NHS Digital Data Release Register - reformatted

University Of Leeds projects

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


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

Frequent users of the Emergency Department: Improving and standardizing services- a mixed methods study — DARS-NIC-666525-M8L1F

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2022-12-01 — 2025-11-30

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Civil Registration (Deaths) - Secondary Care Cut
  2. Emergency Care Data Set (ECDS)
  3. Hospital Episode Statistics Accident and Emergency
  4. Hospital Episode Statistics Admitted Patient Care
  5. Hospital Episode Statistics Critical Care
  6. Hospital Episode Statistics Outpatients
  7. Medicines dispensed in Primary Care (NHSBSA data)
  8. Mental Health Services Data Set

Expected Benefits:

This programme is expected to provide evidence as to which groups of ED users should be targeted; what kind of interventions should be delivered; how those interventions achieve their desired outcomes; and how outcomes should be measured.

The expectation is that the outputs of this study will reach the health and care system via established links with NHS England, the Royal Colleges of Psychiatry and Emergency Medicine and via direct contact with all frequent user services by a cascading series of webinars as detailed in ‘Expected Outputs’.

The findings are hoped to enable UEC networks to make informed planning choices about services for frequent users. The programme team intend to provide best evidence on how interventions work (or fail) in order to guide on-the-ground delivery. The large investment in liaison mental health services (LMHS) over the last 4 years means that NHS stakeholders should be keen to receive evidence of the impact of LMHS on frequent user services. By incorporating patient and public involvement (PPI) in the research, it is expected that awareness of constructive approaches to this important issue will increase.

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

The use of the data could:
• help the system to better understand the health and care needs of populations.
• lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
• advance understanding of regional and national trends in health and social care needs.
• inform planning health services and programmes, for example to improve equity of access, experience and outcomes.
• provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.

The aim is to improve services for UEC frequent attenders by understanding which activities are carried out by services and what difference they make. This is expected to enable us to develop programme theories which includes which aspects of services are important, how they work and which patients they help most. An implementation framework can then be developed to improve services planning and focus on activities likely to bring benefits to the patients.

A Public and Patient Information and Engagement group was consulted regarding the collection of the data for the purposes described above. Two experts by lived experience make up part of the programme team. They attended the design study meetings, commented on all drafts of the study application for NIHR funding and had individual meetings with the principal investigator of the study, contributing to all workstreams of the programme and helping to set up the dissemination strategy.

As part of the study plan, a PPI reference group was set up to follow the progress of the study and assure PPI input in all stages.

To inform and advertise findings to a wider audience and optimise the potential public benefits from the use of the data, the programme team intend to use strong and established links with:

NHS England; the Current Chair of the Faculty of Liaison Psychiatry; the Royal College of Emergency Medicine and its mental health committee; The Association of Ambulance Chief Executives (AACE) who provide ambulance services with a central organisation that supports, coordinates, and implements nationally agreed policy; the Royal College of General Practice; and the European Association of Psychosomatic Medicine to reach a wider European audience.

The principal investigator and experts by lived experience co applicants plan to lead on developing a strategy to inform users and carers on a local and national basis about the findings. The intention is to approach NHS Choices and offer to help with updates as a result of the study.

Outputs:

The main analysis is due to be completed by September 2024 with the aim to disseminate and publish results between November 2024 and February 2025. Results are expected to be published in open access and peer reviewed journals, including publication via the National Institute for Health Research's own journal library, and a paper on “Frequent users of the emergency department: improving services and identifying evidence-based interventions-a mixed methods study” for submission to other appropriate journals. The analysis of the datasets requested are planned to be presented at research meetings, such as national and international liaison psychiatry meetings. These conference presentations and papers will report aggregated results across patient episodes and the results will be based on statistical analysis generated from the data (typically in the format of tables, graphical representations, and text).

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

Longstanding and ongoing engagement with stakeholders, including both scientific and policy-making audiences is expected to provide a direct pathway to impact for the outputs of this research. The Experts by Experience in the team should help inform the dissemination strategy and play an active role in the format and content of academic papers, as well as supporting presentation at local, regional, and national conferences and wider stakeholder meetings.

The results and outputs of the study are planned to be communicated further via the study team's websites, social media accounts and through other public promotion of research utilizing the researchers' networks, including clinical networks, scientific networks, and charitable organisations.

The main outputs that are intended to be produced from this study are:
-Characterization of the different patterns of frequent use of UEC services and associated factors; Detailed costs related to the pattern and use of UEC services by frequent users.
-A robust evaluation of the impact of frequent user services including cost-effectiveness.
-Identification of specific interventions for certain sub-types of frequent users and the mechanisms by which they achieve their desired outcomes.
-An understanding of the impact of COVID-19 on frequent use of UEC services.
-Publications of the main research findings/conference presentations, information across different media outlets including the study website, social media (using podcasts and twitter), PPI organisations links, relevant charities.

The programme team plan to use a multi-level approach to transfer information about the study findings to relevant stakeholders. The top-down approach will involve targeting six key groups: NHS England, The Royal Colleges of Psychiatry, Emergency Medicine and General Practice, Ambulance Services, and the NHS Confederation. The intention is to convene a workshop of relevant national stakeholders and PPI representatives to present the findings from the Programme, and to discuss the recommended improvements to services.

At an intermediate level, the plan is to hold 4 webinars (each one focusing on a particular service type) which will be jointly presented by members of the programme team and key personnel from the case site of relevance, and which will be targeted at the frequent user services that participated in work stream 1 of FUsED.

At the bottom-up level, the intention is to hold 4 further webinars which will again focus on a particular service type. All remaining frequent user services would be invited to attend one of the webinars, according to their type of service. It is intended that any relevant feedback from the webinars would be incorporated into the team's implementation framework.

The programme team intend to co-develop with the patient and public involvement (PPI) reference group plain English summaries, voice-recordings and podcasts of findings and make these available online through blogs and social media.

Processing:

No data will flow to NHS Digital for the purposes of this Agreement.

NHS Digital will provide the relevant records from the HES, ECDS, Mortality, Mental Health and Prescribing datasets to the Leeds Analytic Secure Environment for Research (LASER Platform), a cloud-based Trusted Research Environment system hosted in Leeds Institute of Data Analytics (LIDA). The data will contain no direct identifying data items. The data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

The LASER Platform provides a secure environment for the handling, processing, analysis and storage of sensitive and confidential research data, segregates projects at network level, using separate Virtual Research Environments (VRE), protecting data from the rest of the University's computing facilities and from internet access. It is managed and maintained by University of Leeds IT Services and operated and supported by LIDA's Data Analytics Team (DAT).

The University of Leeds stores data on the Cloud provided by Microsoft Limited.

No other data flow to or from NHS Digital will be undertaken as part of this research project.

Flags for when and what interventions were introduced will be integrated into the NHS Digital data, in order to analyse the impact of hospital trusts introducing interventions for people who were frequent attenders. These flags will be generated as part of another workstream from this programme, and combined with the record level NHS Digital data.

The aggregated information derived from the NHS Digital data will be analysed in parallel with aggregated data from the CUREd database, which covers all hospitals with an ED in the Yorkshire and Humber Region plus associated 999/111/and ambulance data. CUREd has 3.8M attendances over 3 years, covering approximately 88k frequent users.

The data will be accessed onsite at the premises of University of Leeds. The data will also be accessed by authorised personnel via remote access. The data will remain on the servers at Microsoft Limited at all times.

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

The data will not leave the UK at any time.

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

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

There will be no requirement and no attempt to reidentify individuals when using the data.

Researchers from the University of Leeds will process the data for the purposes described in ‘Objectives for Processing’.


Liaison Psychiatry Service Configurations and Referral Patterns and their Effects on outcomes: Sub Study An Evaluation of Cost-effectiveness and Efficiency Using Routine NHS Data — DARS-NIC-315999-W2W4C

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

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

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2019-07-01 — 2020-06-30

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

Objectives:

The purpose of this updated application is to extend the data sharing agreement relating to this data for a further year (until 30/06/2020) to enable analysis to be finalised and prepared for publication. No additional data is being requested as part of this extension request.

Liaison psychiatry (LP) involves the provision of mental health services in non-psychiatric settings, in this case in general hospitals. Liaison services exist because there are higher rates of most mental health problems in general hospitals than there are in the general population. The two main questions asked of them are: do they improve outcomes for the people referred to them and if so can they do so in a cost-effective way? It has even been claimed that LP saves the NHS money by reducing inappropriate use of expensive general hospital stays and treatment for people who are best helped in other ways. The challenge in answering these questions is that liaison services vary greatly in how they are set up, in the sort of referrals they see, and in how they deliver care. Liaison psychiatry for the elderly does not cover the same ground as that for working age adults. So asking whether liaison services are cost effective is not like asking whether a cardiac surgery service is cost-effective but more like (on a smaller scale) asking if general practice is.

A major challenge in assessing the cost-effectiveness of liaison psychiatry services resides in the variability in their case-mix and also in how they are configured. There is also considerable diversity in external (demographic and other service) factors that influence outcomes for liaison psychiatry. LP-MAESTRO is a project at the University of Leeds, which has been funded by the National Institute for Health Research and Health Services and Delivery Research (NIHR HS&DR) as part of a commissioned call (13/58 Organisation, quality and cost-effectiveness of psychiatric liaison services in acute settings), to develop an approach based upon economic modelling and using routinely-collected NHS data, that allows the University to evaluate the cost-effectiveness and efficiency of particular configurations of liaison psychiatry service for specified target populations.

The overall aim of LP-MAESTRO is to evaluate the cost-effectiveness and efficiency of particular configurations of liaison psychiatry service for specified target populations. To do this, an innovative approach based upon linking routinely collected patient-level data and using economic modelling with the resulting aggregated data will be developed and evaluated.

Under the General Data Protection Regulation (GDPR), a legal basis is required for processing of personal data. The legal basis under which data is processed within the project Liaison Psychiatry Measurement and Evaluation of Service Types, Referral Patterns and Outcomes (LP-MAESTRO) 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;”

Processing of data concerning health (and other ‘special categories’ of data) requires the fulfilment of an additional condition under GDPR. The specific condition fulfilled by the processing of such data within LP-MAESTRO is:
•Article 9 (2) (j) – “processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.”

The overall aim is to evaluate the cost-effectiveness and efficiency of particular configurations of liaison psychiatry service for specified target populations. The purposes described in this agreement amount to a sub-study of the LP-MAESTRO project.

LP-MAESTRO is a collaboration between academics and practitioners at the University of Leeds, University of Manchester and Imperial College, Peninsula Schools of Medicine & Dentistry, The Centre for Mental Health, The Royal College of Psychiatrists and Leeds York Partnership Foundation Trust. Leeds University are the Data Controllers for this work described under this agreement - the other organisations noted in the collaboration do not have any influence over the outputs generated. The other collaborators listed provide contributions to the main LP-MAESTRO project DARS-NIC-77953-C4M3T-v1.3. These organisations have no direct role in the processing of the data received under this agreement for the sub-study of LP-MAESTRO

Leeds University will have rights to the data disseminated for this project to relate to the processing of the data. Only staff at the University of Leeds will be involved in the processing of the data received from NHS Digital.

LP-MAESTRO has three work packages as a whole. The current work as described in this agreement was originally intended as pre-protocol preparation for Work Stream 2 of the LP-MAESTRO Project. However, delays in data release mean it has been subsumed into that work stream, demonstrating the value but also the significant drawbacks of using single datasets like HES to attempt to evaluate liaison services.

The work packages within this agreement do not directly relate to the work being undertaken in Workstream 2 which has its own agreement in place - DARS-NIC-77953-C4M3T-v1.3

Workstream 2 – Phase 1 (WS2P1) focuses on 11 acute hospitals in England that were identified within Workstream 1 of LP-MAESTRO and the Liaison Psychiatry Survey England 2015 as not having a Liaison Psychiatry service.

Workstream 2 – Phase 2 (WSP21) focuses on hospitals in England that were identified within Workstream 1 of LP-MAESTRO and the Liaison Psychiatry Survey England 2015 as having a particular configuration of Liaison Psychiatry service. To enable pathways to be constructed for patients attending these hospitals that consider the interaction of patients with the Liaison Psychiatry services in these hospitals, data is additionally
required from the NHS trusts that run these services.

The work-packages in this agreement relate to the preparation for work-stream 2.

Record-level data supplied under this agreement will only be held, processed and stored by the University of Leeds. Other collaborators and partners mentioned above will only have access to aggregated outputs with small numbers suppressed in line with the HES analysis guide.

The data requested under this agreement includes the Hospital Episode Statistics (HES) inpatient episodes for patients (aged 16 years or over) who have attended two specific hospitals in Birmingham over a 5 year period (2007-2011):

o City Hospital Birmingham
o Queen Elizabeth Hospital Birmingham (University Hospitals)

For each episode, the following data items were requested and have been received:

o Patient pseudonym
o Duration of spell
o Diagnostic codes
o Treatment speciality
o Provider code
o Date of admission
o Method of admission

The episodes in the two hospitals have been compared in terms of:

o Length of spell
o Readmission within 12 months from discharge

Figures have been compared (for different patient subgroups) across the hospitals using standard statistical methods.

Special statistical techniques (multilevel negative binomial model) were used to deal with the two challenges:
- [1] length of stay are very unevenly distributed with some people staying only one day and some staying many weeks,
- [2] a single patient may account for several inpatient episodes, complicating interpretation.

This has enabled the estimation of whole hospital effects over time (for the five-year study period) and comparison between hospitals. The data have allowed the study to answer an important question about liaison psychiatry services and their effect on lengths of stay in a general hospital; this was a key part of the logic of the project and is therefore useful to the overall research programme. The analysis indicated a number of factors of relevance in understanding the project as a whole: the inaccuracy of mental health coding in HES (mainly under-reporting); striking differences between hospitals in terms of coding rates and of lengths of inpatient stay (LOS); a time trend for LOS with a linear reduction over a 5 year period – this pattern is extremely important in understanding claims that liaison services reduce hospital lengths of stay; lack of an obvious effect of introduction of a Rapid Assessment Interface and Discharge (RAID) liaison psychiatry service on hospital-wide lengths of stay once the background trend is taken into account.

Data will not be used for any other purpose that is not defined in this agreement. No attempts will be made to re identify individuals with data provided under this agreement.

There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.

Yielded Benefits:

The data so far have allowed the study to answer an important question about liaison psychiatry services and their effect on lengths of stay in a general hospital; this was a key part of the logic of the project and is therefore useful to the overall research programme. Preliminary results have been presented at a Rapid Assessment, Intervention and Discharge (RAID) network conference in Chester in April 2017. The purpose of this updated application is to extend the data sharing agreement relating to this data for a further year (until 30/06/2020) to enable analysis to be finalised and prepared for publication.

Expected Benefits:

The results of this application will be used to determine the cost-effectiveness and efficiency of a particular liaison psychiatry service configuration. They are planned for later this year with two groups in Royal College of Psychiatrists and Centre for Mental Health.
Benefits include:

- Illustration of a value of a particular approach (interrupted time series - which is analysis using a quantitative, statistical method in which multiple (sometimes as many as 40 or 50) repeated observations are made at regular intervals before and after intervention) in evaluating impact of new services.
- Recommendation to commissioners on an approach to evaluating services using routine data.

Project collaborators in Royal College of Psychiatrists and the Centre for Mental Health are conducting interviews and focus groups with service commissioners, to identify the best form and content for materials generated by the project when the aim of those materials is to inform decision-making. These are planned for later this year with two groups in Royal College of Psychiatrists and Centre for Mental Health.


In Work Stream 3 of LP-MAESTRO (a further stage) the study will then generate those materials. The impact on health and social care of any one piece of research is necessarily limited by the impact of competing claims – including policy imperatives that are based upon values rather than evidence. Nonetheless, this work should be influential because it is only the second attempt in the UK to evaluate the effect of liaison psychiatry services on acute hospital lengths of stay.

The study has developed groups of committed and informed members of the public who are all people with experience of long term physical illness and awareness of mental health issues. They are drawn from patient organisations such as Diabetes UK, Breatheasy and Heartline. and have experience of membership of steering committees, development of participant information resources, research websites, patient interventions and dissemination of research findings. These organisations provide representation for patients with physical health problems. Such patients may experience mental health problems during the course of a hospital admission and require care from a liaison psychiatry service.

Outputs:

The data so far have allowed the study to answer an important question about liaison psychiatry services and their effect on lengths of stay in a general hospital; this was a key part of the logic of the project and is therefore useful to the overall research programme. Preliminary results have been presented at a Rapid Assessment, Intervention and Discharge (RAID) network conference in Chester in April 2017, but the main dissemination activity is as below.

There are a number of audiences for the outputs of this research – clinical service providers in liaison psychiatry and general hospital managers, both groups who wish to plan the most effective provision of psychiatric services; commissioners of healthcare in Clinical Commissioning Groups (CCG's) and their associated Commissioning Support Units; data scientists who are interested in the challenges of data-linkage and the information it can yield.

For clinicians and academics in liaison psychiatry and health services researchers the study will produce standard academic publications – the NIHR report, papers and conference presentations. The study will disseminate these outputs via academic and clinical publications . The Centre for Mental Health will produce two publications related to the findings – these are disseminated widely to non-academic audiences.

For non-academics in management the study will produce a synopsis of findings. These will be prepared in paper format and in the form of mini-tutorials that the study will make available by links to the website.

The study will signpost these outputs through articles in newsletters and via professional discussion forums such as the liaison psychiatry jisc-mail group (JISC-Mail provides email discussion lists for education and research) and economic associations’ mailing lists.

To ensure that the research reaches as wide an audience as possible the study plan to develop a series of interactive webinars that will be free to view. After the live webinar, the presentation recording will be available free to download, hosted on the university leading the research and the project webpage and will be publicised via mailing lists and social media such as Twitter.

At the end of the project the study will hold a specialist conference the aim of which will be to review current knowledge in the underpinning areas of whole-service evaluations of cost-effectives as relevant to liaison services and the use of data linkage to evaluate services that cut across sectors, and the specific content area - what the study have learned about cost-effectiveness in liaison psychiatry.

An Academic paper to a health services research or mental health journal will be submitted by the end of 2017 (The previous version of this agreement requested an extension to the agreement end date in order to facilitate the required analysis and enable generation of research outputs. The date for this output has not changed from the previous version of the agreement).

Use of the data will be included in the final report of main project. The end date of the project was previously 31st December 2017. However, a request is currently under consideration by the funder of the main project (NIHR HS&DR) to extend the project for a further 12 months (30th June 2020).

A discussion paper will be produced for mental health service commissioners.

The Birmingham findings will be presented as described in this section, as part of the wider LP MAESTRO findings

A paper published in a medical academic journal will be read mainly by clinicians in liaison psychiatry and by applied health researchers, and this will influence national debates about the nature of liaison provision, which take place in professional forums such as the Royal College of Psychiatrists. Mental Health Service commissioners influence services by the way they fund structures and require certain outcomes; the project will inform the approach to service evaluation when services are commissioned with the aim of reducing hospital lengths of stay. The project has influenced the overall approach in LP-MAESTRO by indicating the need to have patient-level data to evaluate the impact of liaison services.

All outputs will consist of aggregate data with small numbers suppressed in line with the HES Analysis Guide. No record level data will be shared with any third party.

Processing:

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

Data is stored securely in an infrastructure provided by the Leeds Institute for Clinical Trials Research (LICTR). Access to the data is restricted to specific members of the research team authorised by the Principal Investigator and granted access by the administrator(s) of the LICTR infrastructure.

Data relating to this project is backed up to the University of Leeds Central Backup Service on University of Leeds owned and managed servers, located within University of Leeds managed data centres. For disaster recovery purposes this data is mirrored to University of Leeds owned and managed servers located in the TFTA Data Centre at University of York. At no point does the University of York or its staff have access to view or process this data. UoY are renting secure rack space for servers to the University of Leeds. The servers themselves, their storage, access and management are all maintained exclusively by UoL staff. Therefore University of York are not considered to be Data Processors.

Data was initially processed to derive the analytical variables of interest. Special statistical techniques (multilevel negative binomial model) were then used to deal with the two challenges: [1] length of stay are very unevenly distributed with some people staying only one day and some staying many weeks, [2] a single patient may account for several inpatient episodes, complicating interpretation. This has enabled the estimation of whole hospital effects over time (for the five-year study period) and comparison between hospitals. The data supplied has been (and will be) solely used for the purpose outlined within this agreement. Data will be securely destroyed prior to the end date of the data sharing agreement (subject to any further extensions).

This data captured the admissions details for two specific hospitals in Birmingham over a 5 year period to facilitate their comparison.

Only substantive employees of University of Leeds will have access to the data. Project collaborators at the Royal College of Psychiatrists and the Centre for Mental Health do not process any of the data disseminated they only have access to aggregated outputs with small numbers suppressed in line with the HES analysis guide.

The work packages within this agreement do not directly relate to the work being undertaken in Workstream 2 which has its own agreement in place - DARS-NIC-77953-C4M3T-v1.3

Workstream 2 – Phase 1 (WS2P1) focuses on 11 acute hospitals in England that were identified within Workstream 1 of LP-MAESTRO and the Liaison Psychiatry Survey England 2015 as not having a Liaison Psychiatry service.

Workstream 2 – Phase 2 (WSP21) focuses on hospitals in England that were identified within Workstream 1 of LP-MAESTRO and the Liaison Psychiatry Survey England 2015 as having a particular configuration of Liaison Psychiatry service. To enable pathways to be constructed for patients attending these hospitals that consider the interaction of patients with the Liaison Psychiatry services in these hospitals, data is additionally
required from the NHS trusts that run these services.

The work-packages in this agreement relate to the preparation for work-stream 2.

There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.

Data will only be accessed and processed by substantive employees of the University of Leeds and will not be accessed or processed by any other third parties not mentioned in this agreement.


Towards UK post Arthroplasty Follow-up rEcommendations (UK-SAFE) - Work Package 2a (RO-HES) — DARS-NIC-147997-R8B9S

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

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', , Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2020-09-09 — 2023-09-08

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Admitted Patient Care
  3. Hospital Episode Statistics Outpatients

Objectives:

Most people now understand the need for a cost-effective NHS, but seek reassurance that this will not reduce the standard of care. This is particularly true of older people, who are the group most likely to be affected by this research.

Total joint replacement provides considerable improvement in quality of life to people suffering with severe joint damage and in 2013 over 150,000 total hip and knee replacements were conducted. Due to increasing ageing and obesity in the UK population, this number is likely to increase each year. Sometimes, problems can develop with the replaced joint over time and a small percentage of people require further surgery. Because joint failure is not always associated with symptoms, follow-up care is provided to ensure that problems are identified as early as possible.

Towards UK post Arthroplasty (the surgical reconstruction or replacement of a joint) Follow-up recommendations (UK-SAFE) is funded by the National Institute for Health Research (NIHR) - Health Services and Delivery Research (HS&DR) with reference 14/70/146
(see https://www.journalslibrary.nihr.ac.uk/programmes/hsdr/1470146).

The project will examine the requirements for arthroplasty follow-up and produce evidence and consensus-based recommendations as to how, when and on whom follow-up should be conducted. The University of Leeds have assembled a highly experienced multi-disciplinary team from the Leeds and Oxford NIHR Musculoskeletal Biomedical Research Units with the necessary academic expertise to tackle the methodological challenges in undertaking this work to ensure the project yields meaningful results that are accepted by key stakeholders.

UK-SAFE is a research project sponsored by the University of Leeds and funded by the National Institute of Health Research (NIHR) Health Services and Delivery Research Programme (see https://www.fundingawards.nihr.ac.uk/award/14/70/146).

UK-SAFE comprises of a number of Work Packages, which are led by co-applicants from different institutions, including the University of Leeds and the University of Oxford.

The specific work package to which this application relates - UK-SAFE WP2a (RO-HES) - is being undertaken at the University of Leeds. University of Leeds is the data controller in respect of the data within this work package. University of Oxford is not a data controller or processor in respect of any data for UK-SAFE WP2a (RO-HES).

Further information regarding the Work Packages can also be found on the UK-SAFE Project Web site (see https://leedsbrc.nihr.ac.uk/uk-safe-project/).

Work Package 2 of the UK-SAFE project focuses on 'determining when, which and how patients present for revision surgery' and is itself divided into two Work Packages:
1. Work Package 2a which focuses on analysis of data from routine datasets. Work Package 2a is further sub-divided into three Work Packages:
i) Work Package 2a (CPRD-HES) - led by the University of Oxford
ii) Work Package 2a (RO-HES) - led by the University of Leeds
iii) Work Package 2 (NJR-HES-PROMS) - led by the University of Oxford

2. Work Package 2b which focuses on analysis of a prospective cohort.

The 3 Work Packages within Work Package 2a have been designed to provide different, complementary views on 'when, which and how patients present for revision surgery' by drawing on different routine datasets. Work Package 2a (CPRD-HES) and Work Package 2a (RO-HES) provide different, complementary views that include consideration of primary care. Inclusion and exclusion criteria for cohorts and data items, and analytical techniques to apply to these data, have been determined by the research teams at the University of Oxford and the University of Leeds to ensure the comparability of results between Work Package 2a (CPRD-HES) and Work Package 2a (RO-HES).

This application (DARS-NIC-147997-R8B9S) relates only to Work Package 2a (RO-HES), which is led by the University of Leeds. University of Oxford is separately responsible for Work Package 2a (CPRD-HES) and the other Work Packages within the UK-SAFE project for which they provide the leadership.

The University of Leeds is the Data Controller for the data referenced in this application, and the data is processed at the locations listed in 'Section 1c - Data Processor(s)' of the application. Analysis of the data supplied from this application will be undertaken by a team of researchers based at the University of Leeds only. Aggregated results from analysis will then be reviewed by the Study Management group.

The UK SAFE project will examine the requirements for arthroplasty follow-up and produce evidence and consensus-based recommendations as to how, when and on whom follow-up should be conducted.
UK SAFE comprises of 3 complementary evidence synthesis work-packages to inform a final consensus process.
Work packages 1-3 will be discrete research projects, conducted independently. However, knowledge and information from each will feed into and inform the other work streams with some tasks being conducted in parallel.

This project aims to investigate whether good after-care is expensive, in terms of time and money on the part of both patient and hospital staff, and whether individual patient-centred follow-up can better identify potential problems in a timely fashion, to the benefit of all concerned.

Membership of the Study Management Group (SMG) comprises all co-investigators of the UKSAFE programme. The SMG provides advice on the conduct, delivery and dissemination across all work packages in the programme. Under the conditions of funding, the Principal Investigator, (University of Leeds) has responsibility from the National Institute of Health Research (NIHR) for the delivery of the UKSAFE programme. Within this programme, University of Leeds has the sole responsibility for the delivery of the particular work package of the UKSAFE programme to which this application relates (WP2a RO-HES). The purpose for, and means by which this work package is to be delivered have been specified and agreed in accordance with the NIHR funding process. Any comments received from the SMG in respect of the work package are advisory.

This agreement is for data that will be used on Work Package 2a (RO-HES) which is being undertaken at the University of Leeds.

Work Package 2a (RO-HES) has the following objective:

- To determine when, which and how patients present for revision surgery

To fulfil this objective, Work Package 2a (RO-HES) will undertake a retrospective cohort study using the following sources of routine NHS data:

1. Hospital Episode Statistics (HES) : a database provided by NHS Digital containing patient data relating to A&E, inpatient and outpatient episodes

2. ResearchOne : a research database containing de-identified patient data from primary care settings that use the SystmOne clinical information system.

For patients with an inpatient admission (Index Episode) to a hospital in England within the defined index period (1st April 2000 – 31st March 2015) for one of the following procedures:
i) hip replacement
ii) hip revision
iii) knee replacement
iv) knee revision,

The following data will be obtained from Hospital Episode Statistics (HES) for the period from 1st April 2000 to 31st March 2015:

- A&E attendances with
i) a diagnosis of "dislocation/fracture/joint injury/amputation"
ii) a diagnosis (anatomical area) of Hip, Groin, Thigh, Knee or Lower Leg.

- Inpatient admissions with a treatment specialty of:
i) Trauma and Orthopaedics
ii) Rheumatology.

- Outpatient appointments with a treatment specialty of:
i) Trauma and Orthopaedics
ii) Rheumatology.

For patients included within the HES data, the study will determine whether primary care data exists for the patients within TPP's ResearchOne database. If so, a defined set of primary care data will be obtained for these patients for the period prior to 1st April 2015. Additionally, a mapping file will be produced by NHS Digital and supplied to the University of Leeds to enable the HES data for a specific patient to be linked to the corresponding primary care data (if present).

From the linked data, longitudinal records covering primary and secondary care will be constructed for patients.

Based on data provided within the National Joint Registry (NJR) Annual Report, 800,683 primary hip replacements, 89,023 hip revisions, 875,585 primary knee replacements and 54,278 knee revisions were reported (subject to specific inclusion and exclusion criteria) the period from 1 April 2003 to 31 December 2015. Therefore, for a comparable period within the study, it is anticipated that around 900,000 hip replacements and 1,000,000 knee replacements (1,900,000 joint replacements in total) will be identified.

The scope of all hospitals in England has been chosen to enable variation in follow-up for hip and knee replacements and revisions between hospitals to be analysed. The time period of 15 years over which patients will be identified has been chosen to enable variation in follow-up for hip and knee replacements and revisions for patients over time to be analysed.

The legal basis under which data is processed within UK-SAFE Work Package 2a (RO-HES) 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 University of Leeds (as it is formally and legally known) is an independent corporation established by Royal Charter. Its objects, powers and framework of governance are set out in the Charter and its supporting statutes, amendments. The University of Leeds received its Charter as an independent institution from Edward VII in 1904. The royal charter under section II states that The University shall have the powers following:

“To provide for instruction in such branches of learning as the University may think fit, and also to make provision for research and for the advancement and dissemination of knowledge”.

Processing of data concerning health (and other ‘special categories’ of data) requires the fulfilment of an additional condition under GDPR. The specific condition fulfilled by the processing of such data within UK-SAFE Work Package 2a (RO-HES) is:

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

The data are required for research purposes in the public interest - meeting the conditions in the DPA 2018 Schedule 1 Part 1 (4) - which GDPR Recital 52(2) determines is an appropriate derogation from the prohibition on processing special categories of personal data.

Expected Benefits:

Benefits as described in the NIHR funding application.

Upon completion, this research will have major immediate effect on national NHS planning and budgeting and patient well-being. The outputs will be evidence-based support for timing of followup and identification of the most cost-effective follow-up model. This fits directly within the NHS framework for improving outcomes from elective procedures. Rationalising current diversity of followup practices should enable substantial savings for the NHS. Novel follow-up strategies, such as creating a rapid access pathway after joint replacement for symptomatic patients will be examined. The University of Leeds envisage outputs to be readily applicable to the wider NHS, not only hip and knee but also other joint replacements.

The impact will be to reduce the burden on patients and the NHS in terms of outpatient visits and clinical tests that do not add benefit, while optimising detection of potential problems. From an NHS perspective, this work will provide NHS managers with economic and clinical information on arthroplasty follow-up to inform service planning and delivery, and the role of arthroplasty practitioners in this service; provide orthopaedic surgeons with guidance on follow-up, including patient and economic considerations of factors involved; produce arthroplasty follow-up guidelines for adoption by the relevant specialist societies and inclusion with information for their members. From a patient perspective, this work will help to inform patients about follow-up practice and empower them to make choices about future healthcare relating to their joint arthroplasty.

At the end of the project, a policy document will be created with support of the relevant societies, NHS England, CCGs and patient representation. It is anticipated that this will include a stratification algorithm to determine appropriate follow-up for an individual patient, taking into account, for example, implant type and patient factors, and that recommended follow-up pathways for hip may differ to those for knee. This advisory document will be disseminated to all stakeholders, including orthopaedic surgeons, arthroplasty surveillance professionals and NHS managers. With the committed support of these key organisations, it is anticipated that these guidelines will be positively received and that implementation will be widespread. It is the University of Leeds's ambition for the recommended follow-up pathway/s defined by this programme of work to be adopted for all hip and knee replacement patients in the UK and internationally.

Outputs:

This project may deliver the first research-supported, best-for-patient, joint-specific, cost-effective recommendations for follow-up care, providing a gold standard for clinical excellence, and follow-up advice for patients, surgeons, purchasers and health services. Value is not limited to the UK, but has massive global potential.

Nationally, (if successful) the outputs, in the form of an executive summary statement of the agreed pathway/s will be disseminated through appropriate NHS Networks, the NHS England Elective Orthopaedics Subcommittee, the NHS Institute for Innovation and Improvement and professional societies. Dissemination will be key to developing a culture of ‘finding the best way of doing something and doing it everywhere’ to significantly reduce wastage of clinical resources and optimise NHS spend. The University of Leeds have support of the British Hip Society (BHS), British Orthopaedic Association (BOA), British Association for Surgery of the Knee (BASK), NHS England, Arthroplasty Care Practitioners Association (ACPA), the National Joint Registry and three Leeds-based CCGs for this research and for dissemination activities. This includes individuals from these organisations sitting on the project Independent Advisory Group and attendance of representatives from each organisation at the final dissemination meeting in order to promote further cascading of study results. They will not influence the results in any way - just advise on how is best to cascade accordingly.

Support from these organisations in this context refers to broad agreement with the aims and objectives of the project and an interest in the outputs generated by the project. These organisations have no data controller or processor responsibilities in respect of the data from NHS Digital.

The study may put forward the consensus statement to each society’s AGM for adoption as a resolution (if successful).

Internationally, dissemination platforms are already in place through the International Society of Arthroplasty Registers (ISAR) and the European Federation of National Associations of Orthopaedics and Traumatology (EFORT).

Overall and individual work-packages findings may be disseminated through a variety of media. Abstracts may be submitted to major British and international orthopaedic conferences, and separate relevant meetings, including the Health Economics Study Group and Exploiting Existing Data for Health Research conference. The University of Leeds will look to present at the NIHR Methodology Conference and NHS Management conferences and events. Manuscripts will be submitted to appropriate peer-reviewed journals, including general medical, orthopaedic and management journals if appropriate.

Patient dissemination will be supported through the Leeds Biomedical Research Centre Patient and Public Involvement (LBRC PPI) forum and website. Patients with relevant lived experience of the conditions will be involved throughout the programme of work, including one PPI co-applicant and two lay members of the study Independent Advisory Group (both patients with relevant lived experience). The University of Leeds (if appropriate) will hold a PPI conference at the end of the study and will encourage the PPI representatives to be involved in presentations, with support from research staff, to help ensure conference material is appropriate. With lay representatives the University of Leeds will write a lay summary for publication in a patient publication such as The Patient or Inspire (if the project is successful).

To minimise any risk that data published by the research team discloses the identity or attributes of specific patients.

All published outputs from WP2a (RO-HES) will be assessed against the NHS Anonymisation Standard (see http://www.isb.nhs.uk/documents/isb-1523/amd-20-2010/1523202010sp ec.pdf) and ICO's Anonymisation: managing data protection risk - code of practice (see https://ico.org.uk/media/1061/anonymisation-code.pdf) and approved by the Principal Investigator prior to publication.

Any published outputs generated using the data from NHS Digital will contain only aggregated data with small numbers suppressed in line with the HES Analysis Guide

Processing:

A summary of the data flows, which are performed using either: i) NHS Digital's Secure File Transfer (SEFT) or ii) University of Leeds LICTR's Secure File Transfer (SFT), is provided below. This list below explains the TRANSFER MECHANISM - further details of the full flow are included later on in this section.

1. University of Leeds provides TPP (SystmOne) with the cryptographic salt (via SFT)
2. University of Leeds provides NHS Digital with the cryptographic salt (via SFT)
3. NHS Digital provides the University of Leeds with HES A&E, Inpatient and Outpatient data according to specified criteria with patients referenced by HESID (via SEFT)
4. NHS Digital provides TPP (ResearchOne) with a set of patient pseudonyms (via SEFT).
5. TPP (ResearchOne) provides University of Leeds with primary care data for patients identified from the set of patient pseudonyms supplied by NHS Digital with patients referenced by ROID (via SEFT).
6. TPP (ResearchOne) provides NHS Digital with a mapping from each patient pseudonym to a unique ROID (via SEFT)
7. NHS Digital provides University of Leeds with a mapping file that maps a unique HESID to a unique ROID identifier (via SEFT)

The data which will be accessed by the University of Leeds will be pseudonymised. They will have no access to identifiers. They are not permitted to use the data provided to try and re-identify any individual.

Importantly, University of Leeds do not receive any pseudonyms from NHS Digital or ResearchOne.
University of Leeds receives: i) data from NHS Digital where patients are referenced by a HESspecific identifier, ii) data from ResearchOne where patients are referenced by a RO-specific identifier, and iii) a file from NHS Digital which maps HES-specific identifiers to RO-specific identifiers. Linkage of the HES-specific identifier to RO-specific identifier is undertaken at NHS Digital.

ResearchOne has been separated out in the summary above to TPP (ResearchOne) and TPP (SystmOne). Project documentation (Protocol) refers only to ResearchOne to emphasise that the project will use only data from the ResearchOne database. The Phoenix Partnership (TPP) are responsible for SystmOne, ResearchOne, and for ensuring the necessary separation of duties for staff working on SystmOne and ResearchOne.
NHS Digital and TPP will transfer the set of patient pseudonyms (via SEFT) in line with the correct procedures . The ResearchOne database is stored and processed inside the data centres which host the SystmOne production environment. The databases are in Tier 3 data centres that have been accredited by the NHS for storing and processing clinical data. There is a disaster recovery site (hosted to exactly the same standards as the live site) which is used as a back-up location in the event of any failures at the main site. Documentation relating to ResearchOne can be found at:
http://www.researchone.org/documentation/.

University of Leeds generates and supplies a salt key that is used in the generation of pseudonyms by NHSD and TPP (SystemOne). To ensure that the identifier used to generate the pseudonyms (NHS number) cannot be recovered by the University of Leeds, the University of Leeds does not receive any pseudonyms generated using the supplied salt key.
The salt key is a random string. The salt key is generated for this specific project by the University of Leeds and securely transferred to NHS Digital and TPP. The key is then used by NHS Digital and TPP in conjunction with NHS number to generate pseudonyms for patients. These pseudonyms are used by TPP to determine whether patients are present in ResearchOne and by NHS Digital to generate a mapping file that is provided to the University of Leeds.
The “salt” file represents a random string of defined length that is used as an additional input to the pseudonym generation process to reduce the risk
that: i) NHS numbers could be recovered from pseudonyms, and ii) pseudonyms generated from NHS numbers for different projects (and any associated data) could be matched. Use of the salt key in the pseudonym generation process provides a safeguard against the potential recovery of the NHS number from a pseudonym by a brute-force attack – where pseudonyms are generated for all possible NHS numbers – as such an attack would also require to the attacker to have access to the salt key.

Data extracts from ResearchOne contain unique references for each patient that are project-specific – i.e. the reference for a given patient will be different in any two data extracts from ResearchOne. The terms ‘ROID’ or ‘ResearchOne ID’ are used for these references within the project documentation.

o For a given data extract, these project-specific unique references are created and assigned as part of the extract generation process.

o To facilitate linkage with data from NHS Digital for this project, TPP will also generate a pseudonym for each patient as part of the extract generation process, using the salt supplied by UoL and the NHS number contained in the SystmOne data (from which ResearchOne data is generated). (Point 1 + 2 + 3 above)

o NHS Digital will supply a list of pseudonyms to TPP which will represent those patients to include in the data extract from ResearchOne. (Point 4 above)

o TPP will determine those patients for whom data exists within ResearchOne by matching pseudonyms in this list with those created as part of the extract generation process.

o TPP will then supply NHS Digital with a file that maps pseudonyms to ROIDs for the subset of patients who are present in ResearchOne. (point 6)

o NHS Digital will use the file supplied by TPP to generate a file that maps HESIDs to corresponding ROIDs. The file generated by NHS Digital will be supplied to UoL to enable data relating to a given patient to be determined in both the HES and ResearchOne data. (Point 7 above)

o TPP will also supply UoL with a data extract containing the required data items where each patient is uniquely referenced by a ROID. TPP does not supply the pseudonyms to UoL. (Point 5)

The University of Leeds receives the following:
i) HES data referenced by a HES ID
ii) ResearchOne data referenced by a RO ID
iii) a mapping file from HES ID to RO ID.

The linkage methodology has been developed so that the University of Leeds is responsible for the generation and supply of the salt key, and subsequent data flows to the University of Leeds do not contain any data that could be re-identified by the knowledge of the salt key. Additionally, the salt key is used only a one-time basis, such that any pseudonyms generated cannot be matched across data sets obtained for different usages. Approvals for the project (including NHS Ethics) have been obtained on the basis of the proposed linkage methodology.

NHS Digital will identify patients based on the presence of an inpatient admission (Index Episode) to a hospital in England within the defined index period (1st April 2000 – 31st March 2015) for one of the following procedures: i) hip replacement, ii) hip revision, iii) knee replacement, or iv) knee revision. For these patients, NHS Digital will identify any of the following in the period for 1st April 2000 – 31st March 2015:

- A&E attendances with i) a diagnosis of "dislocation/fracture/joint injury/amputation" or ii) a diagnosis (anatomical area) of Hip, Groin, Thigh, Knee or Lower Leg.
- Inpatient admissions with a treatment specialty of i) Trauma and Orthopaedics or ii) Rheumatology.
- Outpatient appointments with a treatment specialty of i) Trauma and Orthopaedics or ii) Rheumatology.

This data will be provided directly to the University of Leeds with patients uniquely referenced by a unique HESID. Additionally, NHS Digital will generate a pseudonym for each included patient, according to the methodology described above, and supply this list of pseudonyms to TPP (ResearchOne).

TPP will generate pseudonyms for all patients in the ResearchOne database by applying the same methodology as NHS Digital and using the salt key supplied to TPP (SystmOne). TPP (ResearchOne) will then determine those patients whose pseudonyms are present in the list provided by NHS Digital. Selected primary care data will be extracted from ResearchOne for these patients for the period prior to and including 31st March 2015.

Primary care data will only be obtained where:
- the GP practice to which the patient is registered using TPP's SystmOne clinical information system and
- has opted-in to ResearchOne (and the patient has not individually opted-out).

TPP (ResearchOne) will provide primary care data directly to University of Leeds. Each patient will be uniquely referenceable in this data using a unique ROID. No pseudonyms will be included in the data provided by ResearchOne to the University of Leeds. TPP (ResearchOne) will also provide NHS Digital with a file that maps each pseudonym present in the list provided by NHS Digital and in the ResearchOne database to its corresponding ROID.

NHS Digital will use the mapping file provided by TPP (ResearchOne) to map the HESID of each patient in the HES data to the ROID identifier of each patient in the ResearchOne data. NHS Digital will supply the resulting mapping file to the University of Leeds who will use it to match the data for a particular patient in HES data to the data for that patient in the RO data (and vice-versa).

Survival analysis will be used to model time to revision. To determine the follow up time of revision, a smoothed Nelson-Aalen cumulative hard rate will be examined to identify any peak in the mid-long term risk of revision. Survival analysis is a statistical technique used to analyse the time until a particular event happens. In this case, the particular event would be a hip/knee revision.
To identify patients most likely to require revision, proportional hazards regression will be used to identify pre-, peri- and post- operative predictors of mid-late term revision.
The project seeks to determine those factors that predict mid-late term revision. The factors are categorised by the time at which their value is determined relative to the operation: pre (before) peri (during) and post (after). Cox proportional hazards regression modelling is a statistical technique used to determine associations between the time of an event happening (e.g. revision) and these factors.
The date of the first incidence of a subject's hip or knee replacement will be used as the start time. The event of interest in all time-to-event models will be the first recorded revision operation. Cox proportional hazards regression modelling will be used to identify pre-, peri- and post- operative predictors of midlate term revision (defined as more than 5y post primary surgery). Should testing reveal that the proportional hazards assumption is not valid, then parametric modelling will be used instead. Shared frailty will be modelled with a random effect for hospitals/providers and another for general practice, since it is anticipated that both hospital practice regarding follow-up and GP behaviour regarding referral will influence the survival time of the primary joint replacement. Competing risks, including mortality and comorbidities following primary surgery will be considered. Linearity of continuous predictors will be assessed using fractional polynomial regression modelling or splines. Analysis will assess the extent to which the relationship between the value of continuous predictors (i.e. predictors whose values might be, for instance, decimal numbers) and time can be represented by a linear function (straight line).
Missing data will be handled by using multiple imputation methods using the ICE (Imputation by Chained Equations) procedure.

Inclusion and exclusion criteria for patients and data items were determined by members of the project team who provided clinical, technical and statistical input. Only those patients and data items determined to be necessary and sufficient to answer the research question were included.

UK-SAFE WP2a (RO-HES) is not part of a PhD project.

All persons accessing the record level data provided by NHS Digital under this agreement are substantive employees of University of Leeds.

Employees of University of Leeds receive training in data protection and confidentiality.

University of Leeds will not link the data further and the only data linkages are those permitted under this application / Data Sharing Agreement.


UK GRACE Risk Score Intervention Study — DARS-NIC-112910-R4X9X

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 2019-01-17 — 2022-01-16 2019.06 — 2022.11.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Civil Registration - Deaths
  3. HES:Civil Registration (Deaths) bridge
  4. Civil Registration (Deaths) - Secondary Care Cut

Objectives:

The UK GRACE Risk Score Intervention Study (UKGRIS) aims to find out whether there is a difference in a patient’s health following an unstable angina attack or a heart attack if treated according to a hospital’s usual care or if treated using the GRACE risk score tool.
The UKGRIS study will randomly assign recruiting hospitals to either continue with their current usual care or use of the GRACE risk score tool for the care of their patients admitted with a suspected NSTEACS (type of unstable angina attack or heart attack). Sites are only recruited into the study if their current usual care is not the use of the GRACE risk score tool.
When a patient has had an NSTEACS, the NHS has care processes (such as medication, further tests or health guidance) which are recommended for the patient based on how severe their NSTEACS is. These are called Class 1 guideline recommended care-processes. To decide whether there is a difference in patient’s health the study will compare each arm of the study (usual care vs GRACE risk score) by looking at how many of these Class 1 guideline care-processes a participant receives.
The study will also look at whether the participant goes on to experience any cardiovascular related events such as cardiac death, heart failure, new onset myocardial infarction, cardiovascular hospitalisation following on from their NSTEACS to see whether there is a difference between the two arms of the study. To look at these cardiovascular related events the study requires hospital episodes and mortality data.

The GRACE Score is a prospectively studied scoring system to risk stratify patients with diagnosed Acute Coronary Syndrome (ACS) to estimate their in-hospital and 6-month to 3-year mortality.

The co-primary objective for the UKGRIS cluster-randomised trial, which plans to recruit 3000 patients from a minimum of 30 hospitals, is to assess whether the application of the GRACE risk score on patients with urgent acute coronary syndromes without ST-segment elevation (NSTEACS) admissions results in better uptake of Class I guideline recommended care-processes, and reduces the incidence of a composite cardiovascular endpoint (cardiac death, heart failure, new onset myocardial infarction, cardiovascular hospitalisation). Secondary objectives are to assess the difference in terms of:
1. unscheduled revascularisations within 12 months
2. duration of hospitalisation within 12 months;
3. patient-reported quality of life at 12 months;
4. the four individual components of the co-primary composite endpoint of cardiovascular events.

This agreement relates to the second co-primary endpoint, and on secondary endpoints 1, 2 and 4. The data required to derive these endpoints are to be obtained through routine electronic health records.

The UKGRIS study was funded by the British Heart Foundation in June 2016 and is currently recruiting patients, having opened in March 2017. The University of Leeds Clinical Trials Research Unit, a UKCRC-registered trials unit, manages the trial and comprises a multidisciplinary team of data managers, trial managers, information systems support and statisticians. All of this data is pseudonymised.

Data from NHS Digital are critical to tracking the clinical follow-up of the patients who consented to take part. Other than a mailed postal questionnaire at 12 months to assess quality of life, The University of Leeds are not performing a clinical follow-up for hospital staff to review medical records to identify relevant clinical events, admissions and / or death information hence the University of Leeds are unable to perform the planned analyses of the UKGRIS trial without the timely delivery of the required NHS Digital data.

The UKGRIS study, as a stand-alone project is wholly confined within the United Kingdom. This research dataset will comprise self-reported questionnaire data, case report forms collected during the trial, and data from other national data cokllections, including HES data and mortality data. This data will be processed to create a research psuedonymised dataset without identifiers, such as date of birth, dates of events/episodes, and including derived variables such as age at registration, numbers of days since registration event/episode.

The protocol has been harmonised with a similar study in Australia (AGRIS* ) with the intention that the two trials (plus an additional planned Canadian study) will combine these derived, de-identified datasets to perform an international collaborative individual participant data (IPD) meta-analysis. Doing so will allow the estimation of smaller differences in cardiovascular events observed during follow-up. Derived data will only be shared with the international collaborators upon agreement with NHS digital that the data is sufficiently derived to satisfy the requirements of NHS digital. The Leeds Institute of Clinical Trials will work with NHS digital to reach agreement on the data to ensure that NHS digital agree that the data is derived sufficiently prior to being shared. A special condition which prevents any onward data sharing has been added to this agreement.

Whilst the main analysis for this study will commence once full patient recruitment has completed at the end of 2019 early 2020 data is being requested now from NHS Digital to allow the study to explore the methodology.

Expected Benefits:

Acute coronary syndrome (ACS) which includes ST-elevation myocardial infarction (STEMI), non ST-elevation myocardial infarction (NSTEMI) and unstable angina (UA) comprises the leading cause of emergency hospitalisation in Europe, a leading cause of death and disability and have major impacts on health economies. NSTEACS represent over half of the cases of ACS of which NSTEMI account for around 50,000 National Health Service hospitalisations per year. Evidence from randomised controlled trials (RCTs) as well as guideline recommendations from the European Society of Cardiology (ESC) and the National Institute for Health and Care Excellence (NICE) support the use of different strategies according to risk status because allocation of a treatment strategy significantly reduces subsequent cardiovascular events. In place of generic treatment of all patients, stratified care has the potential to achieve cost-effective patient-centred treatment as well as improved outcomes.

The state of clinical practice for the management of patients with ACS falls short of the state-of-the-art based on evidence and guidelines, which recommend risk-stratified patient management. Earlier work has shown that there is considerable diversity of clinical practice across centres and countries. The University of Leeds work also reveals that, for patients eligible for care, those who had fewer missed treatment opportunities had improved survival and that this varies geographically within England. Additionally, evidence from the UK (Myocardial Ischemia National Audit Project) MINAP registry has shown that more comprehensive treatment was associated with improved outcome.
Moreover, early ‘failure’ of receipt of an evidence-based care opportunity was significantly associated with subsequent missed guideline recommended treatments. In the UK the adoption of ACS therapies, including the diffusion of primary PCI, lags behind other countries. Between 2004 and 2010 this was associated with over 11,000 avoidable deaths. It is probable, therefore, that earlier and more widespread adherence to evidence-based ACS therapies at initial presentation will result in better outcomes. What is more, the failure to apply major guideline evidence-based treatments, in those without contraindications not only increases preventable deaths from cardiovascular disease, but diminishes the cost effectiveness of therapies.

In light of the unmet need described above, it is expected the following benefits will result from the reported outputs of UKGRIS based on the use of the requested data:
1) A measure of the difference in uptake of each guideline, indicating the difference in immediate resource utilisation due to use of the GRACE risk score requiring medication prescription and / or diagnostic testing;
2) A measure of the difference in cardiovascular events, hospitalisations and unscheduled revascularisations, resulting from data requested in this application, may persuade a decision maker to adopt the GRACE risk score in routine practice for these patients to improve their outcomes, reduce patient burden due to downstream events, as well as reducing medium term resource utilisation.

2015 ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2016;37:267-315.
Myocardial Ischaemia National Audit Project (MINAP). How the NHS cares for patients with heart attack. Twelfth public report April 2012 - March 2013. National Institute for Clinical Outcomes Research, London 2013.
ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation. Eur Heart J 2012 Oct;33(20):2569-619.
NICE. Unstable angina and NSTEMI: the early management of unstable angina and non ST-segment-elevation myocardial infarction. Clinical guideline 94. 2010.
Excess mortality and guideline-indicated care following non-ST-elevation myocardial infarction. European Heart Journal: Acute Cardiovascular Care (2016) Vol 6, Issue 5, pp. 412 - 420
Geographic variation in the treatment of non-ST-segment myocardial infarction in the English National Health Service: a cohort study. BMJ Open. 2016 Jul 12;6(7):e011600
An evaluation of composite indicators of hospital acute myocardial infarction care: a study of 136,392 patients from the Myocardial Ischaemia National Audit Project. Int J Cardiol 2013 Dec 5;170(1):81-7
Acute myocardial infarction: a comparison of short-term survival in national outcome registries in Sweden and the UK. Lancet 2014 The Lancet , Volume 383 , Issue 9925 , 1305 - 1312
International comparisons of acute myocardial infarction. Lancet 2014, Volume 383 , Issue 9925 , 1274 - 1276
The cost of acute myocardial infarction in the new millennium: evidence from a multinational registry. Am Heart J 2006 Jan;151(1):206-12.

Outputs:

A download of data will be required upon approval so that the University of Leeds can present the data at the Trial Steering committee meeting

The British Heart Foundation has funded this study on the basis that The University of Leeds will be obtaining follow up data on the participants to answer the primary and secondary objectives. The University of Leeds provide them with 6 monthly updates on their progress.

The current timelines anticipate an end to recruitment by December 2019, with the final 12 months’ follow-up concluded by December 2020, after which analysis will begin to be complete by June 2021. Prior to that, the independent Data Monitoring Committee has requested an interim review of safety data available on the patients recruited so far, though no binding stopping rules will be in place.
A “Stopping rule” is a criterion (or set of criteria) that, if met, would indicate that the trial should be terminated early (that is, before the scheduled end of recruitment). Typical reasons for terminating early are futility (the final trial results are unlikely to show benefit to the intervention), harm (the intervention is leading to more adverse events, or fewer beneficial outcomes than the standard care arm) or efficacy (at this stage, the intervention benefit is such, that the study is already highly likely to have rejected its null hypothesis). In all of these cases, early termination avoids wasting the time of patients that have yet to be recruited (and avoids exposing them to unnecessary harm / lack of benefit shown in the data so far).

Stopping rules may be “Binding” or “Non-binding”/”Advisory”. Binding stopping rules are mandatory: if the criteria are met, the trial must be terminated early. Advisory stopping rules may be overruled by the DMEC if, on the balance of all the data available, there is still merit in continuing the study.

The study does not have any predetermined rules (Binding or otherwise) where the study would be stopped if the data showed a safety issue in either arm of the study. The data will be reviewed by the Data Monitoring and Ethics Committee and if they consider that it is not safe to continue with the study then it will be based on their medical and scientific expertise rather than any predefined stopping rule.

The Data Monitoring and Ethics Committee (DMEC) provide independent trial oversight and comprise independent members (that is members who are not co-applicants, not involved in trial conduct at the site level and not employees of the sponsoring or funding organisations and not from other participating organisations) with expertise relevant to the conduct of the study. The DMEC will review the safety and ethics of the trial by reviewing interim data during recruitment and will recommend on the continuation of the trial, or if any changes to the study design are indicated. Recommendations from the DMEC are made to the Trial Steering Committee, who make the final recommendation to the sponsor and funder that the study should be terminated early, if necessary. They will be provided with the following anonymised data, which is held in house at CTRU – having collected these on the case report forms - and are not requesting from NHS Digital;
• Aggregate recruitment by centre
• Aggregate screening data by centre by reason
• Aggregated numbers of deaths occurring before discharge and withdrawals
• Aggregated summary data on Protocol adherence
• Aggregate participant baseline characteristics (obtained from hospital completed data)
From the NHS Digital data download that is the subject of this application, It is expected to provide the following information to enable a single informal interim assessment (prior to completion of recruitment) of the safety profile of the GRACE and the Standard Care arms:
• Aggregate Numbers of post-discharge deaths (all-causes) in GRACE arm and the same in Standard care arm
• Aggregate Numbers of deaths (cardiac causes, pre and post discharge), in the GRACE arm and in the Standard care arm
• Aggregate Numbers of participants (and numbers of events) experiencing one or more of the component events of our composite clinical endpoint: Non-fatal myocardial infarction, New onset heart failure (admission), Cardiovascular readmission's (as well as cardiac cause of death), all for the GRACE arm, and separately for the standard care arm.
Details of the full set of data items to be downloaded for the final analysis is given in the original application.

After final analysis (expected completion June 2021) The University of Leeds plan a single publication comprising all outcome data on guideline uptake, cardiovascular outcomes, quality of life, revascularisations and hospital stay duration. The University of Leeds believe that the clinical question is of sufficient strength to submit in the first instance to a high-impact peer-reviewed general medical journal (eg New England Journal of Medicine, The Lancet, Journal of the American Medical Association, Annals of Internal Medicine, BMJ). The University of Leeds believe that these outputs would be of interest to a general medical community, hence their initial submission strategy. Should The University of Leeds be unsuccessful with such journals, they will prioritise publication in high-impact cardiology-specific journals, (eg Journal of the American College of Cardiology, Circulation). Ahead of publication, The University of Leeds would also seek to present their findings at a leading peer-reviewed international cardiology congress (eg European Society of Cardiology). In order to allow access to these outputs, The University of Leeds would either ensure that the outputs were open access, or that author manuscripts were available in depositories for access. (The British Heart Foundation mandates open access as a condition of funding).

The trial has a separate methodological sub study relating to rates of return of postal questionnaires, which may warrant a separate publication. (or inclusion in the main trial output) As this does not require the use of electronic health records, this is not relevant to the present application, and so The University of Leeds do not give further details here.
After final analysis the British Heart Foundation have agreed to an article on their website regarding the outcomes of the study.
The CTRU website will also be updated with information regarding the outcome of the study so this can be disseminated to the general public.

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

Processing:

The University of Leeds will receive data for an identified cohort for the UKGRIS trial, for whom the University of Leeds provide identifiers already collected from participants as part of the trial dataset. These are: name, address, NHS number and date of birth. This ensures the University of Leeds minimise the chance of receiving data for anyone other than consenting trial participants. Identifiers will be sent from the University of Leeds to NHS Digital in an excel spreadsheet via a secure file transfer service. (Details for which can be found in the help documentation on the service homepage at https://lictr.leeds.ac.uk/sft)

The University of Leeds receive identifiers from the cohort, which are submitted to NHS Digital and NHS Digital return the HES and Mortality data with a study id for linkage and no direct patient identifiers.

Initially, data is requested from the time of the first recruitment to the first download (being greater than 12 months after the first participant has been recruited) and this is a safety measure to monitor any difference in events between each arm and will be presented to The University of Leeds Data Monitoring Committee. National data is required to ensure that The University of Leeds have sufficient numbers to identify any safety issues in an arm.

Patients have given written informed consent to participate in the trial and to use their identifiers at the University of Leeds which are collected as part of the trial - data provided by participants and researchers in accordance with the REC-approved trial protocol and participant consent.
The University of Leeds have minimised the number of identifiers and sensitive data items to those that are needed to be able to correctly track participants and ensure that the University of Leeds can answer the study objectives.

Data will be entered into a secure password protected database held locally at the University of Leeds via an automated data import service. Either the Trial Manager or Trial Statistician will access the data to ensure it has been successfully uploaded into the database, this will be the requested NHS Digital HES and Mortality data set. The data will then be processed by the trial statisticians at the Clinical Trials Research Unit, Leeds Institute for Clinical Trials Research (LICTR) at the University of Leeds. All individuals with access to the data are substantive employees of the University of Leeds, data will only be accessed by individuals within the CTRU who are directly involved with the NHS Digital transfer and analysis of the data (Trial statisticians and Trial Manager).

Data will be linked with existing UKGRIS Trial datasets (consisting of patient demographics and clinical characteristics at registration, details of in-hospital management, and results from diagnostic tests (if done) as well as quality of life questionnaire at baseline and 12 months’ follow-up) and The Myocardial Ischaemia National Audit Project (MINAP) and British Cardiovascular Intervention Study (BCIS). The data will be used to determine secondary endpoints relating to safety in terms of cardiac cause of death, new onset MI, heart failure, cardiac hospitalisation, length of hospital stay and unscheduled revascularisations.

The only data linkage that will occur is with the above-named cardiac registry data sets (for which permissions for the data will be sought from the responsible parties). No “trend analysis” will be performed. However, as the Hawthorne Effect (the recruiting hospitals improve performance due to being observed in a trial) is a potential concern, the study may use the above-named data-sets to compare UKGRIS and non-UKGRIS patients in terms of MINAP data on patient management. Any non-UKGRIS patient data accessed for this purpose will be anonymised / aggregated with small number suppressed to minimise the risk of disclosure. There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.
Data will not be used for any other purposes: it will not be used for commercial purposes, nor for direct marketing purposes.

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


Improving the safety and continuity of medicines management at care transitions (ISCOMAT): a cluster Randomised Controlled Trial — DARS-NIC-378185-P4L5Z

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-05-13 — 2024-05-12 2021.05 — 2022.04.

Access method: One-Off

Data-controller type: BRADFORD TEACHING HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Medicines dispensed in Primary Care (NHSBSA data)
  2. Civil Registration (Deaths) - Secondary Care Cut
  3. Emergency Care Data Set (ECDS)
  4. HES:Civil Registration (Deaths) bridge
  5. Hospital Episode Statistics Admitted Patient Care
  6. Hospital Episode Statistics Critical Care
  7. Hospital Episode Statistics Outpatients

Objectives:

Bradford Teaching Hospitals NHS Foundation Trust and the University of Leeds are requesting to use NHS Digital data for a study entitled "Improving the Safety and Continuity Of Medicines management at Transitions of care" (ISCOMAT).

ISCOMAT has received a favourable ethical opinion, is funded by the National Institute for Health Research (NIHR) and is performed by a public authority. Bradford Teaching Hospitals NHS Foundation Trust's and the University of Leeds' lawful bases for processing personal data and health data (defined as special category data) for the purposes of this project are:

Article 6:1(e): Specific task in the ‘public interest’ or task that has a clear basis in law, and

Article 9:2(j): Special category data used for “Archiving in the public interest, scientific or historical research or statistical purposes”, with a basis in law.

Participants consented to have their personal data shared with NHS Digital, including personal details (initials, date of birth, postcode and NHS number) to be shared with NHS Digital for this project. Participants who withdrew their consent for data collection from routine sources will not form part of this cohort for this data application. All consent documentation and subsequent amendments to it were reviewed and approved by the ISCOMAT Patient Led Steering Group.

ISCOMAT Background and rationale:
Making the use of medicines as safe and effective as possible are priorities for patients and healthcare providers. When a patient moves, for example from hospital to home, medicine problems are common and planned changes are not always followed through. Patients particularly at risk are those with long-term illnesses taking several medicines – especially when medicines have been started or changed in hospital.

Heart failure can be managed through a combination of several different drug combinations at titrated doses. Successful management of heart failure patients’ medication can reduce hospitalisations, improve quality of life and increase survival rate. Optimising the management of medication as patients transition from hospital to home is complex, and requires co-ordinated input from different healthcare organisations, including hospitals, pharmacies and general practice, and different healthcare professions.

Heart failure affects 26 million people globally, approximately 900,000 people in the UK and the incidence of new diagnoses of the condition is increasing, affecting older people and those from lower socio-economic groups in greater numbers.

Aim:
ISCOMAT is a programme of interlinked work packages, which developed a Medicines at Transitions Intervention (MaTI) toolkit to help the way heart failure patients are supported with their medicines. MaTI was developed through a process of co-design with patients and healthcare staff, with the aim to improve the safety and continuity of medicines at care transitions, and subsequently reduce mortality and readmission to hospital.

The MaTI toolkit will be evaluated in the ISCOMAT Trial. This is a cluster randomised controlled trial (cRCT), which randomized 43 secondary care cardiology services (clusters) to implement either the MaTI or continue to deliver their usual care.

Cohort:
A total of 1615 men and women aged over 18, who were admitted to a participating hospital with a diagnosis of heart failure and evidence of at least moderate left ventricular systolic dysfunction confirmed within the last 5 years, were recruited between 06/2018 and 03/2020 and consented to share their information with NHS Digital.

Outcome and data required:
The main (primary) outcome is all-cause mortality and Heart Failure related hospitalisation within 12 months of recruitment. This is in line with the aim of the MaTI intervention, which is to reduce mortality and reduce readmissions to hospital.

The key secondary outcome is continued prescription of guideline indicated therapy at 12 months post recruitment. This will help identify if the MaTI toolkit increases the number of heart failure patients who are receiving appropriate heart failure medication, after they are discharged from hospital to home.

Other secondary outcomes will help identify any other potential benefits of the MaTI toolkit, and include: time from registration to death, or to heart failure rehospitalisation; length of time on guideline recommended medications from registration, patient understanding of medicines and satisfaction with medicines related care; number of days alive and out of hospital; hospitalisations; death due to specific causes.

A parallel cost-effectiveness analysis will include Hospital Episode Statistics (HES) Admitted Patient Care (APC), HES Critical Care (CC), HES Outpatients, Emergency Care Data Set (ECDS), Civil Registration (Deaths) Secondary Care Cut (CRD SCC) to derive a costs per all-cause deaths prevented and re-hospitalisation prevented, alongside cost-effectiveness of intervention.

Data to support primary and secondary outcomes as outlined above is available in HES, ECDS, CRD SCC, and the Medicines Dispensed in Primary Care (NHSBA) data.

Data will also be sought from the National Heart Failure Audit via the National Institute of Cardiovascular Outcomes Research (NICOR), clinical data directly from participating hospitals, and patient reported outcomes direct from participants.

Patient-level data is needed from HES, ECDS, linked Civil Registration Mortality Data and Prescribing data to allow the trial team to link these data with the NICOR data, clinical data and patient reported outcomes for our cohort of participants. The linked datasets will subsequently be used as the analysis dataset for the ISCOMAT trial.

Data is requested from the time the first consenting and eligible participant was admitted to hospital (June 2018) until 12 months after the last participant was registered (March 2021). These years are required in order to achieve the outcomes listed above. The hospitals taking part in ISCOMAT are spread throughout England and therefore necessitates the geographical spread of data requested.

Obtaining data held in electronic health records will provide a complete dataset to answer the primary and secondary outcomes. The trial was designed to use data from routine sources as it was determined that this would be the least intrusive way to answer research questions for participants and to also minimise burden on research staff at hospitals.

Data requested for this application is minimised as much as possible. This data sharing agreement relates to the cohort of 1615 (1615 out of 1641 recruited consented to share data with NHS Digital) men and women aged 18 and over at time of admission, with a diagnosis of heart failure with evidence of at least moderate left ventricular systolic dysfunction confirmed within the last 5 years. The specific data requests relate to this cohort and any admissions to hospital and instances of death, including cause of death between the date of registration and 12 months. Obtaining prescribing datasets also supports key secondary outcomes on length of time participants are prescribed guideline indicated therapies. The data requested is proportionate to the data required to answer the primary and secondary outcomes.

Organisations involved:
Bradford Teaching Hospitals NHS Foundation Trust (BTHFT) and the University of Leeds (UoL) are joint controllers. The data is processed at the University of Leeds.

The Chief Investigator is a professor of cardiovascular medicine and honorary Consultant Cardiologist. His substantive employer is the University of Leeds, and he has an honorary contract with BTHFT. The Clinical Trials Research Unit (CTRU), at the University of Leeds, is co-ordinating the trial and is responsible for trial design and conduct, including protocol development, ethics approval, trial monitoring, data collection and ongoing management, and statistical analysis and reporting. All data for the cohort of patients recruited to the trial is processed and stored at the CTRU. The Academic Unit of Health Economics (AUHE) at the University of Leeds will perform the cost effectiveness analysis, and data will be transferred to the trial health economist for processing. The CTRU and the AUHE have both completed the Data Security and Protection Toolkit (DSPT) which evidences each department's compliance against the National Data Guardian’s 10 data security standards.

ISCOMAT is delivered by a multidisciplinary research collaboration between BTHFT (as NHS lead and Sponsor), the University of Bradford and University of Leeds. The collaboration includes patient representatives, and a Patient Led Steering Group is actively involved in conduct and oversight. A contract is in place between the funder (Department of Health) and BTHFT (NHS Lead), and a collaboration agreement is in place between the BTHFT, the University of Leeds, and the University of Bradford. The ISCOMAT trial is the fifth in a series of interlinked work packages that comprise a NIHR Programme Grant for Applied Research (PGfAR). An earlier work package (1B) successfully obtained data from NHS Digital for a cohort of 53 participants (DARS-NIC-40493-G5Y6K). The University of Bradford are not receiving, or otherwise accessing and processing, any data under this data sharing agreement. Processing activities are undertaken at the University of Leeds as fully outlined in the Processing Activities section.

Decisions relating to the processing of personal data remain with BTHFT and UoL. University of Leeds and BTHFT as joint controllers confirm that they will ensure a GDPR compliant, publicly accessible transparency notice is maintained throughout the life of this agreement.

The trial is funded by the NIHR Programme Grants for Applied Research (RP-PG-0514-20009). The trial funder does not make decision on the processing of personal data, and has no role in study design, data collection, data analysis, data interpretation, or writing of the final report.

Expected Benefits:

Heart failure affects 26 million people globally and approximately 900,000 people in the UK. With the incidence of new diagnoses of the condition increasing, the ISCOMAT trial results have the potential to inform the treatment and care of heart failure patients when especially vulnerable during a care transition. The benefits from this dissemination will not be realised for health care until the main results of the trial are published in 2022.

The benefits focus on patient care improvement, and dissemination will be led by the trial research team, including programme management group, trial management group and trial steering committee. The results, placed in open-access peer reviewed publications, are hoped will provide an evidence base with potential to impact on clinical guidance, including National Institute for Health and Care Excellence (NICE) guidelines on heart failure and medicines related care. It is hoped that benefits for health service commissioners will include provision of evidence to support future commissioning of community pharmacy services as well as the need for more effective optimisation of heart failure treatment, with associated health benefits. The aim of this is to ensure that patient medicines management is optimised, and the burden of cardiovascular disease is reduced through preventable cardiovascular events that occur in the period after patients with heart failure are discharged from hospital. Our findings are intended to be, with modifications, transferable to other patient groups who have long-term conditions, frequent hospital readmissions and polypharmacy.

Outputs:

The main analysis is due to be completed by March 2022, with the aim to publish main trial results in late spring, early summer 2022. Results will be published in open access and peer reviewed journals, including publication via the National Institute for Health Research's own journal library, the Lancet, the British Medical Journal (BMJ) and the European Heart Journal (EHJ). Results will also be presented at relevant conferences linked to cardiology and patient safety, including the European Society of Cardiology Congress (Summer 2022). Longstanding and ongoing engagement with stakeholders, including both scientific and policy-making audiences will provide a direct pathway to impact for the outputs of this research.

The Patient-Led Steering Group will inform the dissemination strategy and its members will play an active role in the format and content of academic papers (specifically patient implications) and will present at local, regional and national conferences and wider stakeholder meetings.

Only analyses featuring aggregated data with small number suppression will appear in outputs.

The results and outputs of the study will be further communicated via the study team's websites, social media accounts and through other public promotion of research utilising the study team’s networks, including clinical networks, scientific networks and charitable organisations with heart failure and medicines safety focus.

Lay summaries will be added to the trial website (https://www.bradford.ac.uk/iscomat/) and the trial registry will be updated (https://doi.org/10.1186/ISRCTN66212970). Summaries will also be provided to participating sites. The Use My Data citation - “This work uses data provided by patients and collected by the NHS as part of their care and support” - will be used in all outputs as appropriate, to further acknowledge that the research involved patient data. These outputs will follow the main analysis in 2022.

If the intervention is shown to be effective (as supported by NHS Digital data linkage for primary outcome), the network of champions (patients, staff and other stakeholders) created during the programme will be used to spearhead a plan for adoption and spread. Materials developed during the programme will be made available for wider use.

Processing:

The trial statistician at the Clinical Trials Research Unit (CTRU) will provide the following identifiers: sex, date of birth, postcode and NHS number. Study ID for each participant will be provided to allow linkage of the NHS Digital data to the trial data held by the CTRU. For each participant, date of admission to hospital, and 12 month post registration will be provided. This will provide assurance that minimum data required is obtained. The data will be transferred to NHS Digital via the required secure platform.

NHS Digital will perform an automatic cohort tracing system to search the data provided against existing electronic records to generate a set of records that belong the cohort of 1615 trial participants. This will include linkage of data from Hospital Episode Statistics (HES) Admitted Patient Care (APC), HES Critical Care (CC), HES Outpatients, Emergency Care Data Set (ECDS), Civil Registration (Deaths) Secondary Care Cut, and the Medicines Dispensed in Primary Care (NHSBA) data.

Opt-outs will not be applied, as all participants included in the cohort have consented for their personal data to be shared with NHS Digital to obtain information from their electronic health records, and have not withdrawn their consent for sharing of their personal data with NHS Digital for this purpose.

NHS Digital will transfer the linked record level data to the trial statistician on one occasion. NHS Digital will return pseudonymised data linked using the CTRU supplied Study ID. On receipt of data from NHS Digital, the trial statistician will transfer the data into a secure folder prior to using in statistical software for analysis. As a first step, the trial statistician will perform data cleaning in accordance with CTRU Standard Operating Processes, for example, to ensure no duplicate episodes, no admission after date of death (if deceased). The trial statistician will subsequently link the data obtained from NHS Digital with the trial data held at the CTRU on this cohort, to derive a trial analysis dataset. Linkage of the data will be by the Study ID. Participants in the trial dataset will only be identifiable by their Study ID and all statistical analysis will be conducted with reference to this – there will be no link to patient identifiable data, all data will be pseudonymised.

The statistical analysis will be conducted within a statistical software package in accordance with a Statistical Analysis Plan which will be finalised and agreed by the Trial Management Group in advance of any analysis being undertaken. For the analysis of the primary outcome of all-cause mortality and heart failure rehospitalisation over 12-months follow-up, an indicator will be derived for each participant based on NHS Digital data to indicate whether or not the participant has experienced the primary outcome. The outcome will be compared between the trial arms using a random effects logistic regression model which will include trial data held by CTRU. A similar approach will be taken for the analysis of the secondary outcomes with the most appropriate statistical model chosen based on the type of outcome.

Data items specified in the Health Economics Analysis Plan will be transferred to the trial health economist, via CTRUs Secure File Transfer. Trial statisticians and health economists who access the data are all substantive employees of the University of Leeds, and undergo relevant Data Protection and Information Security training on a regular basis as part of their employment at the University of Leeds.

All data for the cohort of patients recruited to the trial is processed and stored at the CTRU (Organisation Data Service (ODS) is ECC0010), and the Academic Unit of Health Economics (AUHE) at the University of Leeds will perform the cost effectiveness analysis (ODS is 8E218-SEED). No record level data disseminated via NHS Digital for this application will flow from the University of Leeds.

The CTRU server infrastructure is split between two data centres on the main University of Leeds campus. Backups taken from this infrastructure are replicated to the University of Leeds disaster recovery site at the University of York, with tape backups encrypted to AES 256 being kept at Iron Mountain. In all locations data is stored encrypted on disk/ tape. The ability to decrypt is only held by the CTRU. The two disaster recovery sites provide different recovery options. The site at University of York is a warm online copy on disk that can be retrieved instantly for the last 30 days. The Iron Mountain site holds a cold offline copy on tape for 12 months. Neither site can access the data. At the University of York location, the server is University of Leeds own equipment and connects only to the University of Leeds network. This server holds the disaster recovery copy of University of Leeds backups. There is no data processing at this site. The University of York only provides the physical space and power to support this.

Only summary results (no record-level data) will be made publicly available via open access publications, including the NIHR Journals Library publication of the final report. No third party will have access to the data. Data will not be used for any other purposes, and it will not be used for commercial purposes, nor for direct marketing purposes.

The data will only be accessed by authorised members of the team who are all substantive employees of the data controllers through a secure drive on the University of Leeds network. The files will be restricted to those processing data.


Does patient ethnicity predict outcome following neck of femur fracture? — DARS-NIC-318632-T0N3M

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

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2021-09-23 — 2022-09-22 2021.11 — 2022.02.

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Hospital Episode Statistics Admitted Patient Care

Objectives:

There are large variations in the outcomes of orthopaedic surgery across ethnic groups in England and Wales, with patients from Black and Minority Ethnic (BAME) backgrounds struggling to access care and having worse outcomes.

A pilot study at a University Teaching Hospital which serves a large BAME population assessed a locally held database of neck of femur (NOF) fractures. Fracture patterns and outcomes post-fracture in patients from different ethnic backgrounds were compared. South Asian patients were more likely to have the worse fracture types, more likely to be discharged to their own home, and tended to have more co-morbidities and worse mobility. Achievement of best practice tariff (BPT) targets during care was associated with preferentially better outcomes in White patients versus South Asian patients. These findings have not been demonstrated previously.

Traditionally accepted distribution for fracture types, patient demographics and patient mobility may be inconsistent across ethnic groups. As a result, targets for ideal treatment may not be reliably associated with a reduction in mortality in BAME groups. The aim of this data sharing agreement is to compare the outcomes following a NOF fracture across ethnic groups in the UK and explore reasons if any differences are observed which may include physiological differences between groups or other social determinants of health. This analysis is being completed in support of the National Hip Fracture Database service evaluation activity “to improve the quality and cost-effectiveness of hip fracture care; and to reduce the incidence of the injury by improving secondary prevention”. The NHFD has section 251 approval in support of its aim "To support audit, service evaluation and quality improvement activity by NHFD, NHFD participant sites and approved third parties". The analysis being undertaken by the University of Leeds is in the capacity of a service evaluation by an approved third party.

Pseudonymised data will be acquired from the NHFD. This will be linked with Hospital Episode Statistics (HES) Admitted Patient Care (APC) and Civil Registration (Deaths) data, as well as equivalent hospital episode data for patients attending Welsh hospitals using a unique study ID given to all patients in the NHFD. Ethnic groups deemed to have high stability from census data will be used to estimate ethnic group specific demographics, fracture types and risk factors for mortality. Ethnic groups assessed will be White (British/ Irish/ Other), South Asian (Indian, Pakistani, Bangladeshi), Asian (Chinese), Caribbean and African.

Data required from NHS Digital’s HES APC and Deaths datasets includes demographic data (e.g. Age on admission, Ethnic Category, Sex of patient, Index of Multiple Deprivation, Lower Super Output Area (LSOA)), as well as data relating to the diagnosis of, procedures relating to, and subsequent outcomes of patients with NOF fractures. These demographic covariates will be controlled for to study the effect of ethnicity.

The University of Leeds will link NHFD data with the pseudonymised NHS Digital data with the equivalent pseudonymised Patient Episode Database for Wales (PEDW) data to investigate outcomes following NOF fracture by ethnicity. Pseudonymised NHFD data includes variables relating to fracture side, classification and pathology; surgical variables; post-operative outcomes; BPT criteria (geriatrician/ specialist fall/ multi-disciplinary assessments); discharge variables (when and where) and follow-up variables (mobility, medications, residential status).

Selecting smaller geographical areas rather than requesting national data was considered but is not feasible because it would affect the robustness of the findings. The previous pilot study conducted in a geographical location with a high South Asian population included only 53 South Asian patients and even fewer from other ethnic backgrounds from a sample of 1,520 patients. A national data set is required to draw firmer conclusions and study patients from various BAME backgrounds. The geographical spread is required to be England and Wales specifically since this is the geographical coverage of the NHFD. The aim is to include all NOF fractures and the inclusion criteria are a hip fracture on the NHFD between 01/01/2009 and 01/02/2021. This timeframe is necessary to have robust, large scale data to be able to draw accurate conclusions. The data requested is the minimum data set required to achieve the aims of the service evaluation. There are no alternative, less intrusive ways of achieving the purpose.

The NHFD itself is an audit which aims to improve the processes of care and the outcomes for patients with hip fractures, as well as ensure reliable information on quality of care and outcomes is available for patients and the public. The outcomes of this service evaluation align with the outcomes of the NHFD, but include a break down by ethnicity, including specific demographic factors not covered by the current NHFD. The primary outcome will be patient mortality at 365-days post fractured NOF for BAME patients as compared to the White population.

The secondary outcomes will be to assess:
- Differences in mortality at 30- and 120-days
- Associations of clinical comorbities with increased mortality
- Differences in fracture type
- Differences in mobility and residential status
- If BPT achievement is associated with a different outcome

The University of Leeds will undertake this work to support service evaluation and quality improvement activity by the NHFD. University of Leeds will be the controller and processor of this data. HQIP act as data controllers for the NHFD but do not have access to linked data analysed by researchers at University of Leeds. The project is funded by the Royal College of Surgeons of Edinburgh (RCSEd). RCSEd do not determine the purpose or the manner in which the data will be processed.

The justification for processing the data by University of Leeds is Article 6(1)(e) of the GDPR: (processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller).

The justification for the processing of the special category data (health data) by University of Leeds is Article 9(2)(j) of the GDPR: (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.

There is no wider project or collaboration planned.

Expected Benefits:

This evaluation is hoped to lay the foundations in ensuring health services are allocated appropriately and fairly to all accessing treatment in the NHS. The evaluation aims to assess the difference in outcome following neck of femur (NOF) fracture for patients from Black and Minority Ethnic (BAME) backgrounds, and inform National Hip Fracture Database (NHFD) policy on data collection. It intends to provide evidence for the requirement of ethnicity data collection, therefore allowing monitoring to ensure all patients from all backgrounds receive optimal care and treatment following a neck of femur fracture. Trusts will be able to assess the percentages of ethnic minority patients and allocate resources as appropriate.

Through publication in the NHFD Annual Report, Trusts will have easy access to the findings of this evaluation. Publishing in peer-reviewed journals is also anticipated to allow greater discussion of the strengths and weaknesses of the results and will provide the benefit of peer-review of the work from third parties. The University of Leeds will identify risk factors as a means of identifying future areas for investigation.

An example of a future area for investigation that may be generated from this evaluation is the identification of a variation in the incidence of different fracture types between ethnicities. If such a variation does exist, it is anticipated that it will be possible to identify morphological differences in the hip that may account for this. Currently, it is recommended all patients with a displaced intracapsular femoral neck fracture receive a cemented implant. However, morphological differences in the hip may mean certain ethnicities would benefit from a different type of implant. Therefore, patients from BAME backgrounds may be suffering from a higher rate of complications from the use of certain implants, which is likely to lead to costly revision surgery. If the data demonstrates such an effect, it will provide useful information for Trusts to allocate healthcare resources.

It is also known that patients from BAME backgrounds are more likely to suffer from deficiency of Vitamin D, as such bisphosphonate treatment may be less effective in these patients. If the data shows an unexpected effect of bisphosphonate therapy in BAME patients, this may enable future research studies to identify the causes for this which could in turn lead to a trialling of alternative therapies.

Outputs:

The NHFD produce an annual report in which the findings of this evaluation are expected to be included. A report to the Royal College of Surgeons of Edinburgh (RCSEd) as the funding body will also be prepared.

To reach a wider scientific audience, submission to peer reviewed journals are intended to be prepared including to The New England Journal of Medicine, The Lancet, British Medical Journal, and Bone and Joint Journal. It is planned that presentations at Orthopaedic conferences including the American Academy of Orthopaedic Surgeons and British Orthopaedic Association will be prepared.

All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide.

This evaluation is the start of a process of ensuring all patients receive optimal care and treatment following a neck of femur fracture. Members of the study team previously conducted a patient involvement focus group with Bradford residents. The overwhelming message was that care should be tailored to meet individual needs. Patient and Public Involvement (PPI) and focus groups are intended to be consulted to determine the best way to reach patients from various backgrounds with the results of this evaluation. Focus groups consulted in the lead up to this project were surprised that hip fracture care is not more patient specific already. 'Ask the Researcher' events will be held to reach a wider public audience. The aim is to ensure that knowledge developed by this evaluation improves outcome following hip fracture.

Outputs are planned to be realised December 2023.

Processing:

Crown Informatics will send NHS Number, date of birth, Full postcode, Name and FFFAP ID (a unique National Hip Fracture Database (NHFD) person identifier) for all patients in the NHFD database with a neck of femur (NOF) fracture to NHS Digital and NHS Wales Informatics Service (NWIS). Pseudonymised data with the same FFFAP ID will flow to researchers at University of Leeds, with NHS Digital providing HES APC and Civil Registrations (Deaths) data, and NWIS providing Patient Episode Database for Wales (PEDW) data. HES APC data will be filtered to include only the spell relating to the neck of femur (NOF) fracture admission, based on the NOF fracture diagnosis code.

Crown Informatics will also send an encrypted version of pseudonymised NHFD data to the study chief investigator (CI) at the University of Leeds who will transfer data to Leeds Institute of Data Analytics (LIDA). The CI nominates LIDA members to receive the password for data decryption from Crown Informatics.

The pseudonymised data from NHS Digital, NHS Wales Informatics Service and the NHFD will be linked using the FFFAP ID inside the LASER cloud platform at the University of Leeds as needed for analysis.

Patients in the ethnic minority groups will be matched independently to a cohort of the control population (White). Odds of dying at 30 days, 120 days and 365 days respectively will be analysed between White and ethnic minority groups with adjustment for all clinically relevant covariates.

Data processing is carried out by substantive employees and honorary contract holders from the University of Leeds who have been appropriately trained in data protection and confidentiality. Researchers who work on the pseudonymised data set do not have access to the list of patient identifiers sent to NHS digital for linkage purposes.

There is no requirement, and no attempts will be made to identify individual patients. The full Date of Death is required to be able to calculate Kaplan Meier survival curves. Researchers will not be linking NHS Digital data with any other datasets except those listed above. There will be no capacity for researchers to identify any individual patients.

Data will be held at the LIDA, University of Leeds on the LASER cloud platform which is supported by Microsoft Azure. Microsoft Limited supply Cloud Services for the University of Leeds and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement.

Access to the data is only granted to users who have an authorised platform account and the correct permissions to access the project-specific secure environment. To access this secure environment, those authorised users will log into the platform using their credentials and multifactor authentication. Once logged in, they can remotely connect to the secure environment. The secure environment does not permit internet connection, clipboard sharing (copy+paste between systems), nor any other mechanism to access/transfer files unless via means that are documented in the platform’s Information Security Management System.

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, the University of Leeds must ensure 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.


Yorkshire Specialist Register of Cancer in Children and Young People — DARS-NIC-11809-H1Y3W

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

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

Purposes: No (Academic)

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

When:DSA runs 2019-09-01 — 2020-01-31 2017.06 — 2021.09.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Outpatients
  3. Hospital Episode Statistics Admitted Patient Care
  4. Mental Health and Learning Disabilities Data Set
  5. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  6. Mental Health Services Data Set
  7. Mental Health Minimum Data Set
  8. Emergency Care Data Set (ECDS)
  9. HES-ID to MPS-ID HES Accident and Emergency
  10. HES-ID to MPS-ID HES Admitted Patient Care
  11. HES-ID to MPS-ID HES Outpatients

Objectives:

The University of Leeds requires HES and mental health data for a specific cohort to be used, alongside data collected in the Yorkshire Specialist Register of Cancer in Children and Young People (YSRCCYP), to continue its epidemiology and health services research programme.

For background, the YSRCCYP is a regional population based register containing detailed demographic and clinical information on children and young adults aged 0-29 years diagnosed with cancer since 1974. The YSRCCYP covers the Yorkshire and Humber Strategic Health Authority (SHA) which has a total population of 5 million people. Spanning an area of 15,000 square kilometres the Yorkshire and Humber SHA comprises a range of urban and rural communities with a significant ethnic minority population resident in parts of West Yorkshire.

The YSRCCYP research team, within the University of Leeds, is notified of patients eligible for inclusion in the YSRCCYP either directly by the patient’s treatment centre or via electronic reports from the National Cancer Registration and Analysis Service. The YSRCCYP research team then obtains information on patients by manual data abstractions from hospital records. Detailed data on the patient and diagnosis, including treatment information for each of these cases is obtained by a sole data collection officer via the medical records at relevant hospitals in the area, and annual follow up of all cases takes place to ascertain data on any relapses or deaths through letters sent either to the patient’s treating consultant or general practitioner. Data on 9,500 patients have been collected since 1974, however linked HES and mental health data was required for only 8,500 as the cohort shared with NHS Digital excludes participants who passed away before 1996. The cohort submission under approval of this request will consist of approximately 7,000 patients.

The YSRCCYP was originally set up in collaboration with local clinicians to provide research information. Since 1994, the YSRCCYP database and research programme has been managed by and at the University of Leeds’ Division of Epidemiology & Biostatistics. The University of Leeds is the Data Controller for the YSRCCYP with sole responsibility for determining the purposes for which and the manner in which any personal data are processed. The work is currently funded by the Candlelighters Trust.

The purpose of the YSRCCYP is to facilitate population-based epidemiological and health services research. The use of HES and mental health data contributes to this by providing additional information that can be linked with and analysed with data from the YSRCCYP data. The HES and mental health data are not added into the YSRCCYP research database. The two datasets are stored separately but contain common unique study IDs enabling data to be linked at record level. Where required for specific research, relevant data are extracted from the respective databases, linked and analysed by the YSRCCYP research team.

A current research focus is on hospital burden around the time of diagnosis and treatment and monitoring long term risks of hospitalisation associated with cancer treatment. One specific processing activity will relate to describing the risks and prevalence of mental health illness within the cancer cohort compared to the general population.

This type of epidemiological and health services research has the potential to benefit future patients by identifying risk factors which can be used by health professionals to identify those at greatest risk of mental health illness so that interventions and appropriate support can be implemented. It may also reveal important environmental risk factors, examine changes in incidence rates which may help to identify possible causes and understand survival patterns according to ethnic group and socio-economic status in order to ensure that there are no inequalities in outcomes or access to specialist cancer care for certain sub-populations.

The YSRCCYP research team’s research plans include the following objectives:

1) To describe the total burden of hospitalisation among the Yorkshire cancer population aged 0-29 years, to identify clinical and sociodemographic factors which influence the likelihood of hospitalisation and to investigate how hospitalisation rates have changed since 1997.

2) To understand patient care pathways through the NHS before, during and after cancer diagnosis. This includes assessment of time to diagnosis for children and young adults diagnosed with cancer under the age of 30 years to identify where improvements can be made to minimise delays in diagnosis leading to better prognosis and less stress and anxiety on patients and their families.

3) To calculate the risks and costs to the NHS of adverse health events requiring hospital admission for survivors of cancer in this age group so that clinicians can provide appropriate follow-up care.

To address aim 1 above the YSRCCYP research team will utilise HES and mental health data to investigate long term risks of respiratory and mental health illness in the cohort and identify sociodemographic and clinical factors which may affect these risks. The YSRCCYP research team also wish to determine the relative excess risk of these conditions within the cancer cohort compared to the general background population and, in order to make this comparison, requires a separate pseudo-anonymised extract of HES data containing all episodes for patients in the Yorkshire and Humber SHA area only under the age of 60 at admission (the oldest person currently registered). This separate extract is covered under a separate Data Sharing Agreement (reference: NIC-155843-0MQMK).

The YSRCCYP research team require some data items classed as sensitive. These are the Referrer code, which indicates the manner in which the patient was referred to hospital by ascertaining the code of the referring organisation. This allows the YSRCCYP research team to identify particular patient pathways which are associated with an optimal time to diagnosis, a key indicator known to influence survival. Additionally the Consultant code data field is required because it enables the YSRCYYP research team to work out whether patients receive care at specialist cancer centres as opposed to general district hospitals, in order to address important health services research questions such as: ‘Does specialist care improve patient outcomes for children and young people including length of hospital stay and reduce subsequent morbidity and mortality?’. There are currently no databases which link consultant codes to specialist cancer centres for childhood and young adult cancer, so this process needs to be done manually using cohort linked NHS Digital data and the YSRCCYP database.

Yielded Benefits:

iii. Yielded Benefits : The YSRCCYP database has yielded several benefits, for example: • The data collected as part of the YSRCCYP has allowed researchers to better understand the burden on NHS specialist services of late cardiovascular and respiratory morbidity as well as second cancers in relation to childhood and young adult cancer survivors and quantifies the long-term risk of such morbidity for survivors and healthcare professionals looking after them. • The YSRCCYP database has facilitated the production of an up-to-date summary of the latest literature relating to late consequences of cancer treatment on reproductive health, describing the impact on both fertility and pregnancy. • It has allowed researchers to quantify respiratory morbidities, treatment-related risks and their relationship to subsequent morbidity and mortality among long-term survivors of childhood and young adult cancer in Yorkshire. By age 40, cumulative incidence for an admission for any type of respiratory condition was almost 50%. Respiratory admission rates were almost 2 times higher in cancer survivors than in the general population. Treatment with chemotherapy with known lung toxicity increased the risk of admission for all respiratory conditions. Subsequent mortality was highest in those admitted for pneumonia compared to other respiratory conditions. • It has allowed researchers to quantify the prevalence and spectrum of mental health problems found in adult survivors of childhood cancer, based on a systematic review of the current evidence. Problems ranged from depression, anxiety, behavioural problems and drug misuse. Factors increasing the likelihood of mental health problems included treatment with high-dose anthracyclines, cranial irradiation, diagnoses of sarcoma or central nervous system tumours and ongoing physical ill health. The review recommended further work to identify childhood cancer patients who are at risk of developing late mental health morbidity.

Expected Benefits:

The benefits to health and social care will include:
1. Improved patient care. This work will identify to clinicians, commissioners and patients themselves of those individuals who are at greatest risk of hospitalization; this will enable follow-up practices to be tailored to patient needs, help identify potential health problems early and intervene so that patient wellbeing is maximized and NHS burden minimized. For example, those individuals identified from the risk stratification model as being at greatest risk of mental health illness will be offered additional support from NHS services (e.g. psychiatry, social care) through their treating oncologist or GP. The risks of depression following cancer treatment will help to describe the NHS burden of mental health problems in this vulnerable population. This knowledge will be informative to paediatric oncologists and other allied health professionals caring for patients, as well as their GPs, by improving awareness of the timing when depression is likely to be diagnosed so that the quality of care can be improved. Patients will be informed of their risk group via their treating consultant or at their annual hospital clinic follow up appointment. Their GPs will also be informed of the results of the risk stratification via the hospital consultant team. Anticipated dates to complete these activities are by December 2018.

2. Evaluation of treatments to identify best practice and guidance. Work to understand the reasons for the hospitalisation so researchers can identify whether certain treatments are associated with an increased risk of hospitalisation and disseminate this information through scientific journal articles. This will mean that alternative treatment modalities and optimal care can be planned which minimize these complications. Anticipated dates to complete these activities are by June 2019.

3. Evaluation of service provision. Highlight any inequalities in access to specialist cancer care services, particularly in older teenagers and young adults, so that all patients have an equal chance of obtaining the best care irrespective of their personal circumstances and thereby having the best chance of cure. The work will be written up in the form of reports to commissioners and journal articles so that clinicians and commissioners can use this information in order to make any necessary changes to service delivery so that the entire Yorkshire and Humber cancer population is served equally well. Anticipated dates to complete these activities are by December 2018.

4. Financial planning. Information on hospital activity burden and NHS costs associated with the diagnosis and treatment of children and young adults with cancer will be calculated by the University research team in collaboration with health economists at the Leeds Institute of Health Sciences. Changes in costs over the last 20 years will be reported, adjusting for inflation, in order to provide cost projections over the next 10 years. This information will be collated in the form of a report to specialist commissioners of childhood and adolescent cancer services in the Yorkshire & Humber region so that, where required, service changes can be implemented in order to meet future NHS patient demand. Anticipated dates to complete these activities are by December 2019.

At the moment, these data are lacking and once identified by the YSRCCYP research team, they will provide important information:
* to clinicians to help better manage their clinic populations,
* to specialist commissioners to monitor the effectiveness of cancer care and
* to patients in order to understand more about their own risks of complications associated with the treatment they have received and wherever possible self-manage their own care and wellbeing.
* to identify gaps in access to specialist care by the research team for two distinct populations:
i) teenagers and young adults, who do not benefit from the same level of centralised care as that in place for younger children, and
ii) South Asians as they are more likely to present with cancer due to genetic risk factors. Improving care for teenagers and young adults and the south Asian population will ensure that their survival rates are optimal and equivalent to other age groups and ethnic groups, and any subsequent complications of treatment are minimized and if these do occur are then managed appropriately by specialist NHS professionals to ensure a full recovery.

Outputs, such as the risk stratification model, will be integrated into clinical practice through established links between the YSRCCYP research team and paediatric and adolescent oncologists throughout the Yorkshire region. The research programme as a whole benefits enormously from the long-running, close collaboration with haematologists and oncologists in the Yorkshire and the Humber region who all help to ensure that the University's research findings are effectively translated into clinical practice and are involved in all outputs from the YSRCCYP database.

Outputs:

Work describing risks of health effects of treatment in relation to respiratory illnesses will be completed by the YSRCCYP research team and submitted for publication in the British Journal of Cancer (or similar) by June 2018. The June 2018 publication follows a June 2016 publication where descriptive statistics have been produced showing the respiratory conditions diagnosed within the linked cohort. The background admission rates in the general population are required over the same time period to enable further statistical analysis to be carried out. Outcomes of the work will also be disseminated in open-access journals (e.g. BMC Cancer) and presented at conferences including the National Cancer Registration and Analysis Service Cancer Outcomes annual meeting, Teenage Cancer Trust and the International Society of Paediatric Oncology annual conferences. Further work will be submitted to the European Journal of Cancer (or similar) in relation to specific mental health outcomes by December 2018. Analyses describing the variation in clinical pathways including delays and time to diagnosis will be submitted for publication by June 2018 to Journal of Clinical Oncology (or similar).

Additional work describing the rates of hospital activity and differences between ages at diagnosis (e.g. 0-14 vs 15-29) and ethnic group (e.g. south Asian vs non-south Asian) will be completed by October 2017 and submitted for publication to the British Journal of Cancer by December 2017. Details of risk stratification models and the methodology to derive these for individual patients will be disseminated by the research team to every clinician involved in the care of children and young people (CYP) in December 2018. This will be supported by the Yorkshire & Humber CYP cancer network that holds details of all practicing NHS CYP cancer teams and clinicians in the region.

Summary reports of the work and research undertaken will be compiled and also made available on the Yorkshire Register University of Leeds website (http://medhealth.leeds.ac.uk/info/545/yorkshire_specialist_cancer_register), according to the timelines listed earlier in the document.

All outputs will be aggregated with small number suppression in line with the HES Analysis Guide.

As the funder, the Candlelighters Trust may request information for use in its own information dissemination and publicity materials. For example, they may ask for the number of new cases diagnosed per year in Yorkshire and projected incidence rates. The University of Leeds would only share information that is available as a result of the processing activities described above – i.e. the YSRCCYP would not undertake further data processing in order to derive information requested by the Candlelighters Trust and any information shared would be put in the public domain. For clarity, the University of Leeds is not obliged to provide information on request to the Candlelighters Trust and would not share any data that are not aggregated with small numbers suppressed in line with the HES Analysis Guide.

The linked NHS Digital data alongside the background hospitalisation rates will be used to derive key information which will be provided by the YSRCCYP research team to clinicians involved in the long-term care of young people identifying each individual’s risk stratification group (defined as being at ‘low’, ‘medium’, or ‘high’ risk of future complications or health effects, based upon their previous hospital activity patterns, treatment mortality, dose, cancer type and stage). The risk stratification model will be devised by the YSRCCYP research team and disseminated to clinicians in the Yorkshire and Humber region via the Y&H Children’s and Young People’s Cancer Network (December 2018). Only those clinicians involved in the direct care of individuals with cancer will be provided with details of the risk stratification model. Health care commissioners will be provided with aggregated cancer intelligence data on the number of survivors currently being seen at each NHS Trust according to risk stratification group, so future services can be planned effectively (June 2018).

Data will be held for as long as the research project is funded to undertake this piece of epidemiological and applied health research. Though work is currently planned until December 2019, the current funding expires on 31st August 2017. Subject to securing ongoing funding, the data would be retained until December 2019 to allow sufficient time for completion of analyses, submission and final publication of papers.

Processing:

The University of Leeds previously securely transferred files of identifiers for patients in the YSRCCYP (NHS Number, Date of birth, sex and postcode plus a unique study ID) to NHS Digital. NHS Digital returned linked HES and mental health data up to the period 2014/15 including the unique study ID and no other identifiers. This process will be repeated to obtain more recent HES and mental health data for the patients previously linked and to obtain HES and mental health data for patients added to the YSRCCYP since the previous linkage.

The University of Leeds stores the data on an encrypted secure area network (SEED) and access is restricted to individuals working on the YSRCCYP register research programme. Access to the record level data will only be by substantive employees of the University of Leeds and located within the Division of Epidemiology and Biostatistics. No NHS Digital data will be transferred outside of the University of Leeds or shared with any third party individual or organisation (apart from where stored at 2 disaster recovery sites at the University of York and Iron Mountain, where data will be stored only for the purpose of disaster recovery and not processed for any other purpose).

The cohort linked data (HES and mental health) and the pseudo-anonymised HES extract, provided under a separate Data Sharing Agreement (reference: NIC-155843-0MQMK), are stored in separate files and are distinct from the YSRCCYP data itself. The pseudo-anonymised HES extract will not be linked to the cohort data supplied by NHS Digital or in the YSRCCYP database. Different pseudonymised HES IDs will ensure this is not possible.

On receipt of cohort linked data (HES and mental health) the YSRCCYP research team undertake the following processing activities:

The data are initially checked for any errors or inconsistencies. This involves checking to ensure no duplicate episodes remain, which may have arisen either due to supplied duplicate HES episodes or the overlap between previously received HES data by the YSRCCYP research team, some of which may relate to provisional data releases. Further checks are made to ensure no multiple admissions existed which were less than 2 days apart with the same HES_ID, and no admission entries occurred after the date of death if deceased (the latter which is obtained from YSRCCYP database).

Length of hospital stay is calculated from the dates of admission and discharge and compared between cancer diagnostic groups, age groups, gender, ethnic group, socioeconomic status, level of specialist care, and distance from residential address to hospital (hence reasoning why the University needs OA code and grid reference).

Upon completion of checks, an extract of identifiable data (Date of Death and Date of Birth) is taken from the YSRCCYP database and linked to fields from the cohort linked HES data to calculate variables such as the duration from admission to death and age at admission where such variables are relevant to specific research questions.

The data will be compared with (but not linked with) data on inpatient hospital admissions for the general population in Yorkshire under the age of 60 derived from the pseudo-anonymised HES extract, provided under a separate Data Sharing Agreement (reference: NIC-155843-0MQMK). General population data will be compared with a population of the same age range in the cohort who were diagnosed with childhood or young adult cancer. The aim is to assess whether certain hospital admissions are more (or less) common amongst a population of survivors of childhood and young adult cancers following treatment compared to the general population. The risk of admissions of a certain diagnosis in the cancer population will be compared to that in the general population. The YSRCCYP research team aims to look at the whole admission pattern of patients, not simply those that occur in the primary diagnosis fields and therefore require an episode level extract as opposed to aggregated counts of admission.

Summaries of the results will be presented orally at conferences and are intended to be published in academic or medical journals. All outputs will be aggregated with small numbers suppressed and in line with the HES Analysis Guide.

Researchers who are not substantively employed by the University of Leeds may apply for access to data from the YSRCCYP but data supplied by NHS Digital will not be shared with any third parties.

Data will only be used for the purposes described in this statement. The NHS Digital data will not be linked to any other data apart from YSRCCYP data.

The YSRCCYP research team requires data from the full period from 1996/97 to 2016/17 (latest available) for several reasons. Firstly in order to address aim 1 investigating changes in levels of hospitalisation over time and within specific cancer types, age groups and sociodemographic groups. Secondly to maximise statistical power for analyses given the rarity of childhood and young adult cancer; also to assess changes in access over time to specialist cancer care services, as NHS policy regarding the recommendations for treatment of children and young people with cancer has changed with the opening of Principal Treatment Centres in hospitals across in England throughout this time frame.

Evaluating clinical care pathways and time to diagnosis also require data of all admissions prior to cancer diagnosis. The late health effects for childhood and young adult cancer survivors may occur any time after treatment ends and the risk of late effects increases as the cohort ages. In order to fully evaluate the total burden of adverse health events in these survivors’, data are required for as long a time period as possible. This may also include any hospital admissions prior to the patient’s cancer diagnosis to identify any underlying health conditions. The YSRCCYP research team is also notified about any subsequent malignant neoplasms from the National Cancer Registration and Analysis Service prospectively following the original cancer diagnosis and therefore need to retain all historical HES and mental health data in order to scrutinise any such individual’s history of hospital admissions and understand potential reasons for those who experience multiple tumour diagnoses.


Enumerating the impact of COVID-19 on cancer pathways: a robust evaluation of the NHS Digital Trusted Research Environment — DARS-NIC-402417-N9Z5W

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

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

Purposes: No (Academic)

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

When:DSA runs 2021-04-19 — 2023-04-18 2021.05 — 2021.05.

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

Data-controller type: LEEDS TEACHING HOSPITALS NHS TRUST, UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. GPES Data for Pandemic Planning and Research (COVID-19)
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Outpatients
  5. Medicines dispensed in Primary Care (NHSBSA data)
  6. Civil Registration (Deaths) - Secondary Care Cut
  7. COVID-19 Hospitalization in England Surveillance System
  8. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  9. Cancer Waiting Times (CWT) Data Set
  10. Civil Registration - Deaths
  11. National Cancer Registration Data Set
  12. Radiotherapy Data Set
  13. Rapid Cancer Registrations Data Set
  14. Systemic Anti-Cancer Therapy Data Set

Objectives:

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, employees of the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Cancer Trusted Research Environment (TRE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:
• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);
• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);
• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);
• Clinical trial activity including recruitment to and active treatment within trials;
• Outcomes (including both hospital admission, survival, mortality and cause of death) and;
• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).
• Rates of COVID infection, hospitalisation and death in discrete health care regions

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer. A comparison of activity from 2019 and 2020 will be undertaken but this will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 would be required to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work would be organised into work packages (WPs) to be led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the Cancer TRE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN have had PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s used of NHS Digital’s Cancer TRE, some specific areas where patients will be represented by the PPIE group is in:
• The operational processes of running the TRE, including safeguards, controls audits and transparency.
• Reviewing any application to utilise the data in the TRE, including making sure that the application is clearly understandable and has clear potential for patient benefit.
• Reviewing or producing lay summaries of the activity of the TRE, including website content and external communications.
• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.
• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the TRE.
• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the TRE, the outcomes of any results, and the implications for the NHS and patients (current and future).
• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the TRE, with details of the benefits of the work which has been produced.
• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.
• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):
This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.



WP 2 - Analyses:
This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:
Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the TRE in the following ways:
- WP1 has led to the identification of and aspiration to access the datasets via the TRE under this Agreement for the purposes described under WP 2.
- WP2 has yielded a number of planned analyses to be undertaken within the TRE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.
- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the TRE.

The following are examples of analysis plans which will be undertaken using the data in the TRE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:
An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):
The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:
The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:
This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:
Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.


Governance Considerations:
The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:
• UCLPartners
• Queen’s University, Belfast
• Genomics England
• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the Cancer TRE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

Only the University of Leeds and Leeds Teaching Hospitals NHS Trust, who are the data controllers, and substantive employees of these organisations will have access to the record level data within the TRE. No other collaborators have involvement either in capacity as a data controller or processor.

While UCLPartners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The legal basis for the data controllers to process personal data is GDPR Article 6(1)(e) ‘task in the public interest’ and for processing special categories of personal data the legal basis is GDPR Article 9(2)(j) ‘archiving, research and statistics (with a basis in law)’.


Data Requirements:
These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the Cancer TRE within NHS Digital.
The data within the TRE will be pseudonymised. NHS Digital will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the TRE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)
2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types
3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

4. National Cancer Registration Dataset
5. Rapid Cancer Registration dataset
6. Systemic Anti-Cancer Therapy (SACT)
7. Radiotherapy Dataset (RTDS)
8. National Cancer Waiting Times (NCWT)

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

9. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

10. Secondary Uses Service (including SUS PBR for HRGs cost analysis)
11. Hospital Episode Statistics (HES) Admitted Patient Care
12. HES Outpatient
13. HES Accident & Emergency
14. Emergency Care Data Set (ECDS)
15. GPES Data for Pandemic Planning and Research (GDPPR)
16. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:
- only include those datasets required to address the cancer-related questions included within the Agreement;
- only for cancer-related research purposes, as outlined in the proposal;
- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)
- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS Digital and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

Expected Benefits:

Through addressing questions about the impacts of cancer on COVID-19 and the impacts (both direct and indirect) of COVID-19 on cancer, DATA-CAN expects the outputs of this work to inform public health policy and clinical care, benefiting:
• patients with a history of cancer who are at increased risk of poor outcomes with COVID-19 as a result of their cancer or cancer medications;
• patients now and in the future who become unwell with COVID-19 and are at risk of short, medium and long term cancer complications;
• the population as a whole whose cancer services are being affected by the government and health service response to the COVID-19 epidemic.

As outlined above, outputs which will deliver the capability to provide these benefits are expected to start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the three year period of the project through to January 2024.

Outputs:

The outputs of each piece of work will be reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

It is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the three-year period of the project through to January 2024. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months to start emerging.

Processing:

Individually authorised analysts employed by either the University of Leeds or LTHT will be granted remote secure access to the Cancer Trusted Research Environment (TRE) within NHS Digital’s data platform, the Data Processing Service (DPS).

Within the Cancer TRE, the analysts will be able to access pseudonymised linked data from the datasets outlined above.

No details which directly identify data subjects, such as names, NHS Numbers, etc., will be accessible within the TRE.

Analysts will be authorised to access only the data they are permitted to see and can utilise a variety of analytical tools available within the TRE platform.

Only summary, aggregate results data (data will be aggregated with small numbers suppressed in line with the HES analysis guide) will be exported from the TRE and this will be subject to review and approval by the NHS Digital team providing the TRE. The objective of this will be to ensure that no output contains information which could be used either on its own or in conjunction with other data to breach an individual's privacy.


Health related quality of life and clinical outcomes following acute myocardial infarction: linked EMMACE,HES and Civil Registration Mortality Data — DARS-NIC-332338-X1N2G

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

Legal basis: 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 2020-11-01 — 2023-10-31 2021.03 — 2021.03.

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. HES:Civil Registration (Deaths) bridge
  2. Hospital Episode Statistics Admitted Patient Care
  3. Civil Registration - Deaths
  4. Civil Registration (Deaths) - Secondary Care Cut

Objectives:

The objective for processing of this data is to undertake research about health-related quality of life (HRQoL) in patients with myocardial infarction (MI; heart attack). Specifically, University of Leeds wish to investigate the relationship between HRQoL and clinical outcomes in this population. The study is entitled the EMMACE Study: (Evaluation of the Methods and Management of Acute Coronary Events). It is a national longitudinal consented cohort of patient reported outcomes of MI.

More people than ever are surviving their initial presentation with MI. Yet, many will have recurrent cardiovascular events, and some will die prematurely. Whilst HRQoL is an important patient-facing outcome after MI, there is a paucity of information about its association with subsequent clinical events. The overarching aim of this study is to enhance the EMMACE study consented cohort data using national healthcare data (HES and Civil Registration Mortality data) to investigate the association of changes in HRQoL and subsequent clinical outcomes (fatal or non-fatal ) following MI including stroke, recurrent MI, heart failure, atrial fibrillation, deaths following MI.

The University of Leeds is a public authority responsible for conducting scientific research for academic and public benefit. Data in the EMMACE Study is processed to enable the University of Leeds to perform its public task. University of Leeds rely on the following legal bases for processing data under the General Data Protection Regulation:

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. Few centres have sufficient patient through-put to provide this information.

Article 9 (2)(J): Processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.
The University of Leeds EMMACE study aims to investigate health related quality of life in patients with myocardial infarction. University of Leeds wish to investigate the relationship between health related quality of life and clinical outcomes in this population.

COHORT:
The trial has finished recruitment to participants. EMMACE 3 and EMMACE 4 are separate studies and not follow on studies.
The number in the cohort for EMMACE 3 is 5556 participants, recruited between 1st November 2011 and 17th September 2013.
The number in the cohort for EMMACE 4 is 9343 participants, recruited between October 2013 and 24th June 2015
For both trials the total is 14,899 participants.

The specific objectives of the research project are:
1. To describe MI patients according to their changes in HRQoL(from occurrence of MI to discharge, 30 days follow up, 6 months, and 12 months) and determine factors associated with these changes.
2. To summarise the incidence of fatal and non-fatal health outcomes amongst patients and determine if there are common patient clusters with respect to these outcomes.
3. To investigate whether changes in HRQoL have differential impact on fatal and non-fatal clinical outcomes.
4. To investigate the association of quality of care, cardiac rehabilitation, medications, patient characteristics, socioeconomic status, changes in HRQoL with mortality

The 4 objectives which will use the cohort are as follows;

Objectives 1, 3 and 4 will use 9566 patients from both the EMMACE 3 & EMMACE 4 studies who have:
- ST-Elevation Myocardial Infarction (STEMI), which is a very serious type of heart attack during which one of the heart's major arteries that supplies oxygen and nutrient-rich blood to the heart muscle is blocked. ST relates to a section on the ECG test and may indicate whether a heart attack has taken place.
- Non-ST-elevation myocardial infarction (NSTEMI), which is less serious than an STEMI as the supply of blood to the heart may be only partially, rather than completely, blocked.

Please note that this is a subset from the total of 14,899 but only focusing on patients with STEMI and Non STEMI

Objective 2 will use all 14,899 patients from both studies EMMACE 3 & 4 including those without STEMI or NSTEMI

The EMMACE data cohort contains patient data on changes in HRQoL from MI to discharge, 30 days follow up, 6 months, 12 months measured using EQ-5D 3L questionnaire as well as information on cardiac rehabilitation, medications and patient characteristics - however - in order to meet the study objectives, the study team need to enhance the EMMACE dataset through linkage with HES and Civil Registration Mortality Data to determine the subsequent fatal and non-fatal outcomes following MI.

A detailed justification for the request of this level of data is outlined below:

The EMMACE study represents the largest contemporary national longitudinal study of patient reported outcomes and medications data for acute coronary syndrome. The study was designed to improve understanding of the effect of quality of care on health-related outcomes for patients hospitalised with acute coronary syndrome (ACS). The EMMACE studies, with consent for further linkage to electronic healthcare records, were given favourable ethical approval by Leeds (West) Research Ethics committee (REC reference: 10/H131374, 13/YH/0277 and 12/WM/0431).
The EMMACE dataset contains patient reported data at admission, 1 month, 6 months and 1 year concerning patient related quality of life measured by EuroQol 5-dimension (EQ-5D-3L) questionnaire.

All patients were consented to enter the study and for their self-reported data to be linked to future electronic health record data.

EMMACE has already been successfully linked to data from the national heart attack registry (Myocardial Ischemia National Audit project, MINAP) thus providing information about hospital treatment for MI and comorbidities.

Further information in the form of a GDPR compliant transparency information leaflet was sent to all participants.

Whilst the EMMACE study provided information on determinants and trajectories of HRQoL following MI, questions remain on the association of changes in HRQoL and subsequent clinical patient outcomes for patients with MI.

The EMMACE data are limited to the extent that they do not capture the full range of quality of care, comorbidities, patient characteristics, clinical diagnosis, socioeconomic status, treatments and patient outcomes. Thus, the study team are not able to investigate the relationship between HRQoL, socio-economic status, quality of care, clinical diagnosis, treatments and fatal and non-fatal clinical outcomes.

This project has been funded by the British Heart Foundation (BHF) (PG/19/54/34511) to enhance the EMMACE data by linking it with existing electronic data on hospital episodes from HES and Civil Registration Mortality Data - facilitated by NHS Digital.

To summarise the incidence of fatal and non-fatal health outcomes amongst patients and determine if there are common patient clusters with respect to these outcomes and factors associated with these clusters, the EMMACE data will be linked electronically to Hospital Episodes Statistics and Civil Registration Mortality Data.

The HES data requested will include information on cause-specific hospital admissions, all HES records for the patients (i.e. their historical records and prospective ones after they entered EMMACE), any hospital diagnoses, clinical information and treatments.

These repeated cause-specific admissions, episodes and spells will be used to determine the longitudinal AMI patient phenotypes, patient transitions over time, and factors associated with these transitions. Non-fatal outcomes will include all hospital diagnoses such as heart failure, stroke, atrial fibrillation and acute coronary syndrome, with the fatal outcome being all-cause mortality. University of Leeds will investigate the effects of patient characteristics, socioeconomic status, diagnosis, changes in HRQoL, comorbidities, treatments on patient class membership and transition probabilities hence this data request from HES records.

To investigate the association of quality of care, cardiac rehabilitation, medications, treatments, patient characteristics, socioeconomic status, changes in HRQoL with mortality. EMMACE data will be linked electronically to Civil Registration Mortality data for information on cause specific mortality and date of death. Mortality data will be required at individual patient level about the occurrence, timing and causes of any death. The exact date of death will be required to calculate the survival time between date of entry into the EMMACE study and date of death. A survival time for those who have not die but are censored will be required.

To ensure comprehensive information on all confounders, University of Leeds are requesting individual patient level HES data on in-patient hospitalisations, patient demographic characteristics (age of patient, sex of patient, ethnicity), socio-economic factors (IMD indices, smoking status, employment status) information about diagnoses and operations, dates of admission and discharge, where patients were treated, comorbidities, revascularization procedures and treatments.

The research will be undertaken by the established Cardiovascular Epidemiology Research Group within the Leeds Institute of Cardiovascular and Metabolic Medicine, and physically located in the Leeds Institute for Data analytics at the University of Leeds.

The research group has a remit of using large scale routine data (HES) and clinical registries (MINAP registry) alongside advanced analytical epidemiological techniques to better understand and improve the quality of care of patients with cardiovascular disease.

Expected Benefits:

Whilst planned analyses have the potential to achieve high impact peer reviewed publications, it is the clinical implications of the results for healthcare professionals, patients and regulators that are of greater virtue.

The results from the proposed study will help answer major gaps in the knowledge base on the associations between changes in HRQoL and subsequent health outcomes. Identifying precisely in whom worse (or better) outcomes may occur will permit the design and testing of novel interventions targeted specifically at common, and potentially previously unknown, consequences of a heart attack for patients with specific health related quality of life trajectories.

The aim of the EMMACE study is to improve the quality of life and clinical outcomes of patients with MI. The planned research will provide a unique and comprehensive insight into the relationship between changes in HRQoL and clinical outcomes among patients with MI. HRQoL is a patient reported outcome measure (PROM) which can detect change in risk of events for patients, and potentially serve as a predictor of future risk (using patient-facing data capture tools). Understanding the association between changes in HRQoL and health outcomes, and precisely in whom worse (or better) outcomes may occur will permit the design and testing of novel intervention to reduce premature death from MI.

Results from this research will help design interventions to improve quality of life and cardiovascular outcomes in survivors of heart attacks. The results will be used to inform the UK Clinical Commissioning Groups (CCGs) who work in partnerships with hospitals and are responsible for the commissioning of specialist services including acute cardiac care.

In this study, through linkage to HES and Civil Registration Mortality data, University of Leeds will be able to classify patients into particular phenotypes (or disease risk patterns) using fatal (deaths) and non-fatal outcomes (stroke, heart failure, atrial fibrillation, re-infarction and any other hospitalisations). This will allow University of Leeds to determine the types of patients who may benefit from more intensive care, to improve their quality of life and survival.

Outputs:

The planned analysis of the EMMACE study will be disseminated nationally and internationally in peer – reviewed open access research journals (such as European Heart Journal, Heart, BMJ); national and international research conferences, departmental seminars, through the media and stakeholder meetings with patients. The EMMACE researchers have established relations with the International Quality of Life Society (ISOQOL) through which study findings will be disseminated. Furthermore the Cardiovascular Epidemiology research team has established connections with numerous relevant groups through which findings will be disseminated to the NHS as well as patients, including the European Society of Cardiology, the British Cardiovascular Society and NICE. The EMMACE study dissemination strategy will be as follows:

Peer-reviewed publications
Target publications for 2020 are:
Paper 1: Multi-morbidity and health related quality of life after myocardial infarction: A nationwide longitudinal patient-reported outcomes study.
In this paper University of Leeds will look at the association of multi-morbidity and HRQoL following MI.

Paper 2: Cardiac rehabilitation, exercise dose, health related quality of life and mortality after myocardial infarction: A nationwide longitudinal patient-reported outcomes study.
This paper will look at association of cardiac rehabilitation, exercise dose, HRQoL and mortality following MI.

Target publications for 2021 are:
Paper 3: Joint modelling of longitudinal health-related quality of life data and survival.
This paper will look at the association between time to event (mortality) and longitudinal HRQoL through joint modelling. University of Leeds will generate individualized patient-level predictions of survival probability based on the individual’s available HRQoL information.

Paper 4: Determinants of health-related quality of life in survivors of heart attacks: A structural equation modelling approach.
This paper will use the HRQoL conceptual model developed by Wilson and Clearly to look at associations of individual characteristics, environmental characteristics, biological and physiological variables, symptoms status, physical function, general health perceptions and HRQoL.

Target publications for 2022 are:
Paper 5: Identification of myocardial infarction subgroups through phenotyping of fatal and non-fatal outcomes.
This paper will determine MI patient phenotypes based on fatal and non-fatal outcomes using latent transition analysis. Changes in class membership overtime and factors associated with class membership changes will be identified. University of Leeds will investigate the effects of patient demographic, socioeconomic characteristics, treatments, changes in HRQoL and co-morbidities on class membership and transition probabilities.

Conferences
University of Leeds will endeavour to present findings from the study at the following conferences:
-International Society of Quality of life (ISOQOL) conferences in 2021 and 2022:
-British Society of Cardiology conference (June 21/22)
-European Society of Cardiology Congress (August 21/22).

Patient and Public Involvement
The research outputs as described will be published in peer-reviewed journals and presented at conferences and will be reported through press release through national media. A lay person friendly summary of the study results will be disseminated to the West Yorkshire Patient and Public involvement group.

University of Leeds have an active, well-rehearsed and effective relationship with the BHF and University of Leeds press offices, whereby the research findings may be disseminated to the wider regional, national, and international audience. The BHF will publish the results of the study in their free e-newsletter.

University of Leeds will provide an update on the study findings on the Leeds Institute of Cardiovascular and Metabolic Medicine study website which is available to the public.

Additionally:
• A lay person summary will be disseminated to the West Yorkshire Patient and Public involvement group. This group is run by the Leeds Clinical Research Facility Operations Manager at Leeds General Infirmary. There are 40+ members of the group. University of Leeds will contact the Manager when the results are ready and ask to distribute the lay person summary to the group by email. University of Leeds have previously discussed with the Manager about presentations to the group however due to COVID 19 the group no longer has regular meetings. This option would be discussed with the Manager when the results are available.
• The University of Leeds will make a press release for any significant findings from the study. This press release is available to all, articles are on the University of Leeds website thus can be looked at by anybody, including the press, this may result in the increase of knowledge.
• Any findings from the study will be discussed with the BHF, who will disseminate as they see appropriate. This will be in form of a patient newsletter. The BHF assigns a Case Officer to the grant, University of Leeds will direct all discussions about dissemination through the Case Officer.
• A lay person summary will be made available on the University of Leeds website.
• Twitter will be used to signpost the public and experts to the layperson summary and all study publications (@UoLCardioEpi).

Processing:

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

Presently the EMMACE data are stored in two physically different secure locations.

All EMMACE 3 data, including identifiable data such as NHS number, sex and date of birth are stored at the University of Leeds. EMMACE 3 data at the University of Leeds is managed by Leeds Institute of Data Analytics (LIDA) who have control of the data, are responsible for supplying cohort information to NHS Digital and linking NHS Digital data to all non-identifiable data using study ID only. LIDA will supply pseudonymised data to the statisticians in the Cardiology Epidemiology group at the University of Leeds who will analyse the data. Statisticians in the Cardiology Epidemiology group do not have access to personal data but to study ID only.

EMMACE 4 data, including identifiable data such as NHS number, sex and date of birth are stored at the Leeds Teaching Hospitals NHS Trust (LTHT). This is for administrative purposes and for use in facilitating ongoing data linkages.

Access to this environment is controlled by two factor authentication and is granted a need only basis. All data received into this solution is via secure transfer and in accordance with all data sharing agreements. Data will be encrypted in transit and at rest. The data is transferred directly to the processing platform where any agreed processing will take place. Any data in this platform is deleted in accordance with any processing agreement.

All sites and data centres are protected by CCTV. Access control is limited via key fobs to office areas and safe rooms. All networks are segmented and where required for security prevent access, data flow, external access etc. All networks internally and externally are tested on a monthly basis for vulnerabilities.

DATA FLOW INTO NHS DIGITAL:
Leeds Institute of Data Analytics at University of Leeds will send the following identifiers to NHS Digital for the EMMACE 3 Cohort:
• NHS Number
• Sex
• Date of Birth
• Study ID

LTHT will send the following identifiers to NHS Digital for the EMMACE 4 Cohort:
• NHS Number
• Sex
• Date of Birth
• Study ID

All identifiers for participants who have withdrawn from further follow up from the EMMACE 3 and 4 studies will be removed from the data files prior to sending to NHS Digital.

The EMMACE data will be linked to HES and Civil Registration Mortality data for the period November 2011 to 2020 (or latest possible date) by NHS Digital acting as the trusted third party. NHS Digital will return data to the University of Leeds that includes (for patients with prior and/or subsequent hospitalisations) corresponding HES records and corresponding cause of death and date of death for patients who have died. University of Leeds require only Study ID from NHS Digital as the identifier - NHS Number is not required to be returned..

University of Leeds have requested data from 2010/11 to present as the research study EMMACE recruited patients with Myocardial Infarction (MI) from 1st November 2011. In this current research one of the objectives is to summarise the incidence of fatal and non-fatal health outcomes amongst the patients and determine if there are common patient clusters with respect to these outcomes. To undertake this research work University of Leeds will require the episode and spells for periods of care of patients in the research study (EMMACE) who consented for their data to link to electronic health records, clinical information and diagnosis will be required to determine the fatal and non fatal outcomes and duration of outcomes. Geographical information from HES data is required to determine geographical variations in outcomes after Myocardial infarction.

One of the objectives is to investigate the association of cardiac rehabilitation, medications, treatments, patient characteristics, socio-economic status, and changes in HRQoL with mortality. In order to undertake this work, patient data, socioeconomic data, treatments from HES is required. IMD domain and overall ranks scores will be required to look at the relationship of specific domains with HRQoL.

The linked (EMMACE/HES/Civil Registration Mortality) data - the analytical cohort - will be stored separately from the EMMACE cohort that contains patient identifiers.
That is, the analytical cohort (excluding NHS numbers) will be stored in a restricted directory within the University of Leeds password protected secure storage area network (SAN).

The University of Leeds Information Security Policy has been fully implemented and has been drawn up in line with ISO 27001 The University of Leeds are DSPT accredited. The data for this study is considered personal and its storage and sharing will abide by the University of Leeds data protection and sharing policies. The data will only be accessible to authorised individuals in the study team and will only be used for the purpose of this project. Data will not be used for commercial purposes or provided in record level form to any third party or used for any direct marketing.

There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.

Data will only be accessed and processed by substantive employees of University of Leeds and will not be accessed or processed by any other third parties not mentioned in this agreement.


Liaison Psychiatry: Measurement and Evaluation of Service Types, Referral Patterns and Outcomes (Workstream 2 - Phase 1) — DARS-NIC-77953-C4M3T

Opt outs honoured: Yes - patient objections upheld, Anonymised - ICO Code Compliant, Yes (Does not include the flow of confidential data)

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

Purposes: No (Academic)

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

When:DSA runs 2019-04-26 — 2021-06-30 2018.10 — 2019.11.

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Outpatients

Objectives:

The overall aim of LP-MAESTRO is to evaluate the cost-effectiveness and efficiency of particular
configurations of liaison psychiatry services for specified target populations. To do this, an innovative approach based upon linking routinely collected patient-level data and using economic modelling with the resulting aggregated data will be developed and evaluated.

Workstream 2 – Phase 1 (WS2P1) focuses on 11 acute hospitals in England that were identified within

Workstream 1 of LP-MAESTRO and the Liaison Psychiatry Survey England 2015 as not having a Liaison

Psychiatry service. Of those 11 hospitals, 8 gave approval (see approval letters associated with this application) for their data to be included within this study as follows:
-- St Mary’s Hospital (Isle of Wight NHS Trust)
-- James Paget University Hospital (James Paget University Hospitals NHS Foundation Trust)
-- Diana, Princess of Wales Hospital (North Lincolnshire and Goole NHS Foundation Trust)
-- Scunthorpe General Hospital (North Lincolnshire and Goole NHS Foundation Trust)
-- Rotherham Hospital (Rotherham NHS Foundation Trust)
-- Pilgrim Hospital (United Lincolnshire Hospitals NHS Trust)
-- Lincoln County Hospital (United Lincolnshire Hospitals NHS Trust)
-- County Hospital (University Hospitals of North Midlands NHS Trust) - previously Stafford Hospital (Mid Staffordshire NHS Foundation Trust)
The NHS trusts for the following hospitals did not provide approval within the required timescale and are therefore not included within this application:
-- Basingstoke and North Hampshire Hospital (Hampshire Hospitals NHS Foundation Trust)
-- Royal Hampshire County Hospital (Hampshire Hospitals NHS Foundation Trust)
-- Luton and Dunstable Hospital (Luton and Dunstable University Hospitals NHS Foundation Trust)

For patients with an A&E attendance or Inpatient episode (Index Episode) at one of the 8 included hospitals within the defined index period (1st April 2013 – 31st March 2014), A&E attendances, Inpatient admissions and Outpatient appointments will be obtained from Hospital Episode Statistics (HES) for the period from 1st April 2012 - 31st March 2015 (i.e. 1 year prior to the index period, the index period itself and 1 year following
the index period).

For patients included within the HES data, the study will determine whether primary care data exists for the patients within TPP’s ResearchOne database. If so, a defined set of primary care data will be obtained for these patients for the period prior to 1st April 2014. Additionally, a mapping file will be produced by NHS Digital and supplied to the University of Leeds to enable the HES data for a specific patient to be linked to the
corresponding primary care data (if present).

From the linked data, pathways for patients attending the 8 hospitals without a Liaison Psychiatry service will be constructed.

Workstream 2 – Phase 2 (WSP21) focuses on hospitals in England that were identified within Workstream 1 of LP-MAESTRO and the Liaison Psychiatry Survey England 2015 as having a particular configuration of Liaison Psychiatry service. To enable pathways to be constructed for patients attending these hospitals that consider the interaction of patients with the Liaison Psychiatry services in these hospitals, data is additionally
required from the NHS trusts that run these services. A variation to the linkage methodology proposed for WS2P1 would be required to support the use of these additional data sources. Accordingly, WS2P2 is not covered by this application and will be subject to separate approval and application.

For the avoidance of doubt, this application relates ONLY to WS2P1.

Patient pathways constructed within WS2P1 and WS2P2 will be tracked and the cost of each to the health care sector calculated using national data sources. A whole system perspective will be adopted in order to determine if there is an association between the presence and configuration of liaison services and health care utilisation by patients. Metrics will include emergency admissions, occupied bed days and length of stay.
Each metric will be analysed by age band.

Aggregate figures on A&E and Inpatient admissions (for the named hospitals) on which to estimate sample size are not publicly available. This data is required in order to estimate the numbers that can be expected in the study. General figures on the number of A&E attendances and inpatient admissions in a given year are published by HSCIC at the level of the trusts that operate these hospitals (see http://www.hscic.gov.uk/catalogue/PUB16728/acci-emer-atte-eng-2013-14-pla.xlsx and
http://www.hscic.gov.uk/catalogue/PUB16719/hosp-epis-stat-admi-prov-leve-2013-14-tab.xlsx). These figures provide an indicative upper bound on the number of A&E attendances and inpatient admissions that can be expected at any of the hospitals operated by that trust in a given year.

For 2013-2014, these figures were the following:

- Isle of Wight NHS Trust: A&E Attendances - 59,494, Inpatient Admissions - 28,263

- James Paget University Hospitals NHS Foundation Trust: A&E Attendances - 67,726, Inpatient Admissions

- 58,144

- North Lincolnshire and Goole NHS Foundation Trust: A&E Attendances - 137,841, Inpatient Admissions -
107,403

- Rotherham NHS Foundation Trust: A&E Attendances - 74,458, Inpatient Admissions - 74,313

- United Lincolnshire Hospitals NHS Trust: A&E Attendances - 144,788, Inpatient Admissions - 146,845

- University Hospitals of North Midlands NHS Trust: A&E Attendances - 119,709, Inpatient Admissions -
157,605

Yielded Benefits:

Local benefits might be seen as soon as a year after publication. National benefits are more likely to be seen over a 2-5 year timescale. Requested HES data was made available by NHS Digital on 16th November 2018. However, the study are currently awaiting additional required data from both NHS Digital and The Phoenix Partnership before analysis can commence.

Expected Benefits:

The results of this application will be used to determine the cost-effectiveness and efficiency of different liaison psychiatry configurations. Based on these results, the study will prepare two types of report to inform the commissioning and provision of general hospital mental health services (expected date: 2019). One report will be aimed at local commissioners, to aid them in making decisions about local service funding. The other will be aimed at national bodies and especially NHS England, where there is an active interest in such services.

The benefits will be measured through changes in the profile of mental health services, in line with report recommendations, as determined by the yearly national survey of such services currently funded by NHS England and Health Education England. These results should influence provision of mental health services in every acute hospital in the NHS. Since a typical mental health service of that sort sees five thousand or so cases a year, the benefits should accrue to many hundreds of thousands of patients.

Local benefits might be seen as soon as a year after publication. National benefits are more likely to be seen over a 2-5 year timescale.

Outputs:

- The study will publish an academic paper (describing the findings in relation to patient outcomes and cost effectiveness)in a reviewed health services research and probably also in a mental health journal.

The audiences will be [a] academics with an interest in liaison psychiatry services [b] academics with an interest in use of routine data to answer health services questions.
These papers will be submitted by the end of the project. Due to delays in data access a project extension request was submitted to NIHR. Intention to approve a project extension has now been received from NIHR. Once formally approved by the Department of Health, the end date of the project will be 30th June 2019. The study will submit to open-access journals to maximise coverage.

- The funders (NIHR) require a final report of main project in the form of a monograph, at the end of the project. The monograph will be published in the NIHR library, which is widely accessed by academics with an interest in applied health research.

- The study will write two discussion papers for health service commissioners by the end of the project – describing the findings in relation to evidence on the effectiveness of liaison psychiatry services, and our findings on the use of routine data to evaluate services.

- A final methodological paper will describe the project as proof of concept for future research projects using linked data from primary and secondary care settings by the end of the project.

Processing:


A summary of the data flows, which are performed using either: i) NHS Digital's Secure File Transfer (SEFT) or ii) University of Leeds LICTR's Secure File Transfer (SFT), is provided below:
1. University of Leeds provides TPP (SystmOne) with the cryptographic salt (via SFT)
2. University of Leeds provides NHS Digital with the cryptographic salt (via SFT)
3. NHS Digital provides the University of Leeds with HES A&E, Inpatient and Outpatient data according to specified criteria with patients referenced by HESID (via SEFT)
4. NHS Digital provides TPP (ResearchOne) with a set of patient pseudonyms (via SEFT).
5. TPP (ResearchOne) provides University of Leeds with primary care data for patients identified from the set of patient pseudonyms supplied by NHS Digital with patients referenced by ROID (via SEFT).
6. TPP (ResearchOne) provides NHS Digital with a mapping from each patient pseudonym to a unique ROID (via SEFT)
7. NHS Digital provides University of Leeds with a mapping file that maps a unique HESID to a unique ROID identifier (via SEFT)

The data which will be accessed by the University of Leeds will be pseudonymised they will have no access to identifiers. They are not permitted to use to data provided to try and re-identify any individual.

ResearchOne has been separated out in the data flow diagram and the summary above to TPP (ResearchOne) and TPP (SystmOne). Project documentation refers only to ResearchOne to emphasise that the project will use only data from the ResearchOne database. The Phoenix Partnership (TPP) are responsible for SystmOne, ResearchOne, and for ensuring the necessary separation of duties for staff working on SystmOne and ResearchOne. We leave it to NHSD to liaise with TPP regarding the data flows between the two parties, and how these data flows can be performed via SEFT in a manner
that is consistent with the necessary separation of duties. The ResearchOne database is stored and processed inside the data centres which host the SystmOne production environment. It is not possible to disclose the location of these data centres due to governance requirements but they are Tier 3 data centres that have been accredited by the NHS for storing and processing clinical data. There is a disaster recovery
site (hosted to exactly the same standards as the live site) which is used as a back-up location in the event of any failures at the main site. Documentation relating to ResearchOne can be found at:

http://www.researchone.org/documentation/.

University of Leeds generates and supplies a salt key that is used in the generation of pseudonyms by NHSD and TPP (SystmOne). Further details regarding the pseudonym generation process are provided in the "LPMAESTRO - WS2P1 - Pseudonym Generation Process.pdf" evidence document associated with this application. To ensure that the identifier used to generate the pseudonyms (NHS number) cannot be recovered by the University of Leeds, the University of Leeds does not receive any pseudonyms generated
using the supplied salt key. The University of Leeds receives the following: i) HES data referenced by a HES ID, ii) ResearchOne data referenced by a RO ID, and iii) a mapping file from HES ID to RO ID. The linkage methodology has been developed so that the
University of Leeds is responsible for the generation and supply of the salt key, and subsequent data flows to the University of Leeds do not contain any data that could be re-identified by the knowledge of the salt key. Additionally, the salt key is used only a one-time basis, such that any pseudonyms generated cannot be matched across data sets obtained for different usages. Approvals for the project (including NHS Ethics)
have been obtained on the basis of the proposed linkage methodology.

NHS Digital will identify patients based on the presence of an A&E attendance or Inpatient episode (Index Episode) at one of the 8 included hospitals within the defined index period (1st April 2013 – 31st March 2014), A&E attendances, Inpatient admissions and Outpatient appointments will be obtained from Hospital Episode Statistics (HES) for the period from 1st April 2012 - 31st March 2015 (i.e. 1 year prior to the index period, the index period itself and 1 year following the index period). This data will be provided directly to the University of Leeds with patients uniquely referenced by a unique HESID. Additionally, NHS Digital will generate a pseudonym for each included patient, according to the methodology described above, and supply this list of pseudonyms to TPP (ResearchOne).

TPP will generate pseudonyms for all patients in the ResearchOne database by applying the same methodology as NHS Digital and using the salt key supplied to TPP (SystmOne). TPP (ResearchOne) will then determine those patients whose pseudonyms are present in the list provided by NHS Digital. Selected primary care data will be extracted from ResearchOne for these patients for the period prior to and including
31st March 2015.

Primary care data will only be obtained where:
- the GP practice to which the patient is registered using TPP's SystmOne clinical information system and
- has opted-in to ResearchOne (and the patient has not individually opted-out).

TPP (ResearchOne) will provide primary care data directly to University of Leeds. Each patient will be uniquely referenceable in this data using a unique ROID. No pseudonyms will be included in the data provided by ResearchOne to the University of Leeds. TPP (ResearchOne) will also provide NHS Digital with a file that maps each pseudonym present in the list provided by NHS Digital and in the ResearchOne database to its corresponding ROID. NHS Digital will use the mapping file provided by TPP (ResearchOne) to map the HESID of each patient in the HES data to the ROID identifier of each patient in the ResearchOne data. NHS Digital will supply the resulting mapping file to the University of Leeds who will use it to match the data for a particular patient in HES data to the data for that patient in the RO data (and vice-versa).
Based on the HES data and ResearchOne data, patients with admissions to these hospitals (without an LP service) will be matched to referred and non-referred cases from hospitals with an LP service, either by matching for co-variates or by propensity scoring will be determined and implemented. As described in Section 5a (Objective for Processing), WS2P2 of the LP-MAESTRO project will focus on the linkage and
supply of data for patients attending hospitals with an LP service. Application and approvals for WS2P2 will be undertaken separately. Relevant variables for matching will include demographic (e.g. age, carer support, Index of Multiple Deprivation (IMD) calculated from postcode) clinical (e.g. diagnosis, long-term medication)
and health service utilisation (e.g. inpatient days, GP visits, major procedures, A&E/ED visits, and Medical and Surgical outpatient appointments). One of the novelties of this approach is the use of these characteristics identified from HES and from the primary care database to tackle the utilisation in the financial year before referral, as a way of ensuring that outcomes in the financial year after referral are not attributable
to easily identifiable pre-existing characteristics (case complexity) that are confounded with likelihood of referral.

Analysis will use the linked dataset and will estimate a standard regression model for estimating the relation between health care utilisation and key variables capturing the configuration of liaison services. The dependent variable in this model is therefore cost of health care utilisation derived from factors such as inpatient days, readmission rates, Emergency Department attendances and General Practitioner visits. The variables that will be used as determining factors relate to the configuration of liaison services, sourced from the data collected in WS1. The quantum of the liaison service provision will be captured by WS1 data related to structure and process e.g. staffing levels and contact time after referral. The standard regression approach rather than frontier-based approaches will be used as the focus is on how the explanatory variables impact
on the dependent variable, secondary care utilisation, rather than on the efficiency of certain providers.

All persons accessing the record level data provided by NHS Digital under this agreement are substantive employees of University of Leeds.

University of Leeds will not link the data further and the only data linkages are those permitted under this application / Data Sharing Agreement.


UK Women's Cohort Study-HES new database — DARS-NIC-109867-M8S6B

Opt outs honoured: Yes - patient objections upheld, Identifiable, Yes (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7)

Purposes: No (Academic)

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

When:DSA runs 2019-05-23 — 2022-05-22 2019.10 — 2019.10.

Access method: One-Off, Ongoing

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Hospital Episode Statistics Outpatients
  3. Hospital Episode Statistics Admitted Patient Care
  4. Civil Registration (Deaths) - Secondary Care Cut
  5. MRIS - Cause of Death Report
  6. MRIS - Cohort Event Notification Report
  7. MRIS - Flagging Current Status Report
  8. MRIS - Members and Postings Report

Objectives:

The UK Women’s Cohort Study (UKWCS) was established to explore links between diet, lifestyle and chronic disease, in particular cancer. Previous cohort studies exploring diet and cancer have often produced results with small, not statistically significant effect sizes, due in part to the fact that diet is a complex exposure with measurement being subject to a variety of errors and bias. This measurement error has limited the ability to make dietary recommendations linked to chronic disease prevention, and many important questions remain unanswered. In addition, within population subgroups, diet often appears homogeneous, preventing any subtle effects of dietary differences from being detected. The UKWCS aimed to address these issues in a number of ways. Dietary information was obtained using two methods: a food frequency questionnaire (FFQ) and also a 4-day food diary to provide alternative measures of diet to allow for sensitivity analyses and potential minimisation of measurement error.

The UKWCS is a long standing cohort of 35000 women across the UK which is stored in the University of Leeds Integrated Research Campus (IRC). The cohort was established in 1995 and cancer incidence and death information was received on a quarterly basis for the participants. A list of publications resulting form the analysis is available on https://leedsbasic.wpengine.com/ukwcs/publications/

The University of Leeds are processing this data held under this agreement under their role as a University in the performance of a task in the public interest Article 6(2)(e) and Article 9(2)(j) with regards to the processing being necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law.

Most chronic diseases risk can be significantly reduced through changes in lifestyle factors, most markedly improvements in diet. Over recent years, many aspects of diet have been explored in relation to risk of chronic diseases. The Nutritional Epidemiology Group at the University of Leeds already have experience undertaking survival analysis (a statistical method for modelling disease risk) in the large cohort of British women and have previously published findings which show a reduced risk of breast cancer in pre menopausal women consuming a diet high in fibre and an increased risk of breast cancer in postmenopausal women consuming a diet high in meat and processed meat in particular. However, other chronic diseases such as CVD or specific receptor status of a cancer have not been recorded by Office of National Statistics (ONS).

The objective of this application is to create a new database by linking the existing UK Women's Cohort Study (UKWCS) with Hospital Episode Statistics (HES) data and to support analysis of a number of key research questions. The database will be made available to researchers working for the University of Leeds so that new links can be explored between diet/lifestyle and health outcomes. The additional HES data will create a unique research data set for the UK.

UKWCS will use historical HES outpatient and admitted patient care data in its studies to identify diagnosis after 1997 baseline information of dietary and lifestyle were gathered. Its important to determine any co-morbid conditions and identify the date when a patient first had a care visit for a particular diagnosis (index date).

In all cases, the purposes for which the research database can be accessed are restricted to those for the provision of health care or adult social care, or the promotion of health and must be in line with the purposes set out in this agreement relating to diet and lifestyle. The new data base will be used to undertake research into epidemiology of diseases to improve patient care and health economic and geographical studies. These studies support the long term sustainability of the NHS by evaluating cost effectiveness of healthy diet and lifestyle.

Researchers from University of Leeds conducting studies using the new data base need to establish the index date of a patient at the beginning of treatment or diagnosis in order to determine primary diagnosis over a follow up period. Researchers also need to understand if patients have a history of serious co-morbid conditions e.g. if a patient was hospitalised 10 years ago for a stroke then this needs to be taken into account. By answering these questions researchers are able to build cohorts for studies with the right type of characteristics. If historical HES data was not provided then researchers could miss important events which would then not be adjusted for in study results.

Accessing the data involves an application process for bona fide researchers with an established scientific record. This approach ensures the reputations of the UKWCS team and its participants are not compromised through unethical, premature or opportunistic data analysis.
The UKWCS follow the MRC definition of bona fide research:
http://www.mrc.ac.uk/publications/browse/mrc-policy- and-guidance-on-sharing-of-research-data-from-population and-patient-studies/(page 24) - see below section 5b, for details of that process. This data will be pseudonymously linked by NHS Digital.

Researchers will only be given access to the minimum amount of data from the database required for them to carry out their analysis.

The Consumer Data Research Centre (CDRC) and Integrated Research Campus (IRC).

The Consumer Data Research Centre (CDRC/Centre) was established in 2014 by the UK Economic and Social Research Council as part of the phase two Big Data Network. Led by the University of Leeds and University College London, with collaborators at the Universities of Liverpool and Oxford, the CDRC’s key objectives have been to provide stakeholder access to consumer data via a national data service and to deliver an innovative programme of research and training in consumer data analytics. Over the past five years the Centre has achieved considerable success in both acquiring and sharing novel data sets. The University of Leeds has entered into data sharing agreements with data owners on behalf of the Centre, as the CDRC is a non-legal entity. The data disseminated under this agreement will remain under the data controllership of the University of Leeds. Collaborators in the CDRC: University College London the Universities of Liverpool and Oxford do not have any remit of role around the use and access of the NHS Digital disseminated data.

At Leeds, the CDRC forms part of the Leeds Institute for Data Analytics (LIDA); a purpose built facility that brings together applied research groups and data scientists from across a wide range of disciplines. LIDA is underpinned by the Integrated Research Campus (IRC), an advanced computational infrastructure that is highly secure and scaleable to meet the needs of data-intensive research. The IRC platform provides a secure Virtual Research Environment (VRE) for each research project. Access to the CDRC’s most sensitive data is facilitated via the IRC and supported by LIDA’s data services team. All staff working at the LIDA are substantive employees of the University of Leeds.

Following a process of external independent assessment, the IRC has attained accredited certification to the international standard for information security management, ISO/IEC 27001:2013. Alongside its work to align to the ISO standard, the IRC has worked towards compliance with information governance requirements set by NHS Digital and the Department of Health. The IRC’s information security management system has been reviewed up to the minimum ‘level 2’ and is deemed satisfactory. This means that the IRC meets the requirements to store health data shared by NHS Digital, Public Health England and other NHS or social care organisations.

The Senior Management Team (SMT) within Leeds University will assess whether the data access requested by the researchers fits the Centre’s (CDRC) remit. The UKWCS team is notified that an application for the linked UKWCS data has been received. Every application will be examined by the CDRC Research Approval Group (RAG). A policy agreement document is in place to explain the application process for researchers interested in analysing existing data and the terms and conditions that must be agreed before data can be used.

A member of the CDRC Research Approval Group (RAG) will then be selected as the Contact Researcher for each project. If possible, s/he will be the preferred Contact Researcher named on the application form. The Contact Researcher will inform the applicant of the decision in writing. Approval from the committee is “in principle”, subject to the applicant signing and returning the UKWCS Data User’s Agreement Form. The Contact Researcher will be the point of contact for the duration of the project. New project analysis will require a new application being submitted and approval by the CDRC Research Approval Group (RAG). New pseudonymised datasets will be created for each agreed project where the data will be minimised to fit each specific project and the data will be made available within the CDRC where the researcher can have access. The researcher data can be accessed until their specific project end date.

Specific purposes of use for the new database:
Listed below are the relevant exposures and outcomes for which the UKWCS database can be used to explore links between Diet, lifestyle, and chronic disease in line with the CAG approvals to do this below are the areas which will be investigated,


1 Food, nutrient intakes and dietary patterns – identified from both the food frequency questionnaire and food diary data. Chronic diseases prevalent in older people, such as risk of malignant neoplasms, heart disease, other chronic diseases such as diabetes, Alzheimer’s Disease, hip fracture, kidney failure.

2 Measures of physical activity and sedentary behaviour Chronic diseases prevalent in older people, such as risk of malignant neoplasms, heart disease, other chronic diseases such as diabetes, Alzheimer’s Disease, hip fracture, kidney failure.

3 Body mass index and other anthropometric measures available (height, weight, weight change, waist-hip measures, clothes size). Chronic diseases prevalent in older people, such as risk of malignant neoplasms, heart disease, other chronic diseases such as diabetes, Alzheimer’s Disease, hip fracture, kidney failure.

4 Other lifestyle behaviours available in the cohort such as smoking, alcohol intake, taking dietary supplements, breast feeding. Chronic diseases prevalent in older people, such as risk of malignant neoplasms, heart disease, other chronic diseases such as diabetes, Alzheimer’s Disease, hip fracture, kidney failure.

5 Social aspects of participants: education level, social class, marital status, employment status, children in household. Chronic diseases prevalent in older people, such as risk of malignant neoplasms, heart disease, other chronic diseases such as diabetes, Alzheimer’s Disease, hip fracture, kidney failure.

6 Health experience of participants and family members – self-reported eg. previous high blood pressure, high blood cholesterol and treatments for long-term conditions (self-reported) including anti-inflammatory use. Chronic diseases prevalent in older people, such as risk of malignant neoplasms, heart disease, other chronic diseases such as diabetes, Alzheimer’s Disease, hip fracture, kidney failure.

7 Obstetric history of participant, child birthweight, and other lifecourse markers. Chronic diseases prevalent in older people, such as risk of malignant neoplasms, heart disease, other chronic diseases such as diabetes, Alzheimer’s Disease, hip fracture, kidney failure.

Specific examples of each area of research include (these are not intended to be exclusive but to illustrate planned and potential work relating lifestyle data held in the UKWCS to disease outcomes provided by HES):

1. Food intake and dietary patterns on incidence of Alzheimer’s Disease or dementia.
UKWCS will use HES data to examine which dietary factors influence incidence of Alzheimer’s Disease (AD) or dementia. HES records will be used to identify cases of AD or dementia. Specific dietary factors will be the focus: high fat/meat intakes or Mediterranean/vegetarian dietary pattern.

2. Physical activity and risk of all causes of cancer.
Physical activity and sedentary behaviour will be explored in relation to risk of cancer incidence. HES data will be used to provide information on cancer incidence. The study will explore how frequency, amount and intensity of physical activity is associated with future risk of cancer. Sedentary behaviour will also be taken into account.

3. Body mass index, clothes size and risk of colorectal cancer.
The relationship between body mass index (BMI), lifetime change in BMI, and clothes size in relation to risk of colorectal cancer will be explored. HES data will provide the colorectal cancer incidence information. This analysis will help Leeds University to understand the role of weight over the lifecourse in relation to risk of colon and rectal cancer.

4. Breast feeding in relation to risk of breast cancer and other female reproductive cancers.
Breast feeding duration and frequency will be explored as a protective factor for breast cancer incidence. Analysis will make use of PHE hormone receptor status data and HES data for breast cancer risk.

5. Influence of diet on social class and risk of CVD.
Investigators: to be identified and including UKWCS team.
Dietary behaviours are associated with social class. The impact of diet in relation to different social groups on risk of heart disease will be explored. Careful consideration of confounding factors will be required and analysis will be stratified according to social group. HES data will provide information on diagnosis of coronary heart disease, myocardial infarction and stroke.

6. Diet as a mediating factor between high blood pressure and risk of kidney disease.
Essential hypertension is associated with high intakes of salt. Other components of diet will also be explored in relation to risk of essential hypertension. How these factors then link with risk of developing kidney disease will be explored. HES data will provide kidney disease diagnoses.

7. Influence of parity and lactation on hip fracture risk.

Several studies indicate that parity and lactation are associated with modest, short-term bone loss, but the long-term effect on osteoporotic fracture risk is uncertain. The UKWCS has information on parity, lactation and use of oral contraceptives. HES data will provide hip fracture incidence data.



Yielded Benefits:

Below are some of the latest publications produced from the UK Women’s Cohort Study (UKWCS): Dunneram Y; Greenwood DC; Burley VJ; Cade JE (2018) Dietary intake and age at natural menopause: results from the UK Women’s Cohort Study. Journal of epidemiology and community health, Lambert JD, VanDusen SR, Cockcroft JE, Smith E, Greenwood DC, Cade JE: Bitter taste sensitivity, food intake, and risk of malignant cancer in the UK Women’s Cohort Study. European Journal of Nutrition. Pandeya N; Huxley RR; Chung H-F; Dobson AJ; Kuh D; Hardy R; Cade JE; Greenwood DC; Giles GG; Bruinsma F (2018) Female reproductive history and risk of type 2 diabetes: A prospective analysis of 126 721 women. Diabetes, obesity & metabolism, Rada-Fernandez de Jauregui D; Evans CEL; Jones P; Greenwood DC; Hancock N; Cade JE (2018) Common dietary patterns and risk of cancers of the colon and rectum: Analysis from the United Kingdom Women’s Cohort Study (UKWCS). International Journal of Cancer, Zhu D; Chung HF; Pandeya N; Dobson AJ; Kuh D; Crawford SL; Gold EB; Avis NE; Giles GG; Bruinsma F (2018) Body mass index and age at natural menopause: an international pooled analysis of 11 prospective studies. European Journal of Epidemiology, , pp. 1-12 Jones P; Cade JE; Evans CEL; Hancock N; Greenwood DC (2018) Does adherence to the World Cancer Research Fund/American Institute of Cancer Research cancer prevention guidelines reduce risk of colorectal cancer in the UK Women’s Cohort Study?. British Journal of Nutrition, 119 (3), pp. 340-348 Other publications and proceedings are available at https://ukwcs.leeds.ac.uk/publications/

Expected Benefits:

The researchers at university of Leeds will be using the linked data to produce (on an ongoing basis) research publications in peer-reviewed journals and presentations in scientific conferences. The data will be used to undertake independent research into disease management and outcomes to improve patient care, health economic studies and epidemiology of diseases with regards to dietary and lifestyle exposure.

The previous UKWCS database is extensively used by researchers to undertake population-based health research studies. There have been nearly 100 peer reviewed publications utilising the UKWCS database since its establishment in 1995. Findings are also shared through extensive public engagement activities including regular Scientific events and lectures to general public and health groups.

The UKWCS is one of the longest running of the British women's cohort studies. Today, the UKWCS offers a unique opportunity to explore the long-term biological and social processes of ageing and cause of death. Evidence is growing from this cohort study and others, that factors from later life (such as adult smoking, diet, exercise and socioeconomic circumstances) affect the opportunity to age well. This is of interest to policymakers, practitioners, and older people themselves. As the study is nationally representative, it will also provide valuable information regarding the factors associated with health care utilisation of the middle-age of women population.

The linked data set will be used to undertake independent research into disease management and outcomes to improve patient care, health economic studies, nutrition and health epidemiology studies. It anticipates adding to the knowledge to improvements in preventing chronic disease and maintaining good health in middle-aged women. Prevention depends on understanding of causes. The UKWCS can help provide a better understanding of mechanisms underlying disease and health; how these are influenced by the environment and what the potential population impact might be. There is increasing evidence for common pathophysiological pathways including glucose metabolism, inflammation, and hormonal profile for ageing related conditions. In addition to chronic disease and cancers, there need to be a better understanding of outcomes relevant to older populations such as functional health and quality of life. The UKWCS is a large long term prospective study that allows this approach. In particular, through knowledge transfer, public engagement, publications, presentations and invited commentaries (https://ukwcs.leeds.ac.uk/) the UKWCS has contributed to a body of evidence to influence policies and support evidence based medicine.

The example projects provided above have anticipated benefits including:
Project 1: Food intake and dietary patterns on incidence of Alzheimer’s Disease or dementia.
This research will lead to a better understanding of the risks associated with different dietary behaviours and future risk of dementia and Alzheimer’s Disease. It therefore has the potential to impact on public health policy.

Project 2. Physical activity and risk of all causes of cancer.
Physical activity is associated with risk of cancer, however, the interplay between diet and physical activity in relation to BMI and other cancer risks is unclear. The UKWCS has previously shown that fidgeting in sedentary women is protective against all cause mortality. This new analysis will lead to a better understanding of physical activity and sedentary behaviour in relation to cancer risk. It therefore has the potential to have an impact on public health policy.

Project 3. Body mass index, clothes size and risk of colorectal cancer.
Whilst it is known that some cancers are associated with BMI, it is not clear how change in BMI over the life course is associated with risk of colorectal cancer. The UKWCS has previously shown that skirt and blouse size is associated with risk of breast cancer. The study now wishes to repeat this work exploring risk of colorectal cancer. Findings for this study could help to provide a simple contributor to a risk score when measured height and weight to calculate BMI is not available since individuals do know what size clothes they buy.

Project 4. Breast feeding in relation to risk of breast cancer and other female reproductive cancers.
Whilst it is known that breast feeding has many benefits for both mother and child, the relationship of lactation on later risk of breast or other female reproductive hormone cancers is unknown. This work has potential to influence public health policy promoting breast feeding.

Project 5. Influence of diet on social class and risk of CVD.
Middle-class people generally have healthier diets than lower-class people. Dietary mediators seem to play an important role in the pathogenesis of cardiovascular disease, mediating some of the discrepancies in atherosclerosis among different socioeconomic layers. Further understanding of these relationships will help to drive public policy and strategies for reducing inequalities across the social classes.

Project 6. Diet as a mediating factor between high blood pressure and risk of kidney disease.
High blood pressure (HBP or hypertension) is the second leading cause of kidney failure. Over time, uncontrolled high blood pressure can cause arteries around the kidneys to narrow, weaken or harden. Some dietary behaviours may increase blood pressure (eg. high salt) whereas other dietary patterns (eg. DASH diet) may support blood pressure reduction. Understanding of how diet may influence blood pressure and kidney disease will provide more evidence to help develop prevention and treatment strategies with clear public benefit.

Project 7. Influence of parity and lactation on hip fracture risk.
Several studies indicate that parity and lactation are associated with modest, short-term bone loss, but the long-term effect on osteoporotic fracture risk is uncertain. The UKWCS can provide further evidence to the limited data available on this topic worldwide. Any associated effect with oral contraceptive use could influence policy around prescribing

Outputs:

The researchers who use these data will be producing (on an ongoing basis) research publications in peer-reviewed journals structured along the lines of a scientific paper (e.g. Summary, Background, Methods, Results and Discussion) eg. BMJ, Lancet, Nature, British journal of Nutrition, and Public Health Nutrition Journal. Interim tables of results (aggregated data with small number suppression in line with the HES analysis guide) may be circulated as interim results for discussion and appended to the study report at the end of the project. Further outputs include presentations in scientific conferences; such as Nutrition Society Summer Conference, Society for Social Medicine, etc. Leeds University appreciate the time taken for publications to appear and so anticipate the timing for this activity within one or two years after the data has been analysed.

After receiving the data linkage, UKWCS team will focus on optimising the database within 1 month after receiving the data and the database will be available for researchers to access by then.

Researches at the University of Leeds can access pseudonymised, non-sensitive record level database or delivery of aggregated tables; presentations, spreadsheets, word documents and other formal documentation for generation of research publications in peer-reviewed journals; and conference posters or presentations in scientific conferences. Information to be included in health assessments, nutrition and lifestyle epidemiology, natural history of disease, health economics and outcomes research.

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

Processing:

The UK Women's Cohort Study (UKWCS) data provides information on diet, health and lifestyle. This database is stored electronically by the University of Leeds in restricted access files. The new research database proposed (UKWCS-HES) will have the current UKWCS data linked with information from Hospital Episode Statistics (HES) and the Office of Data Release (ODR) from Public Health England.

A long period of data is required as the study is monitoring impact of wider health conditions that may take many years to manifest. The major health conditions are likely to become visible at least 10 years after the certain dietary and lifestyle is practised. The analysis needs to take account of morbidities prior to the start of the study. Individuals who had prior morbidities [e.g. heart defect, cancer, etc.] may be more/less likely to exhibit certain behaviours/contract certain health conditions of relevance to the study.

Due to the potentially wide variety of possible harms which might be attributed to the varied health outcomes in the UK women, the study requires wide ranging hospital episode data not restricted to specific types of episode. The date of birth/incidence/death will generally be used in the analysis to derive age at episodes.

DATA FLOW

The process for data merging and dissemination will have 2 steps.
• Step 1: Create new merged database in secure Virtual Research Environment (VRE) then strip identifiable variables to create a pseudonymised data set.
• Step 2: Pseudonymised data set made available to other researchers in safeguarded area of Consumer Data Research Centre (CDRC).

STEP 1 Create new merged database and pseudonymous data subset

An encrypted participant list which holds ID number, date of birth and NHS number will be created and securely transferred to NHS Digital so cohort participants' records can be extracted. The University of Leeds Integrated Research Campus (IRC) will receive and store data through a secure file transfer of data from the UKWCS database linked with data from both Hospital Episode Statistics (HES) and Civil registration data from NHS Digital and the National Cancer Registration and Analysis Services (NCRAS) from Public Health England. This linked data will form the basis of the new research database (UKWCS-HES).

The location of access is restricted. The IRC Data Services Team carry out disclosure control checks using relevant guidelines on anonymisation, data publication and any legislation or agreements that apply specifically to the project or the dataset. This ensures that no inappropriate data is removed from the Virtual Research Environment (VRE). All direct identifiers will be removed, apart from ID number prior to use by researchers.

All outputs are independently reviewed by the IRC Data Services Team prior to leaving the IRC. This means that the pseudonymised database will be reviewed using the IRC disclosure control process. This is set out by the IRC Data Transfer Policy. This process ensures that anonymity of patients, care providers and any third party is maintained. The staff undertaking disclosure control checking have received training in disclosure control and output checking from the UK Data Services and outputs are reviewed in line with the NHS Digital Disclosure Control Guidance e.g HES analysis guide and any other legislation or agreements that apply to the particular project or dataset.

Once step 1 is complete, the pseudonymised database will be deposited in the Consumer Data Research Centre (CDRC) to facilitate research requests and analysis.

Step 2 - Requests received for access to pseudonymous data set which are when approved made available to the researcher. the researcher will be either a substantive employee of University of Leeds or will have an honorary contract with University of Leeds.

The Senior Management Team (SMT) will assess whether the data access request fits the Centre’s remit. UKWCS team is notified that an application for their data has been received.

If acceptable the application will then be examined by the CDRC Research Approval Group (RAG).

The RAG consists of the chair member, ESRC and CDRC representatives, plus a member of the UKWCS team . A member of the CDRC RAG will then be selected as the Contact Researcher for each project and named on the application feedback letter.

The Contact Researcher will inform the applicant of the decision in writing. Approval from the committee is “in principle”, subject to the applicant signing and returning the CDRC User’s Agreement Form. The Contact Researcher will be the point of contact for the duration of the project. Further use of the data outside those specifically stated in the application form for other areas of interest will require a new application being submitted and approval by the CDRC Research Approval Group (RAG). The researcher will be required to list the variables they are interested in. The RAG will ensure the data requested is adequate, relevant and limited to what is necessary in relation to the purposes for which they have been requested in line with GDPR necessity tests.

RAG would assess whether the request fits with the purposes set out in this agreement. Leeds University ensure that the data accessed by each project outlined in the application has met the necessity test with regards to GDPR requirements.

University of Leeds staff, students and visitors would be able to apply for the data for research. If a researcher is not already a substantive employee of the University of Leeds then an honorary contract with visiting status would be set up containing the following text:

The University of Leeds will inform [your substantive employer] of any incident related to unauthorised disclosure or breach of confidence. [The substantive employer] retains responsibility for your conduct in connection with your work, including in particular your compliance with the terms of the honorary contract, as if your work or activities were performed for [the substantive employer]. Accordingly, [the substantive employer] agrees to take all appropriate disciplinary action promptly if any condition within this Agreement is breached by you.

(The agreement will be signed by the individual, the substantive employer, and the University of Leeds. This will ensure that the individual will be subject to the disciplinary process of their substantive organisation if he/she does something amiss with the data .) For all honorary contracts that the University of Leeds remains the Data Controller.

Any data processing within the study purpose by the applicant will use the pseudonymised database deposited in the Consumer Data Research Centre (CDRC) by the IRC Data Services Team. This will be through the use of a unique identifier assigned to each patient in the database instead of personal details such as name or NHS number; in line with the section 251 approval (without consent) through the Confidentiality Advisory Group (CAG) of the Health Research Authority.

Data may be linked to other publicly available data which would not increase the risk of re identification. Leeds university has appropriate operational arrangements for making sure linkage to the public available data will not increase the risk of re-identification. Risk assessments are conducted to identify risks to information assets in the IRC and classify these by probability and likely impact of occurrence. A risk assessment defines any risk mitigating actions that can be taken to prevent the occurrence or reduce the impact of risk. A treatment plan is then designed in order to manage and contain risk, or a risk owner is assigned, to complete the risk assessment.

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



Improving the safety and continuity of medicines management at care transitions (The ISCOMAT Programme) Work Packages 1 and 2 — DARS-NIC-40493-G5Y6K

Opt outs honoured: N, Anonymised - ICO Code Compliant (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: Non Sensitive, and Sensitive, and Non-Sensitive

When:DSA runs 2018-12-07 — 2020-12-09 2017.12 — 2018.02.

Access method: One-Off

Data-controller type: BRADFORD TEACHING HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

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

Objectives:

Improving the safety and continuity of medicines management at care transitions (ISCOMAT) is a series of interlinked work packages delivered by a multidisciplinary research collaboration between the Bradford Teaching Hospitals NHS Trust (BHTH) (as NHS lead and sponsor), the University of Bradford and University of Leeds. Each work package has designated lead(s) and is supported by researchers and collaborators from each of the organisations. BTHT has overall responsibility for the delivery of the programme and delegates responsibilities to the University of Bradford and the University of Leeds in a collaborator agreement. University of Bradford are not receiving any data as part of this application.

The programme is a series of interlinked projects which will design and test a complex intervention (a Medicines at Transitions Toolkit) to make best use of medicines and reduce harm through effective medicines management for heart failure patients from hospital discharge and into primary care.

When a patient moves between care settings (e.g. from hospital to home) medicine problems are common and planned changes are not always followed through. Patients particularly at risk are those with long-term illnesses taking several medicines – especially when medicines have been started or changed in hospital.
Patients with heart failure are the focus of our study as they are a public health and NHS priority, are frequent service users (including readmission to hospital), and susceptible to poorly managed medicines. Heart failure is responsible for approximately 5% of medical admissions and the hospital readmission rate within 3 months of discharge has been estimated as being as high as 50%.

ISCOMAT aims to help the way patients are supported with their medicines. This may contribute to improving their health through helping them better understand their medicines. It also aims to improve the way medical professionals work together to offer good standards of care to patients when they leave hospital. The specific objectives are listed below:

1. Map and evaluate current medicines management pathways across care transitions, describe the core characteristics of best practice and effective systems at each stage and compare with published evidence.(work package 1a)
2. Devise an underlying data linkage and data collection exercise to measure the effect of the proposed intervention (work package 1b)
3. Synthesise these data to develop a model of best practice that can contribute to a multi-disciplinary intervention (work package 2)
4. Based on a co-design process, integrate a patient-led perspective on the continuity and safety of the medicines management across care transitions to enhance the patient information-giving process as part of a Medicines at Transitions Toolkit (MaTT) intervention (work package 2)
5. Assess the intervention for usability and acceptability, establish an effective implementation process, and determine the feasibility of data collection for economic evaluation (work package 3)
6. Evaluate the effect and cost effectiveness of the intervention in a multi-centre cluster RCT (cRCT), in conjunction with a rigorous process evaluation. (work package 5)

This agreement will facilitate objective 2 (data-linkage) which is a data linkage feasibility study and will construct the data linkage foundations for the cluster RCT (objective 6). A future application will be made to access data for objective 6 (multi-centre cluster RCT). The day-to-day running of WP1a and WP1b is the responsibility of the programme manager employed by the University of Bradford. This includes co-coordinating the development of the research protocol, ethics submission and the identification of sites to identify, consent and recruit participants. The lead investigator for this work package 1 is based at the University of Leeds and the data linkage will be transferred, processed and analysed by researchers at the CTRU, University of Leeds.

The data linkage feasibility study has recruited in the region of 55 patients from four hospitals who were consented and recruited at the point of discharge from an in-hospital stay for heart failure by a research nurse. The hospitals are Castle Hill Hospital in Hull, Leeds General Infirmary, Calderdale Royal Hospital and Royal Blackburn Hospital. The consent process included consent for information about their health conditions and prescribed medicines held by their hospital and GP to be accessed via the organisations (i.e. Data Providers) which hold this information, for example, NHS Digital, SystmOne, EMIS and the National Health Failure Audit (NICOR), along with community pharmacies. Data will be received, processed, stored and analysed by the by the Clinical Trials Research Unit (CTRU) at the University of Leeds. No patient level data will flow to the Bradford Teaching Hospitals NHS Trust from the CTRU.

Upon recruitment from four different hospitals the research nurse (or study research fellow) registered the patient with the CTRU and provided demographic details. Details about the patients study eligibility, admission and discharge medication were also be recorded. Registration was via a secure online database at the CTRU. The data recorded at registration will include patient’s name, date of birth, gender, NHS number and patient study ID.

The study team have mapped the data variables available from each data provider onto the primary and secondary endpoints of the proposed definitive cRCT (objective 6) to allow for an accurate assessment of the patient pathway and important co-morbidities.

The primary endpoint for the definitive trial will be all-cause mortality + HF rehospitalisation measured over 12 months from hospital discharge. We anticipate that the data required for this outcome will be obtained from HES and ONS.

The key secondary endpoint is the number of patients prescribed the correct heart failure medications at 12 months post-discharge. The study anticipate that the data required for this outcome will be from NICOR, primary care and community outpatient pharmacy databases. Clinical and prognostic data such as diagnosis, comorbidities and discharge information, will be collected from the HES, NICOR, and primary care databases.

The findings of this data linkage study work package will inform the data variables required for the definitive cRCT and it is anticipated that a reduced dataset will be required for the subsequent DARS application for the cRCT.

The CTRU statisticians will provide patient identifiers in line with the requirements of HES analysis Guide Requirements. This may include patients name, date of birth, gender, NHS number and patient study ID. The patient identifiers will be sent to NHS Digital for confirmation that there is a record for the patient in HES / ONS. NHS Digital will provide data extract to the CTRU.

The above process will be performed with each of the Data Providers. The identifiers required to accurately identify a study participants will be agreed with each provider as part of the application process, ensuring the minimum identifiers are used. The CTRU statisticians will link the individual patient data items from each of the data providers to allow for the creation of a master patient file.

Yielded Benefits:

Delays have occurred in the access of data from other data sources (e.g. NICOR) and the organisation have been unable to receive data direct from the primary care providers. It is anticipated that the data linkage pipeline work will complete by the end of 2020, and will be based on data obtained directly from NHS Digital only.

Expected Benefits:

The benefit of this data linkage work is that it will allow the study to understand how linked data can be used to explore the intended and unintended outcomes of a transfer of care for people with heart failure.

By using this pilot stage to join the data of a small number of patients the study can explore whether their hospital discharge has been followed by a readmission or death and to explore how multi-disciplinary and multi-organisational care works to safely continue NICE-recommended medicines sets after people leave hospital.

This work will allow the study to develop the capacity to understand how this linked data can be used to measure important outcomes so that they can evaluate a co-designed intervention that improves patient care across a care transfer. The results of the data linkage work are expected to inform the evaluation methods used in the definitive cRCT integrated care (Domain 4.9). The continuing drive for cost effectiveness is explicitly recognised through the studies accompanying and comprehensive economic evaluation. Furthermore, the studies discussions with health service commissioners have highlighted the need for evidence to support future commissioning of community pharmacy services as well as the need for more effective optimisation of heart failure treatment, with associated health benefits.

The overall aim of the research has the potential to reduce the burden of cardiovascular disease by reducing preventable cardiovascular events that occur in the period after patients with heart failure are discharged from hospital through a combination of diminished medication errors and health gains from optimised treatment. Furthermore, the findings and other envisaged outputs may make a valuable contribution to the medicines management of many other NHS patients with long-term conditions.

Outputs:

The study team expect to have a data linkage algorithm in by the end of 2017. The plan is to publish this work in peer-reviewed journals (for example Health informatics, target submission 2018) and present at relevant conferences to inform the wider research community on the lessons learned in data linkages (for example, 'Using electronic health records in clinical trials: rising to the challenge of developing a data linkage pipeline – experience from the ISCOMAT programme' was presented as an at the joint International Clinical Trials Methodology Conference / Society for Clinical Trials 2017 conference in Liverpool on May 7-10, 2017).

The study will inform participants and involved clinicians and hospital teams and update the trial website to share the study findings in various formats (e.g. lay summaries).

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

Processing:

CTRU have receive patient identifiable data (including patient’s name, date of birth, gender, NHS number and patient study ID data) for each consenting participant from the participating site. The total number recruited is 53 participants. This data is processed by the trial data manager and statistician at the CTRU at the University of Leeds.

The trial statistician will provide NHS Digital with study ID, NHS number and date of birth for linkage to HES / ONS. The NHS Digital will provide the linkage to HES APC, OP, A&E, CC and ONS for each study participant.

All transfer of data between the CTRU trial statistician and the NHS Digital will take place via a secure file transfer system / secure data depot as agreed between the data provider and the data recipient.

Upon receipt of the data, data cleaning will be undertaken by CTRU statistician in internal process. This will include processes to ensure no duplicate episodes, no admission after date of death (if deceased). Additional data cleaning, analysis and linkage across each dataset will be in accordance with a Statistical Analysis Plan.

This CTRU trial statistician will subsequently link the HES / ONS record level data to participant record level data from primary care clinical systems (SystmOne and EMIS), a national cardiovascular specialist registry (National Institute of Cardiovascular Outcomes Research) and community pharmacy data. Data will also be linked to the ISCOMAT dataset held at the CTRU (consisting of the patient identifiers and details of patient’s study eligibility, admission and discharge medications). This will enable a data linkage pathway algorithm to be developed. The algorithm will not identify at the individual participants, the outputs will identify the variables and pathway.

The data items linked between the datasets are those relevant to the primary and secondary analysis of the proposed cRCT have been identified in each provider dataset. The data linked by the CTRU across the databases will establish quality and completeness of the data available from each database and derive the most reliable data pathway for the trial. The same patient identifiers will be used across each dataset, if permitted by the provider, to ascertain information on the same patient is collected.

For this data linkage feasibility study, work will be undertaken to provide descriptive statistics which show the extent to which linkage was successful for each data source. No statistical modelling will be attempted. The study will summarise the extent to which can successfully obtain the primary and secondary outcomes of the cRCT. The CTRU statistician will also summarise the covariates that plan to adjust for in the analysis of the subsequent cRCT. These covariates will be pooled from all the data sources. Levels of missing data from each data source will be summarised to demonstrate the acceptability of the data sources for the cRCT. It is anticipated that the study will be able to triangulate data from the various sources to produce a master patient record. The agreement/disagreement between various data sources on common data items will be reported.

All individuals with access to the data are employed by the CTRU, University of Leeds and will have undergone CTRU Data Protection training prior to accessing the data. No other third party will have access to the data. Data will not be used for any other purposes: it will not be used for commercial purposes, nor for direct marketing purposes. The University of Leeds is the sole data processor.

IT Infrastructure: The CTRU server infrastructure is split between two data centres on the main University of Leeds campus. Backups taken from this infrastructure are replicated to the University of Leeds disaster recovery site at the University of York with tape backups being kept at Iron Mountain. In all locations data is stored encrypted on disk/ tape. The 2 disaster recovery sites provide different recovery options. The site at University of York is a warm online copy on disk that can be retrieved instantly for the last 30 days. The Iron Mountain site holds a cold offline copy on tape for 12 months.

At the University of York location, the server is University of Leeds own equipment and connects only to the University of Leeds network. No individual at the University of York can access the data. The University of York only provides the physical space and power to support this.

University of Bradford are not part of the agreement and will not be accessing any data through this application.

ONS Terms and conditions will be adhered to.

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


QuantiCode: Admitted Patient Care Data — DARS-NIC-49164-R3G5K

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

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 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: Yes (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2017-10-01 — 2020-09-30 2017.09 — 2017.11.

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

Objectives:

The University of Leeds are running a project called QuantiCode. This project is funded by the Engineering and Physical Sciences Research Council (EPSRC) from March 2016 to February 2019 (details: http://gtr.rcuk.ac.uk/projects?ref=EP%2FN013980%2F1). The overall QuantiCode project is divided into 3 stages:
1) Data fusion, covering tools for data linkage and visualizing data quality, and thought leadership in data governance.
2) Analytical techniques that allow users to interactively mine longitudinal data for patterns.
3) Governance-aware abstraction techniques that allow users to explore how complex data may (or may not) be simplified to reveal important patterns.

The work will be evaluated by the collaborating organisations to ensure that the solutions are applicable in the real world.

The QuantiCode project involves a number of collaborating organisations (University of Leeds, Bradford Teaching Hospitals NHS Foundation Trust, Consumerdata Limited, NHS Digital, Sainsbury’s Supermarket Limited, Leeds City Council, Leeds North Clinical Commissioning Group, AQ Limited), who are interested in this work and are supplying datasets and will receive reports and tools as outputs of the project. NHS Digital is one of these organisations, as NHS Digital has a number of very large datasets, and Data Quality is an issue which is particularly important – it impacts directly on areas such as running the NHS (invoice validation, etc.), as well as some indirect benefits (research and analysis to develop policy/clinical guidelines). By collaborating with the QuantiCode project, it is expected that there will be benefits for NHS Digital and benefits to healthcare more widely as a result.

Any data provided from NHS Digital to the University of Leeds for this project will not be linked in any way with the other datasets being used. No record-level data from NHS Digital will be shared, or be in any way accessible, to third party organisations (including the other collaborating organisations). Similarly, no aggregated data including small numbers (as defined in the HES Analysis Guide) may be shared with (or be in any way accessible to) third party organisations

Within the bounds of the QuantiCode project, the purpose for processing healthcare data from NHS Digital is to allow different designs of visualisation and machine learning technique to be compared for their ability to meet user requirements, and allow the QuantiCode data analysis tool to be tested prior to release to NHS Digital for in-depth evaluation. A single year of HES Admitted Patient Care data is being requested in order to fulfil these objectives. The single year of hospital data is important as there are data quality process which take place at the end of the year, meaning that a sub-set of data (e.g. 6 months)will display different characteristics to the finalised (“Annual Refresh”) data produced after the end of the financial year. Without healthcare data, it is possible that the methodologies/tools cannot be applied to healthcare data, and the opportunity to improve the healthcare data will be lost.

In addition, a specific purpose for processing the health data is to make a detailed analysis of patterns of “missingness” in data (the manner in which data are missing from a sample of a population). The goal is to be able to investigate patterns that involve: (a) several (3+) variables missing together, and/or (b) are dependent on the particular value of other variables (e.g., provider code and admission type). These patterns are currently unknown and such missingness may involve any variable in a dataset, which is why all variables (except those deemed sensitive or identifiable) have been requested.

Expected Benefits:

It is expected that there will be benefit to health from the outputs provided to NHS Digital. The benefits will occur as benefits to the health system, either directly (through improvements to data collections) or indirectly (better quality data used in analysis/research).

The following headline benefits will arise from NHS Digital’s usage of the tool:

1) Allow NHS Digital to conduct integrity checking to identify occurrences of poor data quality in routinely collected data, for feedback to data providers (target date 30/9/18).

2) Allow NHS Digital to cross-reference variations in data quality issues with external influences (e.g. change in policy, change in priorities, change in resource, change in service provision or structure, coding improvement initiatives) (target date 30/4/19).

3) Allow NHS Digital to conduct bias checking to identify occurrences of poor data quality in routinely collected data, for feedback to data providers (target date 30/9/19).

4) Support NHS Digital in the development of new business rules for automated data profiling and feedback to data providers (target date 30/11/20).

5) Improve NHS Digital’s understandings of biases across time, geography and activity; NHS Digital’s focus has necessarily been on data quality by provider (in order to report back to providers so that data quality issues can be addressed ), with less emphasis given to time, geography and activity.

6) Allow NHS Digital to quantify the impact of data quality issues - e.g., whether the degree of missingness for certain conditions supports linkage match rates.

7) Improve the quality of the data used by NHS Digital when conducting analysis.

8) Improve the quality of the data provided by NHS Digital to third parties when conducting research/analysis.

NHS Digital manages many of the nation’s critical health and care data assets. It collects data from a range of care providers and provides secure and controlled access to those data by legally authorised bodies. Better use of health and care data will help those involved to:
- manage the system more effectively;
- commission better services;
- understand health and care trends in more detail;
- develop new treatments; and
- monitor the safety and effectiveness of care providers.

Understanding the quality of data is essential in deciding whether it is fit for these uses. The benefits above will help NHS Digital develop appropriate methods to monitor, challenge and highlight data quality issues to various audiences, giving the them the ability to correct the data if submitting or adjust their findings accordingly if just analysing.

NHS Digital also has a statutory responsibility, enacted in the Health and Social Care Act 2012 (section 266), to assess the quality of the data it receives against nationally published standards and to publish the results of those assessments. These benefits are likely to lead to new measurements in the report covering this statutory responsibility.

The tools and methodologies developed through the QuantiCode project may also benefit other organisations in other sectors, but the data from NHS Digital is only disseminated on the basis of there being a benefit to health.

Outputs:

The intended outputs relating to health are:

1) Data analysis tool Version 1 (target date 28/2/18). This output will be a visual analytics tool, which allows users to gain an overview of missing data patterns and investigate data integrity in health datasets.

2) Research report 1 (target date 30/9/18). This report will describe the application of the tool to health data, and the benefits that the tool provides. The report will be submitted to a high-impact outlet such as the Journal of the American Medical Informatics Association (the pre-eminent journal for research into methods for analysing health data).

3) Data analysis tool Version 2 (target date 31/5/19). This version of the visual analytics tool will allow users to investigate bias caused by data quality issues in health datasets.

4) Research report 2 (target date 30/11/19). This report will describe the application of the tool for bias investigations, and the benefits that the tool provides. The report will be submitted to the Journal of the American Medical Informatics Association.

Outputs 1 & 3 will not contain any data – a user will load their dataset into the tool to analyse missingness. Outputs 2 & 4 will contain only aggregate level data with small numbers suppressed in line with HES analysis guide. That data will be shown in figures that illustrate the usage of the tool.

The ultimate beneficiaries of this work will be the general public. For example, CCGs and local authorities analyse data to generate business intelligence for operations and investment, with the aim of providing us all with improved and more cost-effective services. Businesses similarly require business intelligence for operations and investment, which translates to jobs and other economic benefits. To bridge the gap between these indirect benefits from the project and popular interest in big data, the University of Leeds will conduct a range of public engagement activities which include live demonstrations at the annual Leeds Festival of Science, a short film, an on-line tutorial about the ethics surrounding data analytics, and publishing articles in the popular scientific press.

Processing:

The dataset (to be) provided by NHS Digital consists of pseudonymised, record-level data. The dataset will be transferred by the University of Leeds’ Integrated Research Campus (IRC) Data Services Team using NHS Digitals Secure Electronic File Transfer system (SEFT) The data will only be accessed by substantive employees of the University who are contributing to the project.
The patient data from NHS Digital will not be linked with any other dataset.

The Quanticode project will develop tools and methodologies for investigating data quality across a number of datasets. The aim is to test these tools and methodologies across a variety of datasets, including health data. Although the QuantiCode project as a whole will examine issues around data linkage, that work will not involve the use of data from NHS Digital data.

The QuantiCode project will process datasets provided by other organisations involved in the project, and the methodologies/tools will be developed to apply across datasets as much as possible. One of the aims of this is to ensure that techniques are developed which are generically applicable, rather than each sector needing to develop their own tools.

The NHS Digital dataset will be used to help design and test a new data analysis tool, which allows users to investigate data quality in health records. The development process for the tool will involve: (a) characterising the dataset so that scalable algorithms and appropriate statistical models may be designed, (b) using the dataset as an exemplar to design and implement new interactive visualization techniques for data quality investigation, (c) running the data to refine the statistical models, and (d) testing of the data analysis tool prior to release to NHS Digital for in-depth evaluation.

The NHS Digital dataset will only be used where necessary for the purposes in this agreement. Live data will not be used for early stages of development/testing when it would be more appropriate to use test data.

The data from NHS Digital may only be processed in order to produce the outputs detailed below (in the Specific Outputs Expected section).


Routinely collected hospital admissions data for care home residents — DARS-NIC-378523-Y5Q9L

Opt outs honoured: N, 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, Other-non-identifiable aggregate care home level data, Health and Social Care Act 2012 – s261(2)(c), Other-Non-identifiable, aggregate data (small numbers suppressed) at the care home level, , Health and Social Care Act 2012 – s261(2)(c); Health and Social Care Act 2012 – s261(7)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2017-06-01 — 2020-05-31 2017.09 — 2017.11.

Access method: One-Off

Data-controller type: BRADFORD TEACHING HOSPITALS NHS FOUNDATION TRUST, UNIVERSITY OF LEEDS, UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Accident and Emergency

Objectives:

The University of Leeds primary aim is to assess the feasibility and reliability of routinely collected data on health resource use.

Residents of care homes are amongst the frailest in our population with significant health and social care needs. The health requirements of residents place considerable burden on the NHS, in primary and secondary care. Greater demands are placed on the workload of GPs providing care for care home residents than caring for people in their own homes, in face to face contacts and out of hours visits. Care home residents are significantly more likely to attend emergency departments by ambulance and be admitted to hospital compared to the older population generally.

Hospital admission exposes residents to risk of hospital acquired infections and falls and is disruptive for this frail population as they struggle to return to their previous health state once discharged. If not appropriately addressed, the burden on NHS primary and secondary care services will continue to rise for this expanding client group.

Promotion of health of frail older people in care homes is poorly and inconsistently developed. Despite the potential for reduced NHS expenditure from improved health, provision of programmes to support activity within UK nursing homes (which could promote health and well-being) is only patchily realised. Only 10% of care home residents receive physiotherapy, and just 3% occupational therapy.

The feasibility trial proposed by The University of Leeds is the final stage of a programme grant funded by the National Institute of Health Research (NIHR). The programme grant has been divided into 5 work streams, with earlier work involving observation of care home environments; interviews with care home staff, residents and relatives to explore how to best implement change in activity; assessing which questionnaires to use and how to best measure activity levels; and developing an appropriate intervention with the aim of increasing activity (or reducing sedentary behaviour) in care homes.

This trial is now testing the intervention in 6 of 12 homes from selected locations within Yorkshire, randomised on a 1:1 basis to receive the REACH intervention plus usual care, or to continue with usual care only. It is anticipated that 8 - 12 residents will be recruited from each of these care homes. Staff working in care homes randomised to receive the REACH intervention will implement the intervention in their care home. Staff working in care homes randomised to the control arm will continue with their usual routine care to residents.

All 12 homes will provide data for the trial, either directly in person, from care home records, or via routine data sources such as NHS Digital. Part of the trial aim is to look at the best method of obtaining both safety (i.e. hospital attendance) and health resource use data. If the University of Leeds are able to do this by collecting HES and other data sets this will inform how data is obtained ultimately to run a large scale trial in many homes. This would happen if The University of Leeds feasibility trial was successful.

The University of Leeds will seek to establish the number of admissions overall from the 12 participating care homes and assess the completeness of this data. This aggregate data will allow assessment of the effect of the intervention at a whole home level, rather than only being reported for consenting residents (a sub-set of the care home population). This will allow us to assess whether the consenting cohort is representative of the whole home or whether there are differences in the number of hospital attendances and admissions for those who are and are not taking part in the research.

Expected Benefits:

A) For the identifiable, consenting cohort benefits include:

• Obtaining reliable ‘safety’ information – i.e. data which will show the reasons for and number of hospital attendances or admissions. This is important to be sure there are no adverse impacts of the intervention. It could also give us an indicator that the new intervention might have some benefits if people from intervention homes attend hospital less.

• Obtaining health resource use information – e.g. the number, type and length of hospital admissions - is a key element of NIHR-funded research. It is important to have this ‘health economic’ data which details the full cost of an intervention – for example, an intervention may appear to be effective, but incur many additional NHS costs such as multiple hospital visits or GP call outs. Without collecting data on health service use we cannot undertake this analysis. Collecting hospital attendance data from HSCIC for the feasibility study will inform how to best undertake this for the main trial, as well as giving an early indicator of resource use.

B) For the aggregate, non-identifiable cohort benefits include:

• An overview of safety at the whole home level. This will help us see the overall safety of the intervention – so we would be able to observe any differences in hospital attendances between ‘intervention’ homes and usual care homes. This would contribute to our decision to proceed with a main trial – i.e. if there are no safety concerns we would be happy to proceed.
• Having hospital attendance data for all (or at least ‘most’) residents gives a more representative picture of health resource use, rather than just that used by recruited (consenting) residents. For example it might be that those who consented are less ill than those who didn’t, so we wouldn’t get a true picture of ‘whole home’ hospital admissions from consenting residents alone. It is an important benefit to be able to report the generalisability of research findings – this data would help us to do that.

Decreasing mobility and increasing dependency have many adverse effects. For residents in care homes, it may lead to increased incidence of pressure sores, contractures, cardio-vascular deconditioning, urinary infections, and loss of independence. Mobility problems and reduced physical activity compound health difficulties by directly affecting physical and psychological health and reducing opportunities to participate in social activities; social isolation negatively impacts on mood and self-esteem, which can then further adversely affect physical health. Residents identify mobility as of central importance to quality of life and well-being and residents with dementia wish for more day-time activities. Physical ill-health and disability are the most consistent risk factors for depression in later life with reports suggesting that, rather than illness per se, it is the resulting functional limitations (handicap) including social participation and meaningful relationships that increase risk of depression. Physical activity provides positive benefits for older people > 65 years for a range of outcomes: decreased disease risk, mood and overall health. For frail institutionalised older people, systematic reviews indicate that physical training can positively affect fitness for some participants; the level of effect may be related to level of frailty. A recent review of the effects of physical activity for older people with dementia (not all of whom were in institutions) reports some benefits for physical function.

Additional benefits may be accrued through enhancing social engagement directly by, for example, participation in communal activities such as exercise sessions, and indirectly by maintaining physical abilities sufficient for the resident to be mobile enough to move around the home and interact with other residents. Such social engagement has been shown to be linked with more successful ageing.

The University of Leeds proposed research to enhance routine physical activity supports the aims of the DH report, NICE guidance and BGS6 reports to promote the well-being of older people in long-term care. It is in keeping with the National Care Home Review, which promotes the concept of care homes as community places with emphasis on creating opportunities for meaningful activity, for shared decision making and for building an environment that supports community.

The outputs will inform feasibility assessment in relation to a larger definitive clinical trial which would assess incremental cost effectiveness of an intervention to increase physical activity in care homes, compared to usual care. This feasibility assessment will be complete by the end of the current NIHR programme grant (14 February 2018).

Outputs:

The University of Leeds will begin the staged process of developing a complex intervention embedded in the routine of care homes to promote physical activity tailored to the context and environment of individual care homes and thereby enhance quality of life for this neglected group.

Ultimately, and if successful, the intervention strategies will be disseminated through the local Care Home Forum, local and national contacts with Adult Social Care and links with national care home providers through co-applicants and the Steering Group.

Successful completion of the feasibility trial (the last stage of the programme grant) will inform the application for funding to undertake a definitive Randomised Controlled Trial (as described in 'objective for processing'), to investigate the effectiveness of a physical activity intervention in care homes across England. The outputs will be used to establish a protocol for this trial (or otherwise, as appropriate).

The University of Leeds will report the results of the REACH trial to the NIHR (the funder) and, if the feasibility study results indicate that it is reasonable to proceed to a main trial, will apply for further NIHR funding to conduct a definitive main trial.

The feasibility assessment will be completed and published at the end of the programme grant (14 Feb 2018). Results for the trial will be presented in a report for the funding body NIHR. Academics will have access to the outputs via anonymised publication in journals. Indicators will not be produced that show the performance of organisations.

The outputs of this would inform best practice in care homes, and would be published in relevant academic journals (for example Age and Aging), non-academic platforms accessible to the general public (e.g. a study website), and would be disseminated to the care home community via relevant national and local forums or events.

Specifically the results of the feasibility study would be published in academic journals (e.g. Age and Aging, BMC Pilot and Feasibility Studies) and disseminated to the participating care home staff, residents and their relatives.

Outputs are expected in January 2018, when the study will complete analysis. Outputs will be disseminated as detailed above, regardless of the findings (and 'success') of the research.

Processing:

1) Consented Record Level Cohort (153)

The University of Leeds CTRU will supply the following identifiers of the consented cohort to the HSCIC: - trial ID, NHS no, DoB uploaded by named CTRU statistician to NHS Digital secure data depot.

NHS Digital will provide a bespoke extract of HES using APC and A&E datasets for the consented cohort of 153 care home residents.

Data is uploaded to the data depot by NHS Digital, and downloaded by a named CTRU statistician.

2) Aggregate Level Cohort

The University of Leeds CTRU will provide NHS Digital with Participating Care Homes’ (N=12) postcodes.

NHS Digital will provide aggregate data for all residents 65 years old and over at these care homes collated. Tabulations will include the number of A&E visits, the length of these visits between certain data parameters; and for the APC dataset they will include the number of hospital admissions (planned and unplanned) and average length of stay.

Aggregate data sets (by care home) uploaded to the data depot by NHS Digital, and downloaded by a named CTRU statistician.

Data Storage

Data will be stored at The University of Leeds in a secure, limited access folder on CTRU network.

Data required for use by health economics will be transferred by the named CTRU trial statistician to the named health economist via the CTRU's secure file transfer system. This data will be stored at The University of Leeds in the Secure Electronic Environment for Data (SEED) system.

Data Processing

1) CTRU enter and store data securely on restricted access UoL server (IGT ref ECC0010) - Data required for use by health economics will be transferred from CTRU and stored in the SEED system (IGT ref 8E218).
2) Data collected for the trial + NHS Digital data used for REACH trial analysis (analysis undertaken by CTRU statistician and health economist as per trial protocol)

Data will be processed by a named statistician and named health economist who are substantively employed by The University of Leeds.

The data will not be used for commercial purposes, and will not be provided to any third party or used for direct marketing.


Comparison of healthcare access for the general population in Yorkshire under the age of 59 to a population who were diagnosed with childhood or young adult cancer — DARS-NIC-155843-0MQMK

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

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), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: No (Academic)

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

When:DSA runs 2019-04-01 — 2022-03-31 2017.06 — 2017.08.

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Mental Health and Learning Disabilities Data Set
  3. Mental Health Minimum Data Set
  4. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  5. Mental Health Services Data Set

Objectives:

The University of Leeds requires HES and mental health data for a specific cohort to be used, alongside data collected in the Yorkshire Specialist Register of Cancer in Children and Young People (YSRCCYP), to continue its epidemiology and health services research programme.

For background, the YSRCCYP is a regional population based register containing detailed demographic and clinical information on children and young adults aged 0-29 years diagnosed with cancer since 1974. The YSRCCYP covers the Yorkshire and Humber Strategic Health Authority (SHA) which has a total population of 5 million people. Spanning an area of 15,000 square kilometres the Yorkshire and Humber SHA comprises a range of urban and rural communities with a significant ethnic minority population resident in parts of West Yorkshire.

The YSRCCYP research team, within the University of Leeds, is notified of patients eligible for inclusion in the YSRCCYP either directly by the patient’s treatment centre or via electronic reports from the National Cancer Registration and Analysis Service. The YSRCCYP research team then obtains information on patients by manual data abstractions from hospital records. Detailed data on the patient and diagnosis, including treatment information for each of these cases is obtained by a sole data collection officer via the medical records at relevant hospitals in the area, and annual follow up of all cases takes place to ascertain data on any relapses or deaths through letters sent either to the patient’s treating consultant or general practitioner. Data on 9,500 patients have been collected since 1974, however linked HES and mental health data was required for only 8,500 as the cohort shared with NHS Digital excludes participants who passed away before 1996. The cohort submission under approval of this request will consist of approximately 7,000 patients.

The YSRCCYP was originally set up in collaboration with local clinicians to provide research information. Since 1994, the YSRCCYP database and research programme has been managed by and at the University of Leeds’ Division of Epidemiology & Biostatistics. The University of Leeds is the Data Controller for the YSRCCYP with sole responsibility for determining the purposes for which and the manner in which any personal data are processed. The work is currently funded by the Candlelighters Trust.

The purpose of the YSRCCYP is to facilitate population-based epidemiological and health services research. The use of HES and mental health data contributes to this by providing additional information that can be linked with and analysed with data from the YSRCCYP data. The HES and mental health data are not added into the YSRCCYP research database. The two datasets are stored separately but contain common unique study IDs enabling data to be linked at record level. Where required for specific research, relevant data are extracted from the respective databases, linked and analysed by the YSRCCYP research team.

A current research focus is on hospital burden around the time of diagnosis and treatment and monitoring long term risks of hospitalisation associated with cancer treatment. One specific processing activity will relate to describing the risks and prevalence of mental health illness within the cancer cohort compared to the general population.

This type of epidemiological and health services research has the potential to benefit future patients by identifying risk factors which can be used by health professionals to identify those at greatest risk of mental health illness so that interventions and appropriate support can be implemented. It may also reveal important environmental risk factors, examine changes in incidence rates which may help to identify possible causes and understand survival patterns according to ethnic group and socio-economic status in order to ensure that there are no inequalities in outcomes or access to specialist cancer care for certain sub-populations.

The YSRCCYP research team’s research plans include the following objectives:

1) To describe the total burden of hospitalisation among the Yorkshire cancer population aged 0-29 years, to identify clinical and sociodemographic factors which influence the likelihood of hospitalisation and to investigate how hospitalisation rates have changed since 1997.

2) To understand patient care pathways through the NHS before, during and after cancer diagnosis. This includes assessment of time to diagnosis for children and young adults diagnosed with cancer under the age of 30 years to identify where improvements can be made to minimise delays in diagnosis leading to better prognosis and less stress and anxiety on patients and their families.

3) To calculate the risks and costs to the NHS of adverse health events requiring hospital admission for survivors of cancer in this age group so that clinicians can provide appropriate follow-up care.

To address aim 1 above the YSRCCYP research team will utilise linked HES and mental health data to investigate long term risks of respiratory and mental health illness in the cohort and identify sociodemographic and clinical factors which may affect these risks. The linked HES and mental health data are covered under a separate Data Sharing Agreement (reference: NIC-11809-H1Y3W).The YSRCCYP research team also wish to determine the relative excess risk of these conditions within the cancer cohort compared to the general background population and, in order to make this comparison, requires a separate pseudo-anonymised extract of HES data containing all episodes for patients in the Yorkshire and Humber SHA area only under the age of 60 at admission (the oldest person currently registered). This separate extract is covered under this Data Sharing Agreement.

The YSRCCYP research team require some data items classed as sensitive. These are the Referrer code, which indicates the manner in which the patient was referred to hospital by ascertaining the code of the referring organisation. This allows the YSRCCYP research team to identify particular patient pathways which are associated with an optimal time to diagnosis, a key indicator known to influence survival. Additionally the Consultant code data field is required because it enables the YSRCYYP research team to work out whether patients receive care at specialist cancer centres as opposed to general district hospitals, in order to address important health services research questions such as: ‘Does specialist care improve patient outcomes for children and young people including length of hospital stay and reduce subsequent morbidity and mortality?’. There are currently no databases which link consultant codes to specialist cancer centres for childhood and young adult cancer, so this process needs to be done manually using cohort linked NHS Digital data and the YSRCCYP database.

Yielded Benefits:

Several peer-reviewed scientific papers incorporating HES and registry linked data have been published including: van Laar M, Feltbower RG, Gale CP, Bowen DT, Oliver SE, Glaser A. Cardiovascular sequelae in long term survivors of young people’s cancer – a linked cohort study. Br J Cancer 2014; 110: 1338-1341. Althumairi A, Feltbower RG, van Laar M, Kinsey SE, Glaser AW, Picton SV. Patterns of hospital admissions and length of stay during 1996 to 2011 among children compared with teenagers and young adults after completing treatment following diagnosis with cancer in Yorkshire. Eur J Cancer Care 2015; 24: pp.9. Fairley L, Stark DP, Yeomanson D, Kinsey SE, Glaser AW, Picton SV, Evans L, Feltbower RG. Access to Principal Treatment Centres and survival rates for children and young people with cancer in Yorkshire, UK. BMC Cancer 2017; 17: 168 Smith L, Norman P, Kapetanstrataki M, Fleming S, Fraser LK, Parslow RC, Feltbower RG. Comparison of ethnic group classification using naming analysis and routinely collected data: application to cancer incidence trends in children and young people. BMJ Open 2017, 7 (9) e016332; DOI: 10.1136/bmjopen-2017-016332 Presentations of on-going work have been presented to academic and clinical audiences including: analysis of mental health late effects to the Royal College of Paediatrics and Child Health 2018 Conference; analysis of respiratory late effects has been presented at the Public Health England Cancer Services, Data and Outcomes Conference in June 2018.

Expected Benefits:

The benefits to health and social care will include:
1. Improved patient care. This work will identify to clinicians, commissioners and patients themselves of those individuals who are at greatest risk of hospitalization; this will enable follow-up practices to be tailored to patient needs, help identify potential health problems early and intervene so that patient wellbeing is maximized and NHS burden minimized. For example, those individuals identified from the risk stratification model as being at greatest risk of mental health illness will be offered additional support from NHS services (e.g. psychiatry, social care) through their treating oncologist or GP. The risks of depression following cancer treatment will help to describe the NHS burden of mental health problems in this vulnerable population. This knowledge will be informative to paediatric oncologists and other allied health professionals caring for patients, as well as their GPs, by improving awareness of the timing when depression is likely to be diagnosed so that the quality of care can be improved. Patients will be informed of their risk group via their treating consultant or at their annual hospital clinic follow up appointment. Their GPs will also be informed of the results of the risk stratification via the hospital consultant team. Anticipated dates to complete these activities are by December 2018.

2. Evaluation of treatments to identify best practice and guidance. Work to understand the reasons for the hospitalisation so researchers can identify whether certain treatments are associated with an increased risk of hospitalisation and disseminate this information through scientific journal articles. This will mean that alternative treatment modalities and optimal care can be planned which minimize these complications. Anticipated dates to complete these activities are by June 2019.

3. Evaluation of service provision. Highlight any inequalities in access to specialist cancer care services, particularly in older teenagers and young adults, so that all patients have an equal chance of obtaining the best care irrespective of their personal circumstances and thereby having the best chance of cure. The work will be written up in the form of reports to commissioners and journal articles so that clinicians and commissioners can use this information in order to make any necessary changes to service delivery so that the entire Yorkshire and Humber cancer population is served equally well. Anticipated dates to complete these activities are by December 2018.

4. Financial planning. Information on hospital activity burden and NHS costs associated with the diagnosis and treatment of children and young adults with cancer will be calculated by the University research team in collaboration with health economists at the Leeds Institute of Health Sciences. Changes in costs over the last 20 years will be reported, adjusting for inflation, in order to provide cost projections over the next 10 years. This information will be collated in the form of a report to specialist commissioners of childhood and adolescent cancer services in the Yorkshire & Humber region so that, where required, service changes can be implemented in order to meet future NHS patient demand. Anticipated dates to complete these activities are by December 2019.

At the moment, these data are lacking and once identified by the YSRCCYP research team, they will provide important information:
* to clinicians to help better manage their clinic populations,
* to specialist commissioners to monitor the effectiveness of cancer care and
* to patients in order to understand more about their own risks of complications associated with the treatment they have received and wherever possible self-manage their own care and wellbeing.
* to identify gaps in access to specialist care by the research team for two distinct populations:
i) teenagers and young adults, who do not benefit from the same level of centralised care as that in place for younger children, and
ii) South Asians as they are more likely to present with cancer due to genetic risk factors. Improving care for teenagers and young adults and the south Asian population will ensure that their survival rates are optimal and equivalent to other age groups and ethnic groups, and any subsequent complications of treatment are minimized and if these do occur are then managed appropriately by specialist NHS professionals to ensure a full recovery.

Outputs, such as the risk stratification model, will be integrated into clinical practice through established links between the YSRCCYP research team and paediatric and adolescent oncologists throughout the Yorkshire region. The research programme as a whole benefits enormously from the long-running, close collaboration with haematologists and oncologists in the Yorkshire and the Humber region who all help to ensure that the University's research findings are effectively translated into clinical practice and are involved in all outputs from the YSRCCYP database.

Outputs:

Work describing risks of health effects of treatment in relation to respiratory illnesses will be completed by the YSRCCYP research team and submitted for publication in the British Journal of Cancer (or similar) by June 2018. The June 2018 publication follows a June 2016 publication where descriptive statistics have been produced showing the respiratory conditions diagnosed within the linked cohort. The background admission rates in the general population are required over the same time period to enable further statistical analysis to be carried out. Outcomes of the work will also be disseminated in open-access journals (e.g. BMC Cancer) and presented at conferences including the National Cancer Registration and Analysis Service Cancer Outcomes annual meeting, Teenage Cancer Trust and the International Society of Paediatric Oncology annual conferences. Further work will be submitted to the European Journal of Cancer (or similar) in relation to specific mental health outcomes by December 2018. Analyses describing the variation in clinical pathways including delays and time to diagnosis will be submitted for publication by June 2018 to Journal of Clinical Oncology (or similar).

Additional work describing the rates of hospital activity and differences between ages at diagnosis (e.g. 0-14 vs 15-29) and ethnic group (e.g. south Asian vs non-south Asian) will be completed by October 2017 and submitted for publication to the British Journal of Cancer by December 2017. Details of risk stratification models and the methodology to derive these for individual patients will be disseminated by the research team to every clinician involved in the care of children and young people (CYP) in December 2018. This will be supported by the Yorkshire & Humber CYP cancer network that holds details of all practicing NHS CYP cancer teams and clinicians in the region.

Summary reports of the work and research undertaken will be compiled and also made available on the Yorkshire Register University of Leeds website (http://medhealth.leeds.ac.uk/info/545/yorkshire_specialist_cancer_register), according to the timelines listed earlier in the document.

All outputs will be aggregated with small number suppression in line with the HES Analysis Guide.

As the funder, the Candlelighters Trust may request information for use in its own information dissemination and publicity materials. For example, they may ask for the number of new cases diagnosed per year in Yorkshire and projected incidence rates. The University of Leeds would only share information that is available as a result of the processing activities described above – i.e. the YSRCCYP would not undertake further data processing in order to derive information requested by the Candlelighters Trust and any information shared would be put in the public domain. For clarity, the University of Leeds is not obliged to provide information on request to the Candlelighters Trust and would not share any data that are not aggregated with small numbers suppressed in line with the HES Analysis Guide.

The linked NHS Digital data alongside the background hospitalisation rates will be used to derive key information which will be provided by the YSRCCYP research team to clinicians involved in the long-term care of young people identifying each individual’s risk stratification group (defined as being at ‘low’, ‘medium’, or ‘high’ risk of future complications or health effects, based upon their previous hospital activity patterns, treatment mortality, dose, cancer type and stage). The risk stratification model will be devised by the YSRCCYP research team and disseminated to clinicians in the Yorkshire and Humber region via the Y&H Children’s and Young People’s Cancer Network (December 2018). Only those clinicians involved in the direct care of individuals with cancer will be provided with details of the risk stratification model. Health care commissioners will be provided with aggregated cancer intelligence data on the number of survivors currently being seen at each NHS Trust according to risk stratification group, so future services can be planned effectively (June 2018).

Data will be held for as long as the research project is funded to undertake this piece of epidemiological and applied health research. Though work is currently planned until December 2019, the current funding expires on 31st August 2017. Subject to securing ongoing funding, the data would be retained until December 2019 to allow sufficient time for completion of analyses, submission and final publication of papers.

Processing:

NHS Digital has previously supplied a pseudo-anonymised HES extract containing details of all inpatient episodes for patients in the Yorkshire and Humber SHA area only under the age of 46 at admission for the period from 1996/97 to 2010/11. A further extract for the period 2011/12 to 2016/17 (latest available) will be supplied and added to the previously supplied extract. These pseudo-anonymised HES extracts are specifically required for comparison of the cohort with the general population of Yorkshire.

The University of Leeds stores the data on an encrypted secure area network (SEED) and access is restricted to individuals working on the YSRCCYP register research programme. Access to the record level data will only be by substantive employees of the University of Leeds and located within the Division of Epidemiology and Biostatistics. No NHS Digital data will be transferred outside of the University of Leeds or shared with any third party individual or organisation (apart from where stored at 2 disaster recovery sites at the University of York and Iron Mountain, where data will be stored only for the purpose of disaster recovery and not processed for any other purpose)

Cohort linked data (HES and mental health), provided under a separate Data Sharing Agreement (reference: DARS-NIC-11809-H1Y3W), and the pseudo-anonymised HES extract are stored in separate files and are distinct from the YSRCCYP data itself. The pseudo-anonymised HES extract will not be linked to the cohort data supplied by NHS Digital or in the YSRCCYP database. Different pseudonymised HES IDs will ensure this is not possible.

On receipt of pseudo-anonymised data (HES and mental health) the YSRCCYP research team undertake the following processing activities:

The pseudo-anonymised HES extract is used to calculate the admission rates (per 100,000 per year) for the same HES diagnoses as the patient cohort. This work has been completed for cardiovascular diseases (van Laar et al, British Journal of Cancer 2014) and for a descriptive piece of health services research as part of a PhD doctoral thesis (Althumairi, University of Leeds, 2017). Work to examine respiratory outcomes according to patient characteristic groups, such as age group, sex, ethnic group, calendar period in the Yorkshire region will be carried out and these data will provide the background rate in the general population.

Rates of admission within the cancer survivors have previously been compared to aggregated hospital admission rates to work out standardised hospitalization admission ratios and assess whether these differed according to cancer diagnosis, treatment, ethnic group, gender, age group, period of diagnosis and socioeconomic status, using statistical models adjusting for patient case-mix while also incorporating the general background hospital admission rates. (Althumairi, University of Leeds, 2017). This process will be repeated using the latest pseudo-anonymised HES extract with a focus on specific disease groups, including respiratory diseases and mental health data, using a similar methodology as the YSRCCYP research team’s previously published work on cardiovascular disease.

The pseudo-anonymised HES extract will be used to compare (but not link) inpatient hospital admissions for the general population in Yorkshire under the age of 60 to data on a population of the same age range in the cohort who were diagnosed with childhood or young adult cancer (derived from data provided under a separate Data Sharing Agreement (reference: NIC-11809-H1Y3W)). The aim is to assess whether certain hospital admissions are more (or less) common amongst a population of survivors of childhood and young adult cancers following treatment compared to the general population. The risk of admissions of a certain diagnosis in the cancer population will be compared to that in the general population. The YSRCCYP research team aims to look at the whole admission pattern of patients, not simply those that occur in the primary diagnosis fields and therefore require an episode level extract as opposed to aggregated counts of admission.

Summaries of the results will be presented orally at conferences and are intended to be published in academic or medical journals. All outputs will be aggregated with small numbers suppressed and in line with the HES Analysis Guide.

Researchers who are not substantively employed by the University of Leeds may apply for access to data from the YSRCCYP but data supplied by NHS Digital will not be shared with any third parties.

Data will only be used for the purposes described in this statement. The NHS Digital data will not be linked to any other data apart from YSRCCYP data.

The YSRCCYP research team requires data from the full period from 1996/97 to 2016/17 (latest available) for several reasons. Firstly in order to address aim 1 investigating changes in levels of hospitalisation over time and within specific cancer types, age groups and sociodemographic groups. Secondly to maximise statistical power for analyses given the rarity of childhood and young adult cancer; also to assess changes in access over time to specialist cancer care services, as NHS policy regarding the recommendations for treatment of children and young people with cancer has changed with the opening of Principal Treatment Centres in hospitals across in England throughout this time frame.

Evaluating clinical care pathways and time to diagnosis also require data of all admissions prior to cancer diagnosis. The late health effects for childhood and young adult cancer survivors may occur any time after treatment ends and the risk of late effects increases as the cohort ages. In order to fully evaluate the total burden of adverse health events in these survivors’, data are required for as long a time period as possible. This may also include any hospital admissions prior to the patient’s cancer diagnosis to identify any underlying health conditions. The YSRCCYP research team is also notified about any subsequent malignant neoplasms from the National Cancer Registration and Analysis Service prospectively following the original cancer diagnosis and therefore need to retain all historical HES and mental health data in order to scrutinise any such individual’s history of hospital admissions and understand potential reasons for those who experience multiple tumour diagnoses.


SHIFT Trial Participant Data MR1384 — DARS-NIC-325074-F0J3D

Opt outs honoured: N, Anonymised - ICO Code Compliant, 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, and Non Sensitive, and Non-Sensitive

When:DSA runs 2018-04-28 — 2021-04-27 2017.03 — 2017.05.

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Accident and Emergency
  3. Mental Health Minimum Data Set
  4. Mental Health and Learning Disabilities Data Set
  5. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  6. MRIS - Cause of Death Report
  7. MRIS - Flagging Current Status Report

Objectives:

The SHIFT (Self-Harm intervention Family Therapy) Trial has been designed as a pragmatic, individually-randomised, controlled trial comparing Family Therapy (FT) with Treatment as Usual (TAU) for adolescents aged 11 – 17 years who have engaged in at least one previous episode of self-harm. The trial aims to recruit 832 participants from centres in Yorkshire, Greater Manchester and London. Family therapy will be delivered by qualified family therapists using a modified version of the Leeds Family Therapy & Research Centre Systemic Family Therapy Manual (LFTRC Manual), the development of which was funded by the MRC to support trials of FT. The primary outcome is rate of repetition of self-harm leading to hospital attendance 18 months after randomisation. Secondary outcomes include rate of repetition at 12 months, cost-effectiveness, quality of life, and predictive/process measures.

Data will be processed alongside other data collected for SHIFT Trial participants to form the final data set for trial analysis. Specifically: HES APC & A&E data will inform the primary outcome of the trial (hospital attendance following self harm) and the safety profile of participants (hospital attendance for any reason); ONS mortality data will inform the safety and population profile; MHLDDS data will enable a fuller description in the trial results of, and accounting for, services accessed by participants. All publications and reports to external bodies utilising the data will be fully anonymised; participants will only be identifiable to the trial team (who are already in receipt of full identifiers by virtue of existing data provided by and for participants).

Data will not be shared with third parties.

Yielded Benefits:

- Publication of results (HTA monograph and academic publication) - Contributing to the evidence base to support commissioning of an individual patient data meta-analysis with the aim to identify subgroups of adolescents in whom a therapeutic intervention for self-harm shows some evidence of benefit in order to guide future primary research.

Expected Benefits:

The SHIFT Trial was commissioned by the Department of Health via their National Institute for Health Research (NIHR) funding stream.

The primary purpose of conducting research like this is to inform NHS practice. The trial design is such that the ‘primary outcome’ is hospital attendance following self-harm 18 months after trial entry – what this means is that the University of Leeds will compare hospital attendances for the group of young people who received family therapy and the group who received usual care. The University of Leeds can only make this statistical comparison when everyone in the trial has been involved for 18 months. This is now the case – the last participants completed follow up in June of this year, so statistical analysis is underway.

Once the data is analysed the University of Leeds will have the results showing whether or not family therapy was better than usual treatment. Whatever the outcome there will be some benefit to the NHS and to people using NHS services. A review of the NIHR report and other literature this will inform NICE guidance which in turn will influence NHS commissioning.

A positive outcome showing that family therapy is more effective than current usual care would influence NICE guidance for best practice within the NHS. This would be established after publication of the main results - in 2016/17.

If family therapy is shown to be no better than standard care, the results will provide other valuable insights which will assist commissioners. For example, it may be that family therapy is does not lead to a decreased number of hospital attendances however, the results will show whether it is more or less cost effective overall. If it is worse or better, this will be similarly disseminated to inform practice.

Outputs:

The primary and secondary analyses from the SHIFT trial will be published as an HTA monograph (SHIFT is funded by the Department of Health’s National Institute for Health Research (NIHR) Health Technology Assessment (HTA) programme. It is a key funder for a lot of large scale research projects across England. One of the requirements of conducting research funded by HTA is that a 50,000 word monograph (or report) is produced at the end of the study, providing detailed evidence of processes undertaken, trial results, interpretation and dissemination plans. The HTA monograph is due for submission March 2016, with an anticipated publication date of October 2016.

The findings will be submitted to relevant peer reviewed journals in the field of child and adolescent mental health and self-harm. There is the intention to more widely disseminate trial results to patient and public groups and to the lay community. The intention is to meet with a young person’s lay group in London (the same group they consulted regarding the newsletter) the National Institute for Health Research’s (NIHR) Young People’s Mental Health Advisory Group. At this forum the results will be presented and questions will be asked for their advice on interpretation from a lay perspective, and also their thoughts on where and how results would best be disseminated.

It is a condition of NIHR funded research that results are disseminated widely and appropriately and not just in academic journals – lay dissemination will be initiated at the meeting with the above group and their advice sought. The SHIFT trial will also look at other existing patient forums – local and national – for oral dissemination, as well as via charitable organisations (such as Young Minds) and local / national lay publications in which they might be able to include suitable articles.

In all cases this would be a summary of findings including the implications of these.

In summary results will be published in usual academic routes, papers in journals, presentations in conferences;

Newsletter to all participants (unless they have told us they don't want this) and to all participating staff;

Information on study web site;

Press releases and possible involvement of national media;

A special conference will be organised in Leeds for all the clinical colleagues who were involved.

The University of Leeds also want to do something with the young people and their families. Exactly what is still under discussion, consultation is still underway with YoungMinds and the NIHR CAMHS user group. This will influence wording of newsletters/ websites etc.

The intention, should the trial show that the intervention is effective, is that the results will ultimately inform NICE guidance and influence NHS practice in this area.

No outputs will ever identify any individual and be aggregated with small numbers suppressed, organisation, nor include any record level data.

Processing:

Data will be processed by the trial statisticians at the Clinical Trials Research Unit, Leeds Institute for Clinical Trials Research (LICTR) at the University of Leeds. It will be securely stored on CTRU systems with access only granted to the statistical team. Data will not be accessed by any third parties, nor will it be accessible across multiple organisations. LICTR has IG toolkit status (Code: ECC0010).

Identifiers will be sent to the HSCIC (Trial ID, postcode, NHS number, gender and Date of Birth). Data will be linked with existing SHIFT Trial datasets (data provided by participants and researchers in accordance with the REC-approved trial protocol and participant consent), as per the existing agreement with HSCIC that this data will augment the dataset with data that is difficult or impractical to obtain from individual NHS organisations. The linked data will be returned, containing identifiers, back to the University of Leeds and only accessed by a named statistician before it is stored in the networks.

Data will not be used for any other purposes: it will not be used for commercial purposes, nor for direct marketing purposes.

All individual accessing or processing the data are employees of the University of Leeds.


Hospitalisation and Mortality after Acute Myocardial Infarction — DARS-NIC-17649-G0X4B

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

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 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2017-02-13 — 2020-02-12 2017.03 — 2017.05.

Access method: One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care

Objectives:

The objective for processing of these data is to perform research into survival following heart attack in England.

Over the last decade, there has been a substantial and sustained decline in mortality rates from cardiovascular disease in the UK. Despite this, cardiovascular disease remains the biggest killer in the UK and someone is admitted to an NHS hospital with a heart attack every three minutes. Moreover, improvements in acute myocardial infarction (AMI; heart attacks) survival are likely to be a major cause for the increasing incidence of heart failure (‘transferred morbidity’), which now affects around 900,000 individuals in the UK and accounts for 5% of all emergency hospitalisations. Presently, most patients with cardiovascular disease are elderly and because AMI survival has increased there are more patients living longer with co-morbidities. More frequently, such patients require specialist cardiovascular care in the form of invasive cardiac procedures including high and low voltage and resynchronization pacemakers and coronary revascularisation. Moreover, they frequently re-present to hospital – escalating the burden of admissions with heart failure.

Specifically, the research will aim to quantify the long term outcomes and hospitalisation rates for survivors of acute myocardial infarction in England.

The objectives of the analysis are:
1. To describe hospitalisation patterns and endpoints (heart failure, cerebrovascular disease, coronary revascularisation, vascular dementia, severe bleeding, acute myocardial infarction, atrial fibrillation, all-cause mortality) for patients hospitalised with non-fatal AMI (i.e. survivors of the index hospital stay) compared to those who have no recorded AMI .
2. To identify factors associated with hospitalisation and endpoints for hospital survivors of index AMI compared to those who have no recorded AMI specifically focusing on geographical variation and the provision of timely percutaneous coronary intervention.

In order to quantify the incidence of a range of hospitalisations (cerebrovascular disease for example) following survival from AMI, the study team at the University of Leeds need to ensure they have a clean cohort for analysis to minimise confounding where possible as well as data of the hospitalisations occurring among patients who have no recorded AMI. Detailed justification for the request of this level of data is outlined below.

1. Reasons for requiring hospitalisations amongst patients with no recorded AMI
In order to quantify the incidence of a range of hospitalisations (cerebrovascular disease, heart failure and other outcomes) following survival from AMI, the study team needs to compare the number of each hospitalisation type occurring amongst AMI patients to the number of each hospitalisation type which occur in the background population (in this case, the background population is the population of patients admitted to hospital without an AMI in the same study period). The hospitalisations occurring in the non-AMI population are used to determine the expected number of each hospitalisation type for someone hospitalised in the same year, and of the same age and sex as someone who has had AMI. The observed numbers of hospitalisations for those with AMI will then be compared to the expected number of hospitalisations amongst those without AMI to determine whether patients with AMI have more hospitalisations than expected (the excess hospitalisation incidence rate). Without this quantification of the excess hospitalisation incidence rate, the results will have no context as the study team will be unable to ascertain whether those with an AMI are more or less likely to experience certain conditions following their AMI than the background population. Determining this is the primary aim of the study.

The study team will require all hospitalisations amongst patients with no recorded AMI (subject to filtering described under “2. Ensuring derivation of a ‘clean’ cohort”) rather than a sample of hospitalisations. The study team considered the feasibility of selecting a reduced number of geographical areas to represent the nation rather than requesting national data but ruled out this approach because it would affect the validity of the findings. This is because an incidence rate is calculated from the observed hospitalisations amongst the AMI patients divided by the observed hospitalisations in the non-AMI population. A sample of hospitalisations (obtained from a reduced set of geographical areas) would change the study design from a population based cohort study to a case-control study, through which it is not possible to calculate incidence rates. Whilst it is possible to obtain relative risks from a case-control study, selecting a sample of ‘controls’ which are representative across a range of hospitalisations (i.e. all the study outcomes) in England could not be guaranteed. Without a representative cohort, the relative risks obtained would be prone to bias. Given the potential impact of the findings on healthcare users and NHS policy, it is essential to minimise uncertainty. In addition, a case-control study design is not suitable for studying multiple outcome measures as proposed by the study team. We would therefore be unable to achieve the study objective of defining the incidence of multiple hospitalisation outcomes following AMI if restricting the non-AMI patient data to a sample of the population, nor guarantee the validity of results which are obtainable under a case-control study design.

Finally, the study team aim to additionally determine the extent of geographical variation in hospitalisations and mortality following AMI, which require the calculation of incidence rates (and therefore require a full population denominator) for all areas in England.

2. Ensuring derivation of a ‘clean’ cohort
The study team cannot be sure that patients admitted to hospital with AMI in a given period of HES data have not had a previous AMI, or, whether they have had any of the conditions they are considering as outcomes, such as cerebrovascular disease prior to their AMI. Therefore, the study team proposes to derive the cohort for analysis from admissions from 2008/09 to present day, however, has requested for NHS digital to exclude all people from the data who have had a previous AMI or any of the hospitalisations the study team are considering as outcomes. The same filtering of prior conditions will be done by NHS digital for patients who have not had an AMI from 2008/09 onwards. This is a substantial minimisation effort by the study team, as without this step, data from 200-1/02 would have been required as part of the data application. Data from 2008/09 onwards will give sufficient data to look at time trends in hospitalisations and mortality as part of the analysis.

Details of all hospital attendances (not restricted to specific conditions with known associations with AMI) are required in order to understand the history of the patient and whether past (non-related) attendances have contributed in any way to that AMI attendance, or to any of the study outcomes including heart and non-heart related outcomes for patients in the AMI or non-AMI cohort. Post attendances also supports this (whether AMI contribute to non-heart related attendances).

Additionally, for each individual NHS Digital will provide a vital status indicator (alive/deceased) and, where individuals are deceased, the number of days between the data of admission and the date of death. The date of admission will not be supplied to the University of Leeds making it impossible for the study team to derive the date of death from the data supplied.

The research will be undertaken by the established Cardiovascular Epidemiology Research Group within the Leeds Institute of Cardiovascular and Metabolic Medicine at the University of Leeds. This research group has a remit of using large scale routine data and clinical registries alongside advanced analytical epidemiological techniques to better understand and improve the quality of care of patients with cardiovascular disease. The proposed work to study the hospitalisation patterns and outcomes for patients with acute myocardial infarction is part of a larger programme of work funded by the British Heart Foundation (Project Grant PG/13/81/30474) in order to fill an important knowledge gap of the long term hospital burden and non-fatal outcomes for patients with AMI using contemporary, large scale and national observational data.

Expected Benefits:

This study will quantify the burden of hospitalisations and long term outcomes for patients who are admitted to NHS hospitals and surviving acute myocardial infarction (AMI) in England. The research outputs as described will be disseminated widely to University of Leeds' established informal networks including the academic community, clinicians, patients and the public as well as NHS commissioners via the formal networks discussed in section 5c. Dissemination of the factors which could lead to increased hospitalisations and mortality to clinicians (via academic publications, presentations at clinical conferences and dissemination via the British Cardiac Society and British Heart Foundation) is envisaged to be a driver for improved patient care and has far reaching clinical and social benefits as outlined below.

Quantifying the burden of hospitalisations and long term outcomes for patients surviving AMI in England will for the first time, on a national scale, provide NHS commissioners with the necessary evidence to plan effectively for service provision and resource allocation for the large proportion of patients who now survive their AMI. Although improvements in treatment have resulted in improved survival rates for patients with AMI – the long term health burden of patients following their AMI is not yet known – and this is what the study team propose to determine. In addition, the findings from this study can be used to inform new endpoints for future clinical trials, to ensure that not only the mortality or short term cardiovascular outcomes of AMI patients are considered, but also longer term cardiovascular and non-cardiovascular outcomes in developing and testing new treatments in future.

In addition, by quantifying the impact of lack of adherence to guideline recommended care on re-hospitalisation and mortality or the impact of delayed PCI treatment on re-hospitalisation and mortality, the Cardiovascular Epidemiology research group would provide the scientific supporting evidence to clinicians to strive for improved adherence to guidelines, which therefore has the potential to improve outcomes for patients.

Increased patient awareness of the impact of AMI on future hospitalisation and mortality, through dissemination to the public as described, could not only lead to patients modifying their own health behaviours to minimise their own risks of future hospitalisation, but patient and public who are informed by this knowledge can also provide strong motivation for clinicians and commissioners to improve patient care and care pathways.

Knowledge of geographical variation in hospitalisation and mortality from AMI will identify key areas of inequality in the NHS, dissemination of this knowledge to NHS commissioners will enable them to act upon such inequalities to ultimately drive up standards and provide direct and measurable benefit to patients and the NHS. This work forms part of the wider research conducted by the University of Leeds' research team (Cardiovascular Epidemiology), and will therefore contribute to a growing body of evidence regarding the quality of care and outcomes for patients surviving AMI, whilst adding important new insights into the long term health burden for the increasing number of AMI survivors which focusses not only on mortality, but importantly, also on re-hospitalisation for a range of cardiovascular and non-cardiovascular conditions.

The Cardiovascular Epidemiology research group has expertise in health services research which directly impacts on patients, policies and healthcare professionals through research papers, the media and conferences. The research group has an excellent track record for translating research to clinical impact, which specific examples listed below:

Research referenced in NICE guidelines:
1) Clinical risk scoring for acute myocardial infarction referenced in NICE Clinical Guideline 94 (Gale CP et al, Heart, 2008; 95(3):221-227)
2) Atrial fibrillation research referenced in Atrial fibrillation: management, NICE clinical guideline 180 (Cowan, Long and Gale et al. Heart (2013): heartjnl-2012)
3) Pre-hospital ECG research referenced in European Resuscitation Council Guidelines for Resuscitation 2015 (Quinn, and Gale, et al. Heart (2014): heartjnl-2013).

Widespread media coverage and beyond:
1) Research by Dondo and Hall et al (Dondo T, Hall M, et al. Eur Heart J Acute Cardiovasc Care. 2016) has received widespread media coverage including radio and TV broadcasts as well as broadsheets and tabloids. This research also resulted in being invited to present at the Westminster health forum, and forms the critical evidence for the non-ST elevation myocardial infarction NICE Implementation Collaborative.
2) Research by Hall and Gale et al (JAMA 2016; Aug 30. doi: 10.1001/jama.2016.10766) as well as Wu, Hall and Gale et al (Eur Heart J Acute Cardiovasc Care 2016; Aug 29. pii: 2048872616661693) forms the evidence for the guidelines in practice NIC project (https://www.guidelinesinpractice.co.uk/nic-projects).
3) The geographic variation in AMI treatment by Dondo, Hall and Gale et al (BMJ Open 2016; 6 (7): e011600) has received widespread media coverage, and has led to a successful Department of Health / NHS England business case to develop the work further into a feedback quality improvement programme for patients, hospitals and commissioners (work currently ongoing).

Several members of the Cardiovascular Epidemiology research group have experience with Public & Patient Involvement, meeting patients to discuss a range of different research proposal and allowing them to influence and be part of the research agenda as well as disseminate research findings back to them, whilst some members of the research group hold very close involvement with the British Heart Foundation, especially their press office and policy group who therefore act as a powerful conduit for change and knowledge dissemination.

The research the Cardiovascular Epidemiology research group propose here is of direct and critical importance to the NHS and the Department of Health. Although heart attacks remain the biggest killer worldwide, survival rates are improving. As such, patients are living longer with their cardiovascular disease, and there are an estimated 7 million people living with cardiovascular disease in the UK. The Cardiovascular Epidemiology research group propose to look at the components of the disease process including the wide range of outcomes following acute myocardial infarctions so that the commissioners, hospitals and NHS England can make evidence informed policy decisions about the need for cardiovascular care, as well as where, when and in whom. The research group has an excellent track record to ensure this research outputs are far reaching with high impact.

Outputs:

Whilst the planned analyses will be disseminated to the academic and medical community in peer reviewed publications and presented at relevant conferences (see below), it is the clinical implications of the results for healthcare professionals, patients and regulators that are of greater virtue. It is clear that the results from the proposed study will help answer major gaps in the knowledge base of the health burden and ongoing hospitalisation for the increasing number of survivors following acute myocardial infarction which can therefore contribute to future healthcare policy. The Cardiovascular Epidemiology research team has established connections with numerous relevant groups through which findings will be disseminated to the NHS as well as patients.

These groups include: The NICE Indicator Advisory Group, the European Society of Cardiology Acute Cardiovascular Care Association, the European Society of Cardiology Acute Cardiovascular Care Association Quality of Care Group, the British Cardiovascular Society Guidelines and Practice Committee and the National Institute for Cardiovascular Outcomes Research (NICOR) Research Executive.

The Cardiovascular Epidemiology research group is led by an Associate Professor of Cardiovascular Health Sciences at the University of Leeds who is also a member of the above groups and is additionally an honorary consultant Cardiologist at York Teaching Hospitals NHS trust and secretary of the European Society of Cardiology Acute Cardiovascular Care Association – offering further dissemination routes which will be utilised.

NICE identifies awareness and knowledge as well as lack of motivation by healthcare professionals to be some of the key barriers to change in the NHS. Patients are at the heart of providing motivation for healthcare professionals to improve care in the NHS, therefore the Cardiovascular Epidemiology research group will focus on dissemination to patients as well through charities listed in point 3 below.

The Cardiovascular Epidemiology research group dissemination strategy will be as follows:
1). Peer-reviewed publication
Paper 1: Hospitalisation and mortality after acute myocardial infarction. Anticipated submission date: March 2018.
This paper will quantify the hospitalisations and long term outcomes for patients surviving acute myocardial infarction as well as determine the factors which lead to increased hospitalisation and morbidity.
Paper 2: Geographical variation in hospitalisation and mortality for patients surviving acute myocardial infarction. Anticipated submission date: August 2018.
This paper will quantify the potential geographical variation in hospitalisation for patients surviving AMI to identify potential healthcare inequalities for NHS Commissioners.
Paper 3: Hospitalisation and mortality for patients surviving acute myocardial infarction according to receipt of timely percutaneous coronary intervention (PCI). Anticipated submission date: August 2020.
This paper will specifically look at the association between timely receipt of PCI and the long term hospitalisations and outcomes for patients surviving AMI.

2). Wider academic dissemination of the research findings will also be made at major national and international conferences as appropriate, such as the British Society of Cardiology conference (June 2017/18/19) and the European Society of Cardiology Congress (August 2018/19/20).

3). Lay summaries of the research findings will be generated and disseminated to the following key stakeholders: the British Cardiovascular Society (BCS), British Heart Foundation (BHF), TakeHeart, NHS commissioners and clinicians/health professionals involved in managing heart attack. The Cardiovascular Epidemiology Research group have previously liaised with these organisations to ensure wide reaching research impact, beyond the academic community (see section 5d) In addition, the group website (Cardiovascular Epidemiology - https://medhealth.leeds.ac.uk/homepage/692/cardiovasucular_epidemiology-leeds_institute_of_cardiovascular_and_metabolic_medicine) as well as the research team's twitter account (@UoLCardioEpi) will be used to update the public, the network of stakeholders, charities, and health professionals throughout the project.

All outputs will be aggregated with small number suppression in line with the HES Analysis Guide.

Processing:

Data will be stored on the University of Leeds' Secure Electronic Environment for Data (SEED) system. The data will only be accessible to authorized individuals in the Cardiovascular Epidemiology Research Group within the Leeds Institute of Cardiovascular and Metabolic Medicine at the University of Leeds. The data will only be accessed by substantive employees of the University of Leeds and only used for the purpose of this project.

The data will be geocoded based on Lower Super Output Area (LSOA) to obtain information on higher aggregated geographical units (Clinical Commissioning Groups). No further linkage to the data will occur. Only summarised and aggregated data will be disseminated in the form of academic presentations and peer-reviewed journals.

The data will not be used for commercial purposes, provided in record level form to any third party or used for any direct marketing.

The study is funded by the British Heart Foundation. For the avoidance of doubt, the British Heart Foundation will not influence the results or dissemination of the research conducted, and the British Heart Foundation will have no role in the design, analysis or interpretation of the research.


Project 18 — DARS-NIC-367152-K6Y1D

Opt outs honoured: Y, N ()

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Non Sensitive

When:2017.09 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. MRIS - List Cleaning Report
  2. MRIS - Personal Demographics Service

Objectives:

Objective for processing: To conduct death checks, retrieve patient addresses and data verification (of the data included in the CVS sent to HSCIC) for the purposes of administering a PROM survey of men with prostate cancer.

** update December 2016 **

The original survey has been completed, and there has always been the intention to send a follow up survey 1 year after the first questionnaire to those men who consented to the first survey, to allow longitudinal assessment of outcomes.

Expected Benefits:

Clinical and scientific progress in managing prostate cancer will only bring benefits in terms of well-being and survival for patients if we develop comprehensive and clinically meaningful approaches to measuring the important patient outcomes.
Primary aims
• To describe the Health-Related Quality of Life (HRQL, e.g., physical, psychosocial) of men with prostate cancer using qualitative and quantitative methods;
• To explore if and how their HRQL is associated (cross-sectional) or is predicted by (longitudinal) disease, treatment and/or patient characteristics with a view to inform development of health care policy and service delivery in ways that better meet the needs of such men and their families;
• To describe the levels of patient empowerment and undertake preliminary exploration of the interaction between patient empowerment and HRQL.
Secondary aims
• To collect data to support, if possible, provider variation and health economic analyses especially for the longitudinal work;
• To analyse the questionnaire data collected by exploring and checking the psychometric properties (e.g., reliability, validity) of the newer, less well-established questionnaire measures and to investigate the possibility of developing an item-bank for HRQL assessment for use with men living with and beyond prostate cancer using Rasch models. Qualitative interviews will be used to identify ‘gaps’ in surveys of importance to patients and patient partners with a view to adding additional items/questionnaires in the second surveys.
• To explore the acceptability/options of electronic PROMs data collection in this cohort and acceptability of real time feedback to service providers to influence/support direct patient care.
The commercial aspect of this application does not, however, detract from the numerous and varied health-related benefits of the project, notably with regards to the insight into life with prostate cancer and intention to improve clinical treatment and policy going forward (see above). This work will ultimately inform clinicians and the NHS about prostate cancer sufferers and in turn help drive improvements to treatment. Picker Institute Europe is a health research charity, and this project supports the organisation's overarching objective to improve patient experience and healthcare.

** update December 2016 **

As data has only recently been received by the University of Leeds the benefits currently remain as above. With the follow up cohort, as NHS Digital will clean the data for patient objections which reduces the risk of sending the survey to men who have opted out under that model. The repeated fact of death check also reduces the risk of distressing the men's family by not contacting them if they are deceased.

Outputs:

The first output will be the survey itself. The applicant will send the PROMs questionnaire to prostate cancer patients in England, Scotland, Wales and Northern Ireland asking a variety of questions about their care and their quality of life. Those who respond will be sent a follow up questionnaires on an annual a year later asking the same questions. The target date for the first mailing is 5th October 2015, with the fieldwork continuing for three years.

Picker Institute Europe will present the research team at University of Leeds with a final data file once the fieldwork is complete from which the research team will carry out various analyses. This data file will consist of case data and will contain sampling information –, NHS trust and reference number - alongside the response data from the questionnaire. The mailing data will not be included in this submission, so names, addresses, year of birth and NHS numbers will not be present.

This data will contribute to a report presented to the funders: Prostate Cancer UK and the Movember foundation and a series of papers submitted to peer-reviewed journals. It is not yet known exactly what the articles will be on and where they will appear, but there is a large research team and it is hoped that there will be many outputs from this rich data source.

** update December 2016 **

The English Cohort part (Year 1) of the survey closed on 21st April 2016, with over 60% response rate. The Research Team in University of Leeds have received the final data file, so analysis is under way.
The next part of the Prostate Cancer project has already started. Mailings have been sent out for all Devolved Nations (Northern Ireland, Scotland and Wales). There is currently no finalised closing date for any of these cohorts. The aim is exactly the same as for the English Cohort, so separate final data files per cohort will be collated and sent to the research team, in the same format as before.

Processing:

A csv file will be prepared to be sent to HSCIC for list cleaning with details of patient surnames and forenames, NHS numbers and date of births. Picker Institute Europe require HSCIC to identify those patients that have died as well as providing back the patient's NHS Numbers, forenames and surnames, addresses and postcodes.

** update December 2016 **

The identifiers for those men who consented to the original survey were flagged by the Picker Institute and Public Health England (PHE) informed to update their cohort details. This means that the data shared with NHS Digital will be for those men who consented only.

PHE will send the cohort details (30,465) to the Picker Institute, who will then pass these onto NHS Digital for list cleaning with the same output as previously provided. Patient objections will apply.

Following the process of the first run, the cohort (split into part A (3000) and part B (27,645)) will be list cleaned multiple times. The first clean will occur once the agreement is approved to allow preparation of the survey once the cleaned data is received. Then subsequent cleans will be performed as needed (3x per cohort) as follow up letters are sent to the men regarding their response.


Project 19 — DARS-NIC-148160-G7YGJ

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:2017.06 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

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

Objectives:

The data supplied by the NHS IC to Light will be used only for the approved Medical Research Project - UK Womens Health and Lifestyle Study


Project 20 — DARS-NIC-148098-9ZV2X

Opt outs honoured: N ()

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

Purposes: ()

Sensitive: Sensitive, and Non Sensitive

When:2016.04 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

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

Objectives:

The data supplied by the NHS IC to Institute of Cancer Research will be used only for the approved Medical Research Project identified above.

Expected Benefits:

To be completed by the applicant

Outputs:

To be completed by the applicant

Processing:

To be completed by applicant


Project 21 — DARS-NIC-148057-2763T

Opt outs honoured: Y, N ()

Legal basis: Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive, and Non Sensitive

When:2016.04 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

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

Objectives:

Background: In collaboration with the Paediatric Care Society, the Paediatric Intensive Care Audit Network (PICANet) was established in 2001 with funding from the Department of Health and Health commission Wales Specialised Services. This prospective clinical audit database of all admission to paediatric intensive care activity, casemix, structure and utilization which will facilitate the following:Identification of best practice;Monitoring of supply and demand;Monitoring and review of outcomes of treatment episodes;Strategic planning and resource requirements: and Study of the epidemiology of critical illness.
Aims1) to determine the longer term outcome of children admitted to and discharged alive from paediatric intensive care 2) to examine the cause of death in children admitted to paediatric intensive care while on the unit and following discharge.3)to determine the overall burden of mortality due to critical illness in children admitted to paediatric intensive care.4) to analyse all of the above in relation to deprivation, ethnic group and geographical location as a means of addressing health inequalities


Project 22 — DARS-NIC-04641-R3Y5V

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 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

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

Objectives:

The Clinical Trials Research Unit (CTRU) at the Leeds Institute of Clinical Trials Research (LICTR), University of Leeds, believe that the cardiology community requires an appropriately powered, randomised controlled trial of non-invasive ischaemia assessment (functional imaging) to determine diagnosis and patient management.

LICTR know that invasive angiography rates are already too high, and that they will increase further if the NICE guidelines (CG95) are followed. LICTR know that from a previous small single centre trial (CECaT), that using functional testing (Cardiac Magnetic Resonance Imaging (CMR), Single Photon Emission Computed Tomography (SPECT), stress echo) invasive angiography could be avoided in 20-25% of patients.

LICTR also know that patients rightly want to avoid unnecessary angiography if at all possible, but to date no clinical trial has tested the safety of this type of strategy in terms of clinical outcome.

LICTR propose the CE-MARC 2 trial, which would be a major advance from the simple and usually small diagnostic accuracy studies that are all too prevalent in the imaging literature. Having benchmarked the diagnostic performance of CMR and shown superiority against SPECT in the CE-MARC study, CTSU now propose to evaluate 3T CMR prospectively in a three-arm trial to assess whether a CMR-guided management strategy is superior to current best clinical practice (based upon either the principles of NICE CG95 or AHA SPECT appropriateness criteria.

This type of study would not previously have been acceptable to clinicians without the findings from CE-MARC defining its diagnostic performance.

It is of note that the widely used modality of SPECT has never been prospectively tested as CTSU propose here for CMR.

For the NHS, the objective of CE-MARC 2 is to provide robust evidence of:

a) Potential improvement in patient care/Health-Related Quality of Life (HRQOL)/outcomes;

b) A strategy by which to reduce unnecessary invasive angiography (by a true replacement test rather than an additional test in the diagnostic pathway);

c) Cost effectiveness of Cardiac Magnetic Resonance Imaging (CMR) in order to inform future NHS capital investment (as general Magnetic Resonance (MR) systems are replaced this study will help inform key capital purchase decisions on whether a 3T system is justified for cardiovascular work).

The purpose of CEMARC 2 is to understand the best method of managing patients with anginal chest pain. This will be quantified by measuring the number of unnecessary angiograms conducted in each arm of the trial.

In line with secondary objectives of the CEMARC 2 Trial, a comparison of safety across the three arms of the trial will be made by measuring cardiovascular events, including cardiovascular cause of death defined as;

• Fatal Myocardial Infarction
• Heart failure
• Acute Unexpected Death
• Stroke
• Pulmonary Embolism
• Cardiovascular Procedure-Related
• Other Cardiovascular
• Unknown

Comparison of safety relates to the long-term follow-up. The University of Leeds will use the events data to establish that MRI/SPECT strategies no not result in excess major cardiovascular events down the line due to missed coronary disease.

To summarise, the study will consider whether patients in MRI/SPECT arms either have less events than NICE patients, or that said events happen much later.

Expected Benefits:

The results of the CEMARC 2 clinical research trial are expected to inform the next update of NICE guideline CG95 (Chest pain of recent onset: assessment and diagnosis) and therefore have enormous potential to change NHS practice, but also to inform future NHS capital expenditure.

The research question is highly relevant to a large number of patients: what is the best initial test for patients coming to an outpatient clinic with chest pain that is suspected stable angina? It is well accepted that a variety of investigations may be used to diagnose Coronary Heart Disease and to determine the need for coronary revascularisation. Whilst the NICE guidelines (CG95) have provided a structured and evidence-based approach to the diagnosis of patients with chest pain, they are not without problems. Full adoption of the guidelines could lead to an increase in invasive angiography, when the University of Leeds know that the rate of unnecessary angiography is already high.

From the involvement of expert patient at the design stage of this study the University of Leeds know that unnecessary angiography is something patients are particularly keen to avoid.

The benefits to patients will be a reduction of unnecessary invasive angiography which would also constitute a cost saving to the NHS.

Outputs:

Previous analyses
The analysis of CE-MARC2 is being performed in a staged manner. The initial primary analysis began when the final patient reached one year’s follow-up, and analysed the primary endpoint (unnecessary angiography) as well as the safety data accrued so far (complications, positive angiography and major adverse cardiovascular events (MACE).

This primary analysis was completed in April 2016 with a manuscript submitted to JAMA that was subsequently published in September 2016. (JAMA. 2016;316(10):1051-1060. doi:10.1001/jama.2016.12680). The results were also presented at the European Society of Cardiology (ESC) 2016 Annual Congress in Rome on 29th August 2016. The summary of the findings was that CMR and SPECT patients saw a substantially lower rate of unnecessary angiography compare to those managed using a NICE Guidelines based management strategy, and – based on the minimum 12 months follow-up at the time – there was no significant difference in the subsequent rates of MACE.

Contemporary coverage of the results included a favourable review from Richard Lehman (BMJ) in a round-up of journal articles, noting that the CE-MARC2 trial “explicitly [set] patient importance above public health importance, though it ended up informing both.” (http://blogs.bmj.com/bmj/2016/09/19/richard-lehmans-journal-review-19-september-2016/) as well as an editorial from the British Cardiovascular Society calling on NICE to review and update guidelines for assessment of stable angina. (Aung, N.
Role of invasive angiography in suspected coronary artery disease: Results from the CE-MARC 2 Trial. BCS Editorial. 23rd September 2016. https://www.bcs.com/pages/news_full.asp?NewsID=19792516)

Further Analyses
The second analysis will be performed after all participants have completed 3 years in the study, which is in March 2018. ONS data is required to April 2018, when this is received an additional safety analysis will be completed at the end of this period. Analysis of this data will be performed along with the analysis of the 3 year Quality of Life data.
Timelines have yet to be confirmed for analysis completion and dissemination, however we are optimistic that these results publication can at least be submitted before the end of 2018.

Trial results will be more widely disseminated to patient and public groups and to the lay community. Should the latest analysis show that the intervention has an appropriate safety profile in relation to its demonstrated benefit of fewer unnecessary angiographies, the results will further inform NICE guidance and influence NHS practice in this area.
No outputs will ever identify any individual, organisation, nor include any record level data.

Processing:

The University of Leeds receive data for an identified cohort for the CEMARC 2 trial, for whom the University of Leeds provide identifiers already collected from participants as part of the trial dataset (and with their consent). These are: name, address, NHS number and date of birth. This ensures the University of Leeds minimise the chance of receiving data for anyone other than consenting trial participants. The University of Leeds need to receive identifiable data to ensure that the University of Leeds have data for the correct individuals and match this with the existing trial data set.

Data will be processed by the trial statisticians at the Clinical Trials Research Unit, Leeds Institute for Clinical Trials Research (LICTR) at the University of Leeds. All individuals with access to the data are employees of the University of Leeds.

It will be securely stored on CTRU systems with access only granted to the statistical team. Data will not be accessed by any third parties, nor will it be accessible across multiple organisations.

Data will be linked with existing CEMARC 2 Trial datasets (existing CEMARC2 Trial datasets consist of patient demographics and results from diagnostic tests, patients have given written informed consent to participate in the trial and the identifiers the University of Leeds are collected as part of the trial - data provided by participants and researchers in accordance with the REC-approved trial protocol and participant consent). The data will be used to determine safety endpoints in terms of cardiovascular event rates, which include cardiovascular cause of death as defined above.

Data will not be used for any other purposes: it will not be used for commercial purposes, nor for direct marketing purposes.

ONS Terms and conditions will be adhered to.

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


MR1172 - CE-MARC - Clinical Evaluation of Magnetic Resonance imaging in Coronary Heart Disease — DARS-NIC-147908-CPCPG

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: Non Sensitive, and Sensitive

When:DSA runs 2019-12-01 — 2020-09-30 2016.04 — 2016.11.

Access method: Ongoing, One-Off

Data-controller type: UNIVERSITY OF LEEDS

Sublicensing allowed: No

Datasets:

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

Objectives:

Primary aim: To assess the diagnostic accuracy of Cardiac Magnetic Resonance (CMR) in detecting coronary heart disease (CHD) compared to the current 'gold standard' X-Ray angiography.
Secondary objectives:
To assess the prognostic value of CMR in predicting long-term outcome.
To compare the diagnostic accuracy of CMR with the current standard clinical investigations of exercise tolerance testing (ETT) and radionuclide perfusion imaging (SPECT)
To evaluate the cost effectiveness of CMR in a diagnostic strategy for the systematic investigation of patients with suspected CHD.
To assess patient preference of the different strategies for investigation of suspected CHD.

Yielded Benefits:

Outputs:

No new or further data will be provided under this version of the agreement. A short term extension is in place as a pragmatic approach to enable legal retention of already disseminated data. This agreement allows retention of data, but not permission to otherwise process it.

These outputs will include an analysis of time until first major adverse cardiovascular event (MACE), and the incidence of at least one of these events, as well as the individual components: cardiac death, arrhythmia, myocardial infarction, heart failure, unplanned revascularisation, stroke/TIA, Acute Coronary Syndrome.

The CEMARC trial team will aim to submit these findings to a high impact general medical journal (e.g. New England Journal of Medicine, Lancet, Journal of the American Medical Association) in the first instance. Conference and scientific meeting presentations will follow, as was the case with earlier outputs (see 5d iii. Yielded benefits).

The outputs are aimed at the entire medical community, hence the trial team aim to publish in a general medical journal rather than a specialist cardiovascular publication. CEMARC have an excellent track record of achieving this with the main CEMARC papers having been published in the Lancet and Annals of Internal Medicine (see 5d iii. Yielded benefits).

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

Processing:

All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data). No new or further data will be provided under this version of the agreement.

A short term extension is in place as a pragmatic approach to enable legal retention of already disseminated data. This agreement allows retention of data, but not permission to otherwise process it.

The flow of identifiers, which have already been sent to NHS Digital under a previous version are as follows:
• Surname/Forename Name
• Address
• Date of birth
• Gender
• NHS Number
• Study ID – the number a participant is allocated when they enter the study.

Data will be downloaded from the NHS Digital link and the data file saved in a secure folder on the P-Drive by a named member of the study team. Data will be entered into a secure password protected database held locally at the Clinical Trials research Unit (CTRU) at the UoL, by a data management assistant who will transcribe the data onto a case report form (CRF). Data will then be entered into a secure password protected database held locally at the UoL by a trained member of the data management team.

A copy of this CRF will then be sent to Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) at the UoL, to be securely filed with their copy of the participant file and the original filed in a secure tambour with other trial documentation at the CTRU. This will be securely filed with their copy of the participant file. Any electronic scanned versions will then be deleted. The original CRF will be filed in a secure tambour with the participant study files that include CRFs and any correspondence over data cleaning at the CTRU.

The data will then be processed by the trial statistician at the Clinical Trials Research Unit, Leeds Institute for Clinical Trials Research (LICTR) at the UoL.

All individuals with access to the data are substantive employees of the UoL, data will only be accessed by individuals with the CTRU who are directly involved with the NHS digital transfer and analysis of the data (Trial statisticians and data management assistant).

The UoL is both the Data controller and the Data Processor. Originally, British Heart Foundation funded this study - British Heart Foundation are no longer involved and have no say in how and what data is processed. The 10-year follow-up of the CEMARC study is being funded by the Chief Investigator at UoL. The Investigator has no say in how and what data is processed.

Data will be linked with existing CEMARC Trial data sets, which consist of patient demographics and results from diagnostic tests. Patients have given written informed consent to participate in the trial and the identifiers the UoL are collected as part of the trial. Data provided by participants and researchers is in accordance with the REC-approved trial protocol and participant consent.

The datasets contain the following information:
Date of clinic visit
• Patient name
• Patient gender
• Date of birth
• Confirmation and date of written consent
• Confirmation of eligibility
• Hospital
• Name of Consultant cardiologist
• Name of randomising CRN/clinician
• NHS number
• Hospital ID
• Ethnicity
• Patient address and telephone number
• GP address and telephone number
• Blood pressure
• Heart rate
• Past medical history including previous cardiovascular problems, diabetes mellitus (Type-1 or Type-2) hypertension and family history
• Smoking history
• Height and weight
• Blood test results
• Research blood sample for biochemical markers
• All drug treatment prior to clinic attendance.
• All drug treatment after clinic attendance.
• Tests clinically planned to include exercise test, SPECT, coronary angiography.
• Initial clinic diagnosis

The following details from the CMR investigation data:
• Date of investigation (If investigation not carried out, reason).
• Scan parameters and timing of protocol stages.
• The heart’s response to adenosine. (Adenosine is used to increase the blood flow in the heart as if the participant has been exercising)
• Comparison of rest/ stress blood flow scans
• Volumes of blood in the heart prior to contraction of the heart and after contraction.
• Evidence of scar tissue.
• Coronary anatomy.
• Cardiovascular complications.
• Exercise Tolerance Test (ETT) investigation data (using an exercise treadmill/bike testing): The CEMARC Clinicial Research Nurse (CRN) will record the following details from the ETT:
1. Date of investigation (If investigation not carried out, reason)
2. Heart rate prior to exercise and after,
3. Blood pressure
4. workload (Metabolic equivalents (METS) this represents the intensity of the exercise),
5. Exercise duration,
6. Any symptoms experienced during the tests,
7. Degree of ST segment shift which can indicate whether the participant has any heart disease,
8. Any irregular heartbeat (arrhythmia).

SPECT investigation data. A Cardiologist will record the following details from the SPECT:
• Date of investigation (If investigation not carried out, reason)
• Response to adenosine.
• Comparison of rest/ stress blood flow-scan
• Cardiovascular complications

A Cardiologist will record the following details from the x-ray angiography investigation data:
• Date of investigation (If investigation not carried out, reason)
• Narrowing in each of the main coronary arteries (blood vessels which transport oxygen to the heart).
• Coronary artery dominance- this has important implications in the imaging of the coronary arteries and any planning for coronary artery bypass grafting
• Any abnormalities to the walls or pumping action of the heart.
• Cardiovascular Complications.

Details of any serious adverse events relating to the investigations were reported to and recorded by the CEMARC CRN or CEMARC Research Fellow. Serious Adverse Events (SAE) and Serious Adverse Reactions (SAR) are defined as an untoward (unfavourable) event or reaction, which is fatal or life-threatening, requires or prolongs hospitalisation, is significantly or permanently disabling or incapacitating, or may jeopardise the patient and may require medical or surgical intervention to prevent a major cardiovascular event. The following details will be provided by the CEMARC CRN or CEMARC Research Fellow:
• Full details in medical terms with a diagnosis, if possible
• Duration (start and end dates; times, if applicable)
• Action taken
• Outcome

The data will be used to determine safety endpoints in terms of cardiovascular event rates, which include cardiovascular cause of death.

Data will not be used for any other purposes: it will not be used for commercial purposes, nor for direct marketing purposes. Data will not be accessed by any third parties, nor will it be accessible across multiple organisations.

Aside from the main CEMARC trial data sets – arising from the CEMARC trial described above (along with the consent provided) the data will not be linked with any other data sets (publicly-available or otherwise), and so this data will not be used to perform any kind of “trend analysis”. There will also be no bench marking against peer groups. The sole purpose of the data is to determine the safety endpoints for the trial, as described above.

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

There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.

Data will only be accessed and processed by substantive employees of UoL and will not be accessed or processed by any other third parties not mentioned in this agreement.

Any Research Fellows and Cardiologists are employed by the NHS sites, their roles on the study are to interpret and collect data from participants’ s investigation and to transcribe onto paper CRFs and to send to the CTRU for data entry. Research Fellows will not have any access to NHS Digital data or to the secure locked tambours where the paper CRFs are kept.