NHS Digital Data Release Register - reformatted

University Of Nottingham projects

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

🚩 University Of Nottingham was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. University Of Nottingham 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.

The clinical and cost-effectiveness of testing for Group B Streptococcus: a cluster randomised trial with economic and acceptability evaluations (GBS3) — DARS-NIC-309246-L8C4C

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); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2024-02-05 — 2027-02-04 breached contract (and anonymisation code) — audit report.

Access method: One-Off

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

  1. Civil Registrations of Death - Secondary Care Cut
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Admitted Patient Care (HES APC)
  4. Hospital Episode Statistics Critical Care (HES Critical Care)
  5. Hospital Episode Statistics Outpatients (HES OP)
  6. Maternity Services Data Set (MSDS) v2

Expected Benefits:

It is envisaged that the results of this trial will provide the UK National Screening Committee (NSC) with the evidence required to decide whether routine GBS testing should be implemented in the UK, addressing criteria 11 and 14 of the NSC’s screening requirements – listed here https://legacyscreening.phe.org.uk/screening-recommendations.php. The results are therefore expected to lead directly to policy decisions around routine testing for the detection of Group B Streptococcus, that will see more immediate patient benefit by identifying high-risk women and supporting the optimization of antenatal care to prevent and reduce the onset of sepsis in new-borns. Should GBS screening prove to be clinically and cost effective, the results will also provide useful data on the acceptability, coverage, cost and impact on health care services of antenatal enriched culture versus intrapartum rapid testing within a UK setting. This will be the first adequately powered RCT of GBS screening in the world and its results may well impact global practice in those countries who have adopted GBS screening without such evidence for its effectiveness.

Further, GBSS and the National Childbirth Trust will use their extensive network of social and mainstream media connections to disseminate these results, in order to increase acceptability and coverage, extremely important for the implementation of new policies to improve the healthcare service, and therefore in the public interest.

All pregnant women in the UK are expected to benefit by receiving an optimal management strategy that provides appropriate, targeted and only necessary treatment for GBS infections. Only women at high risk of passing the infection to their new-born will be treated to decrease the risk for their baby while women who resulted negative to the GBS test will not need to receive antibiotics reducing their risk of intrapartum anaphylaxis due to the treatment. That in turn is also expected to benefit their offspring who will be at a decreased risk of developing early and late onset infections and will not receive unnecessary treatment if their mothers were not at high risk of GBS.

Results from this trial are expected to inform the decision as to whether to change the current clinical practice in the UK with consequent benefit for the whole population. The results of this trial will provide the UK NSC with the evidence required to decide whether routine GBS testing should be implemented in the UK.

The NSC will schedule their next review of their policy to include the results of this trial, available in 2024.

Processing:

The University of Nottingham will provide a number of codes to NHS England, one for each of the NHS English sites that are taking part in the trial and two dates attached to each code which represent the start and end date of data collection.

NHS England Data will provide the relevant records from the MSDS, HES, mortality and ECDS datasets to the University of Nottingham. The Data will:
• contain directly identifying data items including NHS number, Date of Birth and postcode which are required to link the data at record level with data already held by the University of Nottingham.

The research team will then link the NHS England dataset to the rest of the datasets needed in the project using the three identifiers:

(For England):
1. National Neonatal Research (NNRD),
2. Paediatric Intensive Care Audit Network (PicaNet),
3. BadgerNet Neonatal and Maternity,
4. UK Health Security Agency (UKHSA) laboratory test data.

Linkage of the NHS England Data for England with the above datasets occurs within the TRE. NHS England raw data will never leave the TRE.

Once the linkage has been completed, the data will be pseudonymised by the HIC TRE team. The personal identifiers will be kept, however they will be separated from the main data and securely stored in a separate TRE environment as a backup, only accessible by the approved managers based at Nottingham Clinical Trial Unit (NCTU), University of Nottingham. Data will be stored in electronic format and all files, folders and back up files will be securely destroyed at the end of the retention period with the use of an appropriate software.

Other data analysed but not linked to the NHS England Data include:

For Wales:
• NHS Wales Informatics Service maternity, hospital and mortality data
• Health Protection Wales laboratory test data

The research team will also link a subset of the NHS England to three small datasets that have been created by manually collecting data in the trial sites to conduct three different studies: maternal anaphylaxis (a severe reaction to a trigger such as an allergy) outcome assessment, process outcomes assessment and accuracy of routine data to select cases of new born sepsis assessment. The identifiers will be then removed from the analysis dataset and stored in a safe place within the TRE, not accessible by the analysts. The final pseudonymised dataset will be then created for the trial and economic analyses.

The Data will be stored on the TRE at the University of Dundee.

The analysists/statisticians from University of Nottingham and from the University of Oxford will be able to safely access the Data stored at the HIC TRE to conduct the analysis.

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

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

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

The Data will not leave the UK at any time.

Access is restricted to substantive employees of the University of Nottingham, University of Dundee and the University of Oxford.

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

The outcomes of the subset cohort (100 women per site) detailed in section 5a will be linked to the NHS England routine data to be able to conduct the analysis.

Another study will be conducted using hospital notes extracted from the trial sites (not from NHS England routine data), whereby a central new-born baby adjudication will be conducted on a sample of clinical suspected sepsis cases to assess the robustness and accuracy of the algorithm developed to extract the primary outcome from routine data. Within this study, a list of new-borns identified by a panel of neonatologists, who diagnose and treat new-borns, assessing hospital notes will be linked to the NHS England routine data for validation purposes.

The raw routine data received from each data provider will not reach the Nottingham Clinical Trial Unit (NCTU). However, all research data collected manually and stored at NCTU will be encrypted and sent to Dundee TRE to be ‘merged’ with the routine data to create the full final datasets.

Identifiers will be stored in a separate protected folder within the TRE for the length of the Trial. However, at the end of the trial, the final datasets for the analysis and the identifiers will be sent to the NCTU and safely retained for 7 years as per the university policy. Clinical trial data as per the clinical trials regulations should be kept for a minimum of 5 years for an IMP trial. The university policy is 7 years from the date of first publication.

Where data has been pseudonymised, no attempt will be made by any organisation party to this Agreement to re-identify individuals included in the study population.

Access to identifiable data will be restricted only to the senior research fellow, data manager and IT support team to carry out the pseudonymisation and linkage of the datasets within the University of Dundee’s TRE. The statisticians will carry out the final analysis using only pseudonymised datasets.

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

The 3rd Sprint National Anaesthesia Project (SNAP 3) — DARS-NIC-438551-P4C0G

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2023-07-01 — 2026-06-30 2024.03 — 2024.09. breached contract (and anonymisation code) — audit report.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

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

Objectives:

The University of Nottingham requires access to NHS England data for the purpose of the following research project: The 3rd Sprint National Anaesthesia Project (SNAP 3).

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

“The Sprint National Anaesthesia Projects (SNAPs) examine commonly occurring events related to anaesthesia and surgery which affect a large number of patients. Each SNAP is conducted within a short data collection window of a few days at most, though their planning and analysis take much longer. Two SNAPs have been completed to date, with this the third SNAP underway.

SNAP1 focused on Patient-reported outcomes after anaesthesia and was a research project which involved a two-day evaluation of patient-reported outcomes after anaesthesia. SNAP2 focused on the Epidemiology of Critical Care Services after Surgery.

The 3rd Sprint National Anaesthesia Project (SNAP 3) is an observational cohort study that aims to describe the impact of frailty and delirium whilst finding associations between frailty, comorbidity, multimorbidity, and delirium and their management, with outcomes following surgery in older people. In common with SNAP 1 and SNAP 2 it will consist of a short period of data collection from potentially every eligible patient having surgery in a defined period. It is estimated that approximately 6,500 individuals will take part.”

The following NHS England data will be accessed:

• Hospital Episode Statistics (HES) Admitted Patient Care (APC) – The SNAP 3 records relate only to an individual admission, and by linking to inpatient HES data, the study will be able to provide more precise and relevant information to NHS hospitals by allowing the research team to describe longer-term outcomes (e.g., readmission rates) and to improve the SNAP 3 team's understanding of risk attributed to frailty, multimorbidity, and delirium.

• Civil Registration Mortality – The SNAP 3 Team also wishes to link the cohort of patients with mortality data, this will enable the study to detect the consequences of both short and longer-term mortality for those patients. Access to this linked information will support this national research project to improve the quality of care within NHS hospitals for a high-risk patient group.

The level of data will be identifiable, necessary because although the University of Nottingham will receive pseudonymised data (along with their study ID) from NHS England, the University of Nottingham hold the cohort identifiers.

The data will be minimised as follows:

• Limited to a study cohort identified by the University of Nottingham – The SNAP 3 Team will send the NHS number, postcode, date of birth, gender, and unique study identifier of the participants in the cohort to NHS England, the cohort consists of patients 60 years+ and having a surgical procedure during a 5 day recruitment period. The recruitment window was limited to 5 days per site, however, the overall study recruitment window spanned almost 2 months. This was done to allow some sites that were unable to facilitate the study on the specific week in March due to local staffing and logistics, to still contribute to the study.
Recruitment window
(England) 21/3/2022 - 6/5/2022
(Wales) 21/3/2022 - 13/5/2022

The participant cohort will remain the same for the entire project, any participants that withdraw their consent will be removed from the original cohort by the University of Nottingham.

• Limited to data 12 months prior to recruitment and 4 months after recruitment for HES APC and Mortality data for the first year and second year after recruitment.

The University of Nottingham is the controller, as the organisation responsible for ensuring that the data will only be processed for the purpose described above. The SNAP 3 Team seeks guidance from a clinical reference group made up of representatives from key stakeholders (see below). Neither these individuals nor their organisations have access to SNAP 3 data or NHS England data.

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

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

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

The funding is provided by the Royal College of Anaesthetists and the Frances and Augustus Newman Foundation. The funding is specifically for the project described.

Funding to continue the work described will be sought on an ongoing basis.

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

The following organisations are involved in the SNAP 3 project as co-investigators but will not access the data and they do not determine the purposes and means of the processing of personal data under this agreement:
Guys and St Thomas’s Hospital London
Royal Devon and Exeter Hospital NHS Trust
University of Oxford and Oxford University Hospitals NHS Trust
A senior clinical fellow in Australia
University College London

Data will be accessed by a PhD student affiliated with the University of Nottingham. The individual has completed mandatory data protection and confidentiality training and is subject to the University of Nottingham’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 Nottingham. The University of Nottingham 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 Involvement and Engagement (PPIE) group helped refine the purpose of the research. The group supported the collection of the data for the purposes described above.

PPIE has been and will continue to be embedded within the project. The study budget includes appropriate funding for PPIE activity in accordance with NIHR Centre for Engagement and Dissemination guidance (2021).
The study topic itself was chosen by a panel including members of the Patient, Carer and Public Involvement and Engagement Committee at the Royal College of Anaesthetists panel.

PPI work has been completed prior to this study looking at consent processes.

Participant/consultee information sheets have been co-produced with PPI representatives.

Two PPIE representatives are full members of the study steering committee and the study management group. Committee chairs will be briefed to ensure that PPIE voices are welcomed and heard at all times.

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 practices 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 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.
• advance understanding of the need for, or effectiveness of, preventative health and care measures for particular populations or conditions.
• 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.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

Understanding how current clinical practice influences the outcomes of older surgical patients is crucial to improving the design and funding of these complex, multi-specialty pathways. At present the services available to older surgical patients are hugely variable, with different structures, personnel, and resources available. SNAP 3 may determine which elements of perioperative care are essential to the effective management of older patients and ensure that these findings are disseminated at the trust and NHS level. The implementation of alterations to the perioperative medicine services will be measured by repeating an organisational survey which initially was conducted in October 2021. The use of data from the survey’s before and after picture may demonstrate the influence of SNAP 3’s recommendations. The efficacy of these interventions are more complex to measure. Ongoing projects such as the National Emergency Laparotomy Audit (NELA) and the Perioperative Quality Improvement Programme (PQIP) will track outcomes for older surgical patients with frailty and multimorbidity, allowing the detection of the efficacy of new interventions.

In high-risk surgery, such as trauma and cardiac surgery, 36-40% of adult patients develop postoperative delirium, whereas in lower-risk surgery, such as elective arthroplasty, the prevalence of delirium is 5-10%. At present there is no commonly used delirium risk prediction tool which is applicable across all surgical specialties. The production of a risk prediction tool for postoperative delirium may provide an opportunity to screen patients and direct preventative measures toward those at greatest risk of this common complication. Delirium is commonly preventable and is a reversible condition in approximately 40% of cases. Identifying those at risk may have positive effects on patients and healthcare services eg. reduced length of stay, reduced distress for patients, relatives and staff, fewer falls, fewer pressure sores, less functional decline, less incontinence, reduced readmission rates, increased probability of discharge to original address, less worsening of cognitive trajectory and less in-hospital mortality. The estimated date for production of this validated risk prediction score is March 2024.

Frailty, multimorbidity, and delirium in older surgical patients are common problems that effect the public both directly, as patients and relatives, and indirectly through the increased resources required to manage resulting complications. The greater the understanding of these widespread problems, the more refined and effective our surgical pathways may become. The dissemination of this work may also aid the integration and growth of perioperative medicine within UK hospital practice.

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 SNAP 3 study group anticipate that the data processed will allow for the following to be produced:

a. Reports
b. Submissions to peer-reviewed journals
c. Presentations
d. Conferences

The study group will ensure that the results are disseminated widely across clinicians, hospital management groups, health policymakers, patients and our participants. The study’s results will be promoted via email to those participants who have opted in to email updates. Email, social media, podcasts, journals, conferences, websites and established relationships will allow for communication with healthcare professionals and policymakers. Interested members of the public will receive information via newsletters through relevant charities and other organisations such as Age UK. The SNAP 3 team will provide participants with emailed updates as milestones are achieved such as the total number of participants recruited, useful analysis outcomes and publication dates.

One intended output of this research is the creation of a tool which can be used to detect those patients who are at risk of delirium postoperatively. If a successful tool is created, then the knowledge ownership will be shared between the University of Nottingham and the Royal College of Anaesthetists. The Royal College of Anaesthetists have not had any involvement in determining the mean and purpose of the processing (specifically for this tool).

It is anticipated that the initial publication of results in a scientific journal will occur in March 2024, this will be open source. The results of the study will also be disseminated at professional medical conferences and in peer-reviewed journals. Other newsletters and conference presentations will occur prior to and after March 2024. The results will be provided in report form and briefings will be given to interested and influential organisations such as the Royal College of Anaesthetists, Centre for Perioperative Care, British Geriatrics Society and NHS England. A comprehensive list of all bodies for dissemination of results will be produced by the SNAP 3 Study Management and Steering Committee.

The SNAP 3 dataset will be analysed comprehensively as part of a PhD project and a thesis finalised in 2025.

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.

Processing:

The University of Nottingham will transfer data to NHS England. The data will consist of identifying details (specifically, NHS Number, Date of Birth, Postcode, Gender, and a unique person ID) for the cohort to be linked with NHS England data. The cohort will be split into two separate cohorts, one for consented patients and one for consultee patients, to enable national opt-outs to be applied to the consultee patients.

NHS England will provide the relevant records from the HES APC and Civil Registration Mortality datasets to the University of Nottingham. The data will
- contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other record-level data already held by the recipient

The data will not be transferred to any other location.

The data will be stored on servers at the University of Nottingham.

The University of Nottingham stores and backs up data on the Cloud provided by Microsoft Azure.

The data will be accessed onsite at the premises of the University of Nottingham, the data will also be accessed by authorised personnel via remote access. The data will always remain on the servers at the University of Nottingham.

Personnel are prohibited from downloading or copying data to local devices.

The data will not leave England at any time.

Access is restricted to employees or agents of the University of Nottingham who have authorisation from the Principal Investigator.

For Clarity, the following organisations are not permitted to access the data:
Guys and St Thomas’s Hospital London
Royal Devon and Exeter Hospital NHS Trust
University of Oxford and Oxford University Hospitals NHS Trust
The senior clinical fellow in Australia mentioned within the protocol.
University College London

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

The data will be linked at person record level with the cohort’s pseudonymised clinical dataset held by the University of Nottingham.

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

Researchers from the organisation will analyse the data for the purposes described above.

Protect-CH: Prophylactic Therapy in Care Homes Trial — DARS-NIC-437579-V8J5V

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: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-13 — 2022-11-13 breached contract (and anonymisation code) — audit report.

Access method: One-Off

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. COVID-19 Second Generation Surveillance System
  3. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  4. COVID-19 Vaccination Status
  5. Demographics
  6. Emergency Care Data Set (ECDS)
  7. GPES Data for Pandemic Planning and Research (COVID-19)
  8. Hospital Episode Statistics Admitted Patient Care
  9. Hospital Episode Statistics Critical Care
  10. Hospital Episode Statistics Outpatients
  11. Secondary Uses Service Payment By Results Accident & Emergency
  12. Secondary Uses Service Payment By Results Outpatients
  13. Secondary Uses Service Payment By Results Spells
  14. Civil Registrations of Death
  15. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  16. COVID-19 Second Generation Surveillance System (SGSS)
  17. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  18. Hospital Episode Statistics Admitted Patient Care (HES APC)
  19. Hospital Episode Statistics Critical Care (HES Critical Care)
  20. Hospital Episode Statistics Outpatients (HES OP)
  21. COVID-19 SGSS First Positives (Second Generation Surveillance System)

Objectives:

The COVID-19 pandemic has had a devastating effect in care homes. COVID-19 causes illness and death in care home residents and staff. Measures to reduce viral spread into care homes, such as limiting family visits, impact on residents’ health and wellbeing. Beyond public health measures to prevent infection, treatments are urgently needed to minimise these impacts on residents. Many potential treatments have been proposed that might prevent COVID-19 but none have been tested in care homes.

A large clinical trial platform will be set up to test several treatments intended to reduce the spread of COVID-19 within care homes and reduce the risks of hospitalisation and death. A trial platform allows multiple treatments to be tested in parallel, with results analysed regularly. As soon as a treatment is shown to be effective or ineffective, it is removed from the platform. This makes space for new treatments, tested and chosen by government advisors, to be added and rapidly evaluated.

PROTECT-CH will test one or more treatments with the aim of reducing the risk of care home residents catching the virus that causes COVID-19 and of developing severe disease. The results of the study will rapidly be made available to ensure that treatments can be introduced without delay and COVID-19 guidelines quickly updated. The aim of this trial is to set in place a research and governance infrastructure for the efficient delivery of a suite of randomised comparisons to prevent COVID-19 infection and reduce severity/transmission and death in residents in care homes. This trial has been commissioned by the National Institute of Health Research, (NIHR133443) and is badged as an Urgent Public Health (UPH) initiative (trial), under the Data & Connectivity banner.

More than 400 care homes will be recruited from across the UK and approximately 12,000 residents. Care homes will be allocated to a treatment or standard care (no additional treatment). Most of the treatments are expected to be given for two months before assessing whether they have worked, and whether the treatments are cost-effective. Training materials will be developed including videos and audio descriptions for care home staff. For residents, (or legal representatives who will make decisions on their behalf if they do not have capacity) information on the study and the treatments will be provided to help them make an informed decision on whether to take part.

The University of Nottingham has considered the legal basis for processing data under the following articles:
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.
Providing treatments to care home residents during an outbreak will reduce the risk of catching the virus that causes COVID-19 and of developing severe disease. The effectiveness and the cost effectiveness of each intervention are unknown; therefore, this research needs to be carried out in the public interest.

The University of Nottingham has identified the legal basis for processing special category data (ethnicity) under GDPR as 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.

All the relevant variables needed to perform the trial analysis have been identified in each requested dataset and will be extracted by NHS Digital for each participant in the trial. Minimally identifiable data (such as NHS number, date of birth, gender and full postcode) will be used to link all the relevant datasets involved in the analysis including the electronic case report form (eCRF) collected in site by the trial team. The data will then be pseudonymised and identifiable data removed before releasing the dataset for the statistical and economic analysis. The requested NHS Digital data will be used to build the final dataset for the analysis containing all the primary and secondary outcomes and baseline characteristics of each participant. This linked data will be used to carry out the analyses necessary to answer the research questions for this project in order to achieve the identified aim.

Data will be collected from care homes based in England, Scotland, Northern Ireland and Wales and therefore similar data will be requested from the devolved nation equivalents of NHS Digital. Data will be stored and processed in the Trusted Research Environment (TRE) located at University of Dundee (UoD) and managed by the HIC Team (Health Informatics Centre).

The main clinical analysis will be carried out by statisticians at the Nottingham Clinical Trials Unit, University of Nottingham and the economic analysis will be performed by health economists based at the University of Surrey. Other process analyses will be carried out by University of Cambridge. All the analysts will be granted with a secure access to the TRE in Dundee to perform the data management and analyses.

Data will be requested in multiple extracts as participants will be recruited to the study over a period of months. Participants are each followed up for 120 days, and there will be interim analyses conducted, therefore the data flow will be continuous for the duration of the study.

Study participants residing in the same care home will all receive the same study treatment, or usual care. Each treatment under analysis will be compared with the standard care. Each comparison of an active treatment with standard care requires 200 care homes with a 1:1 randomisation (i.e. 100 care homes for each arm) i.e. in the region of 6,400 residents per comparison assuming an average of 32 residents per home taking part in the trial. Justification of these estimates can be found in the protocol section “Power calculation”. The trial design uses a platform structure that allows multiple treatments to be evaluated simultaneously. Randomisation will use equal probability between all active treatments in the platform at the time and a single standard care arm (i.e. allocation ratio 1:1:1:1 if three experimental treatments are in the trial concurrently). To ensure that the platform delivers answers on whether treatments are effective in prevention in a timely manner, the number of active treatments will be limited to three at most at any point. Therefore at least 400 care homes need to be included in the study to compare 3 active treatments to standard care, corresponding to around 13,000 residents.

Care Home criteria:
Inclusions:
· Location: UK care homes for older people, with and without nursing.
· Size: >20 residents in the care home in total.
Exclusions:
· Care Quality Commission quality: Inadequate, or equivalent in devolved administrations.
· Current or recent (within 4 weeks) positive Polymerase Chain Reaction (PCR) or lateral flow test (or equivalent) for SARS-CoV-2 in any resident and/or staff.

Resident criteria:
Inclusions:
· Resident in a Care Home.
· Age >65 years
· Able to give informed consent for participation or has identified a personal legal representative who can give consent, if resident lacks capacity.
Exclusions:
· Currently taking all trial interventions.
· Contraindication to all trial interventions.
· In another COVID-19 prevention or treatment trial.
· Identified by care home staff to have entered end-stage palliative care.
· Resident in care home for short-term respite care.
· Resident’s general practitioner is unable to support their involvement in the trial.

A total of 13 datasets that have been requested as part of this application:
- GPES Data for Pandemic Planning and Research (GDPPR)
- Hospital Episode Statistics (HES) Admitted Patient Care, HES Outpatients, HES Critical Care
- Civil Registration of Deaths
- COVID-19 Vaccination Status
- Demographics
- COVID-19 UK Non-hospital antigen testing results (Pillar 2)
- Second Generation Surveillance System (SGSS)
- Emergency Care Dataset (ECDS)
- Secondary User Service (SUS) Payment By Results (PBR) Accident & Emergency, SUS PBR Outpatients, SUS PBR Spells
These datasets are requested in order to assess the primary and secondary outcomes for the trial analysis, to describe the baseline characteristics of the participants in the trial and to carry out the economic analyses.

1. Baseline characteristics (Age, sex, ethnicity, comorbidities, smoking, previous COVID test, COVID vaccination and frailty index). For this analysis the following datasets are needed: GDPPR, COVID tests (SGSS and COVID-19 UK Non-hospital antigen testing results (Pillar 2)), COVID-19 Vaccination Status.

2. Primary outcome (COVID infection, hospital admission or death). For these outcomes the following datasets are needed: COVID tests, HES APC, Civil Registration of Deaths and Demographics.

3. Secondary outcomes during the 60 days post-randomisation (healthcare contacts for COVID-19 (111,999, outpatients appointments, remote consultations, GP visits etc.), COVID infection with or without symptoms, hospital admission, cause of hospital admission, length of stay, death, cause of death, frailty index). For these outcomes the following datasets are needed: GDPPR, HES Outpatients, ECDS, HES APC, COVID tests, Civil Registration of Deaths, Demographics.

4. Economic evaluation (EQ-5D-5L utilities and EQ-VAS at 60 days, Quality Adjusted Life Years, Healthcare resource use and costs (including A&E attendance, outpatients, hospital admission and critical care hospital stay), Incremental cost-per QALY and Net Monetary Benefit). For these outcomes the following datasets are needed: SUS (A&E, Spells and Outpatients), GDPPR, HES (Outpatients, APC, CC), ECDS.

Some of this information will be collected by care home staff through the eCRF but the plan is to minimise such data collection to reduce burden on care homes, and obtain as much data as possible from routine sources.

Identifiers will be requested to be able to link the data to the eCRF data collected on site. Consent to collect identifiable patient data will be obtained.

The trial is composed of 2 stages:
• Set up stage – 4 months
• Trial data collection/analysis – 20 months

This initial application is to request an 18 months Data Sharing Agreement (DSA) with the possibility to extend depending on progression of the pandemic and ongoing results from the trial.

The requested information could only be obtained from automatically collected routine data. Individually collected data would impose a substantial burden on care homes and would not be an efficient use of public funding, when the required data can be obtained from linkage of national, routine datasets.

Only minimal health data needs to be collected for the purpose of the analysis therefore only relevant variables from specific datasets have been selected and only residents who consented the access to their data will be included in the trial. The time window of data collection is also strictly reduced to the time window relevant for the analyses.

- University of Nottingham is the sole Data Controller and a Data Processor.
- University of Dundee is a data processor and the location where the data will be stored.
- University of Surrey and University of Cambridge are data processors and will be granted access to the TRE managed by the University of Dundee.

The following organisations are involved in the wider project (but are not processing the data):
The University of Edinburgh – Scottish Care Homes leader
The University of Warwick – Hospital at Care home Services expert
The University College London -Care home research expert
The Queen's University of Belfast – NI care home lead
The University of Cardiff – Wales care home lead

This project is funded by the National Institute for Health Research (NIHR) which does not have any role in the research being carried out.

Expected Benefits:

The COVID-19 pandemic has had a catastrophic effect in care homes with direct effects through causing illness and death, and indirect impact from policies to reduce viral spread into care homes, e.g. by limiting family visits.
One treatment, dexamethasone, reduced COVID-19 deaths in hospitalised patients with severe disease and need oxygen therapy; as such, it is not relevant to most people in care homes. Vaccination against SARS-CoV-2 has commenced in care homes but its efficacy in older people with multiple comorbidities and immunosenescence remains poorly defined. This proposal to set up a large platform cluster-randomised trial will test several treatments intended to reduce the spread of COVID-19 within care homes, and reduce the risks of hospitalisations that have had a substantial burden on the provision of the health care to the whole population, triggering in turn lockdowns and further restrictions.

New treatments will be identified to reduce the risk of contracting the severe end of spectrum of COVID19 infection therefore preventing hospitalisation, death and long-term disability in care home residents, with consequent benefits for the whole population and national health services.

Results from this trial are expected to inform decisions whether to change current clinical practice in the UK, in terms of offering prophylactic treatment to home care residents exposed to an immediate COVID outbreak in their care home. The results of this trial will provide benefit to the NHS by reducing hospital admissions and further specialised health care for short and long term COVID effects, with consequent reduction of burden on the health care force and costs. Results can be applied to care home residents in similar types of settings internationally. It is hoped that guidelines and health policies will benefit from these results in real time as soon as the evidence is published, expected to happen in the coming months.

Outputs:

As a result of the data processing, the following will be produced:
• NIHR funder Reports
• Submissions to peer reviewed journals such as “The new England Journal of Medicine” or “The Lancet.
• Presentations at various National and international Conferences, COVID related.

In the outputs only aggregated data will be included. Descriptive, outcome and economic data will be reported at the level of the randomised allocation and not at the level of the care home. Moreover, appropriate disclosure rules will be followed for each dataset used in the analysis in any publication of the final results.

The results of the principal comparisons will be reported first to the trial collaborators. The main reports will be drafted by members of the PROTECT-CH writing committee, and the final version will be agreed by the Platform Steering Committee before submission for publication, on behalf of the collaboration. The trial will be reported in accordance with the relevant Consolidated Standards of Reporting Trials (CONSORT) guidelines. Findings will be disseminated through publication in academic journals and presentations at academic conferences. Dissemination of findings will be prioritised to trial participants (residents/care home staff) who will receive regular newsletter updates. Oral/poster presentations and workshops at sponsor hosted events, community meetings and professional/stake holder/user conferences will be targeted.

The trial team will seek to disseminate in a way to support best practice. They will liaise with the Enabling Research in Care Homes (EnRICH) network to identify potential research users, other researchers, policy makers, commissioners, clinicians, care home managers and staff, care home residents and relatives. Dissemination outputs will be tailored towards each group including peer reviewed journal articles, evidence summaries, briefing papers and video clips. Media coverage will be sought in the form of local newspapers, television and radio outlets and social media. This will be enabled further via connecting with the university’s specialist experts in information technology and communication departments. Requests will be sent to relevant agencies to feature the research project in their newsletters and websites.

The target dates for the achievement of final outcome is not predictable due to unknown progress of the pandemic. It is possible that the process of testing treatments and then replacing them with new ones could go on for many months or years. However, analyses will be carried out in real time and therefore any successful treatment will be identified in a timely manner, and will promptly replace the usual care to reduce the risk of infection in the care home residents. This will follow rapid publication of results. The same will apply for treatments that are shown to be ineffective and therefore promptly removed from the trial to be replaced with any new approved experimental prophylaxis. From a Covid-19 outbreak occurring within the Care Home, the consenting residents in the trial will be monitored for a period of 60 days for the primary outcome and 120 days for secondary outcomes, during which time the various datasets will be sent to the TRE and subsequently analysed by the Data Processing team. Therefore, if numbers allow, the first results could be potentially gathered within the next few months and published before the end of 2021.

Processing:

The University of Nottingham will send to the HIC TRE recurring batches of data obtained from the eCRF for trial participants. These will be sent as soon as the data has been collected on site and when the end of the follow-up period has been reached for each participant / care home. University of Nottingham will also send lists of identifiers (NHS number, Date of Birth, Gender, Postcode) for residents who have consented to take part in the study on to the HIC TRE at University of Dundee, who in turn will send it securely to NHS Digital.

This information will be used by NHS Digital to extract the selected variables from the requested data sources for these specific care home residents in England. NHS Digital will securely send the requested data with the supplied identifiers removed and the Study ID attached at the agreed frequency to the HIC TRE in Dundee, where data managers will perform the linkage between the various datasets and will anonymise the final dataset. These data managers will also pre-process the data to store it securely in the TRE and will perform maintenance work to make sure the data protection requirements are met and the data continue to be securely stored and backed up. They will create an automated procedure to receive multiple batches of data at regular intervals.

Data flows will be recurrent, as care homes are expected to be randomised over a period of weeks or months. Data analyses will be carried out regularly for the Data Monitoring Committee. Fortnightly releases of data are requested to make sure analyses can be carried out in real time and results can be used to inform clinical practice in a timely manner.

At each stage data from all requested datasets extracted for all trial participants will be needed. The first data collection date is expected to be soon after the 1st of May 2021, as soon as participants’ consent forms are received. Prospective data is required for all datasets from the participants’ consent date. Additionally, for the GDPPR dataset retrospective data is also required. This dataset has been collected under a specific COVID-19 related direction, and as such can only be used for COVID-19 research related purposes.

A data manager from the University of Nottingham will remotely access all the data stored on the HIC TRE to perform cleaning and further processing for each batch of data received, with the final aim to create the completed dataset for the analysis. In order to create the final dataset the information collected through the eCRF will be linked with the routine data obtained from NHS Digital and the devolved nation equivalents of NHS Digital. The data manager will also manage and pre-process the data to be used by the Universities of Surrey and Cambridge for the respective analyses. The data will be pseudonymised and will not be used for purposes other than those outlined in the original application. Data analysts from the Universities of Nottingham, Surrey and Cambridge will remotely access the TRE to work on the pseudonymised datasets to perform the clinical and economic analyses.

Personal identifiable data from routine data will not be retained beyond the period of coverage of the data sharing agreement with the routine data providers. Linkage and removal of personal identifiable data e.g. NHS number will be undertaken following receipt of each batch of routine data from the providers. Each participant will be flagged with a pseudonymised ID and only the minimal and necessary variables from different external linked datasets will be retained in the final datasets in order to perform the analyses. All data retained for the purposes of the trial in an anonymised form will be held securely in the HIC TRE and only authorised users who previously received appropriate training will be granted access to the data.

The University of Nottingham will maintain the confidentiality of all participants’ data and will not disclose information by which participants may be identified to any third party where consent has not been gained for this disclosure.

Access to identifiable data will be restricted only to the data manager and HIC support team. The data analysts will carry out analyses only using pseudonymised datasets. 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.

Aspirin To Target Arterial Events in Chronic Kidney Disease (ATTACK) — DARS-NIC-327369-T1M7M

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: 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 2021-03-01 — 2024-02-29 2021.05 — 2023.11. breached contract (and anonymisation code) — audit report.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF SOUTHAMPTON

Sublicensing allowed: No

Datasets:

  1. Cancer Registration Data
  2. Civil Registration - Deaths
  3. Emergency Care Data Set (ECDS)
  4. Hospital Episode Statistics Admitted Patient Care
  5. Civil Registrations of Death
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)

Objectives:

Chronic kidney disease (CKD) is a term used by doctors when the kidneys are not working as well as they should. It is very common and affects as many as one in eight adults in the UK. CKD is important because it is linked to a much higher chance of cardiovascular disease (CVD). CVD is usually caused by small blood clots. Aspirin reduces the risk of blood clot formation but also increases the chances of bleeding. Studies in people with previous CVD show that aspirin reduces the risk of further heart attacks and strokes, and that these benefits are much greater than the risks of bleeding. As a result, aspirin is recommended for people (both with CKD and without CKD) who already have CVD.

The Aspirin To Target Arterial Events in Chronic Kidney Disease (ATTACK) trial is a large open-label randomised multi-centre study set in UK Primary Care, currently just in England. ATTACK aims to demonstrate whether the addition of low-dose (75mg non-enteric coated) aspirin to usual care reduces the risk of major vascular events (excluding confirmed intracranial haemorrhage) in people with CKD who do not have pre-existing CVD, and whether and to what extent the benefits outweigh any harms due to an increased risk of bleeding.

The University of Southampton are sponsors for the ATTACK trial and are the sole Data Controller for this data sharing agreement. The University of Southampton delegated the task of applying for NHS Digital data to the Trial Coordinating Centre hosted by the University of Nottingham. As the trial managers, the University of Nottingham will be data processors of NHS Digital data. Nottinghamshire Health Informatics Service own the servers upon which the ATTACK database is stored and are therefore listed as data processors. TCR (Nottingham) Ltd own the data management software for the trial, storing and handling the data on the ATTACK database in their capacity as data processors. There are other universities and Trusts involved with recruiting patients and advising on the study design and recruitment strategies as detailed in the study’s protocol, but they will not be involved in data processing or handling record level data received from NHS Digital.

ATTACK is funded by the National Institute for Health Research and the British Heart Foundation. The funders assess the scientific value of the trial, and require periodic trial updates, but have no involvement in the trial’s analysis or any data processing. The trial start date was 1st January 2018 and is due to finish in July 2025. The trial will continue and NHS Digital data will be requested until 1,827 major vascular events have occurred, providing enough statistical power to address the study aim.

In order to answer the trial’s primary question of whether aspirin should be prescribed to patients with CKD, the ATTACK trial requires hospital episode statistics (HES) Admitted Patient Care (APC), Civil Registration (Deaths) data and Cancer Registration data from NHS Digital. These data, along with relevant SNOMED-coded data from GP practice records which are directly collected by the trial management team (not from NHS Digital), will serve as the primary source of potential outcome events for the trial. These are events which are monitored as part of the study to determine if there is a true difference between the two arms of the trial. The Emergency Care Data Set (ECDS) is additionally required in order to complete the necessary health economic analysis for the trial. Processing of these routinely collected electronic healthcare data allows large scale trials addressing key clinical topics to be delivered cost-effectively and without the need for commercial sector funding.

The primary outcome measure is the time to first major vascular event from the date of randomisation. A major vascular event is defined as a primary composite outcome of non-fatal myocardial infarction, non-fatal stroke and cardiovascular death (excluding confirmed intracranial haemorrhage). Major bleeding events will be captured as a key safety (secondary) outcome measure. Following the findings of another recently published aspirin trial (ASPREE, New England Journal of Medicine 2018), the Data Monitoring and Ethics Committee (DMEC) for ATTACK has specifically requested regular cancer data as a part of their ongoing safety assessment. Incident cancer is one of the secondary outcomes. There is some evidence that certain types of cancer (e.g. colorectal) are reduced by regular aspirin, and the study seeks to add to this evidence. Mortality, cancer incidence, unplanned hospitalisation and health-related quality of life are additional trial outcomes.

Record-level NHS Digital data is required to track which patient was randomised to which arm of the trial, and compare the outcomes in the two arms of the study. There are no alternative, less intrusive ways of achieving the purpose. Data minimisation has been considered and, as part of that process, a Health Economist has reviewed the list of fields available from HES APC and ECDS and confirmed those that are essential for their analysis.

The information provided by NHS Digital will contain identifiable information to allow study team members to associate it with the correct trial participant. When data analysis is performed, this will be pseudonymised, and patient screening numbers (i.e. study IDs) will be used instead of identifiable data. As the trial is open label (i.e. there is no placebo), the participants and their treating practitioners will know whether they are in the aspirin or usual care arm of the trial. GP records, annual questionnaires to patients, and hospital attendance alerts which are also collected and scrutinised as part of the trial may therefore be subject to bias, or be incomplete sources of information. Record-level NHS Digital data is therefore required to build upon and validate these other sources of information.

Where these sources indicate a potential cardiovascular or major bleeding event, the study team will collect relevant supporting information (from hospital discharge summaries and medical records) and present this to an Endpoint Adjudication Committee who will evaluate this information (blinded to treatment allocation) in order to determine whether patients have reached a trial endpoint. Other trial endpoints will be recorded in the trial database for subsequent statistical analysis and monitoring by the DMEC but are not formally adjudicated.

The ATTACK trial methodology is summarised as follows:
• Potentially eligible adult (aged 18 and over) patients, both male and female, from across England, with historical blood/urine tests suggestive of stage 1-4 CKD (and who meet all other eligibility criteria) identified from GP records are invited to participate. They receive an invitation letter from their GP practice, and if they would like to take part, are asked to return a reply slip in a pre-paid return envelope to the study team. Those who respond are invited to attend a screening visit (this is several weeks after their initial invitation, so they have plenty of time to consider their study participation). Following consent, and signing of the ethically-approved consent form, they undergo a brief baseline health assessment. Patients who are eligible are randomised in an open-label fashion to either 75mg aspirin daily, or to usual care. This means there is no placebo involved in the trial, but both the patient, their GP and the research team are aware of which arm of the trial the patient has been allocated to. GPs are then asked to prescribe aspirin to patients in this arm of the trial via normal NHS systems.
• The scale of the ATTACK trial is large (approximately 25,000 randomised patients are expected overall). Patients make no follow up visits but can notify the trial office of any relevant events, as can their treating healthcare professionals. Patients also receive an annual questionnaire asking them about their health status and aspirin consumption.
• Follow up data is obtained by interrogation of GP electronic records on roughly a 4-weekly basis, and by linkage by TCR (Nottingham) Ltd to data from NHS Digital approximately annually. University of Southampton cannot reasonably achieve the above in a different way other than accessing HES APC/ ECDS, Civil Registration (Deaths) and Cancer Registration data from NHS Digital.

Consented study patients give explicit permission for subsequent scrutiny of their medical records by the research team. This includes relevant sections of medical notes and NHS Digital data. They also explicitly consent for their NHS number and date of birth to be used for linkage purposes, and to be sent to NHS Digital. Patients’ GP data are regularly uploaded to a bespoke ATTACK database/management system via electronic searches looking for any new relevant information in the patients' medical record, or any changes since the last upload. This database/management system has also been prepared to detect and store disease and procedure codes from HES and ECDS.

Data is only requested and collected on patients who have consented for this to happen, via a signed consent form. The University of Southampton only collect relevant data from the patients’ medical record, as agreed with the trial statistician and health economist, to answer the questions the trial is designed to answer.

The legal bases for processing personal data for the ATTACK trial are Articles 6(1)(e) and 9(2)(j) of the General Data Protection Regulation (2018).

GDPR Article 6 (1) (e) is justified because processing is necessary for the performance of a task carried out in the public interest. The University of Southampton is a public authority conducting clinical research with the intention of publication of trial outcomes in clinical journals.

GDPR Article 9 (2) (j) is justified because processing of special category data is necessary for scientific research purposes. Processing 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 subjects. Civil Registration (Deaths) data, Cancer Registration data and HES APC / ECDS data are required in order to test the hypothesis of the ATTACK trial; assess the safety of the trial drug in this patient population; and determine cost-effectiveness.

Expected Benefits:

CKD is important because it is linked to a much higher chance of heart attacks and strokes. On average 2 or 3 of every 100 people with CKD will have a heart attack or stroke every year. The risk of CVD in people with mild CKD is double the risk in people with normal kidney function. The risk increases to five times as high, as CKD worsens.

The impact of CVD in CKD is substantial. Overall CVD is responsible for about one-third of all deaths in the UK. It can have a serious impact upon quality of life and cause considerable disability. CKD is included as a vascular condition within the Department of Health's CVD Outcomes Strategy. The financial impact of CVD in CKD is large: assuming unit costs of £12,000 for a stroke and £7,734 for a myocardial infarct (MI) and incidence of stroke and MI of 12.0 and 11.9 per 1000 patient-years respectively in people with CKD , the annual costs of strokes and MI in people with CKD in England is in the order of £5 billion. By conducting this research, the research team hope to reduce the impact of CVD in this patient population, and save the NHS a huge amount of money in reduced hospital admissions for cardiovascular events. If the trial hypothesis is correct, the University of Southampton would expect to start implementing the intervention as soon as the trial finishes and is written up, as it is expected that the National Institute of Clinical Excellence (NICE) prescribing guidelines to change accordingly. Therefore, if the trial shows that aspirin-prescribing is beneficial, it would be recommended to all CKD patients in the UK who do not currently have an indication to take it (approximately 3 million patients), thus preventing admissions for heart attacks and strokes. Conversely, if aspirin is shown not to be of overall net benefit in this patient population, the approximately 1 million patients who currently take it for primary prevention would be recommended to stop their prescription, this reducing the number of hospital admissions for bleeding complications.

There is currently insufficient evidence to recommend the use or avoidance of aspirin for the primary prevention of CVD in CKD as data on the use of antiplatelet agents in the specific setting of primary prevention in CKD are limited. The literature suggests that the efficacy of aspirin in CVD prevention is at least as great in people with CKD as the general population but the risks may also be greater, and so uncertainty remains about the net balance of benefit and risk.

The current understanding of how to reduce cardiovascular risk in CKD is limited. The Study of Heart and Renal Protection (SHARP) demonstrated that primary prevention with simvastatin and ezetimibe reduced major atherosclerotic events in people with CKD. Evidence on other approaches to prevent CVD in CKD is urgently required. In 2014 the National Institute for Health and Care Excellence (NICE) made a Research Recommendation for a definitive trial of aspirin for primary prevention of CVD in people with CKD.

ATTACK was designed in response to this recommendation. The results of this trial, will provide the evidence to improve clinical outcomes in large numbers of people. Most people with CKD who do not have CVD are not currently prescribed aspirin. In the UK it is believed that around 20-25% of people with CKD and no CVD as prescribed aspirin and 75-80% are not, reflecting the current clinical uncertainty. If ATTACK shows that the benefits of aspirin outweigh the risks in this patient group, then it would suggest that aspirin should be offered to more than 3 million additional people in the UK (excluding those with a contraindication or taking over-the-counter). If use of aspirin for primary prevention of CVD in people with CKD results in a relative reduction of 12.5% in the risk of CVD, 50,000 additional major vascular events over five years may be prevented in this group. Conversely if aspirin is not shown to provide benefit in this patient group, it would provide definitive evidence to stop aspirin in one million people who are now taking it for primary prevention.

If the ATTACK researcher's hypothesis is correct the costs of CVD averted in people participating in the trial alone would cover approximately 50% of the research costs of the study.

Outputs:

The trial will continue until 1,827 major vascular events have occurred: this is anticipated 6 years after the planned recruitment start date of October 2018, so in approximately October 2024 – March 2025.

The primary outputs of the analysis will be scientific papers/posters covering both the medical and procedural aspects of the study. The University of Southampton intends to publish the results of the ATTACK Study in a major scientific journal (such as the New England Journal of Medicine or the Lancet), and will also present details of the study at relevant scientific meetings (such as the International Conference on Trial Methodology, or the British Renal Society’s UK Kidney Week). The study research team will also share regular feedback and recruitment updates with the Clinical Research Network, to help inform and improve the design of primary care trials in the future. The University of Southampton have already been approached on numerous occasions to advise on some of our novel methodologies, include video-training of GP practice staff.

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

In addition, regular summaries and reports of the number of endpoint events by trial arm will be sent to the Data Monitoring and Ethics Committee (DMEC). The role of the DMEC is to monitor these data and make recommendations on whether there are any ethical or safety reasons why the trial should not continue, ensuring that the safety, rights and well-being of the trial participants are paramount. From the trial Protocol the DMEC are required, at a minimum, to meet at the following defined time points: 18 months from the start of recruitment to review safety and assess study recruitment and feasibility; 27 months from the start of recruitment to assess safety, recruitment and the control event rate; and 36 months from the start of recruitment to assess safety, study recruitment and the control event rate.

Patient and public involvement (PPI) is crucial to the success of this project, and has helped in the following ways to date:
- 2 PPI members on the Trial Steering Committee, who attend 6 monthly meetings
- 2 PPI members on the Trial Management Group who attend regular teleconferences, and have provided advice on the protocol, participant information sheet, invitation letter, and recruitment strategies
- 4 PPI members form a "document review panel", and have provided feedback on the participant information sheet, invitation letter and annual questionnaires, both
as part of the original submission and the recent substantial amendment
- The research team are are actively consulting with their PPI colleagues regarding a trial redesign and recruitment restart in light of the COVID-19 pandemic.

Processing:

DATA ACCESS
TCR (Nottingham) Ltd have been contracted as the data processor who store and handle the trial data (including data received from NHS Digital, SNOMED-coded data from GP practice records, and data collected directly from the patient at consent or via their annual questionnaires) on the ATTACK database. The Managing Director of TCR (Nottingham) Ltd securely transfers data to and from NHS Digital using Secure Electronic File Transfer (SEFT). TCR (Nottingham) Ltd has agreed to support the project by developing and maintaining a bespoke software tool and management system to be known as the ATTACK Trial Software Tool and Management System. This system incorporates both bespoke software and Third Party Software and comprises a practice-based ATTACK toolkit to be installed in each GP practice participating in the project, and a web-based trial management system to be available via N3-connected computers. The Product will underpin the project by facilitating recruitment of trial participants and remote data collection, and by providing administration, reporting and development tools for both the research team and GP practices participating in the project.

The main ATTACK database is stored on an N3 server within the N3 network based at Nottinghamshire Health Informatics Service (formally Kings Mill Hospital Data Centre). Nottinghamshire Health Informatics Service supply IT infrastructure for TCR (Nottingham) Ltd, but do not access trial data. Therefore, any access to the data held under this agreement by NHIS would be considered a breach of the agreement. This includes granting of access to the database(s) containing the data, which is a role managed by TCR (Nottingham) Ltd.

TCR (Nottingham) Ltd take a periodic back-up encrypted to AES256 standard which is retrieved to TCR (Nottingham) Ltd on an encrypted hard drive. This is not decrypted, and is a disaster recovery system in case of any problems at NHIS.

TCR (Nottingham) Ltd manages all access permissions which are set on a per-person basis. Only relevant members of the study team from the Universities of Southampton and Nottingham would have access to the record level data provided by NHS Digital. TCR (Nottingham) Ltd provides two levels of access to the data for study staff: (i) the full identifiable data is accessible only to individuals for the purpose of facilitating follow-up contact; and (ii) pseudonymised data stripped of identifiers except for initials (to mitigate risks of quality errors arising from transposition errors if using only a study screening number). The study screening number is accessible to the research team and only this level of data is used in analyses. Authorised study staff access the trial data on the ATTACK database via remote access to the server using N3-connected machines. Record level data requiring formal statistical analysis by team members from the Universities of Southampton and Nottingham can however be exported from this database.

Pseudonymised record level data will be exported via encrypted transfer service onto secure servers at the Universities of Southampton and Nottingham in order to be able to use statistical packages to analyse the data. The servers used will be the main University servers which are designed to store research data. University usernames and passwords are required to access the servers. All pseudonymised data relating to ATTACK will then be stored in specific password-protected folders which are only accessible to authorised personnel, all of whom have completed Good Clinical Practice and Information Governance training and understand the importance of not saving data in insecure locations. ATTACK data will only be held on these servers for as long as is required to analyse the data, and not for longer term storage. Data sharing agreements will be maintained to cover all such activity.
Access to the university servers will be restricted to on-site computers or secure remote access - in line with national UK Government guidance during the COVID-19 pandemic to work from home wherever feasible. Remote access is via Remote Desktop or VPN and uses multifactor authentication. No data will be stored on remote devices. Only a ‘screen view’ of the data will be available.

DATA FLOW
- In order to obtain HES APC, ECDS, Civil Registration (Deaths) and Cancer Registration data, TCR (Nottingham) Ltd will securely send a list of randomised patient study IDs, NHS numbers and dates of birth, along with dates of consent, to NHS Digital on an annual basis. NHS Digital will annually provide HES APC and ECDS information on these patients since their date of consent, plus all available Deaths and Cancer Registration data for the cohort. Patients have explicitly consented for these data to be sent to NHS Digital on their consent form.

- NHS Digital will return HES APC, ECDS, Deaths and Cancer Registrations data to TCR (Nottingham) Ltd with study ID and patient date of birth. Date of birth is required to be returned in addition to study ID to ensure that there are no transcription errors, and that the correct events are allocated to the correct patient when linking back to other trial data held by TCR (Nottingham) Ltd). This linkage will only be performed for consented patients, to match events to the correct participant for the trial’s analysis of comparing events between the two arms of the trial (aspirin arm patients versus standard care patients).

- At individual patient level, the HES APC and ECDS data will be compared with consented patients in the ATTACK database to determine the extent of discrepancies between the detail in this data, and outcome data derived from other sources (GP data, questionnaire data and healthcare professional- or patient-reported events). This will be performed by data processors at the University of Southampton, University of Nottingham and TCR (Nottingham) Ltd. Study ID numbers and initials will be used for this, rather than identifiable information. There will be no requirement or attempt by individuals with a data analysis role only to re-identify individuals. Trial endpoints identified in this way will be recorded on the trial database.

- Potential major vascular events and bleeding events requiring hospitalisation will, in addition, be subject to a process of blinded endpoint adjudication: the trial team will collection additional information on these events (from hospital discharge summaries and medical records) so the events can be formally adjudicated by one of three (separate for cardiac events, strokes and bleeding) Adjudication Committees. The information will be redacted so that the Adjudication Committees will not know whether the subject was receiving aspirin or usual care. However, the identity of the consented patient will be known to relevant, limited members of the study team, to enable the team to request further information from hospitals / GP practices on events of interest (e.g. requesting a discharge summary from a GP practice for a patient who has a HES-coded myocardial infarction).

-The University of Southampton requires all the relevant requested fields within HES APC and ECDS under this agreement together with data on deaths (including cause of death) and cancer diagnoses to perform a Health Economic analysis. Modelling will be used to estimate the net effect of aspirin prescribing on healthcare costs and quality-adjusted survival over a lifetime horizon, using trial data to estimate effects on vascular and bleeding risks, cancer incidence and mortality. Trial data will also be used to estimate health-related quality of life and healthcare costs for the population associated with adverse events. These analyses will require data on all reasons for admission (including length of stay, other related medical events and types of services accessed) in order to study the impact on other health conditions.

All researchers processing NHS Digital data under this agreement bar one are substantive employees of the University of Southampton, University of Nottingham or TCR (Nottingham) Ltd who have been appropriately trained in data protection and confidentiality. The researcher who is not a substantive employee of the listed data controller or processors is a substantive employee of Epsom and St Helier NHS Trust. However, this individual has an honorary contract at the University of Southampton for this trial which details the University regulations, policies and procedures he should abide by. There is a collaboration agreement active between the University of Southampton and Epsom and St Helier NHS Trust, and the individual completes annual IG training which is provided by his substantive employers as a part of his Statutory and Mandatory Training.

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).

HES DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, it must be ensured 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.

Surgical margins in breast conserving surgery for ductal carcinoma in-situ (DCIS) and clinical outcomes (ODR1819_162) — DARS-NIC-656832-M8F7G

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

When:DSA runs 2023-02-24 — 2023-09-01 2023.03 — 2023.03. breached contract (and anonymisation code) — audit report.

Access method: One-Off

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations

Objectives:

On 1 February 2023, NHS Digital merged with NHS England. NHS England has assumed responsibility for all activities previously undertaken by NHS Digital. The merger was completed by a statute change. Any reference made to NHS Digital within this Data Sharing Agreement is in reference to the merged organisation known as NHS England.

The optimal surgical margin in breast conserving surgery for DCIS has not been established. This is in large part due to the absence of accurate surgical and histological margin data. For example the surgical margin currently supported by the American College of Surgeons is based in large part on a study meta-analysis which has multiple weaknesses. The most obvious weakness is that there was no data on the actually surgical margins achieved (as these was not recorded) but rather was based on a margin width which the centre or study had designated as its ‘standard’. The meta-analyses therefore assessed a theoretical margin width and not what the actual margin width that the OFFICIAL2ODR Review Form Part 1A v2 (December 2017)Author: Rachael Brannansurgery achieved.

Patients today therefore arehaving breast conservation surgery for DCIS with margin widths which are not based on data which compared actual margin widths versus clinical outcomes. This audit would aim to provide information of clinical outcomes based on actual surgical margins measured by the pathologistand would represent the most clinically accurate study of its type to date.Project aim:To assess the impact of the size of the width of the tissuebetween the edge of the breast tumour (DCIS) being removed and the edge of the whole surgically excised tissue specimen(known as “margin width”). They wish to establish the optimum margin width for best clinical outcomes. The clinical outcomes assessed would be loco-regional recurrence, distant recurrence and mortality (both overall mortality and breast cancer specific mortality).Data collected by PHE from patients treated by breast conserving surgery for newly diagnosed DCIS will be used to assess whether the size of surgical margins impacts on clinical outcomes such as recurrence rates of DCIS or invasive cancer -either within the treated breast and/or regional lymph nodes or distant metastases –and also on patient survival (both overall survival and breast cancer specific mortality). In addition to the margin width,other parameters which could impact on the analyses would be included. These would include but not be limited to demographic factors (e.g.age, ethnicity, menopausal status, etc) as well as other tumour biological features (e.g.tumour size, grade, presence of microinvasion, hormone receptor status, growth factor status, etc). These other parameters would be included in a multifactor analysis which would produce a more comprehensive and nuanced approach in contrast to the simple observation of margin width effect on clinical outcomes.

Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO) — DARS-NIC-237669-T9W5N

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, 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), 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 - 'Other dissemination of information'

Purposes: No (Academic)

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

When:DSA runs 2019-06-15 — 2022-06-14 2020.04 — 2021.10. breached contract (and anonymisation code) — audit report.

Access method: One-Off

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

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

Objectives:

The Cerebrovascular accident and Acute coronary syndrome and Peri-operative Outcomes study (CAPO) is a database linkage study sponsored by the University of Nottingham. The study aims to assess:

1. What is the impact of clinically recognised pre-operative strokes and heart attacks (myocardial infarction) on perioperative outcome?
2. Do the characteristics and management of strokes and heart attacks modify perioperative outcome?
3. How are the effects of strokes and heart attacks modified by surgical procedure?

Previous strokes and heart attacks (that take place prior to being operated on) are recognised risk factors for an adverse outcome following surgery. It is not clear how long this risk exists and whether it is modified by characteristics of the stroke or heart attack (treatment, pathophysiological effect) or by the type of surgery. Previous work by this group and others using HES (Hospital Episode Statistics) data has demonstrated an association between both strokes and heart attacks, and adverse perioperative outcomes following major orthopaedic surgery; the effects were less evident for patients undergoing major vascular surgery.

The CAPO study proposes to build on this previous work by studying data from a larger cohort of patients from the HES database and linking this HES patient data to patient data from the Myocardial Ischaemia National Audit Project (MINAP), the Sentinel Stroke National Audit Project (SSNAP) and the Office for National Statistics (ONS). Through this data linkage process this study will achieve better capture of patients who have had a stroke or heart attack prior to surgery, as well as additional information about the characteristics and treatment of these events.

The University of Nottingham propose to use pseudonymised patient level HES data to identify a cohort of patients who underwent surgery between 2007 and 2017. The HES data will be linked to data from the MINAP and SSNAP registries to gain information regarding the occurrence of pre-operative strokes or ACS in these patients. This linked data and mortality data will also be used to look at post-operative outcomes in these patients: mortality, postoperative ACS, prolonged length of stay and emergency readmission rates.

Non special category data will be processed on the basis of being a task performed in the public interest (Article 6(1)(e)). Special category data will be processed on the basis of being necessary for reason of public health (Article 9(2)(i)). The use of identifiable information for data linkage has section 251 approval (19/CAG/0013).

There are approximately 4.4 million intermediate surgeries (surgeries routinely undertaken in an operating theatre and/or under general anaesthetic) in England each year (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017). It is therefore estimated that the 10 year study-cohort will contain 44 million intermediate surgical episodes. It is estimated that at least 400,000 of these episodes will represent patients who have had a previous heart attack or stroke. This is based on a conservative estimate of the proportion of the UK population who have had a previous heart attack or stroke as 1% (British Heart Foundation Heart & Circulatory Disease Statistics). 400,000 of the total episodes are estimated to result in patient death within 30 days. This is based on an average 30 day mortality of slightly above 1% of those who undergo intermediate surgery (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017).

This size dataset is required to adequately power the study. Much of the value of the study in terms of informing clinical decision making will result from the analysis of individual surgical subgroups. For total hip and knee arthroplasty where annual numbers are around 100,000 and mortality is 0.2% at thirty days, 2,000 deaths would be observed in the 10-year study dataset. Using a requirement of ten events per predictor to adequately power the regression analysis this would allow the analysis of over 100 predictors. Many of the other surgical subgroups will be much smaller (e.g. abdominal aortic aneurysm repair) or have much lower mortality rates (elective ophthalmological surgery). Hence it is essential to have this large dataset to allow analysis of these subgroups; the analysis of which underpins the ability of the study to produce clinically relevant findings.

The use of a 10-year cohort will also allow assessment of how the relationship between exposures and outcomes changes during the 10-year period. This may reflect temporal changes in the management of heart attacks and strokes or changes in perioperative practice.

Episodes containing surgical events not required in the analysis (obstetric surgery and surgeries likely related to the occurrence of a vascular event) will not be requested.

Selecting a smaller dataset through random sampling of patient episodes would greatly limit the study. Reducing the dataset size would reduce the power of the analysis and the ability to analyse smaller surgical subgroups and subgroups with lower mortality rates. The other limitation with randomly selecting a proportion of the cohort is that if it was done before the data linkage to the other registries this will lose many of the MINAP/SSNAP linked patients and hence compromise the granularity of the analysis. If the patients were selected after linkage and stratified to include all linked patients this would potentially bias the study (it may be that the patients with more severe heart attacks or strokes are more likely to appear in MINAP/SSNAP).

While the primary regression analysis will include only the earliest surgical episode for each patient within the dataset, minimising the dataset by selecting only the earliest patient episodes would not be feasible. University of Nottingham intend to perform analyses of multiple surgical sub-categories. While a patient may have multiple surgical episodes in the full dataset these are unlikely to all be in the same surgical category. Hence if only the earliest surgical episode for each patient is included in the dataset this would lose episodes that would have been used in surgical subgroup analysis.

University of Nottingham also require multiple surgical episodes for each patient to perform a sensitivity analysis. They intend to repeat the analysis using the final surgical episode within each surgical subgroup as the index surgery in patients who had multiple surgeries between 2007 and 2017. Patients without multiple surgeries will be excluded from this analysis. This sensitivity analysis will allow assessment of the appropriateness of using the first surgical event in the primary analysis and may highlight any potential effect on outcome of multiple surgeries post a vascular event.

Expected outcomes are robust estimates of time-dependent risks associated with stroke and ACS, stratified by surgical type and characteristics of stroke and heart attack.

Expected Benefits:

Cardiovascular events (heart attacks or strokes) that have occurred prior to surgery are risk factors for adverse outcomes following surgery. In recent years treatment of heart attacks has improved significantly and more patients are surviving and presenting for surgery following stroke. In addition, surgery is being offered to patients with co-morbidities previously felt to preclude it. The increased risk of surgery associated with cardiovascular events may be due to increased risk associated with the event itself (which might be expected to reduce with time) or increased risk due to the underlying cause of the cardiovascular event (e.g. arterial disease, smoking, diabetes) which may not change with time.

It is increasingly recognised that it is important for medical professionals and patients to work as a team to make the most appropriate decisions about a patient’s care. In this context the joint decision-making process requires knowledge of the optimal timing of surgery following a cardiovascular event. Delaying surgery unnecessarily, at best causes patient distress, and at worst may result in worse outcome. Conversely, proceeding to surgery too soon may expose patients to unnecessary risks. Furthermore, the risks may be specific to the type of operation a patient is having.

It is therefore important to have accurate information about the risks of specific operations in patients who have had previous vascular events. It is important to know how this risk changes with time and if it is affected by the type and severity of the cardiovascular event or the treatment the patient received for it.

Existing studies have provided some insight, but the impact on perioperative outcomes of the interval between stroke or heart attack and surgery still remains unclear. The modifying effects of disease severity, underlying cause and treatment have not been fully investigated. Through combining information from a number of registries collected over a large time period this study will analyse data from a much larger group of patients than previous studies. Unlike previous studies, the dataset analysed in this study will contain detailed data on the type of stroke or heart attack patients may have had previously and information on how they were treated. The study should provide a better understanding of how a heart attack or stroke influences the risk of having a subsequent operation and how this risk changes with time after the heart attack or stroke. University of Nottingham hope to be able to provide accurate information that is specific to different types of surgery. This information should inform the shared decision-making process when planning patient care.

It is estimated that at least 1% of the population of England have had a previous heart attack or stroke (British Heart Foundation Heart & Circulatory Disease Statistics). There are approximately 4.4 million intermediate surgeries (surgeries routinely undertaken in an operating theatre and/or under general anaesthetic) in England each year (Abbott et al. analysis of HES data, British Journal of Anaesthesia 2017). Therefore a conservative estimate of 40,000 patients undergo intermediate surgery in England each year having had a previous heart attack or stroke. The results of this study will provide accurate time-dependent data about the risks associated with these surgeries. This information will inform the shared decision-making process improving assessment of the appropriateness and optimal timing of a surgical intervention. This may potentially lead to improved outcomes for these patients.

University of Nottingham anticipate the study results will be used as a basis for planning randomised controlled trials of potential cardioprotective therapy during the perioperative period. They will also use these data to construct perioperative risk models for NHS patients.

University of Nottingham aim to begin publishing the results of the study within 2 years of the start of the data analysis. This information could then be used to estimate patient risk and guide surgical decision-making. As described it is hoped this will be beneficial to patient care.

Outputs:

All study outputs will only contain anonymous aggregate level data. Small numbers would be suppressed as per the HES analysis guide. University of Nottingham plan to distribute findings from the study in the following ways:

-Peer-reviewed publications in high impact journals

- Direct link of study team (Health Services Research Centre) to Royal College of Anaesthetists and hence Lay Committee and Patient Information Group, allowing timely dissemination of information. The Patient information Group is a sub-committee at the Royal College of Anaesthetists that is responsible for developing and keeping patient information up-to-date. They develop information in varied formats to try and best inform patients about various aspects of anaesthetic/perioperative care.

-Influencing the national (NHS) agenda through existing links of the study team with National Clinical Directors.

-Wide dissemination of findings by the study team
- National and regional presentations
- Social media

- Dissemination of findings through Health Services Research Centre
- Presentations
- Social media
- Published reports

-Linkage of findings with data collection and analysis of surgical and perioperative medicine Getting It Right First Time (GIRFT) project leads.

While many direct outputs from the study will not be aimed specifically at patients/general public it is hoped that the findings, communicated as above, will be used by medical professionals to inform their discussion with patients regarding perioperative risk and joint surgical decision making. Also, as mentioned the direct link of the study group to the Royal College of Anaesthetists Patient Information Group will hopefully allow the finding of the study to influence perioperative patient information.

University of Nottingham would hope to begin publishing the results of the study within 2 years of the start of the data analysis.

Processing:

NHS digital will identify a cohort of patients who have an episode in the HES-APC (Hospital Episode Statistics - Admitted Patient Care) database with a surgical procedure between 2007 and 2017 at the time of which they were 18 years or older.

NHS Digital will receive identifiable patient level data from the Healthcare Quality Improvement Partnership (HQIP) - MINAP and SSNAP data controller. The identifiers will be NHS number, date of birth, sex, and post-code. NHS Digital will link this data to the HES-APC data from 1997 to 2018 for the patients in the cohort. NHS Digital will also link this data to mortality data (date of death).

The linked dataset created by NHS digital will be pseudonymised (identifiers removed/encrypted HES ID created for each patient in dataset).

The linkage of identifiable data by NHS digital to form the pseudonymised dataset has been approved by the Confidential Advisory Group under Section 251 of the NHS Act 2006 (CAG ref: 19/CAG/0013).

The pseudonymised dataset will be transferred to the University of Nottingham where it will be analysed by the study group. Logistical regression analysis will be performed on the data to generate estimates of time-dependent risks associated with strokes and heart attacks, stratified by surgical type and characteristics of stroke and heart attacks. Any results distributed from the analysis will be at an anonymous and aggregated level with small numbers suppressed in line with the HES Analysis Guide.

The University of Nottingham will be the sole data controller for the pseudonymised dataset transferred from NHS digital. Only University of Nottingham employees will access the dataset or make decisions about how it is processed. While non-Nottingham University employees (University of Wisconsin School of Medicine and University College London) were involved in the initial development of the study (study idea) and will be involved in the distribution of the published results of the study they will not be involved in decisions as to how the study dataset is processed and will not access the study dataset. Therefore although the study protocol names two non-Nottingham University employees as co-investigators, they do not have a data controller or data processor role in relation to the data shared under this agreement. While some study team members are substantive employees of the Nottingham University Hospitals NHS Trust they will be seconded to the University of Nottingham (forming an employee-employer relationship) for the purpose of this study; Nottingham University Hospitals NHS Trust will play no role in the study.

At the end of the data retention period the University of Nottingham will destroy the data.

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).

Helicobacter Eradication Aspirin Trial (HEAT) — DARS-NIC-389320-R4M6Z

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, Anonymised - ICO Code Compliant, 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(7), Health and Social Care Act 2012 – s261(2)(c), Informed Patient consent to permit the receipt, processing and release of data by the HSCIC and for the release of ONS mortality data, Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

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

When:DSA runs 2019-05-14 — 2020-05-13 2017.12 — 2020.09. breached contract (and anonymisation code) — audit report.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

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

Objectives:

Helicobacter Eradication Aspirin Trial (HEAT) is a large double-blind (i.e. neither subject nor those running the study know the identity of their randomised treatment), placebo-controlled randomised multi-centre study set in primary care. There are three primary objectives:
1. Medical: To test the hypothesis that a one week course of Helicobacter pylori (H. pylori) eradication in patients using aspirin ≤325mg daily will reduce the incidence of subsequent adjudicated peptic ulcer bleeding that results in hospitalisation.
2. Economic: To test the hypothesis that the intervention has a positive net monetary benefit.
3. Methodological: To establish a methodology for large simple outcomes studies using electronically extracted Primary Care follow-up data, to reduce costs to a level that enables outcomes studies of clinically important questions to be done without the need for industry support.
The data is required as part of the process of endpoint detection for the HEAT trial. This is a large ultra-simple trial which attempts to use electronic data sources to capture possible trial endpoints (primary endpoint is admission to hospital with peptic ulcer bleeding). Other sources of data will be via electronic scrutiny of GP records, ONS mortality data (date and cause of death) and patient alerts, whereby patients inform the study of any attendance at hospital. Cases deemed to have possibly reached an endpoint will have detailed hospital data collated and an Adjudication Committee will evaluate whether patients have had a definite or probable ulcer bleed using the criteria of the TARGET study.
Consented study patients give permission for subsequent scrutiny of their records and any death certification. GP data are repetitively uploaded to a bespoke database/management system which has also been prepared to detect and store disease and procedure codes from HES. Permissions are also already in place for access to all the major hospitals where the trial is being conducted (Southampton & the South West, London, Nottingham & East Midlands / South Yorkshire, Durham and the North, Oxford and South East, Birmingham and the West Midlands) to allow nurse access to gather information on possible cases.

Potentially eligible patients (over 60 years olds taking long-term low-dose aspirin, and who meet all other eligibility criteria) identified from GP records are invited to participate. They receive an invitation letter from their GP practice, and if they would like to take part, are asked to return a reply slip in a pre-paid return envelope to the study team. Those who respond are invited to attend a screening visit at their GP practice (this is several weeks after their initial invitation, so they have plenty of time to consider their study participation). Following consent at their practice, they undergo a brief baseline health assessment and perform a H. pylori breath test. H. pylori positive patients will be randomised to receive eradication treatment or matching placebo. Treatment is dispatched to the patients by post by members of the research team (University of Nottingham staff dispense this from a satellite Pharmacy of Nottingham University Hospitals NHS Trust, and have been trained and are monitored by the Clinical Trials Pharmacist at NUH).

All patient follow-up is electronic. Patients make no follow up visits but can notify the trial office of any relevant [or indeed irrelevant] events. Follow up data is obtained by interrogation of GP electronic records and by routine linkage via NHS Digital to ONS data on deaths (date and cause), and from HES data on hospital admissions.

Yielded Benefits:

The University of Nottingham have been able to estimate event rates, based on previous data received from NHS Digital, which enabled them to calculate more accurately how many patients were required to take part in the study, and cease recruitment on 31-Oct-17 with 30,024 consented participants. The full trial analysis will not be possible until they can close the trial at the point 87 primary endpoints have been achieved, and all data from NHS Digital helps them to work towards this target.

Expected Benefits:

The cost of admission and hospital stay for a bleeding peptic ulcer is likely to be approximately £15,000 per patient for the population that will be analysed. Based on calculations for patients participating in the proposed trial (assuming all ultimately undergo eradication treatment) the trial would lead to the projected prevention of 585 hospitalisations at a saving of approximately £5.85 million, and prevention of ~59 deaths, potentially making the trial itself a cost effective therapeutic intervention. Though cost savings in relation to the trial participants is not the primary purpose of the study, these figures are illustrative of potential savings should the trial results have the expected impact on NHS policy.
If the hypothesis of the trial is correct, patients would benefit medically from the study, and the NHS would make significant cost savings. The results would be presented to NICE (via peer-reviewed published papers) and other policy makers (NHS England, Wales, Scotland and Northern Ireland, SIGN), who may deem that any patient taking aspirin regularly (25% of over 65 years) should be breath tested, and their H. pylori eradicated if present, as the University of Nottingham believe this will halve the bleeding risk for patients. Even if the trial’s hypothesis is incorrect, this knowledge will be of benefit to patients and the NHS. It would inform that antibiotics are not required to treat H. pylori to protect this patient group, and thus reduce
antibiotic prescribing, and associated resistance / costs. Patients would also avoid the one week of side effects (nausea / vomiting) from taking the antibiotics.

Outputs:

The trial will proceed until there are 87 adjudicated cases (there are currently 7 formally adjudicated primary endpoints, and we estimate reaching the target of 87 by early 2020) and will then be analysed to test the hypothesis that H.pylori eradication reduces the incidence of peptic ulcer bleeding. Patients who have been recruited into the study will be informed of the trial results by letter once these are available, as will all participating GP practices. The main primary outputs of the analysis will be scientific papers/posters covering both the medical and procedural aspects of the study. The University of Nottingham intends to publish the results of the HEAT Study in a major scientific journal (such as The Lancet), and will also present details of the study at relevant scientific meetings. For example, the methodology for the study was presented at the Digestive Diseases Federation Conference in London in June 2015 and at the United Gastroenterology Week Conference in Barcelona in October 2015.
The final results of the study, for which the NHS Digital data will be used, will be expected in early 2020 for publication in The Lancet, and these results would be presented at BSG national (and potentially international) meetings. As this study is endpoint-driven, the University of Nottingham require hospitalisation / ulcer bleed data regularly throughout the course of the study, as this will help to determine a more accurate end date, based on event rates. There will also be a report for the funder and sponsor at the end of the trial, which is currently due in January 2020.
All outputs from the study would only include aggregated summaries, with small numbers suppressed in line with the HES Analysis Guide and no patient-level identifiable data would be used.

Processing:

The trial data are controlled by University of Nottingham as Sponsor of the study, but TCR Nottingham have been contracted as the data processor, who store and handle the data on the HEAT database (the Managing Director of TCR securely transfers data to and from NHS Digital, as per the Data Sharing Agreement). The HEAT database is stored on an N3 server within the N3 network based at Nottinghamshire Health Informatics Service (formally King’s Mill Hospital Data Centre). Authorised study staff can access the data via remote access to the server but the data is not removed from the server. TCR Nottingham manages all access permissions which are set on a per-person basis. Only relevant members of the study team would have access to the data provided by NHS Digital. The study team and trial statistician are all substantive employees of the University of Nottingham. TCR Nottingham provides two levels of access to the data for staff at University of Nottingham: (i) the full identifiable data is accessible only to 2 individuals for the purpose of facilitating follow-up contact, and (ii) data stripped of identifiers except for initials to mitigate risks of quality errors arising from transposition errors if using only a study screening number. The study screening number is assessable to the research team and only this level of data is used in analyses.

The University of Nottingham will be making several sequential applications for data from NHS Digital to support follow up activities (the patients' NHS number and date of consent will be provided to NHS Digital, to request details of any hospital admissions or deaths since the patient consented to participate).

The primary endpoint for this trial is a hospitalisation for an ulcer bleed therefore; details of hospital admissions that trial patients experience (i.e. HES data) are required from NHS Digital to ensure that no potential endpoints are missed. Data on hospitalisations will be reviewed and, if it is deemed that a potential endpoint has occurred, then further details will be collected (directly from the medical notes of the admitting hospital) and the event will be adjudicated by a blinded Adjudication Committee (like the trial subjects and investigators (see above)) members of the committee do not know the identity of each subject’s randomised treatment.
The University of Nottingham require all the relevant fields within HES, and cause of death data from ONS, because as part of the secondary analysis of this study, a health economic analysis will be performed comparing many quality of life factors in both arms of the trial (e.g. the cost effective benefit of intervention; length of hospital stay types of services accessed, and other related medical events). For the secondary analysis HES data on all reasons for admissions are required in order to study the impact on other health conditions. To inform the economic analysis it is important to consider the route of admission (elective investigation versus emergency).
Data minimisation has been considered and as part of that process, a health economist has reviewed the list of fields available from HES and confirmed which are required. This is a considerable number of the data fields available, to enable our health economist to accurately estimate the cost to the NHS of each admission. To obtain the HES and ONS data, the Data Processor will send a list of randomised patient study IDs and NHS numbers, along with dates of consent, and request that NHS Digital provides information on hospital admissions or deaths of patients since their date of consent. This will be returned by NHS Digital to the TCR (Nottingham) Ltd securely, and linked to study ID and NHS number (we require two identifiers to be provided, to ensure that there are no transcription errors, and that the correct events are allocated to the correct patient).

The trial will not directly link GP records and HES data. At individual patient level, the HES data will be compared with the HEAT database to determine the extent of discrepancies between the detail in the HES data and the data derived from the GP records.

All processing of ONS data will be in line with ONS standard conditions.

There will be no linkage with other record level data.

MR1185 - DOES THE PRESENCE OF THROMBOPHILIA INCREASE THE RISK OF DEVELOPING IDIOPATHIC PULMONARY FIBROSIS? — DARS-NIC-148215-CQWFM

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - consent provided by participants of research study, Identifiable, Yes, 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(7), Health and Social Care Act 2012 – s261(7)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2010-05-10 — 2020-05-09 2016.05 — 2020.03. breached contract (and anonymisation code) — audit report.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

  1. MRIS - Cohort Event Notification Report
  2. MRIS - Cause of Death Report
  3. MRIS - Flagging Current Status Report
  4. MRIS - Members and Postings Report
  5. MRIS - Personal Demographics Service

Objectives:

Does the presence of thrombophilia increase the risk of developing idiopathic pulmonary fibrosis?

a) Are defects associated with an increased tendency to clot a risk factor for developing IPF.
b) Does the presence of a thrombophillia modify the association of environmental risk factors for IPF?
c) Does thrombophillia worsen the prognosis of patients with IPF?

Evaluating protocols for identifying and managing patients with FH — DARS-NIC-115405-P6X6Q

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2018-11-08 — 2020-11-07 2019.05 — 2019.05. breached contract (and anonymisation code) — audit report.

Access method: One-Off

Data-controller type: UNIVERSITY COLLEGE LONDON (UCL), UNIVERSITY OF NOTTINGHAM, UNIVERSITY OF YORK

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Outpatients
  4. Hospital Episode Statistics Accident and Emergency (HES A and E)
  5. Hospital Episode Statistics Admitted Patient Care (HES APC)
  6. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

Familial Hypercholesterolaemia (FH) is a common inherited cause of raised cholesterol, affecting up to 320,000 people in the UK. However, over 80% of individuals are not identified, leading to many avoidable heart attacks and early deaths. Use of cholesterol lowering medication can prevent over half of these premature heart attacks.

National (NICE) guidelines recommend general practitioners (GPs) identify people with possible FH by using cholesterol levels, family information and physical examination. If FH seems likely, the GP should refer patients to a specialist to confirm diagnosis, usually by genetic testing. If FH is confirmed, treatment should be given and their relatives contacted for genetic testing – known as “cascade” testing.

Implementation of NICE recommendations for cascade testing FH has been very limited to date. Existing cost-effectiveness analyses of FH identification protocols (UK and internationally) have focused on whether or not specific protocols for cascading are cost-effective. Commissioners and policy makers are uncertain about whether current designs for cascading programmes represent the best value for money. In particular, they have questioned whether tighter criteria for cascading could offer better value for money, and whether current service designs offer value for money in terms of maximising the number of relatives tested. This reflects recognition amongst commissioners and policymakers that previous cost-effectiveness results were subject to significant limitations and evidential uncertainties. Department of Health, through NICE, recognised this gap leading to a scoping review by the NIHR Health Technology Assessment (HTA). As a result NIHR HTA commissioned this current NIHR project to address these limitations by comparing a wide range of protocols for cascade testing and addressing a wide range of evidential uncertainties and develop economic models to evaluate the cost-effectiveness of cascade testing in the NHS with the aim of informing the implementation of the most cost-effective and acceptable protocol of care for these patients. This project relies on using existing cohorts and registries, routine NHS data and secondary care service data to inform the parameterisation and structure of the models.

The study team propose in this programme of research to evaluate treatment patterns and short- and long-term cardiovascular outcomes and the NHS costs of patients with FH. The outputs of this linkage request will result in providing the most accurate and up-to-date outcome of FH patients to date. Data on cases managed in primary and secondary care will be linked to data on treatment patterns and cholesterol response. This will provide a rich and accurate source of information to parameterise and inform the structure of the short and long-term economic models, the main deliverable within the HTA programme of work. In order to do this, the study requires Hospital Episode Statistics Accident & Emergency, Hospital Episode Statistics Outpatients, Hospital Episode Statistics Admitted Patient Care. The study has requested multiple years of data to make sure it can model the full life-course of an FH patient, to include both their outcomes across follow-up and health care utilisation. Only then, can the study address all the current gaps in the evidence and capture all events in secondary care as well as conduct economic costing on a patient's health care utilisation over an extended period of time. This means this source of data will be essential in developing the most robust economic model outcomes to inform commissioners and policy-makers on the impacts of various cascade screening strategies as accurately as possible.

Below are all the stakeholders that are involved with the project, with detail as to their activities for the purpose of this project. There is no work in this programme of research taking place outside the UK. All processing activities are within bona-fide UK academic institutions which abide by the highest levels of Data Protection laws and Information Governance rules. No data or specific tools/analysis involving usage of data will be shared with any third parties. Only publication output on the aggregate results of the analysis will be widely disseminated in peer-reviewed journals, conferences, reports, and official HTA monograph.

University of Nottingham: This is the lead organisation submitting the application and carrying out the research. Their role is as a Data Controller given the remit and aims of the project and as a Data Processor as they will receive the pseudonymised dataset from UCL and will conduct the analysis from the linked data (Simon-Broome Registry to HES).

University of York: This is a collaborating institution carrying out the research. Their role is as a data controller given their involvement in the aims and remit of the project and as a Data Processor as they will receive the pseudonymised dataset from UCL and will conduct the analysis from the linked data (Simon-Broome to HES).

UCL: This is a collaborating institution. They are the data guardian and Data Controller for the consented Simon-Broome registry dataset. They will submit the patient identifiers to NHS Digital for linkage of the Simon-Broome to requested HES datasets and receive the pseudonymised linked dataset from NHS digital.

HeartUK: This is a charity involved in promoting the Simon-Broome registry database and follow-up studies using the cohort. The steering group at HeartUK oversees and approves access to use the Simon-Broome registry for research in the public interest. They are not a Data Controller or Data Processor as they will not process, control, or store any of the data and not involved with the aims the research. It provides the forum (I.e. meeting space in London) for hosting the Simon Broome steering group (members are UK academics).

BHF: The British Heart Foundation support patient involvement and will support dissemination of the aggregated results and publications. They are not a Data Controller or Data Processor. They will only see aggregated data with small numbers suppressed (in line with the HES Analysis Guide) in the final report once published, and any publications and dissemination via conference presentations, posters, etc.

Expected Benefits:

Benefits to patients from this data release
If patients with familial hypercholesterolaemia (FH) are not identified they can die at an early age from myocardial Infarction and other cardiovascular disease. It has been well-established that patients with FH who are not diagnosed and treated will have a 50% chance of coronary mortality by 50 years of age in men and 60 years of age in women. At a population level, the UK is incredibly poor at diagnosing FH with close to 80% under diagnosis. This accounts for anywhere from 120,000 to 180,000 individuals currently in the general population who do not know they are affected. Hence, improving the current low detection rate of FH is urgently needed. One of the most cost-effective solutions is to develop protocols of efficient cascade testing to identify affected relatives, especially younger relatives, and to initiate early statin treatment to lower LDL cholesterol will prevent and reduce premature mortality, and long-term coronary morbidity. Available service data highlight the major extent of the problem. National audits show only around one affected relative is identified for each index case. To improve identification and health outcomes for these patients, evidence-based protocols need to be implemented. This data release of using one highest quality and well-established FH disease registries known internationally and linking outcomes to HES will provide the longest follow-up to date. This will allow for novel research to be generated on the long-term outcomes for patients affected by FH and the impact of treatment in real-world settings (as knowledge of impact of treatment for FH is limited to trials). Many patient representatives who themselves have FH, from partner charities, Heart UK and the British Heart Foundation, have expressed a dire need to understand the effectiveness of treatment on long-term outcomes and how these outcomes can inform the development of more effective and efficient ways to cascade screen for relatives.

Benefits to health care practitioners on data release
Many health care practitioners, in particular in primary care commissioners, are still unaware of the magnitude of under-diagnosis, how to identify, or manage FH in current clinical practice. The research outputs, once published, will improve awareness among practitioners and patients, leading to improved compliance anticipated by 2022. Further, the economic model will improve the identification of FH through revised shared care protocols to be reviewed by the next NICE review of the FH guidelines 2024, leading to commissioning of evidence-based FH cascade screening programmes and, ultimately, saving lives.

Benefits to the policy-makers and NHS commissioners from this data release
Cascade testing recommendations exist for the UK but policy-makers have acknowledged they do not reflect the current evidence base, which has evolved significantly since guidance was issued in 2008. Hence, this research project was commissioned by the Department of Health and HTA. There is significant uncertainty regarding whether cascade testing is cost-effective and how it should be implemented. As a result, cascade testing protocols are often piecemeal with variable implementation of services in the UK. To support commissioners deciding on whether to implement a new cascade testing service, or modify an existing service, there is an urgent need for new cost-effectiveness modelling that collates and synthesizes the best available current evidence, evaluates the overall impacts of cascade testing for all affected individuals and answers key questions about how the service should be designed to offer the best possible value for money.

These outputs, which are expected to be published in by 2021, will allow the identification of the most cost-effective design for a FH cascade testing protocol in the NHS which will likely result in a change in the current ways cascade testing in implemented in the UK. The project will inform future NICE implementation for FH cascade testing based on the economic model, to support analysis of the cost, outcomes and savings associated with implementing FH cascade services at local level. Combined with findings from the proposed qualitative research, this work will provide valuable practical information to health care decision makers involved in commissioning or running FH services regarding the appropriate use of NHS resources.

Outputs:

Outputs of the research
The main result (outputs) will be the parametric survival regressions for economic modelling and the cost of hospitalisations. Whilst individual patient level data is required to assist with populating the model, the data used in the modelling is not identifiable as. The data will be used to generate predictions of the proportion of individuals experiencing relevant clinical events over time within the economic model and their costs. This will allow estimates of lifetime costs and QALYs to be generated by the model. The models, along with a full representation of their uncertainty (derived using the variance-covariance matrix for each event) will be incorporated within the model. Outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide.

As well as completing NIHR HTA monograph (expected publication date in 2021), standard dissemination strategies, of peer-reviewed open access primary care, public health, cardiovascular and genetic publications and conference presentations, will be further prioritised. The project will target submitting its work high impact medical journals such as the British Medical Journal, European Heart Journal, Heart, Atherosclerosis, Circulation, or JAMA (the Journal of the American Medical Association) in 2020. No personal data will be used in the write-up or publication of results. Descriptive statistics will only be at the aggregate level with small numbers suppressed in line with HES analysis guide.

Target audience of outputs
The audience of the research outputs are patients, the public, charity groups, policymakers at the Department of Health, Public Health England, NICE. These outputs (publications, reports, monographs) will be made open access (freely available) to all audience members at the end of the study (likely to be 2021). No outputs will be used for any commercial purposes.

The project will ensure that findings are highlighted to the public, patients, and policymakers (NHS, Department of Health, Public Health England and NICE) in partnership with third sector voluntary organisations (Heart UK and British Heart Foundation - BHF). The project has bi-annual meetings with HEART UK and BHF to keep them updated on the study progress and any new potential findings, and having early conversations with Department of Health and Public Health England on a dissemination strategy. This will likely involve a published NIHR Signal in 2021. In the UK, the data controllers are active current contributors to NICE guidelines for FH and will ensure the outputs of this cost-effectiveness analysis inform updated NICE guideline recommendations and quality standards.

The project will also work with the International FH foundation, US CDC Office of Public Health Genomics and European collaborators, and international advisers in Australia, USA and Europe to ensure the analysis informs international guidelines recognising potential differences between international settings. These discussions will occur at the end of the study in 2020 when the project has economic models developed.

All outputs and publications contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide.

The project will support Heart UK to organise patient and health professional focus groups to help refine findings and produce digital dissemination strategies (e.g. involving website, email, Facebook, Twitter or similar). This will occur towards end of the study in 2019-2020. The project is running some 2-3 consensus development groups with HEART UK/BHF in 2020 to interpret and analyse the findings from a patient and stakeholder prospective. Working closely with HEART UK and BHF, the project will develop a disseminate study from the study to the wider public by:

- Networking with existing and potential FH service commissioners across England, e.g. national NHS commissioners workshop
- Presenting study findings in a way that makes sense to managerial and commissioning audiences, e.g. publish articles in NHS professional and health service commissioner journals
- Sharing learning of early implementers of FH services
- Scoping the possibility of producing a FH toolkit incorporating advice on FH service design and a revised costing template for FH services that is generalizable to the English NHS, based on CCG geographies.

The project anticipates that the dissemination strategy will be fully implemented in 2021, with all the publications in the public domain.

Processing:

Data Flow Process
The Simon-Broome register is a register of consenting patients held at University College London (UCL) within their data safe-haven. UCL is the Data Controller for the Simon-Broome Registry. The original Simon-Broome data set includes identifiable variables which will be provided to NHS Digital by UCL for linkage to HES - forename, surname, date of birth, NHS number, postcode, unique study identifier. Gender will also be provided for analysis, and ethnicity is permitted on the same basis. This process is in line with the other current study which includes ongoing linkage of the Simon-Broome data set to Civil Registrations (Deaths) data (NIC 300282), though there will be no linkage between the data released under the different agreements. NHS Digital will then conduct the linkages to the HES datasets (Admitted Patient Care, Accident and Emergency, Outpatients) and return the linked pseudonymised data to UCL removing all the identifiable variables in the Simon-Broome dataset of forename, surname, date of birth, NHS number, postcode and gender. UCL will store the dataset in their safe-haven.

As the cohort is already flagged by NHS Digital for NIC 300282, there will be no new flow of identifiers for this agreement.

Linkage of the HES data to any other dataset, including data released under a different agreement, is not required or permitted under this agreement.

UCL will send a copy of the pseudonymised dataset to the Universities of Nottingham and York, as per the approved secure data transfer protocol specified in the CAG support, ethics approval and HTA protocol.

Data access
All HTA research team members involved with accessing, processing, and analysis of the data are directly employed staff members by their respective institutions (University of Nottingham, University of York, and University College London). There is no data access or processing activities occurring outside of the UK.

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

QResearch Data Linkage Project — DARS-NIC-376367-M5V9H

Type of data: information not disclosed for TRE projects

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

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

Purposes: Yes (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2017-09-26 — 2020-09-25 2017.06 — 2019.01. breached contract (and anonymisation code) — audit report.

Access method: Ongoing

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Outpatients
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Critical Care
  5. Hospital Episode Statistics Accident and Emergency (HES A and E)
  6. Hospital Episode Statistics Admitted Patient Care (HES APC)
  7. Hospital Episode Statistics Critical Care (HES Critical Care)
  8. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The HES data are requested to link to the existing QResearch database so that it can be used for medical research. The HES patient level data linked to QResearch is only accessed by academics employed by University of Nottingham on site at the University of Nottingham. However the researchers involved in a given project (contributing to the research question, design, interpretation and writing of the paper for publication but not handling the data) may be employed by other UK universities. The HES data stays on site at the University of Nottingham and are only handled by University of Nottingham staff and the data processor contracted to the University of Nottingham. The University of Nottingham may have a collaborator at another university on the project team advising on clinical aspects or interpretation of findings, but they will not receive any data. In addition, the external research may initiate a project but the analysis will be done by University of Nottingham staff with the data located at the University of Nottingham.

Only University of Nottingham staff and their data processor will have access to HES record level data and outside researchers will only have access to tabular outputs. HES record level data are not shared with researchers outside of the University of Nottingham. Small numbers are suppressed in line with the ICO guidance.

The QResearch database consists of the coded pseudonymised electronic health records from primary care patients registered with approximately 1,000 general practices spread throughout the UK. The QResearch organisation is a not for profit collaboration between the University of Nottingham and EMIS. The database is widely used for medical research into the causes of disease, its natural history, treatment and outcomes. QResearch was started in 2003 and will continue for the foreseeable future. In addition to coded data from the GP electronic record, the QResearch database also contains the linked cause of death derived from the death certificate data and cancer registration data supplied by the Office of National Statistics following approval by Trent MREC and Secretary of State for Health. The data linkages for QResearch were extended in 2011 to include additional health information from secondary care including HES. The additional HES linked data enables researchers to analyse additional information on patient characteristics, treatment and outcomes which will improve the epidemiological analyses of studies since the data will be more complete. Without the data linkage, for example, research studies may under-estimate the risk and benefits associated with interventions such as prescribed medicines.
The QResearch database linked to HES data is used for research to develop and validate risk prediction algorithms such as QRISK2. QRISK2 is a risk prediction algorithm which calculates an individual’s risk of a heart attack or stroke taking account of their individual risk factors such as age, sex, ethnicity, clinical values and diagnoses. The research describing the derivation and validation of QRISK2 has been published in the BMJ (2008). The software implementing QRISK2 is available as open and closed source software. QRISK2 is recommended by NICE as the risk score for use in its guidance on lipid modification (2014). It is also recommended for use in the NHS Health Check.

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.

The criteria and process for access to the QResearch database are published on the QResearch website (http://www.qresearch.org/SitePages/Informationforresearchers.aspx).

Applications for linked HES data linked to QResearch GP data are restricted to academics employed by University of Nottingham to undertake research. At least one member of the research team must be a medically qualified academic registered with the General Medical Council who signs the guarantee. Eligibility of applications is assessed according to the following criteria.
• You agree NOT to attempt to identify patient(s) or practice(s)?
• You undertake to provide a copy of the final report of the project and copies of any publications within one year of the project completion?
• You agree NOT to release the data to any third party including the funder, sponsor or other such body?
• You agree not to use the data for any other project except that which is expressly described in your protocol
• Do you have a statistician on the project team who has contributed to the design of the study and will advise on the analysis?
• Is the research a benefit to the UK Health and Social care system
If an application does not meet these criteria it would mean that application would be rejected and the data would not be shared.

For studies requiring access to the QResearch primary care data linked to HES, then the same eligibility criteria are applied. However the linked HES data are not disclosed but remain on the servers at the University of Nottingham with analyses undertaken by the team at the university.

Researchers originate a research question or hypothesis; write an outline protocol; and contact QRESEARCH to discuss the feasibility of undertaking the study. If the study is feasible, QRESEARCH will give a broad estimate of the costs of providing the data and will provide a letter to accompany any application for funding. The researcher then secures the necessary funding and completes the QRESEARCH application form, including a detailed protocol and data specification. This application is sent for scientific review and feedback is given to the researcher. The researcher makes any necessary modifications to the protocol and approval is obtained, the researcher is given a timescale for the data extraction. Once the researcher has the data, they have to approve it within one month of receipt.

Yielded Benefits:

The results of research undertaken continues to result in new knowledge and understanding regarding disease epidemiology, health inequalities, drug safety, methods of identifying patients at high risk of serious illnesses. Every year new research is published in high impact international research journals such as the British Medical Journal and the British Journal of General Practice. The research is ongoing with target dates for individual projects rather than one overall target date. A complete list of research papers using QResearch database is published at http://www.qresearch.org/SitePages/publications.aspx There are many benefits arising from this research - some examples are listed here. QRISK, which the applicant continues to develop and enhance, has become the preferred cardiovascular risk assessment tool used across the NHS. It is implemented in every GP practice, used extensively in NHS Health Checks, and a variant is used for the NHS Choices 'Heart Age' tool. It was recognised as an outstanding impact case study in the Research Assessment Exercise in 2014. Use of QRISK2 has led to targeted interventions to reduce CVD risk as shown in NHS health check research published in BMJ Open in 2016. In response to nationally identified NHS needs, the applicant has developed & updated a suite of risk prediction tools to identify patients at high risk of an adverse condition for intervention to improve outcomes. Many of these tools are recommended in policy, NICE guidelines & widely implemented in clinical practice. Examples include three risk assessment tools known as QFracture, QDiabetes and QAdmissions. 1. The QFracture tool which assesses risk of fracture has been recommended in NICE guidelines on fracture prevention (August 2012). It is the preferred tool in the NICE quality standard (2016) & SIGN in Scotland. It was included as a quality indicator within the GP Quality and Outcomes Framework in 2013/4. The tool is integrated in over 4,300 GP practices. It helps identify patients who have a high risk of fracture who can then be offered interventions to reduce their risk of a fracture. This is especially important for elderly patients for whom a osteoporotic fracture can be life changing or life limiting. 2. QDiabetes is recommended by 2012 NICE guidance on diabetes prevention & used to identify patients for the national Diabetes Prevention Programme for interventions to reduce risk of type 2 diabetes. Interventions to reduce diabetes risk will have benefits for the individual patient who may otherwise have developed diabetes. Reducing the incidence of diabetes is also likely to have a wider benefit for the health system given the high work load and costs associated with caring for people with diabetes. 3. Research on identifying patients at high risk of emergency hospital admissions led to the development of the QAdmissions risk assessment tool. This tool is recommended by 2016 NICE guidance on co-morbidity & is used to delivery NHS England's unplanned admissions Designated Enhanced Service by identifying those at high risk of emergency admissions for targeted interventions to reduce their risk of having an emergency admission. This is important since emergency admissions are distressing for the patient and their families but also put strain on the NHS. It will also help GP practices to identify frail older patients as required by the new changes to the 2017 GP contract. Research into the early diagnosis of cancer was awarded the 2012 Royal College of General Practitioners (RCGP) paper of the year category. It also led to implementation of new risk assessment tool in over 4300 GP practices to improve early diagnosis of cancer, in partnership with Macmillan Cancer Support. It also led to professor Hippisley-Cox becoming an expert witness to the All Party Parliamentary Group on Pancreatic Cancer (2012, 2017) which produced high profile recommendations on how to improve early diagnosis of pancreatic cancer. Patients who are diagnosed with cancer at an earlier stage have a better chance of accessing treatment which is capable of improving survival and quality of life. Research on the safety of antidepressants has been published in the British Medical Journal and research on how it could be used to improve prescribing decisions for antidepressants in primary care is supported as part of the new NIHR funded Biomedical Research Centre in Nottingham (2017-2022).

Expected Benefits:

The results of research undertaken continues to result in new knowledge and understanding regarding disease epidemiology, health inequalities, drug safety, methods of identifying patients at high risk of serious illnesses. Every year new research is published in high impact international research journals such as the British Medical Journal and the British Journal of General Practice. The research is ongoing with target dates for individual projects rather than one overall target date.

A complete list of research papers using QResearch database is published at http://www.qresearch.org/SitePages/publications.aspx

Research arising for the QResearch database including the linked data has been used to inform national policy. For example, research findings have been included in NICE guidelines on fragility fracture, diabetes, suspected cancer and lipid modification. Research findings have informed the NHS Health Checks programme and Department of Health guidelines on health checks.

Examples of ongoing research include assessment of the safety of antidepressant drugs and novel anticoagulants; investigation of potential links between diabetes drugs and cancer; quantification of the risk of thrombosis associated with various types of the oral contraceptive pill.

Outputs:

The outputs are research papers which are published in peer reviewer academic scientific journals and presented at academic conferences. The results tables within the papers will only contain statistical information with cell counts of > 5, being suppressed in line with the ICO code on anonymisation. Outputs will contain aggregate level data with small numbers suppressed in line with the HES analysis guide.

No indicators are produced which show performance of an organisation – indeed the identity of the GP practices contributing to QResearch are not shared with any third party.

Processing:

The HES data is linked to the QResearch database at individual patient level using a pseudonymised version of the NHS number which has been supplied in both GP data and the HES data. No strong patient identifiers are received by QResearch as the data is pseudonymised-at-source and at HSCIC. Date of birth is rounded to year of birth.

The resulting data are then used for undertaking primary research. The linked HES-GP data are only accessed by approved research staff with substantive contracts employed by University of Nottingham and its contracted data processor. Data is only processed on site on secure servers at the University of Nottingham. No individual level data will be shared or stored outside the University of Nottingham or supplied to any third party.

As described in the section above, the QResearch database is also linked to ONS mortality and cancer registration data. The database was first linked to ONS mortality data in 2007 and ONS cancer data in 2011. The data fields received from ONS mortality data are: pseudonymised NHS number; year of birth, date of death; ICD10 cause of death. The ONS cancer data includes pseudonymised NHS number; sex; year of birth; date of death; diagnosis date; cancer site and type; cancer stage and grade; cancer behaviour; cancer diagnosed only on death certificate; cancer treatment (surgery, hormone, chemotherapy, other).

In theory it would be possible to link additional datasets to the QResearch database though this would require consultation with the QResearch advisory board, the ethics committee, the confidentiality advisory group. It would also require amendment to the data sharing agreement with the HSCIC.

Evaluation of the Safe At Home safety equipment scheme — DARS-NIC-50919-D5R5D

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Anonymised - ICO Code Compliant, No

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

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2017-08-01 — 2020-07-31 2017.09 — 2017.11. breached contract (and anonymisation code) — audit report.

Access method: One-Off

Data-controller type: SWANSEA UNIVERSITY, UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)

Objectives:

During 2009-2011, the Department for Education funded an £18 million scheme in England to provide safety education and equipment to the poorest families with children under 5. The scheme (Safe At Home) was overseen by the Royal Society for the Prevention of Accidents (RoSPA) and led by local authorities. It included the provision of equipment such as stair gates, fire guards and cupboard locks to over 66,000 families. To date, the effectiveness of this scheme in preventing child injuries from occurring has not been analysed on a national scale.

The aim of the study is to determine if the Safe at Home scheme was associated with the following in children under age 5:
1) a reduction in hospital admissions due to unintentional injuries of any type likely to have occurred within the home
2) a reduction in hospital admissions due to unintentional injuries likely to have occurred within the home that could plausibly be prevented by the equipment provided by the scheme (e.g. falls down stairs, fire burns, poisoning)

The study will also determine if the scheme:
1) was cost-effective as delivered (targeted at the most deprived areas) and
2) would be cost-effective if implemented in ‘lower risk’ populations e.g. those with lower baseline injury incidence or residing in more affluent areas

The HES data will be transferred in full, by NHS Digital, to the SAIL databank/UK SeRP at the Swansea University, where data will be processed and analysed. The HES data will be merged with home safety equipment supply data using Lower Super output area fields in both datasets. PEDW data from Wales, available in SAIL, will be used also to provide some of the control population. Access to the HES/PEDW/equipment supply data by researchers at the University of Nottingham will be via the secure platform connection to SAIL databank/UK SeRP.

Results will only contain aggregated data with small numbers suppressed in line with the HES analysis guide. The analysis will be undertaken at Lower Super Output Area (LSOA) level and results we be presented at LSOA, Clinical Commissioning Group (CCG) and Local Authority level. This is because CCGs and Local Authorities (Public Health and Social Care) commission health and social care interventions and so the results will need to be presented in a way that is relevant to them.

Outputs will be reported in peer-reviewed academic journals and then disseminated further through professional publications, conferences and public dissemination routes.

The number of years of data requested is from 2003/4 to 2015/16. This number of years will provide adequate study power and achieve a sample size of 72 time points recorded on each lower super-output area; that is 6 times per year for the 5.25 years prior to the intervention, 2 years during the intervention delivery and 4.75 years after the intervention between January 2004 to December 2015. This sample provides at least 85% power to detect an effect size of 0.5 for autocorrelations up to values of 0.5.

The data fields requested are restricted to those that are specific to the analysis that will be undertaken, with the primary outcome of injury admission rates in the intervention versus the control areas.

The data requested is only the episode where age at start of the episode is under the age of five.


The HES data from NHS Digital will enhance what the applicant knows about the effectiveness of this type of scheme. Until now effectiveness of home safety equipment provision has only been assessed at the local level (e.g. local evaluations) and as such, there is no robust effectiveness and cost effectiveness data. The National Institute for Health and Care Excellence, NICE, currently recommend that local areas commission home safety equipment provision schemes for families with young children and on the lowest income levels, based on local evaluation data. The results may therefore inform future NICE guidance, depending on the outcome of the analyses.

None of the work will take place outside of England and Wales. These data will not be used for commercial purposes. Data will not be provided, at record level, to any third parties and will not be used for direct marketing.

HES data from NHS digital will only be used for the purposes stated within this agreement.

Expected Benefits:

The National Institute for Health and Care Excellence (NICE) have developed public health guidance on home injury prevention in children: PH29 (unintentional injuries: prevention strategies for under 15s) and PH30 (Unintentional injuries in the home: interventions for under 15s). In these publications NICE recommend that commissioners of health and social care services provide local safety equipment schemes for families most in need (on low incomes and with children under 5). The results from this analysis will inform future updates of this guidance and will provide additional health economic / cost effectiveness data that does not currently exist. This will be achieved by members of the study team sharing the results of the study with the National Accident Prevention Strategy Group which they sit on with Public Health England who are reviewing the child accident prevention guidance, in conjunction with NICE. Members of the study team also sit on the advisory group for this work. This is in addition to usual publication in peer reviewed journals and media engagement when the studies are published.

The results will also inform the commissioning of home safety equipment schemes via the direct dissemination methods to CCGs and Local Authorities. This dissemination will happen via the Faculty of Public Health (individuals from the study team are members and will share the findings via special interest groups in child health and injury prevention) and via the Royal Society for the Prevention of Accidents who are part of the study group and have access to a large practitioner audience nationally and internationally.

The results may indicate that the scheme is not likely to be effective, in which case NHS and Public Health funding should be used to commission alternative injury prevention programmes that are shown to be effective.

If however the study indicates that provision is effective and cost effective it would inform a strong case for local areas to commission schemes in the future. After national funding ended, most areas stopped providing equipment at that time.

Outputs:

The project described in this application will lead to at least two published papers (a 'clinical' effectiveness paper and a cost effectiveness paper) in peer reviewed journals, plus dissemination at the National Society for Academic Primary Care and Safety 2018 world conferences and other professional networks (e.g. via RoSPA). It is anticipated that the papers will be submitted for publication by July 2018 as this is a 12 month study, commencing summer/autumn 2017. Papers will be submitted to British Medical Journal, BMJ Injury Prevention, and Journal of Public Health. There is funding for at least one open access publication which would be free for anyone to read.

Research summaries/briefings will be specifically targeted at commissioners within CCGs and Local Authorities who are the most likely to commission population-level safety equipment schemes and work with Public Health England and the National Institute for Health and Care Excellence to disseminate their findings in evidence reviews that they produce. A lay summary of the research will also be produces and, via the communications teams at the universities of Nottingham and Swansea disseminate this to the media and to RoSPA for their dissemination to parents.

Outputs will contain only aggregate level data with small numbers suppressed in line with the HES analysis guide. Results will be presented at Local Authority and Clinical Commissioning Group level as these are the footprints for current commissioning arrangements for health (NHS), Public Health and Social Care services. It would be aimed at Public Health Consultants, GPs, Commissioners and third sector organisations who may provide equipment on a charitable basis.

The study team will work with patient public representatives and the 3rd sector (e.g. The Royal Society for the Prevention of Accidents (RoSPA) and Child Accident Prevention Trust (CAPT) to develop dissemination materials for local authorities and CCGs to help them ensure that commissioned services are designed to maximise injury prevention. The findings will also be used by the applicant to support an NIHR programme grant application in 2018 on the implementation of child injury prevention programmes.

The dataset itself used in the analysis will not be made publically available and no analysis tools will be generated.

Processing:

Pseudonymised, non-sensitive record level HES data will be transferred from NHS Digital to the SAIL databank/UK Secure e-Research Platform (UKSeRP) for secure storage, processing and statistical/health economic analysis. The legal basis for this is Section 261(1) of the Health and Social Care Act.

The SAIL Databank is now powered by the UK Secure e-Research Platform (UKSeRP), developed by the Health Informatics Group at Swansea University, with support from the Farr Institute of Health Informatics Research funded by Medical Research Council. UKSeRP, a is high powered data management and sharing technology, is infinitely scalable to suit a range of use cases including imaging, genomics and analysis of free text. It benefits from carefully designed Information Governance to ensure person-based data with high privacy risk is managed to the highest standards, and is ISO 27001 certified.

The HES data will be merged in SAIL with home safety equipment supply data using Lower Super output area fields in both datasets. PEDW data from Wales, available in SAIL, will be used also to provide some of the control population. The home safety equipment dataset contains no individually identifiable level data. It is non-sensitive scheme activity data supplied by RoSPA to the SAIL databank. There will be no record level linkage and we are not asking NHS Digital to do the aggregated linkage of RoSPA LSOA level data and HES data. There will be no attempts by the study to identify any individual.

The primary analysis is a controlled interrupted time series analysis with injury rate data points at Lower Super Output Area (LSOA) level. Because injuries are more common in deprived areas, differ between boys and girls and by child age, control areas will be matched on how rural or urban the area is (using Office for National Statistics classification at LSOA level), deprivation, sex and age profiles. As the scheme was implemented in England only and in households with the lowest income and in areas with the highest injury rates, the study will need to supplement the pool of potential control areas with areas of similar levels of deprivation and injury rates in Wales using the PEDW data (the scheme was not implemented in Wales).

Intervention (England) areas will therefore be matched at LSOA level to control areas (England and Wales) on rurality (ONS classification), deprivation, sex and age profiles.

The rates of injury-related hospital admission will be compared in the intervention and control areas before, during and after the scheme’s implementation using an interrupted time series analysis. The applicant will undertake a cost-effectiveness analysis, estimating the incremental cost per hospital admission averted and determine if the cost-effectiveness of the scheme varies according to the level of deprivation of the areas it is implemented in.

The hypothesis is that provision of home safety equipment prevents injuries in children that require hospitalisation and that the provision is cost effective to the public sector.

Data will not be accessible by any parties other than substantive employees of the Swansea University (SAIL databank/UKSeRP) and substantive employees of the University of Nottingham (accessed via remote secure platform connection).

MR1006 - Gedling Lung Health Study — DARS-NIC-147783-6T2MW

Type of data: information not disclosed for TRE projects

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

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Consent (Reasonable Expectation); Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive, and Non Sensitive

When:DSA runs 2022-01-05 — 2023-01-04 2018.03 — 2017.05. breached contract (and anonymisation code) — audit report.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Personal Demographics Service
  4. MRIS - Scottish NHS / Registration
  5. MRIS - Flagging Current Status Report
  6. MRIS - Members and Postings Report

Objectives:

The data supplied to University of Nottingham will be used for the approved medical research project - MR1006 - Gedling Lung Health Study

Yielded Benefits:

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.

University of Nottingham have published over 25 research papers using data from this cohort, a list of the publications made since the use of ONS data in 2007 are detailed in the Yielded Benefits. University of Nottingham researchers have been able to combine the dietary details on half of the cohort linked with data from cohort members' GP electronic record and created a database that can be used for research. Together with the data collected in 1991 and 2000 in the face-to-face research visits within the cohort, a rich dataset with which to investigate a wide range of research questions has been obtained, as set out in the University of Nottingham's previous application. The aim is to continue to publish using the GP data on a wide variety of research questions, in particularly on respiratory health effects on long-term survival. The yearly updates on mortality are increasing the ability to examine outcomes of mortality and cancer. Currently the youngest members of the cohort are around 67 years old, meaning an increased likelihood of certain health outcomes for researchers to examine.

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.

Mortality and cancer registry data are being requested. University of Nottingham have previously supplied the names, dates of birth, and most recent known address of the cohort of people that were originally studies in 1991 to NHS Digital. The NHS Digital data is received and linked to the Gedling cohort dataset. The University of Nottingham are the sole data controller/processor and no other organisations are involved in processing the data.

Data analysis
As describe in this application, data can be analysed using a detailed fatty acid database to produce estimates of individual saturated, omega-3 and omega-6 fatty acid intakes in relation to the prevalence and incidence of common medical diseases linked to diet and obesity including acute respiratory infections, cardiovascular disease (blood pressure, angina, and myocardial infarction), cancers, diabetes, rheumatoid arthritis and liver disease. In addition, the effects of other factors in diet will also be investigated in relation to common medical outcomes. The analyses will be conducted using linear or logistic regression as appropriate and all relations will be explored for the possibility of confounding factors.

NHS Digital linkage
To maximise the number of people from the original cohort identified and followed-up, University of Nottingham used the NHS Digital Medical Research Service (MRIS) to trace all survivors from the original 2,633 cohort members, which was completed in 2007. Where the current address held on University of Nottingham’s systems is correct, as verified by the NHS Digital data, questionnaires (respiratory health and dietary) will be posted directly to the individual. When the current address is incorrect, then the questionnaire will be sent out with a covering letter to the individual via their General Practitioner.

In addition the MRIS service will also identify all deaths in the original cohort and provide information on the cause of death. All living study participants will be flagged for notification of cause of death in the future. Mortality data will be used to investigate the relation between diet and all-cause mortality and between diet and specific causes of death.

NHS Digital already have the cohort population identified and data on deaths and cancer registrations will be sent to University of Nottingham which will then be linked to datasets held at the University of Nottingham on an encrypted hard drive. No data will be shared with individuals/organisations outside the University of Nottingham. All data will be held on an encrypted hard drive.

Project 13 — DARS-NIC-148262-PR6G1

Type of data: information not disclosed for TRE projects

Opt outs honoured: N

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Purposes: ()

Sensitive: Non Sensitive

When:2016.04 — 2017.05. breached contract (and anonymisation code) — audit report.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Flagging Current Status Report
  2. MRIS - Scottish NHS / Registration
  3. MRIS - Cause of Death Report
  4. MRIS - Cohort Event Notification Report

Objectives:

The TARDIS trial will assess the safety and efficacy of intensive antiplatelet therapy, as compared with guideline antiplatelet therapy in patients at high-risk of stroke recurrence.The TARDIS trial will assess the safety and efficacy of intensive antiplatelet therapy, as compared with guideline antiplatelet therapy in patients at high-risk of stroke recurrence.

Project 14 — DARS-NIC-148233-2MP49

Type of data: information not disclosed for TRE projects

Opt outs honoured: N

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Purposes: ()

Sensitive: Sensitive

When:2018.03 — 2017.05. breached contract (and anonymisation code) — audit report.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Personal Demographics Service

Objectives:

The data supplied will be used only for the approved medical research project MR1105 - SNAP (Nicotine replacement therapy in pregnancy)

MR1301: Prospective Study in the Lung Endpoints (PROFILE) — DARS-NIC-160361-NDZKG

Type of data: information not disclosed for TRE projects

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

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Health and Social Care Act 2012 – s261(2)(c)

Purposes: No (Academic)

Sensitive: Sensitive

When:DSA runs 2019-02-28 — 2020-01-31 2016.04 — 2016.08. breached contract (and anonymisation code) — audit report.

Access method: Ongoing

Data-controller type: UNIVERSITY OF NOTTINGHAM

Sublicensing allowed: No

Datasets:

  1. MRIS - Cause of Death Report
  2. MRIS - Cohort Event Notification Report
  3. MRIS - Flagging Current Status Report

Objectives:

The overall aim of this study is to use a prospective cohort study of IPF to validate a panel of published biomarkers and to discover novel candidate biomarkers that can be used in subsequent intervention studies in order to provide proof of mechanism for novel interventions. As such, this is an enabling study which will provide robust biomarkers which can be used in the clinical development of novel therapeutic interventions.

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. The following information provides background information on the yielded benefits of the original study and subsequent data sharing agreement with the Health and Social care Information Centre (which has since become NHS Digital). . This study holds the largest longitudinal data set on patients with IPF in the world and three high impact papers published to date. Initial analysis of the PROFILE study data have already been published as high impact manuscripts (Jenkins et al Lancet Respiratory Medicine 2015, Allen et al Lancet Respiratory Medicine 2017, Maher et al Lancet Respiratory Medicine 2017, Stewart et al Eur Resp J 2019) and have been included as primary endpoints in a clinical trial being undertaken by Boehringer Ingelheim (NCT02788474). These papers have lead to re-design of clinical trials and some of the biomarkers are available in current clinical practice and implementation studies are planned imminently. Further PROFILE study analysis was a central theme of a successful application for an NIHR Research Professorship RP-2017-08-ST2-014 awarded in 2018 entitled Developing a biomarker guided strategy to treat patients with pulmonary fibrosis'

Outputs:

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

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

The following information provides background information on the expected output activities of the original study and subsequent data sharing agreement with the Health and Social Care Information Centre (which has since become NHS Digital)

The PROFILE study has published previous findings in the Lancet Respiratory Medicine in 2015, two studies in 2017 and a study in the European Respiratory Journal 2019.

These data have identified a number of serum and physiological biomarkers that predict disease susceptibility, disease progression and mortality as well as identifying disease susceptibility genes.

The University of Nottingham are currently working to understand the genetic risk factors that predict disease progression and mortality in IPF and to ensure the most reliable estimates of genetic risk to outcome we wish to explore the most up-to-date and complete data sets to ensure reliability of our genetic studies.

The University of Nottingham anticipate generating further outputs related to our available physiological and biochemical data with outcome data that will be published in the next 12 months.

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

Processing:

Mortality data was supplied to the University of Nottingham by the Health and Social Care Information Centre (which has since become NHS Digital) for the purpose of a research study. The University of Nottingham requires notifications of mortality,cancer registrations for a cohort of 550 consented individuals for use in the PROFILE study.

This Data Sharing Agreement permits the retention of the data for an interim period but no other processing of the data is permitted. Permission to retain the data for the interim period is a practical step to enable the study to comply with the necessary legal and ethical requirements. If, for any reason, it is not possible for the study to meet the necessary requirements, this Agreement will be terminated, and destruction of the data will be required.

The following information provides background information on the processing activities of the original study and subsequent data sharing agreement with the then HSCIC.

All data flowing from the University of Nottingham to the Health and Social Care Information Centre (which has since become NHS Digital) is encrypted.

The University of Nottingham previously sent files of identifiers (NHS Number, Date of Birth and Postcode plus Unique Study ID) to the Health and Social Care Information Centre. The Health and Social Care Information Centre periodically provides reports of mortality and cancer notifications to the University of Nottingham. The University of Nottingham stores the data on a server in its Clinical Sciences Building.

Data received from the Health and Social Care Information Centre is entered into the PROFILE study database at the University of Nottingham.

The data will only be accessed by the local University of Nottingham database manager and designated employees for the purpose described, all of whom are substantive employees of the University of Nottingham. The PROFILE study data (including data received from NHS Digital) will not be linked to other data sets.

The data provided is used by authorised individuals all of whom are substantive employees of the University of Nottingham to analyse mortality rates of idiopathic pulmonary fibrosis from initial diagnosis.