NHS Digital Data Release Register - reformatted

University Of Essex projects

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

Examining intersectional inequalities in effective stroke care and stroke outcomes across England — DARS-NIC-720122-Y6Q0Y

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

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

Purposes: No (Academic)

Sensitive: Sensitive, and Non-Sensitive

When:DSA runs 2025-08 – 2026-08

Access method: Ongoing

Data-controller type: UNIVERSITY OF ESSEX

Sublicensing allowed: No

AGD/predecessor discussions: AGD minutes - 3rd July 2025 Final.pdf

Datasets:

  1. Civil Registrations of Death
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)

Type of data: Anonymised - ICO Code Compliant

Objectives:

The University of Essex requires access to NHS England data for the purpose of the following research project:
Examining intersectional inequalities in effective stroke care and stroke outcomes across England

The following is a summary of the aims of the research project provided by the University of Essex:

Stroke stands as the fourth leading cause of death in the UK and one of the biggest causes of disability. There are currently an estimated 1 million people in the UK living with the aftermath of stroke, with approx. 30,000 people dying from stroke each year. Furthermore, the incidence of stroke is expected to increase by 60% by the year 2035 in the UK, with the population of stroke survivors expected to double, making stroke a priority for the health system.

While previous research has shown that deprivation, age, gender, ethnicity, and place of residence (rural/urban) each have an impact on stroke care quality, stroke prevalence and stroke outcomes, no studies have considered the impact of the intersection of these inequalities. In order to ensure that no one is left behind when addressing inequalities in health including stroke, an intersectional approach is indispensable. For example, considering the effect of gender and ethnicity separately can lead to missing the unique care experience of an intersecting identity such as the experience of a black woman. Building on this thought the experience of a black woman in a coastal area might be worse than the experience of a black woman in a non-coastal area and an intersectional lens would allows us to identify these unique experiences.

Furthermore, no research within the UK exists that examines the geographical disparities between coastal and non coastal town when it comes to stroke care and outcomes, despite this being highlighted as an area of concern by both the existing literature and the project partner, the local NHS trust. No current research evaluating stroke care services based on a health system approach that considers both quality of care and important aspect of universal health coverage such as availability, accessibility and contact coverage. With resources being distributed unequally within the country and the strains put on the ambulance services due to the COVID-19 pandemic and NHS underfunding, it is both timely and of extreme importance to consider these elements of health coverage alongside quality of care indicators.

The aim of this project is to identify the intersectional inequalities in the effective coverage of stroke care and post-stroke outcomes, and their negative health consequences within England, and provide evidence for improvement.

This research is the quantitative part of the larger CoastGEM (Coastal Gap in Equality for Stroke care Management) project created in partnership between the University of Essex and the East Suffolk and North Essex Foundation Trust to better address inequalities in stroke and to ensure no one gets left behind. This research will be a part of a PhD thesis.

The methodology is split into two sections:

1. A quantitative analysis of data from the Sentinel Stroke National Audit Programme (SSNAP) set to examine the intersectional inequalities in the effective coverage of stroke care.

2. A quantitative analysis of linked Hospital Episode Statistics and Office of National Statistics mortality data from NHS Digital to examine the intersectional inequalities in mortality at 30 days and 1 year post-stroke, and a sequence data analysis to identify the inequalities in the care pathways 1-year post-stroke.

This data request is solely concerned with the second part of the project. SSNAP data will be sought separately through SSNAP directly.

The following NHS England Data will be accessed:
> Hospital Episode Statistics Admitted Patient Care (HES APC)
> Civil Registration Mortality

These datasets are required to create 1-year post stroke pathways for patients using the number and length of each hospital admission, as well as the type of admission to enable clustering analysis and identify the most common type of patterns. For example, this will allow the researchers to distinguish whether some patients are more likely to have less hospital admissions within the 1st year post stroke or whether some are more likely to have more hospital admission, as well as the severity of these based on type or whether some pathways result in death more often. Analysis will then be conducted on the identified pathways to analyse whether intersectional inequalities make a patient more likely to be on a 1-year post-stroke pathway with more admission of a higher type when compared to others.

Sensitive derived date of death is required to perform the sequence analysis part of the analysis, creating sequences and timelines from first hospital admission to death within the 1st year after stroke. Once these sequences have been established and the four most common timelines identified, the effect of belonging to an intersectional identity can then be examined as well.

The level of the Data will be:
> Pseudonymised

Sensitive patient characteristics such as gender will also be requested. This data will be used for intersectional analysis to analyse the social context of individuals.

LSOA is also required from HES APC for the following reasons:
- To calculate distances from the LSOA to their respective place of care.
- To place the LSOA within an aggregated group of rural/urban origin or coastal/non-coastal origin based on ONS classification available classification for LSOA's.

The importance of accounting for coastal and rural communities and the lack of accessibility for these patients has been strongly echoed by both the NHS Trust and patient voice-oriented charities such as Healthwatch Essex. Furthermore, the lack of research available in these areas makes the inclusion of such data all the timelier and more important.

The Data will be minimised as follows:
> Limited to Data between 2020/21 - latest available
> For HES, limited to a cohort of individuals identified by NHS England who have a stroke event or an event associated with stroke - diabetes, atrial fibrillation and hypertension. This level of minimisation is not feasible for the deaths dataset.

The University of Essex is the research sponsor and the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:

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

Stroke specialists, including stroke nurses, rehabilitation staff, and the stroke lead from Colchester Hospital have communicated that this research is both timely and needed for both the local area and England overall. They have highlighted that there is very little research on inequalities in stroke care and outcomes, despite their experiences showing that inequalities are present and that they negatively affect the patient’s care. This processing is in the public interest because this project aims to provide evidence for the reduction of inequalities in stroke care and outcomes.

The funding is provided by East Suffolk and North Essex Foundation Trust. The funding is specifically for the PhD project described.

The funder will have no ability to suppress or otherwise limit the publication of findings.

The funder, East Suffolk and North Essex Foundation Trust, has provided advice on the objectives and methodology to ensure that the research is accurate, timely and is in line with the needs outlined by stroke care providers. Feedback has also been provided on each indicator selected by the stroke leads at Colchester Hospital.

Data will be accessed by:
> Substantive employees of the University of Essex.
> A PhD student enrolled with the University of Essex. The individual has completed mandatory data protection and confidentiality training and is subject to the University of Essex’s policies on data protection and confidentiality. The individual accessing the data will do so under the supervision of a substantive employee of the University of Essex. the University of Essex would be responsible and liable for any work carried out by the individual. The PhD student would only work on the data for the purposes described in this Data Sharing Agreement (DSA).

Patient involvement is being sought through the involvement of Healthwatch Essex who act as a representative for patient voices in the local community and run monthly sessions with patients specifically designed to involve them in research.

Expected Benefits:

Intersectional literature has shown that outcomes can vary for between intersectional identities in a very different way than they vary between one single inequality such as gender or age. For example, outcomes can be very different for an old-black-female patient living in a low-income area in a rural/coastal town versus the outcome for a young-white-male living in a high-income area in an urban/non-coastal town.

The findings of this research are expected to identify the intersectional inequalities in stroke care and outcomes and provide evidence for policymakers to use in improving the stroke care delivery system. This project's main objectives for impact are:
1. To ensure intersectional inequalities are reflected in stroke policies and guidelines
2. To provide evidence of the geographical inequalities in stroke care and outcomes

The use of the data could:
- help the system to better understand the health and care needs of populations.
- lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
- advance understanding of regional and national trends in health and social care needs.
- advance understanding of the need for, or effectiveness of, preventative health and care measures for particular populations or conditions.
- inform planning health services and programmes, for example to improve equity of access, experience and outcomes.
- inform decisions on how to effectively allocate and evaluate funding according to health needs.
- provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.
- support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

The University of Essex expect policies resulting from these findings to create care that is more inclusive, ensuring that nobody gets left behind and everybody receives the high-quality care that they need. By improving care, this project ultimately aims to improve stroke outcomes and reduce mortality as a result of stroke, as well as provide a model for the identification of intersectional inequalities to be used in the study of other diseases.

To ensure this impact is achieved, the project's partnerships with the local NHS Trust (ESNEFT), Healthwatch Essex, and local stroke charities will be crucial. By engaging both stroke care providers, stroke patients and the local community both in creating this research project and disseminating it, the University of Essex aim to raise awareness of the intersectional inequalities in stroke and provide timely evidence for improvement.

Outputs:

The expected outputs of the processing will be:
> Submissions to peer reviewed journals: two submissions are expected - one on the intersectional inequalities in stroke mortality and one on the 1-year stroke pathways created using sequence analysis on hospital admission trends.
> Presentations at stroke-oriented conferences such as the UK Stroke Forum Conference, International Stroke Conference and UK Stroke Conference. Conferences oriented on the use of the type of methodology and sequence analysis used will also be sought out.

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

The outputs will be communicated to relevant recipients through the following dissemination channels:
> Journals
> Conferences
> Findings will be disseminated with the help of the NHS Trust via their network
> Findings will be disseminated within the university through participation in the annual Student-Staff Conference and the summer methodology in health-focused seminars within the Institute for Public Health and Well-Being
> Findings will be disseminated to stroke patients directly as well through a partnership with Healthwatch Essex and local stroke charities in North Essex.

The project expects to produce the above outputs within 1 year following data access.

Processing:

No data will flow to NHS England for the purposes of this Data Sharing Agreement (DSA).

NHS England will grant access to the Data via the Secure Data Environment (SDE). The SDE is a secure data and research analysis platform. It allows approved researchers with approved projects access to pseudonymised data and industry-leading analytics tools.

NHS England will provide access to the relevant records from the HES and Deaths datasets to the University of Essex via NHS England Secure Data Environment (SDE). The Data will contain no direct identifying data items. The Data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

SDE users can request exportation of aggregated analysis results (suppressed and summarised according to the NHSE SDE Disclosure Control rules) subject to review and approval by the NHS England SDE Output Checking team. The SDE Output Checking team will ensure that no output contains information which could be used either on its own or in conjunction with other data to breach an individual's privacy.

Users must identify themselves via a multi-factor authentication mechanism and are only able to access the datasets detailed within this DSA. The access and use of the system is fully auditable, and all users must comply with the use of the Data as specified in this DSA.

Users are only authorised to access the Data specified in this DSA and can utilise a variety of analytical tools available within the SDE platform. Users are not permitted to export record-level data from the SDE.

The Data will be stored on servers at NHS England.

The Data will be accessed by authorised personnel via remote access.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Remote processing will be from secure locations within England. The data will not leave England at any time.

Access is restricted to employees of the University of Essex and PhD students enrolled with the University of Essex who have authorisation from the PhD supervisor, a Professor of Global Public Health.

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

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

Researchers from, or PhD students enrolled with, the University of Essex will process the Data for the purposes described above.

National Child Measurement Programme (NCMP) School Level Results with LA Flag — DARS-NIC-658395-F0F9N

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

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

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2023-02 – 2026-02

Access method: One-Off

Data-controller type: UNIVERSITY OF ESSEX

Sublicensing allowed: No

AGD/predecessor discussions: AGD minutes - 23 February 2023 final.pdf

Datasets:

  1. National Child Measurement Programme

Type of data: Anonymised - ICO Code Compliant

Objectives:

The objective of this study is to investigate the impact of Universal Free School Meal (UFSM) programmes run in several local authorities in England since 2004 on children's bodyweight outcomes. Previous research by the applicants showed that the Universal Infant Free School Meals policy (UIFSM) which from 2014 makes a free lunch available to all infants in state-funded schools in England significantly reduces children's bodyweights in Reception year. Evaluating the earlier and ongoing local authority schemes will provide additional evidence on the longer-term impacts of UFSM on children's outcomes at age 11 and assess the programme features (such as the number of years free meals are provided and the ages at which they are provided) that are linked to positive outcomes for students, and how these differ by student background. This will be achieved by estimating a statistical model to compare the outcomes of children in local authorities implementing such schemes with the outcomes of otherwise-similar children for whom these were never available.

The analysis will help establish if UFSM policies are, or could be adapted to be, cost-effective in terms of future health of those receiving it. Results may feed into ongoing policy discussions around the retention, expansion and further development of the UIFSM policy, as well as into the development of any local authority-based UFSM initiatives.

The data request asks for inclusion of a Local Authority (LA) identifier which was not included in a previous data extract disseminated to the University of Essex under a separate data sharing agreement. The LA identifier will allow The University of Essex to link to the data extract of publicly available data on characteristics of the LA such as expenditure on health, for example. This will allow The University of Essex to control for other LA-level factors and policies that may affect child weight outcomes, other than the Universal Free School Meal policies that is currently being studied, and therefore avoid confounding the effect of interest with other LA-level effects.

This research proposal is aligned with the overarching NCMP Research Priority to improve the use of NCMP data to benefit child health. The Government remain committed to addressing obesity and to halving childhood obesity and this research will provide insights as to how other government policy is impacting that ambition.

The University of Essex will be the Data Controller for this disseminated data, and will process the disseminated data.

The application is based on external funding from the Nuffield Foundation who will have no access to any data and will not be able to influence or suppress the findings of the survey

Outputs:

The main outputs of the project will be a project report and a research brief. It is expected that an academic paper will be submitted to a leading international economics journals, which will also be presented at national and international academic conferences.

The results of the project will be of interest to a variety of stakeholders, including policy makers at the Department for Education and Department of Health, practitioners at schools, third sector organisations such as the Children's Food Trust and those interested in child obesity, the media and the general public. The findings will be disseminated widely through dedicated web pages, Institute for Social and Economic Research (ISER) newsletter, a dissemination event aimed at policy makers, practitioners and academics, press release and subsequent media engagement to ensure the policy audience is reached.

The results included in these outputs will be descriptive statistics such as means and standard deviations, and regression coefficients from statistical models; small numbers will never be included. Outputs will contain only aggregate level data and no school level data will be published. All outputs will comply with the ICO Guide for Anonymisation. All outputs will be cleared with NHS England before publication.

The project will begin in January 2023. Presentation of results will take place from the spring/summer of 2023 and throughout the year, with publication of the report, research brief and dissemination event for academic and non-academic audiences (including press release) planned for May 2023.

Processing:

NHS England will transfer the NCMP data requested to the Institute for Social and Economic Research at The University of Essex by Secure Electronic File Transfer where it will be analysed by researchers at the University of Essex ("the research team") only. Data processing is only carried out by substantive employees of The University of Essex who have been appropriately trained in data protection and confidentiality.

The data requested will be aggregated to the school level and will use pseudonymised school IDs. Data in each field will be calculated to 1 decimal place, and schools with less than 20 children per year group on average in a particular year will be excluded from the file. No further suppression of small numbers will take place as this will suppress the obesity prevalence levels for around two-thirds of schools making the data not usable for this project.

NHS England does not hold information on school characteristics such as proportion of children eligible for or taking up means-tested Free School Meals, school type (e,g, Community, Academy), or Ofsted rating. The University of Essex will transfer a file of school-by-year level data containing this information to NHS England which will be merged with the NCMP data before it is passed back to the University. The data will not be transferred to or shared with any other organisation. The school-level data for linkage, to be supplied by The University of Essex, are derived from Department for Education ‘Schools, Pupils and Characteristics’ datasets that are publicly available and freely downloadable (https://www.gov.uk/government/statistics/schools-pupils-and-their-characteristics-january-2019 and equivalent for earlier years); and from a database of dates of provision of universal free breakfasts, supplied by the charity Magic Breakfast to The University of Essex for the purposes of this project.

The data will be analysed using statistical methods such as regression analysis, before/after introduction comparisons, difference-in-difference statistical techniques. The research team is requesting a number of years before and after the implementation of the free lunch programs so that they can appropriately control for trends in weight.

There will be no attempt or requirement to re-identify any individuals or schools in the data.

National Child Measurement Programme - effect of providing free lunches to infant school children. — DARS-NIC-82493-P8Y3N

Opt outs honoured: (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2019-12 – 2020-11

Access method: One-Off

Data-controller type: UNIVERSITY OF ESSEX

Sublicensing allowed: No

AGD/predecessor discussions: igard-minutes---28th-may-2020-final.pdf.pdf, igardminutes-4thfebruary2021final_.pdf, IGARD_Minutes_27.04.17.pdf, IGARD_Minutes_11.05.17.pdf

Datasets:

  1. National Child Measurement Programme

Type of data: Anonymised - ICO Code Compliant

Yielded Benefits:

A paper was drafted and presented the results at the Royal Economic Society conference in April 2019, the European Association of Labour Economists conference in September 2019 and at a seminar at NTNU, Norway. Based on the feedback received the study is currently performing further checks and refining the analysis more to get a better picture of the mechanisms that drive the beneficial results found. Spoke about findings at a panel event on the future of universal free school meals at the Labour Party conference fringe in September 2019. A parallel event scheduled for the Conservative conference was cancelled as no parliamentarians were prepared to attend. A meeting has been scheduled with the Cabinet Office, DfE and DHSC to discuss the results. Ultimately, through this research, the hope is that the results will feed into the policy around free meals at school. This is how it is hoped the research will benefit health of children. The findings to date are summarised in the draft abstract as follows: "The Impact of Universal Infant Free School Meals on Child body weight outcomes Since September 2014 school lunches – previously free for very low income students - are available to all children in England in their first three years in school free of charge. We draw on data from the National Child Measurement Program (NCMP) to evaluate the effect of switching from targeted to universal free lunch provision on the body weight outcomes of children aged 4-5, showing how the treatment effect evolves over the school year as the cumulative dosage of exposure to free meals increases. By the end of the school year, on average a child exposed to free lunches is 1 percentage point more likely to be of ‘healthy weight’ and 0.5 percentage points less likely to be obese, and has body mass index (BMI) that is 4.2% of a standard deviation lower than one who is not."

Outputs:

The main outputs of the project will be a project report and a research brief. It is expected that two academic papers will be submitted to leading international economics journals, which will also be present at national and international academic conferences (see yielded benefits).

The results of the project are of interest to a variety of stakeholders, including policy makers at Department for Education and Department of Health, practitioners at schools, third sector organisations such as the Children’s Food Trust and those interested in child obesity, the media and the general public. The findings will be disseminated widely through dedicated web pages, Institute for Social and Economic Research (ISER) newsletter, a dissemination event aimed at policy makers, practitioners and academics, press release and subsequent media engagement to ensure the policy audience is reached.

The results included in these outputs will be descriptive statistics such as means and standard deviations, and regression coefficients from statistical models; small numbers will never be included. Outputs will be aggregated with small numbers suppressed. All outputs will comply with the ICO Guide for Anonymisation. All outputs will be cleared with NHS Digital before publication.

Presentation of results took place from the second half of 2018 and throughout first half of 2019, with publication of the report, research brief and dissemination event for academic and non-academic audiences (including press release) completed. Submission of the academic paper to an economics journal is also planned for late 2019/ beginning of 2020. It is expected that academic reviewers will ask for additional checks and analysis, making access to the data for a longer time-period necessary.

All publications based on this dataset will be shared with Public Health England via NHS Digital before they are published. PHE will have no access to unsuppressed data and will not be able to influence or suppress the findings of the study.

Processing:

Under a previous agreement, NHS Digital transferred the NCMP data requested to the Institute for Social and Economic Research at the University of Essex by Secure Electronic File Transfer where it will be analysed by researchers at the University of Essex (“the research team”) only. All individuals with access to the data containing small numbers are substantive employees of the University of Essex. The data requested will be aggregated containing small numbers and will use pseudonymised school IDs. No suppression of small numbers will take place as this will suppress the obesity prevalence levels for around two-thirds of schools making the data not usable for this project.

NHS Digital does not hold information on the proportion of children on Free School Meals (FSM). FSM take up rates and the deprivation quintile of school (using the Income Deprivation Affecting Children Score) and the take-up rates of school meals which are some of the contextual data items requested. The FSM value and take-up rates will also be grouped into quintiles (5 bands) to mitigate against re-identification.

The University of Essex transferred a file of aggragated school level data containing this information to NHS digital which was merged with the NCMP data before it is passed back to the University. The data will not be transferred to or shared with any other organisation. The data will be analysed using statistical methods such as regression analysis, before/after introduction comparisons, difference-in-difference statistical techniques. The research team is requesting a number of years before and after the implementation of the free lunch program so that they can appropriately control for trends in weight. They will not match the data to any other data source.

The program will be considered to have been of benefit to children if there is a decrease in the proportion of children of unhealthy weight (after controlling for school level factors and trends in weight).
The following conditions apply:
1. No attempt will be made to re-identify a school or a pupil
2. No school level data will be published.
3. There will be no attempt to link the data with other datasets.
4. All publications based on this dataset will be cleared through the Information Asset Owner at NHS Digital who will ensure no school or child can be identified. If he/she is not sure then advice will be sought by the Disclosure Control Panel which is chaired by the Head of Profession for Statistics.

NHS Digital feel that based on these controls there will be very low chance of re-identifying an individual child.

No new data will flow under this agreement. As a paper has now been drafted and presented, it is expected that academic reviewers will ask for additional checks and analysis, making access to the data for a longer time-period necessary.

This project has been based on external funding from the Nuffield Foundation. This extension, however, is not covered by the grant and will be funded by The Research Centre on Micro-Social Change (ESRC-funded). Neither have access to any unsuppressed data and will not be able to influence or suppress the findings of the survey.

Evaluating the effects of Community Treatment Orders (CTO) in England — DARS-NIC-07360-K4R9R

Opt outs honoured: N (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007 , Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii)

Purposes: No (Academic)

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

When:DSA runs 2019-04 – 2022-03 2016.09 — 2016.11.

Access method: One-Off

Data-controller type: UNIVERSITY OF SOUTHAMPTON

Sublicensing allowed: No

AGD/predecessor discussions: igard-minutes-05-july-2018.pdf

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Mental Health Minimum Data Set
  3. Office for National Statistics Mortality Data (linkable to HES)
  4. Bridge file: Hospital Episode Statistics to Mental Health Minimum Data Set
  5. Civil Registration (Deaths) - Secondary Care Cut
  6. HES:Civil Registration (Deaths) bridge
  7. Civil Registrations of Death - Secondary Care Cut
  8. Hospital Episode Statistics Accident and Emergency (HES A and E)
  9. Mental Health Minimum Data Set (MHMDS)

Type of data: Anonymised - ICO Code Compliant

Objectives:

Community Treatment Orders (CTOs) were introduced to the Mental Health Act in 2007 in England and 2008 in Wales allowing patients detained in hospital to continue treatment in the community under specific conditions. To be eligible for a CTO, a patient must be detained in the hospital under the Mental Health Act on a section that allows for compulsory treatment. Around 20,000 patients have been placed on CTOs since 2008. CTOs were introduced to reduce the ‘revolving door’ phenomenon (frequent re-admission to hospital by small number of people with severe and persistent mental illness) and to provide treatment in the least restrictive setting. In practice CTOs tend to be applied at the end of an admission, following complete remission, as a means of optimising treatment adherence in those likely to default or disengage from care. Patients and carers perceive CTOs as coercive and mainly concerned with medication adherence. The use of CTOs remains controversial as its applications seems to run counter to the notions of ‘preventative’ and ‘least restriction’ for which CTOs were introduced to the mental health care system.

The Oxford Community Treatment Order Evaluation Trail (OCTET) compared discharged from hospital on a CTO with discharge from the hospital under section 17 of the Mental Health Act. No significant differences between the groups were found. Swartz et al (1999) randomized 264 severe and persistent mentally ill patients to either CTO or voluntary care following discharge. The results showed that schizophrenia patients on CTO for longer than 180 days had fewer hospital admissions and spend less time in the hospital then the controls receiving voluntary care. Limitations of these trial studies include small sample size, sample selection (exclusion of specific patients, refusal of participation by specific patients). In addition, the relative brief duration of follow-up might be too short to observe beneficial outcomes. Observational studies evaluating CTOs have been undertaken in diverse settings, at different times, using different methods. Results from these studies are inconsistent. Discrepant findings about CTO outcomes highlight the importance of local context. Understanding the effects of local context may also be the key to explaining persistent ethnic inequalities in CTO use.

This lack of evidence for the effectiveness of CTOs is problematic for policy makers, service commissioners and providers and for those who receive mental health care. CTOs require stringent governance and therefore place significant demands on the already stretched NHS mental health budgets. CTOs also reduce satisfaction with care and increase stigma. The Care Quality Commission and the House of Commons Health Committee have called for research into the ‘value of CTOs in different clinical and social circumstances’. The House of Commons Health Committee has noted:’… that the evidence base for this policy remains sparse…’ and recommended ‘…,a fuller analysis of the value of a CTO in different clinical situations’.

The aims of this research project are:

1. To explore spatial and secular variation in the use of Community Treatment Orders (CTOs) in England over a four-year period (2011/12 to 2014/15), including variation between people, places and services and over time in the likelihood of patients on Sections 3 and 37 being placed on CTOs, and in the frequency and time to subsequent events including recall, revocation, readmission and discharge from CTO.

2. To describe and model associations between CTO use and outcomes, namely re-admission, time spent in hospital, time spent in intensive psychiatric care or forensic units, episodes of seclusion and restraint, community mental health service contacts, criminal justice system contacts, Accident & Emergency Department attendances and deaths, after adjusting for propensity to require compulsory treatment.

3. To test the hypotheses that outcomes associated with CTOs (including the re-admission and the adverse outcomes listed in (3) above) vary between people and places. These models will be used to explore which patients, if any, benefit from CTOs and the types of places and service context where CTOs might have the greatest impact on patient and service-level outcomes.

4.To model the additional health care costs associated with CTOs (including administrative and regulatory costs) and the impacts of increasing or decreasing their use using a range of projections.

Note: The term ‘Mental Health (MH)’ data is used to refer to the Health and Social Care Information Centre’s Mental Health Minimum Data Set (MHMDS) for the years from 2011/12 to 2014/15 and Mental Health and Learning Difficulties Minimum Data set for the years since 2014. MH data will be used to address these questions. A cohort of mental health users will be selected from MH data and these records will be linked with corresponding Hospital Episode Statistics Accident and Emergency and ONS Mortality records.

Using Lower Super Output Area (LSOA), ONS staff will link HSCIC MH data to the publicly available data, i.e. Indices of Multiple Deprivation (Department for Communities and Local Government) and aggregate LSOA Census 2011 (ONS) data. This is to further explore the spatial variation in CTO use in England. Effectiveness of CTO will be measured in relation to compulsory treatment. The exposed group will be patients discharged from the hospital on CTOs, the unexposed group will be patients discharged from hospital treatment orders but not subject to CTOs. The two groups will be matched on time of discharge, service provider, and propensity score. The HSCIC data will be used to determine the effectiveness of CTOs compared to compulsory treatment.

Primarily this project will lead to submission of academic papers describing spatial and secular variations in the use of CTOs in England, the effectiveness of CTOs, and healthcare costs associated with CTOs. Results from the project will be presented at internal and external conferences. Findings from the research will be used to engage with public/ third sector organisations or mental health care providers during meetings or conferences. The Mental Health Foundation is a key partner in this research project. With their help two expert reference groups will be recruited: one with carers/mental health care users and one with mental health care professionals. These reference groups will meet to discuss the study aims and methods as well as comment on the released non-disclosive results and support dissemination of findings.

Yielded Benefits:

The lack of evidence for the effectiveness of CTOs is problematic for policy makers, service commissioners and providers and for those who receive (and those who care for people receiving) mental health care. CTOs require stringent governance and therefore place significant (and costly) administrative demands on already stretch NHS mental health budgets. They are perceived by patients and carers as coercive and focused on ensuring medication compliance at the expense of other forms of treatment and (social) support. CTOs may reduce satisfaction with care and increase stigma without achieving any positive health or social care gains. The Care Quality Commission and the House of Common Health Committee have called for research into “the value of CTOs in different clinical and social circumstances”, for instance by evaluating whether CTOs are having an impact on ‘revolving door’ patients, something that clinical trials cannot address and whether and how CTO use is related to uses of other parts of the MHA, given accelerating detention rates. It is possible that services in which large numbers of patients are placed on CTOs are also places with high rates of compulsory admission. With NIHR approval, an advance summary of the research was provided and cited by the Wessely Independent Review of the Mental Health Act. Further detail on the study is eagerly awaited as the Review enters its discussion and implementation phases and we are keen to seize this opportunity to ensure significant impact. The extended data access will facilitate this achievement, offering, for the first time, insights into the practicalities of CTO use drawing on a large ‘real-world’ population study and providing a grounded evidence base for determining the future of CTOs.

Expected Benefits:

Date:
• Improved insight in the use of CTOs. CTOs have been used far more extensively than was anticipated. Analyses will show when, where, and for whom CTOs are being used. Understanding the large spatial and secular variation in the use of CTOs can help inform mental health policy and support commissioning decisions on productive monitoring procedures for CTOs.

• Developing evidence on the effectiveness of CTOs. Understanding patient and outcome characteristics can help identify those inpatient detained under hospital treatment orders that would benefit most from CTO upon release from the hospital.

• Understanding the cost-effectiveness of CTOs. Identifying positive outcomes and the reduced health care costs associated with the use of CTOs will help direct mental health care related funds to where they are most needed.

• Findings that can be translated into actionable conclusions for service users. Involvement of mental health care users, carers, and professionals will ensure a study focus on outcomes and associations relevant to mental health care users. The findings can then be translated into patient-approved interventions. Involvement of the Mental Health Foundations also facilitates dissemination of study findings.

• Findings with direct policy relevance. The research team will ensure that these findings are shared at the earliest opportunity with the Care Quality Commission, the Department of Health, the Chief Medical Officer, the Royal College of Psychiatrists, the NHS Confederation, and NICE.

• Guidance to the National Institute for Health Research on strategies for future policy and practice with regard to CTO use in England. Results might inform future interventions to reduce compulsory admission and variation in CTO use. The research team will work on facilitating the adoption of these patient beneficial interventions within the NHS.

The project is expected to start around March 2016 and expected to be completed in March 2018. Funding for this project has been requested for a period of 2-years.

Outputs:

The expected outputs from this study will include papers on:

• The use of CTOs in England including variations in rates of CTO use at different spatial levels

• The hypotheses that CTOs are associated with reduced (mental health) inpatient care, reduced interaction with accident and emergency services, reduced mortality, and increased community mental health service contacts and these associations vary between places after controlling for patient characteristics.

• The health care resources employed by CTOs for mental health treatment

In addition to mandatory publication in the NIHR Journals Library as required by the project’s funder, the findings will be submitted to high impact journals.

Presentations of interim results will be made to relevant national and international conferences.

The project (i.e. production and dissemination of outputs) is expected to be completed in September 2018. Funding for this project has been awarded for a period of 2-years from March 2016. The project has an absolute end date of September 2020.

The intention is to maximise the potential impact and societal benefits of the research through:
1. Presentation of findings and contributions at national and international scientific conferences
2. Workshops for key stakeholders in each of the three regions from which the clinical academic applicants are drawn: London, the Midlands, and the North East.
3. Discussion of the implications for health services with health care providers and patient support groups (Mental Health Foundation)
4. Engagement with other academics – discussing avenues for future research if the research suggests differential use of CTOs in England
5. Deposition of academic papers in accordance with open access protocol to ensure that published papers are not withheld from a wider audience via journal pay-walls.
6. Development of short plain-language summaries of findings targeted towards non-academic professional audiences (e.g. patient support groups, local authorities, health care professionals, policy makers).
7. Work with Trusts, Innovation Hub, University Partners, and AHSN to ensure dissemination of results and adoption of proposed interventions locally, regionally, and nationally.

Processing:

The HSCIC will create a cohort of Mental Health patient records based on the following criteria:

Patients that have or had a MH spell of care open within the period from April 2011 to March 2015 that includes:
a) any associated Mental Health Act Event Episode/s where the legal status is coded as one of a list of supplied codes indicating detention under specific sections of the Mental Health Act or the Criminal Procedure (Insanity) Act 1964 as amended by the Criminal Procedures (Insanity and Unfitness to Plead) Act 1991, or;
b) any associated Supervised Community Treatment Episode

The HSCIC will then generate a file of pseudonymised Mental Health patient identifiers.

Using this file, the HSCIC will determine the relevant HES ID using a bridging file. They will then extract the relevant HES and ONS Mortality records for those patients identified within the Mental Health cohort. Two bridging files will be created i.e. a HES/ONS bridging file and a Mental Health/HES bridging file. HSCIC will extract the remaining Mental Health data records for the cohort. From the ONS mortality data, the field 'Date of Death' will be replaced with the derived month and year of death only.

The Mental Health data is classed as sensitive. All of the linked data is classed as pseudonymised.

The multiple files will be transferred to the secure environment at ONS VML in Titchfield where ONS staff will use the LSOA to link the HSCIC data to publicly available data (Indices of Multiple Deprivation and aggregate LSOA Census 2011 data) as described above. All data linked to HSCIC data are non-identifiable and publicly available.

Data will be used only for the purposes indicated on the approved ADRN project application and only by ADRN accredited researchers named in this application. Researchers have to undergo ADRN training before accessing any data or intermediate outputs and will only access the data in the secure environment. ONS will ensure that any researchers accessing data have accredited researcher status. All researchers have been guaranteed by someone who can sign up to the breaches and penalties policy by their institution and have received safe data handling training.
Data will not be used for commercial purposes.

The secure environment at ONS VML Titchfield uses state-of-the-art secure information technology and procedures which provide physical, hardware and software security.

Data will be processed (i.e. linked and assembled) in a separate (virtual) secure area than the area the researchers will be accessing the data. All staff handling the data are required to have security clearance at a level appropriate for the data they are going to handle as per the ADRN Secure Environment Policy (ADRN032).

All named individuals in this agreement are employed by the ONS, University of Southampton, the University of Portsmouth, University of Warwick, Ulster University or the Northern Ireland Statistics and Research Agency (NISRA). The researchers named in the application will be granted access to the VML ONS for this specific research project as part of the ADRN services and infrastructure.

The research team will visit ONS VML Titchfield on location to access the linked de-identified dataset in a dedicated secure room. They will be able to use installed software on their allocated PC (thin client) to analyse the data and produce outputs (e.g. tables), but they cannot take anything in or out of the room with them (including mobile, phones, memory sticks or even pen and paper). They will also be watched by the secure environment staff via a CCTV and all their activity when logged in on the PC will be monitored. They will not be able to copy, download or disseminate the data in any way – if they do there will be strict penalties for any breach or misuse of data, following the ADRN breaches and penalties policy (ADRN003).

Due to geographical distance, one instance of remote access to the VML from the secure environment of the Administrative Data Research Centre of Northern Ireland (ADRC-NI) will be needed for one of the researchers (from Ulster University) working on the project, however all data will remain on the ONS VML Titchfield server as per named users accessing on location. ADRC-NI secure environment is located in the Northern Ireland Statistics and Research Agency (NISRA) and the user will undergo training in accordance with the ADRN policy, adhering to the operating procedures of both NISRA and VML safe settings, which will include site specific training and BPSS security. Statistical outputs will only be cleared and released by VML Titchfield.

ONS will act as joint data controller, as theirs will be the location where data will flow to and be stored and ONS will have full control of access of the data. As such, they have provided all the necessary security assurances (current IG toolkit and DPA registration). The listed data users' organisations will not need to separately demonstrate compliance with security assurances as they will be performing data processing activities solely in ONS' controlled environment and will not be storing or transferring data in any way. They are therefore covered by the security assurances of ONS. ONS is ultimately responsible for managing secure access.

Data will be only stored and processed within ONS VML Titchfield.

For all users, outputs will be statistical tables and output of statistical models reviewed by ONS to ensure they are non-disclosive and suitable to be made publicly available. Once cleared for release, ONS then supply the outputs to the named researchers via secure encrypted email.

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

After the end of the project, secure environment staff in ONS Titchfield will store the dataset for as long as required and authorised to do so and will destroy the data, as per the data retention and destruction policy when appropriate, securely and in line with HSCIC requirements.

Once analysis is completed, the research team will produce a two-page plain English summary for ADRN and publish their results.

Finally, note that non-disclosive outputs and results will be discussed among the whole research team before final results are compiled for dissemination. These results will also be used to populate the health care cost analyses. As health cost modelling is based on the non-disclosive results, these analyses can be performed outside the secure facility of the ADRN.