NHS Digital Data Release Register - reformatted

The Health Foundation projects

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

The impact of introducing Any Qualified Providers on hospital performance in England — DARS-NIC-90070-F3K4Z

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Charity)

Sensitive: Non-Sensitive

When:DSA runs 2019-04-02 — 2020-04-01

Access method: One-Off

Data-controller type: THE HEALTH FOUNDATION

Sublicensing allowed: No

Datasets:

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

Objectives:

The primary aim of the project is to examine the introduction of the Any Qualified Provider (AQP) scheme in England, on the behaviour of NHS and non-NHS providers with respect to volumes and quality of elective services which will be measured by patients' waiting time. Any qualified provider AQP) means that when patients are referred, usually by their GP, for a particular service, they should be able to choose from a list of qualified providers who meet NHS service quality requirements, prices and normal contractual obligations.

Senior members of the Health Foundation regularly meet with senior representatives from across government, where the Health Foundation’s views are sought on health policy and practice. The findings from this study will be communicated directly through this channel.

The outcomes from the study will provide Department of Health, NHS England and NHS Improvement with the evidence and hard facts on the effectiveness of the introduction of the AQP Programme on the performance of healthcare providers as well as the outcomes on patients.

The Health Foundation believes it has a legitimate interest for acquiring patient data for the purposes of this project.

The Health Foundation is a charity established to support the improvement of healthcare, including healthcare delivery. If analyses produced using patient data indicate how improvements can be made to how health care is delivered, then ultimately patients will receive better health care. The benefits of delivering better health care are essential for ensuring that patients receive good quality and timely diagnoses and treatment, this is critical for managing the health service. If The Health Foundation were not able to use the data requested, a robust evaluation of the AQP scheme could not be undertaken and therefore the public would not be able to benefit from wider implementation of this scheme. Therefore, the purpose of this project, which is to assess the effectiveness of the new AQP scheme aimed to improve NHS delivery, fits within this legitimate interest.

The Health Foundation believes it is necessary to process data relating to individual patients (analysis) for the purposes of evaluating the effectiveness of the AQP scheme. The Health Foundation considers that without these data, it could not undertake a robust evaluation. The methods required to undertake the evaluation necessarily requires the patient data requested.

Note that The Health Foundation will not have access to any identifiable patient data, and so staff at The Health Foundation will not know of the identity of any of the patients whose data are being analysed. This project will be listed on the NHS Digital Data Release Register, and also listed on The Health Foundation website so that the public can view information about how the data will be used. Given the remit of The Health Foundation to improve the quality of health care received, and that the organisation is an independent charity, and that The Health Foundation is committed to transparency, then it would be possible to explain the use of the data to patients. In addition, The Health Foundation has robust controls in place to ensure that any results of the analysis published cannot be used to identify patients, and that a number of other technical safeguards are in place to protect the data (as demonstrated by compliance with the Data Security and Protection Toolkit). Balancing the benefits of the project with the unlikely impact on any individual patient, The Health Foundation believes it will process the data requested fairly.

The Health Foundation believes that it is in the legitimate interests to process the data applied for (which include special categories of data, containing health records of individuals). The Health Foundation exists to help support improvements in public health. The AQP scheme has been identified as a programme that can deliver such improvements; The Health Foundation wishes to use necessary patient data to evaluate this scheme to determine if the scheme can deliver improvements to public health. In addition, The Health Foundation is confident it has the necessary safeguards in place to protect the confidentiality of the data (as demonstrated by compliance with the Data Security and Protection Toolkit), and therefore, any risk to the public by dissemination of the data to The Health Foundation are minimal and are mitigated.

Patient-level data are required, including diagnostic and surgery codes, and geographic information about where treatment was received by patients, throughout time (before and after the AQP programme was introduced).

Patient-level data from HES are required in order to undertake the following:
- Create measures of quality of treatment (for example, volumes of elective surgery such as knee and hip replacements, readmission rates for elective operations). The patient-level data will allow The Health Foundation to extract patient data for these types of treatment to be able to create the quality measures. Then, The Health Foundation will be able to use this quality measure and compare whether quality improved or fell when the AQP scheme was introduced
- In particular, the diagnostic and surgery codes are required to work out which patients receive elective surgery for e.g. knee and hip operations, so that the quality of treatment measures can be constructed
- Admission dates are required to sort out which patients received certain elective treatments (such as knee or hip operations) before or after AQPs were introduced, then it will be possible to determine whether the AQPs improved quality of treatment received over time. In addition, admission dates are required to calculate readmission, which is a potential measure of quality (for example, if a patient has had to have two or more hip operations in a short period, this may infer low quality treatment was provided to begin with).
- Geographies are required because the AQP was introduced only in certain areas, so these data are necessary to work out areas where AQP were introduced and where they were not, to be able to compare the effectiveness of AQP.
The English government introduced two policies to increase the non-NHS supply of care to NHS patients. The first was the new Treatment Centre programme including Independent Sector Treatment Centres (ISTCs). The introduction of ISTCs in 2003 was specifically aimed at expanding capacity in elective care for which there were long waiting lists in disease areas like hip, knees and cataracts. The second policy was the introduction of the Any Qualified Provider (AQP) programme in 2008 which allows licensed non-NHS providers to supply care to NHS commissioners at the same tariff as set for NHS providers. The AQP programme covered all elective hospital treatment in England. Capacity came on stream progressively and by 2011/12 19% of NHS funded elective hip and knee replacements in England were done in the private sector. These policy changes not only increased the capacity of hospital supply in elective services through the non-NHS providers but also gave an additional incentive for NHS providers to improve their quality of services.

The AQP programme was designed to introduce competition in a way that would improve the quality of treatment provided to patients. Reductions in waiting times for elective surgery such as hip and knee replacements are one way of measuring the effectiveness of AQP and this was already been undertaken. The Health Foundation would like to consider whether the AQP affected the quality of treatment provided in addition to changes in waiting times. For example, if a patient has to have many repeat hip replacements in a short spell of time, then it may infer poor quality treatment has been provided. The Health Foundation would like to determine how quality of treatment was affected by increased competition by health service providers when introduced by the AQP programme.

Patient-level data will be used for this project, so the data subjects will be patients who received hospital treatment for e.g. elective surgery in England before and after the time at which AQP was introduced.

AQP was only introduced in certain geographic areas. Therefore, the patients will be grouped into the following control groups and cohorts:
1 – patients who received treatment in hospitals before AQP was introduced
2 – patients who received treatment in hospitals in areas where AQP was introduced
3 – patients who received treatment in hospitals in areas where AQP was not introduced

The Health Foundation will be able to compare the differences in the outcomes in the quality of treatment received by patients in each of these groups so as able to determine how effective the AQP programme was.

As agreed in the original application, data is only being accessed by substantive Health Foundation’s employees and an award holder (on secondment to the Health Foundation) from the Office of Health Economics who has been specifically contracted for this analysis and has signed specific Health Foundation, IG and non-disclosure agreements.

To understand the impact of these two policies, it is important for policy makers (e.g. Department of Health, NHS England and NHS Improvement) to have empirical evidence on how NHS providers and non-NHS providers responded to the scope for increased non-NHS supply in NHS funded elective hospital services. However, such empirical evidence is very limited. Brown et al. (2008) used the Patients Reported Outcomes Measures (PROMs) data to compare the case-mix and patients' reported outcomes of surgery in ISTCs and in NHS providers. They find that the case-mix of patients treated in ISTCs reported slightly better outcome from that in NHS providers. However, there has not yet been any evaluation of the impact of introducing the AQP in England in 2008 on the hospital healthcare supply and quality of hospital services from private providers and its spill-over effect to the performance of NHS providers. This gap motivates the evaluation project. In particular this proposed study will empirically evaluate whether and to what extent the introduction of the AQP reduce patients’ hospital waiting time and increased the supply of hospital volumes. The Health Foundation will also explore how the private and NHS providers interact with each other under this policy context.

Yielded Benefits:

The initial analysis of the data has focused on data management and descriptive statistics of the study sample. These findings had been discussed internally with the project team at The Health Foundation and not disseminated to external stakeholders. A summary of the sample selection process and descriptive statistics obtained is provided below. A representative sample for analysis has been selected from the pool of HES data. This sample comprises HES episodes for elective hip and knee procedures in each year. The data used in this analysis include HES data between financial years 2005/6 and 2008/9. Two types of elective surgeries including hip replacement and knee replacement surgery have been included. Hospital providers have been categorised in either (1) private provider or (2) NHS provider and estimates have been derived to suggest if a MSOA (or PCT) has patients exposed to hip or knee replacement surgeries completed by private providers. Descriptive statistics have been obtained to report: - the number of MSOAs and PCTs in England that exposed to private providers for hip or knee replacement surgeries between 2005/6 and 2008/9. For both types of surgeries, the number of MSOAs/PCTs that exposed to private providers increased between the four year period. - the number of episodes completed between 2005/6 and 2008/9 by provider type. There is an increasing number of episodes that were completed by private providers. The increasing trend is also observed by NHS providers but less dramatic compare to private providers. - the number of providers by type. In general, the overall number of providers and the number of private providers increased over the four year period. In contrast, a decreasing trend is observed for the number of NHS providers. - the waiting time for patients to get treatment in days by years, types of surgeries, types of providers with unit level at PCT/MSOA. - whether MSOAs/PCTs that exposed to private providers up to 2005/06 present different volumes in number of episodes completed and waiting times. The exposure to private providers in an MSOA/PCT will become a benefit through increased competition, in turn reducing waiting times for NHS patients, and improving the quality of hip and knee replacements as observed by changes in revisions relative to primary surgery at hospital level.

Expected Benefits:

The future of provider competition and independent sector involvement remains uncertain and controversial, and the evaluation will provide hard facts to inform a debate characterised more by opinion than evidence. To disseminate the findings through academic conferences will inform the policy makers and healthcare providers about the effectiveness of the AQP policy on the performance of healthcare providers as well as the outcomes on patients.

The evaluation outputs will be widely disseminated to key stakeholders, including policy makers and health/social care providers. The research outputs will provide empirical evidence to the policy makers about the impacts of the AQP policy on the supply of healthcare in the NHS as well as to what extent it improves the output measured by the reduction of waiting time. For instance, one of the aims for introducing the AQP policy was to reduce patients’ waiting time for hospital services. The policy aims to achieve it by allowing more providers to join the market to compete for hospital services contract. However, there is no empirical evidence about the effectiveness of the AQP incentives on different types of hospital providers (NHS/private providers) regarding the reduction of hospital waiting time. The research will provide empirical evidence for this. This evidence will also inform the policy makers about how to improve the design of the incentives in the future.

In particular, The Health Foundation expects that potentially, patients could benefit from this work if it is proved that the AQP programme had a positive effect due to increased competition between local health treatment providers, and was rolled out more widely by e.g. NHS England. The Health Foundation will look to see if the following will be impacted:
- Short waiting times for routine surgery
- Better quality of treatment (and care)
- More efficiently delivered treatment (and care)
- Fewer readmissions (particular for routine elective surgery such as hip and knee replacements)
- Reduced public subsidies for NHS funders due to increased efficiency gains (such as fewer readmissions)
- Reduced mortality

In addition, if the scheme is proven successful, it could potentially be extended to community services, and specialist treatments, which would benefit patients seeking other treatments. Such benefits would be measured and the magnitude of the benefits could be calculated in future work using HES data again.

Outputs:

As well as publishing the work, the evaluation output will be widely disseminated to key stakeholders, for example the English Department of Health, NHS England and NHS Improvement and academic partner.

Data is only being accessed by substantive Health Foundation’s employees and an award holder from the Office of Health Economics who has been specifically contracted for this analysis and has signed specific Health Foundation, IG and non-disclosure agreements. The Office of Health Economics conducts research and provides consultancy services on health economics and related policy issues that affect health care and the life sciences industries. The Office of Health Economics and the Health Foundation collaborate in the dissemination of the findings of this analysis but it is the Health Foundation who ultimately make decisions about the data - thus they are sole data controller.

The Health Foundation originally expected the project to be completed by 31st August 2018. Due to staff changes the analysis has been extended until the first quarter of 2020.

In the second half of 2019, The Health Foundation will expect to publish a report to measure the impact of non-NHS provision on quality of NHS elective orthopaedics. The report will investigate whether exposure to greater competition from independent sector providers had any impact on the quality of elective surgery provided by NHS hospitals, as measured by revisions. The difference between private providers introduced first as Independent Sector Treatment Centres, and later as Any Qualified providers will be considered.

The Health Foundation results will be presented at key national and international conferences as well as the Office of Health Economics lunch time seminar (for some examples see https://www.ohe.org/events). Office of Health Economics seminars consist of 45 minutes presentations of the research findings, followed by discussion with audience for 45 minutes. Each of the participants gets a hard copy of the research paper/journal article. The aims of the seminar include (1) disseminating the research findings to policy makers and academic researchers; (2) providing opportunities to discuss with the key stakeholders. Attendance at the OHE seminars are by invitation only, these invitations are extended to policy makers at DH and NHS England and in the case of this study the specific policy makers who are already aware of the work will be invited to attend.

The Office of Health Economics (OHE) will seek to engage with the public and specifically patients by promoting the work to a number of patient advocacy groups. OHE will establish a webpage which will provide details on the specifics of the project (aims, methods, expected impact) and will be regularly updated with progress as findings and results emerge. The webpage will be written in plain English with simple messaging. Patient advocacy groups will be contacted and directed at the website. In addition, the findings of this project will be disseminated to the public and patients via regular blogs and via social media.

The Office of Health Economics aim to target the following patients group:
· Patient Participant Groups at GP practices and NHS Trusts
· Patient Liaison Group of the British Orthopaedic Association

The AQP policy allows qualified private providers in the NHS England to supply NHS paid hospital service. The policy provides direct incentives for the private providers to improve their performance as well as indirect incentives for the NHS providers through spill-over effect. It is important for the policy makers to understand (1) whether and how this policy might have an impact, (2) whether and how it has impact on NHS or/and private providers, (3) what the impacts are on patients’ outcomes. This information is crucial for understanding the effectiveness of the policy.

The Health Foundation aims to disseminate the findings through seminars and conferences (between 2019 and 2020) and peer- reviewed publications (it is expected from the second half of 2019). It is expected that the research outputs will generate wide interest for the policy/decision makers who are responsible for the healthcare resources allocation in England, providers/managers of the NHS and private hospitals, and academic researchers in the areas of health economics, health services research and health policy. Those colleagues will be the target audience of the seminars, conferences, report and peer reviewed publications. The Health Foundation will contact the key stakeholders directly to make sure that the research outputs are delivered to the target audience. For instance, the participants of the OHE seminar are through invitation only with the maximum spaces of thirty attendees. OHE seminars are held by the Office of Health Economics six times each year. The key stakeholders are regularly invited and attend the relevant seminars. The key stakeholders for the project include policy and decision makers at the DH and NHS England. They will be invited to attend the presentation. In the case of previous projects, the Health Foundation have used these seminars to present work on “Association between market concentration of hospitals and patient health gain following hip replacement surgery”, which was also published on the journal of health service research and policy in 2015 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4268175/). The presentation to the event generated lots of interest from a number of key stakeholders and the team was invited to present at Monitor (NHS Improvement) to discuss with economists there about the practical implications of the findings to the quality of hospital care and hospital market concentration in England.

In addition, the Health Foundation will rely on their strong links with key stakeholders (NHS teams, national policymakers, e.g., NHS England, and patient advocacy groups) to further disseminate the results and maximise the impact of the work. More specifically, the Health Foundation will actively engage with national policy makers, practitioners and researchers on top of the objective of scientific publication. The project will rely on a member of the Foundation’s Communications team to lead on dissemination of findings which will involve additional channels such as TV, radio interviews, articles on national, local and online media.

Example of engagement and key stakeholders:
• Senior members of Health Foundation staff regularly meet with senior representatives from across government, including the Treasury, Department of Health and Arms-Length Bodies (e.g. Monitor, CQC, NHS England, Health Education England).
• Joint projects or collaborations with NHS organisations. One example is the partnership with NHS England in evaluating new models of care outlined in the Five Year Forward view (http://www.health.org.uk/programmes/projects/improvement-analytics-unit).
• Regular engagement with policy makers at all levels on a range of topics where the Health Foundation has particular expertise: policy, data analytics, economics, patient safety and person-centred care. The Health Foundation’s views are regularly sought on health policy and practice, meaning that the findings from these HES-based analyses will be communicated directly with policymakers. One example is the recent engagement of the Economics team with NHS Wales (http://www.health.org.uk/programmes/projects/fiscal-sustainability-nhs-wales), leading to the following report (http://www.health.org.uk/publication/path-sustainability).
• The Health Foundation has a long history of funding programmes across the NHS which help to improve the quality of health care. For example, funding work on the relationship between patient flow, costs and outcomes in two NHS hospital trusts, which is related to the new project on understanding the drivers of A&E attendances.
• The Health Foundation have an active audience of professionals working in the NHS, many of whom are fellows sponsored by the Health Foundation, award-holders or part of their alumni.

In addition, The Health Foundation’s work has achieved widespread, extensive media coverage; examples of this are BBC News, BBC Radio 4, Financial Times, The Times, Daily Telegraph and The Independent.

Patients will be given the opportunity to discuss the findings and get further involved with the work. This will include their participation to external events, bespoke presentations and external seminars. The Health Foundation’s Communications team works with teams across The Health Foundation to maximise the impact of the work conducted and reach audiences effectively. The Communications team will support the Office of Health Economics through its blog and website, media activity and will promote the findings through its Twitter account which includes many patient groups. OHE will use the feedback from patients to further enrich the analysis and its impact on health care. The engagement aims to increase awareness amongst patients on the effect of Any Qualified Provider programmes in terms of patient outcomes. The work will provide further insight into the way this type of policy can affect patients' decisions and the quality of their care. Findings and results will be presented in aggregated form, and record level data will only be seen by the Health Foundation.

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

Processing:

The Health Foundation will use the completed financial years of HES data from 2007/8 onward for the empirical analysis. AQP policy was introduced to England on the 1st April 2008. Hospital performance data in 2007/8 will be used as pre-AQP information. Data from 2008/9 onward will be used as post-AQP information. Provider information is recorded at hospital site level and patient activity and outcomes information is recorded at finished consultant episodes level. Data between 2003/4 and 2006/7 are used as Instrumental Variable (IV) for the econometric analysis. More details are reported in the method section. The data requested will be accessed by Health Foundation staff only (including a secondee from the Office of Health Economics (OHE), a research charity organisation. The secondee will be treated as a substantive employee of the Health Foundation). The Health Foundation takes full responsibility for the Information Governance and Data Security of the data held and processed. All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

The Health Foundation will focus on the elective hip surgery data analysis. The Health Foundation will split the sample into four groups, i.e. pre-AQP data from Middle Super Output Areas (MSOA) that have no exposure to private providers, post-AQP data from MSOAs that have no exposure to private providers, pre-AQP data from MOSAs that have exposure to private providers and post-AQP data from MSOAs that have exposure to private providers. HES data will not be linked with any other data. The Health Foundation will take a Difference-in-Differences (DID) method to model two hospital outcomes measures, i.e. volumes and waiting time. The results will provide an estimate of the impact of introducing AQP on the performance of private providers and its spill-over effect on the NHS providers.

Private providers from Independent Sector Treatment Centres (ISTC) were introduced in 2003 while the Any Qualified Provider programme was implemented in 2008. It is then expected that different geographical areas (MSOA in this case) were more or less exposed to private providers from 2003 and 2007, and that this level of exposure was not random. For this reason, The Health Foundation will create a proxy measure, e.g. an "instrumental variable", which will flag the MSOA where private providers were already in place through ISTCs before the Any Qualified Provider programme started in 2008. In this way, The Health Foundation can control statistically for the previous exposure to ISTC and obtain robust estimates of the Difference in differences statistical model.

Both models that measure the hospital performance by volumes and waiting time will run at patients’ level as well as the MSOA level.
The research output will be reported to the key stakeholders, such as the English Department of Health, NHS England and NHS Improvement, through sharing the research report and academic publication, as well as presenting to key decision makers, e.g. Any Qualified Provider Team at the Department of Health and the NHS England.

The Health Foundation has confirmed that the HES data will not be linked with any other data.

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

Monitoring the quality of healthcare in England — DARS-NIC-276970-B8Y4H

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Charity)

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

When:DSA runs 2019-08-30 — 2022-08-29 2019.11 — 2024.10.

Access method: Ongoing, One-Off

Data-controller type: THE HEALTH FOUNDATION

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Outpatients
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Critical Care
  5. Civil Registration - Deaths
  6. HES:Civil Registration (Deaths) bridge
  7. Civil Registration (Deaths) - Secondary Care Cut
  8. HES-ID to MPS-ID HES Accident and Emergency
  9. HES-ID to MPS-ID HES Admitted Patient Care
  10. Emergency Care Data Set (ECDS)
  11. Civil Registrations of Death - Secondary Care Cut
  12. Hospital Episode Statistics Accident and Emergency (HES A and E)
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Hospital Episode Statistics Critical Care (HES Critical Care)
  15. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

The Health Foundation is an independent charity working to improve health and the quality of health care in the United Kingdom. As part of this strategy, the Health Foundation Data Analytics team analyses data on the quality of health and care. The Health Foundation is the sole data controller and data processor of the data supplied by NHS Digital under this Agreement.

The Data Analytics team is requesting access to person-level data for an in-house programme of analyses to be completed over the course of the next 5 years.
The aim of this programme is to:
•produce new insights into quality of patient care,
•investigate how the quality of care can be improved
•understand the demand for health care in the UK using linked HES data and innovative analytical methods.

The overall purpose and benefit of this work is to inform the NHS and policy makers about changes in the characteristics and health needs of patients, factors that drive health care utilisation and health outcomes, and variation in health need, and quality of care. The work of The Health Foundation is designed to help the NHS understand the rising demand for health care and to plan for the future. The work packages within this programme will cover a number of thematic areas. These were identified as priorities for care quality and outcomes improvement in the recently published NHS Long Term Plan.

The Health Foundation are processing the data in line with their charitable goals as part of their legitimate interests. This is covered under the GDPR Article 6(1)(f) - This work is necessary for the purposes of the legitimate interests pursued by the controller or by a third party except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child. As set out in the legitimate interest assessment that The Health Foundation have undertaken - the data requested is to help achieve the following:

• To improve health service delivery (by evaluating policies and reporting feedback to the NHS and policy makers)
• To make health policymaking more effective (the work packages look at specific policy implementation and how this has been effective and feedback will be given to policy makers)
• test innovations and spread what works
• build skills and knowledge (data access will help to evaluate and understand the rising demand for healthcare and plan for the future)
• develop and share evidence on what works and why (through conferences, presentations, and journal articles that will explain outcomes and results that have been generated using the NHS Digital Data.

The data is also required for service evaluation purposes - meeting the conditions outlined as per Article 9 (2)(I) of the GDPR. Processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices, on the basis of Union or Member State law which provides for suitable and specific measures to safeguard the rights and freedoms of the data subject, in particular professional secrecy. The Health Foundation are carrying out service evaluation work as described in this agreement to investigate how the quality of care can be improved.

The overall purpose and benefit of this work is to inform the NHS and policy makers about changes in the characteristics and health needs of patients, factors that drive health care utilisation and health outcomes, and variation in health need, and quality of care. The work of The Health Foundation is designed to help the NHS understand the rising demand for health care and to plan for the future. The work packages within this programme will cover a number of thematic areas. These were identified as priorities for care quality and outcomes improvement in the recently published NHS Long Term Plan.

How will The Health Foundation achieve this work?
The Data Analytics team within The Health Foundation wish to undertake the following work streams:

Work stream 1: Monitoring trends

The Health Foundation will use patient-level data to summarise national contexts and to monitor local and national trends in secondary care in order to improve understanding of the drivers of demand and quality of patient care. Examples of trends that The Health Foundation wish to monitor include changes in disease (all diseases) prevalence and complexity over time, healthcare take-up and demand for distinct patient groups (e.g. patients with long-term conditions), as well as variations or changes in the characteristics of patients accessing secondary care. Key areas of focus within this theme will be:

• Multimorbidity: understanding the changing profiles and needs of patients with multiple long-term health conditions, following on from previous Health Foundation publications, which found that over half of hospital admissions and outpatient visits are for people living with 2 or more conditions. The Health Foundation aims to understand more about trends in combinations of conditions that patients present with in different parts of secondary care. Another goal of this workstream is to investigate the levels on under-recording of co-morbidities in electronic health records when they are not the primary reason for admission. This will be done by comparing HES-based prevalence estimates to estimates from other data sources, e.g. CPRD (Clinical Practice Research Datalink). The results from these analyses will help the NHS understand the rising demand for health care and to offer insight for policy makers and commissioners to design better quality patient care.

• Health and care inequality: unmet need and unexplained local variation in health care access and health outcomes. This analysis will help to raise awareness about existing and developing health inequalities and support the NHS and policy makers in finding solutions to address them.

• International comparison of quality metrics. Analysts at The Health Foundation will also analyse the data to provide aggregate statistics for international comparative analysis of health care quality, utilisation, cost and outcomes. This will be a contribution to an ongoing collaboration between the Health Foundation and partners from 11 other countries, including Germany, France, Australia and the USA. The aim is to compare how healthcare spending and demand for high-cost patients differs between countries. Understanding the differences between countries and their approaches will help to inform better management of these patient groups in the NHS. Note that for this project, only aggregate statistics with small numbers suppressed in line with NHS Digital guidance will be shared with colleagues overseas. These will be checked to ensure that no patient can be identified, and that the statistics contain no confidential information. No individual patient data will be shared. The collaborators do not have any influence on the means by which the data at the Health Foundation are being analysed.

• Patterns in healthcare demand and utilisation. Work will analyse the dataset to examine trends in demand for emergency and elective care over time and impact on patient outcomes (such as 30-day and 1-year mortality and 30-day readmission). This will also examine the impact of changing performance of hospital providers for example; changes to bed occupancy rates, A&E performance and waiting times.

Work-stream 1 will require linked patient-level A&E, inpatient, critical care, outpatient and mortality data for the last 10 years (2008/2009 to 2018/2019) for the whole population. To assess historical trends, access to a long time-series of data is required. To assess the health of children and young people, which is of particular interest in the mental health trends and examining trends in healthcare utilisation over time, a whole population sample is required. To assess outcomes, will need linked mortality data, including date of death to calculate 30-day all-cause mortality rates following a hospital admission.

Work stream 2: Seasonal variations

As part of the Health Foundation’s ongoing monitoring of winter pressures and the knock-on effect in care quality, analysts from the Data Analytics Team will investigate seasonal variations in A&E attendance and emergency admissions. This will include investigating patient profiles, including a focus on respiratory conditions due to their prevalence during the winter months, and a focus on long-stay patients.

The Health Foundation will undertake analyses that also aims to understand the consequences of winter pressures for other NHS services throughout the rest of the year, particularly on elective care such as outpatient appointments and elective hospital treatments. Key areas within this will be:
• Seasonal analysis of the volume of elective care and outpatient appointments with respect to geographical variation. This analysis will support policymakers and commissioners in planning for winter, as it will provide insight into areas that will require additional support.
• Cancellation of elective care in winter and their effect on demand and waiting times during other times of the year.
• Seasonal variation of length of stay for elective admissions and association with patient outcomes, such as emergency readmission and mortality.

This analysis will require linked patient-level inpatient and outpatient as well as mortality data, including date of death to calculate 30-day all-cause mortality rates following a hospital admission. This analysis will require data from the last 10 years, because it is important for this work to see whether changes in health service performance over time is affected by seasonal demand and variation. For example, were Health Foundation analysts to use the data from the recent years to see whether demand for health services increased in winter or summer, it would be useful to know whether these are recent phenomenon or whether such seasonal variations existed previously. This is important as The Health Foundation wouldn’t wish to make policy recommendations based on one-off ‘chance’ events, and therefore this justifies why it is necessary to look at seasonal variations within a fairly long-time frame - so that informed proposals can be made.

Work stream 3: Emergency hospital admissions and same-day emergency care

As part of the NHS Long Term Plan, NHS England is aiming to reduce pressure on emergency hospital services by reducing overall emergency admissions and by increasing the proportion of ‘zero-day admissions’ by providing Same Day Emergency Care (SDEC), which is also known as ambulatory emergency care.

The analysis for this workstream will investigate patient and provider characteristics associated with zero-day and 1+ day emergency admissions. Analysts will assess the effect on health outcomes, including 30-day readmission rates and mortality, compared to patients with longer hospital admissions. In addition, the effect of zero-day admissions at provider level will be analysed to explore geographical variation. This will be done using performance measures including A&E waiting times, inpatient bed days, bed occupancy, stranded patients and delayed transfers of care. This analysis will inform policymakers about progress in the implementation of the service changes set out in the NHS Long Term Plan and will provide insight into their effect on quality of patient care.

This analysis will require linked A&E, critical care and inpatient data with quarterly data updates when new data becomes available, so that progress of the implementation of this new care model can be monitored. The NHS Long-Term plan introduces a number of policy initiatives. In order to see how these initiatives will impact hospital emergency admissions, it is important to analyse emergency admissions data over time. For example, if between 2008 and 2018, The Health Foundation analyse a trend which then changes because of the implementation of a new policy, then the true effects of the policy can be determined. If The Health Foundation only used a short time period for analysis, then the significance of the impact of the change in policy would be more difficult to ascertain. Therefore, analysts require a fairly good run of years of data to be able to undertake a robust policy analysis.

Workstream 4: Outpatient care

Over the last decade the number of hospital outpatient appointments in England has almost doubled from 54 to 94 million yearly attendances. Outpatient care currently represents the largest proportion of NHS contact with patients in a hospital setting and accounts for around £8 billion in yearly healthcare expenditure.

The analysis for this workstream aims to provide new insight into quality of outpatient care by descriptively characterising outpatient journeys, focusing on patient characteristics and complexity, provider and appointment characteristics. Trends will be monitored over time, and an assessment of how these factors relate to case-mix in outpatient clinics and analyse geographical variation and variation associated with socioeconomic deprivation. This will provide commissioners, national and local healthcare leaders with better evidence on the patient need and current quality of outpatient care, in order to support them in finding solutions to meet these needs.

After a decade of substantial yearly growth, the number of outpatient appointments has remained constant since 2016/17. In the NHS Long Term Plan, this was attributed to the fact that GP referrals had been successfully constrained in recent years. The Health Foundation will dedicate part of the analysis to investigating the effect of this recent policy change by analysing the characteristics of patients that were not referred as a result and what the effect on outcomes was. This will include the effect on utilisation of other services as well as patient outcomes, such as emergency admissions and mortality.

One in five outpatient appointments in England are reported as cancelled by the patient or the hospital or as ‘did not attend’ (DNA). Missed or cancelled appointments have financial and operational implications for the NHS but can also have negative effects on quality of care and patient outcomes. This analysis will use patient-level data to investigate appointments that are frequently cancelled or missed, as well as geographical variation in cancellations and non-attendances and any links to socioeconomic deprivation. Included in this analysis will be an investigation as to whether the frequency of outpatient appointments, as well as the number of cancelled and missed appointments, is associated with patient outcomes, such as emergency re-admissions and mortality. This will also include comparisons between conventional and novel statistical approaches. This analysis will support policymakers and practitioners in understanding and avoiding non-attendances in outpatient care, which help to improve the efficiency of outpatient clinics and the quality of patient care.

This work stream will require linked patient-level inpatient and outpatient data, as well mortality data, including variables on date and cause of death.
As above, as the Health Foundation are (as part of this Work Stream) looking into policy change. A longer time span of data is required so that the full effect from the implentation of the policy can be analysed, so the true effects can be determined.

The Health Foundation wishes to process these data in order to describe and assess local and national trends in demand for secondary health care. This includes examining patterns and trends pertaining to individuals and their healthcare demands and take-up of healthcare services, in particular, those individuals with multiple health conditions; inequalities in healthcare demand. Furthermore, processing will be undertaken so that these trends can be compared with trends from other countries. In addition, data will be processed to examine seasonal variation in healthcare demand, the characteristics of patients demanding A&E services, and the demand for outpatient services.

By processing these data to generate these trends, The Health Foundation will be able to inform the health service about the situation of healthcare demand, take-up and treatment for the NHS in England. This will provide policymakers with a picture of the state of the health service demand, particularly for individuals with more than one health condition, as well as the extent to which inequalities exist. This information obtained from processing the data will provide the evidence-base for which policymakers can act to make improvements to patient healthcare. This fits with the remit of The Health Foundation, which is to bring about better health and healthcare for people living in the UK. This is essential work as demand for healthcare services continues to increase, due to an aging population, and healthcare providers continue to operate in a tight financial environment.

The Health Foundation will undertake this work by itself, and this will not involve participation of third parties.

If these data were unavailable, then The Health Foundation wouldn’t be able to undertake the work described above, and the benefits stated could not be realised. The Health Foundation has considered using aggregate sources of data for this work, but these have limitations: they have been created in a way which does not enable The Health Foundation to undertake the specific trends in healthcare that the organisation believe is important to contribute to public understanding about the health service.

In requesting to use these data, The Health Foundation will be complying with GDPR, in particular, that data will be used for a legitimate interest, and safeguards will protect the special categories of data used for this workstream.

As mentioned previously, processing the data will enable The Health Foundation to produce analysis relating to national trends of health service utilisation. Patient-level data are required to control for a number of characteristics to prevent biased statistical results from being produced. The Health Foundation seeks to avoid producing misleading analyses, and therefore it is important to use patient-level data to correctly build an accurate picture of healthcare demand and utilisation in England.

In doing so, The Health Foundation believes that the data processing is proportionate to the purpose for which it seeks to use data. There is a relatively low risk that patient data could be exposed, because of the security measures in place for protecting the data, and there is much benefit that will be realised from undertaking this analysis.

The data requested constitute special categories of data under the GDPR, since The Health Foundation has requested medical records pertaining to individuals, albeit in a pseudonymised format. Despite the fact that the data will be pseudonymised, the data may contain information about children and other vulnerable people owing to the fact that The Health Foundation has not restricted the data requested on the basis of age, disability etc. for the analysis. Trends pertaining to all patients and their use of the health service will be generated, although broken down by age group.

The Health Foundation is an independent charity that exists to further progress and improve the health care of the nation. As a charity independent of government funding , and any other interests, it endeavors to make the public aware that the use of patients’ data is solely for the purpose of improving the health service and treatments that patients receive.

There will be no impact on the data subjects (patients) whose data will be included in the extract received by The Health Foundation. Safeguards are in place to ensure that no individual data will be released from it’s accredited secure data environment in which the data will be processed; further checks will be applied to ensure that no statistical results published could reveal the identity, and/or confidential information, about any individual. Processing such data in a secure data environment is typical for organisations such as The Health Foundation, and guidance on security accreditation is sought and applied from a number of organisations including NHS Digital, Office for National Statistics, UK Data Service and HMRC (Her Majesty's Revenue and Customs) Datalab. Information about the use of patient data is available on The Health Foundation website.

Expected Benefits:

The Health Foundation works closely with key stakeholders and has strong links with NHS teams, national policymakers (e.g. NHS England) and patient advocacy groups, and the findings of this analysis will be shared with these stakeholders to inform their work. Recent publications from the team have been referenced by national policy makers in publications such as the Long Term Plan and the Universal Model of Personalised Care (from NHS England).

As outlined in the Health Foundation’s strategy, the overall aim of The Health Foundation’s analytical work is to inform health policy and help shape strategy in the NHS. As the focus of the analysis covers key areas identified in the NHS Long Term Plan, The Health Foundation will provide evidence on topics that are highly relevant to policy makers and health care leaders.

*Workstream 1: Monitoring trends*

• Analyses generated from the ‘Objectives for processing’ descriptions on changes and trends in patient profiles and health care need will help the NHS understand the rising demand for health care. Identifying and describing unmet patient need or gaps in the service will offer insight and solutions that will improve the quality patient care. This will enable policymakers and commissioners to direct their effort in a way that most effectively improves patient quality of patient care, particularly for patients with multiple conditions, and with mental health conditions. One example is The Health Foundation’s work on weekend mortality (DARS-NIC-35820), in which a blog (https://www.health.org.uk/blogs/the-importance-of-good-quality-hospital-data) was published and led to interest by policymakers. Broadly, the published work of The Health Foundation’s Data Analytics team can be found here: https://www.health.org.uk/what-we-do/quality-and-data-analytics/in-house-data-analytics.

The analyses generated for this work will inform policymakers and the NHS about the unwanted variation in care quality and will identify geographical areas or patient groups which are disproportionately affected by health inequalities. This information can then be used by commissioners including NHS England to identify priority areas for reducing inequality, in line with the mandate from Government. Although commissioners of health services are not formally engaged at present, as initial results from analyses are generated, a number of agencies with whom The Health Foundation have good relationships with will be approached. This includes Camden and Islington CCG, Barking and Dagenham local authority, South London and Maudesley NHS Trust (SLAM). A broader communications plan will be developed when the nature of the results, and the relevance of these results to policymakers, becomes clear. It is difficult to be more precise before analysis begins.

The overall benefit of this work is that policymakers and commissioners can use the findings in targeting specific cohorts in the population where inequality is particularly high. Existing initiatives aimed at reducing inequality can be assessed, and better evidence will inform debates on inequality more widely this work will help to provide evidence, which can be used to raise awareness and inform the public discussion about existing and developing health inequalities. It will also support health care leaders and policy makers in addressing them by providing evidence on the effects of policies intended to reduce health and care inequalities.

The analyses from this work will illustrate the changes in healthcare quality and demand in response to major system initiatives set out in the NHS Long Term Plan, such as the redesign of emergency or outpatient services. This will support system leaders in setting national and local priorities for service redesign, provide evidence on the progress implementation and will therefore help to realise the intended financial benefits for the NHS.

The Health Foundation’s work on tracking trends and indicators nationally and internationally will help inform policymakers about the quality of care in comparison to other countries and will provide insight into areas where the UK could do better.

The expected benefits stated above for this particular project demonstrate the ‘legitimate interest’ (Article 6(1)(f)) of the Health Foundation in the following ways. Benefits that patients will accrue as a result of this analysis outweighs by a larger proportion any of the relatively minor risks that a patient is harmed through the remote possibility of re-identification and/or release of their personal special categories of data. This fits within the remit of The Health Foundation which is to improve the health and healthcare of people in the UK. It is necessary to use the data requested in order to put together local and national trends which in turn will lead to the benefits described above, i.e. assessment of fluctuations in demand for health services, to show where variations in equality exist, and to make sure that improvements are made about how health services and quality health care are delivered.

*Workstream 2: Seasonal variations*

Recent years have witnessed pressure on healthcare services in the NHS, particularly in the winter months. Other seasonal variations may occur too, for example, as patients are admitted due to illness related to heat and other climate change effects. It is likely that seasonal variations will not only persist but increase.

Planning for such variation is crucial for ensuring that the health service can deliver quality patient care; funding and resources need to be in place at the right time. Predicting when additional demand, and the type of demand, is crucial for service providers to plan and ensure that health care can be delivered. The results of this analysis will enable providers to use evidence to adjust resources accordingly in advance and to be aware of when seasonal fluctuations in demand are likely to occur.

A positive outcome can be measured by, for example, bed occupancy rates. Where these exceed 100 per cent, this may be evidence of resources not being sufficiently or efficiently distributed. Other outcomes, such as A&E attendance etc. during periods of high seasonal demand, can be measured. Benefits of this work if policymakers are able to plan for seasonal variation could be measured by e.g. smaller A&E attendance figures.

The expected benefits stated above for this particular project demonstrate the ‘legitimate interest’ (Article 6(1)(f)) of the Health Foundation in the following ways. Benefits that patients will accrue as a result of this analysis outweighs by a larger proportion any of the relatively minor risks that a patient is harmed through the remote possibility of re-identification and/or release of their personal special categories of data. This fits within the remit of The Health Foundation which is to improve the health and healthcare of people in the UK. It is necessary to use the data requested in order to put together an analysis of when and how seasonal variations in healthcare demand occur, the analysis could not be undertaken otherwise, and it is expected that health service resources will be better organised to improve patient outcomes as a result of using data about patients’ and their treatments.

*Work stream 3: Emergency hospital admissions and same-day emergency care*

Understanding the characteristics of patients that enter A&E is important to designing A&E services. Similarly, understanding the characteristics of how A&E services are organised is important for understanding the outcomes of patients. Therefore, this work will benefit patients by providing recommendations to the NHS about how A&E and other inpatient services could be organised so that efficient outcomes are achieved, and the best health outcomes are achieved by patients.
Similarly, where geographical variation is detected, then services could be organised and/or resources targeted at areas of the country that lag behind others with respect to patient outcomes and the performance of healthcare providers.

The expected benefits stated above for this particular project demonstrate the ‘legitimate interest’ (Article 6(1)(f)) of the Health Foundation in the following ways. Benefits that patients will accrue as a result of this analysis outweighs by a larger proportion any of the relatively minor risks that a patient is harmed through the remote possibility of re-identification and/or release of their personal special categories of data. This fits within the remit of The Health Foundation which is to improve the health and healthcare of people in the UK. It is necessary to use the data requested in order to put together an analysis of the characteristics of patients who attend A&E services, and of the providers delivering A&E healthcare. Without individual patient data, in pseudonymised form, it would not be possible to infer what kind of patients demand A&E services, in what circumstances they demand these services, and what the outcomes of patients are. Therefore, it would not be possible to deliver a set of recommendations about how A&E services are delivered.

*Workstream 4: Outpatient care*

As stated previously, demand for outpatient services has increased markedly over the last few years. Understanding the characteristics of patients who demand such services will enable providers to plan efficient allocation of these services; where additional resources are required, it is important that these are identified.

Understanding why demand for outpatient services has increased so much will enable The Health Foundation to make recommendations to policy providers about how these services can be provided in the most efficient way while achieving the best possible outcomes for the patients who use these services. The alternative is that demand for these services continues to grow, but without efficient organisation of service provision, outpatient services will work ineffectively.

The expected benefits stated above for this particular project demonstrate the ‘legitimate interest’ (Article 6(1)(f)) of the Health Foundation in the following ways. Benefits that patients will accrue as a result of this analysis outweighs by a larger proportion any of the relatively minor risks that a patient is harmed through the remote possibility of re-identification and/or release of their personal special categories of data. This fits within the remit of The Health Foundation which is to improve the health and healthcare of people in the UK. It is necessary to use the data requested in order to put together an analysis of the characteristics of patients who demand outpatient services. Since the demand for outpatient services has grown significantly, it is likely that patients will differ in their characteristics and reason for using outpatient services significantly. Understanding these differences are critical for being able to analyse demand for outpatient services and for making recommendations about what could work to deliver improved outcomes for patient care.

The Health Foundation assesses the impact of the analyses using objective measures (e.g., number of publication downloads, publication citations and attendances at events and seminars) and records specific instances where The Health Foundations work has informed decision making for the NHS and improved the quality of care ultimately delivered to patients.

As a non-profit organisation, the Health Foundation’s mission is to maximise the public benefit and the impact of the research that is produced in-house. The aim is to produce useful evidence that can inform better policy and ultimately improve health and health care. This is why The Health Foundation target specific areas of interest for policy and NHS users that are less explored and particularly complex to analyse, as is the case for health inequalities.

• The Health Foundation has strong links with NHS teams, national policymakers (e.g., NHS England) and patient advocacy groups:
• Senior members of Health Foundation staff regularly meet with senior representatives from across government, including the Treasury, Department of Health and Arms-Length Bodies (e.g. Monitor, CQC, NHS England, HEE).
• The Health Foundation is currently working on joint projects with NHS organisations. One example is the partnership with NHS England in evaluating new models of care outlined in the Five Year Forward view (http://www.health.org.uk/programmes/projects/improvement-analytics-unit).
• People across the Health Foundation regularly engage with policy makers at all levels on a range of topics where The Health Foundation have particular expertise: policy, data analytics, economics, patient safety and person-centred care. Health Foundation views are regularly sought on health policy and practice, meaning that the findings from these HES-based analyses will be communicated directly with policymakers.
• The Health Foundation have a long history of funding programmes across the NHS which help to improve the quality of health care. For example, funding work on the relationship between patient flow, costs and outcomes in two NHS hospital trusts, which is related to the new project on understanding the drivers of A&E attendances.
• The Health Foundation have an active audience of professionals working in the NHS, many of whom are fellows sponsored by the Health Foundation, award-holders or part of Health Foundation alumni.

Outputs:

Statistical outputs produced from all projects listed previously will be assessed against best practice guidelines on statistical disclosure control and privacy protection to ensure the confidentiality of the data is maintained. All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Several publications will be produced from each of the work streams listed under the Purpose section. These publications typically take the form of:

- Reports aimed at policy makers, disseminated through the Foundation’s website. The Health Foundation Communications Team advertises these reports through social media channels, and in addition, senior The Health Foundation staff highlight these reports to contacts throughout the health and social care system (such as at NHS England).

- Peer-reviewed journal articles

- Blogs on the Foundation’s website or others (e.g. Health Service Journal)

- Conferences and presentations

The Health Foundation’s approach to dissemination includes not only publications but also engagement with national policy makers, practitioners and researchers. The Health Foundation’s Communications team will lead on the dissemination of findings. The Health Foundation’s staff regularly speak to senior NHS leaders. For example, The Health Foundation’s report on multiple conditions (https://www.health.org.uk/publications/understanding-the-health-care-needs-of-people-with-multiple-health-conditions) featured in national media in Autumn 2018, in addition to staff at NHS England charged with designing and delivering national policy on integration and personalised care. Furthermore, The Health Foundation regularly liaises with local providers: for example, results of analysis into social isolation, were relayed to Barking and Dagenham in London. This instigated the establishment of a range of projects aimed to tackle social isolation across different age groups.

Wider dissemination of findings takes place via the media, and through social media and direct e-communication with key stakeholders. For example, a previous publication using HES data, on emergency admissions received extensive coverage in the trade media, support via social media from relevant royal colleges and other stakeholders, and exclusive national press coverage in The Times. Other publications from the team have received similar or greater coverage from media, and strong engagement on social media.

Planned publications:
• Health foundation briefing on trends in emergency admissions since the last Health Foundation analysis published in 2018, 2021
• Health Foundation briefing on the effects of implementation of same-day emergency care (planned for 2021, once data for the financial year 2019/20 is available)
• Health Foundation publication on elective care investigating seasonal demand and demand management practices 2021 and 2023.
• Health Foundation report on outpatient appointments, 2019
• Peer-reviewed publication(s) on outpatient journeys and the effect of missed/cancelled appointments to be published in BMJ, PloS Medicine, BMJ quality and safety or similar.
• Health Foundation publication on mental health (national trends analysis), 2019 and 2021
• Peer-reviewed publication(s) on international comparisons of care quality to be published in BMJ, PloS Medicine, BMJ Quality and Safety or similar (ongoing 2021, 2022, 2023).
• Health Foundation publication on health and care inequalities, 2020
• Health Foundation publication on trends in care quality, and impact of major system changes, 2021 and 2023

Processing:

For this programme of work data will be processed by a limited number of analysts within the Health Foundation’s Secure Data Environment. All researchers with access to the data will have completed information governance and data security training, as well as training specific to the Health Foundation’s infrastructure, and signed a non-disclosure agreement and the terms of use of the Foundation's Secure Data Environment. The Secure Data Environment is recognised for the NHS Digital Data Security and Protection Toolkit, and is accredited under the ISO27001 security standard. This means that a number of processes and policies are in place to ensure the confidentiality of data held for the purposes outlined above, is maintained.

The data will only be analysed on The Health Foundation’s premises in London. Any outputs generated from the data for presentation will be in the form of aggregated outputs, with small number suppression applied in line with the HES analysis guide.

The following describes the processing activities for each individual work stream:

Work Stream A: Data management and cleaning pipeline

As The Health Foundation have used HES data in the past, the Data Analytics team have experience of ‘cleaning’ and organising the data in preparation for analyses. This is important for understanding any data limitations which could affect the interpretation of analyses; it reduces the risk of analysts misunderstanding the data, and ensures data are organised and can be processed consistently throughout the different work streams (which are listed subsequently). This workstream is about undertaking this cleaning upon receipt of data, and for the quarterly updates that are requested.

Cleaning and organising the data is the first preliminary and necessary step for accomplishing the goals set out in the other work streams (see Objectives), which will lead to patient benefits. For reasons of transparency (under Article 9 of the GDPR) and because putting the HES data files together (e.g. Outpatients, A&E etc.) into a useable analytical resource is intensive and significant work, The Health Foundation believe it useful to include this information in the application because the cleaning work is a form of data processing that will serve the purposes and objectives outlined in the workstreams.

Within this pipeline, data will be combined with other publicly available data sources, which will not contain any detail that might lead to increased identification risk of individual patients, but rather add contextual information at an aggregate level. These other data sources will be combined with the data applied for using the geography data items requested, such as Lower Super Output Area (LSOA). For example, it is possible to determine using publicly available data that certain LSOAs will be ‘urban’ or ‘rural’. This demonstrates that patient information from HES will only be combined with the external sources stated below using aggregate data items, not information unique to individual patients.

The external data sources that the data will be combined with include:

Geographical information, including Rural/Urban indicators. Patient characteristics are likely to change between rural and urban areas, and the way in which health services are delivered are likely to differ too. Picking up the differences between rural and urban locations is important for producing statistically robust analyses.

Workforce information, including GP full-time equivalents per GP practice. The way in which services are delivered and benefit patients will be affected by health service workforce levels (such as manpower and skills). In evaluating the quality of health care provided, it is important to take account for health service workforce information.

Socioeconomic deprivation, including Index of Multiple Deprivation. Patients will be living in areas of low, medium or high deprivation, for example. For this application, The Health Foundation is not interested in the deprivation status of individual patients. But understanding the general geographic area in which they live with respect to deprivation will help explain why and how health services are delivered.

Provision and performance of other healthcare services at a CCG or GP level, e.g. opening hours, GP patient survey results, Quality and Outcomes Framework performance. This information is important to factor into analyses: by ensuring that the Health Foundations methods take account of performance of different health services and how they affect patient outcomes will ensure that assessing the quality and trends of health care provision are accurate.

All data requested will be used exclusively for the purposes stated in this application.

For this programme of analysis, the in-house data analytics team require person-level data linked across for inpatient (Elective, non-elective and day case), outpatient, A&E, critical care and mortality data. The data required within this project are:

• HES Admitted Patient Care Data from 2008/09 to 2018/19 and quarterly updates as they become available
• HES Outpatient Data from 2008/09 to 2018/19 and quarterly updates as they become available
• HES Critical Care Data from 2008/09 to 2018/19 and quarterly updates as they become available
• HES Accident and Emergency data from 2008/09 to 2018/19 and quarterly updates as they become available
• Civil Registration Mortality data between 2008/09 and 2018/19 and quarterly updates as they become available.
• HES/Civil Registration Bridge File - Quarterly Updates to facilitate linkage.

To monitor ongoing changes during the implementation of new models of care and their effect on care quality, and the implementation of the NHS Long Term Plan, The Health Foundation require quarterly data updates.

The amount of data requested has been limited to the minimum amount required for this programme of work. Although The Health Foundation has previously received other HES data (linked to mortality data), these were created for different purposes (specifically for the purposes described under DARS-NIC-15411: funding pressures). As such, the data extracts were defined specifically for that work; much of the data required to undertake the objectives specified above require up-to-date and different data items than were specified in this previous DARS application. To be clear data previously disseminated under DARS-NIC-15411 will not be used for this programme of work.

Other justifications for the use of data include:
• Geography: healthcare utilisation displays a lot of regional variation. To monitor national and local trends as well as seasonal variation, all geographical areas need to be covered.
• Time coverage: analysis of trends over time requires rich historical data on seasonal variation, business and economic cycles and long-term trends. For this reason, the Health Foundation are requesting access to data from the last 10 years.
• Population: several work streams aim to cover hospital utilisation of the whole population. Focus on teen mental health will require patients aged under 18 years.
• Variables: costing variables are required for international comparison work. Mortality data, including date of death and cause of death, are required to estimate 30-day mortality after hospital admission and to assess whether cause of death was related to the conditions patients were treated for.

Only substantive employees of the Data Controller (The Health Foundation) will access the record level data being shared under this agreement.

Considerable effort has been made only to request the absolute minimum number of data items required to do the analyses outlined above.

For each work stream, the available data dictionary was consulted and a list of data items were drawn up that would be necessary to undertake the analyses. This list of data items was reviewed iteratively by a number of staff at The Health Foundation to ensure that the data items were necessary and would be used in the analysis process. The Health Foundation are confident that the data requested represents the minimum necessary to achieve the analytical process and outcomes stated in this document.

Where possible, only data items actually recorded by NHS Digital, and not derived data items, have been selected. Analysts at The Health Foundation will endeavour to derive new data items if necessary, thus avoiding the dissemination of more data than is required to The Health Foundation.

Although The Health Foundation has requested a number of years’ of data, this can be justified, in general, for each work stream, by the desire to undertake robust analysis. The Health Foundation wants to make sure that the analyses undertaken are robust; and that where trends are detected, these are actually trends and not one-off events. This is important because The Health Foundation wouldn’t wish to make recommendations about how the health service could change based on limited data; but instead undertaking robust analysis requires good data over a length of time so that The Health Foundation can be truly sure of the trends they believe have been detected. For the workstreams listed above, The Health Foundation have only requested data back to 2008 because ten years’ worth of historical data will be sufficient to undertake a robust trends-analysis.

Funding pressures, phenotyping hospitals, penalising readmission and analysing factors associated with A&E performance in England, patients with long-term conditions — DARS-NIC-15411-C9Z9L

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Charity)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-02-27 — 2020-02-26 2017.06 — 2021.10.

Access method: One-Off, Ongoing

Data-controller type: THE HEALTH FOUNDATION

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Admitted Patient Care
  2. Hospital Episode Statistics Accident and Emergency
  3. Hospital Episode Statistics Critical Care
  4. Hospital Episode Statistics Outpatients
  5. Civil Registration - Deaths
  6. HES:Civil Registration (Deaths) bridge
  7. Civil Registration (Deaths) - Secondary Care Cut
  8. HES-ID to MPS-ID HES Accident and Emergency
  9. HES-ID to MPS-ID HES Admitted Patient Care
  10. HES-ID to MPS-ID HES Outpatients
  11. Civil Registrations of Death - Secondary Care Cut
  12. Hospital Episode Statistics Accident and Emergency (HES A and E)
  13. Hospital Episode Statistics Admitted Patient Care (HES APC)
  14. Hospital Episode Statistics Critical Care (HES Critical Care)
  15. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

As part of this application for an extension to the data retention period, the Health Foundation would like to add the latest financial years of the same datasets (and same variables specification) to be used only in the ongoing strands of analysis.

More specifically, the latest data series will be used for the following work packages:
1. The funding pressures facing health care in England for the next 15-20 years, and how service transformation can lead to greater sustainability
2. Phenotyping English Hospitals
3. Penalising readmission: success or failure (only for the sub-strand analysis on “effect of factors related to workload”, as the rest of the work is now completed)

This will provide further value to the work produced until now and add a more recent evidence base to the ongoing analysis packages (further details are provided in section 5.d)

The Health Foundation is an independent charity working to improve health and the quality of health care in the United Kingdom. The Health Foundation is requesting access to data for four research projects that aim to inform public discussions about the focus, design and effects of policies intended to improve the quality of health care in the United Kingdom or reduce costs. The projects will inform policy makers and the NHS about the variability in quality and costs of health care in England, and thus help to identify priority areas for improving health and social care

These four projects are:
1. The funding pressures facing health care in England for the next 15-20 years, and how service transformation can lead to greater sustainability:
To create an economic model of the person level factors that determine use of hospital services to i) estimate of how spending pressures on these services will grow in the future, and ii) estimate the potential impact of policies to reduce these pressures.

Progress to date: Work on this project is on-going, and the final modelling is expected to be completed in the summer of 2017. Health Foundation analysts have been liaising with experts in the Department of Health and Monitor, to make sure that the analysis maximises potential benefit. Discussions with these experts have led to a better understanding of costing the data using reference cost data and PbR Tariffs.

2. Phenotyping English Hospitals:
Variations in hospital performance and quality of care are significant. This project aims to classify English hospitals with respect to trends in length of stay and 30-day readmission rates for elderly and frail patients. The study follows the phenotyping approach used by Xu et al. (2014).

Progress to date:
The original deadline of the work was November 2016. However, the research team is still conducting the analysis and no final output has been produced to date. The main reasons for delay relate to the extensive research into technical aspects of the methodology.

3. Penalising readmission: success or failure:
Readmission rates have been increasing over the past decades. Various policies have been implemented to revert this trend, including the introduction of financial penalties on hospitals for re-admissions from 2011. However, its effectiveness has never been evaluated. Thus, this project will assess changes in readmission rates following the policy implementation period.

Progress to date: This project is now completed. As a sub strand of this study we would like to understand pressures affecting changes in readmission rates (as factors related to workload, i.e., admission rates, occupancy rates and bed occupancy rates) by using inpatient, outpatient and A&E data covering the most recent years (i.e. 2015/16).

4. Analysis of factors associated with the performance of A&E departments in England:
A&E departments have been under pressure, and this could be because of changes in demand, supply, the resilience of departments, or wider contextual factors (e.g. health policy). The Health Foundation will use person-level HES data to assess changes in the characteristics of patients attending A&E departments over time. The Health Foundation will also assess the relationships between A&E activity and the volume of patients admitted as inpatients.
The Health Foundation will use patients’ clinical information to derive risk-adjusted variables at the Trust level, which will be used within a panel data model that relates these to variables relating to the supply and demand of health care.

Progress to date: This project is near completion. Initial analysis identifying factors associated with A&E performance was presented to the NHS England analytical team in October 2015. Final findings will be published in a working paper series by Spring 2017.


The Health Foundation is committed not to combine the requested HES data with any other data source that might result in increased re-identification risk. The Health Foundation is happy to formalise this commitment in the Data Sharing Agreement (DSA) for this extract.

The Health Foundation’s secure processing environment holds dedicated projects folders that will be used for projects using HES data, as specified in The Health Foundation’s information security policy. Users have access only to data that relates to their project, and the content of all project folders is reviewed regularly to make sure The Health Foundation deliver on this commitment. The process for moving additional data sources on to the secure environment is a carefully controlled process monitored by the Data Manager, part of this process is to review the purpose statement of each project and restrictions on the use of specific datasets.

The only data sources that may be used in combination with HES data will not contain any detail that might lead to increased identification risk, but rather add contextual information at an aggregate level (e.g. contextual geography).

The Health Foundation has limited the amount of data requested for each project to the minimum amount. For example, the analysis of phenotyping English hospitals is limited to records for patients aged 65 and over, and to ten years rather than the full duration. Although all HES data will be held on The Health Foundation’s secure environment, researchers will only access and analyse the required subset of the data on a day-to-day basis.

The largest amount of data is being requested for ‘The funding pressures facing health care in England for the next 15-20 years, and how service transformation can lead to greater sustainability’ in terms of geography, time coverage and population base. Each of the dimensions is discussed below in the context of this project.

- Geography – healthcare utilisation displays a lot of regional variation. In order to produce accurate projections England wide all geographical area’s need to be covered in the research data.
- Time coverage – the aim of the project it to predict long term healthcare use (15-20 years). In order to accurately predict variation over time (including seasonal variation, business cycles and long term trends) rich historic data is required.
- Population – the projects aims to cover hospital utilisation for all conditions. Whole population data gives good coverage (in terms of numbers) on rare conditions. It would be inequitable to narrow the research down to only certain population groups because these groups would then not be considered in important research to inform future budget decisions about the NHS.

Reference
Xu, X., Li, S.-X., Lin, H., Normand, S.-L. T., Kim, N., Ott, L. S., … Krumholz, H. M. (2014). “Phenotyping” Hospital Value of Care for Patients with Heart Failure. Health Services Research, 1997, 1–17. doi:10.1111/1475-6773.12197

Yielded Benefits:

This is an example of some of the work produced so far. - National trends in emergency readmission rates: A longitudinal analysis of administrative data for England between 2006 and 2016 The aim of this paper was to provide a descriptive analysis of readmission rates over time and changes in the degree of ‘unwarranted’ variation between NHS trusts. The Health Foundation found that readmission rates remained stable across the 10-year period, with variation across clinical subgroups. Moreover, variation decreased consistently, suggesting overall improvements in health care quality in England. A revised version of the produced article has been submitted to BMJ Open, with an acceptance decision expected in the next few weeks. Furthermore, the article forms part of a PhD chapter in Dynamics in Quality of Care: The Case of Readmission Rates at Imperial College London. - The implications of high bed occupancy rates on readmission rates in England: A longitudinal study The aim of this paper was to examine the relationship between bed occupancy rates, hospital behaviour and quality care. Hospital behaviour was measured through daily discharge rates, whereby quality of care was measured through readmission rates. The Health Foundation found that following nights of high bed occupancy, hospitals are more likely to discharge patients on the following day, but with no substantial impact on the patients’ risk of being readmitted. The research paper is currently under peer-review at Health Policy, and has been submitted to several conferences for presentation. These include AcademyHealth in Seattle (US), the American Health Economics Conference in Atlanta (US), the European Health Economics Conference in Maastricht (NL), and IRDES in Paris (F). - Do financial penalties reduce readmission rates? A continuous treatment effect evaluation. The aim of this paper was to estimate a causal relationship between different levels of financial penalties on future readmission rates in the English NHS. The Health Foundation used the endogeneity that resulted from setting financial penalty thresholds and following the adjustment using the generalised propensity score; it is estimated dose-response functions to determine the optimal employed financial penalty rate to maximise impact on readmission rates. This work has been presented at numerous conferences, including IRDES in Paris (F), the International Health Economics Association Conference in Boston (US), and at several internal meetings at The Health Foundation and Imperial College London. Moreover, it forms part of the thesis of an analyst from the Health Foundation and is prepared for submission to Health Economics – one of the two best journals for health economics research.

Expected Benefits:

The Health Foundation has strong links with NHS teams, national policymakers (e.g., NHS England) and patient advocacy groups. Examples of these links are:

• Senior members of Health Foundation staff regularly meet with senior representatives from across government, including the Treasury, Department of Health and Arms-Length Bodies (e.g. Monitor, CQC, NHS England, HEE).
• The Health Foundation is currently working on projects for, or jointly with, organisations including NHS England. For example, we have jointly funded an evaluation of the Patient Activation Measure in the NHS, and work together on the ‘5000 Safety Fellows Programme’
• People across the Health Foundation regularly engage with policy makers at all levels on a range of topics where the Health Foundation has particular expertise: policy, data analytics, economics, patient safety and person-centred care. The Health Foundation views are regularly sought on health policy and practice, meaning that the findings from these HES-based analyses will be communicated directly with policymakers.
• The Health Foundation has a long history of funding programmes across the NHS which help to improve the quality of health care. For example, the Health Foundation have funded work on the relationship between patient flow, costs and outcomes in two NHS hospital trusts, which is related to the new project on understanding the drivers of A&E attendances.
• The Health Foundation have an active audience of professionals working in the NHS, many of whom are fellows sponsored by the Health Foundation, award-holders or part of the Health Foundation’s alumni.

The Health Foundation provides leadership and advice on quality improvement as well as commentary on health care policy. The Health Foundation’s analysis of HES data will inform these activities. The Health Foundation assess their impact using objective measures (e.g., number of publication downloads, publication citations and attendances at events and seminars) as well as record specific instances where their work has informed decision making for the NHS and improved the quality of care ultimately delivered to patients.

Due to these strong links with the health service, the Health Foundation is in a good position to reach as much beneficiaries as possible for each of the four projects.

Each project is expected to have the following impact:

1. The funding pressures facing health care in England for the next 15-20 years, and how service transformation can lead to greater sustainability
Following the analysis The Health Foundation will discuss the results of the scenarios of different models of delivery to inform policy makers on the impact that different decisions would have. These will mostly be discussions of the national situation, with some regional analysis at a level similar to government office regions.

To maximise the benefit of the work on this project, it is important that information provided to the Department of Health and Monitor is based on the latest available data. Health Foundation will update the existing work on the basis of the latest available data, that is up to and including 2015/16, providing a comprehensive overview of NHS funding challenges and transformation programmes.

Progress to date: Work on this project is ongoing, and the final modelling is expected to be completed in the summer of 2017. In the meantime our analysts have been liaising with experts in the Department of Health and Monitor, to make sure that the analysis maximises potential benefit. Discussions with these experts have led to a better understanding of costing the data using reference cost data and PbR Tariffs.

2. Phenotyping English Hospitals
This project will help to identify issues surrounding the quality of care of providers for elderly patients via mapping the relationship between length of stay and readmission rates. Identifying poorly performing providers will be of interest for the Care Quality Commission as it may inform the selection of trusts for inspection. On the other hand, identifying providers who perform well, offers the opportunity to conduct qualitative research to understand reasons for such good performance. Good performance processes can be collected and inform best-practice.

This work will also use the latest financial years of data requested (i.e. 2013/14-2015/16). Health Foundation believe this would add additional value and make our findings more relevant for policy. The demographics for England are rapidly changing towards an older and frailer population. Subsequently, demand for health services within this subset of the population is rising, putting increasing pressure on hospitals. The value of receiving more updated data is to allow us to investigate how healthcare providers responded to this change in demographics. Similar to the workload project, by using the most recent data, Health Foundation will be able to make a stronger contribution to the ongoing debate about care for the elderly and frail.

Progress to date:
Experts from Nuffield Trust, Dr. Foster Unit and health Economics Research Unit at Imperial College have also been contacted to maximise policy relevance for this study.The original deadline of the work was November 2016. However, the research team is still conducting the analysis and no final output has been produced till date. The main reasons for delay relate to the extensive research into technical aspects of the methodology.
Preliminary work informed an expansion of research into the relationship between readmission rates and publicly available patient reported outcomes data at the Trust-level. Health Foundation performed a panel data analysis and a research paper will be submitted for peer-review to Medical Care in February 2017.
Health Foundation aim to produce the final findings of the study for September 2017, and to write a research paper aimed for publication on peer-reviewed international journals by the end of 2017.
Due to the length of the peer-review process the Health Foundation will require to retain the data for at least two years, in order to ensure the replicability and validation of the results and, ultimately, their publication,



3. Penalising readmission: success or failure
The penalisation of readmissions has been in place since 2011/2012, yet, has rarely been studied. The Health Foundation’s study will inform policy makers about the likely effectiveness of the chosen financial tool and draw comparisons to the Affordable Care Act in the US. This will inform Monitor and other organisations involved with the policy debate about changes to the way that hospitals are reimbursed for emergency care in the NHS.

Progress to date: This project is now completed.
Early findings were presented at the American Health Economics Association in Philadelphia in July 2016; to internal seminars at The Health Foundation and to external events with the Dr. Foster Unit.
The research paper has been submitted to a best student paper competition at the International Health Economic Association in November 2016. The outcome of this competition will be announced in March 2017.
At the beginning of March 2017, the authors will submit the research paper to the Journal of Health Economics.
Due to the lengthy process of peer-reviewing articles, we expect to require an extension for data access of at least two years.

As a result of the work on penalisation of readmission, we would like to further investigate the effect of factors related to workload.
This work will use the latest financial years of data requested as part of this application. The reason behind this request is that over recent years hospital trusts have reported increasing levels of bed occupancy rates, especially during the winter months. For many trusts, occupancy rates have reached critical levels of above 90%, which anecdotally leads to extreme strains for individual providers and potential adverse consequences for patients. Furthermore, high occupancy rates can also be linked to increasing waiting lists and not meeting A&E targets, which has been a popular subject within the national media. Investigating the relationship between workload and the risk of re-admissions is therefore a very timely concern, and we are particularly interested in the effect that workload pressures have on readmission rates since 2013. As a result, looking at the most recent HES data would feed directly into the current debate about bed pressures.

4. Analysis of factors associated with the performance of A&E departments in England
This project will provide guidance that is urgently needed by NHS England and other policy makers regarding which factors impact most on A&E performance, in particular waiting times. This is needed because an increasing proportion of departments have not met waiting time targets. The project will provide insight about how performance can be improved.

Progress to date: This project is near completion. Initial analysis identifying factors associated with A&E performance was presented to the NHS England analytical team in October 2015. Following the meeting with NHS England, a number of refinements were identified.
The findings will be published in a working paper series by Spring 2017. Aiming to submit the paper for peer-review later in the year.

Outputs:

As outlined above, outputs for all projects will be in line with best practice guidelines on statistical disclosure control and privacy protection.

The outputs for each project are as follows:

1. The funding pressures facing health care in England for the next 15-20 years, and how service transformation can lead to greater sustainability
The primary output of this project will be a Health Foundation report, similar in style to the report “A Decade of Austerity” Nuffield Trust 2012. It will provide an update to the funding pressures that are expected over the next 15-20 years. This report would be made available through the Health Foundation’s website by 2017.

Depending on the results, The Health Foundation will look to publish the results of the historic trends of hospital admission for chronic conditions in a public health journal.

2. Phenotyping English Hospitals
The study will be completed by the end of 2017 and ultimately published in peer-reviewed international journals. These will be a mixture of health services research journals (e.g. Health Services Research and Policy) and economics journals (e.g. the Journal of Health Economics). These journals are read by policy makers, nationally and internationally, who wish to identify and classify hospitals according to the level of quality of care that they provide.

The research will also be presented at conferences and events aimed at policy makers. The Health Foundation will present internally at The Health Foundation and also to statutory bodies such as the Department of Health and Monitor. The Health Foundation will publish a summary of the research on the Health Foundation’s website.

3. Penalising readmission: success or failure
This project serves a similar audience as the previous project, and the same type publication will be pursued. The main work on this study has now been completed and a research paper for publication on peer-reviewed journals has been produced.

While conducting the analysis the researchers developed a deeper understanding of the data and further important research to be derived by this study. The additional research looks into variation of 30-day readmission rates across commissioning groups and investigates how those changes developed over time. Health Foundation hypothesis that a decrease in variation measured via the standard component of variation implies overall improvements in quality of care in the English NHS. Health Foundation are therefore planning to write up and submit a research paper for BMK Open in summer 2017.

In addition to an academic research paper, the results will form part of a PhD thesis chapter.

4. Analysis of factors associated with the performance of A&E departments in England
The findings of this study will be disseminated through meetings with senior policy makers and NHS leaders, plus a short policy-focused report on the Health Foundation’s website. The Health Foundation will also submit the findings to a peer-reviewed journal as above. The study will be completed by December 2015.

Each of the projects listed in the application will produce a number of publications. These publications typically take the form of:
- Reports aimed at policy makers, disseminated through the Foundation’s website
- Peer-reviewed journal articles
- Blogs on the Foundation’s website or others (e.g. Health Service Journal)
- Conferences and presentations
- Press releases

The Health Foundation’s approach to dissemination includes not only publications but also engagement with national policy makers, practitioners and researchers. Each project has member of the Foundation’s Communications team leading on dissemination of findings.

The Foundation works closely with key stakeholders and has strong link with NHS teams, national policymakers (e.g., NHS England) and patient advocacy groups. Examples of these links are:

- The Health Foundation is currently working on projects for, or jointly with, organisations including NHS England. For example, The Health Foundation have jointly funded an evaluation of the Patient Activation Measure in the NHS, and work together on the ‘5000 Safety Fellows Programme’
- People across the Health Foundation regularly engage with policy makers at all levels on a range of topics where The Health Foundation has particular expertise: policy, data analytics, economics, patient safety and person-centred care. The Health Foundation’s views are regularly sought on health policy and practice, meaning that the findings from these HES-based analyses will be communicated directly with policymakers.
- The Health Foundation has a long history of funding programmes across the NHS that help to improve the quality of health care. For example, The Health Foundation have funded work on the relationship between patient flow, costs and outcomes in two NHS hospital trusts, which is related to the new project on understanding the drivers of A&E attendances.
- The Health Foundation have an active audience of professionals working in the NHS, many of whom are fellows sponsored by the Health Foundation, award-holders or part of The Health Foundation’s alumni.

Processing:

In case of all four projects, data will be processed by a limited number of researchers within the Health Foundation’s secure environment. All researchers with access to the data will have completed an accreditation course on data protection legislation and statistical disclosure control, completed an information security training specific to the Health Foundation’s infrastructure, and signed a non-disclosure agreement and the terms of use of the secure environment.

HES Data will only be processed on the Health Foundation’s premises on 90 Long Acre in London and any publication derived from the data will be subjected to best practice guidelines on Statistical Disclosure Control (SDC) including the Code of Practice on Confidential Information, the Anonymisation Standard for Publishing Health and Social Care Data and the code of practice published by the ICO, Anonymisation: managing data protection risk code of practice before being released form the environment.

All data requested will be used exclusively for the purposes stated in this application.

Project specific processing of data is outlined below.

1. The funding pressures facing health care in England for the next 15-20 years, and how service transformation can lead to greater sustainability

For this project, the Health Foundation require person level data linked across for inpatient (Elective, non-elective and day case), outpatient and A&E. The critical care dataset will be used separately (rather than linked to the other data).
The project aims to project cost pressure over the next 15-20 years; therefore the Health Foundation needs to track historic trends over a similar period for the whole population. The Health Foundation will initially estimate the demand pressures for each service type separately, to allow for the differences in the time periods covered by the relevant data sets. The data required within this project are:

• Inpatients between 1997/98 and 2015/16
• Outpatients between 2003/04 and 2015/16
• A&E between 2007/08 and 2015/16
• Critical Care between 2008/09 and 2015/16

Since this involves modelling the evolution of health care utilisation for people with various specific health conditions in the different government office regions, it will need comprehensive data coverage for these time periods.
For each service type, the Health Foundation will explore how service use is affected by factors including age, sex, residence (LSOA), treatment provider (site and trust), commissioner, diagnosis and procedure codes, treatment function, admission method and time.

The Health Foundation will also explore how the level of use of one service affects demand for other services (excluding critical care). As this will require an overlapping time period, the Health Foundation can only explore these interactions for shorter periods. The Health Foundation are comfortable with this limitation as the information will be used to create scenarios for analysis on how policy decisions might impact on total cost projections in addition to the overall projections.
The primary models will be independent service-specific linear, or log-linear person-level models of the trends in the level of activity for emergency inpatients, elective inpatients, outpatients, A&E and critical care. The results of the models will be used to create projections for future use of these services at a national level, and by government office regions (or other similar sized areas as appropriate). The Health Foundation will therefore apply the results of the analysis of historic trends to publicly available population projections produced by the ONS.

The Health Foundation will also measure how service use differs between people with various chronic conditions, namely diabetes, COPD, asthma, coronary heart disease, cancer, arthritis, dementia, epilepsy, renal disease and stroke. The Health Foundation will identify these groups using the diagnosis codes present within the inpatient dataset. Again, as The Health Foundation plan to project the numbers of patients in these groups, The Health Foundation will explore the trend over time for inpatient admissions between 1997/98 and 2015/16. These will be done using a linear regression, with transformations applied where appropriate to ensure the best fit for each condition. By producing trends in this way, The Health Foundation is able to explore the trends for certain co-morbidities, instead of using single condition prevalence projections. However The Health Foundation will compare their estimates to national data on prevalence of these conditions where possible for assurance.

The projections for costs on these services will be combined with projections for other NHS services, such as GP attendances and community pharmacies, produced using publically available data. The combining of data in this way will primarily be done at a national level, and will not be done at a level lower than government office region.
Having established the models and projections, The Health Foundation will use the results to test the impact of a series of assumptions around future changes in NHS delivery. This will take the form of modelling assumptions on how service delivery might change at a national level. For example, The Health Foundation will test the potential impact on total NHS spending of a substantial investment in GP practices, which might be expected to lead to a reduction in hospital admissions. More complex policies are likely to impact on multiple hospital services for certain types of people. In these cases, The Health Foundation will need to understand the relationship between the different hospital service types. For example, if a new community diabetes service is set up that includes additional outpatient appointments, but might reduce the need for inpatient care, The Health Foundation will produce summaries of the current levels of use for these services for people with diabetes, to understand the full impact of the change. Again, these results will only be published at a level no lower than government office regions.

The Health Foundation will also explore the impact of likely productivity growth on the projected growth. The Health Foundation will base this on evidence on recent and longer-term levels of productivity growth by running random effects, fixed effects and stochastic frontier analysis on weighted activity of different types of providers. As with other analysis, results will be used at a national or large regional level.

2. Phenotyping English Hospitals

For this project, inpatient, outpatient and Accident & Emergency data over the last ten years will be used to inform descriptive analysis (i.e. 2003/04 – 2015/16, where available). The project requires data on older people (age 65+).
This descriptive analysis will look at the variation of length of stay vs. readmission rates by hospital provider in England. Multivariate regression analysis will be used to estimate relationships between patient-characteristics and outcome variables. Risk-standardised length of stay for each hospital-year will be calculated, by adjusting for differences in patient case-mix across hospitals over time. Likewise, the risk-standardised 30- day readmission rate will be calculated.
Based on these constructed measures for length of stay and readmission rates, hospital phenotypes will be identified using a group-based, semi parametric mixture modelling approach. The determination of phenotypes will depend upon the Bayesian Information Criteria index, average posterior probability of phenotype and 95% confidence intervals of adjacent trajectories.

Variables covering the following areas are likely to be included in the analysis adjusting for case mix: emergency admissions, source of admission, patient characteristics, provider code and deprivation measures.

Results from the analysis are will include

(i) Estimated regression coefficients (and their associated p-values) relating to the associations between provider characteristics and the phenotype. This information will help understand the associations between hospital characteristics (e.g., teaching hospital status, region) and the two dependent variables (length-of-stay and 30-day readmission rates).
(ii) Graphs mapping the changes in readmission rates and length of stay by Trust over a 10 year period.
(iii) Depending on the number of identified phenotypes, graphics displaying the observed trajectories for each. Each trust can be attributed to one of the created graphics – making classification and groupings of trusts easier and more visual.

All outputs for this project will be at Trust level and no additional sources of information will be combined with HES for this project besides publicly-available Trust-level data.

3. Penalising readmission: success or failure

For this project, inpatient, outpatient and Accident & Emergency data will be needed covering the four years before and after the policy change in England (i.e., 2007 – 2012/13).
Descriptive analysis will look at crude (unadjusted) readmission rates at the Trust level, as well as 30-day readmission rates by Trust when adjusted for case-mix using the method described in project (2).
The consequences of the policy change will be assessed using a segmented regression analysis of interrupted time series, comparing trends before and after the intervention. The analysis will be conducted for all hospital admissions and for subsets of admissions defined by health condition (as determined by the recorded diagnosis codes).
Similar to the above results, results from the analysis will include estimated regression coefficients and associated p-values by NHS Trust, over time, as well as graphs representing the 30-day readmission rate per trust on a monthly basis.

We would also like to understand pressures affecting changes in readmission rates. This strand of the study will investigate the effect of factors related to workload, i.e., admission rates, occupancy rates and bed occupancy rates. This will be in addition to financial penalties employed to reduce re-admissions and results will provide a more detailed understanding of driving mechanisms behind changing readmission rates. For this project we will be needing inpatient, outpatient and A&E data covering the most recent years (i.e. 2015/16).

4. Analysis of factors associated with the performance of A&E departments in England

This project focuses on A&E attendances for the whole population of England, and will cover the time period 2007 – present. In addition to A&E data, The Health Foundation will use inpatient and outpatient data at episode level to characterise patients in terms of their demographics, diagnoses, number of previous attendances, and missed appointments. This information will be used within a series of panel data models to investigate how the performance of an A&E department varies with factors related to demand and supply of health care, and the characteristics of patients.

COVID Oximetry At Home - (CO@H): Improvement Analytics Unit — DARS-NIC-421528-J6S3N

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, No - Statutory exemption to flow confidential data without consent, Anonymised - ICO Code Compliant, No (Statutory exemption to flow confidential data without consent)

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Other-Health and Social Care Act 2012 - s263 (b)

Purposes: No (Charity)

Sensitive: Sensitive

When:DSA runs 2021-04-07 — 2021-09-30 2021.04 — 2021.07.

Access method: Ongoing

Data-controller type: NHS ENGLAND (QUARRY HOUSE)

Sublicensing allowed: No

Datasets:

  1. Covid Oximetry @ Home (CO@H)
  2. Shielded Patient List
  3. Civil Registration - Deaths
  4. Hospital Episode Statistics Critical Care
  5. GPES Data for Pandemic Planning and Research (COVID-19)
  6. COVID-19 Second Generation Surveillance System
  7. Covid-19 UK Non-hospital Antigen Testing Results (pillar 2)
  8. Hospital Episode Statistics Admitted Patient Care
  9. Emergency Care Data Set (ECDS)
  10. Personal Demographic Service
  11. Civil Registrations of Death
  12. COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
  13. COVID-19 Second Generation Surveillance System (SGSS)
  14. COVID-19 UK Non-hospital Antigen Testing Results (Pillar 2)
  15. Hospital Episode Statistics Admitted Patient Care (HES APC)
  16. Hospital Episode Statistics Critical Care (HES Critical Care)

Objectives:

The purpose of this work is derived from the need to evaluate national roll out of the Covid Oximetry @Home (CO@H) programme.

The COVID Oximetry @home (CO@H) programme involves the remote monitoring of patients with coronavirus symptoms. Patients use a pulse oximeter, a small monitor clipped to their finger, to measure their oxygen saturation levels three times a day.
They record their results using a smartphone app, web portal or paper diary. The paper-based option is available at all sites for patients who are uncomfortable with or unable to use a digital solution to record their readings. Patients are supported by clinical staff locally, so that if they need further treatment they can be admitted to hospital at the right time. Currently, services are delivered by a range of provider organisations, including Clinical Commissioning Groups, Primary Care Networks and acute hospital trusts.

Processing this data is in the public interest as it will provide evidence as to the health and safety outcomes of home oximetry as a clinical pathway for patients with Covid-19. This evidence will support the health service to more effectively treat and manage Covid-19, and therefore is of substantial public interest. The Health Research Authority decision tool for defining research has been completed and the proposed work is not considered research and therefore does not need ethical approval.

The data is required for service evaluation purposes - meeting the conditions outlined as per Article 9 (2)(H) of the GDPR. “processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services on the basis of Union or Member State law or pursuant to contract with a health professional and subject to the conditions and safeguards referred to in paragraph 3”. The Health Foundation are carrying out service evaluation work (under the instruction of NHS England) as described in this agreement to investigate how the quality of care can be improved.

As such, this work is of significant public health concern undertaken by a service evaluation team conforming to General Data Protection Regulation (GDPR) Article 6(1)(e) and Article 9(2)(H).

Patients with serious coronavirus symptoms often do not go to hospital early enough, and this can negatively impact patient outcomes. Some patient groups more likely to present late include healthcare workers and BAME patients. Observational data suggests that for every day of delay in hospital admission the chance of death increases by 1%. (Source NHS Digital https://digital.nhs.uk/coronavirus/covid-oximetry-at-home-digital-and-data-services).
Delayed presentation can also lead to invasive treatment in Intensive Care Units being required and longer hospital stays.

The national Covid Oximetry @Home programme builds on initial pilot work that focused on the use of pulse oximetry and the remote monitoring of patients with coronavirus at home, then referred to as ‘virtual wards’. The pilot work focused on three locations (Tees Valley, Slough and North West London). The pilot work aimed to address the clinical problem that patients with severe coronavirus sometimes present to hospital relatively late – mainly due to the fact that in coronavirus oxygen levels can fall to dangerously low levels with very few symptoms.

Clinical Commissioning Groups (CCGs) were advised in November to set up ‘COVID Oximetry @home’ services as rapidly as possible. The default assumption is that the model will be primarily implemented in general practice as one of seven priority goals for the additional £150m General Practice COVID Capacity Expansion Fund. The model relies upon timely referral of patients that may meet the entry criteria from all relevant providers operating within the area. The supply of pulse oximeters available to CCGs is based on national modelling assumptions of case demand using agreed entry criteria.

The eligible population for the CO@H programme is people who are clinically suspected of having or tested positive for COVID-19 and are aged 65 or over or aged 18 and over and considered clinically extremely vulnerable or have a learning disability.

The aim of this work is to quantitatively assess the cost effectiveness and health and safety outcomes of the CO@H intervention as well as variation in access and outcomes. The data requested is uniquely capable of achieving this aim as it contains necessary information about patients who are enrolled onto the CO@H programme as well as their outcomes. Furthermore, the data requested will support critical analysis regarding inequalities to accessing the pathway, patient-level outcomes after being onboarded into the pathway and CCG-level performance of the CO@H programme. Only this data, inclusive of the requested variables, will be able to support these analyses and therefore achieve the aim identified.

The proposed evaluation work is commissioned by NHS England, who have also commissioned Imperial College London to evaluate the CO@H programme. Although both Imperial and the Health Foundation will lead on their own evaluation work stream (and as such apply for these data separately), there is commitment to share learning between the two pieces of work to ensure robust findings, a common definition of key metrics, and improved efficiency in tackling any issues arising from the data.

This evaluation will use routinely collected data from patients who have tested positive for COVID or are clinically suspected of having COVID and have been enrolled into the CO@H programme. Eligibility criteria for the work will NOT include patients under the age of 18. These data will be used comparitevely, by comparing against patients testing positive for COVID, but not in receipt of the CO@h programme. The eligibility criteria for the work are people who are clinically suspected of having, or test positive for COVID-19 and are:
• aged 65 or over, or
• aged 18 and over and considered clinically extremely vulnerable, or
• aged 18 and over and diagnosed with a learning disability.

Data is required for COVID POSITIVE Patients (18+) across all CCGs, (Approx 3.7 million records) PLUS those on the CO@H Programme.

In terms of the datasets required, the following justifications apply:

• General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR) will be used to determine the demographic features (eg sex and LSOA) and clinical comorbidities (eg asthma, diabetes or COPD) of patients enrolled into the CO@H programme. Additionally, these data will be obtained for individuals not enrolled into CO@H, both before and after the start of the CO@H intervention (from March 2020 onwards - CV19 positive patients). This will enable construction of appropriate control populations to address key evaluation questions regarding equity of access to the service and the safety of the service.
This dataset comprises general practice data on patients registered in 97.5% of all practices in England. This will be the source of data on baseline characteristics for the patients included in the analysis.

The age of patients (in whole weeks relative to a reference date) will be calculated by NHS Digital using this dataset. From this, The Health Foundation will derive the age at first COVID-19-positive test (e.g. 65 years and 3 weeks). The Health Foundation will request data for patients born between 1st October 1940 (i.e. turning 80 on 1st October 2020, the earliest potential start date) and 1st May 1971 (i.e. turning 50 on 1st May 2021).

• Covid-19 testing data [COVID-19 Second Generation Surveillance System (SGSS)]
This system holds data on COVID-positive tests, including the full date of first COVID-positive test. SGSS is the national laboratory reporting system used in England to capture routine laboratory data (mainly on infectious diseases and antimicrobial resistance).
Only the first COVID-positive test is captured in this database. The Health Foundation will also be provided testing data from the COVID-19 UK Non-hospital Testing Results (‘pillar 2’). These sources will be used to identify the case cohort.

[COVID-19 UK Non-hospital Antigen Testing Results] will be used to identify those patients enrolled into CO@H following a positive test for Covid-19, and the time between a positive test and enrollment. Additionally, Covid-19 testing data will be used to identify those patients who had a positive Covid-19 test prior to the start of the CO@H intervention as a means of establishing a matched preintervention control population. Patient with a positive Covid-19 test after the start of the CO@H intervention will be identified in order to evaluate the equity of allocation of the intervention across all those with a positive Covid-19 test.

• Bespoke Covid Oximetry @Home data (collected as part of the program) will be used to identify the time and routes of enrollment of patients (primary care or secondary care), in addition to the clinical acuity of patients at onboarding. These data are required to determine the duration between enrollment and presentation to hospital or mortality, and to evaluate variation in clinical acuity and routes of enrollment between sites. These data will also be used to determine the time spent on the home oximetry programme across patient groups and between sites. It will also be used to determine whether patients used a standard or ‘tech enabled’ intervention during their CO@H programme.
o This dataset lists the date of patient onboarding (i.e. enrollment onto the CO@h intervention).
o These data will allow The Health Foundation to check the assumptions of a discontinuity in onboarding at age 65.
o In addition, by triangulating with hospital data, we will be able to check other assumptions – e.g. that onboarding is primarily occurring before hospital attendance.
o Onboarding data were due to be collected across all CCGs from 1st December 2020, with the option of retrospectively collected data from as early as 1st October 2020 from sites that started rolling-out CO@h earlier.
o However, due to COVID-19 pressures, as of mid-January 2021, this patient-level data is not currently being reliably recorded nationally. Thus, the quality of this dataset is a key risk to the execution and validity of the evaluation and its ability to identify a treatment effect.

• HES Admitted Patient Care (HES APC) and HES Critical Care (HES CC) data will be used to identify presentations to critical care departments and hospital admissions for patients enrolled into the CO@H programme, and also those within relevant control populations. Evaluating the rates of secondary care interaction are a critical aspect of the evaluation. Data from March 2017 is required in order to identify any previous diagnoses of comorbidities contained in the hospital records as part of the process of matching intervention patients to control patients. Data are requested from April 2017 to the present date in order to identify clinical comorbidities and procedures not captured in GDPPR that may influence COVID-19 prognosis.

• Shielded Patient List
This dataset identifies patients who are regarded as clinically extremely vulnerable (CEV) and at high risk of serious illness from COVID. Only the CEV flag will be disseminated.

• Emergency Care Data Set (ECDS) data
o This will be used to provide information on A&E attendances; one of the evaluation outcome measures.
o Data are requested from April 2019 to the present date in order to identify clinical comorbidities not captured in GDPPR that may influence COVID-19 prognosis.

• Civil Registration Mortality Data are required for all individuals in order to identify mortality rates in the CO@H intervention population, and also in control populations. Date of death is required to determine the time from enrolment and Covid-19 testing to death in order to conform to Public Health England definitions of Covid-19 mortality. Cause of death will allow non-Covid-19 mortality to be distinguished from deaths attributed to Covid-19.

PDS Data - Care Home Flag from the UPRN Asset
• Data used to flag care home residents
o Based on patient registration information derived from pseudonymised National Health Application and Infrastructure Services (NHAIS) data.
o This will facilitate focussed evaluation of the impact of the CO@h programme in care homes, as requested by NHS England

All data will be required in pseudonymised format to enable patient-level evaluation across datasets.

All datasets will cover the period from March 2020 till the present day. This date range has been selected as it marks the starting point of the COVID pandemic in England, and will therefore be relevant to the programme. The bespoke CO@H data set is only being collected as part of the CO@h programme, and will not be available before October 2020. The date ranges for the SUS APC and ECDS data go back in time further. This historic data will be used to help characterise the patient population eligible for the CO@h programme by looking at previous hospital utilisation.

Data will be required for all of England in order to evaluate performance of the national implementation of CO@H.
Following discussion between the evaluation partners, NHS England and in consultation with NHS Digital, who are assisting with data flows, it has been determined that there is no alternative, less intrusive way (using less information) of achieving the purpose of the evaluation.

In order to minimise the data requested, the Health Foundation have only included variables needed to carry out the analysis that has been agreed by NHS England. As part of a consultation with NHS Digital and clinical and academic experts, the Health Foundation has narrowed the dataset to focus only on information that can demonstrate the health and safety outcomes of the CO@H programme.

Given the role of NHS England in determining the scope, and purpose of the evaluation they are the Data Controller for this data, although all processing will be carried out by the Health Foundation.

For this dissemination - the legal basis to disseminate the data is the Control of Patient Information Notice (COPI) Regulations. NHS Digital has chosen to pseudonymise the confidential information in accordance with the COPI regulations.

Expected Benefits:

Sharing this data enables the evaluation of a major pathway of care for patients with Covid-19. Understanding the cost effectiveness and health and safety outcomes of the CO@H programme is critical to building safe remote monitoring pathways for Covid-19 patients in the community. Delivering effective, safe Covid-19 care is vitally important to patients and their care, as well as to NHS staff and the future of how the pandemic is managed.

In terms of measurable benefits, this work will quantifiably demonstrate the health and safety outcomes of remote oximetry for Covid-19 at a patient and CCG-level. These outcomes will drive how the NHS cares for and monitors Covid-19 patients in the community. They will also reveal any changes needed to make remote oximetry services more equitable and more effective.

The pipeline from outputs to national policy is explicit in this piece of work: the results from this evaluation will be shared regularly with NHS England, specifically with those involved in the policies and standards surrounding Covid Oximetry @ Home services. Therefore, the results from this evaluation will directly inform national policy makers about how best to roll out, modify and improve home oximetry for Covid-19 patients. This pipeline from evaluation to decision making to community benefit has already been demonstrated in the pilot phase of this work, whereby an evaluation of safety of the ‘Covid Virtual Ward’ programme led to the national roll out of the CO@H programme.

The quantitative evaluation of CO@H requires understanding the clinical outcomes of patients onboarded into the CO@H programme as well as key features of their medical history. These datapoints are included in the data collection specification and directly enable an evaluation of the CO@H programme which would not be possible with any other data. Given the unprecedented need to understand how best to manage Covid-19 in the community, the data required for this evaluation will enable a statistically robust analysis which can inform and direct national policy making.

The results from this work will be made available to key stakeholders, namely NHS England in regular reports. Furthermore, the final results will be made public with targeted publications for NHS England, but also within the public academic literature, as a scientific contribution.

The evaluation will guide the ongoing implementation of the CO@H programme at national and local level. It will provide evidence as to the equity of access to the CO@H programme and the safety of the CO@H programme. These findings will be used during the implementation of the programme to support emerging evaluation concerns raised by local sites and the national delivery partners. Actions arising from the evaluation will be implemented centrally by NHS England or locally by Clinical Commissioning Groups and other care providers as required.
Findings from this analysis will benefit all patient eligible for the CO@h programme which include:

• All registered patients in England aged 65 and over
• All registered patients in England aged 18 and over who are deemed clinically extremely vulnerable in relation to COVID-19, in line with Government guidelines

Findings from this evaluation will serve the following purposes:

• To improve health service delivery (by evaluating policies and reporting feedback to the NHS and policy makers)
• To make health policymaking more effective (the work packages look at specific policy implementation and how this has been effective and feedback will be given to policy makers)

The outputs are intended to directly support the provision of the Covid Oximetry at Home programme of care by NHS England and will therefore meet the stated objective.

A key benefit may be the continued roll out of this programme potentially reducing morbidity and mortality from COVID-19.

Outputs:

The Health Foundation expects to produce the following outputs, which are described in detail below:

• Monthly reports with interim findings prepared for the CO@h evaluation workstream
• Final internal briefing for key stakeholders in NHS England, NHS Digital and NHSX.
• Open access paper in peer review journal on the RDD evaluation
• Open access paper in peer review journal on the GSC evaluation
• Publicly available policy briefing published through the Health Foundation website
• Conference presentation on CO@h evaluation (e.g. the annual HSR UK Conference organised by HSR UK for organisations and individuals involved in health services research in policy and practice)

As a result of the data processed described above, the Health Foundation will share interim findings with the CO@h evaluation workstream on a monthly basis (on top of regular reporting in weekly meetings).
The Health Foundation will prepare a briefing on the findings for circulation to key stakeholders in NHS England, NHS Digital and NHSX. These outputs will only contain aggregated data with small number suppression applied.

The Health Foundation will submit two academic papers to peer-reviewed journals. Upon submission, the Health Foundation will also publish a pre-print version of the paper, for immediate dissemination. Provided the Health Foundation is successful in the publication of our paper, the Health Foundation will pay for open access where required.

The Health Foundation will synthesise findings from both studies, as well as the wider literature in a policy briefing that will be made publicly available through the Health Foundation website.

The Health Foundation will present findings from the evaluation at HSR UK (described above).
Where possible the Health Foundation will collaborate with evaluation partners in the CO@h programme, to synthesise evidence across multiple studies, and maximise impact form the work.

The overall timeline of this work will be dependent on the development of the COVID-19 pandemic in England, and the duration of the CO@h programme as a result of this. The suggested timeline below may be subject to change.

Timeline:
• Monthly reports to CO@h programme from February 2021 to March 2021 (or April 2021 if the COPI notice for accessing data is extended)
• Briefing to key stakeholders – April 2021
• Submission to peer review journal on RDD – May 2021
• Submission to peer review journal on GSC – May 2021
• Dissemination of both papers through pre-print server – May 2021
• Publication of both papers will depend on peer review process – December 2021
• Policy briefing – June 2021
• Conference presentation at HSR UK – July 2021, as described above

Processing:

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

The Health Foundation will use two distinct statistical methods to evaluate the CO@h programme. Each of these approaches is described in a Statistical Analysis Plan, or protocol, but also described below.

(1) Regression discontinuity design (RDD):

This evaluation will take advantage of the 65-year threshold for eligibility for CO@h for patients with a confirmed COVID-19 diagnosis. The Health Foundation will compare hospital outcomes between patients who have tested positive to COVID-19 and are aged 65 or over, with those of patients who have tested positive to COVID-19 just under 65. The analysis will produce a ‘local treatment effect’ at age 65.

The Health Foundation expects that the risk of severe complications from COVID-19 is highest in the first 28 days – consistent with Public Health England’s definition of COVID death as being within 28 days of the first positive test. Furthermore, the standard operating procedure for CO@h stipulates that if there are no signs of deterioration within 14 days of onset of symptoms, patients can be discharged from CO@h. Therefore, in this evaluation, each patient above and below the running variable’s threshold will have a follow-up period of up to 28 days from their first COVID-positive test. This analysis will focus primarily on the pre-hospital use of oximeters.

Regression discontinuity design is appropriate in situations where eligibility for an intervention changes sharply at a predefined threshold (in this instance at different age thresholds. This design largely avoids problems of observed or unobserved confounding, as patients just below and above the threshold will in general be expected to be similar in baseline characteristics. Under these circumstances the Health Foundation can therefore attribute any change in outcomes at the threshold to the intervention.

(2) Generalised Synthetic Control (GSC):

The use of pulse oximeters (as described in section 5a above) for remote monitoring of high-risk individuals with a COVID-19 diagnosis is taking place in a growing number of GP practices and community teams in England. A clinical pathway using pulse oximetry technology for remote monitoring is being delivered by a growing number of CCGs in England not only in primary and community health-care settings (primary care remote home monitoring model), but also to patients being discharged from A&E departments (secondary care model) or from hospitals (step-down model). Individuals eligible to enter a CO@H pathway (the target population) are COVID-19 confirmed patients who are either of 65 years of age or over, or identified as clinically extremely vulnerable irrespective of their age.

National roll-out of pulse oximeters for remote monitoring of high-risk COVID-19 patients since December 2020. Known delays in a number of CCGs ordering and accessing the technology has led in practice to a staggered roll-out across CCGs over time. A programme evaluation could therefore proceed by comparing on a range of outcomes CCGs offering to their eligible patient population a CO@h pathway (treated or intervention units) over a prefixed period of time (the analysis or follow-up period) with those CCGs not concurrently providing the technology (untreated or control units). The start and length of the follow-up period would be chosen to ensure that by its end there remains a sufficiently sized pool of control CCGs in England to carry out a meaningful outcome comparison from. The exact analysis length will be based on the data and will depend upon uptake and spread. Outcomes chosen to inform this comparison would comprise selected secondary care and mortality indicators, which will be retrospectively collected from administrative data.

The effect on a given outcome of the CO@h intervention implemented in a treated CCG at a given time following its introduction (post-intervention or follow-up period) will be quantified by the change (if any) detected in the CCG at that time between the outcome rate that was actually recorded, and what would have been hypothetically observed had the CCG not implemented a CO@h pathway (the counterfactual). As is invariably the case in programme evaluation assessments relying on retrospectively collected data, the counterfactual cannot be observed in practice; as such it needs estimating. The evaluation will rely on the Generalised Synthetic Control (GSynth ) method. The synthetic control method is used to evaluate the effect of an intervention in comparative case studies. It involves the construction of a weighted combination of groups used as controls, to which the treatment group (those who receive the CO@H intervention) is compared. This comparison is used to estimate what would have happened to the treatment group if it had not received the intervention. Unlike difference in differences approaches, this method can account for the effects of confounders changing over time, by weighting the control group to better match the treatment group before the intervention.

Once a counterfactual is derived for each CCG implementing a CO@h pathway during the evaluation follow-up period, an estimate of the impact at a given time of the CO@h initiative across treated CCGs (the Average Treatment effect among the Treated, or ATT) will be obtained by averaging across treated CCGs the effect estimates obtained for the corresponding period. Lastly, an overall estimate of the impact of CO@h in CCGs where it is implemented can be obtained by averaging previously derived impact estimates over the evaluation follow-up period.

The Health Foundation will not link any additional information to the data requested on patient level for either analysis design listed above, however, the Health Foundation will add contextual information derived from public data sources, and will include information at LSOA level (e.g. English indices of deprivation 2019, www.gov.uk), at GP level (e.g. characterisation of GP practice registered population using Quality Outcome Framework achievement and prevalence scores, NHS Digital), and at CCG level (e.g. number of registered GPs, NHS Digital).

Both analysis designs listed above will only require the use of pseudonymised data. These data will be processed on the Health Foundation Secure Data Environment (SDE), a dedicated analytics environment designed to maintain the confidentiality of the data, and protect against any unwarranted disclosure of information. The SDE is a secure environment hosted in an off-site secure data processing facility owned by UK Cloud (listed as storage location). All processing will be carried out by Approved Users of the SDE. Approved Users are substantive employees of the Health Foundation (including associate analysts that maybe payed through a contract, rather than pay-roll), or employees of NHS England with access to the Health Foundation’s environment. All Approved Users need to complete mandatory information governance training specific to the SDE, to help them understand their responsibilities, and make sure they have the appropriate skills to process information safely. No information can be removed from the SDE without going through a thorough Statistical Disclosure Control (SDC) process, to make sure that analysis findings cannot be used to identify individuals, and are in line with the latest guidance on SDC (which includes the suppression of any small numbers). This process requires at least two pairs of eyes to review analysis findings prior to release from the system.

Assessment of health inequality — DARS-NIC-90019-Q8P9K

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Charity)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-04-02 — 2022-04-01 2017.09 — 2020.02.

Access method: One-Off

Data-controller type: THE HEALTH FOUNDATION

Sublicensing allowed: No

Datasets:

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

Objectives:

The Health Foundation is an independent charity working to improve health and the quality of health care in the United Kingdom. The Health Foundation is requesting access to HES data for the “Assessment of inequality” project to inform public discussions about the focus, design and effects of policies intended to improve the quality of health care in the United Kingdom. The project will inform policymakers and the NHS about the variability in health inequality with respect to NHS hospital services and A&E waiting times in England by geographical area and ethnicity, and thus help to identify priority areas for reducing inequality. The aim of the project is to identify areas (geographical and within treatment specialities) in which healthcare inequality exists. The Health Foundation will disseminate these findings with the aim of raising awareness of existing and growing inequalities in access to healthcare and how these have changed over time and also to inform policy makers of areas in which there is potential for these inequalities to be redressed.

The Health Foundation meets regularly with representatives from Department of Health, NHS England and NHS Improvement and the findings will inform ongoing conversations and interim findings will be presented to these representatives. The Health Foundation will also engage with patient advocacy groups to ensure that the findings will benefit NHS hospital patients.

Objective:
(i) The objective of this project is to create an evidence base that will inform policymakers in the Department of Health, NHS England and NHS Improvement about the variability in health inequality with respect to NHS hospital services and A&E waiting times in England by treatment speciality, geographical area and ethnicity.
(ii) The Health Foundation will also assess health inequality within maternity services due to the topical nature of this issue and the high level of media coverage in recent years including issues identified at Morecambe Bay maternity (Bunyan, 2015).
(iii) The project will also create an economics model of the determinant of health inequality by geographical area, deprivation and ethnicity.
It is recognised in the literature that health inequality exists in England for example Cookson et al. (2016) highlights that residents of more deprived areas are more likely to die from treatable conditions and less likely to see a specialist than residents of less deprived areas. England is not alone in the existence of health inequality; Hart & Williams (2009) also discussed the presence of health inequality in the American setting, linking inequality to quality of life as well as health service factors such as access to care and quality of care.

The NHS has a mandate from the government to reduce health inequality (Department of Health, 2015). One reason that this analysis aims to investigate health inequality in England is to assess how the health inequality level has changed in recent years, as the NHS has faced rising financial difficulty, and whether it can be expected to reduce in future years in line with the NHS’ mandate.

The Health Foundation would also like to assess health inequality within maternity services due to the topical nature of this issue and the high level of media coverage in recent years including issues identified at Morecambe Bay maternity (Bunyan, 2015).

The Health Foundation will use hospital episode statistics (HES) data at pseudonymised patient level to assess the relationship between geographical area and inequality using a measure of inequality such as the slope index of inequality or the relative index of inequality.

Trends in inequality will be examined in the years before the current period of austerity (2003-2010) and in the current period of austerity (2010-date). The Health Foundation require a sufficient length of time to reliably compare the changes in the trends during these two periods and examine the significant differences between the intervals. This is needed in order to adequately capture the impact of austerity on inequality in healthcare.
The reason The Health Foundation wish to examine these differences is based on the theory that before austerity there will have been more resources available to put towards access to health care and to allocate these resources in the most equal way may have been easier during this period than the current period of austerity. Austerity aims to reduce deficits using methods such as reducing expenditure to bring it in line with revenue. Austerity is often associated with a reduction in government spending; in times of austerity this may result in spending cuts within certain hospital departments. The Health Foundation wish to investigate whether certain groups of the population are disproportionally affected by these cuts in comparison to others.

Yielded Benefits:

In the last year, initial results from this work undertaken by Economics team at The Health Foundation suggest that as time goes on, access to secondary health services has increased for both the top and bottom socio-economic groups. For the earlier years, analysts found that access was increasing for the bottom socio-economic groups, leading to a reduction in health access inequality, suggesting that funding to improve access among the most deprived groups in society was having an effect. Analysts in the Economics team are surprised that access to the top socio-economic groups (need and take up of health services) has begun to increase. This is an area that the Economics team will continue working on as they employ more robust analytical methods to provide further insights. As these results are preliminary initial results, they have not yet been published, and won’t be until further investigations are concluded. When The Health Foundation is in a position to publish these results (i.e. when robust results are created), then it is the intention to inform policymakers and NHS England, so that inequalities can be addressed, and that the experience of patients is equal.

Expected Benefits:

Benefits
In line with the primary objectives described above, the purpose of this project is to build an evidence base on inequality across England. This information will be used by commissioners including NHS England to identify priority areas for reducing inequality, in line with the aforementioned mandate from Government.

The overall benefit of this work is that policymakers and commissioners can use the findings in targeting specific cohorts in the population where inequality is particularly high. Existing initiatives aimed at reducing inequality can be assessed, and better evidence will inform debates on inequality more widely.
Specifically, objectives (i) and (ii) will inform the varying level of inequality across geographical areas and difference health care services (objective (ii) focussing primarily on the latter). Variation in inequality by health care service will help target commissioners in tackling the problem of inequality. Objective (iii) will model the cost of care for patients that are more or less deprived of access to health care (e.g. the average cost of an outpatient appointment may be higher for hard to reach groups). This will benefit commissioners and policy makers in prioritising this particular policy area.

As described in the outputs section, outputs (a) and (d), as well as ongoing interaction with the Department of Health, NHS England and NHS Improvement will deliver the benefit for policy makers and commissioners, and in turn for patients.
Outputs (b), (c) and the involvement of patient advocacy groups are targeted towards our objective to inform the public debate about health inequality in England.

Note: the purpose of this project is to identify areas for improvement regarding inequality in access to health care services including hospital services, maternity services and access to A&E. Although the Health Foundation can help inform proposals to reduce inequality going forward, this project will not reduce inequality in and of itself.

Audience

As a non-profit organisation, the Health Foundation’s mission is to maximise the public benefit and the impact of the research that is produced in-house. The aim is to produce useful evidence that can inform better policy and ultimately improve health and health care. This is why The Health Foundation target specific areas of interest for policy and NHS users that are less explored and particularly complex to analyse. This is the case of health inequalities.
The Health Foundation has strong links with NHS teams, national policymakers (e.g., NHS England) and patient advocacy groups. Examples of these links for previous projects are:
• Senior members of Health Foundation staff regularly meet with senior representatives from across government, including the Treasury, Department of Health and Arms-Length Bodies (e.g. Monitor, CQC, NHS England, HEE).
• The Health Foundation is currently working on joint projects with NHS organisations. One example is our partnership with NHS England in evaluating new models of care outlined in the Five Year Forward view (http://www.health.org.uk/programmes/projects/improvement-analytics-unit).
• People across the Health Foundation regularly engage with policy makers at all levels on a range of topics where we have particular expertise: policy, data analytics, economics, patient safety and person-centred care. Health Foundation views are regularly sought on health policy and practice, meaning that the findings from these HES-based analyses will be communicated directly with policymakers. One example is the recent engagement of the Economics team with NHS Wales (http://www.health.org.uk/programmes/projects/fiscal-sustainability-nhs-wales), leading to the following report (http://www.health.org.uk/publication/path-sustainability).
• The Health Foundation have a long history of funding programmes across the NHS which help to improve the quality of health care. For example, funding work on the relationship between patient flow, costs and outcomes in two NHS hospital trusts, which is related to the new project on understanding the drivers of A&E attendances.
• The Health Foundation have an active audience of professionals working in the NHS, many of whom are fellows sponsored by the Health Foundation, award-holders or part of our alumni.
Engagement
The approach to dissemination includes not only publications but also active engagement with national policy makers, practitioners and researchers. This project will have a member of the Foundation’s Communications team leading on dissemination of findings which will include a number of alternative channels as TV, radio interviews and articles on national, local and online media.

Outputs:

As outlined above, outputs will be aggregated with small numbers supressed in line with the HES analysis guide.
Results from the analysis will include:
• Summary statistics (including number of observations, mean values and standard deviation values) for inequality regression analyses assessing health inequality in relation to geographical area, deprivation and ethnicity;
• Estimated regression coefficients (and their associated p-values, which show the level of statistical significance of the estimated coefficient.) relating to the associations between health inequality and geographical area, deprivation and ethnicity;
• Charts and maps to show changes in health inequality by geographical area, deprivation and ethnicity at the Trust or local authority level between 2003/04 and 2016/17;
• The results of the regressions included in this analysis will be presented in a tabular format with an accompanying body of text describing and explaining the results.
Planned outputs for this body of work are:
(a) A Health Foundation report, similar to the recent report on the need for a dedicated transformation fund, Making change possible: a Transformation Fund for the NHS (the Health Foundation and the King’s Fund, 2015) ( https://www.kingsfund.org.uk/press/press-releases/making-change-happen-transformation-fund-nh). This will be accompanied by a detailed communications plan on how to target the media to ensure the results have the maximum penetration. It is expected that this report will be published in the first quarter of 2018 (January – March 2018).
(b) Findings will be submitted to international peer-reviewed journals. These will be a mixture of health services research journals (e.g. Health Services Research and Policy) and economics journals (e.g. the Journal of Health Economics). These journals are read by policy makers, nationally and internationally, who wish to identify and classify hospitals according to the level of quality of care that they provide. The expectation is to submit articles for peer review no later than March 2018.
(c) Interim findings will be submitted to (and if accepted presented at) various conferences to seek early feedback and to allow improvement of the work. Conferences targeted include: The Health Economist’s Study Group at University of Aberdeen (June 2017) or London City University (January 2018)), NHS Providers annual conference (November 2017), NHS Confed annual conference (June 2017 or 2018)
(d) Findings will be presented at The Health Foundation to statutory bodies such as the Department of Health, NHS England and NHS Improvement. The Health Foundation expect to invite the statutory bodies by June 2018.

Note: The Health Foundation meets regularly with representatives from the Department of Health, NHS England and NHS Improvement. The proposed work will inform ongoing conversation with these organisations and interim findings will be presented to their representatives in addition to the more formal outputs listed above. Similarly, The Health Foundation will engage with patient advocacy groups in order to ensure findings that may benefit NHS hospital patients, are communicated with these groups who can use them towards positive change.

Processing:

The requested data will be processed by a limited number of analysts within the Health Foundation’s Secure Data Environment (SDE). All researchers with access to the SDE will have completed an accreditation course on data protection legislation and statistical disclosure control, completed an information security training specific to the Health Foundation’s infrastructure, and signed a non-disclosure agreement and the terms of use of the secure environment. All researchers with access to the data are substantive employees of the Health Foundation.

The data will only be processed on the Health Foundation’s premises on 90 Long Acre in London and any publication derived from the data will be aggregated with small numbers supressed in line with the NHS guidance before being released from the environment.

As outlined in the objectives above, The Health Foundation would like to evaluate health inequality over time, and across different geographies within England. The aim is to investigate how changes in inequality in the most recent decade compares with changes in the preceding decade. There is a particular interest in trends in inequality and access to health care in the period before the current period of austerity and trends during the current period of austerity. For the purpose of this project The Health Foundation will consider the following periods:
• 2003/04 until 2009/10 as the pre-austerity period;
• 2010, as the start of the austerity;
• 2010/11 onwards as the austerity period.

For that purpose, the following comprehensive datasets are required:
• Inpatients from 2003/04 to date
• Outpatients from 2003/04 to date
• A&E from 2007/08 to date
For this project, The Health Foundation will combine inpatient, outpatient and A&E records over time to establish patients’ health care utilisation. The data will be further enhanced by linking in additional contextual information at GP practice level, or small area level (note: The Health Foundation will NOT link any data at patient level). Contextual data sources are typically publicly available statistics published by the Office for National Statistics, NHS Digital or NHS England (e.g. aggregated census data at small area level, GP patient survey data aggregated at GP level).

As stated in the methodology, The Health Foundation wish to examine the differences in the changes in inequality over the period running up to austerity compared to during the current period of austerity. It is essential to this project to analyse data from all available years pre-austerity (from 2003/04) in order to capture all significant changes in health inequality within hospital departments in the period running up to austerity for an accurate comparison with the period of austerity.
As A&E data are only available from 2007 onwards, this will restrict the analysis to a 3 year period before the period of austerity. However, The Health Foundation are expecting to complement this trend with underlying trends in hospital admissions and outpatients therefore it is imperative to this project to examine trends in inequality before austerity using the earliest available data for inpatients and outpatients (from 2003/04).

The data will be used to generate descriptive statistics on inequality across different health care services, geographies within England, ethnicity and over time in line with objectives (i) and (ii). Measures of inequality that will be used include the slope index and the relative index of inequality. Objective (iii) will require the Health Foundation to apply statistical modelling to the same data, explaining inequality levels in terms of prevalence of health conditions, age, sex, location of residence, ethnicity and time.

Future demand pressures on mental health services in England — DARS-NIC-179115-S0R1W

Type of data: information not disclosed for TRE projects

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

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

Purposes: No (Charity)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2018-09-10 — 2020-09-09 2018.10 — 2019.02.

Access method: One-Off

Data-controller type: THE HEALTH FOUNDATION

Sublicensing allowed: No

Datasets:

  1. Mental Health Services Data Set
  2. Mental Health Services Data Set (MHSDS)

Objectives:

The Health Foundation is an independent charity working to improve health and the quality of health care in the United Kingdom. The Health Foundation is requesting access to Mental Health Services data set (MHSDS) to analyse trends in mental health activity at a detailed level. In 2010/11 Mental Health was responsible for 10% of spending by the NHS (1). From then to 2014/15 there was an increase in average referrals to community mental health teams of 19 per cent, for crisis and home treatment teams the increase was 18 per cent(2).

There were 145 fewer psychiatrists across all grades (full time equivalent) in March 2017 than March 2010 (1.64% decrease). Over the same period there has been a decline in the number of mental health nurses of 5,161 (12.63%)(3).

In March 2015, research by Community Care and BBC News found that the funding for NHS trusts to provide mental health services had fallen by 8.25%, £600 million, in real terms over the course of the last parliament (from 2010/11 to 2014/15) (4). The data, based on 43 Freedom of Information (FOI) requests to 56 mental health trusts in England, showed that total funding for the trusts͛ mental health services fell in cash terms from £6.7 billion in 2010/11 to an expected £6.6 billion in 2014/15.

Figures from NHS Digital suggest that over a five-year period from 2008/09 to 2013/14 social care expenditure on adults with mental health needs aged between 18 and 64 reduced in cash terms from £1.2 billion to £1.1 billion(5).

This increase in referrals has been coupled with a reduction in real terms funding and staff for mental health services. The Health Foundation seek to analyse how this budgetary change has affected trends in activity. The project will inform policymakers and the NHS about the variability in quality and costs of mental health care in England, and thus help to identify priority areas for improving health. The aim of the project is to create an economic model of the person level factors that determine use of mental health services to i) estimate of how spending pressures on these services will grow in the future, and ii) estimate the potential impact of policies to reduce these pressures.

This work, as well as being its own piece of research on the determinants of mental health activity, will also feed into the current project (NIC-15411-C9Z9L): ͞The funding pressures facing health care in England for the next 15-20 years, and how service transformation can lead to greater sustainability. This is a wider projection model for healthcare activity and spending that is designed to inform public policy on healthcare finance and to improve the quality of health care in the United Kingdom.

The Health Foundation have been developing a model of projection for spending on health care. This has been used previously by the Nuffield trust in a decade of austerity, by the Health Foundation in Transformation Fund and in Wales on Path to Sustainability. Currently mental health activity is not modelled, with the assumption put in place that spending on mental health services holds its share of total spending.

Aggregate results from the MHSDS data used for this work will inform the design of this part of the projection model, as well as digging deeper into trends and activity levels in secondary mental health services. This will help to improve greatly the quality of the spending projections model, as well as enabling organisations to project the likely demand pressures on mental health services themselves. Note that no patient level data between the two projects will be shared or combined.

Finally, mental health services are suffering from restricting budgets and growing demand and it is clear that significant efficiency savings are being made. The Health Foundation would like to learn more about how these savings are being achieved, where they can be duplicated elsewhere in the healthcare service.

It is also possible that these savings are gained through reduced service or quality of mental health service, as recent increases in delayed discharges may indicate (6). If this is the case then the Health Foundation would like to learn about where these reductions are occurring. The quality and extent of mental health services will have clear knock on implications for use of the rest of the service and incorporate them into the wider projection model.

References
(1) Nuffield Trust, 2012. A decade of austerity? The funding pressures facing the NHS from 2010/11 to 2021/22. https://www.nuffieldtrust.org.uk/research/a-decade-of-austerity-the-funding-pressures-facing-the-nhs-from-2010-11-to-2021-22
(2) NHS Confederation, 2016. Key facts and trends in mental health 2016 update.
http://www.nhsconfed.org/-/media/Confederation/Files/Publications/Documents/MHN-key-facts-and-trends-factsheet_Fs1356_3_WEB.pdf
(3) NHS Digital, 2017. NHS Workforce Statistics - March 2017, Provisional statistics. https://digital.nhs.uk/catalogue/PUB30003
(4) Community Care, 2015. Mental health trust funding down 8% from 2010 despite coalitions’ drive for parity of esteem. http://www.communitycare.co.uk/2015/03/20/mental-health-trust-funding-8-since-2010-despite-coalitions-drive-parity-esteem/
(5) NHS Digital, 2014. Personal Social Services: Expenditure and Unit Costs, England - 2013-14, Final release. https://digital.nhs.uk/catalogue/PUB16111
(6) Mind, 2017. Mind comments on delayed discharge in mental health trusts. https://www.mind.org.uk/news-campaigns/news/mind-comments-on-delayed-discharge-in-mental-health-trusts/#.Wmnvn65l-Ul

Expected Benefits:

The Health Foundation has strong links with NHS teams, national policymakers (e.g., NHS England) and patient advocacy groups. The Health Foundation provide leadership and advice on quality improvement as well as commentary on health care policy. The analysis of MHSDS data will inform these activities. The Health Foundation assess the impact using objective measures (e.g., number of publication downloads, publication citations and attendances at events and seminars) as well as record specific instances where our work has informed decision making for the NHS and improved the quality of care ultimately delivered to patients.

Due to these strong links with the health service, the Health Foundation is well positioned to reach as many beneficiaries as possible for this project. The Health Foundation will engage with relevant national policy makers including the Department of Health, NHS England and NHS improvement during the design of the modelling, to ensure they are aware of the work, and create a level of early buy in. The results will be published with a launch event in late Autumn 2018 to ensure the Health Foundation properly explain them, and invite open discussion. Following the analysis, The Health Foundation will discuss the results of the scenarios of different models of delivery to further inform policy makers on the impact that different decisions would have. These will mostly be discussions of the national situation, with some regional analysis at a level similar to government office regions.

This work will also feed into the projection model (1) that has been used and quoted by NHS Confed (2), the IFS (3), King’s Fund (4), Nuffield Trust, OBR (5) and NHS England (specifically Simon Stevens).

It will predominantly shed light on the likely pressures facing mental health services, which will help commissioners and care providers to effectively allocate funding. Importantly this will help insure the right level of investment and, particularly, workforce are available to meet the needs of those with mental ill health over the next 15 years.

The Health Foundation will soon be publishing a report of how money moves throughout the NHS based on an analysis of the Department of Health accounts. Throughout this process The Health Foundation have been in contact with the team at NHS England behind the mental health dashboard. Their team has been helpful and engaged with the Health Foundation to ensure the analysis accurately reflects NHS mental health spending and activity data. The Health Foundation plan to present their findings from this analysis to the NHS mental health spending team for peer review. In the wake of the mental health five year forward view, it will help inform the national planning process for mental health.

The Health Foundation hope to work with the NHS England team again during the analysis and reporting stage of the current project. This will ensure consistency and raise awareness. The aim of the analysis is to explore regional variations in mental health activity as well as project expected mental health activity and associated cost. The analysis can be used to plan and allocate resources to those areas which are expected to need them most, both regionally and within mental health clusters.

In addition, the findings of this work will be shared with relevant patient groups via the Health Foundation comms team. For example, the Health Foundation regularly gets in touch with relevant patient groups through a plain English summary of the findings together with a copy of the original publication. The Health Foundation will invite patients to get in touch if they would like to further discuss the work. The Health Foundation would be happy to present their results to their regular meetings or to invite patient representatives to external events.

References
(1) https://www.health.org.uk/sites/health/files/FundingOverview_NHSFundingProjections.pdf
(2) http://www.nhsconfed.org/news/2018/01/nhs-confederation-teams-up-with-independent-experts-for-study-into-health-and-care-funding
(3) https://www.ifs.org.uk/uploads/publications/budgets/gb2017/gb2017ch5.pdf
(4) https://www.kingsfund.org.uk/publications/hospital-activity-funding-changes
(5) http://cdn.obr.uk/July_2017_Fiscal_risks.pdf

Outputs:

Outputs for all projects will be in line with best practice guidelines on statistical disclosure control and privacy protection.

The project will aim to investigate whether there are significant differences in mental health activity across regions in England. If the analysis does find differences by region, The Health Foundation will investigate the extent of these differences and present the findings in the final report. The study will also aim to find the key drivers of these differences in activity in order to explain why differences in mental health activity occur.

The analysis will project the expected funding pressures on mental health services. Based on this, The Health Foundation will comment on the future budget required to keep up with expected mental health activity under a variety of scenarios including:

- Expected changes in population using ONS population projections by age, sex and region

- Expected changes in NHS pay, under the recent pay deal and after accounting for drift, it is expected that NHS staff pay will increase at an average annual rate of 2% over the next 15 years. Pay accounts for around 65% of hospital operating costs, pay increases will increase spending pressures on the NHS and therefore a larger budget will be required to keep up with expected mental health activity assuming all other factors are held constant.

- Efficiency savings from increased productivity. Using data from the OBR economic fiscal outlook , it is expected that efficiency gains of an average of 0.8% over the next 5 years. Higher productivity will increase efficiency and reduce the spending pressures on the NHS and mental health.

The primary output of this project will be a Health Foundation report, similar in style to the report ‘The path to sustainability' available at http://www.health.org.uk/publication/path-sustainability. It will provide an update to the funding pressures that are expected over the next 15-20 years. Before publishing, The Health Foundation will approach contacts from budgeting and planning organisations such as NHS England for peer review. One benefit of this is to ensure the findings are consistent with the expectations of the NHS and involved bodies, and by involving them early in the reporting process The Health Foundation can raise awareness of the upcoming publication. The report will be targeted at a national audience, with a discussion around regional variation in mental health activity. This report will be made publicly available through the Health Foundation’s website by 2021.

The main report will be written with the interested public in mind. There will be an accompanying technical appendix designed for technical experts seeking to replicate the methods used in the model. The final report will be published and publicised by the Health Foundations dedicated communications team, who regularly generate a wide reach for The Health Foundation's work, Including media, stakeholders in the English and UK health system and the public.

Note that the Health Foundation meets regularly with representatives from the Department of Health, NHS England and NHS Improvement. The proposed work will inform ongoing conversations with these organisations and interim findings will be presented to their representatives in addition to the more formal outputs listed above.


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

Processing:

Data will be processed only by approved users within the Health Foundation’s secure environment. All analysts with access to the data will have completed an accreditation course on data protection legislation and statistical disclosure control, completed an information security training specific to the Health Foundation’s infrastructure, and signed a non-disclosure agreement and the terms of use of the secure environment. All analysts with access to the data are substantive employees of the Health Foundation.

MHSDS Data will only be processed on the Health Foundation’s premises and any publication derived from the data will be subjected to best practice guidelines on Statistical Disclosure Control (SDC) including the Code of Practice on Confidential Information, the Anonymisation Standard for Publishing Health and Social Care Data and the code of practice published by the ICO, Anonymisation: managing data protection risk code of practice before being released form the environment.

For this project, person level data for mental health services is required. The project aims to project cost pressures over the next 15-20 years; therefore, The Health Foundation need to track historic trends over a similar period for the whole population. The minimum data required within this project are Mental health (MHSDS) data for the latest two financial years (2016/17 and 2017/18).

Since this involves modelling the evolution of health care utilisation for people with various specific health conditions in the different government office regions, it will need comprehensive data coverage for these two years on community services (1.c), inpatients records (2.a) and service users (3).

The Health Foundation will explore whether mental health service use is affected by factors including age, sex, residence (government office regions), diagnosis and procedure codes, treatment function, admission method, the presence of other long-term conditions and time.

The primary models will be independent service-specific linear, or log-linear person-level models of the trends in the level of activity for mental health services. The results of the models will be used to create projections for future use at a national level, and by government office regions (or other similar sized areas as appropriate). The Health Foundation will therefore apply the results of the analysis of historic trends to publicly available population and mortality projections produced by the Office of National Statistics.

The Health Foundation will explore the trend over time for mental health patients from the latest two financial years of MHDMS. These will be done using a linear regression, with transformations applied where appropriate to ensure the best fit for each condition. By producing trends in this way, The Health Foundation are able to explore the trends for certain co-morbidities, instead of using single condition prevalence projections. However, The Health Foundation will compare their estimates to national data on prevalence of these conditions where possible for assurance.

The projections for costs on these services will be combined with projections for other NHS services, such as GP attendances and community pharmacies, produced using publicly available data. The combining of projection results in this way will primarily be done at a national level, and will not be done at a level lower than government office region. Therefore, there are no privacy or confidentiality concerns when combining the results.

Having established the models and projections, the results will be used to test the impact of a series of assumptions around future changes in NHS delivery. This will take the form of modelling assumptions on how service delivery might change at a national level. For example, The Health Foundation will test the potential impact on total NHS spending of a substantial investment in GP practices, which might be expected to lead to a reduction in mental health activity. Again, these results will only be published at a level no lower than government office regions.

The Health Foundation will also explore the impact of likely productivity growth on the projected growth. This will be based on evidence of recent and longer-term levels of productivity growth by running random effects, fixed effects and stochastic frontier analysis on weighted activity of different types of providers. As with other analysis, results will be used at a national or large regional level.

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

There will be no data linkage undertaken with NHS digital data provided under this agreement.

Data provided under this agreement are also stored in a private secure data centre facility “UK Cloud” based in England. UK Cloud is ISO27001 and IG toolkit certified, and it is used by a number of UK Public Sector Organisations.

The Health Foundation is aware that they will not be able to estimate trends with only the latest two years of MHMDS data (2016/17 & 2017/18). Unfortunately, the only other financial year available (2015/16) from the MHMDS series is incomplete while the data series before 2015/16 is not compatible.

In order to address this limitation, it is proposed that the Health Foundation use aggregate public information from the Adult Psychiatric Morbidity Survey (APMS). This survey is carried out every 7 years and reports the treated prevalence of common mental disorders which has grown from 24.4% in 2007 to 39.4% in 2014. The APMS also gives a breakdown of data by age and sex, to which they can apply age and sex specific population estimates and projections.

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

For data from the Mental Health (MHSDS, MHLDDS, MHMDS) data sets, the following disclosure control rules must be applied:
• National-level figures only may be presented unrounded, without small number suppression
• Suppress all numbers between 0 and 5
• Round all other numbers to the nearest 5
• Percentages can be calculated based on unrounded values, but need to be rounded to the nearest integer in any outputs
• In addition for Learning Disability data in Mental Health (MHSDS, MHLDDS, MHMDS), the England-level data also must apply the suppression of all numbers between 0 and 5, and rounding of other numbers to the nearest 5.

The LIA was carried out by The Health Foundation using the ICO template and considered by NHS Digital. The Health Foundation concluded that they can rely on legitimate interests for this processing. A summary of the decision justification is provided below;

1. Purpose test: are you pursuing a legitimate interest? The Health Foundation is an independent charity committed to bringing about better health and health care for people in the UK. Their aim is a healthier population, supported by high quality health care that can be equitably accessed.

2. Necessity test: is the processing necessary for that purpose? Having access to pseudonymised patient records allows the Health Foundation to analyse the impact of new initiatives to drive learning and improvement. Given the complexity of the analyses, it is often not possible to rely on aggregate and/or less confidential data. An assessment is made for each use of data to ensure that no other means of aggregation can be used.

3. Balancing test: do the individual’s interests override the legitimate interest? The Health Foundation only process pseudonymised patient data (as anonymised with the ICO’s code of practice). There is no direct relationship and collection of information from the data subjects (e.g. patients).When possible, if the analysis involves potentially vulnerable groups the Heath Foundation seek the advice of external steering groups or advocacy patients groups to help us considering any further privacy implication and harm to data subjects. All data is held securely and all outputs are aggregated with small number suppressed.


Project 7 — DARS-NIC-35820-Y3H1M

Type of data: information not disclosed for TRE projects

Opt outs honoured: N

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Non Sensitive

When:2016.12 — 2017.02.

Access method: One-Off

Data-controller type:

Sublicensing allowed:

Datasets:

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

Objectives:

The Health Foundation is an independent charity working to improve health and the quality of health care in the United Kingdom. The Health Foundation is requesting access to data aiming to inform public discussions about the focus, design and effects of policies intended to improve the quality of health care in the United Kingdom or reduce costs. The project will inform policy makers and the NHS about the variability in quality of health care in England, and thus help to identify priority areas for improving health and social care

A “weekend effect” on mortality following emergency admission is well established. However, there is still uncertainty if this effect is due to patient mix or organisational characteristics. This project will be in two phases: Firstly, the Health Foundation will aim to understand the weekend effect and variation across all days of the week, optimising risk adjustment (case-mix), exploring the effect of organisational and staff-related factors and examining variability in the weekend effect between providers (cross-sectional). This analysis will inform a second phase, aiming to identify mortality trends (weekday and weekend) over time, classify English hospitals by observed trajectories and investigate relationships between ‘phenotypes’ and hospital characteristics (time-series). The study follows the ‘phenotyping’ approach used by Xu et al. (2014) for patients undergoing an emergency admission.

Expected Benefits:

The Health Foundation has strong links with NHS teams, national policymakers (e.g., NHS England) and patient advocacy groups. The Health Foundation provide leadership and advice on quality improvement as well as commentary on health care policy. The Health Foundations analysis of HES data will inform these activities. The Health Foundation assess the impact using objective measures (e.g., number of publication downloads, publication citations and attendances at events and seminars) as well as record specific instances where the work of The Health Foundation has informed decision making for the NHS and improved the quality of care ultimately delivered to patients.
Due to these strong links with the health service, the Health Foundation is in a good position to reach as much beneficiaries as possible for this project.

This study aims to evaluate the “weekend effect” by optimising risk adjustment and exploring factors that potentially contribute to it. Moreover, variation in provider performance between trusts will be explored, both cross-sectionally and over time. Identifying time trends in mortality rates between providers will shed light on the possible performance trajectories in improving quality of care at the weekend and any trade-offs in weekday quality and relate these to provider characteristics. This novel approach will provide useful information in light of a general policy move towards seven-day working. In addition, identifying providers who perform well or/and improve over time offers the opportunity to conduct qualitative research in the future that will help to understand the reasons behind these differences. Good performance processes can be collected and form part of a best-practice policy.

The analysis for the first phase of the project is expected to be completed by the end of 2016, with the aim to realise the benefits through publication by the Spring of 2017. The subsequent second phase will start in the first quarter of 2017, aiming for completion by the end of the year.

Outputs:

Outputs for this project will be in line with best practice guidelines on statistical disclosure control and privacy protection.

The aim is to publish the study and its findings in peer-reviewed international journals. These will be a mixture of health services research journals, and health economics journals. The health services journals the Health Foundation will target are: the BMJ, Health Services Research, Health Policy. The target economic journals include: the Journal of Health Economics, Health Economics, European Journal of Health Economics and the Journal of Health Services Research and Policy.
The Health Foundation will aim to submit for publication in spring 2017.

The aforementioned journals are read by policy makers, nationally and internationally, who wish to identify and classify providers according to the level of quality of care that they provide. Further engagement with key stakeholders will take place through presentation at conferences and events aimed at policy makers.

Throughout the analysis period the Health Foundation will actively engage with statutory bodies such as the Department of Health and Monitor, and international organisations involved in healthcare policy (e.g. OECD, WHO, the World Bank).

All published material will be in line with HSCIC’s ‘Code of Practice on Confidential Information’, the ‘Anonymisation Standard for publishing Health and Social Care Data’ and ICO’s guide to ‘Anonymisation: managing data protection risk code of practice’. All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide. All results are manually checked by two independent analysts.

All outputs (graphs, tables, results) that are released from the secure environment (and therefore being considered for publication) are subject to a process called Statistical Disclosure Control. This process ensures that re-identification of the outputs is not possible. In order to ensure this, the outputs themselves are considered, but also in combination with other information available in the public domain (this is called secondary disclosure). The Health Foundation follow best practice guidelines that are in line with NHS requirements. All outputs are considered by at least two members of staff, prior to being released from our secure environment.

Processing:

For this project data will be processed by a limited number of analysts within the Health Foundation’s secure environment. All researchers with access to the data will have completed information governance and data security training, as well as training specific to the Health Foundation’s infrastructure, and signed a non-disclosure agreement and the terms of use of the Foundation's Secure Data Environment.

HES Data will only be processed on the Health Foundation’s premises in London and any publication derived from the data will be subjected to best practice guidelines on Statistical Disclosure Control (SDC) including the Code of Practice on Confidential Information, the Anonymisation Standard for Publishing Health and Social Care Data and the code of practice published by the ICO, Anonymisation: managing data protection risk code of practice before being released from the environment.

Data requested:
This study will use admitted patient care data and accident and emergency data (cross-section only). The Health Foundation request non-sensitive date relating to patient characteristics (including IMD and rural/urban indicators), admissions, discharges, episodes and spells, clinical data; some provider information and GP practice code. In addition, the Health Foundation are requesting the variable mental category (mentcat), as this variable will help determine, together with the diagnosis codes, the subgroup of patients with mental ill health and severe mental ill health.
For the first phase of the project, the cross-sectional analysis the Health Foundation will only use data from 2012/13 to 2014/15, as the calculation of comorbidity indices used for risk adjustment requires data over the three years prior to each hospital admission. The second phase, the time-series analysis, requires data over a ten-year period to identify phenotypes. This will ensure an adequate period over which to identify changes in hospital performance (respective mortality rates) over time. In addition, as in the cross-sectional analysis, this analysis requires data over the three years prior to the initial trajectory analysis for the risk adjustment. Therefore we will need data for a 13-year period, from 2002/03 – 2014/15.
Although the majority of the analysis will be at trust level, patient level data is required to adequately risk adjust for case mix.

Additional data:
The data supplied by HSCIC will be linked to publicly available aggregate provider level data. The data used in the analysis will be supplemented by information that is already available in the public domain. HSCIC published trust level information including trust characteristics, staffing characteristics, number of beds, etc. This information will be linked to the HES using trust identifiers regularly available on HES.

Processing:
Different methods of risk-adjustment will be explored in the cross-sectional analysis, building on previously established models. The descriptive analysis will look at the variation in admissions and 30-day mortality by provider (hospital site and trust) level.

Risk-standardised 30-day mortality rates will be estimated for each provider, by adjusting for differences in patient case-mix. For the cross-sectional analysis, these will be estimated for each day of the week, as well as aggregated over the weekend (Sat-Sun) and weekdays (Mon-Fri). In addition, an alternative definition of weekend will be explored as a sensitivity analysis, using the A&E conclusion date and time, for patients who attend A&E. Due to lack of data for the 10-year period, the time-series analysis will concentrate on weekend (Sat-Sun) vs weekday (Mon-Fri). Risk-standardised mortality rates will be calculated quarterly and annually for the time series analysis.

Multivariate logistic regression analysis will be conducted to estimate relationships between provider characteristics, the weekend effect and 30-day mortality (cross-sectional and time-series).

The provider phenotypes will be identified using a group-based, semi parametric mixture modelling approach via the SAS macro PROC TRAJ. The determination of phenotypes will depend upon the Bayesian Information Criteria index, average posterior probability of phenotype and 95% confidence intervals of adjacent trajectories.

Outputs:
Outputs will be released at hospital or trust level. However, the Health Foundation will not identify individual hospitals in our output.

The Health Foundation will produce risk-standardised 30-day mortality rates for each day of the week (cross-sectional study only) and for weekdays and weekends, at hospital site and trust level (cross-sectional and time-series analysis).

The multivariate logistic regression analysis will produce regression coefficients, associated p-values and odds ratios. These data will help understand the influence and importance that different provider characteristics (e.g. if it is a teaching hospital, which region it belongs to, staffing levels) have on 30-day mortality rates and how these are associated with the observed weekend effect.

Odds ratios of 30-day mortality by day of the week will be displayed and illustrated using box plots.

Charts mapping the changes over time in 30-day mortality by provider across the study period will be produced.

Depending on the number of identified phenotypes, graphics displaying the obtained trajectories will be created (e.g. high weekday mortality and low weekend mortality, or high weekday and low weekend mortality rates). Each provider can be attributed to one of the created graphics – making classification and groupings of trusts easier and more visual.

Similar output will be created for the subgroup analyses on patient groups of particular interest: depending on route of admission (through A&E or direct admissions); for emergency surgery, myocardial infarction, stroke, heart failure; and patients with mental ill health.

Minimisation efforts related to the inpatient data:
Only non-sensitive data relating to patient characteristics, admissions, discharges, episodes and spells, and clinical data are requested. Out of the available socio-economic data, only rural/urban indicator, LSOA and overall IMD information is requested. This information is necessary to identify the patient population of interest, outcomes and patient characteristics such as age, gender, comorbidities and IMD scores, which will be used in the matching process and in the modelling.
Also requested is the GP practice code and some organisational variables but these have been restricted to provider type and code and site code. These variables are needed for the trust level analyses.
In addition, there is a request for the variable mental category (mentcat), as this variable will help determine, together with the diagnosis codes, the subgroup of patients with mental ill health and severe mental ill health.
This application has not requested variables that are sensitive/identifiable, nor other variables that are not necessary to the analysis, such as items relating to Health Research Group, Maternity, Augmented care period, or psychiatry.

Time period:
The cross-sectional analysis requires data for one year only. However, the calculation of the comorbidity indices used for risk adjustment requires data for up to three years prior to each hospital admission. The time-series analysis requires data over a ten-year period to identify phenotypes. This will ensure an adequate period over which to identify changes in hospital performance (respective mortality rates) over time. In addition, as in the cross-sectional analysis, this analysis requires data over the three years prior to the initial trajectory analysis for the risk adjustment

Minimisation efforts related to A&E data:
Only non-sensitive data relating to patient characteristics (incl rural/urban indicator, LSOA and overall IMD information), attendances, clinical diagnoses and clinical treatment, some provider information and GP practice code were requested.
The A&E attendances will be linked to the ACP admissions, using information on patient characteristics and dates. Information such arrival mode may be relevant to risk adjustment. The A&E discharge time will be used as proxy for admission time.