NHS Digital Data Release Register - reformatted

University Of York

Project 1 — DARS-NIC-03452-G8Z1V

Opt outs honoured: N

Sensitive: Sensitive, and Non Sensitive

When: 2016/04 (or before) — 2016/08.

Repeats: Ongoing

Legal basis: Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012)

Categories: Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Critical Care
  • Hospital Episode Statistics Outpatients
  • Hospital Episode Statistics Accident and Emergency
  • Mental Health and Learning Disabilities Data Set
  • Patient Reported Outcome Measures (Linkable to HES)

Benefits:

The benefits are to be delivered on an ongoing basis in accordance with CHE’s funding agreements, and accessible from CHE’s website: http://www.york.ac.uk/che/. For all of the above projects, DH have commissioned the work as evidenced by letters supplied. The expected benefits include: Project 1 – to December 2017 The Department of Health uses CHE’s work on of efficiency, effectiveness and productivity to provide numerical answers and context for, among others, Health Select Committees, the Public Accounts Committee and Public Expenditure Inquiries; the Office of National Statistics draws heavily on CHE’s work in producing the national accounts; CHE disseminate the work through various media to inform the public about NHS productivity. Project 2 – to December 2017 CHE’s projects evaluating the performance of health care providers provide evidence to inform national and regional (Yorkshire and Humber) policy-makers and providers about the scope and focus of performance improvement and outcome measures, tariff design, and patient choice. Project 3 – to December 2017 CHE’s evaluations of the impacts of health care policy, organisation, finance and delivery of NHS services are used to inform resource allocation arrangements and the design and direction of future policy regarding the health and social care sectors with CHE’s advice and analyses being sought to feed into White papers and specific government reviews. Project 4 – to December 2017 CHE’s projects investigating socio-economic inequality will help the NHS address its duty under the Health and Social Care Act 2012 to consider reducing health inequalities. By the end of 2015 CHE will produce prototype NHS equity dashboards” (e.g. similar to http://health-inequalities.blogspot.co.uk/ which uses QOF data) that help national and local NHS organisations to monitor performance in reducing inequalities in health outcomes and access to healthcare at different stages of the patient pathway. An example of CHE’s work in this area is here: http://www.sciencedirect.com/science/article/pii/S0277953612001086 Project 5 – to December 2017 The projects assessing the interface between the different sectors of the health care system are used to inform discharge arrangements, design of integrated care arrangements and to identify opportunities for substitution of different types of health and social care services. Project 6 and 7 – to December 2017 CHE’s projects examining cost-effectiveness will produce information which can be used to assist national and local decision making regarding an efficient use of healthcare resources in the NHS. CHE has an international reputation in undertaking cost-effectiveness analyses: http://www.eepru.org.uk/Publications(2353189).htm Project 8 – to November 2016 The rationale for the project is to assess the economic arguments surrounding the issue of doctor re validation with particular emphasis on measuring changes to medical performance and assessing the cost-effectiveness of the programme in terms of not only increased health related quality of life for the population but also public assurance. We also directly address the extent to which the arguments outlined in the DH pre-programme impact assessment which was used to support the adoption of revalidation are being realised.

Outputs:

The outputs from all of the projects will include peer reviewed papers in academic journals, reports for funders, lay summaries such as newsletters and blogs, and conference and seminar presentations to academic, policy, professional and public audiences. The Centre for Health Economics has a long-established track record in delivery of policy research that utilises HES data, as recognized by the award of the Queens Anniversary Prize in 2007. Examples of recent publications arising from the above projects that have employed the HES data can be found here http://eshcru.ac.uk/publications/index.htm; http://www.york.ac.uk/che/publications/in-house/; and http://www.eepru.org.uk/Publications(2353189).htm. Reports will be produced containing aggregate results that show trends over time, differences across providers, commissioners, geographical areas and by patient subgroups and patient characteristics. The results will contain estimated correlations showing associations between patient outcomes and patient characteristics, hospital, institutional, geographic and environmental factors. Statistical results will be presented in interactive spreadsheets or “Dashboards” (e.g. similar to http://health-inequalities.blogspot.co.uk/ which uses QOF data and only contains aggregated data which can be interrogated), tables and maps of aggregate statistics summarising patient characteristics and will comply with ONS guidelines on disclosure of potentially patient identifiable data i.e. no small numbered cells and figures will be reported. The outputs from each project will be delivered in accordance with CHE’s funding agreements, which run to different timelines with various milestones for each. The key milestones and timelines for each project (including 2015 publications) are: Project 1 - interim reports by September 2016, final report by December 2017 for Department of Health (Ref 103/0001). Castelli A, Street A, Verzulli R, Ward P. Examining variations in hospital productivity in the English NHS. European Journal of Health Economics, 2015, 16 (3), 243-254; DOI 10.1007/s10198-014-0569-5. Bojke C, Castelli A, Grašič K, Street A. Productivity of the English NHS: 2012/13/update. Centre for Health Economics, University of York; CHE Research Paper 110, 2015. Aragon Aragon M, Castelli A, Gaughan J. Hospital Trusts productivity in the English NHS: uncovering the possible drivers of productivity variations. Centre for Health Economics, University of York; CHE Research Paper 117, 2015. Project 2 - interim and final reports for Department of Health (Ref 103/0001) by July & December 2016 and 2017; interim and final report for NIHR SDO (Ref 11/1022/19) by June 2016 and December 2017. Gutacker N, Street A. Multidimensional performance assessment using dominance criteria. Centre for Health Economics, University of York;CHE Research Paper 115. 2015. Castelli A, Daidone S, Jacobs R, Kasteridis P, Street AD. The determinants of costs and length of stay for hip fracture patients. PLoS One 2015;doi:10.1371/journal.pone.013354 Gutacker N, Street A, Gomes M, Bojke C. Should English healthcare providers be penalised for failing to collect patient-reported outcome measures (PROMs)? Journal of the Royal Society of Medicine, 2015; 108: 304-316 DOI: 10.1177/0141076815576700 Gomes M, Gutacker N, Street A, Bojke C. Addressing missing data in patient-reported outcome measures (PROMs): implications for the use of PROMs for comparing provider performance. Health Economics, 2015;doi:10.1002/hec.3173. Gutacker N, Bloor K, Cookson R, Garcia-Armesto S, Bernal-Delgado E. Comparing hospital performance within and across countries: an illustrative study of coronary artery bypass graft surgery in England and Spain. European Journal of Public Health 2015;25(suppl1):28-34. Gutacker N, Bloor K, Cookson R. Comparing the performance of the Charlson/Deyo and Elixhauser co-morbidity indices across five European countries and three conditions. European Journal of Public Health 2015;(suppl1):15-20. Jacobs R, Gutacker N, Mason A, Goddard M, Gravelle H, Kendrick T, Gilbody S. Determinants of hospital length of stay for people with serious mental illness in England and implications for payment systems: a regression analysis. BMC Health Services Research 2015;15:439. Moran V, Jacobs R. Comparing the performance of English mental health providers in achieving patient outcomes. Social Science & Medicine 2015;140:127-136. Bojke C, Grasic K, Street A. How much should be paid for Prescribed Specialised Services? Centre for Health Economics, University of York; CHE Research Paper 118, 2015. Project 3 - final report for Wellcome Trust [ref: 105624] by March 2016; interim and final reports for Department of Health (Ref 103/0001) by July & December 2016 and 2017; progress and final NIHR HS&DR 13/54/40 NIHR HS&DR by, January and July 2016, January and July 2017, January and July 2018. Santos R, Gravelle H, Propper C. Does quality affect patients’ choice of doctor? Evidence from the UK. The Economic Journal 2015;doi:10.1111/ecoj.12282. Gutacker N, Siciliani L, Moscelli G, Gravelle H. Do Patients Choose Hospitals That Improve Their Health? Centre for Health Economics, University of York; CHE Research Paper 111, 2015. Project 4 - interim and final reports for NIHR HS&DR (Ref DRF/2014-07-055) by July & December 2016 and 2017; interim and final reports for Funder NIHR, SRF-2013-06-015) by July & December 2016 and 2017 and 2018; Cookson R, Gutacker N, Siciliani L. Waiting time prioritisation: evidence from England. Centre for Health Economics, University of York; CHE Research Paper 114, 2015 Moscelli G, Siciliani L, Gutacker N, Cookson R. Socioeconomic inequality of access to healthcare: Does patients’ choice explain the gradient? Evidence from the English NHS. Centre for Health Economics, University of York; CHE Research Paper 112, 2015. Cookson R, Gutacker N, Garcia-Armesto, S, Angulo-Pueyo E, Christiansen T, Bloor K, Bernal-Delgado E. Socioeconomic inequality in hip replacement in four European countries from 2002 to 2009 – area level analysis of hospital data. European Journal of Public Health 2015;25(suppl1):21-27. Project 5 - interim and final reports for Department of Health (Ref 103/0001) due July & December 2016 and 2017. Gaughan J, Gravelle H, Siciliani L. Testing the Bed-Blocking Hypothesis: Does Nursing and Care Home Supply Reduce Delayed Hospital Discharges? Health Economics 2015;24(S1):32–44. Kasteridis P, Goddard M, Jacobs R, Santos R, Mason A. The Impact of Primary Care Quality on Inpatient Length of Stay for People with Dementia: An Analysis by Discharge Destination. Centre for Health Economics, University of York; CHE Research Paper 113, 2015. Kasteridis P, Mason A, Goddard M, Jacobs R, Santos R, McGonigal G. The Influence of Primary Care Quality on Hospital Admissions for People with Dementia in England: a Regression Analysis. PLoS One 2015;10(3):e0121506. Jacobs R, Gutacker N, Mason A, Goddard M, Gravelle H, Kendrick T. Do higher primary care practice performance scores predict lower rates of emergency admissions for persons with serious mental illness? An analysis of secondary panel data. NIHR HS & DR Journal 2015;3(16). Project 6 - interim and final reports for Department of Health (Ref 104/0001) due December 2016 and 2017. Project 7 - interim and final reports for Department of Health (Ref 104/0001) due December 2016 and 2017. Project 8 - final report for Department of Health (reference PR-R9-0114-11002) due November 2016. All products are available free of charge and available to the public via CHE’s website http://www.york.ac.uk/che.

Processing:

Whilst the nature of detailed analysis in relation to each project varies, the broad context of processing is consistent. The following processing activities apply to all of the projects listed above. Data storage: Data will only be stored on the CHE data analysis server and the backup server and will only be accessible to individuals associated with the Centre for Health Economics, University of York. Access to data is restricted to specific individuals according to role and project. Access to sensitive data is also restricted to only those individuals working within projects that are authorised to use sensitive data. Data analyses: CHE will use standard software (e.g. STATA, SAS, R) to analyse the data, derive descriptive statistics and apply multiple regression models to explore the relationships between variables. Data linkage: CHE will run the data through the HRG grouper and attach Reference Cost data using HRG codes. The data will then be linked: • to aggregated census and other geographical data using the LSOA (Lower Super Outputs Area) variables; • to Quality and Outcomes Framework and the Attribution Data Set using GP codes; and • to accounts and organisational-level data using provider codes. For the revalidation project CHE will use the consultant code to link with General Medical Council (GMC) register data on consultant age, gender, specialty and date and outcome of revalidation. The consultant code is a sensitive code and therefore access will be restricted to researchers involved in the revalidation project. Once linkage is performed for that project CHE will pseudonymise the consultant identifier. None of the linkages CHE perform will enable re-identification of any patients. No data will be linked to record level patient data. Data processing: Analyses of the HES and MHMDS data will involve estimation of statistical and econometric models using software including Stata, SAS and R. The analyses will take account of 1) patient demographic and socio-economic information such as age, gender, ethnicity, carer support, deprivation measures; 2) patient diagnostic information such as diagnoses (co-morbidities), Charlson score, psychiatric history, HRG or PbR care cluster; 3) treatment information such as admission type, specialty of provider, use of the Mental Health Act, community and inpatient services received by patients; 4) quality and outcomes such as PROMs, 30-day survival, HoNOS scores, waiting times, readmissions, and social outcomes such as employment and accommodation status; 5) service level factors such as number of contacts with staff, and delayed discharge. For all projects the data will be used to undertake both cross-sectional and longitudinal analyses, allowing analyses within-year variations and of changes over time.

Objectives:

Centre for Health Economics (CHE), based at University of York are requesting data for the following projects involving economic analyses of health and social care. Please note that for each of the following projects CHE staff will analyse individual level data from the various datasets. Only aggregated results will be published and disseminated. Project 1 - Measurement of efficiency, effectiveness and productivity in the delivery of health care system nationally, sub-nationally and among hospitals; In the current economic climate it is particularly important that we are able to identify and monitor changes in efficiency and productivity. The purpose of this project is to produce information for the Department of Health and Secretary of State for Health on efficiency, effectiveness and productivity and to provide numerical answers and context for, among others, Health Select Committees, the Public Accounts Committee and Public Expenditure Inquiries. The work also contributes to the measurement of productivity of the health service in the national accounts, compiled by the Office of National Statistics. Funder: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001) This project will use only the following data: HES APC 1998/99-2014/15; A&E 2007/08 - 2014/15; Critical Care 2011/12 – 2014/15; Outpatient 2011/12-2014/15; PROMs 2009/10 – 2014/15; ONS mortality 1998/99 – 2014/15, The project also requires use of the sensitive PROMs and ONS mortality data as measures of the quality of health care. Project 2 - Evaluation of differences in the performance of health care providers in terms of the amount and cost of provision and in patient outcomes including mortality and self-reported morbidity; The purpose of this project is to produce evidence to inform national and regional (Yorkshire and Humber) policy-makers and providers about the scope and focus of performance improvement and outcome measures, tariff design, and patient choice. The project is designed to develop a more systematic evidence base that will allow policy-makers, providers and commissioners to develop policies to achieve efficiency and outcome-based commissioning and to redeploy resources to produce more efficient mixes of services both within and across the health and social care sectors. Funders: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001) • National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care Yorkshire and Humber (CLAHRC YH) (Ref NIHR CLARHC YH II 14653) This project will use the sensitive field Consultant Code which is required to assess variations across consultants in measures of patient safety, quality and patient reported outcomes. • NIHR SDO Information and Value Based Commissioning - explaining the variation and causes of hospital activity and outcomes (Ref 11/1022/19) The work for all three funders will require the sensitive PROMs and ONS mortality data to measure patient outcomes including mortality and self-reported morbidity. The project will use only the following data: HES APC 1989/90 - 2014/15, Sensitive field: Consultant Code; HES Outpatient 2002/03 - 2014/15; PROMs 2009/10 – 2014/15; ONS mortality 1997/98 – 2014/15. Project 3 - Evaluation of the impacts of health care policy, organisation, finance and delivery of NHS services and quantification of differences in health care utilisation, expenditure, morbidity and mortality over time, across geographic regions, health providers, and among different patient groups; The purpose of this project is to produce information that will be used by the Department of Health to inform resource allocation arrangements and the design and direction of future policy regarding the health and social care sectors with CHE’s advice and analyses being sought to feed into White papers and specific government reviews. This project includes understanding which type of “market” for health and social care services – from highly regulated internal markets to fully decentralised market models – best achieves strategic goals. The main aims are to: analyse the potential for use of markets in health and social care to improve overall performance; analyse the impact that different configurations of markets can make on prices, outputs, quality and outcomes; explore how the best configurations could be implemented in practice. Funders: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001) • NIHR HS&DR 10/1011/22 and NIHR HS&DR 13/54/40 Relationships between primary care and secondary care outcomes for people with mental illness • Wellcome Trust [ref: 105624] through the Centre for Chronic Diseases and Disorders (C2D2) at the University of York: Finance and organisation of mental health services The project will use only the following data: HES APC 1998/99 – 2014/15; A&E 2007/08 – 2014/15; Outpatient 2002/03 – 2014/15; PROMs 2009/10 – 2014/15; MHMDS 2011/12 – 2014/15, ONS mortality 1998/99 -2014/15. The work for all three funders will require the use of the sensitive PROMs and ONS mortality data to measure morbidity and mortality over time. This project will also require use of MHMDS data linked to HES data in order to carry out analyses into the economics around mental health and mental health care provision. CHE are requesting sensitive MHMDS fields and sensitive HES psychiatric fields (Legal group of patient, Legal status classification, and Detention category). These relate to the legal category / legal status of the patient and if CHE’s analyses are to be robust, are crucial for CHE’s models as an important indicator of patient severity. CHE will need all sensitive data items to accurately control for the impact of detention on resource use and utilisation. CHE need to check data consistency between HES and the MHMDS and therefore require sensitive data on legal status in both datasets. Project 4 - Investigation of access to and socio-economic inequality in the use healthcare, patient outcomes, clinical practice, choice of provider, competition and concentration of health care services across England; The purpose of this project is to produce information that the Department of Health will use to address the NHS’ duty under the Health and Social Care Act 2012 to consider reducing health inequalities. CHE will produce prototype NHS equity dashboards to help national and local NHS organisations to monitor performance in reducing inequalities in health outcomes and access to healthcare at different stages of the patient pathway. Funders: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001) • NIHR HS&DR (Ref 11/2004/39): Developing indicators of change in NHS equity performance • NIHR HS&DR (Ref DRF/2014-07-055): Doctoral Research Fellowship - Measuring & explaining variations in general practice performance. The project will use only the following data: HES APC 1989/90 – 2014/15; PROMs 2009/10 – 2014/15; ONS mortality 1997/98 – 2014/15. The work for both funders will use the following sensitive PROMs and ONS mortality data to measure patient outcomes. Project 5 - Evaluation of the interface between the different sectors of the health care system, including the effects of quality and access of primary care on patient use and outcomes in secondary care; and the relationship between long term care, social care and secondary care utilisation. It has long been understood that health and social care services are frequently providing treatment and care for the same individuals, so ensuring that these are ‘joined up’ or well co-ordinated has in one form or another been a key objective of policy. In practice, however, both the services and approaches to monitoring these have developed separately, with potential implications for the efficiency and effectiveness of both health and social care. The purpose of this project is to produce information that will be used by the Department of Health to inform discharge arrangements and the design of integrated care arrangements and to identify opportunities for substitution of different types of health and social care services. CHE shall also be developing an online web tool to inform patients about their likely outcome of surgery to impact on shared decision making in primary care in York. Funder: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001) • ESRC Impact Accelerator Account - developing an online web tool (Ref A0158801) The project will use only the following data: HES APC 1989/90– 2014/15; A&E 2007/08 – 2014/15; Outpatient 2002/03 – 2014/15; Critical Care 2011/12 – 2014/15, PROMs 2009/10 – 2014/15; ONS mortality 1997/98 – 2014/15. This project requires the sensitive PROMs and ONS mortality data to measure patient outcomes in secondary care. Project 6 - Estimation of resource use, costs and other parameters for cost-effectiveness analysis to support NHS and DH decisions. The purpose of this project is to estimate the costs and health outcomes associated with a range of medical interventions identified as priorities by the Department of Health. These include interventions in oncology, cardiology and infectious disease. Only HES APC data for the years 1997/98 -2014/15 are required to estimate costs. Access to ONS mortality data, also limited to the years 1997/98 - 2014/15, are required to estimate impact on survival. Funder: • Department of Health to the Policy Research Unit in the Economic Evaluation of Health and Care Interventions (Ref 104/0001) The project will use only the following data: HES APC 1997/98 - 2014/15; ONS mortality 1997/98 - 2014/15. This project requires the sensitive ONS mortality data to measure cost-effectiveness. Project 7 - To assess variability in uptake of treatments to inform the cost-effectiveness of interventions to increase uptake of high-value interventions. The Department of Health is interested in the uptake of health care interventions which have been recommended by national guidelines. These interventions are identified by the Department of Health and include drug treatments for hepatitis C. The research is seeking to estimate uptake using HES APC data, for the years 1997/98 - 2014/15, as well as the implications for costs and survival (ONS mortality, limited to years 1997/98 - 2014/15) uptake falling short of national recommendations. Funder: • Department of Health to the Policy Research Unit in the Economic Evaluation of Health and Care Interventions (Ref 104/0001) The project will use the following data: HES APC 1997/98 - 2014/15; ONS mortality 1997/98 - 2014/15. This project requires the sensitive ONS mortality data to measure cost-effectiveness. Project 8 - Evaluating the development of medical revalidation in England and its impact on organisational performance and medical practice. This project requires HES data to examine the impact of revalidation and related systems for managing medical performance in NHS acute care, looking at individual level and organisational level effects. Funder: • Policy Research Programme (reference PR-R9-0114-11002). CHE lead: Dr Chris Bojke. The project will use only the following data: HES APC 2007/08 - 2014/15; A&E 2007/08 – 2014/15; Outpatient 2007/08 – 2014/15; PROMs 2009/10 – 2014/15. This project requires the sensitive PROMs data to measure organizational performance and the Consultant Code to assess differences in medical practice. CHE confirms that the data under this application would only be used for the eight projects listed, and any additional project (whether as part of the DH programme or otherwise) would require a separate approval. Equally individuals working on each project will only be permitted to access the data relating to that project, as identified within this application. Access is granted for each project only to the named individuals associated with that project under authorised user names. Such access is password controlled (with a password reset required on a regular refresh). The controls enable a single copy of the data to be held, reducing security risk associated with multiple copies being provided per project. This model is aligned with similar arrangements for other sizeable research institutions. The access procedures are set out in our System Level Security Policy (November 2015), as follows: “Logical measures for access control and privilege management Permissions to access the working data files are managed using Window’s Active Directory and the NTFS file system. Only members of CHE have access to the file store directory, and the HES data storage directory restricts access to only those staff with permission to access the HES data. The ONS data will be kept in compressed encrypted format within an ONS data directory with user permissions given only to ONS approved projects and users that have signed the ONS data usage form. Permissions are managed centrally with only John Galloway authorised to configure user permissions once authorisation has been granted in writing from Adriana Castelli or Katja Grasic. Access to the CHE analysis server (ADACX) is controlled by Mark Wilson who is only authorised to provide access to users following written approval by Adriana Castelli or Katja Grasic. who provide confirmation that users have permission to analyse the HES data and are listed on the HES data user agreements with the HSCIC. The HES server will be used to analyse the ONS data which will be stored in encrypted format within a directory with user permissions set to allow only individuals named on the ONS data user agreement.” Further, access to data is administered and monitored by Adriana Castelli through a registry. The registry lists all the projects with relevant Principal Investigator (PI) for which a valid Data Sharing Agreement issued by the Health and Social Care Information Centre is in place. Every member of staff working on a project(s) is requested to sign a non-disclosure form on an annual basis. The purpose of this form is to ensure compliance to the Centre for Health Economics and the University of York’s data protection policies, adherence to the Data Protection Act and all its Principles, and to the Centre for Health Economics System Level Security Policy. Members of staff who fail to return a signed form by the deadline provided will be excluded from access to the data until a signed form is returned. A copy of the non-disclosure form is attached. The use of ONS mortality data is approved on an individual basis per project.


Project 2 — DARS-NIC-06759-X5V7P

Opt outs honoured: N

Sensitive: Non Sensitive, and 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, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007

Categories: Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Accident and Emergency
  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Critical Care
  • Hospital Episode Statistics Outpatients
  • MRIS - Cause of Death Report
  • MRIS - Flagging Current Status Report

Benefits:

Population-based data on clinically meaningful haematological malignancy subtypes (>60 subtypes) are not available elsewhere (cancer registries have difficulty in accessing diagnostic information systematically and tend to group into 4 main categories that contain a mix of diseases). Importantly, the YHHN area is representative of the UK in terms of both demography and clinical practice, meaning that results are highly generalizable and are of potential importance to the commissioning of cancer care services at a national level. YHHN is uniquely placed to utilise up-to-date diagnostic and treatment data to conduct research on these complex cancers. By linking the patient cohort to HES, our registry will extend its population-based data to include antecedent and post-diagnostic events in the healthcare setting. The use of HES data will be multifactorial; and will be used to examine a number of questions along the patient pathway, including potentially aetiological factors and routes to diagnosis, as well as healthcare utilisation patterns & costings (before diagnosis, around the time of diagnosis, and onwards into the survivorship phase). There is a dearth of “real-world” information for patients diagnosed with haematological malignancies, and measurable benefits will include the provision of good quality population-based data to inform clinicians, patients, and commissioners. For example, some patients with aggressive cancers (such as diffuse large B-cell lymphoma) can be ‘cured’ but once in the survivorship phase, little is known about their healthcare needs. Likewise, precursor conditions such as monoclonal gammopathy of uncertain significance (MGUS) and monoclonal B-cell lymphocytosis (MBL), which can respectively progress to their more aggressive counterparts myeloma and chronic lymphocytic leukaemia, have been linked to other serious morbidities; MGUS with osteoporotic fractures and thrombotic disease and MBL most notably with infections. Again, however, there is currently a paucity of good quality information on these topics. The researchers will investigate these, and many other, putative associations in-depth across the entire patient pathway. Having a sample of HES data for the general population is essential in order to put the healthcare patterns of patients with haematological cancers into context, in much the same way as relative survival takes account background mortality levels. In addition, ‘real-world’ population-based data that includes all health service contacts are required not only to inform aetiological hypotheses and plan future healthcare services, but also to monitor the impact of future therapeutic changes in the general patient population. The target date for expected measurable benefits to healthcare will be by the end of December 2019.

Outputs:

Outputs utilising the requested data will begin soon after data receipt, and will continue for a minimum of five years. Specific outputs are described below. The University will use traditional publication routes (peer-reviewed, open access publications and conference presentations) and the HMRN website (www.hmrn.org) to disseminate findings to local, national and international practitioners and academics. The peer-reviewed journals targeted are likely to be similar to those that have already published in: British Journal of Cancer, British Journal of Haematology, Blood, British Medical Journal Open, Cancer Epidemiology, Journal of Clinical Oncology, PLoS One, and Value in Health among many others. To ensure accessibility, all reports will be published under creative commons attribution 4.0 licence (CC BY); support for this is included in all of the grant applications. Likewise, findings will be disseminated at conferences; those that are regularly attended include meetings of National Cancer Intelligence Network (NCIN), American and British Societies of Haematology (ASH & BSH), European Haematology Association (EHA), National Awareness and Early Detection Initiative (NAEDI), and the Palliative Care Congress. Outputs will follow guidelines on disclosure control and will only contain aggregated data with small numbers suppressed.

Processing:

In order to conduct this research, the University needs to compare the healthcare experiences of individuals in the patient cohort to that of the general population. For these analyses, the researchers are looking to source a comparison population selected from the general population to link to HES, ONS and Cancer Registrations. Selection of the control population sample and linkage to HES will be carried out by HSCIC. All personal identifying data will remain at the HSCIC and will not be made available to the University. Data for the comparison population, whether from ONS or HES, would be pseudonymised and will not contain personal sensitive fields. For each YHHN patient, 10 people with the same year of birth and sex will be randomly selected from among those alive and registered with a GP practice in the study region during the year the case was diagnosed. The study region at the core of YHHN covers the Primary Care Trusts of Bradford and Airedale, Calderdale, Kirklees, Leeds, North Yorkshire and York, Wakefield District, East Riding of Yorkshire, Hull, North Lincolnshire, and Northeast Lincolnshire Care Plus. In order to match the control sample to YHHN cases, HSCIC will use the demographic details of the YHHN cohort already flagged in the patient tracking service under MR1126. The choice of 10 “controls” for each YHHN patient will ensure adequate statistical power for the comparative analyses; and, with around 18,000 patients diagnosed September 2004 - August 2012, the University would be requesting data extracts on 180,000 non-YHHN subjects. Data requested from HSCIC for all controls are: • Sex • Year of birth • Identifier of matched case - HSCIC holds the anonymised identifiers for YHHN cases for patient tracking and control selection under MR1126. As an example, if a case has an identifier of 01-0001, then the first control would be 01-0001-01, the second 01-0001-02, etc. This will allow the University to know which controls were matched to each case. Analyses will examine health events that have happened in the past (before diagnosis/pseudo-diagnosis) and follow events that occur in the future; and some analyses will require data to be censored in the event of death or subsequent cancer. For this purpose, HSCIC will ‘flag’ the general population sample for future death and cancer registration; the extracted control cohort will be flagged in the patient tracking service and the following data, extracted from death and cancer registrations, supplied: • Month and year of death • Underlying cause of death • Month and year of cancer diagnosis • Cancer type HSCIC will link the control cohort to HES records. Data required for this linkage which will not be released to the applicants are: • NHS number • Sex • Date of birth • Postcode HSCIC will link the control sample to HES records and supply a pseudonymised HES output. Data received from HSCIC for this research will not include any patient identifiable information. Data will be stored and processed at the Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York. Data will be stored on a Microsoft SQL server running on a secured Windows Server and will only be accessible by the Epidemiology and Cancer Statistics Group staff. No identifiable data will be shared with third parties.

Objectives:

The overarching aim of the study is to examine how illness and healthcare patterns among patients with haematological cancers differs from that of those who do not have these cancers. The study cohort consists of patients with haematological cancers from the Yorkshire and Humberside Haematology Network (YHHN). The YHHN patient cohort lies at the centre of research carried out by the Haematological Malignancy Research Network (HMRN - www.hmrn.org), and for consistency and clarity YHHN (as opposed to HMRN) is referred to throughout this application. With 14 hospitals and a catchment population of around 4 million people, YHHN is a specialised “real-world” population-based register recording and analysing data on all patients diagnosed with haematological cancers in the Yorkshire and Humberside area. Since its start in 2004, YHHN has registered over 25,000 patients with a haematological malignancy. The University now wish to create a control cohort linked to the same routinely collected health data as YHHN for the following reasons; • to study potential risk factors and comorbidities for haematological malignancies including, for example, autoimmune conditions, chronic infections, and medical procedures; • to investigate whether illness patterns among patients with precursor haematological malignancies, such as monoclonal B-cell lymphocytosis (MBL) and monoclonal gammopathy of uncertain significance (MGUS), differ from those seen in the general population, both before and after their diagnosis. For comparative purposes, the control sample will be selected from the general population by the HSCIC. For each YHHN case diagnosed 2004-12, 10 people with the same year of birth and sex will be randomly selected from among those alive and registered with a GP practice in the study region during the year the case was diagnosed. This 'control' sample of approximately180,000 people, will be linked to HES records, as well as demographic, cancer registration and mortality data. The proposal has undergone peer review by Cancer Research UK and has been awarded funding (CRUK grant number C9474/A18362).


Project 3 — DARS-NIC-12881-L1H2B

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2016/09 — 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

Benefits:

NACR know from the research literature and NHS innovation initiatives that cardiac rehab programmes vary in the mode and quality of service delivery. (The RAMIT study - West RR, Jones DA, Henderson AH. Rehabilitation After Myocardial Infarction Trial (RAMIT):multi-centre randomised controlled trial of comprehensive cardiac rehabilitation in patients following acute myocardial infarction - Heart 2011;98:637–44). The NACR report highlighted many of these shortfalls in 2015 at Strategic Clinical Network (SCN) level and provided further important detail at local level which allows individual programmes to see how they are performing against clinical minimum standards. This new reporting approach will deliver the required detail and enable CCGs and hospitals to see how they are performing against clinical minimum standards. The BACPR, in collaboration with the NACR, is running a national certification programme which aims to ensure that all CR programmes are working to agreed clinical minimum standards supplied at a programme level, to help make judgements about their level of achievement. This BACPR minimum standards state that CR programmes should be submitting data to the NACR and the National Certification Programme (NCP) can’t be achieved without NACR registration. The NCP and the NACR both require a sense of the number of patients that were eligible for CR each year to generate accurate figures on uptake. The only mechanism for the NACR to derive the number of eligible patients is through HES. There will be tailored audit reports, national certification programme and key performance measures for local service accountability. The ability to report locally will not only enable commissioners and providers to make decisions based on the same high quality data but will also enable programmes to apply for national certification against clinical minimum standards. The overall aim is not to close CR programmes but is instead to drive up quality of delivery and optimise outcomes for patients. The NACR and the University of York expect to see these improvements within 12 months of the analysis and reports.

Outputs:

This data will be reported at organisational level in the 2016 National Audit of Cardiac Rehabilitation (NACR) Annual Report with Strategic Clinical Network (SCN), and local reporting of key performance indicators and aggregated patients outcomes - expected Publication November 2016 and as part of wider dissemination in peer reviewed journals, including Heart and the International Journal of Cardiology. Only aggregated data will be reported. Small numbers will be supressed in line with the HES analysis guide. The report will also be available online with open access and circulated via email to cardiac rehabilitation programmes. There will be no charge for this. University of York also use HES data, at a local programme level, to characterise high and low performing CR programmes based on the extent to which they meet the British Association for Cardiovascular Prevention and Rehabilitation (BACPR) minimum standards. As part of this approach, they seek to establish degree by which CR attendance influences hospital readmissions which is becoming increasing important for commissioners, providers and patients. In the last 12 months the NACR has published two papers; one on volume and outcome and the other on the impact of early versus late CR on patient outcomes. These papers established the first set of national level data on these important service indicators and it is intended to do likewise for other minimum standard indicators. Although this gives a good picture of the UK, and is world leading in that regard, the University need to do the same at a local programme level. To do this well they need to take account of the number and characteristics of patients that were eligible (attenders and non-attenders of CR) and not just base it on the number that attended CR. The rationale for this is that there could be a high degree of system or tacit selectivity at a programme level. The anticipated publication of outputs will be late 2016.

Processing:

The HSCIC will send pseudonymised, non-sensitive data to the University of York. The British Heart Foundation (BHF) funded team supporting the NACR (employed by and based at the University of York) has substantial analytical skills and infrastructure with a proven record in managing the national audit. The audit team support over 1000 NACR users and are supported by the University of York analysts in cleaning and validating the data and carrying out basic and advanced statistical analyses using SPSS and Stata (software packages to enable statistical analysis of the data) which are licenced through the University of York. The funders will not have any influence on the outcomes of the analysis. The 1000 NACR users are multidisciplinary cardiac rehabilitation staff who work within hospital or community programmes. They enter patient-level data on the individual patients that they see and have access to this data through the NACR platform. No attempt is made to link the data entered by the 1,000 NACR users to the HES data supplied by HSCIC The data is analysed by grouping the patients and the conditions to produce summaries by both region and CCG. This is then compared to the NACR data to generate uptake figures.

Objectives:

This request for data is to enable the National Audit of Cardiac Rehabilitation (NACR) to report accurately on cardiac rehab so that commissioners can make informed decisions about the performance of services they fund. The same data helps the NACR team to report on performance against national clinical standards and patient outcomes at CCG and local clinical cardiac rehabilitation programme level. The NACR aims to generate data on cardiac rehabilitation to help inform commissioning decisions and drive up the quality of provision and outcome for patients attending cardiac rehabilitation. Previous NACR reports from 2007 to 2013 reported at regional level which, although helpful in understanding the extent and quality of provision at the former Strategic Health Authority level, was unable to highlight high and low performing services and is no longer valid. As the NACR carries out more multi-factor analysis the numbers of patients in these analyses, in any one year, starts to become very small. For instance, five or more condition types are split and factored in (e.g. elective PCI, MI, MI+PCI, CABG and heart failure) plus gender, ethnicity and three age categories. This can result in fewer than 100 patients per group for any of the eight patients' outcomes the University report, (QoL, physical activity status, fitness, HADs, BMI, waist circumference, BP, chol). In order to enable these important analyses, data from previous years needs to be combined with the new data.


Project 4 — DARS-NIC-147884-R7CBN

Opt outs honoured: Y

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

Objectives:

To examine the long-term survival of UKCCS case children and factors, or combinations of factors, that might effect survival including treatment, demograpics and various exposures. The analyses will provide important insights into possible improvements in treatment of children with cancer and the identification of children at increased risk of relapse.


Project 5 — DARS-NIC-148035-41S3L

Opt outs honoured: Y, N

Sensitive: Sensitive, and Non Sensitive

When: 2016/04 (or before) — 2016/08.

Repeats: Ongoing

Legal basis: Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012)

Categories: Identifiable

Datasets:

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

Benefits:

With over 50 different sub-types and many pre-cursor conditions, haematological malignancies comprise a heterogeneous group of cancers with widely differing treatments and prognoses ranging from relatively indolent through to more aggressive forms. YHHN, an inclusive register of patients newly diagnosed with a haematological malignancy whilst resident in the former Strategic Health Authorities of West Yorkshire and North & East Yorkshire and Northern Lincolnshire, was established on 1st September, 2004. With a population of just under 4 million, around 2000 people are newly diagnosed with a haematological malignancy in the region each year. These patients are diagnosed by a central diagnostic laboratory, the Haematological Malignancy Diagnostic Service (HMDS) (www.hmds.org.uk ) based at St James's Hospital, Leeds. HMDS is part of the Clinical Haematology Network which covers the 14 hospitals (6 multi-disciplinary teams) within the Network region. This partnership is further enhanced by formal links with the Epidemiology & Genetics Unit (EGU) based at the University of York (www.egu.york.ac.uk). This collaborative group is ideally placed not only to inform local clinicians and local audit, but also has the potential to be developed as a resource for high quality population-based clinical research – the findings from which are likely to have implications across the country as a whole.

Outputs:

10.0 Transfer of Data between the NHS IC and the Department of Health Sciences Seebohm Rowntree Buliding University of York • The Data is categorised as Restricted and will be treated by the NHS IC in accordance with NHS IC protocols for the transfer and use of NHS Restricted Data. Electronic or disk • Before transfer the NHS IC will encrypt the data using the required standard of '256-bit AES encryption' compatible with the receiving organisations systems with a password length of at least 12 characters which must include numbers, letters and symbols, and should be a mix of upper and lower case characters. • The Data will be sent via secure electronic file to a Permitted User at the Department of Health Sciences Seebohm Rowntree Buliding University of York • The password will be provided to the Permitted User at the Department of Health Sciences Seebohm Rowntree Buliding University of York taking responsibility for arrangements under this Agreement via telephone or e-mail. • The named person must not share the Data or password with any other person at any time. • Before transfer of data to the NHS IC the Department of Health Sciences Seebohm Rowntree Buliding University of York will encrypt the data using the required standard of '256-bit AES encryption' compatible with NHS IC systems. • Paper • The NHS IC will arrange for secure courier of the data to Department of Health Sciences Seebohm Rowntree Buliding University of York • Packages containing patient data are addressed specifically to the principal contact • All packages are double-wrapped • All packages are despatched by recorded delivery for which the recipient's signature is required • Progress of delivery up to point of receipt will be tracked on-line using a unique tracking number 11.0 Storage of Data Refer to the System Level Security Policy. This policy has been approved for this project by the DH Security Officer in conjunction with the application, NIGB and DMsG approval given for this project, detailed in section 4 of this agreement. Data Storage was covered in the policy.

Processing:

No contact will be made with any individual(s) that could be identified from the information supplied, except as specified in the protocol and associated letters agreed between the Department of Health Sciences Seebohm Rowntree Buliding University of York and the NHS IC. Use of these Datasets are for the sole purpose set out above. The Data must not be shared with any other organisation or named individual not explicitly referred to within this agreement. If the information referred to herein is subject to an FOI or other request to share the Data, then agreement from the NHS IC must be sought before undertaking this. The Dataset must not be shared with any third party in the format in which it is provided to you by the NHS IC. Information tools derived from this Dataset will not be provided to any organisations without the specific consent of the NHS IC. Any publications derived from this Data by any party must be subject to ONS confidentiality guidance on the release of Health Statistics: http://www.ons.gov.uk/about/consultations/closed-consultations/disclosure-review-for-health-statistics---consultation-on-guidance/

Objectives:

To examine the survival of YHHN patients in relation to their presenting diagnostics, prognostics and treatment. The YHHN is a unique population based inclusive register, and the findings will have implications for the country as a whole. Data access will be restricted to the research team mentioned in section 7 of this agreement. Any amendments will be notified to the NHS IC.


Project 6 — DARS-NIC-390749-C4P0X

Opt outs honoured: Y

Sensitive: Non Sensitive, and Sensitive

When: 2016/09 — 2018/02.

Repeats: One-Off, Ongoing

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC, Section 42(4) of the Statistics and Registration Service Act (2007) as amended by section 287 of the Health and Social Care Act (2012)

Categories: Anonymised - ICO code compliant, Identifiable

Datasets:

  • Hospital Episode Statistics Accident and Emergency
  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Critical Care
  • Hospital Episode Statistics Outpatients
  • MRIS - Cause of Death Report
  • MRIS - Flagging Current Status Report
  • MRIS - Members and Postings Report

Benefits:

Population-based data on clinically meaningful haematological malignancy subtypes (>60 subtypes) are not available elsewhere (cancer registries have difficulty in accessing diagnostic information systematically and tend to group into 4 main categories that contain a mix of diseases). Furthermore, the YHHN area is representative of the UK in terms of both demography and clinical practice, meaning that results are highly generalizable and are of potential importance to the commissioning of cancer care services at a national level. YHHN is uniquely placed to utilise up-to-date diagnostic and treatment data to conduct research on these complex cancers. By linking the patient cohort to HES, the registry will extend its population-based data to include antecedent and post-diagnostic events in the healthcare setting. The uses of HES data will be multifactorial; and will be used to examine a number of questions along the patient pathway, including aetiological factors, routes to diagnosis, as well as healthcare utilisation patterns & costings (before diagnosis, around the time of diagnosis, and onwards into the survivorship phase). With respect to measurable benefits these will, in large part, result from the provision of good quality data/information (to clinicians, patients, and commissioners) that are currently lacking. For example, some patients with aggressive cancers (such as diffuse large B-cell lymphoma) can be ‘cured’ but once in this survivorship phase, little is known about their healthcare needs. Precursor conditions such as monoclonal gammopathy of uncertain significance (MGUS) and monoclonal B-cell lymphocytosis (MBL), which can progress to their more aggressive counterparts myeloma and chronic lymphocytic leukaemia, are also linked to other serious morbidities; MGUS with osteoporotic fractures and thrombotic disease and MBL most notably with infections. The University will investigate these, and many other, associations in-depth across the entire patient pathway. The healthcare patterns of haematological cancer patients will be put into context with a population of similar ages from a sample of the general population to compare with YHHN. In this context, ‘real-world’ population-based data that includes all health service contacts are required not only to inform aetiological hypotheses and plan future healthcare services, but also to monitor the impact of future therapeutic changes in the general patient population. The target date for expected measurable benefits to healthcare will be by the end of December 2019.

Outputs:

Haematological oncology is one of the most rapidly evolving areas of cancer research; and ≥ 60 clinically meaningful diagnostic groups are currently recognized in the latest World Health Organization (WHO) classification. Comprehensive reliable population-based information about the underlying occurrence and survival of patients diagnosed with these cancers, and their associated health care usage is limited – and linked register/HSCIC data provide a valuable UK resource for clinicians, patients and researchers. Thus far the university have published accurate population-based information on the survival and prevalence of haematological malignancies, classified for the first time into clinically meaningful diagnostic groups1,2. Mortality data has also been used in conjunction with diagnostic, demographic and treatment data to examine survival by socio-demographic factors. Importantly, in this regard it was found that patients with chronic myeloid leukaemia living in less affluent areas had poorer survival than those living in more affluent areas, despite the fact that all patients had equal access to the daily oral medication required to control the disease3. Additionally, as part of a joint project with the National Cancer Equality Initiative established by the Department of Health, the university examined whether older people with haematological cancer were being under-treated. Using linked data, the university was able to show that patients with aggressive, but potentially curable, non-Hodgkin lymphoma who were fit enough to receive intensive chemotherapy were treated with curative intent, and that chronological age was not a major determinant of the decision making process. Critically, by linking to mortality data we also demonstrated that older, fitter patients who were treated showed the same survival benefit compared to younger people4. Linked register/HSCIC data have also been used to examine the treatment pathways and financial costs of haematological cancers; one example being that of diffuse large B-cell lymphoma, where we estimated that it costs the NHS £88-92 million annually to treat this disease 5. Below is a sample of outputs produced from register/HSCIC linked data - 1. Smith, A. et al. Lymphoma incidence, survival and prevalence 2004–2014: sub-type analyses from the UK’s Haematological Malignancy Research Network. Br J Cancer (2015). doi:10.1038/bjc.2015.94 2. Roman, E. et al. Myeloid malignancies in the real-world: occurrence, progression and survival in the UK’s population-based Haematological Malignancy Research Network 2004-15. Cancer Epidemiology (2016). doi:10.1016/j.canep.2016.03.011 3. Smith, A. G. et al. Determinants of survival in patients with chronic myeloid leukaemia treated in the new era of oral therapy: findings from a UK population-based patient cohort. BMJ Open 4, e004266 (2014). 4. Smith, A. et al. Impact of age and socioeconomic status on treatment and survival from aggressive lymphoma: a UK population-based study of diffuse large B-cell lymphoma. Cancer Epidemiology (2015). doi:10.1016/j.canep.2015.08.015 5. Wang, H.-I. et al. Treatment cost and life expectancy of diffuse large B-cell lymphoma (DLBCL): a discrete event simulation model on a UK population-based observational cohort. Eur J Health Econ 1–13 (2016). doi:10.1007/s10198-016-0775-4 As part of the partnership with the NHS, the Epidemiology and Cancer Statistics Group routinely conduct clinical audits across the study area. These audits use YHHN data to examine disease management, benchmarking treatment with local and national guidelines. Audit reports are discussed at biannual Network Audit Meetings attended by lead clinicians from the 14 hospitals, as well as patient representatives. In addition, audit reports are available to all Network clinical staff via the members website. With respect to research outputs, traditional publication routes (peer-reviewed, open access publications and conference presentations) and the HMRN website (www.hmrn.org ) will be used to disseminate findings to local, national and international practitioners and academics. The peer-reviewed journals targeted are likely to be similar to those that we have already published in: British Journal of Cancer, British Journal of Haematology, Blood, British Medical Journal Open, Cancer Epidemiology, Journal of Clinical Oncology, PLoS One, and Value in Health among many others. To ensure accessibility, all peer-reviewed reports will be published under creative commons attribution 4.0 licence (CC BY); support for this is included in all grant applications. In addition, findings will be disseminated at conferences; those that are regularly attended include the National Cancer Intelligence Network (NCIN) meetings, and conferences run by the American and British Societies of Haematology (ASH & BSH), European Haematology Association (EHA), National Awareness and Early Detection Initiative (NAEDI), and the Palliative Care Congress. Outputs utilising the requested data will begin soon after data receipt, and will continue for a minimum of five years. All outputs will follow guidelines on disclosure control and will only contain aggregated data with small numbers suppressed.

Processing:

YHHN has registered over 25 thousand cases of haematological malignancy and has approval which has permitted linkage of this cohort to ONS Mortality, cancer and HES data. The University are interested in the causes of these diseases, as well as investigating and monitoring the short-term and long-term health care activity of patients with these complex cancers. YHHN was established in 2004 specifically to provide robust generalisable data to inform clinical practice and research. It is predicated on NHS infrastructures, and is a collaborative venture between University researchers and clinicians. All diagnoses, including disease progressions and transformations, are coded to the latest WHO classifications by clinical staff at a single integrated haematopathology laboratory that contains all of the technology and expertise required for diagnosis and on-going monitoring; and all patients have full treatment, response and outcome data collected to clinical trial standards. Data will be stored and processed at the Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York. Data will be stored on a Microsoft SQL server running on a secure Windows Server and will only be accessible by staff within the Epidemiology and Cancer Statistics Group. No identifiable data will be shared with third parties.

Objectives:

The aim of the study is to: 1) examine the disease management of haematological cancers and benchmark treatment with local and national guidelines 2) examine how illness and healthcare patterns among patients with haematological cancers differ from those of who do not have these cancers. Patients with haematological cancers are from the Yorkshire and Humberside Haematology Network (YHHN). For clarity the cohort is referred to in this application as the YHHN cohort. It has been collected as part of the activities of the Haematological Malignancy Research Network (HMRN) www.hmrn.org. YHHN is a specialised population-based register recording and analysing data on all patients diagnosed with haematological cancers (leukaemias, lymphomas and myelomas) in the Yorkshire and Humberside area. Since its start in 2004, YHHN has registered over 25,000 patients with haematological malignancies. To examine disease management and treatment across the full patient pathway, the University now wish to link secondary care and mortality data to supplement the disease and treatment data collected in YHHN. Comparisons between YHHN patients and persons who do not have a haematological cancer will also be made using an anonymised sample from the general population (Covered under a separate data sharing agreement NIC-06759 ) The proposal has undergone peer review and is funded by Bloodwise (Reference 06001) and Cancer Research UK (CRUK grant number C9474/A18362).


Project 7 — DARS-NIC-50329-G1L1P

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 Outpatients

Benefits:

With more than 60,000 admissions every year and an estimated annual cost of two billion pounds in direct healthcare costs alone, hip fractures represent a large proportion of the total NHS activity. The Best Practice Tariff (BPT) for hip fracture aims to improve the quality of care for this patient group by incentivising treatment according to best clinical practice. It rewards the achievement of a number of specific care standards, for example time to surgery, prevention of falls and involvement of a geriatrician throughout the care pathway. Financial incentives, such as those provided by the BPT, have the potential to influence provider behaviour and can be instrumental in improving quality of care and reducing costs. The current evidence base is insufficient to help inform decisions about future refinements and roll-out of BPT tariffs. If BPTs are not cost-effective, then the associated resources might be better invested elsewhere. CHE's proposed comprehensive review and evaluation of the effectiveness and cost-effectiveness of the hip fracture BPT will help ensure the efficient use of resources in the NHS, by demonstrating whether the benefits of the programme measured by patient health outcomes outweigh its opportunity cost. The work is commissioned by NHS England, and will provide the policy makers with the evidence of cost-effectiveness of the BPT tariff for hip fracture. This will include the information on whether the BPT works as intended, whether the tariff is set appropriately or there should be changes made to it. CHE will give recommendation for future development of the BPT tariff, not only for the hip fracture, but also for other clinical areas. NHS England will be able to use the information to update their BPT pricing policies and create better incentives for hospitals to provide high quality care to patients.

Outputs:

CHE shall be providing quarterly reports to NHS England for the duration of the project, with a final report due in December 2017. This will be converted into a scientific article for publication in an international journal, the hope being that this is published during 2018. The quarterly reports will show CHE's progress with the research project and are likely to contain preliminary results as well as description of methodology. Research will be done in different steps, for example, data preparation, descriptive statistics, econometric modelling. CHE will convey these steps in an interim report. Different methodology will be used in the work (for example different econometric methods, Ordinary Least Squares (OLS), Generalised Linear Model (GLM)) and the results are likely to change according to the method used. All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide. In the article, CHE will report the methodology of the research project, including details on econometric method. CHE will provide the readers with descriptive statistics of the data as well as give an overview of the findings.

Processing:

The University of York’s CHE holds a set of pseudonymised HES data for the years 1989/90 to 2015/16 plus vital status at 7, 30, 90 and 365 days post-date of admission derived from ONS mortality data. This data was provided under a separate Data Sharing Agreement DARS-NIC-84254-J2G1Q. CHE will extract and utilise a subset of this data for use in this project. Once extracted, the subset will not be relinked with the ‘master’ dataset. The Royal College of Physicians (RCP) hold the National Hip Fracture Database (NHFD) at Crown Informatics. Crown Informatics will extract the identifiers of each patient whose data is held in the NHFD and will assign a unique patient ID to each patient (ID#1). This ID will not be present in the NHFD and will not be retained by RCP once transferred. Crown Informatics (on behalf of RCP) will securely transfer a file containing the patient identifiers (NHS Number, DoB, Postcode & Sex) plus the unique patient ID (ID#1) to NHS Digital. No clinical data from the NHFD will be supplied to NHS Digital. NHS Digital will link the identifiers to its HES patient index and extract the matching HESIDs (ID#2). The HESIDs will be encrypted using the same encryption key as used for DARS-NIC-84254-J2G1Q [the other DSA]. NHS Digital will produce a bridging file matching the NHFD ID (ID#1) with the encrypted HESID (ID#2). Additionally NHS Digital will assign to each patient a unique study ID (ID#3) that is not common to the data supplied under DARS-NIC-84254-J2G1Q [the other DSA]. NHS Digital will supply the bridging file to CHE. Crown Informatics will flow pseudonymised NHFD data containing the unique NHFD ID (ID#1). Crown Informatics will then destroy any record of the unique NHFD ID (ID#1) that could be used to relink that ID to identifiers held in the NHFD. NHS Digital will require HQIP to ensure that ID#1 is destroyed by Crown Informatics once the audit data has flowed to the University of York and NHS Digital could seek confirmation from HQIP that this condition has been imposed. CHE will use the encrypted HESID (ID#2) to extract the relevant pseudonymised HES + ONS/derived mortality data from the ‘master’ dataset. CHE will use the bridging file to link HES data (and linked derivations) to the pseudonymised NHFD data. CHE will remove from the linked dataset both the NHFD ID (ID#1) and the encrypted HESID (ID#2) leaving only the unique study ID (ID#3) as a remaining patient identifier ensuring the data is pseudonymised and cannot be relinked back to identifiers by CHE, RCP, or Crown Informatics. The linked dataset will be held and maintained separately to the data provided to CHE under DARS-NIC-84254-J2G1Q and will not be linked with any other data. This is a retrospective observational study using a regression-based case-control approach. The cost-effectiveness of the hip fracture BPT will be evaluated using an interrupted time series approach, as well as a difference-in-difference approach with two control groups: 1. Non-English providers that are not subject to the BPT but are included in NHFD 2. High vs low performing providers in previous years All analyses will employ appropriate econometric techniques such as Hierarchical Generalised Linear Modelling to isolate the effect of BPT achievement from that of patient characteristics (i.e. case-mix). These models are appropriate for the non-normal distribution of outcomes and clustering of patients in providers. Data quality and completeness will be assessed prior to analysis. If more than 5% of data on key outcome or explanatory variables are missing CHE will employ multiple imputation techniques to address the effect of the missing data. Changes in mortality will be translated into quality-adjusted life years (QALYs) using life expectancy data, population health related quality of life (HRQoL) data, and utility values from the UK general public. This will allow CHE to express all patient health outcomes in terms of a common metric, QALYs. The cost of care to the purchaser will be calculated as the sum of HRG base tariff payment for hip fracture treatment, BPT bonus and cost of additional activity in post-acute care not covered by the BPT, including A&E attendances, outpatient appointments, and emergency readmissions. The costs to hospitals and other providers of delivering care according to BPT requirements will be assessed using reference cost data and length of stay data. Cost-effectiveness will be calculated as incremental cost per QALY. CHE will determine the probability that the hip fracture BPT is cost-effective over a range of different valuations for a unit gain in QALY. Authorised users Only substantive employees of CHE will have access to the data and will access the data only for the purpose set out in this application.

Objectives:

The objective of this research is to assess the cost-effectiveness of the hip fracture Best Practice Tariff (BPT) from an NHS perspective by measuring its impact on process quality and outcomes and comparing it to its cost implications. To this end, the University of York, Centre for Health Economics (CHE) will explore how the introduction of the hip fracture BPT and subsequent changes to it and the national tariff have affected: 1. Achievement on the incentivized process quality standards, 2. Patients’ health outcomes (i.e. mortality and quality adjusted life years) and the occurrence of adverse events (infections, readmissions), 3. Cost to the purchaser of care. Furthermore, to explore why producers may respond differently to the BPT, CHE will explore: 4. How the BPT has affected providers’ unit costs, 5. How improvements on specific quality standards correlate with patients' health outcomes, 6. How improvements on specific quality standards correlate with costs and how this relationship changes as achievement levels improve, 7. Which elements of the BPT for hip fracture are the hardest to achieve (i.e. their level) and offer most scope for improvement (i.e. provider variability in average achievement), 8. Whether providers with a positive profit margin (tariff and BPT bonus net of unit costs) are more responsive to the BPT than those with a negative profit margin. CHE's proposed research project differs from previous evaluations of the BPT in that it evaluates both short- and long-term effects of the introduction of the BPT and explicitly links improvements in process quality to outcomes and costs. This allows, for the first time, a full evaluation of the cost-effectiveness of the BPT.


Project 8 — DARS-NIC-73974-P0L1Z

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2018/03 — 2018/05.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

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

Benefits:

The PREVAIL study will provide evidence on whether AM-PICCs reduce infections and are cost-effective in improving health of preterm babies. The question of the effectiveness and cost-effectiveness of AM-PICC for preterm babies is of high importance to the NHS. Survival in neonatal care has improved remarkably over time, but the rates of permanent neurological disability in preterm babies are high and have not improved. For example, more than 1 in 4 babies with gestations of less than 26 weeks have a serious disability at 2 years. Infections increase the risk of neurological disability. Consequently, interventions that reduce the risk of infections will reduce the burden of disability in premature babies. AM-PICCs have been shown to be effective in reducing blood stream infections in children and adults. However, there is no evidence on their benefits in preterm babies, who are at a high risk of infection. Given the lack of evidence on benefit, and their increased costs compared to the standard PICC, NHS neonatal units currently use the standard PICC. The PREVAIL study will address this gap in knowledge by finding out whether AM-PICCs reduce the risk of infections in preterm babies, and whether this reduced risk justified their increased cost. The findings of the study will help hospitals and policy makers to decide whether to implement AM-PICCs or not. To inform these decisions, PREVAIL will present the results to policy makers in a report to NIHR-HTA in which explicit research recommendations and implications for practice will be made. Findings and recommendations for practice will also be presented at clinical conferences and in peer reviewed journal publications. Findings will be fed back to neonatal units and regional neonatal networks through the Neonatal Data Analysis Unit. It is expected that, thanks to the PREVAIL study, hospital managers and clinicians will have evidence about how good are AM-PICC vs. standard-PICC in preventing infections, improving health and reducing costs. This evidence will inform their decisions about which type of PICC to buy for neonatal care units. We expect this evidence to be used as soon as it is reported, in late 2018 – early 2019. Parents will have a better understanding about the risks of infection and their consequences to the health related quality of life and life expectancy of their babies, and how the different types of PICC can prevent infections. PREVAIL will disseminate this information via Bliss, as soon as the results are available in late 2018 – early 2019. PREVAIL cannot give a date for benefits to the NHS being realised as any benefits depend on many factors, including the results of the study (i.e. whether there are any clinical and cost benefits or harms of AM-PICCs and how large and certain these effects are) and on other barriers and facilitators of implementation. PREVAIL’s aim is to disseminate and explain the findings of the study to policy makers, service providers and the public so that decisions can be made about impregnated CVCs and any benefits to the NHS can be realised. If results show an important benefit of AM-PICCs, PREVAIL will advocate for the findings to be incorporated into national guidance to neonatal units and to be reviewed by NICE. PREVAIL will also advocate for national monitoring of uptake of AM-PICCs (if findings are positive) through national audits.

Outputs:

The outputs of this research are an understanding about whether AM-PICC compared with standard-PICC reduces the risk of infections and their complications, including death, and the consequences for NHS costs. The NHS makes decisions on which interventions to fund based on information on their effect on health and costs. Cost is important given that the NHS has limited funds; hence cost savings can release funds to be invested in other interventions that improve health. Conversely, interventions that are more costly may warrant funding if they improve health over and beyond the health forgone due to disinvesting in other interventions. In this context, hospitals should invest in AM-PICCs if AM-PICC prevent infections and are good value for money. In other words, AM-PICCs may be cost-saving, in that preventing infections may reduce the cost of hospital care; or AM-PICC may be more costly, but their additional costs are offset by the gain in health-related quality of life and/or life expectancy, from the prevention of complications due to infection. The UoY, UoL and UCL will report the output of the study in a number of outlets; the outputs will be produced in an appropriate way depending on the audience: • NIHR Health Technology Assessment monograph detailing the methods and the results of the PREVAIL study. This includes: the methods of the PREVAIL trial, the methods and results of the effectiveness analysis on the risk and short term consequences of infection, and the methods and results of the economic analysis on the short and long term consequences of infections in health-related quality of life, life expectancy and costs. The expected publication date is 2019, and it is open access to all readers. • Peer-reviewed publications in high impact journals such as Paediatrics. PREVAIL envisage that the UoL will lead at least one peer-reviewed publication on the effectiveness analysis and that the UoY will lead at least one peer-reviewed publication on the economic analysis. These will be submitted by the end of 2018. Given the long lead times required for peer-reviewed papers, publication will likely be in 2019 but unfortunately this cannot be more specific. The publications will be deposited in each institution open access repositories or published in open access format. • Presentation of the results at national and international conferences and neonatal network meetings, throughout 2018 and 2019. • The results will be shared with the parents of the PREVAIL babies, through the PREVAIL website. • The results will also be shared with user representatives such as via the Bliss parent newsletter, website and social media. Examples of this kind of summary can be seen here http://www.bliss.org.uk/achievements The NIHR monograph, peer-reviewed publications, and presentations at conferences are targeted at clinicians, hospital managers, and researchers. Clinicians make decisions about which type of PICC to use, and therefore are ideally placed to use this research to directly inform the care provided to preterm babies. Clinicians and hospital managers are involved in purchasing decisions about which type of PICC to obtain. Researchers can take the results of this study forward and continue to improve the understanding about infections in preterm babies and how to prevent them. Health economists working in the area of neonatal care, for example, may be interested in PREVAIL’s methodological approach. The outputs disseminated by Bliss are targeted at parents and aim to improve their understanding about the risks and consequences of infection and whether AM-PICC vs. standard-PICC can prevent them. This will help parents understand the evidence on which decisions affecting their baby are based on. The output of the analysis will be reported only in aggregate format as average and standard deviation of the cost of hospital care. Small numbers will be suppressed in line with HES analysis guide.

Processing:

The UoL holds the PREVAIL trial database. This includes identifying details of the participating babies plus details of blood stream infections, resistance, antibiotics and feeds. Other than the Date of Birth, no identifiers would be shared with the UoY or UCL, nor linked with the data to be supplied by NHS Digital. The UoL will send to NHS Digital the babies’ identifiers (NHS number, date of birth, post code and the PREVAIL trial ID). The UoL will also send the time period for which the data is requested for each baby, which is between the date of randomisation and 183 days post randomisation. NHS Digital will extract the relevant HES records for each baby and, if applicable, the date of death sourced from the Personal Demographic Service (PDS). NHS Digital will link the hospital records and date of death to the PREVAIL trial ID and strip the dataset of any personal identifiers (date of birth, NHS number, postcode). NHS Digital will securely transfer the dataset to the Centre for Health Economics (CHE) at UoY. The data will be saved directly to the CHE data server via secure LAN connection. The data transfer across the LAN network is not encrypted but secured by the internal network security of the UoY (data is not copied outside of the internal network). Additionally, the UoL receives data from the Paediatric Intensive Care Unit (PICU) linked to the PREVAIL trial ID from the Paediatric Intensive Care Audit Network (PICANet). This data contains HRG code and length of stay at the PICU plus date and type of discharge. UoL will provide pseudonymised data from PICANet linked to the PREVAIL trial ID to the UoY. The UoY also receives pseudonymised Neonatal data linked to the PREVAIL trial ID from Public Heath England’s Neonatal Data Analysis Unit (NDAU). This data contains HRG code and length of stay at the neonatal unit plus date and type of discharge. The UoL will also supply to the UoY a copy of the data collected during the PREVAIL clinical trial (PREVAIL dataset). This copy of the PREVAIL dataset will contain a minimum of personal information about the PREVAIL babies: trial ID, date of randomisation, date of birth, and relevant data that has been collected by the UoL from the recruiting hospitals during the trial. Date of randomisation is required to calculate the hospital length of stay during the PREVAIL trial follow-up period. Date of birth is required to ascertain whether there are differences in costs or health outcomes by the baby’s age at randomisation and trial enrolment. From the HES and PDS data supplied by NHS Digital, the UoY will create a dataset containing the PREVIAL trial ID, date of death if death occurred, and date of discharge if method of discharge from hospital is death. This dataset will be encrypted and sent via the access controlled UoY drop-off service to the UoL. These are the only data fields sent from the UoY to the UoL. Using the trial ID, the UoL will link this dataset to a copy of the PREVAIL trial dataset stripped of personal identifiers. The UoL will use these data to determine the effect of AM-PICC vs. standard-PICC on the risk of death and the time to death. The UoY will use the NHS Digital dataset to calculate the cost of inpatient care, outpatient care and accident and emergency care for each PREVAIL baby. The UoY will link the cost of inpatient care, outpatient care and accident and emergency care, and date of death to the data supplied by UoL (described above). The UoY will use the date of death to calculate survival over the follow-up period. This will inform the calculation of survival and quality-adjusted survival in the decision model. The three cost elements (cost of inpatient care, the cost of outpatient care and the cost of accident and emergency care) do not constitute the full cost of hospital care for the babies enrolled in the PREVAIL trial (the PREVAIL babies). In order for the total cost of hospital care to be calculated, data is required on the hospital stays by the PREVAIL babies in the neonatal care unit and in the paediatric care unit. Data on hospital stays in the neonatal care unit is held in the National Neonatal Research Database (NNRD). Data on hospital stays in the paediatric care unit are held in the Paediatric Intensive Care Audit Network database (PICANet). The PREVAIL babies have all had stays in the neonatal care unit, since it is the setting where the trial took place and the babies were recruited. Babies in the neonatal care unit may transfer to the inpatient wards if surgery takes place, such as surgery for retinopathy, which is common in preterm babies. Therefore, if some babies have had surgery, this additional resource use will be recorded in HES inpatient rather than in NNRD. Babies can be hospitalised in a paediatric unit, which is recorded in PICANet, if they were discharged home but have required more hospital care subsequently. This is because babies, if readmitted to hospital, are admitted to the paediatric unit, rather than the neonatal unit, due to concerns about infections. Babies may be seen at outpatient appointments for follow-up, and this data is stored in HES outpatients. Accident and emergency admissions, if they occurred, will be recorded in HES accident and emergency. For these reasons, the UoY, the UoL and UCL have sought hospitalisations data from NNRD, PICANet and HES. In summary, for each PREVAIL baby, the UoY will calculate: • The cost of neonatal care, from data held in NNRD. • The cost of paediatric care, from data held in PICANet. • The cost of inpatient care, from data held in HES inpatient. • The cost of outpatient care, from data held in HES outpatient. • The cost of accident and emergency care, from data held in HES accident and emergency. Summed up together, these 5 cost elements constitute the cost of hospital care for each PREVAIL baby. The UoY will link the 5 cost elements to the PREVAIL dataset. The objectives are: • To determine whether having an AM-PICC or a standard-PICC has a direct impact on costs, whether infection has a direct impact on costs, and if so, in which cost element. • To estimate the cost of hospital care by whether infection occurred and by whether death occurred, which will inform the decision model for the health economic analysis. • To investigate clinical characteristics that may predict the cost of hospital care and their risk of infection. These characteristics will be used to determine whether there are babies for whom AM-PICCs or standard-PICCS are more beneficial and more cost-effective, and therefore should be prioritised for receiving them. UCL will not have access to the individual level data, but it will collaborate in the development of the methods and interpretation of the results. The UoY will store and archive the data used for the health economic analysis. Of the NHS Digital data, this is date of exit for reason of death, and hospitalisations recorded in HES inpatient, HES outpatient and HES accident and emergency. The NHS Digital data will be stored for the duration of the analyses. The derived data (e.g. hospital cost for each baby) will be held for minimum of 10 years, in line with data retention requirements stipulated by the funder (NIHR) and a maximum of 15 years, in line with contractual agreements with the study sponsor (UCL). These data will be encrypted and held on central IT system with backup provided by IT services. The UoL will store and archive the data used for the effectiveness analysis. Of the NHS Digital data, this will consist of the the date of death (derived from the PDS date and/or HES discharge dates) of the PREVAIL babies who died within the follow-up period of the PREVAIL trial (183 days). The personal information on the PREVAIL babies is stored by the UoL on a networked filestore with access restricted (via ACL’s) to central IT staff who maintain the filestore and CTRC staff with a demonstrated need to access the files. The persons at the UoL and at the UoY conducting the processing activities involving data from NHS Digital have no access to the personal information on the PREVAIL babies other than date of birth, date of randomisation, and, if applicable, ‘date of death’ (i.e. PDS date and/or HES discharge date). There will be no attempt to identify the PREVAIL babies from this data. The UoL holds the PREVAIL patient identifiers separately and unlinked, and will not link the identifiers to the data received from NHS Digital. The individuals with access to the data are all direct employees of the UoL or UoY. For UoY, only members of CHE who are authorised to access sensitive data by the CHE liaison officers and who require access to these data as part of their research activities will be allowed to use the system. All staff members are required to comply with the department’s and the university’s policies on the handling and usage of research and sensitive data. For UoL, all staff members are required to comply with CTRC SOP’s and University Policies on the handling and usage of research and sensitive data. All CTRC staff members undertake data protection training on an annual basis. The data requested will only be used to calculate the cost of hospital care, risk of death and time to death for each baby taking part in PREVAIL over the 183 days follow-up period as detailed. The data will not be used for any commercial or marketing purposes; the data will not be provided in record level form to any third party. The outputs of the analysis will be reported in aggregate form as average and standard error. All outputs will be aggregated with small numbers suppressed (in line with the HES Analysis Guide).

Objectives:

The University of Liverpool (UoL), the University of York (UoY) and University College London (UCL) jointly require HES data and demographic data (date of death) for use in the PREVAIL study. The PREVAIL study is a randomised controlled trial to determine the clinical and cost-effectiveness of using antimicrobial and antifungal impregnated peripherally inserted central venous catheters (AM-PICC) in very preterm babies compared with standard-PICC. It is funded by the National Institute for Health Research - Health Technology Assessment (NIHR-HTA) programme Recruitment started in August 2015 and finished on the 11th January 2017 following which 828 babies were recruited via their parent(s)/guardian(s) throughout England. The parents or guardians of the babies taking part in PREVAIL gave informed consent for the PREVAIL research team to collect information on their baby's routine records from the birth to up to 6 months following their inclusion in the study. The trial has three Data Controllers. UCL, UoY and UoL collaborate in deciding the appropriate methods for analysis and on the interpretation of the results. The co-principal investigators are (respectively) an employee of UCL and an employee of Bradford Teaching Hospitals NHS Foundation Trust who is the honorary chair at the Hull York Medical School (a partnership between the University of York and the University of Hull). The UoL runs the PREVAIL trial and will conduct the effectiveness analysis. The UoY will conduct the health economic analysis. UCL, as co-PI, will oversee the study. The UCL co-PI will only have access to results in the aggregate form, but will collaborate in the planning of the analyses. Given this involvement, UCL is a co-data controller although not data processor of the patient level data. The individual at UCL will only have access to aggregated results from the data processors within this agreement which may contain small numbers. Bradford Teaching Hospitals NHS Foundation Trust will have no input in the planning of the analyses but will assist the team in the interpretation of the results. The input of the Bradford Teaching Hospitals NHS Foundation Trust co-PI in the PREVAIL project is centred in the conceptualisation, supervision and design of the clinical trial, interpretation of the results and application to clinical practice. Bradford Teaching Hospitals NHS Foundation Trust will have no access to the data and will only have access to the aggregated results which are suppressed in line with the HES Analysis Guide. For these reasons, Bradford Teaching Hospitals NHS Foundation Trust is not a data controller nor a data processor. The University of Liverpool (UoL) and University of York (UoY) are co-data processors because they will have access to the individual level data and conduct the analysis. The UoL will send the identifiers of the babies enrolled in PREVAIL to NHS Digital, since it runs the PREVAIL trial and stores the personal data. Neither UCL nor the UoY have access to this personal information on the PREVAIL babies. The PREVAIL study has 3 major work streams: 1. Randomised controlled trial comparing AM-PICC with standard-PICC in reducing infections and associated complications during the stay at the neonatal care unit. This is led by the University of Liverpool (UoL). 2. Health economic analysis comparing AM-PICC with standard-PICC in improving health-related quality of life and life expectancy, and their impact on costs of health care. This is led by the University of York (UoY). 3. Generalisability analysis to understand the risk of infection across the various neonatal units. This is led by the University College London (UCL). The PREVAIL study will use NHS Digital data to inform Workstream 1, namely about whether the type of PICC affects the risk of death, and Workstream 2, namely on the cost of hospital care and risk of death by type of PICC. The UoL will evaluate whether AM-PICC avoids infections (primary outcome) and other adverse health outcomes, including risk of death and time to death, compared with standard-PICC. In order to compare risk and time to death over the 183 days of follow-up, the UoL requires information on the date of death over the 183 days of follow-up. It is necessary to identify the date of death to calculate the effect of AM-PICC vs standard-PICC on mortality using appropriate time to event methods. Comparing risk of death between groups using information on whether death occurred, without access to the exact date of death, will risk diluting any effect between the two groups, and increases the risk of bias. The UoL will obtain the data on date of death from PDS and date of discharge (if method of discharge is death) from HES. Previous studies suggest that there are some inconsistencies in routine records. Having the two sources indicating date of death will allow the UoL to determine whether there are inconsistencies in records, and if inconsistencies are found, to present a sensitivity analysis on the effect of AM-PICC vs. S-PICC on the time to death under each data source. The purpose of this sensitivity analysis is to understand whether using a different data source has an impact on the effect of AM-PICC vs. S-PICC. The UoY will conduct the health economics analysis. The health economic analysis will evaluate the costs to the NHS of using AM-PICC or standard-PICC, and compare those with the health outcomes, namely health-related quality of life and life expectancy, under the two options. The objective of the health economic analysis is to inform a decision of whether the NHS should invest in AM-PICC for all or some preterm babies. Health economic evidence is important for the NHS so that clinicians can make an informed decision on whether a specific type of PICC is good value for money. The NHS runs a fixed budget, therefore if additional funds are invested in some interventions, other interventions cannot be funded. This means that an intervention is good value for money if it is better for health and cost saving, or it increases costs but this cost increase is offset by the gains in health, compared to other interventions that could have been funded. The health economic analysis has five components: (a) comparison of health care costs between trial groups, (b) decision modelling to extrapolate the health outcomes and health care costs from the 183 days follow-up to the expected lifetime of the babies, (c) value of information analysis on the key sources of uncertainty, (d) value of implementing the cost-effective intervention in the NHS, and (e) estimate of the costs of a blood stream infection to the NHS. Component (a) and (b) are relevant to this application. Component (a) cost comparison will identify the health care resource use recorded for each PREVAIL baby and cost it using the appropriate unit cost. It will indicate whether there are differences in cost between trial group over the 183 days of follow-up and the magnitude of any differences. Component (b) decision modelling will simulate the health outcomes (health-related quality of life and life expectancy) and health care costs of the PREVAIL babies to their expected lifetime. The decision model requires information on the costs of the PREVAIL babies by trial group and health status at follow-up; this includes whether babies had a blood stream infection, whether death occurred within the 183 days of follow-up, and its date, so that UoY can calculate survival by trial group and infection group. Hence, the UoY request for data on health care resource use held in HES, and date of death, between randomisation and 183 days post-randomisation, held in PDS.


Project 9 — DARS-NIC-84254-J2G1Q

Opt outs honoured: N

Sensitive: Sensitive

When: 2017/03 — 2017/05.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Mental Health and Learning Disabilities Data Set

Benefits:

The benefits are to be delivered on an ongoing basis in accordance with CHE’s funding agreements, and accessible from CHE’s website: http://www.york.ac.uk/che/. For all of the above projects, various funders have commissioned the work as evidenced by letters supplied. The expected benefits include: Project 1 – to December 2017 The Department of Health uses CHE’s work on of efficiency, effectiveness and productivity to provide numerical answers and context for, among others, Parliamentary Health Committees, the Public Accounts Committee and Public Expenditure Inquiries. By detailing the amount and quality of care secured from NHS resources this work provides evidence about what the NHS is doing with the budget it receives and helps identify opportunities for better use of funding. This supports public accountability and transparency, and helps ensure that the NHS receives the budget it needs to meet health care demands and makes best use of taxpayers’ money. Strong productivity growth for the economy as a whole is important because it increases tax revenues and helps improve wages and living standards. The Office of National Statistics draws heavily on CHE’s work in producing the national accounts, having adopted CHE’s methodological approach to measuring the contribution made by the NHS to national Gross Domestic Product (GDP) and, in assessing this contribution, by accounting for quality of NHS care using measures that CHE constructs from the data supplied by NHS Digital. Given that much government policy is designed to influence GDP, accurate measurement is essential to ensuring that policy is correctly focused and the government is properly held to account for its policies. CHE disseminates the work through various media to inform the public about NHS productivity. For example, this blog in The Conversation (https://theconversation.com/nhs-outpaces-the-uk-economy-in-productivity-gains-53899) has been widely cited to counter misconceptions that NHS productivity is poor. In fact, NHS productivity growth has outpaced that of the economy as a whole since the 2008 recession. Ensuring that the public is fully informed of this fact helps bolster support for the NHS, thereby making it more likely that the government provides the NHS with the funding required to meet the health care needs of the population. Project 2 – to December 2017 CHE’s projects evaluating the performance of health care providers provide evidence to inform national and regional (Yorkshire and Humber – Y&H) policy-makers and providers about the scope and focus of performance improvement and outcome measures, tariff design, and patient choice. The project will assist decisions regarding the provision of services that offer the greatest value for money according to the benefits achieved. In due course this will translate to a more efficient allocation of health care resources, through appropriate budget spend. Where resources are allocated, according to the maximum benefits achieved, with a particular target condition, health benefits ensue. In addition, by working with local decisions makers, to promote the use of evidence based medicine and prospective evaluation, this will increase the potential for future decisions to be grounded on economic principles and consideration of the tradeoffs between choices made. In the short term, the work conducted to inform the NYH Major Trauma Network meeting will help to establish an appropriate, affordable, major trauma rehabilitation service in Y&H. This will translate to patients benefits associated with appropriate rehabilitation, as well as gains to the health service, in terms of reduced length of stay. It is anticipated that the work looking at the care hubs implemented in Y&H, will similarly be used to support commission/de-commissioning decisions regarding the future use of such services. Project 3 – to December 2017 CHE’s evaluations of the impacts of health care policy, organisation, finance and delivery of NHS services are used to inform resource allocation arrangements and the design and direction of future policy regarding the health and social care sectors with CHE’s advice and analyses being sought to feed into White papers and specific government reviews. The main benefits from the projects will be to make better informed policy choices on issues related to: the design of payment systems, including financial incentives; the viability of small hospitals, and the implications from closing them e.g. in terms of restricted patient choices; the case for and against further expansion of private sector providers within the NHS; the usefulness of competition policies to improve access to hospitals (in the form of reduced waiting times); the likely impact of the introduction of the waiting times standards in mental health services, and supporting policymakers (e.g. NHE England and NHS Improvement) to improve the finance, organisation and quality of mental healthcare provision for the benefit of service users. Project 4 – to December 2017 CHE’s projects investigating inequalities in healthcare access and outcomes are helping the NHS address its duty under the Health and Social Care Act 2012 to reduce health inequalities. Following extensive stakeholder involvement and knowledge transfer activity in 2016, our methods were adopted by NHS England in August 2016, as reported in The Guardian, The Independent, and various health media. Indicators of local inequality in potentially avoidable emergency hospitalisation based on our work have been incorporated in the CCG Improvement and Assessment Framework and the associated RightCare information packs distributed to all CCGs, and the NHS Equality and Health Inequalities Team is now actively promoting the use of these indicators by CCGs as part of the NHS quality assurance process for evaluating the equity impacts of local new models of care. As part of our public and stakeholder engagement work for this project, we have developed various visualization tools and public-facing dissemination materials, which are collected together at this website: http://www.york.ac.uk/che/research/equity/monitoring/ Project 5 – to December 2017 The main beneficiaries of the aftermysurgery.org.uk webtool are local patients, their GPs and the Vale of York CCG, which commissions NHS services in the local area. Patients using the webtool will be better informed about the likely effect of surgery on their health, thus allowing them to make informed decisions about their healthcare choices and engage more with their GPs during the consultation. GPs benefit by being able to have a more informed and structured discussion with their patients about their healthcare options. The web tool can help to illustrate the likely impact of surgery on patients’ health, thus helping GPs communicate expectations about the effectiveness of surgery for individual patients. GPs can also draw on the data on local hospital quality to suggest a healthcare provider to the patient. The local Vale of York CCG benefits financially if the information communicated via the webtool leads to reductions in elective hospital activity. This would happen if patients that do not consider surgery to be sufficiently beneficial decide not to undergo the operation but seek other ways to manage their condition (e.g. medical management, physiotherapy). Furthermore, the web tool helps the CCG fulfil its obligation to help communicate information about hospital quality to patients and their GPs. The webtool is to be launched officially by the Vale of York CCG in January 2017. Its usefulness will then be evaluated, allowing for refinement of the interface, and national roll-out in late 2017. Project 6 – to November 2016 The rationale for the project is to assess the economic arguments surrounding the issue of doctor re validation with particular emphasis on measuring changes to medical performance and assessing the cost-effectiveness of the programme in terms of not only increased health related quality of life for the population but also public assurance. We also directly address the extent to which the arguments outlined in the DH pre-programme impact assessment which was used to support the adoption of revalidation are being realised.

Outputs:

The outputs from all of the projects will include peer reviewed papers in academic journals, reports for funders, lay summaries such as newsletters and blogs, and conference and seminar presentations to academic, policy, professional and public audiences. The Centre for Health Economics has a long-established track record in delivery of policy research that utilises HES data, as recognized by the award of the Queens Anniversary Prize in 2007. Examples of recent publications arising from the above projects that have employed the HES data can be found here http://eshcru.ac.uk/publications/index.htm and http://www.york.ac.uk/che/publications/in-house/. Reports will be produced containing aggregate results that show trends over time, differences across providers, commissioners, geographical areas and by patient subgroups and patient characteristics. The results will contain estimated correlations showing associations between patient outcomes and patient characteristics, hospital, institutional, geographic and environmental factors. Statistical results will be presented in interactive spreadsheets or “Dashboards” (e.g. similar to http://health-inequalities.blogspot.co.uk/ which uses QOF data and only contains aggregated data which can be interrogated), tables and maps of aggregate statistics summarising patient characteristics. Reporting will comply with ONS guidelines on disclosure of potentially patient identifiable data i.e. no small numbered cells and figures will be reported. The outputs from each project will be delivered in accordance with CHE’s funding agreements, which run to different timelines with various milestones for each. The key milestones and timelines for each project (including 2015 publications) are: Project 1 - The primary output from this project is the production of an annual update to national NHS productivity figures that incorporates the most recent financial year of data. Under this project, CHE has demonstrated that NHS productivity growth is meeting the requirements of the Five Year Forward View and outpaces that of the economy as a whole. CHE’s figures are widely used to inform policy discourse, with the DoH relying on the information for internal monitoring purposes and for external reporting and response purposes, such as to inform annual Spending Reviews. Under this project, CHE also provides data about the quality of NHS care to the Office of National Statistics that are used in the construction of the national accounts. In 2016, CHE presented productivity figures to the House of Commons Health Committee on the Impact of the Spending Review on health and social care and to the House of Lords committee on the long-term sustainability of the NHS. In addition to the annual update of national figures, CHE also undertakes analyses of variation in hospital productivity and produces short reports or memorandum for the DoH to address specific questions about NHS productivity. CHE presents the work regularly to various audiences, including politicians, policy makers, academics, health professions and the general public through seminars, conference presentations and media appearances. CHE has produced the following outputs during 2016: Bojke C, Castelli A, Grašič K, Howdon D, Street A. Productivity of the English NHS: 2013/14 update. Centre for Health Economics, University of York; CHE Research Paper 126, January 2016. Bojke C, Castelli A, Grašič K, Street A, Productivity growth in the English National Health Service from 1998/1999 to 2013/2014, Health Economics, 2016 DOI: 10.1002/hec.3338. Bojke C, Castelli A, Grašič K, Howdon D, Street A. Did NHS productivity increase under the Coalition government? In: Exworthy M, Mannion R, Powell M. Dismantling the NHS? Evaluating the impact of health reforms. Policy Press, 2016. Aragon Aragon M, Castelli A, Chalkley M, Gaughan J. Hospital productivity growth in the English NHS 2008/09 to 2013/14 Centre for Health Economics, University of York; CHE Research Paper 138, October 2016. Street A, Grašič K. NHS outpaces the UK economy in productivity gains. The Conversation, 29 January 2016. Bojke C, Castelli A, Grašič K, Mason A, Street A. Measurement and analysis of NHS productivity growth: adjusting for the quality of healthcare output. Centre for Health Economics, University of York; draft report to DoH, September 2016. Bojke C, Grašič K, Howdon D, Street A. Alternative sources of primary care data for productivity calculations. Centre for Health Economics, University of York; draft report to DoH, July 2016. Bojke C, Castelli A, Grašič K, Howdon D, Street A. Productivity of the English NHS: 2014/15 update. Centre for Health Economics, University of York; draft report to DoH, November 2016. Project 2 - This project will produce a range of outputs, including reports to support policy decisions and peer reviewed publications. Where appropriate, analysis will also be disseminated to national and local decision makers at formal and informal meetings, including strategic commissioning groups. CHE has produced the following outputs during 2016: Duarte A, Bojke C, Richardson G, Bojke L. Final reports on commissioning of rehabilitation services in Yorkshire and Humber region, produced for York CCG. Delivered January 2016 and June 2016. Both of these reports were presented at NYH Major Trauma Network - Network Rehabilitation Strategy Group Meetings. In 2017 CHE will deliver: • a final report on commissioning of care hubs in the Yorkshire and Humber region, produced for York CCG, expected June 2017; • a final report on the Vanguards delivered in Harrogate, produced for Harrogate and Rural CCG to be delivered June 2017; • publication of analysis undertaken to inform commissioning of rehabilitation services in Yorkshire and Humber region, to be submitted to Rehabilitation journal in February 2017; • publication of analysis undertaken to inform commissioning of care hubs in Yorkshire and Humber region, to be submitted to HSJ journal in September 2017; and • completion of analysis undertaken to determine the use of multiple versus stated stenting in elective PCI, to be submitted to a cardiovascular journal, such as the British Journal of Cardiology. Chalkley M, Aragón MJ. Demand Management for Elective Care: System Reform and other Drivers of Growth: An examination of the factors affecting the growth of elective hospital activity in England from 1998 to 2012 and the implications of those for managing demand for elective activity. Chapter 2 in “Elective hospital admissions: secondary data analysis and modelling with an emphasis on policies to moderate growth", to published in 2017 (https://www.journalslibrary.nihr.ac.uk/projects/11102219/#/). Project 3 - During 2016 the following outputs have been produced as part of the ESHCRU workstream on markets and organizational structures in health and social care markets, and as part of NIHR HS&DR 13/54/40 and Wellcome Trust [ref: 105624] through C2D2: Jacobs, R., Chalkley, M., Aragón, M.J., Böhnke, J.R., Clark, M., Moran, V. & Gilbody, S. (2016) Funding of mental health services: Do available data support episodic payment? CHE Research Paper 137, Centre for Health Economics: University of York. Moran V, Jacobs R, Mason A. Variations in performance of mental health providers in the English NHS: An analysis of the relationship between readmission rates and length-of-stay. Administration and Policy in Mental Health and Mental Health Services Research Jan 2016. 20110.1007/s10488-015-0711-4 Gutacker, N., Siciliani, L., Moscelli, G., Gravelle, H. Choice of hospital: which type of quality matters? CHE Research Paper 111 and Journal of Health Economics, 2016, 50, 230-246. Gaughan, J., Gravelle, H., Siciliani, L. Delayed discharges and hospital type: evidence from the English NHS. CHE Research Paper 133. To appear in Fiscal Studies. Moscelli, G., Sicilliani, L., Gutacker, N., Gravelle, H. Location, quality and choice of hospital: evidence from England 2002/3-2012/13. CHE Research Paper 123 and Journal of Urban and Regional Economics, 2016, 60, 112-124. Moscelli, G., Gravelle, H., Siciliani, L. Market structure, patient choice, and hospital quality for elective patients. CHE Research Paper 139. Centre for Health Economics: University of York. During 2017, CHE will produce reports on ongoing work on quality of NHS versus private hospitals (March 2017), quality of small hospitals (December 2017), effects on patients of hospital closure (December 2017), competition and quality in general practice (March 2017), the effect of competition on hospital waiting times, and waiting time inequalities across (eg due to different quality) and within hospitals (December 2017), as well as papers on mental health funding (December 2017). Project 4 - The primary output from this project in 2016 was the final report to NIHR HS&DR (Ref DRF/2014-07-055) submitted in January 2016 and published in Health Services and Delivery Research in August 2016; together with the annual progress report to NIHR TCC (Ref: SRF-2013-06-015) in December 2016. CHE has produced the following outputs during 2016: Cookson, R., Asaria, M., Ali, S., Ferguson, B., Fleetcroft, R., Goddard, M., Goldblatt, P, Laudicella, M, and Raine, R. (2016). Health Equity Indicators for the English NHS: a longitudinal whole-population study at the small-area level. Health Services and Delivery Research, 4 (26). https://dx.doi.org/10.3310/hsdr04260 Asaria M, Cookson R, Fleetcroft R, Ali S. Unequal socioeconomic distribution of the primary care workforce: whole-population small area longitudinal study. BMJ Open 2016;6(1):e8783 doi: 10.1136/bmjopen-2015-008783 Asaria M, Ali S, Doran T, Ferguson B, Fleetcroft R, Goddard M, Goldblatt P, Laudicella M, Raine R, Cookson R. How a universal health system reduces inequalities – Lessons from England. Journal of Epidemiology and Community Health 2016; doi: 10.1136/jech-2015-206742 Asaria, M., Doran, T. & Cookson, R. (2016). The costs of inequality: whole-population modelling study of lifetime inpatient hospital costs in the English National Health Service by level of neighbourhood deprivation. Journal of Epidemiology and Community Health. Accepted 19 April 2016. doi:10.1136/jech-2016-207447 Sheringham, J., Asaria, M., Barratt, H., Raine, R., & Cookson, R. (2016). Are some areas more equal than others? Socioeconomic inequality in potentially avoidable emergency hospital admissions within English local authority areas. Journal of Health Services Research & Policy. doi:10.1177/1355819616679198 first published on November 15, 2016 Cookson, R. A., Propper, C., Asaria, M., & Raine, R. (2016). Socio-Economic Inequalities in Health Care in England. Fiscal Studies 37(3-4), 371–403. DOI: 10.1111/j.1475-5890.2016.12109 Fleetcroft, R., Asaria, M., Ali, S., & Cookson, R. (2016). Outcomes and inequalities in diabetes from 2004/2005 to 2011/2012: English longitudinal study. British Journal of General Practice. DOI: 10.3399/bjgp16X688381 Gutacker, N., Siciliani, L. and Cookson, R., 2016. Waiting time prioritisation: evidence from England. Social Science & Medicine, 159, pp.140-151 Project 5 - Under this project CHE, working alongside Vale of York CCG, has generated a web tool to support discussions between patients and their GPs about whether to undergo planned surgery. This uses the APD and PROMs data to underpin an online web tool accessed at aftermysugery.org.uk. This tool can be used by patients and their GPs, who input basic demographic data and fill in a pre-operative health status questionnaire. The webtool then returns a predicted post-operative health status, together with national comparator data, displayed in various visual formats. This information is designed to a) help patients decide whether they feel the expected health improvement is sufficiently high to make having the operation worthwhile, b) inform patients about the likelihood of a negative outcome, and c) provide information about which hospitals secure better outcomes for their patients. Work under this project has also established that payments made to GPs as part of the Quality and Outcomes Framework (QOF) dementia review have helped reduce the risk of long-term care home placement following acute hospital admission and that hospital patients discharged to the community have significantly shorter stays if they are cared for by general practices that reviewed a higher percentage of their patients with dementia. This demonstrates that the dementia review can improve the health and well-being of those with dementia and their carers. CHE has produced the following outputs during 2016: Online webtool: aftermysurgery.org.uk inviting prospective patients to “Find out how people like you felt after surgery” Goddard M, Kasteridis P, Jacobs R, Santos R, Mason A. Bridging the gap: The impact of quality of primary care on duration of hospital stay for people with dementia. Journal of Integrated Care 2016; 24:15-25. Kasteridis P, Mason A, Goddard M, Jacobs R, Santos R, Rodriguez-Sanchez B, McGonigal G. Risk of Care Home Placement following Acute Hospital Admission: Effects of a Pay-for-Performance Scheme for Dementia. PLoS ONE 2016; 11:e0155850. Goddard M, Mason AR. Integrated Care: A Pill for All Ills? International Journal of Health Policy and Management 2017; 6:1-3. 10.15171/ijhpm.2016.111 (epub: 13 Aug 2016) Project 6 - final report for Department of Health (reference PR-R9-0114-11002) due April 2017. All products are available free of charge and available to the public via CHE’s website http://www.york.ac.uk/che.

Processing:

Whilst the nature of detailed analysis in relation to each project varies, the broad context of processing is consistent. The following processing activities apply to all of the projects listed above. Data storage: Data will only be stored on the CHE data analysis server and the backup server and will only be accessible within the Centre for Health Economics to individuals who are substantively employed by the University of York. Access to data is restricted to specific individuals according to role and project. Access to sensitive data is also restricted to only those individuals working within projects that are authorised to use sensitive data. Data analyses: CHE will use standard software (e.g. STATA, SAS, R) to analyse the data, derive descriptive statistics and apply multiple regression models to explore the relationships between variables. Data linkage: CHE will run the data through the HRG grouper and attach Reference Cost data using HRG codes and will link HES APC with MHMDS/MHLDS using the bridging file. The data will then be linked: • to aggregated census and other geographical data using the LSOA (Lower Super Outputs Area) variables; • to Quality and Outcomes Framework and the Attribution Data Set using GP codes; and • to accounts and organisational-level data using provider codes. For the revalidation project CHE will use the consultant code to link with General Medical Council (GMC) register data on consultant age, gender, specialty and date and outcome of revalidation. The consultant code is a sensitive code and therefore access will be restricted to researchers involved in the revalidation project. Once linkage is performed for that project CHE will pseudonymise the consultant identifier. None of the linkages CHE perform will enable re-identification of any patients. No data will be linked to record level patient data. Data processing: Analyses of the HES and MHMDS/MHLDS data will involve estimation of statistical and econometric models using software including Stata, SAS and R. The analyses will take account of 1) patient demographic and socio-economic information such as age, gender, ethnicity, carer support, deprivation measures; 2) patient diagnostic information such as diagnoses (co-morbidities), Charlson score, psychiatric history, HRG or PbR care cluster; 3) treatment information such as admission type, specialty of provider, use of the Mental Health Act, community and inpatient services received by patients; 4) quality and outcomes such as PROMs, 30-day survival, HoNOS scores, waiting times, readmissions, and social outcomes such as employment and accommodation status; 5) service level factors such as number of contacts with staff, and delayed discharge. For all projects the data will be used to undertake both cross-sectional and longitudinal analyses, allowing analyses within-year variations and of changes over time.

Objectives:

The Centre for Health Economics (CHE), based at University of York is requesting data for the following projects involving economic analyses of health and social care. Please note that for each of the following projects CHE staff will analyse individual level data from the various datasets. Only aggregated results will be published and disseminated. Almost all of these projects are funded, at least in part, by the Department of Health (DoH) via a major programme of work funded as a Policy Research Unit (PRU) in the Economics of Health and Social Care Systems (http://eshcru.ac.uk/). The aim of the PRU is to inform and guide policy-making in the health and social care sectors by undertaking high quality, robust and policy-relevant research, based on the discipline of economics, thereby helping to improve the health and well-being of the population, reflecting distributional concerns and population diversity. A detailed work programme for the next two years of programme funding is developed in advance in collaboration with both a DoH Stakeholder Group and the PRU’s Advisory Group with meetings being held with each Group every six months. Approximately 20% of funding is reserved for the PRU to respond to short-term responsive requests for research. This process ensures that the work programme can be shaped to reflect enduring and emerging policy concerns. For some projects, additional funding has been secured to enable extended or deeper analyses of the research topic. Under previous Data Sharing Agreements ONS date of death data was supplied. To further reduce the amount of potentially identifiable data items being processed, this data item will no longer be required and the data item previously supplied will be destroyed. In its place, the CHE will retain derived information indicating whether or not the patient was alive 7, 30, 90 and 365 days after admission. In new data, CHE requires flags added to the HES APC data indicating, for each admission, whether or not the patient was alive 7, 30, 90 and 365 days after admission. Under no circumstances will any attempt be made to backward engineer the date of death, and staff will be reminded that such action is prohibited and would be in breach of CHE’s data sharing responsibilities. All of the work involves analysing the data in different ways. For example, an analysis under project 1 may focus on particular specialties, comparison of productivity across hospitals, or may be a broader assessment of national productivity. Many of the statistical methods to be employed require longitudinal data to investigate how changes in patient outcomes (including morbidity, mortality, emergency readmissions, length of stay, admissions for conditions that could be managed in primary care, inpatient admission rates after A&E attendance) are related to changes in policy (including payment policies and incentives), changes in market configurations, changes in organisational structure, and changes in patient characteristics. Pseudonymised patient level information is required to allow for the influence of past utilisation, for demographic factors, for socio-economic factors (e.g. deprivation) linked to the small area in which patients live, and patient distance from hospitals, social care providers, and general practices. It is also essential in investigating the equity implications of policies, market structure, and organisational arrangements. The Principal Investigators and Project Leads are responsible for determining what analyses will be undertaken and what data will be used for each analysis in support of the objectives agreed with the funding organisations. Project 1 - Measurement of efficiency, effectiveness and productivity in the delivery of health care system nationally, sub-nationally and among hospitals; The purpose of this project is to produce information for the Department of Health (DoH) and Secretary of State for Health on efficiency, effectiveness and productivity. In the current economic climate it is particularly important that changes in efficiency and productivity can be identified and monitored. This helps ensure accountability to the public for how the annual NHS budget is spent and to identify opportunities for better use of resources devoted to the NHS. This project provides numerical answers and context for, among others, House of Commons Health Committee, the Public Accounts Committee, Public Expenditure Inquiries, and DoH submissions in support of annual Spending Reviews. The work also contributes to the measurement of productivity of the health service in the national accounts, compiled by the Office of National Statistics. Funder: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001). CHE Lead: Andrew Street This project will use only the following data: HES APC 1998/99-2015/16; A&E 2007/08 - 2015/16; Critical Care 2011/12 – 2015/16; Outpatient 2011/12-2015/16; PROMs 2009/10 – 2015/16. Most of the work undertaken under this project involves measurement of productivity over time, hence the need to hold the data from 1998/99. It is also necessary to construct aggregated measures of NHS output and quality based on what has happened to each individual patient in whatever setting care has been delivered, hence the need for patient-level information. The project also requires use of the sensitive PROMs data as measures of the quality of health care. Project 2 - Evaluation of differences in the performance of health care providers in terms of the amount and cost of provision and in patient outcomes including mortality and self-reported morbidity; The purpose of this project is to produce information for National and local decision makers, such as the Department of Health (DoH), Clinical Commissioning Groups (CCGs) and Local Authorities (LAs), to assist decisions regarding the provision of services that offer the greatest value for money according to the benefits achieved. Delivering appropriate, high quality, health care services to patients, in the most cost-effective way, are important priorities in any health care system. Advancing these priorities requires the analyses of such things as variations in practice and of the relationship between patient outcomes and hospital and consultant workload; which dimensions of performance are most important to patients; and the extent to which financial incentives motivate best practice. Ultimately this project informs the assessment of the most efficient and cost-effective way of delivering a particular service. This helps ensure accountability to the public for how the annual NHS budget is spent and to identify opportunities for better use of resources devoted to the NHS. The project is designed to develop a more systematic evidence base that will allow policy-makers, providers and commissioners to develop policies to achieve efficiency and outcome-based commissioning; to publish information on performance in formats that are most useful to the intended stakeholders, and to redeploy resources to produce more efficient mixes of services both within and across the health and social care sectors. Funders: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001). CHE Lead: Andrew Street • National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care Yorkshire and Humber (CLAHRC YH) (Ref NIHR CLARHC YH II 14653) • NIHR SDO Information and Value Based Commissioning - explaining the variation and causes of hospital activity and outcomes (Ref 11/1022/19). CHE Lead: Martin Chalkley • NHS England - Economic evaluation of the Fragility Hip Fracture Best Practice Tariff. CHE Lead: Nils Gutacker • EuroQol Research Foundation (Ref 2016450). The role of EQ-5D value sets based on patient preferences in the context of hospital choice in the national PROM programme in England. CHE lead: Nils Gutacker The work for all these funders will require the sensitive PROMs data to measure patient outcomes. The project will use only the following data: HES APC 1989/90 - 2015/16, Sensitive field: Consultant Code; HES Outpatient 2002/03 - 2015/16; PROMs 2009/10 – 2015/16. Project 3 - Evaluation of the impacts of health care policy, organisation, finance and delivery of NHS services and quantification of differences in health care utilisation, expenditure, morbidity and mortality over time, across geographic regions, health providers, and among different patient groups; The purpose of this project is to produce evidence to inform the Department of Health’s decisions on resource allocation and the design and direction of future policy regarding the health and social care sectors, with CHE’s advice and analyses being sought to feed into White papers and specific government reviews. This project includes understanding which type of “market” for health and social care services – from highly regulated internal markets to fully decentralised market models – best achieves strategic goals. It also includes evaluations of payment policies (including financial incentive schemes) and changes to the organisation of services (e.g. co-location of general practitioners alongside emergency departments) that seek to encourage good quality, cost-effective care and/or facilitate access to timely care. The main aims are to: analyse the potential for use of markets and payment mechanisms in health and social care to improve overall performance; analyse the impact that different payment policies or market configurations can have on prices, outputs, quality and outcomes; explore how the best payment systems and market configurations could be implemented in practice; and establish the effect of innovative organisational forms on costs and quality of care. Funders: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001). CHE Lead: Hugh Gravelle • NIHR HS&DR 10/1011/22 and NIHR HS&DR 13/54/40 Relationships between quality of primary care and secondary care outcomes for people with mental illness. CHE Lead: Rowena Jacobs • Wellcome Trust [ref: 105624] through the Centre for Chronic Diseases and Disorders (C2D2) at the University of York: Finance and organisation of mental health services. CHE Lead: Rowena Jacobs • Health Foundation [ref: 57151] Efficiency, cost and quality of mental healthcare provision. CHE Lead: Rowena Jacobs • NIHR HS&DR (Ref DRF/2014-07-055): Doctoral Research Fellowship - Measuring & explaining variations in general practice performance. CHE Lead: Rita Santos. • NIHR HS&DR (Ref 15/145/06): General Practitioners and Emergency Departments (GPED) Efficient Models of Care. CHE lead: Nils Gutacker The project will use only the following data: HES APC 1998/99 – 2015/16; A&E 2007/08 – 2015/16; Outpatient 2002/03 – 2015/16; PROMs 2009/10 – 2015/16; MHMDS 2011/12 – 2013/14; MHLDS 2014/15 – 2015/16; HES APC Sensitive Psychiatric Fields: Detention category (DETNCAT), Legal group of patient (psychiatric) (LEGALGPC), Legal status classification (LEGLSTAT) The work for all funders will require the use of the sensitive PROMs data to measure morbidity over time. This project will also require use of MHMDS & MHLDS data linked to HES data in order to carry out analyses into the economics around mental health and mental health care provision. CHE is requesting sensitive MHMDS/MHLDS fields and sensitive HES psychiatric fields (Legal group of patient, Legal status classification, and Detention category). These relate to the legal category / legal status of the patient which is an important indicator of patient severity. CHE will need these sensitive data items to accurately control for the impact of detention on resource use and utilisation. CHE needs to check data consistency between HES and the MHMDS/MHLDS and therefore requires sensitive data on legal status in both datasets. Project 4 - Investigation of variation and inequalities of access, utilization, costs, patient outcomes, clinical practice, choice of provider, competition and concentration of health care services across England. The purpose of this project is to produce information that the Department of Health and Office of National Statistics will use to address the NHS’ duty under the Health and Social Care Act 2012 to consider reducing health inequalities. CHE has recently developed new methods of local health equity monitoring for health care quality assurance, which NHS England adopted in 2016. In collaboration with analysts at NHS England, CHE will refine and use these methods and related measures to monitor the progress of national and local NHS organisations in reducing inequalities in healthcare access and outcomes, to gain insight into the determinants of inequalities, and to evaluate the equity impacts of local new models of care. The work will also assist the ONS to conduct distributional analyses of NHS spending for use in constructing statistics about in-kind social transfers. Funder: • NIHR TCC (Ref SRF-2013-06-015) Health equity impacts: evaluating the impacts of organisations and interventions on social inequalities in health. CHE Lead: Professor Richard Cookson • ONS Update of current methodology for allocating social transfers in kind. CHE Lead: Miqdad Asaria The project will use only the following data: HES APC 1989/90 – 2015/16; A&E 2007/08 – 2015/16; Outpatient 2002/03 – 2015/16; Critical Care 2011/12 – 2015/16; PROMs 2009/10 – 2015/16. The work requires the use of sensitive PROMs data to measure patient outcomes in secondary care. Project 5 - Evaluation of the interface between the different sectors of the health care system, including the effects of quality and access of primary care on patient use and outcomes in secondary care; and the relationship between long term care, social care and secondary care utilisation. It has long been understood that health and social care services frequently provide treatment and care for the same individuals, so ensuring that these are ‘joined up’ or well co-ordinated has been an important and long-standing policy objective. In practice, however, both the services and approaches to monitoring these have developed separately, with potential implications for the efficiency and effectiveness of both health and social care. The purpose of this project is to produce evidence that will be used by the Department of Health and commissioners to inform discharge arrangements and the design of integrated care arrangements and to identify opportunities for substitution of different types of health and social care services. CHE shall also be developing an online web tool to inform patients about their likely outcome of surgery to impact on shared decision making in primary care in York. Funders: • Department of Health to the Policy Research Unit in the Economics of Health and Social Care Systems (Ref 103/0001) CHE Lead: Andrew Street • ESRC Impact Accelerator Account - developing an online web tool (Ref A0158801) CHE Lead: Nils Gutacker The project will use only the following data: HES APC 1989/90– 2015/16; A&E 2007/08 – 2015/16; Outpatient 2002/03 – 2015/16; Critical Care 2011/12 – 2015/16, PROMs 2009/10 – 2015/16. This project requires the sensitive PROMs data to measure patient outcomes in secondary care. Project 6 - Evaluating the development of medical revalidation in England and its impact on organisational performance and medical practice. In the past, once they had qualified, health professionals were subject to little or no scrutiny during their career unless their performance gave cause for concerns or there were complaints about them. But in 2012 the General Medical Council introduced a new requirement for all doctors to be “revalidated” at least once every five years while they hold a licence to practise. The purpose of this project is to measure the effect of medical revalidation on patient outcomes, including mortality, emergency re-admission and PROMs for several tracer conditions such as AMI, hip replacement etc., as well as to identify any unintended effects on the supply of medical labour in the English NHS. This project requires HES data to examine the impact of revalidation and related systems for managing medical performance in NHS acute care, looking at individual level and organisational level effects. Evidence on the effectiveness of revalidation will allow policy makers to modify the current system and/or encourage its wider roll-out to other health professions to improve the quality of care provided, thereby benefitting patients in the English NHS and elsewhere. Funder: • Policy Research Programme (reference PR-R9-0114-11002). CHE lead: Nils Gutacker. The project will use only the following data: HES APC 2007/08 - 2015/16; A&E 2007/08 – 2015/16; Outpatient 2007/08 – 2015/16; PROMs 2009/10 – 2015/16. This project requires the sensitive PROMs data to measure organizational performance and the Consultant Code to assess differences in medical practice. CHE confirms that the data under this application would only be used for the six projects listed, and any additional project (whether as part of the DH programme or otherwise) would require a separate approval. Equally individuals working on each project will only be permitted to access the data relating to that project, as identified within this application. Access is granted for each project only to the named individuals associated with that project under authorised user names. Such access is password controlled (with a password reset required on a regular refresh). The controls enable a single copy of the data to be held, reducing security risk associated with multiple copies being provided per project. This model is aligned with similar arrangements for other sizeable research institutions. The access procedures are set out in the University of York’ System Level Security Policy (October 2016), as follows: “Logical measures for access control and privilege management “Permissions to access the data are managed using Window’s Active Directory. Access to datasets is granted to named users only, as approved in the data sharing agreements. Users can store derived datasets in their personal user folders or in shared project folders, where access is granted to individuals working on the respective projects. Users are only allowed to store derived data in project folders if all users who can access the folder also have permission to access the source data according to current data sharing agreements. “Access rights and permissions are reviewed for each data application and re-application. The ADACX IT manager configures user permissions once authorisation has been granted in writing from the CHE liaison officers, who maintain a list of user permissions.” Further, access to data is administered and monitored by the CHE liaison officers through a registry. The registry lists all the projects with relevant Principal Investigator (PI) for which a valid Data Sharing Agreement issued by NHS Digital is in place. Every member of staff working on a project(s) is requested to sign a non-disclosure form on an annual basis. The purpose of this form is to ensure compliance to the Centre for Health Economics and the University of York’s data protection policies, adherence to the Data Protection Act and all its principles, and to the Centre for Health Economics System Level Security Policy. Members of staff who fail to return a signed form by the deadline provided will be excluded from access to the data until a signed form is returned.