Centre for Health Economics, University of York, Programme Level Agreement

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: + Civil Registrations of Death; + Diagnostic Imaging Data Set (DID); + Medicines dispensed in Primary Care (NHSBSA data); + NDRS Cancer Consolidated Data Set

Objective for processing

[1 paragraph unchanged] “Centre for Health Economics, University of York, Programme Level Agreement” York” The following is a summary of the aims of the research programme provided by by, or on behalf of of, the CHE: Centre for Health Economics (CHE): The Centre for Health Economics Economics(CHE) is a research department of the University of York, dedicated to the [46 words unchanged] and Wellbeing; Justice and Equality; Risk, Evidence and Decision Making; and Technologies of for the Future. CHE Centre for Health Economics(CHE) produces policy relevant policy-relevant research and innovative methods that advance the use of health economics to improve population health. As the NHS continues to grapple with financial pressures, pressures and the short and long-term impacts of the COVID-19 pandemic, research carried out in CHE Centre for Health Economics(CHE) aims to support decisions about where and how increasingly limited budgets are spent. CHE Centre for Health Economics(CHE) works closely with decision-makers at international, national and local levels to ensure that research is addressing their needs and priorities. CHE’s Centre for Health Economics(CHE)’s research (http://www.york.ac.uk/che/research/) using NHS England data is organised into six priority areas (research themes): 1) Economic Evaluation and Health Technology Assessment 2) Health and Social Care Policy 3) Equity in health and health care 4) Health and social care 4) Methods [2 paragraphs unchanged] CHE's priority research areas are reviewed by the CHE Executive and the Departmental Research Committee every three years, as part of the Research Strategy (last (next review 2022). October 2026). Projects or programmes of work are broadly aligned to a priority area, with cross-cutting research across these. For example, Economic Evaluation cuts across a number of themes, including Health and Social Care, Public Health, and Equity in health and health care; and Health Policy includes research in Health and Social Care, and Mental Health. Each priority area is led by a senior researcher, typically a Professor or Reader (Associate Professor), academic member of staff, who are is substantively employed by the University of York - Centre for Health Economics. at the Centre. Case studies highlighting cross-cutting research: NHS England Data can be used for the following purposes: - Allocating resources in the NHS (https://www.york.ac.uk/research/impact/allocating- resources-in-the-nhs/); - Research within CHE’s six strategic themes. - Deciding which health and care treatments should be nationally funded (https://www.york.ac.uk/research/impact/funded-treatment-decisions/); - Scoping analyses to assess feasibility of future projects. - How productive is the NHS? (https://www.york.ac.uk/research/impact/how-productive-is- the-nhs/) - Responsive analyses commissioned by policy bodies (e.g., DHSC). The research undertaken using NHS England data informs health and social care policy and practice by identifying the effectiveness, efficiency, distribution, and quality of a wide range of services provided to the population. It produces insights that allow the maximisation of health gain and other measures of benefit from limited healthcare budgets, along with information on how health and health care is/can be distributed equally to meet the health needs of varying demographics. NHS England data potentially provides a view of health care utilisation for CHE to understand how effective delivery of care is distributed both nationally and locally, contributing to the delivery of new healthcare policy aimed at improving the quality of care. - Evaluations of health interventions, policy impacts, health inequalities, healthcare performance, and public health strategies RATIONALE FOR STRATEGIC PRIORITIES AND PROGRAMMES NHS England data cannot be used for commercial purposes. If a research project submitted to the DARG has a commercial benefit, it would require a separate data application to NHS England. 1. Economic Evaluation and Health Technology Assessment: The Data Access Request Group (DARG) provides oversight of all requests to access NHS England data in the Centre for Health Economics (CHE). As a companion group of the CHE Data Governance Group (DGG), the DARG manages and reviews procedures and criteria for accessing NHS England data, and is responsible for the assessment and decision making on requests for access to these data. The DARG Terms of Reference outline the purpose and scope of the group, membership and accountability, and agreed processes. Economic Evaluation and Health Technology Assessment focuses on research and training relating to the economic evaluation of health care programmes and interventions. CHE undertakes a range of methodological research in economic evaluation, and the design, conduct and analysis of applied economic evaluations. These include integrated economic and clinical randomised trials, decision analytic modelling studies and economic and statistical evaluation of observational and retrospective data sets. Additionally, CHE conducts economic evaluation in a number of cross-cutting themes, primarily: social care, public health, and global health. The DARG considers requests for access to data on the basis of the following criteria: Programmes of work include: - NICE Technology Assessment Reviews; - Policy Research Unit in Economic Evaluation of Health and Care Interventions (EEPRU, http://www.eepru.org.uk/); - Supporting local decision makers (ARC-YH, https://www.arc-yh.nihr.ac.uk/); - Health opportunity costs; - Elicitation: capturing the uncertain beliefs of clinical experts in a quantitative form to use in further analysis using evidence synthesis (a process to combine evidence from multiple sources using appropriate statistical techniques); - Personalised medicine; - Research prioritisation. 2. Health Policy: Health Policy undertakes applied and methodological economics research to critically appraise and evaluate organisational and incentive structures of the healthcare system. This covers the behaviour and performance of organisations and individuals within the healthcare system. Programmes of work include: - Contracting and reimbursement; - Efficiency and Productivity; - Workforce; - Integrated Health & Social care; - Measuring health & quality of care; - Organisation and structure of health systems; - NIHR Policy Research Unit in Economics of Health Systems and Interface with Social Care (ESHCRU, https://eshcru.com/). 3. Equity in health and health care : There are substantial inequalities in health and health care outcomes between more and less socially disadvantaged people, which raise important concerns about quality of care and justice. CHE’s work in this area includes not only studies that aim to describe and understand such health inequalities, but also studies that aim to provide decision makers with information about the impacts of their decisions on health inequalities, such as distributional cost-effectiveness analysis, health equity measurement and monitoring for health care quality improvement, and quasi-experimental evaluation of policy impacts on health inequalities. Programmes of work include: - Distributional cost-effectiveness analysis (DCEA); - NHS equity indicators; econometric methods and policy evaluation; - The equity impacts of hospital competition; - Inequality in waiting times; - Primary care workforce distribution; - Deliberative process for addressing equity concerns; - Public preferences for reducing health inequality. 4. Health and social care: Economic constraints on public sector budgets and improvements in care generally mean that people are living longer and there is an increased need for research on how best to allocate resources and deliver services that are efficient, equitable and offer good value for money. Programmes of work include: - ESHCRU (https://eshcru.com/) - EEPRU (http://www.eepru.org.uk/) CHE’s research on social care is developed under the programmes of these two Policy Research Units, both funded by the National Institute for Health Research (NIHR) on behalf of the Department of Health and Social Care. The NIHR School for Social Care Research (SSCR) is also a core funder of CHE’s economic evaluations of social care interventions. 5. Mental Health: Mental health problems are the largest single cause of disability in the UK, representing a quarter of the national burden of ill-health, and are the leading cause of sickness absence. Programmes of work in the area of mental health economics and policy include: - Socio-economic determinants of mental illness; the nature of the treatment and the quality of care received by people with mental illness; - Health inequalities in treatment rates; - Mental health outcomes; - The economic evaluation of mental health interventions and services; - The organisation and funding of mental health services; - The performance of mental health providers. 6. Public Health: Public health services play a vital role in preventing ill health and reducing health inequalities. The Office for Health Improvement and Disparities launched in October 2021 with the intent to coordinate public health activities across central and local government, the NHS and wider society. CHEs research on public health is a cross-cutting research theme. Programmes of work include: - Socioeconomic determinants of health, health behaviour and health inequalities; - Economic consequences of health and health inequalities; - Economic evaluation of public health interventions; - Evaluation of public health interventions through econometric methods and microsimulation (an alternative method which involves simulating the impacts of hypothetical and/or new programmes or forecasting the impacts of existing programmes in new contexts and over time); - Local health and care research partnerships; - Resource allocation and health inequalities; - Commissioning public health services. The methods for use of HES data and other NHS England datasets will vary from project to project, with data analysed in different ways and employing a variety of statistical methods. However, there are a number of common ways in which the data is used. This Agreement permits use of the data for the following: • Assessing data quality, completeness, relevance and volume of data prior to and during undertaking research analysis • Measurement of efficiency, effectiveness, and productivity of health and social care systems nationally, subnationally, and at the organisational level, e.g. health and social care providers, integrated care systems, public health providers etc. • Evaluation of differences in the performance of health care providers in terms of the amount, cost and quality of provision and in patient outcomes including mortality and self-reported morbidity • Evaluation of the impacts of health care policy, organisation, finance and delivery of NHS services and public health services and quantification of differences in health care utilisation, expenditure, morbidity and mortality over time, across geographic regions, health and social care providers, and among different patient groups • Investigation of the level of and inequalities in access, outcomes, and costs of health services in England • Evaluation of the interface between the different sectors and different organisations of the healthcare system, including the effects of quality and access of primary care on patient use and outcomes in secondary care; and the relationship between public health services, long term care, social care and secondary care utilisation • Evaluation of the impact of the COVID-19 pandemic on the demand for services, and healthcare utilisation • Evaluating the NHS budgetary impacts, resource use implications and morbidity and mortality effects of specific health care interventions, including screening, diagnosis, management and treatment to inform economic evaluation • Exploring and evaluating patterns of comorbidity, pathways of care, health and social care use and cost, and health and care outcomes of specific populations to inform economic evaluation and decision analytic models • Evaluating the impact of specific health service interventions on healthcare resource use, morbidity, survival and risk of further illness, to inform economic evaluation and decision models • Evaluating the size and characteristics of populations impacted by specified health policies in order to estimate the level of burden and population distribution of costs and outcomes; • Assessing changes over time in access, public health services, healthcare delivery and utilisation, diagnoses, treatment and patient characteristics to support evaluation of health policy impacts • Evaluating changes in NHS expenditure, programme budget categories and resource use over time alongside impacts on morbidity and mortality to estimate the marginal productivity of the NHS. PROJECT SCOPING AND RESPONSIVE ANALYSIS CHE are implementing a new strategy to assess the viability of new projects. Across many of CHE’s strategic research priorities, analyses may be undertaken of NHS England data for scoping research and responsive analyses, as described below. Scoping analysis: When a new project idea or research question is conceived, it may be both beneficial and necessary to use NHS England datasets to carry out preliminary analysis prior to the submission of a research funding application. Such scoping analyses would support researchers in testing their proposed research questions to confirm feasibility, and allow researchers to generate relevant, accurate and high quality proposals with the confidence that the data can be used to generate the desired outcome and impact. During scoping analysis, researchers may undertake the following types of assessment: - Test whether key outcomes of interest are numerous enough. - Check whether coding is consistent across organisations and geographic areas, and over time. - Determine whether particular statistical methods would be appropriate for the questions being asked. - Test whether CHE research would have the necessary statistical power to be able to make high quality conclusions. - Assess the minimum level of data required for the purpose. Scoping analysis is approved by the Data Access Request Group (DARG). Requests for scoping analysis are submitted by the individual(s) within a project team, and a record of requests and outcomes is kept in a register maintained by DARG. The request captures the aim of the scoping, data set(s) required, data fields and years necessary; and the approval date and person, outcome of scoping exercise, and status of data is recorded on the register. It also confirms that other sources of data have been considered prior to this request. Where the outcome of the scoping exercise is to proceed with a research funding application, the working dataset used for the scoping exercise will be kept, pending the outcome of the funding application. If the individual(s) conclude that the project is not feasible, or the funding application is unsuccessful, the working dataset used will be erased. No member of staff will ever make copies of full NHS England datasets. Responsive analysis: The University of York - Centre for Health Economics holds several NIHR Policy Research Programme contracts. Some of these, such as the contracts for the Policy Research Units, include a requirement to undertake rapid response research. The aim of this responsive facility is to meet emerging needs of policy makers at the Department of Health and Social Care (DHSC) or its arm’s length bodies (e.g. NHS England). The evidence can be commissioned at short notice, and the nature of the requests depends on the issues and challenges facing the Department as priorities and policy evolve and develop. For example, the study team may be asked to provide evidence quickly in response to Parliamentary Questions; changes in priorities in the health or care system may lead to requests for a short piece of analysis to inform new policies; or evidence to support pressing analytical needs within the Department may be requested. These responsive requests are additional to the core, planned work undertaken under the auspices of the same contracts. Whilst the topic of some requests may fall within the broad priority areas outlined above, this cannot be guaranteed. Therefore, University of York wish to include an additional ‘responsive analysis’ purpose to ensure University of York have the necessary permissions in place to ensure the study team can respond to DHSC rapid requests in line with University of York's contractual requirements. HOW DECISIONS ARE MADE ABOUT PROJECTS AND USE OF NHS ENGLAND DATASETS This Agreement permits CHE to use the data for the purposes of projects undertaken within the work programmes described above, and which are conceived, planned, approved and initiated through the following process: New projects are conceived in a collaborative process, drawing on the relevant specialisms and experience of researchers across the research themes. Research questions are developed, and appropriate potential funding opportunities are identified - i.e. internal sources (University of York/ Centre for Health Economics) or an external funding organisation (e.g. National Institute for Health and Care Research (NIHR), Medical Research Council (MRC), Economic and Social Research Council (ESRC), Department of Health and Social Care (DHSC), etc). Complying with the relevant funder’s requirements and application processes, the research team, led by the principal investigator, will ensure that: • The project has a clearly defined objective that meets the scope and eligibility criteria of the funding call • A detailed research plan is prepared, including data requirements, methods, project management, dissemination, outputs, anticipated impact and a project timetable • The use of NHS England datasets is necessary to fulfil the aims and objectives of the project, and that use is proportionate,. This includes taking consideration of data minimisation, NHS England datasets requested, years requested, size of cohorts, and exclusion criteria applied. All staff and postgraduate students are provided with information and support on Data Protection Impact Assessments (DPIAs) and are provided with screening questions to determine whether a DPIA should be undertaken. The Principal Investigator (PI) will determine whether a DPIA is required; and will seek guidance from the CHE Data Governance Group, or the University Data Protection Officer, where necessary. An internal review of each funding proposal takes place, by two senior members of staff appointed by the CHE Department Research Committee Chair and Deputy Chairs. The purpose of this review is to: provide independent advice and guidance for principal investigators; ensure that all proposals being made in CHEs name meet CHEs quality standards, fit the research mission and maintain CHEs reputation; and ensure that the resources that are being requested are adequate to deliver the work. Upon completion of the review, the finalised proposal will be submitted to the funding body, and will undergo panel review (internal funding) or peer review (external funding). A project ‘kick-off’ meeting is held to make all members of the team working on the project aware of its key features and planned pathway to completion, including key deadlines, required outputs, etc. The CHE principal investigator, and the research team, will be bound by the research plan, and committed to achieving the agreed deliverables of the project, and in line with the terms and conditions of the funder. The following steps are required to apply for access to NHS England data: 1. Completion of ‘CHE Data Access Request Form - NHS England Data’ by researcher 2. Review of application by Data Access Request Group (DARG) 3. Centre for Health Economics: NHS England Data Access Register (internal and public facing) updated The Data Access Request Group (DARG) provides oversight of all requests to access NHS England data in the Centre for Health Economics (CHE). As a companion group of the CHE Data Governance Group (DGG), the DARG will manage and review procedures and criteria for accessing NHS England data, and be responsible for the assessment and decision making on requests for access to these data. DARG consider requests for access to data on the basis of the following criteria: [9 paragraphs unchanged] The Programme Level Agreement does not permit use of NHS England data for commercial purposes. If a research project submitted to the DARG has a commercial benefit, it would require a separate data application to NHS England. The following steps are required to apply for access to NHS England data: The DARG will meet monthly and will maintain a register of applications and decisions made. This will be publicly available on the CHE website for the benefit of participants and other researchers, and will include a lay summary of successful applications. 1. Completion of ‘CHE Data Access Request Form - NHS England Data’ by researcher EXAMPLES OF PROJECTS: 2. Review of application by Data Access Request Group (DARG) 1. Project title: Efficiency, cost and quality of mental health care provision 3. Updates to the Centre for Health Economics: NHS England Data Access Register (internal and public facing) CHE Programme: Mental Health CHE maintains a public register of all approved data access requests. The register includes lay summaries of successful applications. This ensures transparency and supports NHS England’s oversight responsibilities Overview: This project looked at the efficiency, cost and quality of current mental health care provision, and how changes can be made to drive efficiency improvements. The team assessed which quality indicators are valued by service users and clinicians. These included aspects such as improvements in outcomes, better and more equitable access to care, and distance to providers. Quality adjusted life year (QALY) weightings were developed for each of these indicators in order to assess efficiency, using a QALY framework. These data were used to produce a cost-effectiveness plane for mental health trusts, to enable the team to identify high-quality, low-cost providers, and to further examine organisational factors associated with cost effectiveness. This information informed estimates of how resources can be reallocated to be more cost effective, and what input-mix (eg capital, labour) might be associated with improved cost effectiveness. Any analysis undertaken needs to meet the aims within one of these six priority areas (research themes) Data minimisation approach: The work used HES APC 2014/15- 2019/20; HES APC 2020/21 monthly data to and including September 2021; MHMDS 2013/14, MHLDS 2014/15-2015/16. 1.Economic Evaluation Duration: 2017 - 2021 Aim: To assess the cost-effectiveness of health care programmes and interventions. Funder: Health Foundation. Ref. 57151 Objectives: Conduct methodological and applied economic evaluations. Support decision-making through trials, modelling, and analysis. Evaluate interventions in social care, public health, and global health. Inform NICE assessments and local decision-makers. 2. Project title: Partnership for Responsive Policy Analysis and Research (PREPARE) CHE Programme: Health Policy Programmes of work include: Overview: This project is exploring the links between child health and child poverty, in particular the NHS hospital utilisation of children born into deprivation (using the indices of - NICE Technology Assessment Reviews; deprivation (ID) as a proxy for poverty) in comparison with children who are not born in deprived areas. The study also explores whether any difference in hospital utilisation over the early life course has changed over time. To do this the project is creating a birth cohort of children born in NHS hospitals in England in specific financial years (2000, 2005, 2010, 2015, 2018), and is tracking their use of NHS services (inpatient, outpatient and A&E) over their life course (up to age 18 for those born in 2000). The analysts will then test whether the age-sex adjusted differential use of hospital services across children born into rich and poor neighbourhoods has changed over time. - Policy Research Unit in Economic Evaluation of Health and Care Interventions (EEPRU, http://www.eepru.org.uk/); Data minimisation approach: The work will use only HES APC 2000/01-2020/21; HES A&E 2007/08 - 2018/19; HES OP 2002/03-2020/21; Emergency Care Dataset 2017/18-2020/21. Duration: April 2020 - March 2025 - Supporting local decision makers (Applied Research Collaboration Yorkshire and Humber - ARC-YH, https://www.arc-yh.nihr.ac.uk/); Funder: NIHR Policy Research Programme. NIHR 200702. Health opportunity costs; 3. Project title: Analysis of purchaser-provider contracts: modelling risk sharing and incentive implications. - Elicitation: capturing the uncertain beliefs of clinical experts in a quantitative form to use in further analysis using evidence synthesis (a process to combine evidence from multiple sources using appropriate statistical techniques); CHE Programme: Health and social care: ESHCRU - Personalised medicine; Overview: The previous consensus regarding the development of contract arrangements (towards more fixed price, Payment by Results, National Tariff contracts) was subject to critical review (NHS England and NHS Improvement joint pricing team, 2019). Different arrangements are being developed for emergency and elective acute care, mental health services and a variety of ‘locally priced’ services (NHS England and NHS Improvement, 2019). The reformed financing would use a blended payment mechanism consisting of a two-part tariff, which comprises a fixed sum with payment either reduced or increased at a given fixed rate for treatments above or below a given threshold. This project develops a theoretical and empirical investigation of the impact of blended payment on emergency care provision. The overall aim is to provide relevant theoretical and empirical insight into the trade-offs, risks and benefits of different forms of contract on the provision of emergency care. - Research prioritisation. Output 1 investigates the variation of providers’ optimal proportion of patient to admit from an A&E attendance to major A&E Department. 2. Health and Social Care Policy Output 2 analyses the variation on number of A&E attendances to major A&E department across the purchasers of emergency services (Clinical Commissioning Groups). Aim: To improve the efficiency, equity, and value of health and social care delivery. Output 3 combines the estimates of Output 1 and 2 to examine how purchasers’ efforts to decrease A&E attendances to Major A&E Departments influence the providers proportion of patients admit from the same departments. Objectives: Design and evaluate organisational and incentive structures. Analyse performance of health and social care systems. Study contracting, reimbursement, productivity, and workforce issues. Support integrated care and health system reforms. Output 4 analyses the variation of providers’ optimal proportion of psychosis patients to from the different referral sources. Programmes of work include: The primary data source was the 2018/19 individual patient level A&E Hospital Episode Statistics (HES) data which was combined with General Practice (GP) level characteristics for the analysis in Outputs 1-3. For Output 4, the Mental Health Services Data Set (MHSDS) was used. - Contracting and reimbursement; Note this is not an exhaustive list. - Efficiency and Productivity; Data minimisation approach: The primary data source was the 2018/19 individual patient level A&E Hospital Episode Statistics (HES) data. Only individual level data essential to the Output 1 analysis is kept, as gender, age and ethnicity. The patients’ GP practice code recorded on the HES episode is used to attribute to each patient their GP practice characteristics (e.g. clinical quality, number of GPs, extended access offer) and the patients’ residence (LSOA) to attribute to each patient the distance to the AED and their area of residence characteristics (e.g. Index of Multiple Deprivation). In Output 2, the total number of A&E Major Department attendances at GP practice level was used. The study team collected the set of GP practice characteristics, e.g. patient list demographic and disease prevalence, clinical quality, number of GPs, extended access offer from the NHS England primary area hub. Output 3 analysis uses the information at provider and purchaser (Clinical Commission Group) level. - Workforce; In addition, for the analysis on mental health the study team use the MHSDS data for 2018. Only individual level data essential to Output 4 analysis is kept, as gender, age, and ethnicity. - Integrated Health & Social care; Duration: 24 months (2021) - Measuring health & quality of care; Funder: NIHR PRP ESHCRU II (Policy Research unit in the Economics of Social and Health Care). - Organisation and structure of health systems; The above are a few examples of the way in which NHS England data is used under this Agreement only for illustrative purposes. University of York can provide, upon request of NHS England, all uses of NHS England data. - NIHR Policy Research Unit in Economics of Health Systems and Interface with Social Care (ESHCRU, https://eshcru.com/). - REAL Supply Research Unit (REAL-S, https:/realsupply.ac.uk/). 3. Equity Aim: To understand and address inequalities in health and healthcare outcomes. Objectives: Measure and monitor health equity. Evaluate policy impacts on health inequalities. Use distributional cost-effectiveness analysis. Explore public preferences and equity indicators. Programmes of work include: - Distributional cost-effectiveness analysis (DCEA); - NHS equity indicators; econometric methods and policy evaluation; - The equity impacts of hospital competition; - Inequality in waiting times; - Primary care workforce distribution; - Deliberative process for addressing equity concerns; - Public preferences for reducing health inequality. 4. Methods Aim: To develop and apply robust statistical and analytical methods using NHS data. Objectives: Assess data quality and relevance. Evaluate provider performance and policy impacts. Analyse health system efficiency and productivity. Support decision modelling and economic evaluation. 5. Mental Health Aim: To evaluate mental health services and their impact on health and economic outcomes. Objectives: Study determinants and inequalities in mental health. Assess access, quality, and cost of mental health care. Evaluate mental health interventions and outcomes. Analyse the performance of mental health providers. Programmes of work in the area of mental health economics and policy adopt a range of methods and cover: - Socio-economic determinants of mental illness; - Health inequalities; - The interplay between mental and physical health; - Use of physical healthcare services for people with mental health problems; - Access to mental healthcare services; - The organisation, funding and delivery of mental health services; - Quality of mental healthcare provision; - The cost of mental healthcare provision; - The economic evaluation of mental health interventions and services; - Mental health outcomes; - The performance of mental health providers. 6. Public Health Aim: To evaluate public health interventions and their role in reducing health inequalities. Objectives: Study socioeconomic determinants of health. Assess economic consequences of health behaviours. Use econometric and microsimulation methods. Support local partnerships and commissioning strategies. Programmes of work include: - CHE is one of the academic centres in the Public Health Policy Research Unit (https://www.phpru.online/) - Socioeconomic determinants of health, health behaviour and health inequalities; - Economic consequences of health and health inequalities; - Economic evaluation of public health interventions; - Evaluation of public health interventions through econometric methods and microsimulation (an alternative method which involves simulating the impacts of hypothetical and/or new programmes or forecasting the impacts of existing programmes in new contexts and over time); - Local health and care research partnerships; - Resource allocation and health inequalities; - Commissioning public health services. PROJECT SCOPING AND RESPONSIVE ANALYSIS CHE has implemented a new strategy to assess the viability of new projects. Across many of CHE’s strategic research priorities, analyses may be undertaken of NHS England data for scoping research and responsive analyses, as described below. Scoping analysis When a new project idea or research question is conceived, it may be both beneficial and necessary to use NHS England datasets to carry out preliminary analysis prior to the submission of a research funding application. Such scoping analyses would support researchers in testing their proposed research questions to confirm feasibility, and allow researchers to generate relevant, accurate and high quality proposals with the confidence that the data can be used to generate the desired outcome and impact. During scoping analysis, researchers may undertake the following types of assessment: - Test whether key outcomes of interest are numerous enough; - Check whether coding is consistent across organisations and geographic areas, and over time; - Determine whether particular statistical methods would be appropriate for the questions being asked; - Test whether CHE research would have the necessary statistical power to be able to make high quality conclusions; - Assess the minimum level of data required for the purpose. Scoping analysis is approved by the Data Access Request Group (DARG). Requests for scoping analysis are submitted by the individual(s) within a project team, and a record of requests and outcomes is kept in a register maintained by DARG. The request captures the aim of the scoping, data set(s) required, data fields and years necessary; and the approval date and person, outcome of scoping exercise, and status of data is recorded on the register. It also confirms that other sources of data have been considered prior to this request. Where the outcome of the scoping exercise is to proceed with a research funding application, the working dataset used for the scoping exercise will be kept, pending the outcome of the funding application. If the individual(s) conclude that the project is not feasible, or the funding application is unsuccessful, the working dataset used will be erased. No member of staff will ever make copies of full NHS England datasets. Requests for scoping analyses may also include scoping analysis for PhD students who are not familiar with NHS England datasets, and who wish to explore them to better understand the data fields that are needed for their own PhD research project(s). Responsive analysis The University of York Centre for Health Economics holds several NIHR Policy Research Programme contracts. Some of these, such as the contracts for the Policy Research Units, include a requirement to undertake rapid response research. The aim of this responsive facility is to meet emerging needs of policy makers at the Department of Health and Social Care (DHSC) or its arm’s length bodies (e.g. NHS England). The evidence can be commissioned at short notice, and the nature of the requests depends on the issues and challenges facing the Department as priorities and policy evolve and develop. For example, the study team may be asked to provide evidence quickly in response to Parliamentary Questions; changes in priorities in the health or care system may lead to requests for a short piece of analysis to inform new policies; or evidence to support pressing analytical needs within the Department may be requested. These responsive requests are additional to the core, planned work undertaken under the auspices of the same contracts. Whilst the topic of some requests may fall within the broad priority areas outlined above, this cannot be guaranteed. Therefore, the University of York wishes to include an additional ‘responsive analysis’ purpose to ensure University of York have the necessary permissions in place to ensure the study team can respond to DHSC rapid requests in line with the University of York's contractual requirements. [1 paragraph unchanged] - Hospital Episode Statistics (HES): Critical Care, Care , Outpatients, Admitted Patient Care (APC), Accident and Emergency (A&E) – necessary to [7 words unchanged] admissions, risk associated with admission, describing hospital resource use of patients, cost estimations. estimations; - Emergency Care Data (ECDS) [historically, HES Accident and Emergency] - · Emergency Care Data Set (ECDS) – necessary because this dataset replaced HES Accident & Emergency data data; - Civil Registration (Deaths) - Secondary Care Cut (CRD SCC) – necessary to report rates of mortality and model risks of certain diseases. diseases; - Patient Reported Outcome Measures (PROMS) - necessary to measure health benefits produced by the health system. system; - Mental Health Services Data Set (MHSDS) [historically, (MHSDS), Mental Health Minimum Data Set (MHMDS) & Mental Health and Learning Disabilities [48 words unchanged] funding of mental health services; and the performance of mental health providers. - Community Services Data Set – necessary to enable CHE to explore the role of community services in helping prevent unnecessary hospital admissions and enabling speedier hospital discharges. As the population of England becomes older, there are more patients with chronic conditions that receive treatment in the community, so its use is more relevant now than it was previously. Therefore the use of this dataset will assist CHE when commissioned with policy research by the Department of Health and Social Care. - Improving Access to Psychological Therapies (IAPT) Data Set – necessary for research on the relationship between mental health and economic outcomes such as labour market participation. Key variables in the data include employment, self-employed status, employment support advisor indicator, absenteeism, benefit receipt, disability code, and diagnosis. This data will be used to develop economic models and framework to evaluate cost effectiveness and productivity. Different projects will have different requirements in terms of data dissemination frequency. For example, some projects will only require updated data annually whereas some projects will need more frequent data on a quarterly basis. Quarterly dissemination of data supports responsive projects, providing more timely evidence to policymakers - for example, to support the response to the COVID-19 pandemic. - Medicines Dispensed in Primary Care (NHS Business Services Authority data product) - necessary for research in which we examine the full cost of care, and we can estimate all costs in a patient's secondary care pathway, but we can't currently estimate key costs in primary care, which are typically medication use. - Diagnostic Imaging Dataset (DIDs) -necessary for research into whether higher imaging rates impact the four-hour target performance and throughput of Emergency Care Departments (and in which direction), and whether the use and growth in imaging services shortens/prolongs emergency care admissions -National Disease Registration Service (NDRS) Cancer Consolidated Data Set - necessary for research into the impacts of health technology assessment on the NHS and for research into the welfare impact of new treatments [1 paragraph unchanged] As part of the CHE data access request form, a data fields selection form is completed for every application requesting access to NHS England data which details the data fields and periods required. Each project requirements are different therefore data minimisation is applied to each project at inception. This could be limited to data periods or geographic regions however each project will be unique and all data minimisation will be reviewed by DARG. The Data will be minimised as follows: - Data minimisation is different for each projects. This could be limited to data periods or geographic regions, however each project will be unique and all data minimisation will be reviewed by DARG. [1 paragraph unchanged] Though CHE may be commissioned by another organisation to undertake a project involving the processing of data under this Agreement, CHE will retain sole discretion for determining if and how the data would be used for any purpose. Economics of Health Systems and Interface with Social Care (ESHCRU), Policy Research Unit in Economic Evaluation of Health and Care Interventions (EEPRU) and Applied Research Collaboration (Yorkshire and Humber) are examples of current research collaborations in CHE not separate organisations. Where the University of York - Centre for Health Economics is a partner in research collaborations, including (but not limited to) ESHCRU, EEPRU, and Applied Research Collaboration-Yorkshire and Humber (ARC-YH), the team within the University of York will be solely responsible for all decisions on how this research will be carried out including all decisions in respect of what data processing is required. Data provided as part of this Agreement will not be shared with collaborators. The University of York - Centre for Health Economics cannot be compelled by any third party to process the data for any purpose or in any way. The data will only ever be used for purposes that directly support the priorities of the University of York - Centre for Health Economics, as described in this Agreement. Data provided as part of this Agreement will not be shared with collaborators [5 paragraphs unchanged] The funding for all projects under this programme level Agreement comes from multiple sources. Current funders for ongoing projects include: The funding for all projects under this Programme Level Agreement will come from multiple sources. CHE’s research is largely externally funded, with a broad potential funding base which could include (but not limited to): National Institute for Health Research (NIHR); European Union; Wellcome; and UK Research and Innovation (UKRI). In addition to external sources of funding, CHE may receive internal (University of York/ Centre for Health Economics) research funding. The NIHR is the sole current funder for ongoing projects. Funding to continue the work described will be sought on an ongoing basis. • National Institute for Health Research (NIHR) The funder(s) will have no ability to suppress or otherwise limit the publication of findings. • The Health Foundation Amazon Web Services is a processor acting under the instructions of University of York Funding to continue the work described will be sought on an ongoing basis. Data will be assessed by : CHE’s research is largely externally funded, with a broad potential funding base which could include (but not limited to): National Institute for Health Research (NIHR); European Union; Wellcome; and UK Research and Innovation (UKRI). In addition to external sources of funding, CHE may receive internal (University of York/ Centre for Health Economics) research funding. - substantive employees The funder(s) will have no ability - Any student working with the Data held under this Data Sharing Agreement (DSA) must have completed relevant data protection and confidentiality training and are subject to University of York’s policies on data protection and confidentiality. Any student accessing the Data will do so under the supervision of a substantive employee of University of York. University of York would be responsible and liable for any work carried out by students. These students would only work on the Data for the purposes described in this DSA A Public and Patient Involvement and Engagement (PPIE) group helps refine the purposes of the research projects. University of York (Centre for Health Economics) will use PPIE during the development of research projects using NHS England Data. When putting together new project proposals PPIE panels, in the form of advisory groups, are used to scrutinise the proposals. Such advisory groups provide valuable insights.

Processing activities

The University of York currently hold pseudonymised data which were supplied under a different data sharing agreement with NHS England (DARS-NIC-84254), for the below datasets: No data will flow to NHS England for the purposes of this Data Sharing Agreement - Hospital Episode Statistics (HES): Critical Care, (2011/12-2021/22) NHS England will provide the relevant records from the datasets listed in this agreement to University of York. The data will contain no direct identifying data items. The data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient. - Hospital Episode Statistics (HES) Outpatients, (2003/04-2021/22) - Hospital Episode Statistics (HES) Admitted Patient Care (APC) (1989/90-2021/22) - Emergency Care Data (ECDS) (2017/18-2021/22) [historically, HES Accident and Emergency (2007/08-2019/20)] - Civil Registration (Deaths) - Secondary Care Cut (CRD SCC) - Patient Reported Outcome Measures (PROMS) (2009/10-2020/21) - Mental Health Services Data Set (MHSDS) [historically, Mental Health Minimum Data Set (MHMDS) & Mental Health and Learning Disabilities Data Set (MHLDDS)] (2011/12-2020/21) Under this Agreement, the University of York are requesting latest available-2024/25 quarterly and annual disseminations of pseudonymised data for those datasets listed above, additionally the Community Services Data Set (2015/16-2024/25 and Improving Access to Psychological Therapies (IAPT) Data Set (2012/13-2024/25) are required. No data will flow to NHS England for the purposes of this Agreement. NHS England data will provide the relevant records from the above datasets to the University of York. The data will contain no direct identifying data items. The data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient. [2 paragraphs unchanged] * Remote processing would be from secure locations within the territory of use identified within the agreement (UK and EEA) The Data will be accessed by authorized personnel via remote access. * Remote access is via devices that are maintained by the controller The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract. * All remote access is undertaken within the scope of the organisations DSPT (or other security arrangements as per this agreement), and complies with the University’s remote access policy For remote access: * No data will be held locally on the remote device. - Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA; * None of the above removes the conditions set out elsewhere within the agreement (eg: who may carry out processing, and for what purpose) - Access controls granting users the minimum level of access required are in place; Access is restricted to employees or agents of University of York who have authorisation from the Principal Investigator. - Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data; - Multifactor authentication (MFA) is required for remote access; - Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access; - All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy. The data will not leave the UK & EEA at any time. Access is restricted to substantive employees of University of York. Any MSc or PHD students accessing the data will do so under the supervision of a substantive employee of University of York. [1 paragraph unchanged] The NHS England data will not be linked with other patient record level data. [9 paragraphs unchanged] CHE will run the data through the Healthcare Resource Group (HRG) grouper and attach National Cost Collection data (previously National Reference Cost data) using HRG codes and will link HES APC with MHMDS/MHLDS/MHSDS using the bridging file. Linking NHS England data with other datasets on healthcare costs, quality indicators, indices of deprivation, primary and secondary workforce, etc, does enhance the NHS England data, making them more useful to answer specific research questions, for example, inequity in waiting time or access to healthcare services, and/or when evaluating policy reforms aimed, for example at increasing the efficiency of hospital provision. Should the Centre for Health Economics wish to undertake a project involving a specific cohort of patients for which a data linkage is required, a separate application to NHS England and, subject to approval, a separate Data Sharing Agreement permitting the processing will be required. [1 paragraph unchanged] Researchers from the Centre for Health Economics University of York researchers will process and analyse the data for the purposes described above. above For data from the Mental Health (MHSDS, MHLDDS, MHMDS) data sets, and any Mental Health data linked to HES, the following disclosure control rules must be applied: • National-level figures only may be presented unrounded, without small number suppression Suppress all numbers between 0 and 5. • Round all other numbers to the nearest 5. • Percentages can be calculated based on unrounded values, but need to be rounded to the nearest integer in any outputs. • In addition, for Learning Disability data in Mental Health (MHSDS, MHLDDS, MHMDS), the England-level data also must apply the suppression of all numbers between 0 and 5, and rounding of other numbers to the nearest 5. From the date this Agreement takes effect, the following separate Agreements between NHS England and the University of York will be terminated: • DARS-NIC-84254-J2G1Q

Expected output

[36 paragraphs unchanged] • Presentations to Clinical Commissioning Groups (CCGs), Integrated Care Boards(ICBs), Integrated Care Systems (ICS), Primary Care Networks (PCN), NHS trusts, and Patient & Public Involvement and Engagement groups [12 paragraphs unchanged]

Benefits reported

Two examples of yielded benefits to date are as follows. These are not exhaustive examples of yielded benefits under this Data Sharing Agreements. Agreement. A pdf document, DARS-NIC-667040-B5T1X - all yielded benefits & outputs_2025_07_18, provides a complete list of all yielded benefits and outputs to date and has been attached to this application in section 4. Application overview - List of uploaded documents The first project is work commissioned by the Department of Health and Social Care (DHSC) /National Institute for Health and Care Research (NIHR) and it relates to the production each year of an annual update of the national NHS productivity figures that incorporate the most recent financial year of data. Annual updates of NHS productivity growth rate figures were used by the DHSC both externally and internally in monitoring, informing policy debate, the annual spending review, and negotiations on budget setting. Under this project, CHE also provided data about the quality of NHS care to the Office of National Statistics that are used each year in the construction of the national accounts. Over the years, additional analyses of productivity growth have been carried out at the hospital-level, specialty level, and geographical level. Hospital-level productivity analyses also examined the factors underlying variation in productivity, which assist the DHSC in exploring how to get the best value from NHS resources. The first example is the research project “A national investigation of mental health care crisis systems and their impact for the Mental Health Act”. A key benefit to date has been to provide policymakers with evidence on the characteristics of service users that interact with different mental health crisis care services, and utilisation of different service models of care. Delivery of acute care, including the impacts of innovative models within acute care systems, and arrangements for Mental Health Act (MHA) assessments, have been identified as very high priorities for both NHS England and DHSC policymakers. They are thus the primary beneficiaries of the research. A second example relates to work carried out in 2017 on patient-assessed outcomes which was extended, by working with the Vale of York commissioning body, to generate a web tool to support discussions between patients and their GPs about whether to undergo planned surgery. CHE developed the online tool, aftermysurgery.org.uk to inform patients about their likely outcome of hip and knee surgery and groin hernia repair. This online tool uses Patient Reported Outcome Measures (PROMs) data to present, for each user of the tool, information on health outcomes experienced by other patients that have similar preoperative characteristics. The intention of this tool is for it to be used in primary care to facilitate shared decision-making between general practitioners and patients. Having an operation is a big decision and it is natural to wonder how you will feel after surgery. Many people in this situation would like to know how patients before them have benefited from surgery. This online tool shows what thousands of NHS patients have said about their own experiences. It can be used to see how patients of the same age and with similar health problems felt after they had their operation. Patients complete the survey before and several months after surgery. Prior to deciding on surgery this tool allows patients to compare themselves to people who are similar to them and see how much surgery helped them. It is hoped that this benefits patients by giving them a better idea of what to expect if they decide to have surgery, and helps them decide whether to go ahead with surgery or not, in conjunction with their GP. The toolkit remains live, and is an ongoing benefit from this project. This study is vitally important in a mental healthcare system that is resource constrained and faces unprecedented demand, particularly following the pandemic. Demand for crisis mental health services has increased by one third since before the pandemic and doubled since 2017. More than 90,000 people per month are referred to community crisis services. The study provides empirical evidence for decision makers about how to make best use of these resources. This study can help ensure that the most optimal types of service models are identified and that extra investment is directed to areas, providers, and service models that can benefit the most. The second example is the project “The effects of advancements in health care technology on expenditure” which provides valuable evidence for NHS planning by quantifying how medical technology advances affect healthcare costs and patient outcomes. The findings show that whilst new technologies in acute myocardial infarction care have reduced inpatient bed days and improved survival rates, they have also increased overall healthcare expenditure. The analysis reveals important inequalities, with less deprived patients and those in certain regions benefiting more from technological advances, suggesting policies could mandate more equitable distribution of specialist cardiac services across regions. By identifying specific procedures driving cost changes, this work could support developing more sophisticated health technology assessment processes that account for survival benefits and long-term cost implications, enabling more efficient allocation of limited NHS resources.

Unchanged: Expected measurable benefits.