NHS Digital will be linked to unique study ID using date of birth and NHS number to ensure a perfect match to each participant’s date of vascular event to calculate outcomes (Kaplan-Meier survival analyses). All data supplied by NHS Digital will be used only for the approved Medical Research Project MR1086-The Oxford Vascular Study. No data will be shared with any individuals or agencies outside of the study team and all study staff are substantive employees of the University of Oxford.

The data is held in an access-controlled server room within the University of Oxford Medical Sciences Division, situated on the Old Road Campus and connected to the main University network, located behind a firewall. Physical access is limited to Computer Services Department staff. Data will be encrypted using industry standard techniques meeting the Information Governance Toolkit standard (RBQ).


EXTEND Study: Needs-Assessed Care for Early Psychosis — DARS-NIC-474674-R3F7S

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Yes (Section 251 NHS Act 2006)

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

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2022-11-25 — 2025-11-24 2023.02 — 2024.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  2. Civil Registration - Deaths
  3. Emergency Care Data Set (ECDS)
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Mental Health Services Data Set
  7. Civil Registrations of Death
  8. Hospital Episode Statistics Accident and Emergency (HES A and E)
  9. Hospital Episode Statistics Admitted Patient Care (HES APC)
  10. Mental Health Services Data Set (MHSDS)

Objectives:

The University of Oxford requires access to NHS Digital data for the purpose of the following research project: EXTEND Study: Needs-Assessed Care for Early Psychosis

The EXTEND study team are researchers from universities across the UK, led by the Chief Investigator from the University of Oxford.

The following is a summary of the aims of the research project provided by the University of Oxford:
'The purpose of this research is to investigate the impact of alternative durations of Early Intervention in Psychosis (EIP) care on service users’ health outcomes. This will include understanding and contextualising the existing variations in the duration of EIP care provided and service user outcomes, and estimating the cost-effectiveness of an alternative, flexible, needs-assessed EIP service. To do this, the study team proposes to create and analyse a pseudonymised dataset linking routine health service data from NHS Digital, to a clinical audit dataset held by the Royal College of Psychiatrists (National Clinical Audit of Psychosis- NCAP).'

Early Intervention in Psychosis (EIP) services are phase-specific, multidisciplinary, community-based mental health teams that treat people who are experiencing, or who have recently experienced, their first episode of a psychotic illness. EIP services are the principal pathway for the treatment of an emergent psychosis in the NHS in England.

It is not known what the optimal length of treatment should be for individuals within EIP services. It is not known whether the length of treatment, in itself, improves or reduces the chance of a ‘good’ outcome. The majority (58%) of individuals with First Episode Psychosis (FEP) will have an initial remission of their symptoms after the first episode of psychosis and 38% will reach eventual symptomatic and functional recovery. There is also a significant proportion who do not reach remission nor recovery criteria after their FEP, representing 3000 people a year in England. Furthermore, there is a range of illness trajectories following a first episode, meaning the eventual outcome is not easy to predict at the beginning of the illness.

Given this range of possible outcomes and trajectories, it is likely that a flexible, needs-focused treatment is required for those who experience FEP, rather than the current standard package of 3 years of assertive community treatment for everyone. It is possible, therefore that some people would benefit from longer treatment within EIP to help sustain the improvements made in the first few years. Conversely, it is possible that the length of treatment in itself is not relevant, but it is the delivery of NICE-recommended treatments that is the most effective component of treatment, which could be delivered over a shorter timeframe.

The following NHS Digital data will be accessed:
• Hospital Episode Statistics (HES) Admitted Patient Care (APC)
• HES Accident & Emergency (A&E)
• Emergency Care Data Set (ECDS)
• Mental Health Services Data Set (MHSDS)
• Civil Registration Deaths (mortality)

The requested data from MHSDS, ECDS, HES and mortality will be linked with the pseudonymised records from the National Clinical Audit of Psychosis (NCAP). The linked dataset will provide data on a large representative cohort of patients receiving care from EIP services, together with detailed data on health service use and outcomes. This will allow an analysis of the objectives of the EXTEND study - the impact of the duration of EIP care on outcomes.

The level of the data will be pseudonymised.

The data will be minimised as follows:
• Limited to data for a study cohort identified from NCAP data in 2019/20 and 2020/21 which the Royal College of Psychiatrists will provide to NHS Digital.
• Limited to data between 2016/17 and latest available at the time of dissemination (expected in 2023).

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

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

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

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

The funding is provided by the National Institute for Health Research (NIHR). The funding is specifically for the EXTEND study - Personalised Care for Early Psychosis, funding is in place until May 2025.

Cardiff University and Imperial College London (co-investigators on the EXTEND project) will be data processors acting under the instructions of the University of Oxford.

The Office for National Statistics (ONS) is a data processor. The role of ONS role is limited to hosting and providing access to the NHS Digital data in their Secure Research Service (SRS). ONS will receive the NHS Digital data and will upload it to the Secure Research Service (SRS). NHS Digital data will not be stored on any premises other than those of the Office for National Statistics.

Other co-investigators on the project (including from Pennine Care NHS Foundation Trust, Leeds and York Partnership NHS Foundation Trust, Keele University, Centre for Mental Health and Manchester Metropolitan University) do not require access to the NHS Digital data and do not determine the means and purposes for processing for this specific study. These institutions are conducting qualitative, policy or project management work as part of the broader NIHR grant. This includes a Manchester Metropolitan University (MMU) professor who is the co-chief investigator (and is therefore listed as leading the project on publicly available material, including the privacy notice) but does not determine the means and purposes for the processing in this agreement.

This EXTEND study is part of an overall programme of research funded through the NIHR through a Programme Grant for Applied Research (PGfAR) and for which the Professor from MMU is Programme Chief Investigator. There are several work packages that different universities are leading and this study is being led by the Professor from University of Oxford as Chief Investigator for this specific study. Therefore, whilst the Professor at MMU has responsibility for the overall programme of research, for the purpose of this specific processing Oxford University is the sole data controller.

Data will be accessed by a PhD student affiliated with Imperial College London. The individual has completed mandatory data protection and confidentiality training and is subject to the University of Oxfords' policies on data protection and confidentiality. The individual accessing the data will do so under the supervision of a substantive employee of Imperial College London. Imperial College London would be responsible and liable for any work carried out by the individual. The PhD student would only work on the data for the purposes described in this Agreement.

A Public and Patient Information and Engagement (PPIE) group was consulted regarding the collection of the data for the purposes described above.

The study has convened an EXTEND patient and carer Involvement Group (EXTEND-InG), chaired by the two PPI co-investigators, which has already met to discuss the proposed data linkage and the methods for informing individuals affected.

Expected Benefits:

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

The use of the data could
• help the health and social care system to better understand the health and care needs of populations.
• lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
• advance understanding of regional and national trends in health and social care needs.
• inform planning health services and programmes, for example, to improve equity of access, experience, and outcomes.
• inform decisions on how to effectively allocate and evaluate funding according to health needs.
• provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from or areas of poorer practice that need to be addressed.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

This study intends to estimate the impact of alternative models of provision of Early Intervention in Psychosis care. If it finds that extended, or more flexible, duration of EIP care benefits patients experiencing First Episode Psychosis (FEP) and is cost-effective, it could guide the direct improvement of the National Health Service (NHS).

Evidence generated from the study may have relevance to tens of thousands of people with a diagnosis of psychosis. Furthermore, the data generated has the potential to impact on their carers, clinicians, service managers and Integrated Care Boards (ICBs).

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

The linked NCAP data and NHS Digital data may be suitable to be used as a resource for future research into care for early psychosis, subject to the required approvals.

Outputs:

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

The outputs of the processing will be national-level aggregates and modelling. Some statistics will be reported at the EIP team level (<100 individuals). Statistical disclosure risk for small numbers will be managed in line with the ONS protocols on disclosure risk for health data.

The expected outputs of the processing and how they will be communicated to relevant recipients through the following dissemination channels:
- Interim reports to the funder on the progress of data linking and causal inference.
- End of programme reports to the funder on each of the key work packages: understanding existing duration in EIP care; causal impact of different durations of EIP care on patient outcomes; cost-effectiveness of alternative duration EIP provision.
- Submissions to open-access peer-reviewed journals (e.g. Lancet Psychiatry or British Journal of Psychiatry).
- Presentations at national and international conferences (e.g. International Early Intervention Association / International Congress of The Royal College of Psychiatrists).
- Specific reports on findings for healthcare policymakers.
- Guidance for EIP service providers to aid in the development of a national implementation strategy if the intervention is found to be effective.

Production of policy-focused and Patient and Public Involvement (PPI)-focused outputs (such as blogs, videos, briefings and short reports) will be ongoing throughout the course of the funded project period (June 2022 to May 2025). The funder requires interim reports at 9 months and 18 months. Final reports, including journal submissions, are intended to be completed by the end of the funded project period (May 2025).

Processing:

Royal College of Psychiatrists (RCPsych) will transfer data from NCAP to NHS Digital. The data will consist of identifying details (specifically NHS Number, age, gender, and partial postcode) along with a unique person ID ('pseudonymous key') for the cohort to be linked with NHS Digital data.

NHS Digital will provide the relevant records from the HES APC, HES A&E, ECDS, MHSDS, and Civil Registration Deaths datasets to ONS. The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other record level data (NCAP data) already held by ONS.

RCPsych is also sending directly to ONS the same unique person ID with their pseudonymised NCAP data which the EXTEND study team will then use to link to the NHS Digital data via the unique person ID.

The ONS will store the NHS Digital data as part of its Secure Research Service (SRS), which only grants access to accredited and approved researchers. The ONS Information Asset Owner (IAO) will take overall responsibility for the Controller’s data after delivery to ONS. The ONS IAO will ensure all data are managed in accordance with Standard Disclosure Control (SDC), and all applicable Data Protection Legislation.

Researchers from the University of Oxford, Cardiff University and Imperial College London will have access to the pseudonymised linked dataset through the ONS SRS.

Once researchers and their research projects are accredited or approved, projects using the SRS have a project space created. Data sets requested for projects will be mapped to the project space. Researchers named on projects will then be provided with their account details and instructions on how to access the SRS. Access to the SRS is through a safe setting. Safe settings may be in safe rooms on ONS sites, in safe rooms on other certified sites, or through an organisation that has an Assured Organisational Connectivity Agreement with ONS and which maintains current certification.

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

Access is restricted to employees or agents of the University of Oxford, Imperial College London and Cardiff University who have authorisation from the University of Oxford Chief Investigator.

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

The NHS Digital data will be linked at person record level to the NCAP data obtained from RCPsych.

ONS will not be linking any of their datasets to the NHS Digital data (i.e. the NHS Digital data will be held in isolation on SRS but will be linked by the pseudo key to the NCAP data (all pseudonymised).

There will be no requirement and no attempt to reidentify individuals when using the data.

Researchers from the University of Oxford, Cardiff University, and Imperial College London will conduct statistical analysis to understand the existing variation in duration of EIP care, estimate the effect of increasing EIP duration from 3 to 5 years and estimate the cost-effectiveness of alternative models of EIP provision. All statistical outputs from this work will be checked by the ONS for disclosure and will take the form of aggregate statistics and modelling.


Active Monitoring for AtriaL Fibrillation - AMALFI trial — DARS-NIC-470203-Y2L7J

Type of data: information not disclosed for TRE projects

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

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

Purposes: Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-08-01 — 2025-07-31 2022.09 — 2024.02.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Critical Care
  5. Hospital Episode Statistics Outpatients
  6. Medicines dispensed in Primary Care (NHSBSA data)
  7. Civil Registrations of Death
  8. Hospital Episode Statistics Admitted Patient Care (HES APC)
  9. Hospital Episode Statistics Critical Care (HES Critical Care)
  10. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The University of Oxford requires linked healthcare data for consented participants in the Active Monitoring for AtriaL Fibrillation (AMALFI) study for baseline characterisation of participants and follow-up purposes. This includes centrally-collected data on primary care records, medications dispensed in the community, mortality, and Hospital Episode Statistics (HES) datasets.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide, and is estimated to affect over 1 million people in the UK. In AF, the atria (upper chambers of the heart) beat in an uncoordinated way, which disturbs the normal blood flow and can lead to the formation of blood clots inside the heart. These can travel through the bloodstream and create a blockage in the arteries supplying the brain, causing a stroke. Patients with AF are at a 5-fold increased risk of stroke, but this risk can be effectively reduced by up to two thirds with anticoagulation (blood-thinners). However, AF can occur only in short and infrequent episodes that make it hard to capture and start treatment, and it may also not cause any symptoms; as a result, some patients might have undetected AF until the time when they have a stroke.

A potential solution for this problem is to actively look for silent AF through screening in patients who are considered at risk. This is already routinely done in primary care when patients over the age of 65 years present for some other reason (for example for a routine appointment or a flu jab), in which their doctor might assess their pulse or do an electrocardiogram (ECG). However, this assessment is very short and is unlikely to detect short and infrequent AF episodes. New technology such as extended cardiac monitors and digital wearables offer the potential for increased and more frequent monitoring periods, and easier access to patients - but they are also more expensive and create additional workload for the healthcare system. At the moment, there is no conclusive evidence that screening for silent AF improves either clinical outcomes or patient quality-of-life, or if employing new AF screening strategies is a cost-effective strategy (and if so, how exactly it should be performed).

The AMALFI study is a randomised clinical trial of screening for subclinical (undiagnosed) AF in elderly patients with no previous AF, who are at increased risk of both AF and a subsequent stroke – this selection is based on a CHA2DS2VASc score of 3 or higher in men and 4 or higher in women (the CHA2DS2VASc score is a standard tool used by clinicians to assess stroke risk in patients with AF and help them decide who should receive anticoagulation). AMALFI is comparing a two-week remote continuous cardiac monitoring period with a ZioPatch to usual care alone: consenting participants will be assigned to one of the two groups by chance, in a similar way to tossing a coin, called “randomization”. The study has recruited 5,043 people through primary care practices in England. Recruitment started in 2019 and finished on February 28th 2022. The cohort is composed of 5,043 people, minus those that have withdrawn consent (6 thus far). This number of unconsented individuals may increase within the proposed duration of this Agreement, in which case, the University of Oxford will send NHS Digital an updated cohort. The main outcome of the study is the proportion of participants with newly-detected AF in both arms 2.5 years after randomisation (as shown in primary care records), with additional analyses planned in subgroups of age and sex, and at 5 years. The study may then continue collecting follow-up data for a period of up to 20 years after the initial 5 years. This long follow-up period was envisaged so that further data may be collected for longer-term outcomes (i.e. beyond 5 years), if a longer timeframe for assessment is considered important following the initial results.

If shown to be effective (and cost-effective), this approach to screening could form the basis for a potential future nationwide screening program, which could prevent stroke, disability, and premature death in this patient population. A second objective of the study is to develop streamlined procedures for running clinical trials in primary care, namely by comparing the outputs if using data collected directly from primary care practices or centrally-held data such as the datasets managed by NHS Digital.

AMALFI is sponsored by the University of Oxford and funded by the National Institute for Healthcare Research (NIHR) through the NIHR Oxford Biomedical Research Centre, with additional support from the NIHR Thames Valley and South Midlands Clinical Research Network (CRN) in the form of logistical support with recruitment only. The protocol and study procedures have been developed by a team of investigators spanning the Nuffield Department of Population Health (NDPH), the Radcliffe Department of Medicine, and the Nuffield Department of Primary Healthcare Sciences (all of which are departments of the University of Oxford) and is being run by the Clinical Trial Service Unit (CTSU) at NDPH.

Trial procedures are simple and remote, with no physical sites or dedicated staff apart from a small team at the CTSU, and no study visits. Eligible patients are being identified from primary care records in participating practices associated with the CRN. The practice runs a search of their records and generates a list of eligible patients, which is then uploaded to DocMail (a standard NHS mailing service). DocMail processes the mailing of the study documentation and, if interested, patients will return a completed questionnaire and consent form to the study team at CTSU – this includes their personal details such as name, address, date-of-birth, and NHS number. After this, participants are randomised and mailed a letter with or without a patch to self-administer (depending on the treatment allocation). Patients in the active/screening group are asked to wear their patch for 14 days and then return it using an enclosed box to iRhythm, the patch manufacturer, which analyses the data collected via the patch. iRhythm have not had and will not have any involvement in the design, conduct, analysis, or reporting of this study, nor will they have any access to NHS Digital data. A monitoring report is provided to the study team and the relevant findings shared with the patient’s GP, who manages subsequent treatment if needed. There are no study visits and follow-up data is only currently being collected from electronic record extractions at the individual practices taking part in the study. Information on quality-of-life will be collected through remote completion of mailed EQ5D (EuroQoL-5 Dimensions) questionnaires at two occasions (and for all participants at the same time): once the overall study recruitment has finished, and again approximately 2.5 years after that (i.e., coinciding with the timing of the primary outcome assessment). These questionnaires are a standard tool used in both research and clinical care settings within the NHS to assess several domains of quality-of-life (QoL; mobility, self-care, usual activities, pain/discomfort, anxiety/depression).

The University of Oxford will be the sole data controller who also process data for the study. The University of Oxford is the Data Controller as they determine the purposes for which and the manner in which the personal data disseminated under this Agreement are to be processed. The data will be stored and processed at the University of Oxford in secure servers and under strict access restrictions, and it will not be released to any other organisations or used for other purposes other than this study.

Altogether, the study requires the following datasets:
1. Medicines Dispensed in the Community (NHSBSA data)
2. Civil Registrations (mortality data)
3. HES Critical Care
4. HES Admitted Patient Care
5. Emergency Care Data Set
6. HES Outpatients

The study has also identified the need for General Practice (GP) Data, but at the current time, this data is not available. A national collection of primary care data would be a valuable resource for this study to draw upon for the research.

The data requested will be used to assess the study outcomes (namely the detection of AF) as well as other important events, such as the initiation of medication for AF, the need for additional appointments and tests, as well as hospital admissions and deaths. Altogether, these data will help the University of Oxford understand if AF screening can improve AF detection rates, what are the associated costs of doing so, and if there are particular safety signals of concern. It may also provide some initial indication of whether this procedure can improve clinical outcomes, although this is not the main purpose of the study. In particular, the NHSBSA data will be used to calculate the number of people starting anticoagulation in the active and control groups, which in turn will help the University of Oxford understand what are the likely benefits and risks of anticoagulation for subclinical AF in reducing strokes versus bleeding events.

AMALFI is collecting medications data via two routes: primary records extracted from each GP practice taking part in the study, and the centralised, nationwide NHSBSA dataset. Both sources will be used to assess rates of initiation of anticoagulation and other medications in the study cohort, and their impact on effectiveness (stroke, heart failure) and safety (bleeding) events resulting from new diagnoses of atrial fibrillation.

Given the novelty of the NHSBSA data, it is not yet known how well it overlaps with other pre-existent data sources (primary care records, in this case), and whether the NHSBSA dataset can be used on its own to retrieve medication exposure. If that was the case this would potentially improve clinical trial efficiency significantly via simplified data collection, both in AMALFI and beyond.

This work is to be undertaken in line with the NHSBSA Direction of assessing effectiveness and safety of medicines as the team is developing the methodological work required to guide future research using these data.

Finally, the conjunction of clinical events (detailed in the Civil Registrations, Medicines, HES Admitted Patient Care and HES Accident & Emergency datasets) with information on healthcare resource use (complemented by the HES Outpatients data) will provide a rich resource to assess the relative cost implications of screening from the perspective of the healthcare system, which will be crucial to inform future discussions on implementation. An additional aim of this work will be to undertake trial methodology research, specifically comparing the NHSBSA medicines data to medication data that is already being collected by the study from local GP practices. This exercise will focus on comparing the numbers of people identifying as taking particular drugs in each data source (rather than trying to audit the data collected in the NHSBSA dataset), and is hoped to help pave the way for broader use of the NSHBSA dataset for clinical trials.

Data minimisation will be pursued by only requesting datasets directly related to the outcomes of interest to the trial (clinical outcomes using primary care, admissions, and mortality data; medication initiation using primary care and dispensed medicines data; and health-care resource use using the remaining HES datasets), and requesting only the fields needed in each dataset; these have been reviewed by a clinician and a health-economist to ensure that only the necessary data is requested. Data is also only being requested for as far back as 5 years before the start of recruitment, i.e., from 2014/15 to latest available.

The objective of undertaking the AMALFI research study aiming to improve future patients’ health is the justification for processing under GDPR Article 6(1)(e) and Article 9(2)(j). In particular, AMALFI aims to provide high-grade evidence on the potential efficacy and cost-effectiveness of atrial fibrillation screening in the NHS, which it is hoped will inform future considerations regarding whether and how to roll-out a nationwide screening program, much like the existing programs for breast, cervical, and colorectal cancer. All participants in AMALFI have provided written informed consent to take part in the study, including specific consent for access to data held by NHS Digital to be provided to the University of Oxford for the purpose of this study. The study has received favourable Research Ethics Committee approval from the London - Bromley Research Ethics Committee (REC reference 19/LO/0220) and is registered in the International Standard Randomised Controlled Trials registry (reference ISRCTN15544176) and the NIHR portfolio; the Integrated Research Application System (IRAS) reference number is 234837.

Recruitment under each version of the consent:
Consent Form (v1.1) 06-FEB-19; (284 consented; in use May 2019 - August 2019) - this version only had HES/ONS wording.
Consent Form (v2.0) 15-AUG-19; (1000 consented; in use February 2020 - December 2020) - this version only had HES/ONS wording - edit not related to linkage.
Consent Form (v2.1) 27-APR-20; (2045 consented; in use February 2021 – July 2021) - this version only had HES/ONS - edit not related to linkage.
Consent Form (v3.0) 01-MAY-21; (812 consented; in use September 2021 - October 2021) - this version had GP/Medicines wording.
Consent Form (v3.1) 25-OCT-21; (902 consented; in use November 2021 - January 2022) - this version had GP/Medicines wording - edit not related to linkage.

The University of Oxford established the Clinical Trial Service Unit (CTSU), now within the Nuffield Department of Population Health, in the 1980s to conduct large trials such as the International Study of Infarct Survival (ISIS) trials. Since then CTSU has successfully completed a number of landmark studies including the 20,000 participant Heart Protection Study, the 9500 participant SHARP study, the 26,000 participant HPS-2/THRIVE study and the 30,000 participant HPS-3/REVEAL study. More recently, CTSU has coordinated the 40,000+ RECOVERY trial of treatments for COVID-19, which showed that dexamethasone, tocilizumab, and the REGN-COVID2 monoclonal antibodies were effective in reducing all-cause mortality in this population.

AMALFI is sponsored by the University of Oxford and is adopted onto the NIHR Portfolio as an academic study. iRhythm are the manufacturers of ZioPatch, the device which is being used in the study, and are providing it free of charge. iRhythm have not had and will not have any involvement in the design, conduct, analysis, or reporting of this study.

Although iRhythm could have an indirect commercial benefit if the study was to be positive (i.e., expanded use of the Zio Patch device in UK practice), this would only occur as a consequence of the study providing evidence of a benefit for public health (and pending a detailed assessment by policymakers such as the National Institute for Health and Care Excellence and others, whom would only recommend screening with the Zio Patch if any commercial benefit gained by iRhythm was outweighed by the benefits to health and social care). Moreover, the study will include cost-effectiveness analyses that will factor in not only the benefits but also any costs from the proposed intervention, producing important data for health economics analyses to be conducted in the future by policymakers, such as the National Institute for Health and Care Excellence.

Expected Benefits:

1. Provision of the data requested may help AMALFI provide important results that may affect standard clinical practice in the UK and beyond, by generating reliable evidence on the efficacy and cost-effectiveness of remote screening for subclinical AF using a self-applied patch. In particular, the datasets requested in this data dissemination are expected to form the basis for the assessment of the impacts of AF screening on anticoagulation rates, hospital admissions, outpatient appointments and A&E attendances, and deaths. While several monitoring devices are available, there is scarce randomised evidence of the added value of using such devices on top of usual care, particularly in a longer time frame (which may lead to AF cases being detected regardless of the use of the device, diluting its benefit and therefore cost-effectiveness). It is therefore expected that results from AMALFI might be incorporated in future National Institute for Health and Care Excellence (NICE), the Scottish Intercollegiate Guidelines Network (SIGN), and UK National Screening Committee guidelines; in particular, and depending on what the results of efficacy and cost-effectiveness show, AMALFI might provide the basis for a recommendation of targeted screening in elderly patients with additional comorbidities using a wearable patch in the UK, most likely in the primary care setting (and potentially managed via a central coordinating system replicating the methodology used in AMALFI). These results also have the potential to affect the care of millions of people worldwide, with potentially significant benefits in terms of reduction of fatal or disabling stroke and reduced healthcare costs (by means of reduced number of hospitalisations or A&E attendances) – the extent of which will be assessed by the detailed efficacy and cost-effectiveness analyses planned.

2. AMALFI is a streamlined and remote study with minimal data collection undertaken by participants, and none by their GPs. Participants are only asked to complete a short one-page questionnaire at enrolment (with remote EQ5D questionnaires planned at 2.5 and 5 years after inclusion), while GPs will perform a standard data extraction from their records at approximately 1, 2.5, and 5 years after randomisation. While these simple procedures make it easier for both participants and GPs to take part, they are limited in their capacity to provide detailed data that is of interest to the study (such as hospitalizations, secondary care appointments, mortality, and others). Therefore, access to data held by NHS Digital for participants in the AMALFI study will be crucial for detailed assessments of the impact of AF screening on a range of outcomes that would be hard to capture through more bespoke methods. Moreover, the provision of data on primary care records and medications as held by NHS Digital will allow the study team to potentially drop the need for GPs to run any data extractions for follow-up, further reducing the burden of taking part in research and making clinical trials more efficient, cost-effective, and attractive to busy clinicians. The comparative assessments of data collected directly from GPs or similar data held by NHS Digital may fuel the use of centrally held data by other researchers. The methods developed as part of this study may then be shared with the scientific community to improve the development of streamlined trials in cardiovascular disease and other fields.

3. The results should inform future discussions on the potential implementation of a nationwide screening program for subclinical atrial fibrillation and will be developed and disseminated to the wider public with the assistance of the Public Advisory Panel at the Nuffield Department of Population Health. If such a program were to be implemented based on these results, it could potentially involve several thousands of eligible patients in the UK each year, while paving the way for similar programs in other countries around the world.

4. Finally, the University of Oxford will aim to reach policymakers such as the National Institute for Health and Care Excellence (NICE), the Scottish Intercollegiate Guidelines Network (SIGN), and UK National Screening Committee (UKNSC). Although the University of Oxford does not expect an immediate policy change following the results of this study, the data produced may be used by both bodies to guide future recommendations for subclinical AF screening in UK practice. The University of Oxford will do this by registering as a stakeholder with these institutions and commenting on their AF management and screening guidance documents based on the findings.

Outputs:

The main results of AMALFI are expected in mid-late 2024, with long-term results in 2026. Further long-term results may be published if a longer timeframe for assessment is considered important following these results.

Dissemination of the results will be aimed at three different audiences: 1) clinical and research community; 2) patients and charities; and 3) policymakers.

The results will be disseminated widely within the clinical and research community, including presentation at relevant conferences (such as the European Society of Cardiology congress or the European Heart Rhythm Association congress) and publication in a high-impact medical journal such as Circulation, Journal of the American College of Cardiology, or European Heart Journal. Further academic papers (including results of cost-effectiveness analysis and papers about the trial methods) will be published in high impact, peer-reviewed journals (possible outlets include Trials, Clinical Trials, EuroPace, European Heart Journal Quality of Care and Clinical Outcomes) and on the trial website.

For patients and charities, a non-technical summary of the main study findings will be sent to participants and relevant charities, such as the British Heart Foundation and Arrhythmia Alliance (as well as NIHR who has funded the trial up to this stage) and published on the study website. Patient and Public Involvement will be sought in the design and sharing of outputs from the Public Advisory Panel at the Nuffield Department of Population Health (https://www.ndph.ox.ac.uk/research/participant-panel).

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

The medicines data is not deemed disclosive and information on a GP level is available in the public domain. However, should the study team consider that published information poses a risk of re-identification, the following suppression methodology should be applied:
· Zeros should be shown.
· 1-7 to be rounded to 5.
· Any other numbers rounded to nearest 5.
· Rounding unnecessary for averages etc.
· Percentages calculated from rounded values.
· If zeros need to be suppressed, round to 5.

Processing:

The flows of data:

1. The University of Oxford will provide NHS Digital with personal identifiers (sex, date-of-birth, and NHS number) plus a study ID for a cohort of consenting participants in the AMALFI study, via Secure Electronic File Transfer (SEFT). The University of Oxford will resend the cohort to NHS Digital before each data dissemination to ensure that any potential new withdrawals of consent are removed.

2. NHS Digital will link the cohort to the datasets requested and send the data back to University of Oxford via SEFT. The data will contain
- identifiable data of date-of-birth and NHS number.
- for the Civil Registration Deaths dataset, Cause of Death will also be flowed which is classed as identifiable as it is a free text field and so could potentially contain identifying information.
- requested data from the datasets.

University of Oxford are requesting that date-of-birth and NHS number (which is provided in step 1 above) are flowed back to University of Oxford for the purpose of linkage validation by the research team. The research team would like to ensure that the NHS Digital data is correctly linked given a specific cohort is being studied and many of the study outcomes will rely on the provision of correctly linked data.

The study ID is used to link the information received from NHS Digital to the cohort. However, this does not allow the University of Oxford to confirm that the data actually belongs to the correct person – therefore it is standard practice to cross-check identifiers provided by NHS Digital with those that the University of Oxford already hold to confirm correct linkage (note that NHS number and date of birth are already known to the University of Oxford, therefore NHS Digital will not be providing data that is not already held).

If a participant withdraws their consent to participation in the study (including for data linkage with NHS Digital), their wish will be recorded and they will not be included in the cohort sent to NHS Digital for linkage. The linkage cohort will be updated before each data dissemination to accommodate any potential new withdrawals of consent. Data from withdrawn participants is stored up until the point of withdrawal, with no further data collection taking place after that point.

The record-level identifiable data received from NHS Digital will be stored in a secure location within England and Wales and will only be accessed by individuals within the Clinical Trial Service Unit who have authorisation to access the data for the purpose(s) described, all of whom are substantive employees of the University of Oxford and have been appropriately trained in data protection and confidentiality. The raw data will be securely held at the CTSU within The University of Oxford in a restricted database (with access limited to a very small number of individuals), and it will not be shared outside the University of Oxford.

Data will be stored in an encrypted study database in a pseudonymised form, with identifiable fields such as NHS number or names encrypted in situ using state-of-the-art encryption methods (in line with the NHS Data Security and Protection toolkit). Access to this database is restricted to the study team and on a need to know basis, protected with username and password, and can only be accessed from internal networks. Information stored in the database can be accessed either via an internal desktop program (used to log information and contacts with participants), or directly within the database server. For the desktop program, only the study team individuals who have direct contact with participants can see identifiable fields. Within the database server, access to the identifiable fields is locked with a decryption key held by the two database managers, who are qualified programmers and substantial employees of the University of Oxford. The data will not be used by individuals outside the AMALFI study team and therefore there are no perceived risks of re-identification at this stage (outside the group of people who already have access to identifiable information as a consequence of their roles in managing the trial and contacting with participants).

Besides the data linkage described in this Agreement, AMALFI is also collecting electronic primary care records directly from participating GP practices via local data linkage; besides this, no other linkage is currently being pursued. The linked data received from NHS Digital will be stored separately from the primary care data collected via the participating GP practices until the data analysis stage (where it may be combined to produce the study outcomes). The data to be provided will not be matched to publicly available data.

The data collected via this Agreement will be used to determine the presence of atrial fibrillation diagnoses and associated symptoms (primary care and HES APC), quantify and characterise reasons for hospital admission (HES APC) and death (Civil Registrations), assess medication use (primary care and Dispensing data). In addition to this, the University of Oxford will further estimate healthcare resource use (hospital admissions, A&E attendances, outpatient appointments, need for diagnostic tests) for health economics analyses (using HES APC, HES critical care, Emergency Care Data Set, and HES outpatients).


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

Type of data: information not disclosed for TRE projects

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: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-17 — 2024-05-16 2022.02 — 2024.02.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Admitted Patient Care
  4. Civil Registrations of Death
  5. Hospital Episode Statistics Accident and Emergency (HES A and E)
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)

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.


MR1086 - The Oxford Vascular Study: incidence and outcome of stroke , transient ischaemic attack — DARS-NIC-148369-8PPWK

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Yes - patient objections upheld, Identifiable, Yes (Consent (Reasonable Expectation), Section 251 NHS Act 2006)

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(2)(c), Consent (Reasonable Expectation); Health and Social Care Act 2012 – s261(2)(c), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

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

When:DSA runs 2019-03-01 — 2020-10-02 2017.09 — 2024.02.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. Demographics
  4. MRIS - Scottish NHS / Registration
  5. MRIS - Flagging Current Status Report
  6. MRIS - List Cleaning Report
  7. MRIS - Members and Postings Report
  8. Civil Registration - Deaths
  9. Civil Registrations of Death

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).


Evaluating the age extension of the NHS Breast Screening Programme (AgeX Trial) (ODR_2014_367) — DARS-NIC-656752-G2L2P

Type of data: information not disclosed for TRE projects

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

Legal basis: Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(2)(d); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-07-01 — 2026-03-31 2024.01 — 2024.01.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS National Radiotherapy Dataset (RTDS)
  3. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

The University of Oxford requires National Disease Registration Service (NDRS) data for the purposes of the following research project: Evaluating the age extension of the NHS Breast Screening Programme (known as the AgeX Trial). This request was previously managed by Public Health England (PHE), prior to their dissolution in October 2021, under the reference ODR_2014_367.

The NHS Breast Screening Programme (NHSBSP) routinely invites women aged 50-70 years to come for a three-yearly screening. Because of uncertainty about the effects of screening outside this age range, an England-wide cluster-randomised trial is underway to assess the risks and benefits of additional invitations for screening at ages 47 to 49 and, separately, after age 71 (currently 71-73).

The following is a summary of the aims of the research project provided by the University of Oxford:
• Amass and analyse sufficient evidence that will enable the final reports to provide definitive unequivocal evidence on an issue that has been the subject of controversy for over 15 years – specifically whether the harms of breast screening outweigh the benefits.
• Assess the risks of screening (in particular, the chances of being diagnosed and treated for non-life-threatening cancer) and benefits (in particular, the chances of saving a life) for women undergoing additional screening at ages 47-49, and 71-73.

The findings will help the UK government decide whether to widen the age range for routine breast screening.

The University of Oxford requires continued access to the following NDRS data previously disseminated by PHE:
• NDRS Cancer Registration Data (01/01/1995-31/12/2018)

In addition, this request covers the dissemination of:
• NDRS Cancer Registration data (01/01/2019 – latest available).
• Systemic Anti-Cancer Therapy (SACT) dataset (01/04/2012- latest Available)
• Radiotherapy Data Set (RTDS) (01/04/2009-latest available)
Data will be disseminated annually until the end of this Data Sharing Agreement (DSA).

NDRS Cancer Registration Data provides the study with information on tumour characteristics of incident cancers (including histology, size, stage, grade, nodal involvement, and receptor profile); and treatment information. Additional information from the SACT dataset and the RTDS provide information on the subsequent treatment of incident cancers. These data can be used to better understand the health outcomes of women included in the trial.

The level of the data held and disseminated will be identifiable. Identifiable data is required to permit the linkage of the data being disseminated under this Agreement with the Civil Registration (Deaths), Demographics, Cancer Registrations and Hospital Episode Statistics (HES) Admitted Patient Care (APC) disseminated under DARS-NIC-147931-DT25Y; and NHS Screening records (previously provided by PHE, but now provided by NHS England). However, it should be noted that only pseudonymised data is processed for the purpose of analysis. All identifiers will be stored separately from the pseudonymised data used for analysis, with access restricted to the senior systems analyst. The identifiers need to be stored in the event any participant withdraws from the trial so the study team can identify and delete their data from further analysis

The data requested has been limited to the minimum amount necessary to achieve the purposes outlined within this DSA, and will be minimised as follows:
• The data will be limited to a cohort of ~4.5 million women that have been included in the AgeX trial in England. This includes all women aged 47-49 or 71-73 who have been randomised into or randomised out of receiving additional breast screenings.
• The request is limited to data between 01/01/1995-Latest Available, it is necessary to have data over such a long period because firstly, the screening programme currently offers women 7 screenings between the ages of 50 and 70 and the trial is investigating the effect of adding just one screen to the existing 7 routinely offered. Therefore, the screening period is already more than 20 years and the effects of screening are likely to become visible at least 10 years after the first screening. Secondly, it is essential for the trial design to have information on morbidity prior to randomization.

In addition, the AgeX trial team have undertaken extensive work with the NDRS Analysts to ensure compliance with the General Data Protection Regulation (GDPR) Principle of Data Minimisation.

The University of Oxford is the research sponsor and controller who determines the purpose and means of processing the requested data and is the organisation responsible for ensuring that the data will only be processed for the abovementioned purpose. Only the University of Oxford is permitted to process the data disseminated under this DSA.

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

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

The processing has been deemed to be in the public interest as the research has the potential to determine future policy on National Breast Screening.

The funding is provided by the Department for Health and Social Care, Cancer Research UK and the Medical Research Council. The funding is specifically for the study described. Funding is currently in place until April 2024 with applications in train for future funding. No funder will be given access to the data disseminated under this Agreement or plays a role in determining the purpose and means of processing nor have the ability to suppress or otherwise limit the publication of findings.

Members of the public who are representative of women in the trial have worked in collaboration with the AgeX investigators to ensure that the public voice is represented and included in decision making at all stages of the trial. These members of the public currently include two lay members of the Trial Management Group, and Women members of three public advisory groups: Oxford Biomedical Research Centre PPI Advisory Group; the Oxford Cancer Patient and Public Advisory Group; and Independent Cancer Patients’ Voice. The scope of involvement of the lay members of the Trial Management Group has included providing a public’s perspective on the ongoing progress and conduct of the trial including adherence to the protocol, the need for changes to the protocol, considering recommendations of the data monitoring and ethics committee, and publicly available lay information. The members of the three public advisory groups have provided further input to publicly available lay information. Other PPI activities include, but are not limited to, developing the participant facing information during randomisation, reviewing the content on the AgeX website which has recently been updated (https://www.ceu.ox.ac.uk/research/agex-trial), commenting on the lay summary for a recent grant application. When study results are available, they will be further consulted to provide input to draft manuscripts and grey literature reports, as well as the co-creation of press releases, lay summaries, infographics, and multimedia content such as podcasts and short videos to maximise opportunities for dissemination”.

The study has support under section 251 of the NHS Act 2006 to enable the common law duty of confidentiality to be temporarily lifted so that confidential patient information can be processed without consent, in line with the s251 approvals obtained by this study the national data opt-out applies.

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

Yielded Benefits:

The AgeX Trial is ongoing. The first analysis of the data will not be complete until 2027/28, therefore there are no yielded benefits to date.

Expected Benefits:

The aim of the trial is to assess reliably the risks and benefits of additional NHS invitations for breast screening before age 50 and, separately, after age 70. The results are expected to help determine future NHS policy on age at breast screening, as well as providing a greater understanding of costs and benefits to the NHS and its patients of extending the current breast screening age. The main results are not expected before the mid-2020s but interim results will be reviewed and the trial end date may be brought forward if the evidence is clear before then.

The UK Health Security Agency may use the findings to inform government and influence policy. This may affect breast screening policy in the UK, and influence policy in much of the rest of the world for decades after the results have been published.

While it is not certain whether the results of the study will lead to the extension of the national breast screening age, revisions to national policy based on scientific evidence have the potential to:
• Improve patient outcomes
• Lead to a more informed allocation of funds for screening services
Ultimately benefitting the provision of health and social care.

The benefits of interim analyses are that these will be used to monitor the protection and safety of trial participants in addition to feeding into the wider aims.

Outputs:

The AgeX trial is ongoing. Results on mortality until 2026 will be reported as soon as they become available (no earlier than 2027), but electronic follow-up could still continue, and longer follow-up will be reported as it becomes available. Results on process indicators will be reported in 2023-24.

These outputs, when available, will be communicated to relevant recipients through the following dissemination channels:
• Submission of academic papers to open-access, high-impact, peer-reviewed journals.
• Public reports developed in collaboration with NHS regulatory bodies to ensure the results are used to help provide evidence for health guidelines and best clinical practice.
• The AgeX Trial website at www.agex.co.uk will provide links to open-access peer-reviewed publications and offer free downloads of lay summaries of key and important findings.
• The Twitter handles at NDPH (@Oxford_NDPH) and Oxford Medical Sciences Division (@OxfordMedSci) with a combined following of over 11,000 will promote all significant findings.
• Presentation of research findings at conferences e.g. the UK Interdisciplinary Breast Cancer Symposium, a biennial conference for all those with an interest in the prevention, early treatment and diagnosis of breast cancer last held in 2022; and the European Breast Cancer Conference, an annual conference for all stakeholders in the breast cancer community

As with any trial, it is necessary to gather evidence incrementally throughout the course of the trial in order to check that the trial itself is not exposing participants to increased risk of harm or, conversely, to check for evidence of benefits. The outputs from the interim analyses will continue to be annual reports to the Data Ethics and Monitoring Committee which may also request additional analyses within the scope of the clinical trials objectives if they identify the need. The Data Ethics and Monitoring Committee must report any concerns about the trial or findings to the trial management group.

Outputs will include any data aggregated with small numbers suppressed in line with the appropriate suppression rules.

Processing:

To support future dissemination the University of Oxford will transfer data to NHS England. The data will consist of identifying details: NHS Number, Date of Birth and AgeX ID (StudyID).

NDRS Data Production will provide the relevant records from NDRS Cancer Registrations, NDRS RTDS and NDRS SACT to the University of Oxford. The data will contain directly identifying data items including NHS Number, Date of Birth and AgeX ID to support linkage with other datasets obtained by the study.

All data received from NHS England is added to the core AgeX database. The data will not be transferred to any other location.

The data will be held on servers exclusively at the Cancer Epidemiology Unit (CEU) within the Nuffield Department of Population Health (NDPH) at the University of Oxford and used solely for the purpose of this project.

Backup storage is in three separate secure rooms within NDPH buildings. Backups should be useable in the event of a disaster at the main site and will be accorded the same physical & electronic protections as live data.

The data will be accessed onsite at the premises of the University of Oxford. Data will also be accessed remotely using laptops provided by the University of Oxford using a secure VPN.

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

Access is restricted to individuals within the Cancer Epidemiology Unit in the Nuffield Department of Population Health at the University of Oxford, who have authorisation from the Principal Investigator. All such individuals are substantive employees of the University of Oxford and have received appropriate training in data protection and confidentiality.

The data will be linked as described above at an individual record level with the following datasets:
• Civil Registration (Deaths) – disseminated under DARS-NIC-147931-DT25Y
• Cancer Registration Data- disseminated under DARS-NIC-147931-DT25Y
• Demographics Data- disseminated under DARS-NIC-147931-DT25Y
• HES APC Data- disseminated under DARS-NIC-147931-DT25Y
• NHS Screening Data – previously disseminated by PHE

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use a pseudonymised subset of the data provided. When using the pseudonymised data there will be no requirement or attempt to reidentify individuals.


WAX: Weight Bearing in Ankle Fractures. A randomised clinical trial of weight-bearing following operatively treated ankle fracture. — DARS-NIC-504846-J6X8M

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, No (Consent (Reasonable Expectation))

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

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2022-10-20 — 2025-10-19 2023.06 — 2024.01.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Emergency Care Data Set (ECDS)
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Critical Care
  4. Hospital Episode Statistics Outpatients
  5. Hospital Episode Statistics Admitted Patient Care (HES APC)
  6. Hospital Episode Statistics Critical Care (HES Critical Care)
  7. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The University of Oxford requires access to NHS Digital data for the purpose of the following research project: WAX: Weight Bearing in Ankle Fractures. A randomised clinical trial of weight-bearing following operatively treated ankle fracture.

The study aims to determine whether functional outcomes after early weight-bearing in patients with operatively treated unstable ankle fractures are not worse than adopting a delayed weight-bearing regime which is usual care.

University of Oxford will analyse the dataset to:
1. Investigate the difference in risk of adverse events between the trial treatment groups in the first 12 months post-surgery.
2. Investigate the resource use, costs and comparative cost utility between the trial treatment groups in the first 12 months post- surgery.

This study is a randomised clinical trial, which is the best method to compare treatments to guide the care of patients. Randomisation will be used to produce two groups of patients: those given advice to walk on their operated ankle 2 weeks after surgery, and those who wait until 6 weeks. Patient follow-up will extend to 12 months.

It is funded by the National Institute for Health Research (NIHR) Research for Patient Benefit (RfPB) programme, reference number PB-PG-1217-20029. There will be a report submitted to the funder currently planned for the end of February 2023. The study cohort will go through a one-year follow up in January 2023. The data has been requested until 2025 to allow peer review of submitted manuscripts and/or responses to readers, as there may be a need for additional analyses.

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

The study requires processing of special category data and relies on Article 9(2)(j) as a lawful basis for processing data.

Data for this project has been minimised to ensure researchers only have access to the data they require to carry out the statistical and scientific processing of the data and to meet the purpose of the project for which there is a public interest.

NHS Research Ethics Approval has been granted for this study and all participants have prospectively consented to share their data in line with the processing described in this agreement.

The project is not part of a wider project, collaboration, or associated work.

The data subjects will be the trial participant cohort who fulfil all eligibility criteria as defined in the project Protocol. Every participant has provided prospective consent to access their personal data.

The cohort will include adults (18 years+) undergoing surgery for an ankle fracture. All participants will be treated non-weight-bearing until their two-week postoperative follow-up visit. They will then be instructed to either begin weight-bearing on the injured leg or remain non-weight-bearing for an additional 4 weeks. The decision on which instruction they are given will be made by chance using a process called randomisation so that neither patients nor surgeons can influence the choice. All other care will be as per usual treatment. Participants will report how well their ankle is healing and working, and their quality of life using questionnaires at intervals over the first year following surgery. Differences in healthcare costs will also be compared as another element of this research.

The University of Oxford recruited 562 participants over a 21-month period (between 13th January 2020 and 29th October 2021), from more than 20 hospitals. At least 436 participants were required in this study. This number was calculated based on previous scientific research to ensure that the study was large enough to reach a firm conclusion about its aims. The published results will inform NICE recommendations and will influence clinical practice.

The participant population for this study consisted of adult patients with an operatively treated ankle fracture:

Inclusion Criteria
• Age 18 years and above.
• The patient has undergone operative fixation for an unstable ankle fracture.
• Surgery was performed within 14 days of the injury.
• In the opinion of the treating surgeon, the participant might benefit from early weight-bearing.
• Able and willing to give informed consent.

Exclusion Criteria
The participant may not enter the study if ANY of the following apply:
• A lack of protective sensation (e.g. peripheral neuropathy).
• Inability to adhere to trial procedures.
• Bilateral operatively treated ankle fractures.
• Already in a trial for ankle fracture.
• Patient has received a hindfoot nail to treat index fracture.

There are around 170 ankle fractures each day in the UK. Many of these injuries heal with support in a plaster cast or splint, but some require surgery to restore the natural alignment of the bones and fix them in place with screws and plates. This improves how the ankle works once the fracture has healed.

Following surgery for an ankle fracture, patients are commonly told not to walk on the affected leg for six weeks in order to allow the bones to heal. Restricting the weight put through the affected leg may reduce the chance of surgical complications such as infection, breakage of the plates and screws, and loss of alignment requiring revision surgery. However, this restriction has been associated with problems such as blood clots, muscle weakness, stiffness, and poor recovery. It is unclear that the traditional six weeks period of limited walking is of any benefit. A recent national review found that surgeons gave patients very varied instructions following ankle fracture surgery, indicating that overall, UK surgeons have differing opinions about the best extended treatment pathway.

There has been little high-quality research in this area. The National Institute for Health and Care Excellence (NICE) and the James Lind Alliance (JLA) Priority Settings Partnerships have identified this question as one of their top priorities for research in trauma.

The objectives that are addressed through this data processing are:
1. Investigate the difference in risk of adverse events between the trial treatment groups in the first 12 months post-surgery.
2. Investigate the resource use, costs, and comparative cost utility between the trial treatment groups in the first 12 months post- surgery.

Emergency Care Data set (ECDS), Hospital Episode Statistics (HES) Admitted Patient Care and Outpatient datasets will be used.

Each of the requested datasets provide distinct data that are not available elsewhere and are required to adjust for between-participant variation and to determine outcomes necessary to answer the research questions described in the objectives.

Data will be required at the level of the participant in order to construct an adequately explanatory statistical model to address the research questions; all data will be de-identified prior to transfer to University of Oxford.

Only 4 years of data for each participant is required in order to fully describe important characteristics of the participants to determine between-participant variation. This includes the one-year follow-up data to determine any adverse events that required treatment and the associated costs.

Only consented trial participants in England will be included in the requested cohort. The team carried out a multicentre trial in order that the results are generalisable to NHS practice (for a better comparison) and therefore require data from participants across England.

In planning the study with patient representatives and gaining NHS Research Ethics approval, the team explored alternatives means to address these objectives and this approach was considered both proportionate and appropriate.

The research team is minimising data requested to only the trial participant cohort; data for each participant in the cohort will be requested for the period of time that they are involved in the trial follow-up.

University of Oxford is the sole data controller and processor for these data. No other third-party organisations are involved in this study. The study team plan, and have ethical approval to, archive the de-identified data required for the study for 3 years beyond the end of the study. It is usual to do this in this type of clinical trial so that if there are queries around the study, the interpretation or the statistical methods used can be answered fully and if necessary with reference to the original data.

Outputs:

At the conclusion of this study, it is hoped that the University of Oxford will have provided the most robust evidence available to infer whether patients who have had surgery for an ankle fracture should wait 6 weeks before walking on the operated leg or walk on their operated leg sooner following surgery. Patients and members of the public will help design a publicity strategy so that the results of the study are distributed outside of the routine scientific literature.

A report will be produced, which will inform the full update to the National Institute for Health and Care Excellence (NICE) Guidance NG38 (Fractures (non-complex): assessment and management) in 2024. Plain English outputs will include papers and web and blog media. A major international free-to-access publication is planned, alongside two national and two international presentations.

The University of Oxford have worked with members of the public who have personal experience of lower limb fractures and have knowledge of how weight-bearing advice can affect patients’ lives. A Patient and Public Involvement (PPI) member has access to the wider pool of experienced representatives who make up the Oxford Trauma and Emergency Care Patient and Public Involvement Group (the study's own PPI group). This group provides wider review of materials and provides input in reviewing plain language literature prior to dissemination, giving a broader forum for review, and providing efficient utilisation of the Patient and Public Involvement member. Using the INVOLVE guidance, the University of Oxford have given the members information on how they can be involved in the research and the type of support and training available to them.

Patients sit on the trial management and steering committees and have a key role in drafting trial documents for participants, attending conferences and assisting with the publication of the results. A Patient and Public Involvement member and a clinical expert led on the final drafting of the patient written intervention instructions.

For wider dissemination, the patient representatives will lead dissemination to the patients and carers directly through their extensive network of patient advocacy organisations which include the ARUK Centre for Epidemiology, Wales Centre for Primary and Emergency Care (Including Unscheduled) Care research (PRIME) and the Oxford Link and other local interface organisations.

They have already helped to generate a plain language summary for patients and the public. This document is available in paper copy, podcast and as a blog. An abstract will be submitted to the biannual NIHR INVOLVE Conference (https://www.invo.org.uk/current-work/) and a PPI member will give a presentation. Posters will also be prepared with the PPI team for inclusion at any workshop or conference where relevant PPI is being discussed.

In addition, to disseminate directly to study participants, findings will be more widely available locally through posters in appropriate outpatient rooms and liaising with identified service user groups.

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

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

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

Patients, patient advocacy groups, and members of the public:
Our patient representatives will lead dissemination to the patients and carers directly through their extensive network of patient advocacy organisations which include the ARUK Centre for Epidemiology, Wales Centre for Primary and Emergency Care (Including Unscheduled) Care Research (PRIME) and the Oxford Link and other local interface organisations.

They will help generate a plain language summary for patients and the public. This document will be available in paper copy, podcast and as a blog. An abstract will be submitted to the biannual INVOLVE Conference and a Patient and Public Involvement member will give a presentation. Posters will also be prepared with the PPI team for inclusion at any workshop or conference where relevant PPI is being discussed. In addition, to disseminate directly to study participants, findings will be more widely available locally through posters in appropriate outpatient rooms and liaising with identified service user groups.

Health care providers:
The trial team will work with the Oxford NIHR Biomedical Research Centre (BRC) and Collaborations for Leadership in Applied Health Research and Care (CLARHC) media teams to maximise the reach of the press and publicity outputs from this study. The team has costed the application to include one free-to-access publication in the mainstream literature. The final results will be submitted for presentations at annual meetings of the British Orthopaedic Association (BOA) and the Orthopaedic Trauma Society (OTS). The findings will be presented to the entire NHS via the NHS national electronic Library for Health (NHS Evidence). International ‘reach’ of the published research findings will be supplemented by presentations at high visibility meetings such as the Orthopaedic Trauma Association (OTA) Annual Meeting (US) and European Federation of National Associations of Orthopaedics and Traumatology (EFORT) Annual Congress (Europe).

In addition, the team is developing complementary systems incorporating non-traditional media. The Chief Investigator has been developing an enhanced web presence through blogging on the leading UK trauma and orthopaedic websites. These blogs engage both trauma and research communities. They have been very successful and have provided a means for rapid dissemination. The team plans to expand this activity into additional subject-specific and general blogs such as the British Medical Journal (BMJ).

National guidelines:
The research team will use their established network involvement to disseminate these research findings. These include the NIHR Clinical Research Network, and specialist interest groups (British Orthopaedic Association, Orthopaedic Trauma Society, Orthopaedic Trauma Association and The European Federation of National Associations of Orthopaedics and Traumatology).

The team will alert the relevant NICE standing committee to the results of the trial by notifying their surveillance team.

The study team is due to report in March 2023 and inform the full update to NICE Guidance NG38 in 2024. Progress in the work has been successful despite COVID and they are confident of hitting this timeline. De-identified data will be stored securely for a period of 3 years by University of Oxford following the final report to respond to any queries regarding the study.

Processing:

A file of unique identifiers and patient-level identifiers (NHS number, date of birth, sex, and postcode) will be sent from the University of Oxford to NHS Digital. The cohort includes 562 participants.

NHS Digital will link HES data for each patient identified in the cohort using the matching data file (containing NHS number, date of birth, gender, and postcode) to the unique identifier. The HES data will be at patient level and de-identified. NHS Digital will destroy the linkage file once linkage is achieved. The de-identified HES data, which will include special category health data, with the linked ID will be sent to the University of Oxford.

There will be no subsequent flows of data.

The processing organisation is University of Oxford. Two processing/storage sites will be used: Botnar Research Centre and Nuffield Department of Primary Care Health Sciences.

The trial team will initially prepare the linkage file as described above. On receipt of the linked, de-identified data from NHS Digital the trial team will carry out a prospective economic evaluation, conducted from an NHS and personal social services perspective, using the data provided by NHS Digital, augmented with participants’ self-reports. The economic evaluation will estimate the difference in the cost of resource inputs used by participants in the two arms of the trial, allowing comparisons to be made between the two weight-bearing strategies following ankle fracture fixation and enabling costs and consequences to be compared. Resource utilisation will be captured through the data provided by NHS Digital. The costs of the treatment options, including supplementary interventions (e.g., revision surgery) and rehabilitation inputs will be estimated using NHS reference costs and standardised to current prices. Health-related quality of life will be collected from participants’ self-report at randomisation, and at 6 weeks, 4- and 12-months post- randomisation using the EuroQol EQ-5D-5L measure; responses will be used to generate quality adjusted life-years (QALYs). The economic evaluation will be framed as a cost-utility analysis with results expressed in terms of incremental cost per QALY gained. The team will use non-parametric bootstrap estimation to derive 95% Confidence Intervals (CIs) for mean cost differences between the trial groups and to calculate 95% CIs for incremental cost- effectiveness ratios. The magnitude and significance of the coefficients on the interactions between the covariates and the intervention variable will provide estimates of the cost-effectiveness of the treatment options by participant subgroup.

The data will not be linked to any other data and only the linkages described are permitted under this Agreement.

Routine statistical procedures to suppress small cell numbers (less than 5) will be used to reduce the risk of re-identification. No attempt will be made in the processing to re-identify individuals.

Data processing will only be carried out by substantive employees of the University of Oxford who have been appropriately trained in data protection and confidentiality.

Data will only be accessible to these employees in a designated, locked, secure data processing office with standalone computers in accordance with the data security policies of the University of Oxford, Big Health Data Group (NDORMS), and Nuffield Department of Primary Care Health Sciences.


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

Type of data: information not disclosed for TRE projects

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: No (Academic)

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

When:DSA runs 2019-12-18 — 2022-12-17 2018.10 — 2024.01.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. MRIS - Flagging Current Status Report
  5. MRIS - Scottish NHS / Registration
  6. Civil Registration - Deaths
  7. Demographics
  8. Cancer Registration Data
  9. Hospital Episode Statistics Admitted Patient Care
  10. Hospital Episode Statistics Admitted Patient Care (HES APC)
  11. Civil Registrations of Death

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.


Tumours of the Central Nervous System: Incidence, Survival and Variation in Treatments (ODR1819_255) — DARS-NIC-656841-D0P8Y

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-08-07 — 2024-08-06 2023.08 — 2023.10.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer registration (pre-1995)
  2. NDRS Cancer Registrations
  3. NDRS Linked Cancer Waiting Times (Treatments only)
  4. NDRS Linked HES AE
  5. NDRS Linked HES APC
  6. NDRS Linked HES Outpatient
  7. NDRS National Radiotherapy Dataset (RTDS)
  8. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

The University of Oxford requires access to NHS England National Disease Registration Service (NDRS) data for the following research project: Tumours of the Central Nervous System: Incidence, Survival and Variation in Treatments (ODR1819_255).

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

1. Characterise the incidence of developing various types of primary Central Nervous System (CNS) tumours since 1971
2. Characterise survival following a primary CNS tumour diagnosis
3. Characterise the medical histories leading to a primary CNS tumour diagnosis

The study will further:

1. Characterise the causes of death attributed to patients dying after a diagnosis of a primary CNS tumour and the factors associated with this risk.
2. Characterise the risk of experiencing a further CNS tumour-related event among patients who have been diagnosed with a primary CNS tumour and the factors associated with this risk.
3. Characterise the risk of subsequent events that may be treatment-related.

The following NHS England National Disease Registration Service (NDRS) National Cancer Registration and Analysis Service (NCRAS) data have already been accessed in support of this study :
- NDRS Cancer registration– necessary to estimate CNS tumour incidence, mortality and survival rates
- NDRS Hospital Episode Statistics Admitted Patient Care (HES APC) – necessary to provide information on hospital admissions that may be related to the CNS tumour diagnosis and to describe hospital resource use
- NDRS Hospital Episode Statistics Outpatients (HES OP) - necessary to provide information on outpatient visits following a CNS tumour diagnosis and to describe hospital resource use
- NDRS Hospital Episode Statistics Accident & Emergency (HES A&E) - necessary to provide information on emergency admissions before and following a CNS tumour diagnosis
- NDRS Systemic Cancer Dataset (SACT) - necessary to provide information on chemotherapy treatments received by CNS tumour patients to describe usage and trends over time
- NDRS Radiotherapy Dataset (RTDS) - necessary to provide information on radiotherapy treatments received by CNS tumour patients to describe usage and trends over time
- NDRS Cancer Wait Times (CWT) – necessary to investigate relationships between wait times and CNS tumour diagnoses and their outcomes
Data was released for all individuals who had been diagnosed with a primary CNS tumour between 01/01/1971 to 31/12/2017.

The University of Oxford now wishes to request a refresh of the above-listed datasets for individuals diagnosed with a primary CNS tumour between 01/01/2018 to 31/12/2020.

All data already held, and data being requested is Pseudonymised

The data already held has been minimised as follows:
• Limited to data for a study cohort identified by the NDRS that includes all individuals diagnosed with a primary CNS tumour (defined by specific ICD codes)
• Limited to data for England
• Limited to data between 1st January 1971 and 31st December 2017

The data requested will be minimised as follows:
• Limited to data for a study cohort identified by the NDRS that includes all individuals diagnosed with a primary CNS tumour (defined by specific ICD codes)
• Limited to data for England
• Limited to data between 1st January 2018 and 31st December 2020

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

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

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

The Nuffield Department of Population Health, University of Oxford funds the project.

Data will be accessed by:
A PhD student affiliated with the University of Oxford, who is undertaking this project in support of the completion of their PhD. The individual has completed mandatory data protection and confidentiality training and is subject to the University of Oxford’s policies on data protection and confidentiality. The individual accessing the data will do so under the supervision of a substantive employee of the University of Oxford. The University of Oxford would be responsible and liable for any work carried out by the individual. The PhD student would only work on the data for the purposes described in this Agreement.

The project team have consulted individuals affected by a CNS tumour (patients and carers) via online support groups regarding the collection and analyses of the data for the purposes described above. This was achieved through individual discussions to identify aspects of research that are of relevance and importance to patients.

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

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

Yielded Benefits:

· The manuscript cited in the outputs has proven useful in providing the clinical community with detailed insights into the apparent long-term increase in incidence of CNS tumours in the English population. In particular it has yielded a potential explanation for the observed increases in incidence of non-malignant CNS tumours by identifying important differences in the methods of diagnosis. · An extension of the work published in the aforementioned manuscript was presented to attendees of the largest annual national meningioma (the most common non-malignant CNS tumour) meeting. This (not yet published) research identified important geographic (regional) variation in national diagnoses of meningiomas and yielded important discussions and new collaborations in order to develop this work further and guide future clinical management. · The data for this study were originally provided to us via Public Health England prior to NHS England becoming the data controller. Accessing these data has proven useful in allowing the principal investigator to spend extended periods of time thoroughly examining the quality of the national CNS tumour data and identifying areas of improvement which are necessary to conduct high quality and clinically relevant research into these tumours. As a result of this, the principal investigator, alongside two collaborators with experience in epidemiological research pertaining to CNS tumours, have established the Brain Tumour Data Improvement Initiative in early 2023. The goal of this initiative is to engage stakeholders at a national level including data stewards, data users, patients, clinicians, advocacy groups, funders, and charitable organisations in improving the completeness and quality of data on CNS tumours in cancer registries across the four nations. Initial meetings have already taken place and the initiative has attracted attention and support from the CNS tumour patient community, the director of a leading brain tumour charity, the chair of the NCRI Brain Tumour Group, as well as members of the CNS tumour clinical and research community nationally.

Expected Benefits:

The findings of this research study are expected to contribute to evidence-based decision-making for national guidelines on CNS tumours, local decision-makers such as neurosurgeons and neuro-oncologists, and patients to inform best practices to improve the care, treatment and experience of health care users relevant to the subject matter of the study.

The use of the data could:
• Help the NHS to better understand the health and care needs of the CNS tumour population
• Lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience of CNS tumour patients
• Advance understanding of regional and national trends in health and social care needs for CNS tumour patients
• Advance understanding of the need for, or effectiveness of, preventative health and care measures for the CNS tumour patient population.

The study team has regular contact with all the major UK brain tumour charities (Brainstrust, Brain Tumour Research, The Brain Tumour Charity, and Brain Tumour Support) and will optimise the potential public benefits from the use of the data by disseminating findings (in layperson language) to the tens of thousands of CNS tumour patients and their carers that are part of these groups.

The principal investigator of the study is also a member of the National Cancer Research Institute (NCRI) Brain Group which supports, oversees and facilitates collaborative research on brain and CNS tumours nationally, so the findings can reach a larger audience.

Outputs:

The processing carried out thus far has produced the following outputs:
• Seminar at the Cancer Epidemiology Unit Seminar Series - Nuffield Department of Population Health (completed December 2019)
• Presentation at the Nuffield Department of Population Health Annual Symposium (completed January 2020)
• Presentation at the Yorkshire Brain Tumour Symposium (completed July 2022)
• Presentation at the British-Irish Meningioma Symposium Annual Symposium (completed October 2022)
• Presentation at the Yorkshire Brain Tumour Symposium (completed July 2022)
• Presentation at the British-Irish Meningioma Symposium Annual Symposium (completed October 2022)
• Presentation at Cancer Research UK Oxford Centre 2023 Annual Symposium (completed March 2023)

The expected outputs of the continued processing will be:
• Submission to peer-reviewed journals on an ongoing basis
• Presentation at the Nuffield Department of Population Health Annual Symposium (expected June 2023)
• Presentation at the British Neuro-Oncology Society Annual Conference (expected July 2023)
• Nuffield Department of Population Health DPhil Students’ Symposium (expected July/August 2023)
• Presentation at the British-Irish Meningioma Symposium Annual Symposium (expected September 2023)
• Submission of PhD thesis (expected January 2024)

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

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Social media
• Posters displayed at conferences and symposia
• Press/media engagement
• Public promotion of the research – shared with major UK brain tumour charities such as Brainstrust, Brain Tumour Research, The Brain Tumour Charity, Brain Tumour Support

Outputs will be produced throughout 2023-2024 as described above.

The study has submitted abstracts to conferences and presented some of the results of our analyses at national conferences as well as seminars within the University of Oxford:

• Seminar at the Cancer Epidemiology Unit Seminar Series - Nuffield Department of Population Health (December 2019)
• Presentation at the Nuffield Department of Population Health Annual Symposium (January 2020)
• Presentation at the Yorkshire Brain Tumour Symposium (July 2022)
• Presentation at the British-Irish Meningioma Symposium Annual Symposium (October 2022)
• Presentation at Cancer Research UK Oxford Centre Annual Symposium (March 2023)

The study has had a manuscript on trends in CNS tumour incidence accepted in January 2023 by the leading scientific journal in the field of neuro-oncology, which is called Neuro-Oncology. https://doi.org/10.1093/neuonc/noad001

Processing:

No data will flow to NHS England for the purposes of this Agreement.

NHS England will provide the relevant records from the following datasets to the University of Oxford:

NDRS Cancer Registration
NDRS Hospital Episode Statistics Admitted Patient Care (HES APC)
NDRS Hospital Episode Statistics Outpatients (HES OP)
NDRS Hospital Episode Statistics Accident & Emergency (HES A&E)
NDRS Systemic Cancer Dataset (SACT)
NDRS National Radiotherapy Dataset (RTDS)
NDRS Cancer Waiting Times (CWT).

Data will contain no direct identifying data items. The data will be pseudonymised and individuals cannot be reidentified through linkage under data in the possession of the recipient.

The data will not be transferred to any other location.

Pseudonymised data will be securely stored within the Nuffield Department of Population Health (NDPH) file store and will remain there until the end of the study.

The University of Oxford (Nuffield Department of Population Health) uses on-campus backup services.

The data will be accessed by authorised personnel onsite at the University of Oxford, and also on some occasions where necessary, via remote access (VPN). Where information is being accessed via VPN individuals are prohibited from downloading or copying data onto local devices.

The data will remain on the servers at the University of Oxford at all times.

The data will only be accessed within England.

Data will be accessed by a PhD student at the University of Oxford. The individual will act as an agent of the University of Oxford and will be operating under the supervision of substantive employees of the University of Oxford.

The data will be linked at the person record level with the dataset(s) already obtained from the National Disease and Registration Service, via a pseudonymised study (patient) ID.

Data will be analysed and processed by a PhD student of the University of Oxford for the purposes described above, and in support of the completion of their PhD.


Hodgkin and Non-Hodgkin Lymphoma:Using routine data to identify recurrence, and variation in the use of radiotherapy ( ODR1920_011 ) — DARS-NIC-656849-P9M6C

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-05-23 — 2026-05-22 2023.10 — 2023.10.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

University of Oxford requires access to NHS England data for the purpose of the following research project: Hodgkin and Non-Hodgkin Lymphoma: Using routine data to identify recurrence, and variation in the use of radiotherapy.

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

Lymphoma is a form of cancer which is very sensitive to treatment, both with chemotherapy and radiotherapy. Significant variation in the use of radiotherapy was identified in a report in 2015, which may be more related to geographical and organisational factors rather than patient or disease factors.

This project has two main aims:
• undertake analysis of radiotherapy usage in England, to understand the causes and clinical impact of any variation on patient outcomes,
• use the routine datasets available within NHS England to further understand subsequent relapse and recurrence of lymphoma. Factors predicting recurrence will be identified and used to develop a model to help predict those patients who may experience recurrence of their lymphoma following standard treatment.
The final aspect of analysis will be to look at what long-term side-effects survivors of lymphoma develop. In particular to analyse the incidence of heart disease, stroke and subsequent cancers.

The data accessed from NHS England will form the foundation of improving understanding into the use of radiotherapy, recurrence rates of lymphoma, and late-toxicity in an English population. Having access to population-based data spanning decades will allow the identification of trends which may not otherwise be seen. The large cohort size of the NHS England data will allow statistical analysis to identify any significant predictors of recurrence, or factors associated with variations in radiotherapy usage in the UK.

The following NHS England data will be accessed:
• Hospital Episode Statistics
- Accident & Emergency (HESAE)
- Inpatient (HESAPC)
- Outpatients (HESOP)
• Cancer Registry
• Diagnostic Imaging Dataset (DIDS)
• Systemic Anti-Cancer Therapy Dataset (SACT)
• National Cancer Waiting Times Dataset (CWT
• Radiotherapy Dataset (RTDS)

The quantum of Data requested is necessary to determine treatment patterns, patterns of presentation, co-morbidities, initial treatment, recurrence, and investigation. The Cancer Registry data is necessary to provide a cohort of unique individuals, to allow analyses by age, sex, ethnicity, and vital status and to allow ascertainment of the index diagnosis including multiple prognostic factors and help determine the treatments used.


The level of the data will be pseudonymised and will be minimised as follows:
• Limited to data indexing between 01st January 1997 to 31st December 2020 ;
• Limited to approximately 264,443 records
• Limited to the following geographic areas: England
• Limited to conditions relevant to the study identified by specific ICD or OPCS codes which cover;

Hodgkin Lymphoma, Follicular and non Follicure Lymphoma Mature T/NK-cell lymphomas, Other specified and unspecified types of non-Hodgkin lymphoma, Other specified types of T/NK-cell lymphoma, Malignant immunoproliferative diseases, Hodgkin’s disease, Lymphosarcoma and reticulosarcoma and other specified malignant tumours of lymphatic tissue. morphology codes.

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

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

The University of Oxford rely on Article 9(2)(j) - processing is necessary for archiving purposes in public interest, scientific or historical research purposes. The legitimate need for processing special category data under 9(2)(j) as: "necessary for scientific research purposes to increase medial knowledge for the benefit of all and to improve public health".

The funding is provided by a grant from Cancer Research UK. The funding is specifically for the study described. Funding is in place for 12 months. Funding to continue the work described will be sought on an ongoing basis via an annual grant cycle.

University of Oxford is the sole data controller and sole data processor.

There are no other organisation(s) involved or accessing the NHS England data, including organisations acting in an advisory capacity or as part of an oversight or steering committee.

The design of the proposed use of the data has been discussed with and supported by a Project Advisory Group comprised of 4 individuals previously treated for lymphoma, contacted via the Oxford Blood Group patient involvement group ( https://oxfordbrc.nihr.ac.uk/ppi/oxford-blood-group).

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

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

Yielded Benefits:

Data for this study has previously been shared when the data were controlled and managed by Public Health England (PHE). As such there are some yielded benefits to be observed from the access to the data for the study prior to NHS England becoming data controller. It should be noted, as the study is, by definition, focused on the long-term outcomes of cancer treatments it is not possible to directly assess the benefits of the research as these would not become measurable for many years following any influence on clinical practice. However, some of examples of this study’s research (the late effects of cancer treatments) have been cited and referenced in clinical guidelines and policy documents nationally and internationally over the past 5. The inclusion of research in multiple clinical guidelines and policy documents, for example recent research on the same themes (long term effects of cancer treatments) from the study has been cited in: • 2022 ESC Guidelines on Cardio-Oncology (10.1093/eurheartj/ehac244) • 2022 Update to NCCN Guidelines: Hodgkin Lymphoma, Version 2.2023 • 2022 ACC/AHA/HFSA Guideline for the Management of Heart Failure (10.1016/j.cardfail.2022.02.010) • 2022Position paper of the Heart Failure Working Group of the Austrian Society of Cardiology • 2022 Radiation Therapy Across Pediatric Hodgkin Lymphoma Research Group Protocols: A Report From the Staging, Evaluation, and Response Criteria Harmonization (SEARCH) for Childhood, Adolescent, and Young Adult Hodgkin Lymphoma (CAYAHL) Group (10.1016/j.ijrobp.2021.07.1716) • 2021 Stratification and management of cardiovascular risk in cancer patients. A consensus document of the SEC, FEC, SEOM, SEOR, SEHH, SEMG, AEEMT, AEEC, and AECC (10.1016/j.rec.2020.11.020) • 2021 Cardiovascular Manifestations From Therapeutic Radiation: A Multidisciplinary Expert Consensus Statement From the International Cardio-Oncology Society (10.1016/j.jaccao.2021.06.003) • 2021 Coronary artery disease surveillance among childhood, adolescent and young adult cancer survivors: A systematic review and recommendations from the International Late Effects of Childhood Cancer Guideline Harmonization Group (10.1016/j.ejca.2021.06.021) • 2020 Fondazione Italiana Linfomi (FIL) expert consensus on the use of intensity-modulated and image-guided radiotherapy for Hodgkin’s lymphoma involving the mediastinum (10.1186/s13014-020-01504-8) • 2020 Onco-Cardiology: Consensus Paper of the German Cardiac Society, the German Society for Pediatric Cardiology and Congenital Heart Defects and the German Society for Hematology and Medical Oncology (10.1007/s00392-020-01636-7) • 2020 Guidelines for Long-Term Follow-Up after Childhood Cancer: Practical Implications for the Daily Work (10.1159/000504200) • 2020 Long-Term Follow-Up Guidelines and Organization of Long-Term Follow-Up Care for Childhood and Young Adult Cancer Survivors (10.1007/978-3-030-49140-6_44) • 2019 Evidence-based recommendations for the organization of long-term follow-up care for childhood and adolescent cancer survivors: a report from the PanCareSurFup Guidelines Working Group (10.1007/s11764-019-00795-5) • 2019 Cardio-Oncology Rehabilitation to Manage Cardiovascular Outcomes in Cancer Patients and Survivors: A Scientific Statement From the American Heart Association (10.1161/CIR.0000000000000679) • 2018 Proton therapy for adults with mediastinal lymphomas: the International Lymphoma Radiation Oncology Group guidelines (10.1182/blood-2018-03-837633) • 2018 Bone sarcomas: ESMO–PaedCan–EURACAN Clinical Practice Guidelines for diagnosis, treatment and follow-up (10.1093/annonc/mdy310) • 2018 Proton therapy for pediatric malignancies: Fact, figures and costs. A joint consensus statement from the pediatric subcommittee of PTCOG, PROS and EPTN (10.1016/j.radonc.2018.05.020) Additionally, examples cited include how the data is being used in the development of clinical studies with examples included below. • Citation in: 2019 The Evolving Design of NIH-Funded Cardio-Oncology Studies to Address Cancer Treatment-Related Cardiovascular Toxicity (10.1016/j.jaccao.2019.08.007) • Use of data to inform the development of the PROSPERITY trial (‘A randomised multi-centre phase II study of protons versus photons to deliver intensity modulated radiotherapy with deep inspiration breath hold for the treatment of mediastinal lymphoma’) • Use of data to inform the development of a study of lung cancer screening in Hodgkin lymphoma survivors (led by Dr Kim Linton, Christie Hospital, Manchester) • Use of data to inform the development and analysis and interpretation of a study of Response Adapted incorporation of Tislelizumab into the Front-line treatment of older patients with Hodgkin lymphoma (RATIFTY) – Funded will open soon These activities were sufficient over the past 5 years for the study team to obtain an extension of CRUK’s programme grant for a further 5 years (from April 2022) to continue research and yield further such benefits.

Expected Benefits:

The study’s CRUK programme grant (‘Benefits and Risks of Cancer Treatment’) utilises data from a variety of different sources (also including clinical trials, large cohort studies and radiation dosimetry studies) to provide relevant information to clinicians and patients and allow optimal treatment decisions to be made. The data provided to The University of Oxford by NHS England is another important source of data that contributes towards the overall project aims. It is therefore in the public interest for this data to be released, processed and the results disseminated.

Specifically, the data provided by NHS England will allow:
• Analysis of variation in radiotherapy use across the country and the possible reasons behind this variation.
• Assessment of the long-term risks (e.g. cause-specific mortality and second cancer incidence) following lymphoma diagnosis and treatment.
• Development of an algorithm to detect lymphoma recurrence in routinely collected data to give population-based indications of how recurrence risk has varied by treatment strategies.
The results of this work will contribute towards an improved understanding of the optimal management of different sub-types of lymphoma to further improve the observed outcomes.

Approximately 16,500 people are diagnosed with lymphoma in the UK each year, making it the 6th most common cancer type overall (after breast, prostate, lung, bowel and melanoma skin cancer). Improvements in the management of, and the long-term outcomes after, lymphoma therefore stand to make a substantial benefit to public health.

The study teams record of delivering planned outputs in this area is evidenced by the publication and citation record originating from the programme. In addition the study contributes through informing national (and international) clinical guidelines and the development of clinical trials.

This study is not in direct support of an individual PhD project, but this study has already formed part of a successful PhD thesis (the original data applicant, Dr Rebecca Shakir) and it is planned that these data will be used as part of a further PhD project over the next 4 years.

Outputs:

The expected outputs of the processing will be:
• Abstracts and presentations at national and international conferences
• Submissions to peer reviewed journals anticipating 1 publication per year over the next 3 years.
• Provision of results to other researchers to help in the development of their research studies and in clinical trials
• Results will also be shared directly with people affected by lymphoma at Lymphoma Action’s National Conference and their Lymphoma Matters publication.
• Planned that these data will be used as part of a further PhD project over the next 4 years.

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

The results of analyses of lymphoma outcomes and late effects will be presented using standard epidemiology measures such as Overall Survival (OS), cause-specific mortality (CSM), standardized mortality ratios (SMR), standardized incidence ratios (SIR), absolute excess risk (AER) and cumulative incidences and mortality. These analyses will be completed, presented and published as a number of smaller projects over the next 4+ years, coinciding with the study’s current programme grant funding cycle from CRUK.

Methods to infer recurrence of lymphoma from routinely collected data will be developed over the next 4+ years as part of a Clinical Research Fellow post funded within our CRUK programme. It is hoped that this work will form a component of a PhD thesis and will also be presented and published separately.

The study research group has a strong record of achieving previous research goals, have an excellent publication record and have maintained continuous programmatic funding from CRUK for >10 years. The study team envisage continuing research using these data into the future, requesting renewals and data up-dates every 2-3 years.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Journals
• Public events such as conferences
• Publication and citation record originating from the programme
• Contribution through informing national (and international) clinical guidelines
• Contribution through the development of clinical trials
The results of analyses of radiotherapy usage will be presented using the proportion of cases receiving radiotherapy and assessing variation by factors including geography, travel time from nearest radiotherapy centre and multiple deprivation index. This analysis will be completed and presented within the next year and subsequently prepared for appropriate publication.

Processing:

No data will flow to NHS England for the purposes of this Agreement.
NHS England will provide the relevant records from the HES A&E, HES IP, HES OP, CANCER Registry, DIDS, SACT, CWT and RTDS datasets to University of Oxford.

The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other older record level data already held by the recipient within the scope of this study and Data Sharing Agreement. Data will not be linked to other datasets out of scope of this agreement.

The data will not be transferred to any other location.

Within Nuffield Department of Population Health (NDPH) department in Oxford University, electronic data files are kept on password-protected network servers behind a local firewall. Servers are kept in a locked room with access restricted to IT staff.
Access to data is restricted via user identification. No data are moved or copied from these servers. The primary data received from NHS England are also stored on the secure NDPH network behind a firewall. The IT department have setup a special permissions compliant folder to receive and hold data securely. The PI of the group controls who can access this folder and the list is reviewed every 6 months. Data are not copied but can be accessed by analysis programs. Receipt of data is recorded in The University of Oxford asset register. When data are to be deleted a request is made to the IT department who provide a deletion certificate which the study team enter into the asset register (any backups resulting from the 28-day back-up cycle are also deleted).

Backups are held for 6 months on internal servers spread over three locations within the Old Road Campus, at The University of Oxford. Backed up data is encrypted both in transit and at rest. After 6 months, any expired data is deleted from the server. Access to data is restricted via user identification. No data are moved or copied from these servers.

The data will be accessed by authorised personnel via remote access. The data will remain on the servers at University of Oxford at all times. Personnel are prohibited from downloading or copying data to local devices.

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

Data processing and access will be carried out by substantive employees of the data processor/controller (University of Oxford) who have authorisation from the PI who is working within University of Oxford under honorary contract. All individuals have been appropriately trained in data protection and confidentiality.

No other organisation is permitted to access the data.

There will be no requirement and no attempt to reidentify individuals when using the data. Analysts from the University of Oxford will process the data only for the purposes described above.


Evaluating Clinical Outcomes in Hip, Knee, Foot, and Ankle Surgery — DARS-NIC-667559-J3L9G

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2023-04-20 — 2026-04-19 2023.06 — 2023.09.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)
  4. Patient Reported Outcome Measures (Linkable to HES)

Objectives:

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

Evaluating Clinical Outcomes in Hip, Knee, Foot, and Ankle Surgery

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

“The purpose of this project is to analyse national hospital episode data to determine the rate of adverse events associated with commonly performed orthopaedic procedures of the lower limbs, investigate the impact of surgeon and unit volume on outcomes, and benchmark proposed thresholds for care outcomes (rate of adverse events or outcomes) that could permit the monitoring of the quality of care and outcomes in the future.

Building upon previous work (DARS-NIC-68703-R4Y6C-v3.5), these national data will be used to identify adverse events for a range of commonly performed hip, knee, foot, and ankle interventions. This study proposes to determine the rate of complications (such as infection, pulmonary embolism, stroke, heart attack, amputation, death) that occur following these procedures along with the risk of readmission, reoperation and revision surgery. The impact of surgeon and treating unit volume will be analysed for individual procedures or groups of similar procedures. National Joint Registry data shows that low volume caseload surgeons may have a higher reoperation rate (Liddle et al JBJS Am 2016), but a similar analysis has not been performed in the Hospital Episode Statistics for joint replacement to investigate whether similar results can be reported, and no such analysis has been performed for the other commonly performed orthopaedic procedures.”

The following NHS England data will be accessed:
• Hospital Episode Statistics (HES) Admitted Patient Care (APC)
• Civil Registration Mortality.
• Patient Reported Outcome Measures (PROMs)

The data requested are required for the analysis of the following:
- to construct a co-morbidity profile for patients (5-year look back Charlson comorbidity index).
- Analyse trends in the rates of procedures being performed (e.g., changes related to the publication of evidence)
- trends in the rates of complications and trends in associations between procedures over time – such as the association between ankle fracture surgery and subsequent ankle replacement or fusion for osteoarthritis, knee fracture surgery and subsequent knee replacement, etc.
- provide adequate numbers for valid analysis of the less commonly performed procedures.

The level of the data will be Pseudonymised.

The data will be minimised as follows:
- Limited to data for a study cohort identified by NHS England as meeting the following criteria:
- Patients who underwent a procedure identified by a prespecified list of OPCS codes limited to orthopaedic procedures and limited anatomically to hip, knee, foot or ankle between 1998 and 2023
- Limited to data between 1998 and 2023. For each individual patient, HES data will only be provided from the date 5 years before the qualifying procedure and all data after until 2023. 5-years look back and the follow up period is necessary as there is no long term outcome data for these procedures. It makes the best use of all of the patient data requested, maximising the potential benefits and impact of the work. For less commonly performed procedures, this allows a larger sample to be analysed increasing the statistical validity of the work.

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

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

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

This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research and aims to produce publicly available information to inform future decisions over patients’ treatments or care.

The funding is provided by the Academy of Medical Sciences. The funding is specifically for the project described. Funding is in place until the end of this agreement.

Data will only be accessed by substantive employees of the University of Oxford.

A Public and Patient Information and Engagement group were consulted regarding the collection of the data for the purposes described above. The study will develop plain English summaries of findings for communication to patients and members of the public. These will be freely available and published on the NDORMS website (ndorms.ox.ac.uk). The findings may also be presented at patient and public engagement events. The proposed analysis plan and outputs have been reviewed and approved by an established patient and public involvement (PPI) group.

Expected Benefits:

The use of the data could:

• help the health and social care system to better understand the health and care needs of populations.
• lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
• advance understanding of regional and national trends in health and social care needs.
• inform planning health services and programmes, for example to improve equity of access, experience and outcomes.
• inform decisions on how to effectively allocate and evaluate funding according to health needs.
• provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.

The study aims to improve health practice, reducing harm by disseminating findings on the rate of complications associated with orthopaedic procedures performed for the hip, knee, foot, and ankle. This work is in the public interest in the context of the expected measurable benefits.

Analysis will be reported for the studied procedures in different populations of patients and factors associated with a higher risk of adverse events will be summarised. Variation will be studied and reported along with trends at a geographic level.

The impact of hospital and surgeon volume on outcomes will be studied and reported and this is likely to inform improvements to care through recommendations on service design and care pathways. It is highly likely that complication rates vary by health provider (hospital or surgeon level) for these procedures and this investigation will be important in benchmarking care so that an outlier hospital, for example, could be identified in the future to improve outcomes and avoid harms. It is likely that surgeons with a higher volume practice in some procedures may have better outcomes, but it is not known for which procedures this is important – this study may help to define the procedures that are best performed by more specialist surgeons with a high volume of experience rather than ‘generalists’ performing smaller numbers. This may not be case for all procedures, but it not currently known if this is the case for procedures other than joint replacement.

The outcomes from this study may inform patients and surgeons about the risks of procedures and aims to support the shared decision-making process and could lead to fewer high-risk procedures being performed where this risk was previously unknown. Adverse outcomes for certain procedures performed for similar indications may be identified and compared. For example, in foot and ankle surgery, outcomes of ankle replacement and ankle arthrodesis will be compared. These two procedures can be offered for similar indications but there is little information to inform patients and surgeons on relative risks of rarer but serious adverse events. This is because the number of these procedures performed in single centres is usually small and numbers reported in series in the literature also too small to be adequately powered to report this information.

The study outcomes may inform NHS managers, commissioners and other health professionals of the outcomes and predictors of outcome for some of the most common orthopedic procedures. This may encourage a change in practice where necessary, for example due to geographic variation or inappropriately high rates of surgery or higher than expected complication rates. The study outcomes may provide commissioners with evidence of any factors that can explain or address unwarranted variation.

In summary, it is hoped that some of the measurable benefits to health and or social care will be:

1. Patients may be better informed and empowered in the shared decision-making process around these surgical procedures. They may have a better understanding of the risks and long-term outcomes, and this may be invaluable in the consenting process. This improvement could benefit hundreds of thousands of patients undergoing hip, knee, foot and ankle procedures each year.

2. Surgeons may be informed and supported in delivering evidence-based surgery. This may change practice, encouraging ineffective procedures to be abandoned or improve decision making by providing rich data on the relative risks of procedures. The findings of this study may be disseminated to surgeons through journal publications, conference presentations, and communication through social media and the British Orthopaedic Association (BOA).

3. NHS commissioners may be supported in decision making around pathway design and service improvement. For example, for any specific procedures where low volumes are shown to be associated with poor outcomes. Some types of procedures or procedures for certain groups of patients may be found to be of limited benefit or of unacceptably high risk, and such procedures could be recommended for decommissioning. This may lead to large cost savings and ensure patients do not undergo procedures with high risks of adverse events for limited or no benefit. Similarly, the outcomes could help ensure patients do not undergo treatment on a care pathway that could be optimised, for example, in a higher volume centre (should the data analysis support such a recommendation).

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

Outputs:

The expected outputs of the processing will be:

• A report of findings to the British Orthopaedic Association (BOA) to produce British Orthopaedic Association Standards (BOASts) which are guidelines on the management of orthopaedic conditions. The evidence generated from the proposed work may inform new BOASts or updates to current BOASts.

• Submissions to peer reviewed journals. The first publication target is 18 months from data receipt, with further publications at 6 monthly intervals.

• Presentations to the British Association of Surgeons of the Knee (BASK), British Orthopaedic Association (BOA), British Hip Society (BHS), and British Orthopaedic Foot and Ankle Society (BOFAS) Annual Meetings are targets for the presentation of the proposed work. International dissemination will also be sought, through journal publications and conferences such as the American Academy of Orthopaedic Surgeons (AAOS) and European Federation of National Associations of Orthopaedics and Traumatology (EFORT).

• Publication of dashboards on the University of Oxfords' website, including social media engagement with patients, surgeons, researchers, and allied health professionals. The NDORMs Twitter account (@ndorms) will be used to announce study progress and results. This is intended to engage patients, surgeons, and researchers with research outputs as they are produced.

• Public reports: The study will develop Plain English summaries of findings for communication to patients and members of the public - these will be freely available and published on the NDORMS website (ndorms.ox.ac.uk). The findings may also be presented at patient and public engagement events.

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

The outputs will be communicated to relevant recipients through the following dissemination channels:

• Journals
• Workshops involving patient and public engagement events and groups
• Social media
• Public reports
• Industry newsletters

The target date for publication of the results and other outputs is spring 2025.

Processing:

No data will flow to NHS England for the purposes of this agreement.

NHS England will provide the relevant records from the HES APC, Civil Registration Mortality and PROMS datasets to the University of Oxford. The data will contain no direct identifying data items. The data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

The data will not be transferred to any other location.

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

The data will be accessed onsite at the premises of the University of Oxford only.

Personnel are prohibited from downloading or copying data to local devices.

The data will not leave England, at any time.

Access is restricted to individuals within the Botnar Research Centre, Nuffield Department of Orthopaedic, Rheumatology & Musculoskeletal Science (NDORMS) of the University of Oxford who have authorisation from the Principal Investigator. All such individuals are substantive employees of the University of Oxford.

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

The data will not be linked with any other data.

There will be no requirement and no attempt to reidentify individuals when using the data.

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


QResearch and Q-Covid (ODR1819_247) — DARS-NIC-656839-K5V9L

Type of data: information not disclosed for TRE projects

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

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

Purposes: Yes (Academic)

Sensitive: Sensitive

When:DSA runs 2023-05-22 — 2024-05-21 2023.07 — 2023.09.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: Yes

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS National Radiotherapy Dataset (RTDS)
  3. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

The University of Oxford requires access to NHS England National Disease Registration Service (NDRS) data for the following research projects:
Q-Research Linked Database and Q-Covid.

Q-RESEARCH:
The Q-Research project aims to develop and maintain a high-quality database of general practice-derived data linked to secondary care data for use in ethical medical research. The database is used for medical research into the causes of disease, history of treatment and outcomes. The Q-Research database (GP data only) is distinct from the linked asset (QResearch linked database).

Under the Public Health England Office of Data Release (PHE ODR), the Q-Research project was granted permission to onward share the NDRS Cancer Registry data with other UK Universities. The project team are now seeking additional permissions to use the Radio Therapy Dataset (RTDS) and Systemic Anti Cancer Dataset (SACT) data for Q-Research; and, onward share the RTDS and SACT data via the Q-Research database with other UK Universities.

The onward sharing of the data will be subject to the following restrictions:
• The University of Oxford is only permitted to onward share SACT and RTDS where there is a linked cancer registration record.
• The University of Oxford will only share data that can be linked to a GP record they have received from EMIS Health.

Q-COVID:
The Q-Covid project aims to continue to develop an evidence-based risk prediction model that estimates a person’s combined risk of catching coronavirus and being admitted to hospital, catching coronavirus and dying, and dying of coronavirus following a positive PCR test.

There are currently two-ongoing Q-Covid projects that require continued access to RTDS and SACT data, these are:
• Uptake and comparative safety of new COVID-19 therapeutics by age, sex, region, ethnicity, comorbidities, medication, deprivation, risk level and evidence of prior COVID infection. https://www.qresearch.org/research/approved-research-programs-and-projects/uptake-and-comparative-safety-of-new-covid-19-therapeutics/
• Development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population. https://www.qresearch.org/research/approved-research-programs-and-projects/development-and-evaluation-of-a-tool-for-predicting-risk-of-short-term-adverse-outcomes-due-to-covid-19-in-the-general-uk-population/
After these projects conclude NHS England would not expect any further Q-Covid projects to use NDRS data.

To support Q-Research and Q-Covid, Public Health England (PHE) Office for Data Release (ODR) previously disseminated NDRS Cancer Registry data (from January 1993 to December 2018), NDRS Radiotherapy Dataset (RTDS; from July 2018 to May 2020) previously for use in Q-Covid only and NDRS Systemic Anti-Cancer Therapy (SACT) data (from July 2018 to May 2020) previously for use in Q-Covid only.

The study team now requests to receive the latest available data for the NDRS Cancer Registry, RTDS and SACT, and to receive both SACT and RTDS records for cohort members dating back to 2010 onwards.

All data being disseminated is deemed to be pseudonymised.

The data requested will be minimised as follows:
- The NDRS Cancer Registry data is limited to 01/01/1995- 31/12/2020.
- The RTDS and SACT data is limited to 2010- 31/10/2022, only data that link to a NDRS Cancer Registry Record will be supplied
The study team have liaised extensively with the NDRS Production team to ensure that the data being requested and retained is limited to only those data items that are necessary to achieve the purpose outlined within this Data Sharing Agreement (DSA).

Under a separate Agreement (DARS-NIC-382794-T3L3M) NHS England provision Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES). This data will be linked to the NDRS data disseminated under this Agreement, and the GP data contained within the Q-Research database (received from EMIS Health).

The patient-level data linked to QResearch (QResearch linked database) is only accessed by either:
1. the University of Oxford for research projects approved by the University of Oxford QResearch Governance Approvals Route*. This access will be restricted to individuals substantively employed by the University of Oxford, students registered with the University of Oxford and individuals from other universities that have an honorary contract or secondment agreement with the University of Oxford.
2. other UK Universities for research projects that have been approved by the QResearch Governance Approvals Route. This will be supported by the sublicence data-sharing model.

The University of Oxford is the controller who has determined the purpose and means of processing the data being disseminated by NHS England. As the sole controller, the University of Oxford is responsible for ensuring that data will only be processed as described within this DSA.

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

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

Dancing House Consulting process the data disseminated under this Agreement under the direction of the University of Oxford.

Dancing House Consulting provide IT services to the University of Oxford, this includes backup services and database administration services. Dancing House Consulting supply support, but do not access data for any other reason. Therefore, any access to the data held under this agreement for any other reason would be considered a breach of the agreement.

The funding for this work comes from multiple sources. Current funders include but are not limited to:
- National Institute for Health Research (NIHR).
- Wellcome Trust
- Health Data Research UK (HDR UK)
- Cancer Research UK
- Blood cancer UK
- Pancreatic cancer UK
- Children with Cancer UK
Funding is ongoing and will continue to be obtained from several different sources.

* The University of Oxford QResearch Governance Approvals Route
Research undertaken using the data from the QResearch-linked database continues to be processed using the existing arrangements with respect to scientific review and the provision of annual reports to the Derby Research and Ethics Committee (DREC).

All research projects have to be peer-reviewed, original, hypothesis-driven or hypothesis tested and intended for publication in an academic peer-reviewed journal. All research undertaken using the QResearch database and linked data are subject to independent peer review and the results of all research are published.

Researchers are charged for the work in generating the outputs for research projects and a contribution to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch-linked data such as QCancer are published as free open-source software and also licensed for a fee as closed-source software from third parties such as Oxford University Innovations, for organisations unable to use the open source.

A summary of the QResearch Application Governance Process is detailed below:

1) Researchers originate a research question and write an outline protocol.
2) Pre-submission enquiry
3) IF feasible, cost estimate & letter of support
4) Researchers secure funding
5) A detailed data specification is produced
6) Co-produce a lay summary with Patient and Public Involvement (PPI) groups
7) Submit the Application
8) Review by Scientific Committee & feedback is given
9) Revisions if needed
10) Obtain approval
11) Timeline agreed for extraction
12) Approve within one month (with associated sublicence agreement in place before NHS England Data is released, if the application is not from the University of Oxford)

Requests are submitted and then reviewed at the monthly QResearch Science Committee. The minutes of the Science Committee is published here https://www.qresearch.org/about/scientific-committee/committee-minutes/

The committee advises the QResearch team on scientific issues relating to research applications, ensuring that each application has a clear research question or hypothesis which is likely to lead to generalisable findings capable of publication in a peer-reviewed medical journal. They advise if the research meets a minimum scientific standard and if not, amendments that will be required. They also assess the risks involved and will seek advice from QResearch Advisory Group if required. The committee ensures they follow the criteria and principles set out by the QResearch Advisory Board in assessing and advising on research applications where data is requested from the QResearch or QResearch-linked databases.

The Chief Investigator for QResearch is responsible for ensuring that data access is provided in accordance with the protocol, and ethics approval for the research database and following the advice of the advisory and scientific committees.

The researchers do not have access to the entire QResearch-linked database. Once an application has been approved (and a sub-licence agreement is in place), a subset of the pseudonymised record-level data (as approved for the study) will be extracted and stored on the University of Oxford servers (as described in more detail in section 5b Processing Activities) and researchers will be given a login to remotely access the specific extract via the University of Oxford servers to conduct their analysis. All remote access must take place within the UK. No record-level data can be downloaded by researchers as the IT system restricts this.

For further information on the application governance process please see the links to the QResearch website below.

QResearch Home Page: https://www.qresearch.org/
Scientific Committee – QResearch: https://www.qresearch.org/about/scientific-committee/
Approved Research Programs and Projects – QResearch: https://www.qresearch.org/research/research-programs-and-projects/
Data – QResearch: https://www.qresearch.org/data

The data are requested to link to the existing QResearch database to be used for medical research by academics employed by UK universities. QResearch is a not-for-profit collaboration between the University of Oxford and Egton Medical Information Systems (EMIS). QResearch is part of EMIS’ corporate social responsibility portfolio and provides GP data from contributing GP practices on a not-for-profit basis. EMIS are not involved with processing the NHS England or GP data at the University of Oxford.

Researchers are charged for generating the outputs from research projects and contributing to the running costs. All subsequent research outputs from QResearch are made publicly and freely available. Risk prediction algorithms derived from QResearch linked data such as QRISK2 are published as free open source software and also licensed for a fee as closed source software from organisations such as Oxford University Innovations and ClinRisk Ltd for organisations unable to use the open source.

The data will never be used for sales or marketing purposes.

The NHS England data will only be used for research and analyses where there is a clear benefit to health and social care in England and Wales in order for NHS England to be confident that Oxford meets the requirements under the Health and Social Care Act 2012 as amended by the Care Act 2014.

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

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

Yielded Benefits:

There have been many yielded benefits arising from work. The team have derived two key benefits from the Q Research work, two examples; HES and Mortality Linked data: Cancer prediction modelling The database was used to develop the QCancer – www.qcancer.org which assesses the risk that a patient may have a current undiagnosed cancer based on the patient’s risk factors and symptoms. The tool quantifies overall cancer risk and risk of individual cancers to help management decisions e.g. to refer the patient for an urgent 2-week wait or to organise more investigations or to reassure and review the patients as needed. the tools is embedded in GP systems and available for use in clinical consultations. Similar tools are being developed to help identify cancer among children and young people and to inform targeted screening programs among adults better. QResearch linked database was used to develop the NIHR-funded QCOVID tool https://digital.nhs.uk/coronavirus/risk-assessment/clinical-tool which identifies patients at risk of COVID-19 death and hospital admission. It is used to risk stratify the entire population to add patients to the shielded patient list and prioritise them for vaccination. It is also used as a clinical tool in consultation between patients and clinicians to personalise risk improve decision making and guide interventions including immunosuppressed patients with cancer and those receiving chemotherapy. In summary, the benefits yielded so far include the cancer work; Benefits for individuals – personalised risk estimates to improve decision making; prioritisation for referral, screening and other measures including workplace adjustments. Benefits for clinicians – more reliable objective information on cancer risks to support decision making; automated calculation to supplement decision making (avoids the need for every clinician to assess risk factors individually). Benefits for researchers- tools to stratify patients for clinical trial entry, which may help make trials run more efficiently and report more quickly, Benefits for policymakers – better evidence base to inform the development of policy (e.g. distribution of vaccination, prioritisation of novel therapeutics), ensuing equity (e.g adjusting risk by ethnicity to avoid widening health inequalities), the cost-effectiveness of the use of resources and appropriate defendable prioritisation; planning of services.

Expected Benefits:

The QResearch database is widely used by researchers to help understand patterns of disease, safety or medicines, development of prediction tools, research into health inequalities and other similar research questions where the results are likely to have benefits for patients, the NHS or to improve understanding of the disease. The research results continue to result in new knowledge and experience regarding disease epidemiology, health inequalities, drug safety, and methods of identifying patients at high risk of serious illnesses. Every year new research is published in high-impact international research journals such as the British Medical Journal and the British Journal of General Practice. The research is ongoing with target dates for individual projects rather than one overall target date.

A complete list of research papers using the QResearch database is published at http://www.qresearch.org/SitePages/publications.aspx

Research arising from the QResearch database including the linked data has been used to inform national policy. For example, research findings have been included in NICE guidelines on suspected cancer, fragility fracture, diabetes, and lipid modification. Research findings have informed the NHS Health Checks programme and Department of Health guidelines on health checks.

Examples of research include an assessment of the safety of COVID-19 vaccines among people with cancer; an investigation of potential links between diabetes drugs and cancer; quantification of the risk of breast cancer associated with various types of oral contraceptive pills and HRT.

Outputs:

The outputs are research papers which are published in peer reviewed academic scientific journals and presented at academic conferences. All research is published in academic journals with a link from the QResearch website on an ongoing basis. The publications are accompanied by press releases from relevant organisations and highlighted on social media.

Results are also regularly shared with patient participants on the QResearch Advisory Board and PPI representatives on individual research projects.

Examples of conferences include the annual academic conference for the Society of Academic Primary Care and the UK Research and Innovation (UKRI); international conferences such as the North American Primary Care Research Group; the annual conferences of the EMIS National User Group (a national education and research charity representing the GP practices which contribute data to QResearch); annual conferences run by cancer charities such as Macmillan Cancer Support and Pancreatic Cancer UK; local and regional conferences run by the Nottingham Biomedical Research Centre.

Results are also shared with policymakers, including the Chief Medical Officer's (CMO’s) office, the Medicines and Healthcare Products Agency (MHRA), Joint Committee on Vaccination and Immunisation (JCVI), the Department of Health and Social Care (DHSC), Scottish Office and National Institute for Health Care Excellence (NICE) guideline committees on a regular basis via their stakeholder consultations in order to support the development of relevant guidelines.

Outputs will only contain aggregate-level data with small numbers suppressed in line with the HES analysis guide.

No indicators are produced that show the performance of an organisation – indeed the identity of the GP practices contributing to QResearch is not shared with any third party.

Examples of research-related outputs:

The outputs include a risk prediction tool (QCovid) to identify those at high risk of severe outcomes from COVID-19 (including those with cancer and on cancer treatments) and multiple COVID-19-related research reports, research papers which are published in peer-reviewed academic scientific journals (for example, British Medical Journal (BMJ) and Lancet Journals) and presented at academic conferences (for example, Annual Scientific Meeting of the Society for Academic Primary Care (SAPC).

Other outputs include an analysis of the safety of COVID-19 vaccinations and of the uptake, safety and effectiveness of monoclonal antibodies among people with blood cancer.

All research is published in academic journals with a link from the QResearch website on an ongoing basis.

A list of all publications arising from the QResearch database https://www.qresearch.org/publications/research-papers/

Examples of research outputs:

Research funded by INNOVATE UK to develop a risk stratification tool to identify those at high risk of oesophageal cancer will likely lead to a more efficient way of identifying patients who might be eligible for the Cytosponge device (which is an alternative to endoscopy). This is especially important given the limitations on use of endoscopy arising from the COVID-19 pandemic (results expected 2023/4).

Another project funded by INNOVATE UK investigates the risks and benefits and health economic consequences of the pilot lung cancer screening program is expected to inform the development of the national screening program (results expected 2023/4).

Processing:

EMIS Health (commercial supplier of GP computer systems) process the GP data from the original data controllers (GP practices) and sends it to the University of Oxford. EMIS is not able to access or process any GP data once it is located at the University of Oxford.

EMIS Health is neither a data processor nor a data controller for the data provided by NHS England under this Agreement. EMIS Health is not able to access the NHS England data under any circumstances. GP practices (data controllers) have permitted the GP data it supplies to be linked with the data from NHS England for purposes determined by the Principal Investigator at the University of Oxford and described in this agreement.

No data will flow to NHS England for this Agreement.

Before providing data to the University of Oxford, NHS England will use the Open Pseudonymiser software (www.openpseudonymiser.org) to pseudonymise the NHS England data at source. NHS England will use a project-specific ‘salt’ key to ensure that the identifiers are specific to the University of Oxford. NHS England retains the salt key, meaning that the University of Oxford is unable to re-identify the data but can still link the data with the pseudonymised GP data. The University of Oxford will not hold or be given access to a copy of the pseudonymisation salt key.

NHS England will provide the University of Oxford with the relevant records and fields from the following NDRS datasets: Cancer Registration, SACT and RTDS datasets.

The data will contain no directly identifying data items. The data will be pseudonymised, and there will be no attempt or requirement to re-identify individuals by linking the records with other data already held by the University of Oxford.

NHS England provides pseudonymised data to the University of Oxford via Secure Electronic File Transfer (SEFT). The data will be linked to other data already contained within the QResearch database at the individual patient level using a pseudonymised version of the NHS number which has been supplied in both GP data and the NHS England data. The linkage will incorporate the following data, all of which are pseudonymised:
• The NDRS data disseminated under this Agreement
• The Civil Registration of Deaths, COVID-19-related datasets and all sub-sets of Hospital Episode Statistics (HES) provisioned under DARS-NIC-382794-T3L3M
• Intensive Care National Audit & Research Centre (ICNARC) data
• Lung Cancer Screening Data

The University of Oxford uses offsite backup services provided by Dancing House Consulting.

The data will be accessed by authorised personnel via remote access. The data will always remain on the servers at the University of Oxford.

Researchers are prohibited from and not technically capable of downloading or copying data to local devices.

The data will not leave the UK at any time. All remote access must take place within the UK.

The QResearch database linked to NHS England data will only be accessed by a limited number of substantively employed, individuals within the QResearch unit. They will produce subsets of the data that will be accessed by the University of Oxford (with access restricted to individuals substantively employed by the University of Oxford, students registered with the University of Oxford and individuals from other universities that have an honorary contract or secondment agreement) or its sublicensee(s) as per the QResearch Application and Approvals process.

The subsets of data are then used for undertaking research as described in this agreement. These staff will process and analyse the subset of data to address an approved research question(s).

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

There is no requirement to re-identify individuals from the data and no attempts will ever be made to do this.

Regular reviews will be undertaken to ensure that all appropriate controls are in place to minimise any risk of re-identification.

The University of Oxford conducts an annual internal audit for auditing the technical controls in place. The scope of the internal audit applies to the review of the QResearch Systems Level Security Policy and QResearch Workstation Setup Requirements.


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

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, Yes, No (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(b)(ii); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-12 — 2024-05-05 2022.05 — 2023.09.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care
  4. Patient Reported Outcome Measures (Linkable to HES)
  5. Civil Registrations of Death - Secondary Care Cut
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)

Expected Benefits:

It is hoped that the expected measurable benefits to health and or social care will be:
1. Patients potentially better informed to participate in the decision to undergo revision hip and knee replacement. Patients will hopefully be informed about the observed joint function, quality of life, short-term complications, longer-term outcomes and variations in care following revision joint replacement. It is hoped patients will be informed via social media engagement, public reports and patient engagement work as listed in the section above. The rationale for a broad, multifaceted engagement strategy is to reach as wide a patient audience as possible. Patients undergoing revision joint replacement are heterogenous and whilst many are avidly engaged with social media, many prefer more traditional engagement activities.

2. It is hoped that surgeons will be supported to change practice to deliver evidence-based surgery. Surgeons will hopefully be informed of the findings via journal publications, conference presentations, a DPhil thesis, and communication through social media and the British Orthopaedic Association (BOA). Target dates have been listed in the output strategy above. A broad engagement strategy has been chosen in order to reach as many surgeons and researchers practicing in this are from across the country. For example, the BOA is in regular communication with more than 5,000 members across the UK.

3. It is hoped that NHS commissioners will be supported to promote evidence-based surgery and appropriate resource allocation. There are approximately 13000 revision joint replacement procedures performed each year in the UK. The hypothesis for this work is that some types of procedures or procedures for certain groups of patients may be found to be of limited benefit and as such may be candidates for decommissioning. This may lead to cost savings, and may also mean that patients do not experience procedures with high risks of adverse events for limited or no benefit. This information will be available to care providers and commissioners via outputs 1/2/5 above.

4. It is hoped that there will be improvement in patient reported outcome measures (PROMs) following revision surgery. The NHS routinely collects data on the patient perspective following revision hip and knee replacement as part of the NHS PROMs programme. If this proposal is successful and changes are implemented into practice, then one might expect improvement in PROMs over time.

Outputs:

The specific outputs from the proposed work can be classified as:
1. Peer reviewed journal publications. This will include original articles on patient-reported outcomes, short term complications and longer term outcomes from revision hip and knee replacements. These publications will be Open Access. A first publication is target at 9 months from data receipt, with further publications at 6 monthly intervals.

2. Conference presentations: The proposed work will be presented at national and international conferences. This is to engage a broad spectrum of surgeons and allied health professionals who practice in or around revision joint replacement surgery across the UK. The British Association of Surgeons of the Knee (BASK) and British Orthopaedic Association (BOA) Annual Meetings in 2021 are targets for presentation of the proposed work.

3. Clinical practice guidelines. The University of Oxford study team work closely with BASK and the BOA and have been involved in recent work to produce British Orthopaedic Association Standards (BOASts) which are guidelines on the management of orthopaedic conditions. The evidence generated from the proposed work will be used to update the BOASTs for revision joint replacement. The target date for this is 2023.

4. Social media engagement with patients, surgeons, researchers and allied health professionals. The NDORMs Twitter account (@ndorms) will be used to announce study progress and results. This is intended to engage patients, surgeons and researchers with research outputs as they are produced.

5. Public reports: A project summary will be provided on the NDORMs study webpage. The proposed work will also produce a summary for the National Joint Registry Annual Report. This first summary is intended for the NJR 19th Annual report in 2022.

6. DPhil thesis. This is intended to be published Open Access in 2023 to provide information on outcomes following revision knee replacement. The DPhil student is funded by the Royal College of Surgeons (RCS). The RCS will have no access to the data and no role in its analysis or interpretation.

7. Patients engagement work: The University of Oxford has already started to involve patients and the public with this proposal and will continue this over the duration of the proposal. The Patient and Public Involvement Strategy for this proposal is as follows:
(i) Establishing key priorities for research on revision joint replacement.
See previous references to James Lind Alliance Priority Setting Partnership work.

(ii) Establishing patient views on data linkage without consent
This has been tested in 4 patients known to the research team (mix of men, women, different ages, from various parts of the country who have had a known problem with an implant after surgery). Patients were chosen as a convenience sample by the Nuffield Orthopaedic Centre, Oxford. 4/4 patients agreed that it would not be practical to contact all patients to obtain consent due to the size of the population. The feedback from all had a common theme: the potential benefits from new information on revision knee replacement meant that it was important for this research to be performed. They were satisfied that opt-out mechanisms were in place should patients wish to do so.

(iii) Establishing patient views on the programme of revision knee replacement research proposed
Telephone interviews have been performed with four patients to describe the proposed research programme. They provided very positive feedback. Some quotes were:
-“This will provide very useful information”
-“I think it can help others in the future, and it seems like a very good idea”
-“I have been through several operations on my knee and there isn’t much information out there for patients like me.”
-“I actually had very good information from Oxford when undergoing my revision knee replacement, and I really wish that information on revision knee replacement was rather better known around the country.”

(iv) Extended PPI work
The University of Oxford is recruiting a PPI group of 8-12 patients who are awaiting or have undergone revision knee replacement. The University of Oxford will explore with this group:
-What factors are important to patients in the decision to undergo revision knee replacement?
-How should outcomes following revision knee replacement be evaluated in a way that is meaningful to patients?
This group is currently being recruited.

(v) Revision arthroplasty study website
This is being set-up. Lay summaries of research will be available on this website.

(vi) Open days
These were held regularly, but are currently paused due to Covid-19, but will be reinstated in-person or virtually within the first year of the project.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

All organisations party to this agreement must comply with the data sharing framework contract requirements, including those regarding the use (and purposes of that use) by “personnel” (as defined within the data sharing framework contract i.e. employees, agents and contractors of the data recipient who may have access to that data).

STAGE 1
(Data Flow 1) On behalf of HQIP, Northgate Information Solutions will transfer the following identifying fields into NHS Digital from the National Joint Registry (NJR):
- NHS number
- Date of Birth
- Gender
- Postcode
- NJR unique identifier (which will be designated the Study ID)

The NJR unique identifier is provided for each eligible patient from the NJR for the purpose of linkage to NHS Digital held datasets.

NHS Digital will create the study cohort:
(i) NHS Digital will link the NJR cohort to HES using sensitive identifiers
(ii) NHS Digital will identify a cohort of patients with a hip or knee replacement (University of Oxford will send in the operation codes) from HES APC (1998/99 to 2019/20)
(iii) NHS Digital will identify all hip and knee replacement procedures on PROMs
(iv) NHS Digital will combine the cohorts from (i), (ii) and (iii), and extract:
-All HES APC episodes for these patients from 1998/99 to 2019/20
-Civil Registrations (Mortality) for these patients

(Data Flow 2) NHS Digital will transfer to the Big Health Data Group (BHDG) at University of Oxford, pseudonymised records of eligible individuals from HES APC, Civil Registration (deaths) and PROMS. The only pseudonym to be returned is the Study ID.

(Data Flow 3) Northgate Information Solutions will transfer to the Big Health Data Group (BHDG) at University of Oxford, pseudonymised records of eligible individuals from the NJR. These records will include:
- Study ID
- Age at surgery in years
- Gender.

(Data Flow 4) On receipt of the NJR/HQIP and NHS Digital data sets, the BHDG will be responsible for linking the two data sources. The resulting pseudonymised record-level data-set will be linked, stored and analysed within the BHDG's Data Security Protection Toolkit (DSPT) compliant environment.

STAGE 2
(Data Flow 5)
When the Master Person Service (MPS - an enhanced person-matching algorithm that increases the number of linkable records where incomplete records have been submitted.) is available for PROMs, NHS Digital will repeat linkage of the NJR to PROMs based on the sensitive identifiers provided in Data Flow 1 (which will have been retained). NHS Digital will supply the PROMS_SERIAL_NO (a unique ID in PROMS) and Study_ID to BHDG in University of Oxford as a separate linkage file.

The University of Oxford is requesting HES APC data for patients found in the NJR cohort AND patients with hip and knee joint replacements not found in the NJR cohort.

There will be no linkage to any publicly available data. There will be no attempt to re-identify individuals from this data-set, and results will be presented at aggregate level with small numbers suppressed in line with the HES Analysis Guide. The linked data set containing data from NHS Digital will not be accessed by the NJR/HQIP. Only substantive employees of the data controller will have access to the data under this agreement. These employees of the data controller have been appropriately trained in data protection and confidentiality. Within the University of Oxford Big Health Data Group, data is held in the Secure Computing Room, which is access controlled. Data are encrypted and stored in a safe. Data are accessed on non-networked computers.

DATA MINIMISATION:
>Datasets
1. NJR-HES-PROMs-Civil Registrations (Mortality) are requested. It is not possible to reduce the number of datasets because: (i) incomplete case ascertainment of NJR (ii) further granularity is required on patient comorbidities and complications (pre-existing and new) from HES and PROMs datasets (iii) data on mortality is required as a competing risk for implant (re)revision
2. The purpose can be achieved in a less intrusive way by using pseudonymised data.

>Years
3. The proposed study will investigate trends over time in modern arthroplasty practices. As such, data from 1998 is appropriate.

>Filtering
4. The proposed study will investigate geographic trends so geographic narrowing is inappropriate.
5. The proposed study will investigate the effect of patient demographics, so filtering is inappropriate - except data for those under 18 is not required.
6. The proposed study requests data on patients who have received a hip or knee joint replacement and requests filtering on this criterion (using OPCS codes supplied and linkage to the NJR dataset)

>Episodes
7. The study is investigating both the effect of pre-existing comorbidity on outcomes and the development of new comorbidity both in the short-term and long-term (up to 15 years). As such, episodes 5 years prior to joint replacement and all subsequent episodes are relevant.
8. Elective episodes are relevant as they may represent further surgery to the joint replacement or a new comorbidity
9. Maternity and neonatal episodes are not required and have not been requested.
10. Timeframe - Data from 1998 is requested to appropriately investigate trends overtime in modern arthroplasty practices.

Fields
11. Fields have been selected to provide predictors and outcomes of interest. This includes ETHNOS as ethnicity may be a predictor of outcome.
12. Full date of death has not been requested, but month/year has been requested instead to prevent intrusion

Cohorts
13/14. Linkage to NJR cohort is requested AND/OR matching with a pre-specified list of hip and knee replacement OPCS codes

There will be no data linkage undertaken with NHS digital data provided under this agreement that is not already noted in the agreement.


Project to Help Improve Decision Aids for Predicting Outcomes in Early Breast Cancer: (ODR1718_390) — DARS-NIC-656818-N1B5Q

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2023-07-01 — 2026-06-30 2023.08 — 2023.08.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

The University of Oxford requires access to NHS England data for the purpose of the following research programme: Project to Help Improve Decision Aids for Predicting Outcomes in Early Breast Cancer.

Female invasive breast cancer is the commonest cancer in England, with over 40,000 new cases diagnosed and nearly 10,000 deaths each year. Invasive breast cancer is a long drawn out disease, and the risk of recurrence or death from breast cancer continues for at least 20 years after diagnosis. Most patients have early stage disease and receive surgery as their first treatment. Outcomes following treatment for early invasive breast cancer differ substantially across different countries and across different patient characteristics within a country. Patients diagnosed with breast cancer and the clinicians who treat them need estimates of their likely prognosis to inform treatment decisions, follow-up, and prediction of event rates for groups of patients in clinical trials. They also need estimates of the risks of diseases other than breast cancer. These estimates require large-scale, population-based studies that consider the effects of multiple patient and tumour factors on the risks of recurrence of breast cancer, of death from breast cancer and of the incidence and mortality of other diseases. It is known that survival from breast cancer has improved and that incidence and mortality of other diseases has changed. However, detailed estimates based on patients treated recently are not currently available. These estimates are needed to enable clinicians to estimate prognosis for patients treated today using characteristics such as age, tumour size, nodal status, grade, receptor status and screening status.

The objectives of this project are as follows:

1. To describe the incidence of second cancers among women diagnosed with breast cancer according to the characteristics of both patients and their tumours, and to assess the extent to which this has changed with calendar year of diagnosis and how it varies with time since diagnosis.

2. To describe patterns of breast cancer mortality and of mortality from other causes according to the characteristics of both patients and their tumours, and to assess the extent to which this mortality has changed with calendar year of diagnosis and how it varies with time since diagnosis.

3. To describe the incidence of other diseases among women diagnosed with breast cancer according to the characteristics of both patients and their tumours, and to assess the extent to which this mortality has changed with calendar year of diagnosis and how it varies with time since diagnosis.

4. To provide predictions of the absolute magnitude of the likely benefits and risks of the various treatment options available for patients diagnosed recently, making them relevant to patients diagnosed today.

5. To provide estimate of the risk of developing a recurrence of breast cancer from routinely collected data, using methods derived in a separate project (ODR1718_364) which is being carried out in conjunction with NDRS staff.

To achieve objective 1 The University of Oxford would like to receive updated versions of two files previously disseminated under Public Health England (PHE). These involve providing data on cancer registrations up to the end of 2020 for patients already in the study. In addition, The University of Oxford received information on the potential prognostic factor Ki67.

To achieve objectives 2-5 The University of Oxford would like to receive the information summarised below and additionally, would like to receive information on the prognostic factor Ki67. This information will be supplied using new pseudo_ids. However, The University of Oxford would like to receive a file linking the old pseudo_ids with the new pseudo_ids for those patients who are in the existing cohort. It is important for the fulfilment of objectives 2-5 that The university of Oxford receive information on patients diagnosed since 2017. As recently shown (BMJ2023;381:e074684), the breast cancer mortality rate increases rapidly during the first two years after initial diagnosis and reaches a peak during the third year. The study team have also shown that mortality rates at any given time after diagnosis have been changing rapidly in recent years. Therefore additional patients diagnosed since 2017 is required in order to be able to provide estimates that are relevant for patients who are being diagnosed now. The study team also need information on patients diagnosed recently to estimate the risk of developing a recurrence, partly in order to provide up-to-date estimates but also in order to make use of recent developments in data capture and storage by NDRS.

To achieve objectives 2-5, the following NHS England data will be accessed:

• National Disease Registration Service (NDRS) Cancer Registration
• National Disease Registration Service (NDRS) Hospital Episode Statistics
- Admitted Patient Care
- Outpatients
- Accident & Emergency
• National Disease Registration Service (NDRS) National Radiotherapy (RTDS)
• National Disease Registration Service (NDRS) Systemic Anti Cancer (SACT)
• National Disease Registration Service (NDRS) Cancer Wait Times (CWT)
• National Disease Registration Service (NDRS) Diagnostic Imaging Dataset (DIDs)
• National Disease Registration Service (NDRS) Cancer Pathway (CWT)

The quantum of Data requested is necessary to achieve the objectives of this project.

The level of the data will be Pseudonymised and will be minimised as follows

• Limited to data for a study cohort identified by NHS England
• Limited to data between 1 Jan 1971 – latest available
• Limited to conditions relevant to the study identified by specific ICD codes for invasive breast cancer ICD10:
C50x, ICD9: 174X, ICD8: 174X;
• Limited to the following geographic areas [England]
• Women only

The University of Oxford is the research sponsor and the data controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above. Additionally, the study team have taken all steps necessary to ensure that they have all the appropriate institutional ethical support in place from University of Oxford.

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

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

The funding is provided by The University of Oxford and Cancer Research UK via a Programme Grant. Funding is in place until 2027. Cancer Research UK will have no ability to suppress or otherwise limit the publication of findings of this research.

The University of Oxford is the sole data controller and sole data processor.

There are no other organisation(s) involved or accessing the NHS England data, including organisations acting in an advisory capacity or as part of an oversight or steering committee.

Before starting the project, the opinions of oncologists, surgeons, breast cancer groups (e.g. the National Cancer Research Institute Breast Clinical Studies Group and the National Cancer Intelligence Network Breast Site Specific Clinical Reference Group) and consumer representatives (Independent Cancer Patients Voices) were sought in an advisory capacity using questionnaires and at meetings to help inform the objectives of the work.

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

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

Yielded Benefits:

Data for this study has previously been shared when the data were controlled and managed by Public Health England (PHE). As such there are some yielded benefits to be observed from the access to the data for the study prior to NHS England becoming data controller. These yielded benefits are noted below: The manuscripts cited in the outputs have proved helpful in planning resources needed for radiotherapy and are hoped will influence clinical practice and guidelines. This research work has already changed clinical practice. In breast cancer where The University of Oxford have provided clinicians with information on the benefits and risks of various treatment options. This allows them to make informed choices about which treatments to recommend to individual patients. Studies derived from this research have been primary references in each of the major international guidelines for the management of breast cancer including those produced by the National Institute for Health and Care Excellence (NICE)1,2 the Scottish Intercollegiate Guidelines Network (SIGN),32 the UK’s Royal College of Radiologists (RCR),4 the American National Comprehensive Cancer Network (NCCN),5 the Japan Breast Cancer Society,6 and the joint American Society of Clinical Oncology/American Society for Radiation Oncology/Society for Surgical Oncology (ASCO/ASTRO/SSO).7 The results of this research are essential in treatment decisions, so they are used in training oncologists and related health care professionals. For example, results have been presented annually at the European Society of Therapeutic Radiation Oncology teaching course since 2009 and at the 4-yearly National Cancer Institute Radiation Epidemiology Dosimetry course. References: 1: Early and locally advanced breast cancer: diagnosis and management. [I] Evidence reviews for postmastectomy Radiotherapy. NICE guideline NG101, Evidence reviews. July 2018; https://www.nice.org.uk/guidance/ng101/evidence/evidence-review-i-postmastectomy-radiotherapy-pdf-176567997780 2: Early and locally advanced breast cancer: diagnosis and management. [H] Evidence reviews for breast radiotherapy. NICE guideline NG101, Evidence reviews. July 2018; https://www.nice.org.uk/guidance/ng101/evidence/evidence-review-h-breast-radiotherapy-pdf-4904666613 3: SIGN 134. Treatment of primary breast cancer. A national clinical guideline. September 2013; https://www.sign.ac.uk/assets/sign134.pdf 4: Postoperative radiotherapy for breast cancer: UK consensus statements. November 2016; https://www.rcr.ac.uk/system/files/publication/field_publication_files/bfco2016_breast-consensus-guidelines.pdf 5: National Comprehensive Cancer Network Clinical Practice Guideline in Oncology: Breast cancer Version 5.2020. https://www2.tri-kobe.org/nccn/guideline/breast/english/breast.pdf 6: Komoike Y, Inokuchi M, Toshikazu T, Kaouru K, Goro K, Takehiko S, Hiromitsu J, Noriaki W, Shozo O, Hirofumi M. Japan Breast Cancer Society clinical practice guideline for surgical treatment of breast cancer. Breast Cancer 2015; 22(1): 37-48. 7: Recht A, Comen EA, Fine RE, Fleming GF, Hardenbergh PH, Ho AY, Hudis CA, Hwang ES, Kirshner JJ, Morrow M, Saleron KE, Sledge Jr GW, Solin LJ, Spears PA, Whelan TJ, Somerfield MR, Edge SB. Postmastectomy Radiotherapy: An American Society of Clinical Oncology, American Society for Radiation Oncology, and Society of Surgical Oncology Focused Guideline Update. Practical Radiation Oncology 2016; 6(6): e219-34

Expected Benefits:

The findings of this project are hoped to provide high quality information to enable patients and clinicians to make informed decisions in the treatment of breast cancer based on the individual characteristics of the patient. For many patients, several different treatment options are available and selecting the best one can be challenging. The results of this project will make this selection easier and can be expected to improve outcomes for breast cancer patients.

The results of the project will also provide baseline figures against which national audits can be compared to assess how widely evidence from recent guidelines has been implemented. These can be used in several ways, including estimation of the number of women needed in randomised trials and to inform radiotherapy resource allocation.

The expected benefit to patients as an outcome subject to the findings is that patients will be better informed of the likely benefits and risks of the various treatment options available to them, taking account of their individual characteristics.

The proposed outputs will be published in peer-reviewed journals. They will also be presented at appropriate conferences focussing on breast cancer and its consequences. The findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

Clinicians will be made aware of the findings through publications in peer-reviewed journals. The University of Oxford are also liaising with groups of patient representatives, such as Independent Cancer Patients’ Voice. The University of Oxford also inform CRUK of the results of our work and, where appropriate, they will issue press releases.

Outputs:

The expected outputs of the processing will be:

• A series of peer-reviewed publications reporting the analyses of the data from the NDRS on outcomes in breast cancer patients, and on the development and validation of the prediction models. These are listed below with their current target dates:

• The first publication appeared in the journal Clinical Oncology in 2020 that provided estimates of the proportion of women receiving adjuvant breast cancer radiotherapy who would be eligible for partial breast radiotherapy according to both the NICE guidelines and the Royal College of Radiologists Consensus Statement. A second publication has been accepted by the British Medical Journal (BMJ) and will be published in June 2023.

A paper describing a population based observational cohort study of breast cancer mortality in 500,000 women diagnosed with early invasive breast cancer in England, 1993-2015 has been accepted for publication in the British Medical Journal (BMJ). These findings:
- A manuscript describing the ability of Ki67 (a marker of cell proliferation which is available from routinely collected pathology reports) to improve prediction of mortality from breast cancer has been prepared and will be submitted for publication shortly. It is expected that this will be completed early in 2024.

• An analysis of the incidence of and mortality from other cancers in women diagnosed with breast cancer. It is expected that this will be completed in 2024

• An analysis of mortality from non-cancer diseases in women diagnosed with breast cancer. It is expected that this will be completed in 2024.

• An analysis of the incidence of non-cancer diseases in women diagnosed with breast cancer. It is expected that this will be completed in 2024.

• Finally, when the algorithm to identify recurrences in women with early breast cancer is ready, analyses of patterns of recurrence in women diagnosed with early breast cancer will be prepared and submitted to peer-reviewed journals. It is expected that this will be completed in 2025.

In addition to the above:

• Presentations will be made at conferences relating to breast cancer and other meetings to publicise the work.

• Periodic updates will be published to incorporate additional follow-up on women already diagnosed with breast cancer, information on women recently diagnosed with breast cancer, and appropriate improvements to the model.

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

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

Processing:

No data will flow to NHS England for the purposes of this Agreement.

NHS England will provide the relevant records from the NDRS HES A&E, HES IP, HES OP, CANCER Registry, SACT, CWT, RTDS and DIDS datasets to University of Oxford.

All data linkage will be undertaken by NHS England, before data are transferred to researchers at The University of Oxford.

The data will remain on the servers at University of Oxford at all times. The data will not be transferred to any other location and will not leave England/Wales at any time.

The University of Oxford provides IT support and all IT hosting services.

Data will be stored within Nuffield Department of Population Health (NDPH) in Oxford University. Electronic data files are kept on password-protected network servers behind a local firewall. Servers are kept in a locked room with access restricted to IT staff.

Access to electronic data is restricted via user identification. Backups are held on private internal servers spread over three locations within the Old Road Campus of the University of Oxford. Backed up data is encrypted both in transit and at rest. Access to data is restricted via user identification. No data are moved or copied from these servers.

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

Analysts and researchers from the Nuffield Department of Population Health at The University of Oxford will analyse the data for the purposes described above and there will be no requirement and no attempt to reidentify individuals when using the data in Oxford.

Data processing and access will be carried out by substantive employees of the data processor/controller (University of Oxford) who have authorisation from the PI and who have been appropriately trained in data protection and confidentiality.

Whereby during the term of this agreement processing is required to be carried out by students affiliated with the University of Oxford (to potentially form part of studies ie: a DPhil degree) The University of Oxford, will only do so if beneficial to the research. Whereby during the term of this agreement processing is required to be carried out by individuals with honorary contracts (to help introduce increased level of clinical expertise), The University of Oxford will only do so if beneficial to the research to help achieve the study objectives.

The University of Oxford will ensure the correct supervisory and contractual requirements for the individuals are in place and The University of Oxfords organisational governance policies and controls are adhered to.

The data will be accessed by authorised personnel via remote access. Personnel are prohibited from downloading or copying data to local devices.

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


Outcomes of Patients who survived Treatment on an Intensive Care unit for COVID-19 in England and Wales (OPTIC-19): a comparative retrospective cohort study — DARS-NIC-419335-H5P8T

Type of data: information not disclosed for TRE projects

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'., Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-09-15 — 2023-09-14 2021.11 — 2023.08.

Access method: One-Off

Data-controller type: INTENSIVE CARE NATIONAL AUDIT & RESEARCH CENTRE (ICNARC), UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Emergency Care Data Set (ECDS)
  3. GPES Data for Pandemic Planning and Research (COVID-19)
  4. Hospital Episode Statistics Accident and Emergency
  5. Hospital Episode Statistics Admitted Patient Care
  6. Hospital Episode Statistics Outpatients
  7. MSDS (Maternity Services Data Set)
  8. MSDS (Maternity Services Data Set) v1.5
  9. Civil Registrations of Death
  10. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  11. Hospital Episode Statistics Accident and Emergency (HES A and E)
  12. Hospital Episode Statistics Admitted Patient Care (HES APC)
  13. Hospital Episode Statistics Outpatients (HES OP)
  14. Maternity Services Data Set (MSDS) v1.5

Expected Benefits:

Through addressing questions about the impacts of severe COVID-19 on subsequent adverse events among survivors, the outputs of this work hope to inform:
- Clinicians regarding the ongoing/future risks to their patients
- Patients now and in the future of their short, medium and long-term risks.
- The wider health care community and health services that are tailored to the treatment of patients during and after ICU. These organisations are hope to include the ICUsteps charity and Oxford Critical Care Forum.

This work hopes to identify potentially modifiable risk factors that may lead to identification and treatment of patients who have survived treatment for COVID-19 on the ICU. Ultimately the benefit will depend on which risk factors are identified and the degree to which they can be modified in clinical practice. For example, if survivors of severe COVID-19 have an excess risk of cardiovascular disease, these patients might benefit from statin therapy even if identified as low risk by current primary care guidelines (e.g. as predicted by QRISK-2).

ICNARC is one of few organisations internationally who collate detailed data on intensive care patients at scale. For this reason, the study team expect their study to be one of the largest to inform the follow-up care of patients who have survived severe COVID-19.

Through publication of several scientific papers and presentations at scientific meetings on the topic the study team hope to raise the understanding of the scale of the risks faced by patients following ICU. This work should lead to further funded work that result in prevention and treatment options.

Outputs:

This study aims to publish at least two journal articles describing the risk faced by survivors of COVID-19 treated on an ICU. The first article aims to report six month outcomes (target date: 1st October 2021) and the second aims to include one year outcomes (target date: 1st December 2021).

The study team will be responsible for publishing outputs in high-impact open access peer-reviewed journals, such as the British Medical Journal, Intensive Care Medicine and the Lancet. All outputs will be aggregated with small number suppression applied as per the HES analysis guide. All published output aim to be accompanied by a corresponding press releases including lay summaries of the findings and its applicability to patients. When major findings are published, the Departmental press office aims to assist with press releases, social media messages and interviews.

The study hopes to also be promoted through the CCRG Twitter handle (@KadoorieCentre), which has over 1000 followers comprising of patients and health care professionals. Findings hope to be be presented at national and international conferences to experts in the field – for example, the UK Intensive Care Society State-of-the-Art annual conference and one of the European Society of Intensive Care Medicine’s bi-annual conferences.

The study team aim to present their results to relevant patient groups and their families via the ICU charity “ICUsteps” (https://www.icusteps.org/). They hope to also discuss their progress with the Oxford ICU patient forum, whose members include former ICU patients and their relatives. The study team hope to specifically seek the advice of both groups on how best to present the study results to the wider public. The study team developed a patient notification strategy with input from the Oxford Research Ethics Committee (REC) and members of the Oxford ICU Forum (a group of previous ICU patients, families, and lay members). The study will fully implement the National Data Opt-out and will therefore exclude any records related to patients who have notified the NHS of their wish for their data not to be used in research.

For a previous study, the study team were advised by the ethics committee that placing posters in the relative rooms or waiting areas of the participating ICUs to notify patients of the study, “was not practical and should not therefore be used”. All members of the Patient and Public Involvement (PPI) panel agreed with the ethics committee that displaying posters would not be appropriate. However, the PPI group advised that information should be available on a study website. The group advised that the website summary should be brief and accessible, with links to the detail (such as formal privacy policy) available. Members of the previous study PPI group were also consulted for this study (OPTIC-19) and were very clear in their support.

The aim is to achieve these outputs within the 15 month study period.

The study website (https://www.ndcn.ox.ac.uk/research/critical-care-research-group-kadoorie-centre/research-studies/six-month-outcomes-after-surviving-treatment-for-covid-19-disease-on-an-intensive-care-unit-in-england-optic-19) will be updated with all the details of the above.

The study team aim to engage with senior critical care clinicians in Oxford and Thames Valley should the results suggest how clinical follow-up of patients treated for COVID-19 on the Intensive Care Unit (ICU) might be improved.

Processing:

The Data Flow for this agreement will consist of the below:
a. ICNARC will identify the study cohort and allocate participants a unique study ID.
b. Identifiers (NHS Number, Date of Birth, Gender and Post Code) and the unique study ID will be submitted by ICNARC to NHS Digital using their secure electronic file transfer (SEFT) system.
c. NHS Digital will link to record-level HES, MSDS, GDPPR and Civil Registrations using the patient identifiers provided.
d. NHS Digital will then remove identifiers to pseudonymise the extracts.
e. NHS Digital will send the pseudonymised record-level extracts of the above-mentioned data products for the duration of the study via SEFT to the Critical Care Research Group at the University of Oxford.

The pseudonymised data from NHS Digital (HES/MSDS/GDPPR/Civil Registration data) will be linked by The Critical Care Research Group at the University of Oxford to health data and National audits from NHS Wales Informatics Service (NWIS), Barts' health NHS Trust (on behalf of the National Institute for Cardiovascular Outcomes Research (NICOR), Kings College London (on behalf of the Sentinel Stroke National Audit Programme (SSNAP), and the UK Renal Association (UKRR) and then subject to a process of data cleaning and data quality assessment. The study will also link data from the UK Obstetric Surveillance System (UKOSS) to identify patients who were pregnant at the time of ICU admission.

The resulting pseudonymised dataset will then be used for statistical analysis in keeping with a pre-defined statistical analysis plan.

No data will be matched to publicly available data and there will be no requirement/attempt to re-identify individuals.

As ICNARC is responsible for and runs the CMP program, ICNARC will always hold a copy of both the source data (the CMP program) and the study specific pseudo-anonymous data (for analysis purposes). Due to pre-existing privacy commitments if a patient contacted ICNARC and requested their data was removed from the data set then they would be obliged to do so. During the period the study is running, patients who raise requests to have their data removed from the study with either ICNARC or the CCRG will be identified by their ICNARC ID (by ICNARC) and their data removed from the study database by the CCRG/ICNARC. After the study period ends, the study team will destroy the ledger linking the ICNARC CMP ID to the OPTIC-19 Study ID making it impossible to directly link the study dataset to the individual. In terms of the study itself, all analysis will be performed on the anonymous dataset and there is no intention or requirement to re-identify the data at a later stage.

Both ICNARC and Oxford are collaborators on this project and run separate specialist analysis platforms and expertise within the groups (hence the co-data controller relationship). As result we will require the work to be performed by both teams in both environments. All data processing at the Critical Care Research Group at the University of Oxford and ICNARC will take place using secure systems. The data will not leave these systems at any time. All data held within these environments are owned and run solely by the respective data controllers/processors/data guardians.

The final pseudonymised study data will be stored securely within the CCRG Data Safe Haven and ICNARC servers for a minimum of five years after the end of the study, in keeping with the MRC Retention Framework for Research Data and Records.

Data processing is only carried out by substantive employees of the University Of Oxford and ICNARC who have been appropriately trained in data protection and confidentiality.

All data processing within the Critical Care Research Group at the University of Oxford takes place within a secure system which is designed in keeping with the principles of NHS Digital Security Assurance requirements. The data does not leave the system at any time and users connect via a remote desktop connection to a protected analysis environment that runs within the system - all connections are via encrypted tunnels into the system. The remote desktop connection prevents uses from transferring files or copying data in either direction. No data is copied or transferred to the remote device/client machine. Access to the environment is protected by two firewalls, departmental Virtual Private Network (VPN) and requires strong key based login.

The system is located in a locked, access-controlled server room within the CCRG research offices. All remote machines are university owned, standard build computers that conform to Cyber Essentials Plus accreditation and are compliant with the NHS Digital Data Security and Protection Toolkit (DSPT).

The study data set will never be released from this environment and it will be deleted at the end of its retention period.

Members of the study team, both in Oxford and at ICNARC, will undertaking statistical analysis of the study data set. For this reason, a copy of the pseudonymous data set will also be held at ICNARC (conforming with NHS DSP). Data will be stored on secure servers at ICNARC (office in London) or servers which are owned by an authorised contractor called Exponential-e (https://www.exponential-e.com/). Exponential-E are a contractor authorised by ICNARC and provide protection with a leading anti-virus protection. The anti-virus protection that is provided to ICNARC's servers provides protection against all currently known malware whereby is being updated on a daily basis with over 400,000 variations of updates per day. In addition to this signature based protection the level ICNARC also has advanced signatureless protection. This protects against the latest attacks more commonly known as “zero day” . These attacks are seen more with ransomware attacks and will detect an attack in progress, stop it in its tracks and then clean any effected server. The console then provides a function of reporting for analysis to review. Exponential-e are compliant with ISO 9001; ISO 27001; ISO 14001; ISO 22301; ISO 50001; ISO 20000 and also hold a Health & Social Care Network Complaint certificate of compliance. Employees of Exponential-E will not access the data, but will provide storage/back-up, and as such, are listed as processors.

Identifiable data held in the Case Mix Programme will be kept separate to the pseudonymised dataset for analysis. No attempt to reidentify participants will be made.

The data will be accessed from a networked PC via a Local Area Network. Firewalls are in place to prevent unauthorised remote access. Access to the networked PC is via username and password. All data analysis will be conducted within the confines of the ICNARC secure server, and will not be downloaded to remote devices for storage or processing. Only authorised members of staff working on the study will access the data. The CCRG will confirm that this data set is deleted at the end of the same study retention period.


EVAREST/BSE-NSTEP Study Cohort to gather follow up data — DARS-NIC-620484-W0B2K

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, No (Consent (Reasonable Expectation))

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

Purposes: Yes (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2023-05-11 — 2026-05-10 2023.07 — 2023.07.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Objectives:

The University of Oxford are requesting NHS England pseudonymised record level data for the Study: Echocardiography: Value and Accuracy at REst and STress “EVAREST”

BACKGROUND:
Stress echocardiography is a commonly used test to assess for heart disease. It is performed routinely across the country in many different ways. The University of Oxford are examining how stress echocardiography is used in the diagnosis of heart disease, whether there are differences in how the test is performed between hospitals and how the results of the stress echocardiogram guides patients’ care. The EVAREST study should allow University of Oxford to gather information about how this test was performed and how it has helped doctors give patients the most appropriate care. University of Oxford will also examine how stress echocardiography is performed across the country.

STUDY AIMS
The primary objective of this study is to characterise the change in extracellular MVs and associated blood biomarkers during standardised stress echocardiogram protocols and understand the relevance of this change as a predictive marker of coronary disease. However, the request for data in this agreement relates to part of the secondary objectives of the study, namely to investigate the use of stress echocardiography as a clinical procedure in the UK (Group 1-3).

Identifying the long-term outcome data from these patients post functional imaging, is an integral piece of this research project. This analysis will look to assess performance and accuracy of stress echocardiography practice in the UK, which will also include an analysis on the costs associated with the long-term patient care pathway of those who have received a stress echocardiogram.

ORGANISATIONS AND RESPONSIBILITIES
The University of Oxford will be the sole data controller for this agreement and will also be processing the data. The study team are based within the Cardiovascular Clinical Research Facility (CCRF) within the University of Oxford. The sole sponsor and funder for the data analysis section of this project is the University of Oxford.

The British Society of Echocardiography act as an advisory board for the purposes of the study, but are not the sponsor of the study, nor do they decide the purpose and means of processing the data, and do not/will not have access to record-level data from NHS England. The University of Oxford have reviewed ICO requirements / definition of a Data Controller and are satisfied that the British Society of Echocardiography are not a data controller.

In the past, the study has variously been funded by an National Institute for Health and Care Research (NIHR) - Health Education England (HEE) Healthcare Science Research Fellowship, Ultromics Ltd and Lantheus Medical Imaging Inc but these organisations are no longer involved with the study and will have no access to record level NHS England data. The University of Oxford have reviewed ICO requirements / definition of a Data Controller and are satisfied that these organisaitons are not a data controller.

DATA REQUESTED
The University of Oxford are requesting access to the following record level pseudonymised NHS England datasets from the period 2018/19 to latest available data:

- Hospital Episode Statistics (HES) HES Admitted Patient Care (APC)
- HES Outpatients (OP)
- HES Critical Care (CC)
- Emergency Care Dataset (ECDS)
- Diagnostic Imaging Dataset (DIDS)
- Civil Registration (Deaths) Data

The data requested will create a clinical picture of the immediate and subsequent cardiac history for each patient enrolled in the study. This data will be aligned with the initial clinical reasoning and interpretation of cardiac disease/risk to help identify the initial success of the functional testing (stress echocardiography).

The overarching EVAREST project seeks to investigate the accuracy and feasibility of stress echocardiography as a functional imaging modality for cardiology. This requires primarily a large cohort (there are multiple methods of performing stress echocardiography) and a substantial follow-up period in which it is possible to identify any patterns of disease or trends with associated outcomes/risk factors. These will ultimately help improve the accuracy of the test when being performed if it highlights the needs for alterative testing methods, or greater weighting on certain risk factors or demographics.

In order to ascertain the immediate, short term and long-term outcomes in patients having undergone stress echocardiography, this study requires a detailed and long-term follow-up plan. This includes acquiring data surrounding potential cardiac pathways post stress echocardiography, death, admission to Emergency Department (ED) for chest pain and any cardiac imaging or diagnostic testing that may have been undertaken and subsequently altered a patient’s treatment pathway.

This will ensure that this study can build a cardiac history for each participant, and compare this to their initial presentation, the immediate results of the stress echocardiography and the subsequent intervention strategies should this be implemented.

With regards to the acquisition of this data, whilst some could be obtained from the individual patient notes, it is likely that patients will have moved across Trust boundaries, be seen at different NHS hospitals for acute admissions etc during the lengthy follow-up period, and as a result, NHS England is content that the request is the most appropriate and least intrusive method for obtaining the high-quality data required to make these informed observations.

The study team have worked to minimise the data that is requested so that only data requested relating to cardiac investigations/events, in addition to death data. The disease in investigation is common and will help to minimise risk with patient identification. A pseudonymised study ID is used by the University of Oxford, so that once the data is linked and extracted, the study team can analyse the data meaningfully using only a Study ID.

COHORT
This EVAREST programme of work started in 2014 and seeks to obtain 10-year follow-up data on all participants who have consented to follow-up data from NHS England. This study is still actively recruiting.

Study Participants were added to three groups. Groups 1 and 2 collectively (Phase 1 of the study) consists of 8,000 participants referred for stress echocardiogram by their clinical consultant in order to establish likelihood of coronary artery disease (CAD). Recruitment started in early 2015 and completed in March 2020.
Group 3 (Phase 2 of the study) consists of up to 15,000 participants referred for stress echocardiogram for the investigation of any disease. This includes, but is not limited to, stress echocardiography to assess ischaemia, valvular function, left ventricular outflow tract obstruction, diastology*, myocardial perfusion and tissue viability.

*diastology - The scientific study of the heart muscle when it is not contracting but is in diastole (at rest)

The cohort provided to NHS England will be approximately 6,000 individuals from the above 3 groups. 3,000 from phase 1 and 3,000 from phase 2.

The cohort consists of patients over the age of 18, eligible for recruitment having undergone stress echocardiography at one of the designated recruitment centres.

If a participant requests to withdraw from the study, this will be notated within the Castor eDC system used as part of the study. There is a specific withdrawal Case Report Form (CRF) that will be used for these requests. The participant will have an opportunity to provide a reason for their withdrawal if they so choose. The study team will also ask the participant if the study has permission to keep data after the withdrawal. If the participant does not consent to this, then the database will alert the study team member to delete all data from within the eDC that has been collected to date for that participant with the exception of details of their original consent and withdrawal.

LEGAL BASIS FOR COMMON LAW DUTY OF CONFIDENTIALITY
The study team at University of Oxford will be providing one cohort for this request containing approximately 6,000 individual records. Consent to data linkage has been sought for all participants in phases 1 and 2.

For those study participants in phase 1 (groups 1 and 2) recruited between June 2015 and 21 October 2019 (originally about 8,000 individuals ), consent was originally sought for a 12 month follow up, and then these study participants were re-consented for a further 10 years follow-up period. Only those that re-consented (approximately 3,000) will be a part of the cohort sent to NHS England. Of the phase 1 study participants, the consent documents provide for requesting NHS England data for a maximum of 10 years** from 12 months after the first date they consented into the study.

For those study participants in phase 2 (group 3) recruited from 21 October 2019 onwards (approximately 3,000 individuals), the consent documents provide for requesting NHS England for a maximum of 10 years** from the date of first consent.

**However, it is noted here that due to trial budget constraints, the EVAREST study is requesting NHS England data only between the periods of 2018 to the latest data available under the consent rules stated above.

The cohort provided to NHS England will only contain participants who consent to data linkage. NHS England will not apply National Data Opt-Out for these participants.

UK GDPR LEGAL BASIS FOR PROCESSING OF PERSONAL DATA
The University of Oxford, as the Data Controller who is also processing the data will process Personal Data under UK GDPR Article 6 (1) (e) - Processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. As a higher education establishment, the University of Oxford conducts research to improve health care and services, and the data requested is necessary for the performance of a task carried out in the public interest. The University of Oxford hopes that this research study and the dissemination of the results will benefit the health and care of the general public by providing a rich detailed look into Stress Echocardiography practice in the UK and health outcomes following the investigation. This work should enable the study team to identify the accuracy of the investigation as well as areas for improvement. This will allow for corrective action to boost accuracy of Stress Echocardiography and thereby increase the quality of the health of individuals presenting for a Stress Echocardiogram investigation. The dissemination is in the public interest as it should provide evidence for the improvement of patient health and care. The outputs should provide the data needed to identify the accuracy and performance of Stress Echocardiography in across the UK for a large cohort of patients.

Additionally, under UK GDPR Article 9(2)(j) processing of Special Category Personal Data (of which Health data is one) is necessary for archiving for research purposes. Data minimisation processes are being followed and only data that is specifically required for the purposes of this study have been requested, to protect the rights of the data subjects. The data are required for research purposes in the public interest – meeting the conditions in the DPA 2018 Schedule 1 Part 1 (4) – which UK GDPR Recital 52(2) determines is an appropriate derogation from the prohibition on processing special categories of personal data.

TRANSPARENCY ON COMMERCIAL BENEFITS
Whilst Ultromics Ltd and Lantheus Medical Imaging Inc were originally funders of this study but are no longer involved and will have no access to record level NHS England data under this agreement, for the purposes of transparency it is stated here that Ultromics Ltd and Lantheus Medical Imaging Inc may receive indirect benefit from association with the EVAREST study. However, Ultromics Ltd and Lantheus Medical Imaging Inc will have no ability to suppress or otherwise limit the publication of findings from this study.

Expected Benefits:

The research study and the dissemination of the results hopes to benefit the health and care of the general public by providing a detailed look into Stress Echocardiography practice in the UK and health outcomes following the investigation. This work hopes to enable the study team to identify the accuracy of the investigation as well as areas for improvement. This should allow for corrective action to boost accuracy of Stress Echocardiography and thereby increase the quality of the health of individuals presenting for a Stress Echocardiogram investigation.

The dissemination is in the public interest as it hopes to provide evidence for the improvement of patient health and care. The outputs aim to provide the data needed to identify the accuracy and performance of Stress Echocardiography in across the UK for a large cohort of patients. Once the purpose is achieved, the benefits discussed hope to be realised.

The study team hope that the details of the work and dissemination will look to identify room for improvement in the practice of Stress Echocardiography. This could potentially impact all centres in the UK who routinely perform stress echocardiograms (around 120 as of 2014). If areas for improvement are noted and actioned, this could potentially lead to an increase in overall diagnostic accuracy of stress echocardiography, thereby reducing the need for potentially unnecessary further procedures and investigations in the patient care pathway. A reduction in unnecessary procedures and interventions could potentially decrease the burden on the NHS and allow resources to be utilised elsewhere. Individual patients could receive the benefit in having a more experienced and accurate stress echocardiogram investigation. This benefit in the individual level could be identified through further downstream research studies assessing stress echocardiography and patient health outcomes. It could take time to achieve these benefits as implementing trainings and affirmative action plans for increasing centre performance can take time. Policy change and cost savings can also require sufficient time to enact. The University of Oxford would expect that within the next 10 years they could see evidence of change in the patient care pathway, burden to NHS resources, and potentially national/international policy due to this dissemination.

Outputs:

The study team at University of Oxford aim to publish this work in a peer-reviewed journal. During the course of analysis there may be conferences and presentations that are conducted that include mention of EVAREST either in part or fully. All data included in presentations or publications will be anonymised meaning only high-level aggregate data with small numbers supressed (as per the HES analysis guide) will be presented.

The University of Oxford will aim to facilitate the dissemination of the research and scientific work to stakeholders during the project and after completion. The study team will aim to disseminate this research to the scientific public through presentations, publications and discussions. The study team will also aim to disseminate this research to the general public through publications. The study team are also planning to disseminate this work for potential policy change such as with National Institute for Health and Care Excellence (NICE) or European Society of Cardiology (ESC). This should all be accomplished through conferences, publications, presentations, webinars, engagement using professional and established relationships.

The study team aim to analyse the data and public preliminary work in 2023/2024 contingent upon when the data is received from NHS England. There may be various presentations, conferences, public events within that time that the data will also be presented at.

Processing:

DATAFLOW
Transfer of linkage file/identifiers from University of Oxford to NHS England:
- University of Oxford will send the list of Patient Identifiable Data (PID) in the form of one file - including participant Study ID, NHS Number, Date of Birth (DoB) and Post Code along with the date that data should flow from for each individual in the cohort. University of Oxford will send this file securely to NHS England via a Secure Electronic File Transfer Service (SEFT) or other secure, NHS England approved file transfer mechanism.

- The NHS England data production teams will link patient identifiers to the datasets requested and extract data either:
a) for phase one study participants originally consented between June 2015 and 21 October 2019 - from 12 months after the date of consent*.
b) for phase two study participants consented from 21 October onwards - from date of participants' first consent date.
(*PLEASE NOTE: The Study team have requested the extraction of data to be for NHS England data for the periods 2018/19 to latest available data only)

- The NHS England production teams will remove patient identifiers from the linked data.

- NHS England transfers the linked data via SEFT or other secure, NHS England approved file transfer mechanism to University of Oxford. This data is pseudonymised (only the participant ID from the linkage transfer is kept and identifiable fields are removed).

- University of Oxford study team downloads the data from SEFT to an encrypted system within the University of Oxford Medical Sciences Division IT Network.

The data will be accessed through this secure network. To remotely access the devices requires a secure 2-factor Medical Sciences Division IT authenticator (VPN) and users are then able to securely access the secure server on the University’s IT framework. All data analysis will be conducted within the confines of the University’s secure server, and will not be downloaded to remote devices for storage or processing.

All data analysis will be conducted by EVAREST study team members who are substantive employees of the University of Oxford or authorised study team members with an appropriate contract which has been reviewed and approved by NHS England.

The Patient identifiers provided to NHS England were originally collected by the local study teams at each participating site in the study and were then provided to the University of Oxford study team. These identifiers are only held at the University of Oxford for the purposes of providing to the NHS England team for linkage purposes. Once the identifiers are provided to the NHS England team, they will be destroyed by the University of Oxford study team prior to receiving record-level NHS England data.

The University of Oxford will not be sharing record-level NHS England data outside of the University of Oxford. All record-level NHS England data will be maintained and analysed within the University of Oxford.

Those handling the data for the Data Controller will have been authorised to do so internally and will have logged information security training.

Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide (see below)

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


MR565: The Million Women Study - addition of only 1 year complete HES data for 2018/2019. — DARS-NIC-389134-S8L1C

Type of data: information not disclosed for TRE projects

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: No (Academic)

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

When:DSA runs 2020-05-21 — 2021-07-26 2017.06 — 2023.07.

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
  12. Civil Registrations of Death
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)

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.


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

Type of data: information not disclosed for TRE projects

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(2)(b)(ii), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.; Other-Section 251, Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. ; Other-Section 251, Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. ; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261(5)(d); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2018-08-01 — 2021-07-31 2019.02 — 2023.06.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Scottish NHS / Registration
  4. MRIS - Flagging Current Status Report
  5. MRIS - Members and Postings Report
  6. Demographics
  7. Civil Registration - Deaths
  8. MRIS - Bespoke
  9. Civil Registrations of Death

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).


MR1231 - The 3C Study (Campath, Calcineurin inhibitor reduction and Chronic allograft nephropathy) — DARS-NIC-388486-D9M5N

Type of data: information not disclosed for TRE projects

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: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-02-01 — 2022-01-31 2017.09 — 2023.06.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - Members and Postings Report
  2. MRIS - Cause of Death Report
  3. MRIS - Cohort Event Notification Report
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Outpatients
  6. MRIS - Scottish NHS / Registration
  7. Civil Registration - Deaths
  8. Cancer Registration Data
  9. Demographics
  10. MRIS - Flagging Current Status Report
  11. Hospital Episode Statistics Admitted Patient Care (HES APC)
  12. Hospital Episode Statistics Outpatients (HES OP)
  13. Civil Registrations of Death

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


Establishing a UK Colorectal Cancer Intelligence Hub - The COloRECTal Cancer Data Repository (CORECT-R) (ODR2021_249) — DARS-NIC-656885-M7T5X

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2023-02-03 — 2024-03-17 2023.03 — 2023.05.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked Cancer Waiting Times (Treatments only)
  3. NDRS Linked DIDs
  4. NDRS Linked HES AE
  5. NDRS Linked HES APC
  6. NDRS Linked HES Outpatient
  7. NDRS National Cancer Patient Experience Survey (CPES)
  8. NDRS National Radiotherapy Dataset (RTDS)
  9. NDRS Rapid Cancer Registrations
  10. NDRS Somatic Molecular Dataset
  11. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

The UK Colorectal Cancer Intelligence Hub is a research programme whose aim is to generate high quality bowel cancer information that will improve care and
outcomes for patients. It does this through compiling and using datasets relevant to the disease in the COloRECTal cancer data Repository (CORECT-R). This platform is available to the wider research community.

The research team will access cancer registration data collated by the National Cancer Registration and Analysis Service (NCRAS; the national cancer registry in
England) about all people who have been diagnosed with bowel cancer since 01 April 1997. This health data will include detailed information about each person:
• (such as their age, ethnicity and the area they live in);
• their diagnosis (the type of cancer they have, the stage and when it was diagnosed);
• the treatment they received (including details of surgery, chemotherapy and
radiotherapy);
• attendances in hospital and their experience of care.

The data will be brought together with other health datasets to build CORECT-R and support researchers to ask important questions about bowel cancer. Access to data within CORECT-R will be made available to the whole research community enabling pioneering research into bowel cancer. The programme will also help support all aspects of bowel cancer research from laboratory studies to the delivery of clinical care to improve survival. The model used will also support research into other cancer sites and disease areas.

Expected Benefits:

The aim of the research is to improve bowel cancer treatment and care across the UK through identifying areas of poor practice and opportunities for improvement. It will do this by creating a data research platform, known as CORECT-R which will be made available to the whole research community enabling pioneering research into bowel cancer. The programme will also help support all aspects of bowel cancer research from laboratory studies to the delivery of clinical care to improve survival. The model used will also support research into other cancer sites and disease areas.

Outputs:

Linking multiple datasets relating to the management of bowel cancer together to provide a UK-wide view of care, experience and outcomes and making these available to authorised users for research. This linked data enables:
• better understanding of the reasons for differences in care and outcomes in these patients
• studies into the clinical performance of the NHS and to identify opportunities to improve performance
• the NHS to make sure it delivers the best care and complies with clinical guidelines; and
• supports the running of clinical trials

Processing:

It is imperative that individuals in any routine non-cancer datasets in CORECT-R cannot be
directly identified. Our data management and data flows are designed to prevent identification by
undertaking linkage using a secure pseudonymisation process. Extracts of non-cancer data will be
specified from the relevant data source and their unique identifier (such as their NHS number) will
be put through a cryptographic ‘salt’ process. It is possible that there may be some overlap
between the non-cancer dataset and the cancer dataset (for example, if we seek to find all who
have undergone a colonoscopy there will be some individuals within the population where a
cancer was found and so known to CORECT-R already). As such, the identifiers of cancer
patients will also be put through the same cryptographic ‘salt’ process. When the two datasets are
aligned the colorectal cancer patients within the full population will be identifiable as they will
both have the same salted key. For those without cancer only the resulting encrypted identifier
(and the relevant clinical detail) will be accessible to the CORECT-R data managers. The salt ‘key
keepers’ will be nominated staff within the relevant data controller’s organisation and
separate from the CORECT-R data management team. This will remove the possibility of the
CORECT-R team being able to ascertain the identity of those without cancer


RCGP Research Surveillance Network Observational Research Umbrella (RCGP RSC ORUm) — DARS-NIC-381683-R6R6K

Type of data: information not disclosed for TRE projects

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: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2021-02-14 — 2024-02-13 2021.04 — 2023.05.

Access method: Ongoing

Data-controller type: PUBLIC HEALTH ENGLAND (PHE), ROYAL COLLEGE OF GENERAL PRACTITIONERS

Sublicensing allowed: No

Datasets:

  1. Mental Health Services Data Set
  2. COVID-19 Hospitalization in England Surveillance System
  3. COVID-19 Second Generation Surveillance System
  4. Diagnostic Imaging Dataset
  5. Emergency Care Data Set (ECDS)
  6. Secondary Uses Service Payment By Results Accident & Emergency
  7. Secondary Uses Service Payment By Results Episodes
  8. Secondary Uses Service Payment By Results Outpatients
  9. Secondary Uses Service Payment By Results Spells
  10. COVID-19 Second Generation Surveillance System (SGSS)
  11. Diagnostic Imaging Data Set (DID)
  12. Mental Health Services Data Set (MHSDS)
  13. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Objectives:

Since the outbreak of COVID-19 in Wuhan, China, and the subsequent pandemic, PHE has commissioned the RCGP RSC to incorporate the monitoring of COVID-19 into its virology surveillance scheme. A vital part of this work has been to monitor the number of suspected COVID-19 cases in the community in a timely way.

PHE and the RCGP are Joint Data Controllers for this request. The RCGP Research Surveillance Centre (RCGP RSC) is based at the University of Oxford. The RCGP RSC is a growing network of over 1200 GP surgeries based in England. University of Oxford is the data processor.

PHE

Public Health England (PHE) holds a contract with the Royal Collage of Practitioners (RCGP) who in turn hold a contract with the University of Oxford to deliver information to support surveillance and monitoring of vaccine efficacy on Influenza.

RCGP

The Royal College or GPs (RCGP) Research and Surveillance Centre (RSC) has over 50 years’ experience of undertaking surveillance and research activities, predominantly in influenza surveillance. Pseudonymised patient data is extracted from over 1600 practices on a weekly basis, feeding into the disease surveillance and research funded through Public Health England (PHE). The COVID-19 activities set out in this agreement fall within the wider Disease Surveillance activities.

University of Oxford – are a data processor. The secure network which holds the physical data is at the University of Oxford. The University of Oxford acts as Data Processor on behalf of the Data Controller (RCGP and PHE).

The lead Professor who is the RCGP RSC Director, has moved his main appointment from the University of Surrey to the University of Oxford. Oxford currently provide the academic and clinical informatics input to inform data usages and ensure this adheres to contract held with PHE. Additionally, the study produces research outputs from the University of Oxford (these outputs have small numbers suppressed and Oxford are therefore not listed as a data processor).

The surveillance function of the RCGP RSC provides a unique platform upon which to build population based observational epidemiological studies designed to inform the national public health response to COVID-19. Direct COVID-19 analyses will study for example which patient-level characteristics are associated with COVID-19 infection, predictors of adverse outcomes, and potential treatments. Indirect COVID-19 analyses will for example provide near real-time monitoring to inform strategies to mitigate the indirect effects of the national response to COVID-19 on other "COVID-19 sensitive" non-communicable diseases.

Built on high quality primary care electronic health records data, the Joint Data Controllers for this request (PHE and RCGP) hope to add to the existing RCGP RSC HES (Critical Care, Outpatients, A&E, Admitted patient care) and Civil Registration (mortality) Data (CRD) linkages to support the priority observational COVID-19 studies outlined below.

OVERALL AIM

The study aims to establish an umbrella agreement for data linkages to support the RCGP RSC to conduct observational epidemiological studies inform the national public health response to COVID-19.

PRIORITY OBSERVATIONAL WORKSTREAMS

The following three priority workstreams outline analyses underway or in set-up using the RCGP RSC dataset.

1. RGGP RSC COVID-19 SURVEILLANCE

Aim - to identify whether there is undetected community transmission of COVID-19, estimate population susceptibility, and monitor the temporal and geographical distribution of COVID-19 infection in the community.

Specific objectives
1 a. To monitor the burden of suspected COVID-19 activity in the community through primary care surveillance and clinical coding of possible COVID-19 cases referred into the containment pathway

1 b. To provide virological evidence on the presence and extent of undetected community transmission of COVID-19 and monitor positivity rates among individuals presenting ILI or acute respiratory tract infections to primary care. PHE see all specimens (identified by NHS Number within their laboratory department) then pseudonymise this identifier to allow linkage. The PHE data and NHS Digital data will all be pseudonymised using the same algorithm so that a fully linked record for each person in the database will be available for the research team. The analysis will therefore be done by the team at an individual level but without the need to know who that individual is.

1 c. To estimate baseline susceptibility to COVID-19 in the community and estimate both symptomatic and asymptomatic exposure rates in the population through seroprevalence monitoring

1 d. To pilot implementation of a scheme for collection of convalescent sera with antibody profiles among recovered cases of COVID-19 discharged to the community. PHE see all specimens (identified by NHS Number within their laboratory department) then pseudonymise this identifier to allow linkage. The PHE data and NHS Digital data will all be pseudonymised using the same algorithm so that a fully linked record for each person in the database will be available for the research team. The analysis will therefore be done by the team at an individual level but without the need to know who that individual is.


2. DECISION-COVID: DEfining the CharacterIStIcs Of Individuals with suspected Novel COronaVIrus Disease and risk factors for development of the disease.

Aim - To better understand the characteristics of patients being tested for COVID-19 and to determine the associations between demographics, comorbidity and medications on the likelihood of developing COVID-19 and subsequent complications (e.g. hospitalisation, admission to an intensive care unit, death).

Specific objectives
2 a. Identify patient demographics and co-morbidities that predict the diagnosis of COVID-19 and subsequent complications (e.g. hospitalisation, admission to an intensive care unit, pulmonary events, death).

2 b. Identify medications that are associated with and increased or decreased risk COVID-19 infection and complications (e.g. hospitalisation, admission to an intensive care unit, pulmonary events, death).


3. MAINROUTE-C19: Monitoring Attendance, INvestigation, Referral, and OUTcomEs in Primary Care: impact of and recovery from COVID-19 lockdown

Aim - To describe and analyse the impact of the COVID-19 lockdown on presentation patterns, diagnoses, monitoring and outcomes of common non-communicable diseases, such as cancer, cardiovascular disease, diabetes and mental health.

Specific objectives
3 a. To produce practice-level data analytics on presentation, management and diagnoses of common non-communicable diseases and preventive health activities before, during and after COVID-19 lockdown, by region, practice, gender, and age

3 b. To examine the effect of the COVID-19 lockdown (and release) on presentation, management and diagnoses of common non-communicable diseases and preventive health activities by region, practice, gender, age and ethnicity

3 c. To determine the effects of the changes in presentation, management and diagnosis on long-term outcomes such as hospitalisation, morbidity and mortality, and some condition-specific outcomes.


EXISTING DATASET

The main aim of this application is to build on the exiting RCGP RSC database. The RCGP RSC dataset includes individual patient level up-to-date primary and secondary care data which can be easily queried. Primary care/general practice data is rich in terms of diagnosis and information about the process of care. For example, the database contains the following variables for each patient (where present):
• Detailed demographic and risk factor data.
• COVID-19 appointments: including information on whether or not a virology swab was taken and the outcome of the swab
• Non-COVID-19 appointments.
• Detailed data for the 32 conditions monitored by RCGP RSC on behalf of PHE
• Vaccination status: date of vaccination, type of vaccination
• Co-morbid conditions
• Medication which may be associated with better or adverse outcomes.
• Test results
• Referrals made
• A & E visits
• Inpatient appointments, including critical care
• Outpatient appointments
• Mortality data (if applicable).

Existing linkages include CRD and HES data provide key information about the outcomes of care:
• HES: Critical Care
• HES: Outpatients
• HES: A&E
• HES: Admitted patient care
• CRD (mortality) data

ADDITIONAL LINKAGES REQUESTED

Additional individual level linkages to the entire RCGP-RSC cohort will support the priority analyses outlined above. Individual patient level data is required because individual patient level linkage allows much more precise statistical analyses to be made, compared with comparing aggregate data. Additional historical and updating linkages are requested to the following additional datasets:

• Cancer Registration Data
• Secondary Uses Service Payment By Results Episodes
• Secondary Uses Service Payment By Results Outpatients
• Secondary Uses Service Payment By Results Accident & Emergency
• Secondary Uses Service Payment By Results Spells
• Mental Health Services Data Set
• Diagnostic Imaging Dataset
• Emergency Care Data Set (ECDS)
• COVID-19 Hospitalisation in England Surveillance System (CHESS) Dataset
• Second Generation Surveillance System (SGSS) Dataset


Historic data are needed because longitudinal data better enable the RCGP RSC to predict what might happen in the future; even a small increase in the ability to understand flu and COVID-19 and its associated morbidity and mortality would offer benefits for patients and the NHS. Both historical and future data are needed in order to build a robust database and reporting system using up-to-date primary and secondary care data at the individual patient level, which can be easily queried. This will enable the study group to answer a wide range of questions which will have an impact on the provision of health care in England. For example, the data will be used to answer questions posed by PHE, who make many decisions about healthcare, such as the vaccination programme, or preventative measures. In MAINROUTE, for example, longitudinal data will allow time series analyses to be conducted as part of objcetive 3 b. which will compare primary care activity before, during and after "lockdown" to establish whether changed in primary care activity are associated with changes in disease presentation and outcome.

The same pseudonymisation algorithm will be applied to all data involved in this study (and any other studies) so the researchers can draw scientific conclusions for a study population. The PHE data and NHS Digital data will all be pseudonymised at University of Oxford prior to researcher access using the same algorithm so that a fully linked record for each person in the database will be available for the research team.

REGULATORY FRAMEWORK

The GDPR Lawful basis for processing the requested data under this agreement are;

Public Health England;
Article 6(1)(e) (Public Task processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller).

Article 9(2)(h) (processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services)

and

Article 9(2)(i) (processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices).
PHE exist to protect and improve the nation's health and wellbeing, and reduce health inequalities.

RCGP;
Article 6(1)(f) processing is necessary for the purposes of the legitimate interests pursued by a controller, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child. This shall not apply to processing carried out by public authorities in the performance of their tasks.

Article 9(2)(i) (processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices).

Additionally the request for data is supported by PHE as they have an emanation of the Secretary of State for health and social care, to both self-approve the use of Control of Patient Information Regulation 3 and to grant this approval to third parties processing confidential patient information without consent for purposes that fall under the scope of Regulation 3.

This authority to has been in existence since PHE was established in 2013 although the large majority of the Regulation 3 approvals granted since that date have been internal to PHE; only a very small number have been granted by PHE to third parties. Specifically the work being undertaken under Reg 3 in this application is limited to Communicable Disease surveillance and other risks to public health’.

The data will not be shared with third parties and only used within the data processors listed in this agreement. Data disseminated under this application can only be used for different purposes after those different purposes have been approved by NHS Digital under separate applications and a live DSA is in place.

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

Expected Benefits:

The surveillance work conducted by the RCGP RSC on behalf of the Data Controllers is used by Department of Health, NHS England and PHE to monitor trends in a number of infectious conditions. Specifically for COVID-19, the RSC aims to identify whether there is undetected community transmission of COVID-19, estimate population susceptibility, and monitor the temporal and geographical distribution of COVID-19 infection in the community. In addition, the RCGP RSC will describe and analyse the impact of the COVID-19 lockdown on presentation patterns, diagnoses, monitoring and outcomes of common non-communicable diseases, such as cancer, cardiovascular disease, diabetes and mental health. Furthermore the analyses conducted under RCGP RSC ORUm will lead to a better understanding of the characteristics of patients being tested for COVID-19 and the associations between demographics, comorbidity and medications on the likelihood of developing COVID-19 and subsequent complications (e.g. hospitalisation, admission to an intensive care unit, death).

Specific benefits

The linkages described in this protocol can help assess the severity and mortality of a given condition, thereby alerting PHE on whether larger measures should be implemented. This could lead to improved healthcare and reduced mortality of certain conditions. Additionally, the linkages allow the RCGP RSC to identify how COVID-19 lockdown has put additional pressure on the health system in terms of delayed testing and referral, meaning that plans can be put in place in order to prevent or deal with these pressures during subsequent waves of the pandemic.

By supporting RGGP RSC COVID-19 SURVEILLANCE the researchers will be able to augment direct RCGP RSC COVID-19 surveillance using dedicated national COVID feeds (CHESS/SGSS) and enable full care pathway analysis from presentation to community providers (GP/111) through to secondary/tertiary care (ECDS/HES/SUS).

By supporting DECISION-COVID linked data will allow analyses to determine associations between demographics, comorbidity and medications of patients presenting to GP and the likelihood of developing COVID-19 and subsequent complications such as hospitalisation, admission to an intensive care unit, death (ECDS/SUS/HES/ONS), and to characterise socioeconomic and ethnic disparities in patients being tested (CHESS/SGSS) for COVID-19.

By supporting MAINROUTE-C19 linked data will enable an end-to-end description of the impact of the COVID-19 lockdown on the clinical pathway in terms of presentation patterns (GP RSC), testing (RCGP RSC/SUS/HES/DID) diagnoses (GP RSC/SUS/HES/Cancer/MHDS), monitoring (RCGP RSC) and outcomes (GP RSC/SUS/HES/Cancer/ONS) of common non-communicable diseases, such as cancer, cardiovascular disease, diabetes and mental health.

Outputs:

Specific Outputs for this study are:

• To track the impact of COVID-19 lockdown, visual descriptions (dashboards) of the number and rates of patients presenting with specific symptoms (primary care data), being tested for specific tests (including DID data), or referred for particular conditions will be presented over time (at weekly frequency) from 2018 will be hosted online. The raw data will be overlaid by 7-day moving averages, adjusted for seasonality. Subgroups of data will be identified to enable display by GP practice, region, age group, gender, and ethnicity.
• Using HES, SUS, ECDS, Mental Health Services Data, and Cancer data, outcomes will be examined through 7-day moving averages and presented graphically over time for the years 2018, 2019 and 2020 onwards to descriptively compare levels of activity.

Findings from this study will also contribute to existing outputs as follows:

• The RCGP RSC weekly report is circulated to a selected list of recipients on Wednesdays and it is publicly available on Thursdays at 2 pm at the RCGP RSC website (http://www.rcgp.org.uk/clinical-and-research/our-programmes/research-and-surveillance-centre.aspx). This report currently covers incidence rates of 37 infectious and respiratory conditions in England. It is expected that, in future, hospitalisation trends will be included. This is incorporated into the syndromic surveillance carried out by PHE on a daily basis, which allow them to determine any urgent priorities for local health protection teams.
• Similar to this, an annual report is published covering the annual trends of the 37 conditions. Each year, this report has a new theme which is explored in a paper submitted to a peer-reviewed journal (usually British Journal of General Practice). Themes explored include demographic disparities in disease presentation, higher rates of consultations for lower respiratory infections for boys, and urban/rural disparities of presentation.
• In January of every year, the University of Oxford provide a mid-season flu cohort to PHE with data up to the end of December. This is a fully pseudonymised patient-level extract collected by a PHE statistician using a secure drive. This data extract contains details of influenza swabbing, chronic conditions, and vaccination status for each patient. It is hoped to be able to include details of emergency attendances or admission around influenza, pneumonia, or lower respiratory tract infection events. At the end of the flu season (varies from March to May), a second extract is provided updating the first, with data recorded after December.
• The data from both of these extracts is used to estimate seasonal influenza vaccine effectiveness, stratified by comorbidities and demographics. HES data allow the University of Oxford/PHE and RCGP to include the impact of any changes in effectiveness, assessed through changes in hospital admissions/emergencies due to respiratory conditions. The results are published at the mid-season and at the end of season stage, on the peer-reviewed journal Eurosurveillance.
• Important results from either of these will be further analysed and presented at the RCGP annual conference, the PHE annual conference, and the PHE annual epidemiology conference.

Processing:

Flows of data:
• Data are initially extracted from practices that are members of the Royal College of General Practitioners (RCGP RSC) Research and Surveillance Network by Wellbeing. The University of Oxford subcontracts with Wellbeing to do this as part its contractual responsibilities. The data are pseudonymised at source within the Wellbeing extraction process.

• The University of Oxford, on behalf of RCGP RSC, will provide NHS digital with a list of hashed NHS numbers and hashed date of birth for the cohort. NHS Digital will be operating under instruction as a data processor from the Data Controllers in this agreement to process the cohort data as per the details set out in this agreement and return the linked data asset. That data will flow back from NHS Digital using the same hashed algoritham therefore the research team will only be accessing pseudonymised data.

The Hashing process is as follows:
1. An encryption salt is held by a designated staff member of the University of Oxford Medical Science Division who is not a member of the research team.
2. When a data linkage is required, the encryption salt holder sends the encryption salt to the data provider (NHS D)
3. The data provider NHS D in this case will hash personal identifiers (in the data requested under this agreement) using a hashing algorithm
4. The hashing algorithm is SHA2-512.

The data are then linked across the datasets requested in NHS Digital using hashed NHS numbers.

On receipt of the data from NHS Digital University of Oxford will then link the NHS Digital data with the cohort data already held in the University using the same hashed algorithm. The data will be pseudonymised in a consistent manner so that the research team are then only working with a fully pseudonymised dataset. Each individual in the cohort will have a fully linked record.

NHS digital will provide back linked data including hashed NHS Number and hashed DOB:
• Cancer Registration Data
• Secondary Uses Service Payment By Results Episodes
• Secondary Uses Service Payment By Results Outpatients
• Secondary Uses Service Payment By Results Accident & Emergency
• Secondary Uses Service Payment By Results Spells
• Mental Health Services Data Set
• Diagnostic Imaging Dataset
• Emergency Care Data Set (ECDS)
• COVID-19 Hospitalisation in England Surveillance System (CHESS) Dataset

• University of Oxford will store the data on the secure network.

• University of Oxford will process and aggregate pseudonymised data to produce approved reports for surveillance (as part of the National surveillance process); and quality improvement.

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

All record level data will be held and stored within England and Wales.

Detailed explanation of flows of data:

a) Data flow from RCGP RSC network member practices to University of Oxford: Wellbeing extract the data from the practices. Patients who have opted out of data sharing do not have their data extracted, unless they have consented to a specific surveillance programme or study. This extract provides the study with information about patient’s visits to general practices including the date of the appointment, the reason for the visit and any relevant vaccination information. The University of Oxford also receive patient’s NHS numbers and date of births which are pseudonymised using SHA-512 algorithm. Detailed information about this algorithm is held in a separate location by IT services at the University of Oxford. It is this department who will share the identifiers with NHS Digital for the linkage leaving the research team only access to the pseudo data.

b) University of Oxford Storage and processing of data: The data about patients registered with RCGP RSC general practices is stored on the secure server at the University of Oxford which can only be accessed from the University of Oxford. The data will be processed within secure network and dedicated analysis server of the Surveillance Group. The secure network is located behind a firewall within the University’s network, all in-bounded connections are blocked, but out-bounded connections are allowed. Patient level data are held in the database server within the RSC Group’s secure network.

c) Pseudonymised data will be stored on the database server within the RSC’s secure network once fully linked with the NHS digital returned data. The pseudonymisation algorithm is held in a separate location by IT services at the University of Oxford.

d) University of Oxford process and aggregate pseudonymised data to produce reports. For example, University of Oxford on behalf of RCGP RSC provide a mid-season flu cohort to PHE with data up to the end of December. This is a fully pseudonymised patient-level extract collected by a PHE statistician using a secure drive. The University of Oxford also produce an end of season report, an annual report and weekly reports that are available to the public and use aggregated data on rates of infectious and allergic conditions.

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

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

Only three SQL developers and one senior project manager can access the main database. Surveillance databases are created for approved analyses once they have been agreed by the RCGP RSC approval committee. This agreed protocol includes the list of variables required for the database. The SQL developers create separate databases for individual projects only including the required variables, for the required time interval.

There will be no requirement nor attempt to re-identify individuals from the data by the research team. The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.





MR1483 - HPS-4/TIMI 65/ORION-4: A double-blind randomized placebo-controlled trial assessing the effects of inclisiran on clinical outcomes among people with atherosclerotic cardiovascular disease. Application for data for invitation. — DARS-NIC-172240-R4R0L

Type of data: information not disclosed for TRE projects

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: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2018-10-01 — 2020-06-30 2018.10 — 2023.04.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. MRIS - List Cleaning Report
  2. Demographics
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Admitted Patient Care (HES APC)

Objectives:

The University of Oxford requires demographic, mortality and HES data to recruit participants into the ORION-4 study.

Investigators at The University of Oxford have instigated this work to achieve benefits for patients by obtaining reliable evidence about the safety and effectiveness of a new cholesterol lowering medication called Inclisiran. Inclisiran is given as an injection 2-3 times a year and reduces bad (LDL ) cholesterol. The ORION-4 study will find out whether inclisiran safely reduces heart attacks, strokes and cardiovascular deaths in people who already have cardiovascular disease. If shown to be effective, this treatment could substantially reduce premature death and disability from these conditions. A secondary objective is developing streamlined trial methods that would benefit future research.

The ORION-4 study is co-sponsored by The University of Oxford and The Medicines Company. The protocol and procedures have been developed by the Chief Investigator at the Clinical Trial Service Unit, University of Oxford in an academic collaboration with the TIMI Group - an academic research group within Harvard University - and The Medicines Company which comprise the Steering Committee for the trial. The Steering Committee would determine the scientific objectives of the trial, ensure adequate progress towards those objectives and review any papers prior to publication. As is usual with this type of trial, the Steering Committee also has other international experts from other institutions to advise the trial management team.

In respect of the data under this Agreement, the University of Oxford is the sole data controller. While the Steering Committee signs off the high level plan, the University has full autonomy to determine what personal data is obtained and how it will be processed. The University of Oxford would determine how, when and by whom personal data is processed and is responsible for the security of those data.

The data will be stored and processed at the University of Oxford. Patient’s NHS and Hospital Numbers may be shared with the NHS Trusts that treated them so that the Trust can confirm patient’s eligibility by checking local laboratory results for cholesterol levels. Other than sharing these data items with NHS Trusts, data supplied by NHS Digital would not be released to any other organisation or used for any other purpose. No Harvard University employees will have access to record level data under this Agreement. The Medicines Company will not access data under this Agreement.

The University of Oxford established the Clinical Trial Service Unit (CTSU), now within the Nuffield Department of Population Health, in the 1980s to conduct large trials such as the International Study of Infarct Survival (ISIS) trials. Since then CTSU has successfully completed a number of landmark studies including the 20,000 participant Heart Protection Study, the 9500 participant SHARP study, the 26,000 participant HPS-2/THRIVE study and the 30,000 participant HPS-3/REVEAL study.

The aim of processing the data is to recruit consenting participants for a randomized trial. At the beginning of the trial, half of the participants will be put in the group to be given active inclisiran and the other half will be put in the group to be given placebo injections. This will be done by chance, in a similar way to tossing a coin, called “randomization”. The participants will be followed to find out whether the active inclisiran group experienced fewer heart attacks, strokes and cardiovascular disease outcomes than the placebo group thereby demonstrating the effects of the treatments. The trial will also seek to establish whether the treatment is safe by looking to see whether the active inclisiran group evidenced increased risk of any other health conditions/outcomes.

The demographic (including name, address and GP practice details), mortality and HES data are required to assist the University of Oxford in identifying and recruiting eligible participants. Potentially eligible participants will be invited on behalf of the Local Investigator using local NHS headed paper to attend a Screening Appointment at the ORION-4 clinic (usually in their local NHS Hospital). If they choose to attend, they will be invited to consent to participate in the clinical trial.

For those who provide informed consent, the University of Oxford will apply to NHS Digital for subsequent follow up data under a separate Data Sharing Agreement.

Yielded Benefits:

By 2020, the trial has established around 100 research sites across the UK and recruitment is progressing well. Because of the requirement of the trial to include people with higher cholesterol values a substantial proportion of people volunteering are not able to take part which has meant that recruitment has been slower than expected. However, because of the large-scale central invitation process using the data requested in this application, additional patients can be invited without substantial extra cost.

Expected Benefits:

The results of ORION-4 will be relevant to the 7 million people living with cardiovascular disease in the UK and many more around the world. Bad (LDL) cholesterol is a strong reversible risk factor for cardiovascular disease. Evidence from large, randomized trials have lead to the widespread use of statins in individuals with and at risk of vascular disease which has resulted in substantial benefits for patients. Recent research suggests that further lowering of bad (LDL) cholesterol results in additional reductions in the risk of heart attacks, strokes and death from cardiovascular disease. Inclisiran is a new medication which reduces LDL cholesterol by about half. If shown to be safe and effective and made widely available to high risk individuals, treatment with inclisiran might be expected to prevent a substantial proportion of the 0.5M heart attacks, 0.25M strokes and 0.15M deaths from cardiovascular disease which occur each year in the UK.

It is expected that the results of ORION-4 in 2025 will be incorporated into National and International Guidelines for the treatment and prevention of cardiovascular disease, including guidelines from the National Institute for Health and Care Excellence (NICE) and The Scottish Intercollegiate Guidelines Network (SIGN). Inclisiran is given by injection every 6 months and reduces bad (LDL) cholesterol by about half when given either alone or with statins. Other drugs which work in a similar way to inclisiran are available, but require 4 weekly injections and are expensive to produce. As a result they are not widely available for patients in the UK. Since inclisiran requires an injection only every 6 months and has lower production costs, it is likely that it will become available to patients if proved to be safe and effective in reducing the risk of heart attacks and strokes. Furthermore this treatment may overcome problems with medication adherence which are particularly problematic for long term preventative medicines. Therefore the results of ORION-4 are likely to change clinical practice in the prevention of cardiovascular disease both in the UK and around the world and would be expected to have a substantial impact on the numbers of heart attacks, strokes and deaths from cardiovascular disease globally.

The data from NHS Digital is extremely beneficial in recruiting the large numbers of participants needed for the success of this study. At CTSU large efficient trials have been conducted which produce reliable answers by recruiting large numbers of participants. Both the THRIVE and REVEAL trials each randomized over 8,000 patients in the UK using methods similar to those proposed for ORION-4 although in those studies patients' details were obtained direct from NHS Hospital Trusts rather than from NHS Digital. Many people invited to take part in research choose not to for a variety of reasons, therefore it is necessary to send very large numbers of invitations to successfully recruit to a large study like ORION-4. In REVEAL around 300,000 invitations were required to randomize about 8,000 people into the study. For ORION-4 it is expected that between 400,000 and 500,000 invitation letters would need to be sent to achieve the recruitment target. It would be considerably more difficult to achieve this without the data requested from NHS Digital.

Beyond the ORION-4 study, the recruitment methods using data from NHS Digital would inform trial design and produce benefits to future research. To reliably assess the effects of treatment it is necessary to randomize a large enough numbers of participants to avoid getting the wrong answer by chance and many randomized trials are too small to answer the research question reliably. Recruiting large numbers of participants is difficult and can be prohibitively expensive and many trials fail to reach their recruitment target. Cost-effective, streamlined methods of trial recruitment are needed to improve health by obtaining reliable knowledge about which treatments work and which are harmful. Using NHS Digital data to mail invitation letters to large numbers of potentially eligible people will provide just such a method to ensure the success of this trial and the methods developed would benefit future studies. CTSU is committed to developing streamlined methods of conducting randomized trials so that more trials can produce reliable answers. Members of the ORION-4 team are working with organisations such as the Clinical Trials Transformation Initiative (CTTi), a public-private partnership to develop practices aiming to increase quality and efficiency of clinical trials. Learning from the recruitment methods developed in ORION-4 will be shared by publications in open-access, peer reviewed journals, by courses run by CTSU and shared with other researchers using initiatives such as the CTTi.

Outputs:

The main trial results of ORION-4 are expected in 2025 and will inform the treatment of people living with cardiovascular disease around the world. The results will be disseminated widely, including presentation at relevant conferences and publication in an open-access, high-impact medical journal. Further academic papers (including results of cost-effectiveness analysis and papers about the trial methods) will be published in open-access, high impact, peer-reviewed journals and on the trial website. After the close of the study, additional results assessing the long-term effects of inclisiran obtained through data linkage or participant questionnaires will be published.

A non-technical summary of the main study findings will be sent to participants and relevant charities, such as the British Heart Foundation and Heart-UK, and published on the study website. For each paper a short presentation will be developed to summarise the key findings which will be presented at key conferences.

This study will use streamlined recruitment methods to identify and recruit 15,000 eligible participants cost-effectively. The United Kingdom will recruit around 12,000 participants and the United States of America will recruit the remaining 3000 participants. Recruiting such large numbers in the UK has a number of potential advantages including; enhanced efficiency and lower cost and enabling record linkage for important outcomes both during the scheduled treatment period and after the close of the trial, along with benefits to future UK research. The data requested in this application will be used to identify and recruit most of the 12,000 eligible UK participants by the end of 2019.

From experience with previous trials it is anticipated that between 20 and 30 people will need to be invited for each participant randomized into the study and therefore obtaining large numbers of potentially eligible participants is critical to successful recruitment. In previous studies lists of such individuals have been obtained from individual NHS Trusts, with Section 251 support. Obtaining the list of potentially eligible individuals from NHS Digital leads to the following benefits for the study; First, any delay in obtaining the data while waiting for local data analyst time and technical difficulties associated with dealing with different dataset formats from different NHS trusts would be avoided. Second, the risk of sending the invitation to the wrong address would be reduced. If data is sought directly from the NHS Trust and the patient has moved since they last visited that secondary care provider, then the address for invitation would be out of date. Thirdly, obtaining data directly from NHS Digital allows individual preferences about opt-outs to use of their data be upheld.

Obtaining GP practice information for each potentially eligible participant will help to ensure that correspondence is sent to the correct GP practice. Once a participant has been screened and provided consent, a standard ethics approved letter containing details of the trial and the individual’s current cholesterol lowering treatment, and highlighting the guideline recommended treatment for such patients, will be sent to their GP. The GP is asked to do two things before the randomization appointment 2 months later; (i) review the individual’s cholesterol lowering treatment and (ii) inform the trial coordinating centre if they have concerns about that participant entering the trial. It is therefore very important that letters go to the right practice. Previously, clinical trials have relied on patients to provide their GP details with subsequent checking by the coordinating centre. This is time-consuming and can lead to errors and it will be more efficient and accurate to use up-to-date GP information through NHS Digital’s List Cleaning service.

The List Cleaning outputs will reduce the risk of attempting to contact recently deceased individuals and potentially causing distress to living relatives. Furthermore the regular list cleaning will help to ensure that addresses are accurate. If the invitation were sent to the wrong address opened and the Participant Information Leaflet read carefully it would be possible to infer that the invited individual had vascular disease. Although the risk of this happening is low, it is important to minimise this risk by undertaking regular list cleaning.

Once recruitment is complete, reports will be generated using these data in order to describe the recruitment procedures for the trial (for example establishing the number of individuals invited to participate by age and sex). Such reports will not contain any identifying information (including small groups which could potentially be identified) and will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide. This will be undertaken as soon as possible after the end of the recruitment period in 2020 and before the analysis of the main study results is complete in 2025.

Processing:

The University of Oxford will establish ORION-4 sites (generally in NHS Trusts which treated high numbers of individuals for heart attacks, strokes or cardiovascular conditions). Once a local NHS Trust has completed the study feasibility assessment, the University of Oxford will inform NHS Digital that that NHS Trust is now a confirmed site.

Using a combination of the Hospital Episodes Statistics (HES) and Personal Demographics Service (PDS) databases, NHS Digital will extract the details of patients aged 55 and over for whom a previous hospital episode with an ICD 10 code or other diagnostic code indicating eligibility for the trial has been recorded by one or more of those NHS Trusts. Patients who are deceased or who are not current registered with an NHS GP would be excluded.

NHS Digital will provide to the University of Oxford a file containing the following data items for potentially eligible participants:
• Name
• Latest address and postcode
• Date of Birth
• Sex
• ICD 10 or other diagnostic or procedure codes to indicate eligibility
• NHS Trust
• NHS Number
• Hospital Number
• GP practice code
• Admission date of most recent episode with an ICD 10 code or other diagnostic code meeting the inclusion criteria

The University of Oxford will undertake further work to ascertain eligibility. This may include sending a list of NHS and Hospital Numbers securely to the local NHS Trust so that they can undertake further eligibility checks based on the blood cholesterol levels as recorded in the Trust laboratory system.

During the study recruitment period, the University of Oxford will regularly submit batched lists of potentially eligible individuals back to NHS Digital who will provide a ‘List Cleaning’ service and report back the individuals’ current vital status, current address and current GP practice code. This information is required to minimise the risk of writing to recently deceased individuals or writing to incorrect addresses. The GP practice code is required so that a letter can be sent to the GP immediately after a participant’s screening appointment in order to inform the GP of the participants planned enrolment into the trial and allow the GP to opt that participant out of randomization if they feel appropriate.

The University of Oxford will write to the potential participants identified in the List Cleaning reports inviting them to an ORION-4 Screening Appointment at the ORION-4 clinic within the relevant NHS Trust. Should they choose to attend, at the appointment they will be invited to participate in the trial and give informed consent if they wish.

The data received from NHS Digital will only be accessed by individuals within the Clinical Trial Service Unit who have authorisation to access the data for the purpose(s) described, all of whom are substantive employees of the University of Oxford. The potential exception to this is that NHS and Hospital Numbers may be shared with the NHS Trusts that have previously treated the potential participants. This would not involve giving those NHS Trusts new information about the participants, since they recorded the data in the first place. It would simply be a practical step to enable the Trusts to identify the individuals in their own patient records in order to undertake a further eligibility check based on local laboratory blood cholesterol results.

After invitation, individuals who have not responded will be considered to have declined to participate. These individuals will not be invited again.

Data about those participants who declined to participate, or have been considered to have declined to participate through non-response, will be held initially in order to avoid inviting those individuals again. Once recruitment is complete, reports will be generated using these data in order to describe the recruitment procedures for the trial (for example establishing the number of individuals invited to participate by age and sex). Such reports will not contain any identifying information (including small groups which could potentially be identified). Once these reports have been completed, the data provided by NHS Digital for those individuals will be irrevocably deleted. This will be undertaken as soon as possible after the end of the recruitment period in 2020 and before the analysis of the main study results is complete in 2025.

The data provided under this Agreement will only be used for the purposes of recruitment and recruitment analysis and will not be used for any subsequent purposes within the clinical trial.


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

Type of data: information not disclosed for TRE projects

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: No (Academic)

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

When:DSA runs 2019-11-02 — 2020-10-31 2017.12 — 2023.04.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Office for National Statistics Mortality Data
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Critical Care
  5. Hospital Episode Statistics Outpatients
  6. Bridge file: Hospital Episode Statistics to Mortality Data from the Office of National Statistics
  7. MRIS - List Cleaning Report
  8. HES:Civil Registration (Deaths) bridge
  9. Civil Registration - Deaths
  10. Emergency Care Data Set (ECDS)
  11. Civil Registration (Deaths) - Secondary Care Cut
  12. Civil Registrations of Death - Secondary Care Cut
  13. Hospital Episode Statistics Accident and Emergency (HES A and E)
  14. Hospital Episode Statistics Admitted Patient Care (HES APC)
  15. Hospital Episode Statistics Critical Care (HES Critical Care)
  16. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The University of Oxford require a list cleaning to take place first following approval. Then there would be a period of time to allow for any participant withdrawals before Oxford supplied the cohort to NHSD for linkage. The purpose of the list clean is to notify the study of any cohort members that have died. Confirmation of deceased cohort members will allow the study not to cause further distress by sending newsletters to the families of the deceased.

Coronary artery bypass graft surgery (CABG) continues to be the optimum revascularisation strategy for most patients with multi-vessel coronary artery disease. Although the biological variability between patients should be crucial for the prediction of long-term outcome of patients undergoing cardiac surgery, the exact mechanism linking the biology of the heart, the vascular grafts used and the myocardium with clinical outcome are unclear.

To address this shortfall in literature evidence, this study is aimed at assessing the venous and arterial redox states of patients undergoing CABG and valve repair/replacement surgery, in addition to data related to myocardial redox state, general biochemistry and imaging.

The cohort includes patients from 3 studies
1) the Arterial Revascularisation Trial (ART) (November 2004 to current; REC: MREC04/03/006) aimed at comparing survival following bilateral versus single internal mammary grafting in coronary revascularisation

2) the Bypass Vascular study (January 2005 to current; REC: 04/Q1605/95 ) aiming among others to compare in vivo measures of vascular function with post-operative clinical outcome after cardiac surgery

3) the AdipoRedOx study (15/09/2011 to current; REC: 11/SC/140), aiming to investigate the role of the interactions between adipose tissue and cardiovascular oxidative stress, in the prediction of post-operative outcome of patients undergoing cardiac surgery.

Each study has gained informed consent from participants to access their medical records to collect post-operative information that may have a predictive value after cardiac surgery.

Importantly, these studies aim to link the collected data (i.e. risk factors, data on vascular function etc.) with patient clinical outcome data, producing the world’s most comprehensive resource comparing vascular biology with clinical outcome post-cardiac surgery.

The primary objectives of the study are to -

Investigate the mechanisms by which adiponectin affects
vascular/myocardial redox state, endothelial function and clinical outcome
of patients undergoing coronary artery bypass grafting operation (CABG).

Secondary objectives are to-

1) Search for a possible signal from the myocardium/vascular wall to
epicardial/perivascular adipose tissue, that regulates the synthesis of
adipokines and other signalling molecules
2) Search for novel biomarkers/signalling molecules identified in
peripheral blood or expressed in adipose tissue, that regulate
vascular/myocardial redox state and/or predict vein graft patency

In summary these objective will then potentially results in the creation of patient risk models with which to improve health outcomes.

The first step in achieving these objectives will be to provide further fair processing information to the participants via a newsletter. This will be followed by linkage to HES and ONS mortality data.

Yielded Benefits:

Recent data have shown that treatment of patients with diabetes with insulin, may lead to significant damage of the heart arteries if the treatment is not accompanied by a drug called insulin sensitizer. This could lead to major changes in the treatment of these patients globally (https://inews.co.uk/news/health/diabetes-drug-prevent-heart-attacks-strokes). The University of Oxford team have previously shown that obesity may not be necessarily bad, and those patients with high body mass index may be “protected against cardiovascular mortality” because fat in the body may secrete protective substances. This is called obesity paradox and has major implications for the treatment of patients with heart diseases (Diabetes 2015, link to press coverage about the obesity paradox: https://www.telegraph.co.uk/news/science/science-news/11657811/Why-obesity-protects-against-heart-disease-and-heart-attack.html). The University of Oxford has recently identified a major therapeutic target for the treatment of heart diseases, and that discovery led to intense research to develop new drugs to modify this target (presented in the last European Society of Cardiology 2018 Congress, and received the Best Poster Award). The University of Oxford has recently develop a method to detect patients at risk for future heart attacks using the ox-HVF cohort (Science Transl Med 2017), which was validated in a recent publication (Lancet 2018). This method has been included into the recent Up-To-Date guidance (https://www.uptodate.com/contents/cardiac-imaging-with-computed-tomography-and-magnetic-resonance-in-the-adult) and can be used to detect patients who may need intense medical therapy to prevent future heart attacks. The University of Oxford group has developed a novel imaging biomarker (see Antonopoulos et al Science Translational Medicine 2017), namely the Fat Attenuation Index (FAI), which has been shown to be a marker of vascular inflammation at early disease stages. Validation of this biomarker in large cohorts of patients with residual cardiovascular risk showed that FAI is able to detect patients at high risk for cardiac mortality and is also predictive of non-fatal heart attacks. This permits reclassification of an individual’s risk, above and beyond the current state-of-the-art diagnostic tools, with strong implications for guiding medical management in patients and guiding the use of primary and secondary prevention measures. The development of this technology is a significant example that highlights the strength and unique ability of the Ox-HVF cohort in combining data across different and diverse fields - from clinical and epidemiological data to basic science and imaging data to outcome data (requested in the current application)- to create new, boundary-pushing ideas that promote health and serve the public interest. Of note, FAI was featured by iNews as one of the ten health innovations that could soon be on the NHS (https://inews.co.uk/news/health/the-ten-health-innovations-that-could-soon-be-on-the-nhs/). The University of Oxford has found that insulin treatment in diabetic people should be accompanied by medication targeting a specific molecule, which is regarded to be able to sensitize the human vessels to insulin signalling, in order to avoid damage to the heart arteries. Furthermore, they have shown that a molecule secreted from fat surrounding the human vessels, can trigger the development of damage and inflammation to them and therefore could constitute a promising therapeutic target.

Expected Benefits:


In summary, this data will be used to characterize the predictors of clinical outcome post cardiac surgery. This will allow for the identification of patients at risk and take measures to improve clinical outcome (survival and hospitalization rates) in this population.

The outputs of this research will be published in high impact peer review journals and will be presented in scientific congresses.

Due to the unique baseline phenotyping of these patients, the tested set of predictors for clinical outcome post cardiac surgery will provide a unique opportunity to understand the mechanisms affecting morbidity and mortality of these patients, and will lead to the development of novel therapeutic strategies to improve health care in this population.

Benefits:
1. The potential design of risk stratification models in primary and secondary prevention to improve clinical outcome at population level in cardiovascular disease
2. Identify high risk features that enable aggressive therapeutic strategies in high risk populations that can be implemented in to clinical practice.
3. Identify potential novel therapeutic targets involved in cardiovascular disease progression which will lead to future drug discovery.


Outputs:

The initial output will be a list of surviving cohort members which will be used to write out to participants with fair processing information and the opportunity to withdraw from the study. The list cleaning will help to ensure material is sent to only cohort members who are alive thus reducing the risk of causing emotional distress to family members of deceased participants. The study will then supply NHS Digital with a 'cleaned' version of the cohort for linkage.

The research outputs will include peer reviewed publications in leading international journals, presentations in scientific meetings and possible media reports.

Access to the data provided will be given only to the study investigators, within the University of Oxford, and no third parties will have access to this information. The study outputs will include publications in peer reviewed journals, presentations in international and national congresses.

The data will be used for research only and not be used to create indicators showing the performance of any organization.

All outputs will only contain aggregated data with small numbers suppressed in adherence to the HES analysis guide.

Outputs are expected 6-12 months after the data is received.

In summary:
Journals being targeted to submit to/publish in:
• The New England Journal of Medicine,
• The Journal of the American Medical Association,
• The Lancet,
• Circulation,
• Journal of the American College of Cardiology or The British Medical Journal.
Congresses targeted to submit to:
• Scientific sessions of the American Heart Association
• Scientific sessions of the European Society of Cardiology
• Scientific sessions of the American College of Cardiology
• Scientific sessions of the British Cardiac Society

Processing:


The data needed from NHS Digital are:

a) Fact of death data via list cleaning - this will be used to send an update to participants describing how data will be linked and providing withdrawal instructions.

b) The mortality data (including cause of death) from the day of surgery (provided) until today. Oxford will provide a list of NHS numbers so the mortality data returned should include the cause of death and the date of death for each individual patient

c) Similarly, hospitalization/admissions (that should include reason for hospital admission and the date, for each individual patient in the cohort).

Collection of this data is vital to obtaining the primary endpoint statistics linking the existing study data with post-surgery clinical outcome.

Only the named study investigators will have access to the record-level data, which will be stored securely in swipe-card-secured premises in the University of Oxford, in a password protected computer. No record-level data is being provided to a 3rd party and only aggregated data will be publicised/provided to 3rd parties.

The University will directly send NHS Digital a list of NHS numbers on the NHS Digital transferring system. An internal study number will identify subjects, and study details will not contain personal data such as names, NHS numbers or date of birth. The personal data that applies to a particular number would be kept locked separately away in the Division of Cardiovascular Medicine at the John Radcliffe Hospital.

The linking database will be kept on a high security password protected computer (to which only the study investigators will have access). Furthermore, the database computer will be kept in a swipe card-secured area of the Department (only authorized individuals have access to this area, and it is carefully controlled).

If applicable, information stored on laptop computers of the study investigators will contain additional password protection pertaining to relevant documents; this will be in addition to all computers being password protected. All data will not contain subject-identifiable material, and will be stored in a linked de-identified form.

The Investigators will be involved in reviewing drafts of the manuscripts, abstracts, press releases and any other publications arising from the study. No third parties will have access to the information as all analyses will be carried out within the University of Oxford, and no third organization will be involved.

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

The applicant agrees to adhere to the Office for National Statistics terms and conditions as described in this agreement.

The data will only be used for the purposes described in this agreement.

No data will shared with 3rd parties.

No data will be used for commercial purposes.


OPtimising Treatment for Mild Systolic hypertension in the Elderly: a randomised controlled trial (OPTiMISE) — DARS-NIC-459340-M8R2R

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, No (Consent (Reasonable Expectation))

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-07-01 — 2025-06-30 2023.02 — 2023.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

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

Yielded Benefits:

This is a new data request, so no benefits have yet been yielded.

Outputs:

All findings from the proposed research are intended to be published in peer-reviewed journals under an open-access license, with target journals including the British Medical Journal (BMJ), Journal of the American Medical Association (JAMA) Internal Medicine and Hypertension. Only aggregated data with small numbers suppressed in line with the HES Analysis Guide will be presented in published outputs. It is anticipated that the study findings will support better patient-centred management plans for the prevention of cardiovascular disease in older individuals and therefore will be available for the next iterations of the NICE hypertension and multi-morbidity guidelines.

The University of Oxford intend to present results at national scientific meetings (e.g. of the British and Irish Hypertension Society, Society for Academic Primary care, British Geriatrics Society) and international conferences (e.g., for the European Society of Cardiology, North American Primary Care Research Group). The University of Oxford will publish a summary of our findings on the study website (https://www.phctrials.ox.ac.uk/studies/optimise) and submit a final study report to the MHRA and ethics committee who provided approval for the study. Where appropriate, we will press release the results of the research in conjunction with their publication in scientific journals, and fully engage with any arising media inquiries that result. Social media (e.g. Twitter) will be used to draw attention to the work and stimulate debate, particularly when it is presented at conferences or published in the lay and scientific media.

Multiple channels of communication will be used to disseminate study findings including written feedback to study participants, plain English summaries, newsletters and community engagement events. We will work closely with our PPI representatives to ensure results are presented and disseminated in a patient friendly manner. An article discussing the issues raised by the research will be written for ‘The Conversation’, an online newspaper written by academics which is free and easy to read for the general public.

The University of Oxford will aim to present the findings of their analyses using these data at conferences in late 2022 and throughout 2023 and publish the final results in publications and online in early 2023.

Processing:

1. Participants who have consented to the OPTiMISE trial will have their data initially linked with the primary care data which is already held as part of ORCHID.
2. The University of Oxford will provide NHS Digital with a list of NHS numbers and date of births along with a unique Study ID for the OPTiMISE cohort.
3. A specific member of the University of Oxford IT team within the IT department will share the identifiers with NHS Digital, not the research team.
4. NHS Digital will send back to University of Oxford the pseudonymised, record level cohort data with Hospital Episode Statistics (HES), Admitted Patient Care (APC) and Accident & Emergency (A&E) data, Emergency Care Dataset (ECDS) data and mortality data included. Files will be sent securely back to University of Oxford via the Secure Electronic File Transfer System (SEFT).
5. University of Oxford will download and store the data within their secure ORCHID trusted research environment.
6. University of Oxford will process the pseudonymised data to meet the aims and objectives of the study (as detailed in ‘Objectives for Processing’). This will include matching the pseudonymised data from NHS Digital with the pseudonymised study data using the unique study ID. There will be no subsequent flows of data from the University of Oxford which has not already been suppressed in accordance with the small number suppression rules in the HES Analysis Guide.

Once data have been provided by NHS Digital, the University of Oxford will have no need to re-identify participants for the purpose of data processing. All patient identifiers are stored (securely and) separately from the main study database. Patient identifiers will be permanently destroyed at the earliest opportunity, in line with ethical and GDPR requirements and University policy.

The data will be controlled and processed by a group of substantive staff who are all based at the University of Oxford and under an employment contract. All staff are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Query Language (SQL) developers, Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) practice liaison officers, a project manager and a head of department. All staff will access NHS Digital data from secure workstations or secure laptops with encrypted drives within the group’s secure network. No data will be accessed outside of the location where the data is stored.

Analysis will be done by the clinical trials unit within the Nuffield department of Primary Care Health Sciences at the University of Oxford.


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

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-10-01 — 2024-09-30 2022.02 — 2023.01.

Access method: One-Off

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. HES:Civil Registration (Deaths) bridge
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Outpatients
  5. Civil Registrations of Death - Secondary Care Cut
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)
  7. Hospital Episode Statistics Outpatients (HES OP)

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.


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

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2021-05-13 — 2024-05-12 2022.11 — 2022.11.

Access method: Ongoing

Data-controller type: UNIVERSITY OF OXFORD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)

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 D