NHS Digital Data Release Register - reformatted

University of Leeds

🚩 University of Leeds received 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 datasets, but the identifiers are consistent between datasets for the same recipient, and NHS Digital does not know what their recipients actually do.

Project 1 — DARS-NIC-77953-C4M3T

Opt outs honoured: Yes - patient objections upheld (Does not include the flow of confidential data)

Sensitive: Sensitive, and Non Sensitive

When: 2018/10 — 2019/11.

Repeats: One-Off

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

Categories: Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Accident and Emergency
  • 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.


Project 2 — DARS-NIC-49164-R3G5K

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2017/09 — 2017/11.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • 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).


Project 3 — DARS-NIC-40493-G5Y6K

Opt outs honoured: N

Sensitive: Non Sensitive, and Sensitive

When: 2017/12 — 2018/02.

Repeats: One-Off

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

Categories: Identifiable

Datasets:

  • Hospital Episode Statistics Critical Care
  • Hospital Episode Statistics Accident and Emergency
  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Outpatients
  • Bridge file: Hospital Episode Statistics to Mortality Data from the Office of National Statistics
  • Office for National Statistics Mortality Data

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.

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).


Project 4 — DARS-NIC-378523-Y5Q9L

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2017/09 — 2017/11.

Repeats: One-Off

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

Categories: Identifiable

Datasets:

  • Hospital Episode Statistics Admitted Patient Care
  • 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.


Project 5 — DARS-NIC-367152-K6Y1D

Opt outs honoured: Y, N

Sensitive: Non Sensitive

When: 2016/04 (or before) — 2018/02.

Repeats: Ongoing

Legal basis: Section 251 approval is in place for the flow of identifiable data

Categories: Identifiable

Datasets:

  • MRIS - List Cleaning Report
  • 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.

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.

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 finaldata 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.

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.


Project 6 — DARS-NIC-325074-F0J3D

Opt outs honoured: N

Sensitive: Sensitive, and Non Sensitive

When: 2017/03 — 2017/05.

Repeats: One-Off

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

Categories: Identifiable, Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Accident and Emergency
  • Mental Health Minimum Data Set
  • Mental Health and Learning Disabilities Data Set

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.

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.


Project 7 — DARS-NIC-17649-G0X4B

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2017/03 — 2017/05.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • 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 8 — DARS-NIC-155843-0MQMK

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2017/06 — 2017/08.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Admitted Patient Care

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.

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.


Project 9 — DARS-NIC-148160-G7YGJ

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/04 (or before) — 2018/02.

Repeats: Ongoing

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

Categories: Identifiable

Datasets:

  • MRIS - Cause of Death Report
  • MRIS - Cohort Event Notification Report
  • MRIS - Scottish NHS / Registration

Objectives:

The data supplied by NHS IC to LIGHT will be used only for the approved Medical Research Project identified above.


Project 10 — DARS-NIC-148098-9ZV2X

Opt outs honoured: N

Sensitive: Sensitive, and Non Sensitive

When: 2016/04 (or before) — 2017/02.

Repeats: Ongoing

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

Categories: Identifiable

Datasets:

  • MRIS - Cause of Death Report
  • MRIS - Cohort Event Notification Report
  • 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 11 — DARS-NIC-148057-2763T

Opt outs honoured: Y, N

Sensitive: Sensitive, and Non Sensitive

When: 2016/04 (or before) — 2017/02.

Repeats: Ongoing

Legal basis: Section 251 approval is in place for the flow of identifiable data

Categories: Identifiable

Datasets:

  • MRIS - Cause of Death Report
  • MRIS - Cohort Event Notification Report
  • 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 12 — DARS-NIC-147908-CPCPG

Opt outs honoured: N

Sensitive: Non Sensitive, and Sensitive

When: 2016/04 (or before) — 2016/11.

Repeats: Ongoing

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

Categories: Identifiable

Datasets:

  • MRIS - Cohort Event Notification Report
  • MRIS - Cause of Death 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.


Project 13 — DARS-NIC-11809-H1Y3W

Opt outs honoured: Y

Sensitive: Sensitive, and Non Sensitive

When: 2016/04 (or before) — 2017/11.

Repeats: One-Off, Ongoing

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012

Categories: Identifiable, Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Accident and Emergency
  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Outpatients
  • Mental Health and Learning Disabilities Data Set
  • Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set

Objectives:

The University of Leeds (“the University”) requires approval for data processing to continue its epidemiology and health services research programme evaluating pathways and time to diagnosis for children and young adults diagnosed with cancer under the age of 30, and to calculate the risks and costs to the NHS of adverse health events requiring hospital admission for survivors of cancer in this age group. Work will exploit existing cancer registry data held by the Yorkshire Specialist Register of Cancer in Children and Young People (YSRCCYP) together with linked HSCIC data. HSCICS data are therefore vital in order to provide a comprehensive picture of NHS activity preceding, during and following diagnosis and treatment of children and young people’s their cancer. The purpose of the YSRCCYP research database is to facilitate population-based epidemiological research This type of research has the potential to benefit future patients by identifying important environmental risk factors, examining 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. Identifiable data are necessary for a number of reasons: (1) So that the University can undertake accurate spatial analyses such as space-time clustering at a sufficiently high resolution (OA level) so that raised cancer risks can be precisely measured in relation to putative environmental exposures such as benzene levels from car exhausts and other specific sources of pollution such as petro-chemical factories, incinerators etc. (2) Consultant codes enable the University of Leeds to work out whether patients receive care at specialist cancer centers 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 in existence which link consultants to specialist cancer centers for childhood and young adult cancer, so this process needs to be done manually using linked HSCIC data and the YSRCCYP database. (3) The local patient identifier field is required to enable accurate validation of cancer registration data through linkage to records held on the Patient Pathway Manager (PPM) system at Leeds Teaching Hospitals NHS Trust (LTHT) . Validation is undertaken to ensure no eligible cancer patients are excluded from the YSRCCYP by looking at the number of un-linked records from PPM and to ensure that treatment information is complete and up-to-date. Some of these records pre-date the introduction of NHS number and therefore the University requires an alternative unique identifier to be used in place of NHS number. Note none of the LTHT (PPM) datasets will be linked to HSCIC data; these data are provided in order for the University to confirm and validate the correct cancer diagnosis, date of diagnosis, address/postcode and treatment is recorded i.e. core cancer registration data which the University and YSRCCYP are entitled to process under their current CAG approval (CAG 1-07(b)/2014). These and other identifiers are retained on the YSRCCYP database and their use will be restricted to this project to ensure that any retrospective data validation exercises, e.g. with the National Cancer Registration Service can be carried out effectively and in a timely manner, particularly as hospital provider codes, hospital unit numbers and NHS numbers etc. may themselves change over time. One previous specific example was a recent study in which the University was invited to collaborate with colleagues at Newcastle University on a retrospective observational study to determine factors associated with length of survival following neuroblastoma relapse for children diagnosed since 1990. This study devised and tested an information package for parents on the epidemiology of relapsed neuroblastoma and parental information needs, to better inform clinicians and parents of children with relapsed neuroblastoma when making treatment decisions in these difficult circumstances, in order to benefit future patients. This important research would not have been possible if the University had lost the right to retain identifiable information as the University was able to exploit the availability of detailed electronic information on treatment, diagnosis, and other molecular pathology over time available from the YSRCCYP. Patient benefit would therefore have been severely compromised if the University failed to retain this crucial information.

Expected Benefits:

The linked HSCIC data will be used to derive key information which will be provided by the University 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 motality, 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 (March 2017). 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 (May 2017). 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 pediatric 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 March 2017. 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. 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. 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. At the moment, these data are lacking and once identified by the University 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 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 pediatric and adolescent oncologists throughout the Yorkshire region. The research programme as a whole benefits enormously from the long-running, close collaboration with hematologists and oncologists in the Yorkshire and the Humber region who all help to ensure that our 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 December 2016. Outcomes of the work will also be disseminated in open-access journals (e.g. BMC Cancer) and presented at conferences including the National Cancer Intelligence Network 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 April 2017. Analyses describing the variation in clinical pathways including delays and time to diagnosis will be submitted for publication by June 2017 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 March 2017. 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. Data will be held for as long as the research project is funded to undertake this piece of epidemiological and applied health research. Funding currently expires on 31st August 2017; therefore the planned data retention period runs initially until 31 December 2017 to make sufficient arrangements for data deletion. Individual level HSCIC data will not be onwardly disclosed in any form of output. Only aggregated data with small numbers suppressed may be disclosed in publications, e.g. peer review journals and reports.

Processing:

The linked HSCIC data will initially be cleaned to ensure no duplicate episodes remain, no multiple admissions less than 2 days apart with the same HSCIC_ID exist, and no admission entries occur after the date of death (if deceased). Length of hospital stay will then be calculated from the dates of admission and discharge and compared between diagnostic groups, age groups, gender, ethnic group, socioeconomic status, level of specialist care, and distance from residential address to hospital (another reason why the University needs OA code and grid reference). Rates of admission within the cancer survivors will be compared to aggregated hospital admission rates to work out standardised hospitalization admission ratios and assess whether these differ according to cancer diagnosis, treatment, ethnic group, gender, age group, period of diagnosis and socioeconomic status. Data will be processed and stored according to the data security policy in operation at the University. All linked HSCIC data are stored on an encrypted secure area network (SEED) and access is restricted to individuals working on the YSRCCYP register research project, all of whom are employees of the University of Leeds. Data will only be used for the purpose described in this statement. These HSCIC data will not be linked to any primary care data.


Project 14 — DARS-NIC-112910-R4X9X

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

Sensitive: Non Sensitive, and Sensitive

When: 2019/06 — 2019/06.

Repeats: One-Off

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

Categories: Identifiable

Datasets:

  • Hospital Episode Statistics Admitted Patient Care
  • Civil Registration - Deaths
  • HES:Civil Registration (Deaths) bridge

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).


Project 15 — DARS-NIC-109867-M8S6B

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

Sensitive: Sensitive, and Non Sensitive

When: 2019/10 — 2019/10.

Repeats: One-Off

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

Categories: Identifiable

Datasets:

  • Civil Registration - Deaths
  • Hospital Episode Statistics Outpatients
  • Hospital Episode Statistics Admitted Patient Care

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).


Project 16 — DARS-NIC-04641-R3Y5V

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/12 — 2018/05.

Repeats: Ongoing

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

Categories: Identifiable

Datasets:

  • MRIS - Flagging Current Status Report
  • MRIS - Cause of Death Report
  • MRIS - Cohort Event Notification 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:

The primary analysis will be complete by April 2016 with a planned manuscript submission July 2016. The dates for manuscript submission and ESC 2016 presentation are correct, but the final analysis won’t be complete by April. It is being done in a staged approach. The University of Leeds will have enough analyses to submit abstract by end April 2016, enough for the manuscript by July 2016, and the rest by the time of presentation. The manuscript will include initial safety data (1 year follow up). Results will be disseminated through manuscript submissions to relevant peer reviewed journals. It is not possible to confirm the name of a journal until the manuscript has been accepted. As the study’s forerunner, CEMARC, was published in The Lancet, the University of Leeds expect to again publish in a 4 star journal with the New England Journal of Medicine being the target journal for submission for CE-MARC2. The planned follow-up period for the study is 3 years (will require on-going ONS data for the entire follow-up period) and an additional safety analysis will be completed at the end of this period. The data will also be presented at the European Society of Cardiology annual meeting (August 2016). ESC 2016 will be presentation of the primary and secondary endpoint analyses. Whatever follow-up data the University of Leeds have at that point will be considered for inclusion (should have 1 year’s data for most patients, at least). Trial results will be more widely disseminated to patient and public groups and to the lay community. Should the trial show that the intervention is effective, the results will ultimately 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.