NHS Digital Data Release Register - reformatted

University Of Essex projects

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


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

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(2)(b)(ii)

Purposes: No (Academic)

Sensitive: Non-Sensitive

When:DSA runs 2023-02-23 — 2026-02-22

Access method: One-Off

Data-controller type: UNIVERSITY OF ESSEX

Sublicensing allowed: No

Datasets:

  1. National Child Measurement Programme

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

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); 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 2019-12-01 — 2020-11-30

Access method: One-Off

Data-controller type: UNIVERSITY OF ESSEX

Sublicensing allowed: No

Datasets:

  1. National Child Measurement Programme

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

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Anonymised - ICO Code Compliant (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 2019-04-01 — 2022-03-31 2016.09 — 2016.11.

Access method: One-Off

Data-controller type: UNIVERSITY OF SOUTHAMPTON

Sublicensing allowed: No

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)

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.