NHS Digital Data Release Register - reformatted

Natcen Social Research projects

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

Research on Health and Ageing using English Longitudinal Study of Ageing (ELSA) data linked to NHS data (HES and ECDS) — DARS-NIC-739463-H4P9N

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable (Consent (Reasonable Expectation))

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

Purposes: No (Research)

Sensitive: Non-Sensitive

When:DSA runs 2024-07-19 — 2027-07-18

Access method: Ongoing

Data-controller type: INSTITUTE FOR FISCAL STUDIES, NATCEN SOCIAL RESEARCH, UNIVERSITY COLLEGE LONDON (UCL), UNIVERSITY OF EAST ANGLIA, UNIVERSITY OF MANCHESTER

Sublicensing allowed: No

Datasets:

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

Objectives:

University College London (UCL), the Institute for Fiscal Studies (IFS), the University of Manchester (UoM), the University of East Anglia (UEA), and NatCen Social Research (NatCen) requires access to NHS England data for the purpose of the following research programme:

Research on Health and Ageing using English Longitudinal Study of Ageing (ELSA)

The following is a summary of the aims of the research programme provided by or on behalf of University College London (UCL), the Institute for Fiscal Studies (IFS), the University of Manchester (UoM), the University of East Anglia (UEA), and NatCen Social Research (NatCen):

The English Longitudinal Study of Ageing (ELSA) is a well-established, on-going, multi-disciplinary cohort study involving a collaboration between University College London (UCL), the Institute for Fiscal Studies (IFS), the University of Manchester (UoM), the University of East Anglia (UEA), and NatCen Social Research (NatCen), who constitute the ELSA research group. ELSA aims to provide valuable insights into a range of social, health and economic issues.

The Data will be used for a programme of research on health and ageing in England. This is a long-standing and on-going programme of work which aims to improve understanding of the ageing process, and how the use of health care affects this ageing process and the evolution of health over the lifecycle.

Linking NHS England data with ELSA will allow the study team to combine detailed Hospital episode statistics – Admitted Patient Care, Outpatients, Critical Care and Accident and Emergency Care Data Set information on health outcomes; the use of hospital services; the quality of health care and the identification of trends in health that will impact on future demands for health care with wider characteristics of the elderly population. The proposed linkage of ELSA to administrative health data will provide novel data for research on ageing in England.

Linkage of study members in ELSA to routinely-collected data offers not only additional rich, complementary information about their health which cannot be gathered using these methods (e.g., valid data on diagnosis and prognosis of common chronic diseases such as cancer and depression) and a streamlined approached to access data from national sources.

UCL, NatCen, UoM and UEA use the linked data for purposes which focus on epidemiological and social research whilst IFS use the linked data for purposes which focus on the economics regarding health and social care.

Linking NHS England data with ELSA data will allow the programme of research on ageing and health in England which aims to improve understanding of the ageing process, including predictors of various age-related disease diagnoses (e.g., heart disease, stroke, specific cancers, depression, dementia), and how health and the use of health care affect that ageing process.

Specifically, the data will improve understanding of:
1) Variation in hospital use across individuals with different individual and family characteristics, particularly at the end of life, providing a new understanding of the extent to which spending is efficiently allocated across different types of people.

2) The relationship between social care provision and hospital use, in particular the extent to which lack of social care availability may increase use of hospital care either through more entry into hospital or delayed exit.

3) Social inequalities in health among older people in England, and the relationship between these inequalities and other social characteristics, quality of care, and disability. This work is important for future planning of health care provision.

4) The incidence of dementia in the ELSA population

Secondary objectives:
• to understand what factors influence survival, and whether attrition from the repeated measures in the study has happened because of drop-out or because they died. (Mortality data will be supplied under DARS-NIC-759062-F2L6B)
• compare the risk of mortality following the onset of different health conditions across demographic and socioeconomic groups within the older population in England, and between similar groups in England and the USA.

Other projects that will take place as part of this programme of work are:
(1) To examine how the pattern of hospital care use changes in the final year(s) of life, and to examine whether it is proximity to death, as opposed to age, that determines healthcare utilisation (controlling for other characteristics captured in the ELSA data).

(2) To compare the risk of survival following the onset of different health conditions across demographic and socioeconomic groups within the older population in England, and between similar groups in England. UCL will use the information on cause of death to find out who has had an onset of a condition prior to their death, so that UCL can work out the probability of survival among those who experience (e.g.) a heart attack.

Below are the projects that will take place as part of this programme of work:

(1) To understand the extent to which variation exists in the use of NHS hospital services among the older population that is not explained by differences in need? IFS will examine variation in the use and cost of hospital care across the socio-economic gradient, differences in cognitive abilities, and across geographic areas.

(2) To examine how the pattern of hospital care use changes in the final year(s) of life, and to examine whether it is proximity to death, as opposed to age, that determines healthcare utilisation (controlling for other characteristics captured in the ELSA data)

(3) To understand the extent to which individuals can substitute between different types of social care and hospital care? For example, IFS will examine whether reduced availability of publicly funded social care (as a result of cuts to local authority spending) has resulted in an increased use of NHS hospitals.

(4) To compare the risk of survival following the onset of different health conditions across demographic and socioeconomic groups within the older population in England, and between similar groups in England and the US (US data will be obtained separately). IFS will use the information on cause of death from mortality data to find out who has had an onset of a condition prior to their death, so that IFS can work out the probability of survival among those who experience (e.g.) a heart attack. IFS has missing survey information on those who die before they are able to report a new onset, and the cause of death information allows them to fill in the gap.

NatCen complete the field work to collect ELSA data, including participants’ personal information for linkage with NHS England data. NatCen will submit the cohort to NHSE and will receive the linked data. Natcen then pseudonymise the linked ELSA data prior to onward sharing with UCL and IFS. UCL, NatCen, UoM, and UEA will use the linked data for purposes which focus on epidemiological and social research whilst IFS use the linked data for purposes which focus on the economics regarding health and social care.

The following NHS England Data will be accessed:
• Hospital Episode Statistics
o Admitted Patient Care – necessary to address how the use of admitted patient care services affects the ageing process and the evolution of health over the lifecycle. It is necessary to consider the use of all types of hospital services to fully address this question.
o Accident & Emergency – necessary to address how the use of Accident and Emergency services affects the ageing process and the evolution of health over the lifecycle. It is necessary to consider the use of all types of hospital services to fully address this question.
o Critical Care – necessary to address how the use of Critical Care services affects the ageing process and the evolution of health over the lifecycle. It is necessary to consider the use of all types of hospital services to fully address this question.
o Outpatients – necessary to address how the use of Outpatients services affects the ageing process and the evolution of health over the lifecycle. It is necessary to consider the use of all types of hospital services to fully address this question.
• Emergency Care Data Set (ECDS) – necessary because this dataset replaced HES Accident & Emergency data
The level of the Data will be Identifiable, necessary because although the applicant will pseudonymise the data before analysis there could be a justifiable reason for reidentifying a cohort member (for example, to accommodate opt outs).

The identifying details will be stored in a separate database to the linked dataset used for analysis.

The Data will be minimised as follows:
• Limited to a study cohort of approx. 17,498 participants who consented to participate.
• Limited to data between 1997/98 and latest available data.

NatCen are permitted to send NHS England ‘NHS Number’ for participant list validation. This includes NHS Numbers already held by NatCen in the ELSA study database

University College London (UCL), the Institute for Fiscal Studies (IFS), the University of Manchester (UoM), the University of East Anglia (UEA), and NatCen Social Research (NatCen) are the joint Controllers as the organisations responsible for ensuring that the Data will only be processed for the purposes described above.

UCL, UoM and UEAs 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.

NatCen and IFSs lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party. Natcen and IFS, as part of their legitimate interests, will use the data for a programme of research on health and ageing in England which aims to improve understanding of the ageing process, and how the use of health care affects this ageing process and the evolution of health over the lifecycle.

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.

This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research, which protects and promotes the interests of patients, service users and the public, and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care.

The funding comes from multiple sources. Current funders include :
• National Institute on Aging via National Institutes of Health (NIH)
• A consortium of UK government departments: Department for Health and Social Care; Department for Transport; Department for Work and Pensions, which is coordinated by the National Institute for Health Research

Funding to continue the work described will be sought on an ongoing basis.

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

Equinix LD3 are a data centre provider for NatCen. They are a facility that provide IT housing, security, data, power, etc. They are used by NatCen as a backup and disaster recovery location. NatCen own the servers housed at Equinix, and Equinix have no access to any NatCen data, including the linked NHSE data.

Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure backup of data stored in UCL’s Data Safe Haven.

Data may be accessed by:
• Substantive employees of UCL, IFS, Natcen, UAE or UoM.
• Individuals with honorary contracts with UCL, IFS, Natcen, UAE or UoM.
• Undergraduate, Masters or PhD students enrolled with UCL, IFS, Natcen, UAE or UoM. Any student working with the Data held under this Data Sharing Agreement (DSA) must have completed relevant data protection and confidentiality training and are subject to UCL, IFS, Natcen, UAE and UoMs policies on data protection and confidentiality. Any students accessing the Data will do so under the supervision of a substantive employee of UCL, IFS, Natcen, UAE or UoM. UCL, IFS, Natcen, UAE and UoM would be responsible and liable for any work carried out by students. These students would only work on the Data for the purposes described in this DSA.

Individuals holding an honorary contract under the supervision of a substantive employee of UCL, UoM, UEA, IFS or NatCen will process data for the purposes described in this DSA only. The controllers must maintain records in a single location that cover the following details of each individual given access under an honorary contract:
- Their substantive employer;
- Their role in respect of the purpose for the processing specified in the DSA;
- The start date and end date of the duration in which the Data will be accessed by the individual under an honorary contract;
- The necessity for the Data to be accessed by the person(s) holding an honorary contract, instead of a substantive employee of an organisation named as controller or a processor in this DSA;
- Confirmation that an appropriate contract is in place which follows the relevant guidance and is countersigned by the substantive employer of the honorary contract holder.

The ELSA collaboration regularly engage with ELSA participants and the general public through several means including printed participant newsletters, blog posts on the ELSA website, YouTube, and X (formerly Twitter). ELSA recently celebrated its 20 year anniversary and to mark this a report was produced which highlighted key findings from a selection of the almost 1300 published articles that have used ELSA data originating from the contributions of 19,000 study participants. The report was written in accessible language aimed at a lay audience. The report is available on the ELSA website to download: https://www.elsa-project.ac.uk/celebrating-elsa and printed copies have been sent to fieldworkers as part of their Wave 11 briefing packs for participants. A film was also produced which included ELSA participants: https://youtu.be/Ov4TXHdVpAY. As part of this process, the participants made several suggestions on how to improve the study such as including more current issues in the questionnaire which the ELSA Management Group will take forward for Wave 12. Following this engagement with participants, a formal PPIE group will be formed for ELSA.

Yielded Benefits:

ELSA data are used extensively by various UK government departments. For example, the Department for Work and Pensions (DWP) uses ELSA data to examine factors which may affect life expectancy. Their business analysts use ELSA for their digital evidence pack, where they look at digital inclusion and how this varies by demographic. The DWP Housing and Benefit team use ELSA data to look into decisions around downsizing, and their Pensions and Later Life analysts use the data to work on the state pension review. ELSA has also been a crucial piece of information for calibrating simulation models in the impact assessment looking at how the Social Care Charging Reform will evolve. ELSA is also an important input to research on allocation formulae that will underpin the reforms. There is a need to update these formulae so they are as current as possible, and ELSA is integral to this process. ELSA has also been used in the following ways:: 1) The linked data were used in ELSA analysis of trends in dementia between 2002 and 2019 which projected incidence into the future and estimated that around 1.7 million people in England and Wales might have dementia by 2040. This is rather higher than previously estimated. The analysis suggests that dementia incidence might not be declining any longer in England and Wales as it was in the first decade of the century. The researchers warn that if these trends continue, the burden on health and social care will be large, given the growing number of older people. Continued monitoring of the incidence trend using more recent linked data will be important in shaping social care policy. This analysis was featured by several media outlets: https://news.sky.com/story/1-7m-people-could-be-living-with-dementia-in-england-and-wales-by-2040-says-new-report-12993182 https://inews.co.uk/news/science/obesity-dementia-patients-uk-double-2040-2713009 https://www.thetimes.co.uk/article/dementia-rates-rising-faster-than-thought-due-to-unhealthy-lifestyles-7nq7w5qgm https://www.telegraph.co.uk/news/2023/10/26/17-million-people-in-england-and-wales-dementia-2040/ 2) ELSA data were used in the Chief Medical Officer’s annual report 2023: health in an ageing society https://www.gov.uk/government/publications/chief-medical-officers-annual-report-2023-health-in-an-ageing-society. ELSA analyses were referenced to demonstrate that the number of people living with dementia is expected to rise to 1.7 million by 2040, rather higher than previous estimates. The report also included ELSA work which estimated the district-level prevalence of frailty, showing that higher rates of frailty in people aged over 50 years in areas of higher deprivation. 3) Analyses using the linked data were included is a report by the Centre for Ageing Better, ‘Boom and bust?’ published in November 2021, which found that people in their 50s and 60s today face worse circumstances than the cohort before them, with 1 in 5 people in this age group likely to face multiple, long-term problems: https://www.ageing-better.org.uk/sites/default/files/2021-11/boom-and-bust-report-thelast-baby-boomers.pdf. The resulting report showed that across many key aspects of life such as health, work, housing, finances, family make-up and social lives, people in their 50s and 60s today are facing worse circumstances than people who were at the same age in 2002. The report also highlighted that people from minority ethnic backgrounds are at particular risk of experiencing an old age marred by multiple, chronic problems such as poor health, poor finances and poor social connections. The evidence presented in this report is of key importance for national and local policy makers and practitioners who are aiming to improve experiences and outcomes for people as they approach later life and in later life. This report also set out a series of recommendations for government. A documentary was produced to accompany this report: https://www.youtube.com/watch?v=SYYD19b1vPE. 4) ELSA data were used in a recent NIHR alert on obesity and dementia: https://evidence.nihr.ac.uk/alert/overweight-linked-increased-risk-dementia/. The alert focussed on an ELSA analysis that showed that people who carry excess weight in midlife have an increased risk of developing dementia. The alert explains that this poses a serious public health problem as more than a third of adults are now overweight and could explain why the global rates of dementia almost tripled between 1975 and 2016. This ELSA study is important as it provides evidence of the potential benefits of targeted health interventions by policy makers to reduce levels of obesity. 5) An NIHR Alert based on analyses using the linked data was published as part of a Collection on loneliness, published in September 2021: https://evidence.nihr.ac.uk/collection/how-can-we-reduce-the-toll-of-loneliness-in-older-adults/. This work drew on published analyses that used the linked data to highlight the impact of loneliness on older people’s health and wellbeing and the need for interventions that reduce the toll of loneliness among older people. A podcast episode was also produced as part of this Collection which the ELSA PI, Andrew Steptoe, took part in: https://open.spotify.com/episode/4WJka6Yt9gl4Xl7CW6qXwD 6) Several UCL-led analyses using the linked data were also cited in the WHO scoping review: What is the evidence on the role of the arts in improving health and well-being? (2019) https://www.euro.who.int/en/publications/abstracts/what-is-the-evidence-on-the-role-of-the-arts-in-improving-health-and-well-being-a-scoping-review-2019. This review led to the establishment of the WHO Collaborating Centre for Arts & Health at UCL in 2021. ELSA linked data is one of the key sources contributing to the evidence base for and monitoring of social prescribing in England. A longitudinal analysis using linked data in ELSA was published in the British Medical Journal in 2019, showing that greater cultural activity was related to reduced mortality over a 14 year follow-up period, independently of socioeconomic factors and initial health status. This article was widely cited, being picked up by more than 70 news outlets, and being the subject of a BMJ Video blog (https://www.bmj.com/content/367/bmj.l6377). 7) The ELSA team produced an analysis of the linked data to examine how the pattern of end-of-life hospital inpatient spending varies across different groups in England. The analysis showed that the pattern of end-of-life spending varies across household composition and socioeconomic status. Quarterly spending increases more sharply for those in couples at the end of life: a 10% reduction in time to death is associated with a 10% rise in individual spending among couples, but only 8% for singles. Spending is also lower in the last 18 months of life for those with no formal qualifications relative to their more educated peers due to lower use of elective care. Differences across groups were not explained by differences in observed morbidity or cause of death, but could be explained by differential access to, or preferences for, care. Given recent trends towards increased cohabitation at older ages and higher educational attainment, these results suggest that policymakers should consider a broader range of sociodemographic attributes when forecasting future health spending and in evaluating inequity in healthcare use: https://ifs.org.uk/publications/variation-end-life-hospital-spending-england-evidence-linked-survey-and-administrative 8) A recent analysis of ELSA data by the Institute for Fiscal Studies showed that early retirement is increasingly concentrated amongst the wealthy, while poorer people are more likely to stop working due to ill health: https://ifs.org.uk/publications/understanding-retirement-uk The report showed that for people in their late 50s and early 60s, employment rates are the highest for those with around average levels of wealth, with poorer people more likely to be economically inactive (but not retired) and richer people more likely to be retired. Above state pension age, it is those with higher levels of wealth that are more likely to stay on in paid work, though that is particularly likely to be either on low hours or in self-employment. These people are also more likely to draw a number of different incomes – as well as employment income, most will also draw their state pension, and a large minority will also be in receipt of private pension income. 9) Results from projects relating to understanding how population health care needs are likely to change were presented to analysts at DHSC and NHS England in October 2018, and to the DHSC Social Care Analysis team in March 2019, with updates on the work (or newly required extensions) requested by DHSC each time. These presentations have been requested by DHSC as part of their evidence gathering on how demand for NHS and various forms of social care is changing, and how use for certain types of care are likely to impact other parts of the health and social care system (e.g. if the generosity of the publicly provided social care system is scaled back, how is this likely to impact informal carers and NHS hospitals?). In particular, the March 2019 presentation was requested by the Social Care Analysis team as part of their preparations for the 2019 Spending Review. The research will therefore potentially influence the future provision of health and social care in England through increasing the evidence base used by DHSC and NHS England in their decision making-processes.

Expected Benefits:

ELSA will have value in contributing to evidence-based decision making for policy makers, planning services, predicting future needs, estimating the costs of care, and understanding the impact of various ageing states on individuals and their families.

New funding from the National Institute on Aging has charged the study explicitly to model the incidence of dementia in the ELSA population, and this will be greatly facilitated by the availability of hospital care statistics. At present, ELSAs estimates of dementia incidence and prevalence are based on cognitive tests and ratings from relatives and carers. Having information about the use of hospital services by ELSA participants with dementia and cognitive impairment will strengthen the evidence base and provide a platform for more detailed analyses of the determinants and consequences of dementia. ELSA will also be able to fulfil the mandate from the National Institute on Aging to provide analyses that can be used to compare dementia rates in the UK and USA.

ELSA would model the use of NHS-funded inpatient services (provided by HES) by individuals with similar underlying health needs, but who differ in other, non-need based characteristics (provided by ELSA). The relationship between receipt of social care and hospital admissions will then be modelled to examine whether cuts in social care are likely to increase probability of hospital admission.

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 such as obesity and diabetes.
• 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.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients. Clients will need to take action based on the information provided to them in order to realise the potential improvement opportunities. For example, a recent analysis of ELSA data included in an NIHR report showed that people who carry excess weight in midlife have an increased risk of developing dementia. This was underlined in the Chief Medical Officer’s annual report 2023 which referenced ELSA data to show how the number of people living with dementia is expected to rise to 1.7 million by 2040, rather higher than previous estimates. These ELSA analyses suggests that active intervention for reducing obesity should be targeted at the groups most at risk of dementia, including women carrying excess weight around the waist.

Outputs:

The expected outputs of the processing will be:
• Submissions to peer reviewed journals: Up to 10 analyses are expected to be submitted before the expiration of the DSA
• Presentations to UK government departments of DHSC, DfT and DWP
• Presentations at appropriate conferences
• Blog posts on the ELSA website
• Press/media engagement as appropriate
• Public promotion of the research via the ELSA website
• Participant newsletters

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.

Next target dates for production and dissemination of the outputs are expected to be Winter 2024.

Processing:

NatCen will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, Postcode, Gender and a unique person ID) for the cohort to be linked with NHS England data.

NHS England will provide the relevant records from the HES and ECDS datasets to NatCen. The Data will contain no direct identifying data items but will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient.

NatCen will securely transfer the Data to UCL, IFS, UoM, and UEA.

The Data will be stored on servers at NatCen, UCL, IFS, UoM and UEA.

NatCen uses offsite back-up services provided by Equinix LD3 data centre.

NatCen stores Data on the Cloud provided by Equinix LD3 data centre.

Amazon Web Services provides cloud hosting services to UCL and will store the data as contracted by UCL.

UCL uses offsite data centre services provided by VIRTUS data centre. VIRTUS does not have access to the data.

The Data will be accessed onsite at the premises of UoM and UEA In addition, the Data will be accessed by authorised personnel at UCL, NatCen and IFS via remote access.

The Controllers 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 the UK. The data will not leave the UK at any time.

Access is restricted to employees or agents of UCL, NatCen, IFS, UoM and UEA who have authorisation from the Principal Investigator at UCL.

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

The Data will be linked at person record level with the ELSA data which is a unique and rich longitudinal study on the dynamics of health, social, wellbeing and economic circumstances* in the English population aged 50 and older which has been running since 2002.

*ELSA may also link participants' details (with their consent) to economic information provided by organisations such as Department for work and Pension and HM Revenue and Customs. These data may include national insurance contributions, tax records and benefits.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset.

Researchers from the UCL, NatCen, IFS, UoM and UEA will analyse the Data for the purposes described above.

Research on Health and Ageing using English Longitudinal Study of Ageing (ELSA) data linked to NHS data (Cancer and Mortality) — DARS-NIC-759062-F2L6B

Type of data: information not disclosed for TRE projects

Opt outs honoured: Identifiable (Consent (Reasonable Expectation))

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

Purposes: No (Research)

Sensitive: Non-Sensitive, and Sensitive

When:DSA runs 2024-07-19 — 2027-07-18

Access method: Ongoing

Data-controller type: INSTITUTE FOR FISCAL STUDIES, NATCEN SOCIAL RESEARCH, UNIVERSITY COLLEGE LONDON (UCL), UNIVERSITY OF EAST ANGLIA, UNIVERSITY OF MANCHESTER

Sublicensing allowed: No

Datasets:

  1. Cancer Registration Data
  2. Civil Registrations of Death

Objectives:

University College London (UCL), the Institute for Fiscal Studies (IFS), the University of Manchester (UoM), the University of East Anglia (UEA), and NatCen Social Research (NatCen) requires access to NHS England data for the purpose of the following research programme:

Research on Health and Ageing using English Longitudinal Study of Ageing (ELSA)

The following is a summary of the aims of the research programme provided by or on behalf of University College London (UCL), the Institute for Fiscal Studies (IFS), the University of Manchester (UoM), the University of East Anglia (UEA), and NatCen Social Research (NatCen):

The English Longitudinal Study of Ageing (ELSA) is a well-established, on-going, multi-disciplinary cohort study involving a collaboration between University College London (UCL), the Institute for Fiscal Studies (IFS), the University of Manchester (UoM), the University of East Anglia (UEA), and NatCen Social Research (NatCen), who constitute the ELSA research group. ELSA aims to provide valuable insights into a range of social, health and economic issues.

The Data will be used for a programme of research on health and ageing in England. This is a long-standing and on-going programme of work which aims to improve understanding of the ageing process, and how the use of health care affects this ageing process and the evolution of health over the lifecycle.

Linking NHS England data with ELSA will allow the study team to combine detailed information on health outcomes; the use of hospital services; the quality of health care and the identification of trends in health that will impact on future demands for health care with wider characteristics of the elderly population. The proposed linkage of ELSA to administrative health data will provide novel data for research on ageing in England.

Linkage of study members in ELSA to routinely-collected data offers not only additional rich, complementary information about their health which cannot be gathered using these methods (e.g., valid data on diagnosis and prognosis of common chronic diseases such as cancer and depression) and a streamlined approached to access data from national sources.

UCL, NatCen, UoM and UEA use the linked data for purposes which focus on epidemiological and social research whilst IFS use the linked data for purposes which focus on the economics regarding health and social care.

Linking NHS England data with ELSA will be used to continue the programme of research on ageing and health in England which aims to improve understanding of the ageing process, including predictors of various age-related disease diagnoses (e.g., heart disease, stroke, specific cancers, depression, dementia), and how health and the use of health care affect that ageing process.

Specifically, the data will improve understanding of:
1) Variation in hospital use across individuals with different individual and family characteristics, particularly at the end of life, providing a new understanding of the extent to which spending is efficiently allocated across different types of people.

2) The relationship between social care provision and hospital use, in particular the extent to which lack of social care availability may increase use of hospital care either through more entry into hospital or delayed exit.

3) Social inequalities in health among older people in England, and the relationship between these inequalities and other social characteristics, quality of care, and disability. This work is important for future planning of health care provision.

4) The incidence of dementia in the ELSA population

Secondary objectives:
• to understand what factors influence survival, and whether attrition from the repeated measures in the study has happened because of drop-out or because they died.
• compare the risk of mortality following the onset of different health conditions across demographic and socioeconomic groups within the older population in England, and between similar groups in England and the USA.

Other projects that will take place as part of this programme of work are:
(1) To examine how the pattern of hospital care use changes in the final year(s) of life, and to examine whether it is proximity to death, as opposed to age, that determines healthcare utilisation (controlling for other characteristics captured in the ELSA data).

(2) To compare the risk of survival following the onset of different health conditions across demographic and socioeconomic groups within the older population in England, and between similar groups in England. UCL will use the information on cause of death to find out who has had an onset of a condition prior to their death, so that UCL can work out the probability of survival among those who experience (e.g.) a heart attack.

Below are the projects that will take place as part of this programme of work:

(1) To understand the extent to which variation exists in the use of NHS hospital services among the older population that is not explained by differences in need? IFS will examine variation in the use and cost of hospital care across the socio-economic gradient, differences in cognitive abilities, and across geographic areas.

(2) To examine how the pattern of hospital care use changes in the final year(s) of life, and to examine whether it is proximity to death, as opposed to age, that determines healthcare utilisation (controlling for other characteristics captured in the ELSA data)

(3) To understand the extent to which individuals can substitute between different types of social care and hospital care? For example, IFS will examine whether reduced availability of publicly funded social care (as a result of cuts to local authority spending) has resulted in an increased use of NHS hospitals.

(4) To compare the risk of survival following the onset of different health conditions across demographic and socioeconomic groups within the older population in England, and between similar groups in England and the US (US data will be obtained separately). IFS will use the information on cause of death from mortality data to find out who has had an onset of a condition prior to their death, so that IFS can work out the probability of survival among those who experience (e.g.) a heart attack. IFS has missing survey information on those who die before they are able to report a new onset, and the cause of death information allows them to fill in the gap.

NatCen complete the field work to collect ELSA data, including participants’ personal information for linkage with NHS England data. NatCen will submit the cohort to NHSE and will receive the linked data. Natcen then pseudonymise the linked ELSA data prior to onward sharing with UCL and IFS. UCL, NatCen, UoM, and UEA will use the linked data for purposes which focus on epidemiological and social research whilst IFS use the linked data for purposes which focus on the economics regarding health and social care.

The following NHS England Data will be accessed:
• Civil Registration Mortality – necessary to compare risk of mortality following the onset of different health conditions and other factors across demographic and socioeconomic groups within the older population in England. Mortality data is also used for sample cleaning processes and derivation.
• Cancer Registration – necessary to address the following issues: The relationship between body weight, changes in body weight, and cancer incidence among older people. The impact of cancer diagnosis on health behaviours and quality of life. The association between bowel cancer screening (measured in ELSA since 2012) and cancer incidence. The relationship between psychosocial factors (depression, social isolation, cognitive function) and cancer incidence. (UCL)

The level of the Data will be Identifiable, necessary because although the applicant will pseudonymise the data before analysis there could be a justifiable reason for reidentifying a cohort member (for example, to accommodate opt outs).

The identifying details will be stored in a separate database to the linked dataset used for analysis.

The Data will be minimised as follows:
• Limited to a study cohort of approx. 21,370 participants who consented to participate.
• Limited to data between 1997/98 and latest available data.

University College London (UCL), the Institute for Fiscal Studies (IFS), the University of Manchester (UoM), the University of East Anglia (UEA), and NatCen Social Research (NatCen) are the joint Controllers as the organisations responsible for ensuring that the Data will only be processed for the purposes described above.

UCL, UoM and UEAs 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.

NatCen and IFSs lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party. Natcen and IFS, as part of their legitimate interests, will use the data for a programme of research on health and ageing in England which aims to improve understanding of the ageing process, and how the use of health care affects this ageing process and the evolution of health over the lifecycle.

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.

This processing is in the public interest because it adheres to the UK Policy Framework for Health and Social Care Research, which protects and promotes the interests of patients, service users and the public, and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care.

The funding comes from multiple sources. Current funders include :
• National Institute on Aging via National Institutes of Health (NIH)
• A consortium of UK government departments: Department for Health and Social Care; Department for Transport; Department for Work and Pensions, which is coordinated by the National Institute for Health Research

Funding to continue the work described will be sought on an ongoing basis.

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

Equinix LD3 are a data centre provider for NatCen. They are a facility that provide IT housing, security, data, power, etc. They are used by NatCen as a backup and disaster recovery location. NatCen own the servers housed at Equinix, and Equinix have no access to any NatCen data, including the linked NHSE data.

Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure backup of data stored in UCL’s Data Safe Haven.

Data may be accessed by:
• Substantive employees of UCL, IFS, Natcen, UAE or UoM.
• Individuals with honorary contracts with UCL, IFS, Natcen, UAE or UoM.
• Undergraduate, Masters or PhD students enrolled with UCL, IFS, Natcen, UAE or UoM. Any student working with the Data held under this Data Sharing Agreement (DSA) must have completed relevant data protection and confidentiality training and are subject to UCL, IFS, Natcen, UAE and UoMs policies on data protection and confidentiality. Any students accessing the Data will do so under the supervision of a substantive employee of UCL, IFS, Natcen, UAE or UoM. UCL, IFS, Natcen, UAE and UoM would be responsible and liable for any work carried out by students. These students would only work on the Data for the purposes described in this DSA.

Individuals holding an honorary contract under the supervision of a substantive employee of UCL, UoM, UEA, IFS or NatCen will process data for the purposes described in this DSA only. The controllers must maintain records in a single location that cover the following details of each individual given access under an honorary contract:
- Their substantive employer;
- Their role in respect of the purpose for the processing specified in the DSA;
- The start date and end date of the duration in which the Data will be accessed by the individual under an honorary contract;
- The necessity for the Data to be accessed by the person(s) holding an honorary contract, instead of a substantive employee of an organisation named as controller or a processor in this DSA;
- Confirmation that an appropriate contract is in place which follows the relevant guidance and is countersigned by the substantive employer of the honorary contract holder.

The ELSA collaboration regularly engage with ELSA participants and the general public through several means including printed participant newsletters, blog posts on the ELSA website, YouTube, and X (formerly Twitter). ELSA recently celebrated its 20 year anniversary and to mark this a report was produced which highlighted key findings from a selection of the almost 1300 published articles that have used ELSA data originating from the contributions of 19,000 study participants. The report was written in accessible language aimed at a lay audience. The report is available on the ELSA website to download: https://www.elsa-project.ac.uk/celebrating-elsa and printed copies have been sent to fieldworkers as part of their Wave 11 briefing packs for participants. A film was also produced which included ELSA participants: https://youtu.be/Ov4TXHdVpAY. As part of this process, the participants made several suggestions on how to improve the study such as including more current issues in the questionnaire which the ELSA Management Group will take forward for Wave 12. Following this engagement with participants, a formal PPIE group will be formed for ELSA.

Yielded Benefits:

ELSA data are used extensively by various UK government departments. For example, the Department for Work and Pensions (DWP) uses ELSA data to examine factors which may affect life expectancy. Their business analysts use ELSA for their digital evidence pack, where they look at digital inclusion and how this varies by demographic. The DWP Housing and Benefit team use ELSA data to look into decisions around downsizing, and their Pensions and Later Life analysts use the data to work on the state pension review. ELSA has also been a crucial piece of information for calibrating simulation models in the impact assessment looking at how the Social Care Charging Reform will evolve. ELSA is also an important input to research on allocation formulae that will underpin the reforms. There is a need to update these formulae so they are as current as possible, and ELSA is integral to this process. ELSA has also been used in the following ways:: 1) The linked data were used in a ELSA analysis of trends in dementia between 2002 and 2019 which projected incidence into the future and estimated that around 1.7 million people in England and Wales might have dementia by 2040. This is rather higher than previously estimated. The analysis suggests that dementia incidence might not be declining any longer in England and Wales as it was in the first decade of the century. The researchers warn that if these trends continue, the burden on health and social care will be large, given the growing number of older people. Continued monitoring of the incidence trend using more recent linked data will be important in shaping social care policy. This analysis was featured by several media outlets: https://news.sky.com/story/1-7m-people-could-be-living-with-dementia-in-england-and-wales-by-2040-says-new-report-12993182 https://inews.co.uk/news/science/obesity-dementia-patients-uk-double-2040-2713009 https://www.thetimes.co.uk/article/dementia-rates-rising-faster-than-thought-due-to-unhealthy-lifestyles-7nq7w5qgm https://www.telegraph.co.uk/news/2023/10/26/17-million-people-in-england-and-wales-dementia-2040/ 2) ELSA data were used in the Chief Medical Officer’s annual report 2023: health in an ageing society https://www.gov.uk/government/publications/chief-medical-officers-annual-report-2023-health-in-an-ageing-society. ELSA analyses were referenced to demonstrate that the number of people living with dementia is expected to rise to 1.7 million by 2040, rather higher than previous estimates. The report also included ELSA work which estimated the district-level prevalence of frailty, showing that higher rates of frailty in people aged over 50 years in areas of higher deprivation. 3) Analyses using the linked data were included is a report by the Centre for Ageing Better, ‘Boom and bust?’ published in November 2021, which found that people in their 50s and 60s today face worse circumstances than the cohort before them, with 1 in 5 people in this age group likely to face multiple, long-term problems: https://www.ageing-better.org.uk/sites/default/files/2021-11/boom-and-bust-report-thelast-baby-boomers.pdf. The resulting report showed that across many key aspects of life such as health, work, housing, finances, family make-up and social lives, people in their 50s and 60s today are facing worse circumstances than people who were at the same age in 2002. The report also highlighted that people from minority ethnic backgrounds are at particular risk of experiencing an old age marred by multiple, chronic problems such as poor health, poor finances and poor social connections. The evidence presented in this report is of key importance for national and local policy makers and practitioners who are aiming to improve experiences and outcomes for people as they approach later life and in later life. This report also set out a series of recommendations for government. A documentary was produced to accompany this report: https://www.youtube.com/watch?v=SYYD19b1vPE. 4) ELSA data were used in a recent NIHR alert on obesity and dementia: https://evidence.nihr.ac.uk/alert/overweight-linked-increased-risk-dementia/. The alert focussed on an ELSA analysis that showed that people who carry excess weight in midlife have an increased risk of developing dementia. The alert explains that this poses a serious public health problem as more than a third of adults are now overweight and could explain why the global rates of dementia almost tripled between 1975 and 2016. This ELSA study is important as it provides evidence of the potential benefits of targeted health interventions by policy makers to reduce levels of obesity. 5) An NIHR Alert based on analyses using the linked data was published as part of a Collection on loneliness, published in September 2021: https://evidence.nihr.ac.uk/collection/how-can-we-reduce-the-toll-of-loneliness-in-older-adults/. This work drew on published analyses that used the linked data to highlight the impact of loneliness on older people’s health and wellbeing and the need for interventions that reduce the toll of loneliness among older people. A podcast episode was also produced as part of this Collection which the ELSA PI, Andrew Steptoe, took part in: https://open.spotify.com/episode/4WJka6Yt9gl4Xl7CW6qXwD 6) Several UCL-led analyses using the linked data were also cited in the WHO scoping review: What is the evidence on the role of the arts in improving health and well-being? (2019) https://www.euro.who.int/en/publications/abstracts/what-is-the-evidence-on-the-role-of-the-arts-in-improving-health-and-well-being-a-scoping-review-2019. This review led to the establishment of the WHO Collaborating Centre for Arts & Health at UCL in 2021. ELSA linked data is one of the key sources contributing to the evidence base for and monitoring of social prescribing in England. A longitudinal analysis using linked data in ELSA was published in the British Medical Journal in 2019, showing that greater cultural activity was related to reduced mortality over a 14 year follow-up period, independently of socioeconomic factors and initial health status. This article was widely cited, being picked up by more than 70 news outlets, and being the subject of a BMJ Video blog (https://www.bmj.com/content/367/bmj.l6377). 7) The ELSA team produced an analysis of the linked data to examine how the pattern of end-of-life hospital inpatient spending varies across different groups in England. The analysis showed that the pattern of end-of-life spending varies across household composition and socioeconomic status. Quarterly spending increases more sharply for those in couples at the end of life: a 10% reduction in time to death is associated with a 10% rise in individual spending among couples, but only 8% for singles. Spending is also lower in the last 18 months of life for those with no formal qualifications relative to their more educated peers due to lower use of elective care. Differences across groups were not explained by differences in observed morbidity or cause of death, but could be explained by differential access to, or preferences for, care. Given recent trends towards increased cohabitation at older ages and higher educational attainment, these results suggest that policymakers should consider a broader range of sociodemographic attributes when forecasting future health spending and in evaluating inequity in healthcare use: https://ifs.org.uk/publications/variation-end-life-hospital-spending-england-evidence-linked-survey-and-administrative 8) A recent analysis of ELSA data by the Institute for Fiscal Studies showed that early retirement is increasingly concentrated amongst the wealthy, while poorer people are more likely to stop working due to ill health: https://ifs.org.uk/publications/understanding-retirement-uk The report showed that for people in their late 50s and early 60s, employment rates are the highest for those with around average levels of wealth, with poorer people more likely to be economically inactive (but not retired) and richer people more likely to be retired. Above state pension age, it is those with higher levels of wealth that are more likely to stay on in paid work, though that is particularly likely to be either on low hours or in self-employment. These people are also more likely to draw a number of different incomes – as well as employment income, most will also draw their state pension, and a large minority will also be in receipt of private pension income. 9) Results from projects relating to understanding how population health care needs are likely to change were presented to analysts at DHSC and NHS England in October 2018, and to the DHSC Social Care Analysis team in March 2019, with updates on the work (or newly required extensions) requested by DHSC each time. These presentations have been requested by DHSC as part of their evidence gathering on how demand for NHS and various forms of social care is changing, and how use for certain types of care are likely to impact other parts of the health and social care system (e.g. if the generosity of the publicly provided social care system is scaled back, how is this likely to impact informal carers and NHS hospitals?). In particular, the March 2019 presentation was requested by the Social Care Analysis team as part of their preparations for the 2019 Spending Review. The research will therefore potentially influence the future provision of health and social care in England through increasing the evidence base used by DHSC and NHS England in their decision making-processes.

Expected Benefits:

ELSA will have value in contributing to evidence-based decision making for policy makers, planning services, predicting future needs, estimating the costs of care, and understanding the impact of various ageing states on individuals and their families.

New funding from the National Institute on Aging has charged the study explicitly to model the incidence of dementia in the ELSA population, and this will be greatly facilitated by the availability of hospital care statistics. At present, ELSAs estimates of dementia incidence and prevalence are based on cognitive tests and ratings from relatives and carers. Having information about the use of hospital services by ELSA participants with dementia and cognitive impairment will strengthen the evidence base and provide a platform for more detailed analyses of the determinants and consequences of dementia. ELSA will also be able to fulfil the mandate from the National Institute on Aging to provide analyses that can be used to compare dementia rates in the UK and USA.

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 such as obesity and diabetes.
• 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.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients. Clients will need to take action based on the information provided to them in order to realise the potential improvement opportunities. For example, a recent analysis of ELSA data included in an NIHR report showed that people who carry excess weight in midlife have an increased risk of developing dementia. This was underlined in the Chief Medical Officer’s annual report 2023 which referenced ELSA data to show how the number of people living with dementia is expected to rise to 1.7 million by 2040, rather higher than previous estimates. These ELSA analyses suggests that active intervention for reducing obesity should be targeted at the groups most at risk of dementia, including women carrying excess weight around the waist.

Outputs:

The expected outputs of the processing will be:
• Submissions to peer reviewed journals: Up to 10 analyses are expected to be submitted before the expiration of the DSA
• Presentations to UK government departments of DHSC, DfT and DWP
• Presentations at appropriate conferences
• Blog posts on the ELSA website
• Press/media engagement as appropriate
• Public promotion of the research via the ELSA website
• Participant newsletters

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.

Next target dates for production and dissemination of the outputs are expected to be Winter 2024.

Processing:

NatCen will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, Postcode, Gender and a unique person ID) for the cohort to be linked with NHS England data.

NHS England will provide the relevant records from the Civil Registration Mortality, and cancer registration datasets to NatCen. The Data will contain no direct identifying data items but will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient.

NatCen will securely transfer the Data to UCL, IFS, UoM, and UEA.

The Data will be stored on servers at NatCen, UCL, IFS, UoM and UEA.

NatCen uses offsite back-up services provided by Equinix LD3 data centre.

NatCen stores Data on the Cloud provided by Equinix LD3 data centre.

Amazon Web Services provides cloud hosting services to UCL and will store the data as contracted by UCL.

UCL uses offsite data centre services provided by VIRTUS data centre. VIRTUS does not have access to the data.

The Data will be accessed onsite at the premises of UoM and UEA In addition, the Data will be accessed by authorised personnel at UCL, NatCen and IFS via remote access.

The Controllers 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 the UK. The data will not leave the UK at any time.

Access is restricted to employees or agents of UCL, NatCen, IFS, UoM and UEA who have authorisation from the Principal Investigator at UCL.

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

The Data will be linked at person record level with the ELSA data which is a unique and rich longitudinal study on the dynamics of health, social, wellbeing and economic circumstances* in the English population aged 50 and older which has been running since 2002.

*ELSA may also link participants' details (with their consent) to economic information provided by organisations such as Department for work and Pension and HM Revenue and Customs. These data may include national insurance contributions, tax records and benefits.

The identifying details will be stored in a separate database to the linked dataset used for analysis. All analyses will use the pseudonymised dataset. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset.

Researchers from the UCL, NatCen, IFS, UoM and UEA will analyse the Data for the purposes described above.

Patterning of children and young peoples' mental health before and in the context of Covid-19: findings from the 2017 Mental Health of Children and Young People survey and the 2020 MHCYP Covid-19 follow up survey — DARS-NIC-404798-C1Z9R

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 - 'Other dissemination of information'

Purposes: No (Research)

Sensitive: Non-Sensitive

When:DSA runs 2020-12-17 — 2023-12-16

Access method: One-Off

Data-controller type: NATIONAL CENTRE FOR SOCIAL RESEARCH

Sublicensing allowed: No

Datasets:

  1. Mental Health of Children and Young People
  2. Mental Health of Children and Young People (MHCYP)

Objectives:

This agreement from NatCen is for access to the Mental Health of Children and Young People (MHCYP) survey 2017 and Mental Health of Children and Young People (MHCYP) survey follow up carried out in 2020. This piece of work aims to understand temporal trends and inequalities in mental disorder and service use in children and young people, and the different ways in which symptoms of mental distress and difficulty cluster within a national representative sample of children and young people. This will provide up-to-date evidence using the best sources of data on recent trends in child mental health.

This agreement will use the MHCYP survey 2020 follow up survey of the same children and young people to document the extent to which their mental health has changed during the Covid-19 pandemic. Having an understanding of this distribution pre- and post-pandemic, and how they cluster within sub-groups of the population, can help policymakers and service providers understand the population, deliver support and engagement, and check that they are reaching the relevant groups in the population in the post-Covid context. Moreover, assessing the impact of the Covid-19 pandemic on children and young people's mental health will elucidate causal pathways and highlight pathways amenable to intervention to prevent mental health difficulties persisting into adulthood for this generation affected by these extraordinary social circumstances.

The legal basis under GDPR for processing this data falls under Article 6 (1)(f) giving the lawful basis for processing where: “processing 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.”

A full Legitimate Interests Assessment has been carried out and provided to NHS Digital, based on the ICO template.

The ultimate aim is for the research to help deliver improvements to the health and social care system and ultimately to benefit patients. Without rigorous research into this issue to provide a contribution to the debate, policies may be made without a detailed understanding of who needs and uses health services.

The MHCYP data is the most recent and highest quality data available which can determine the prevalence and inequalities in child mental health and treatment and service use in England. While there are an abundance of alternative community-led data collections or data from trials and interventions carried out by government departments (Department for Education/Department of Health and Social Care) or mental health research centres (e.g. Anna Freud), these are not representative of the general population and tend to sample specific at-risk groups receiving targeted services. In line with the legitimate interest assessment completed by NatCen), Processing of the MHCYP data will therefore yield unique insights into the prevalence and characteristics of children and young people

-with different types of disorder which will drive demand for services
-with different combinations of disorders which can shape the provision of cross-cutting service
-experiencing inequalities in rates of disorder which might pinpoint areas amenable to intervention
-unable to access specialist services
-experiencing mental health issues in the context of family members with similar conditions.

Having access to the survey dataset means that NatCen can analyse it. The dataset is unique. It is the first survey of its kind for more than a decade, and so no other recent dataset is available. NatCen does not process any data that is not relevant and would be unable to achieve the aims of the research without these data.

In brief, the purpose of this is to investigate prevalence and inequalities in child mental health and treatment and service use in England. The ultimate aim is for the research to help deliver improvements to the health and social care system and ultimately to benefit patients. Without rigorous research into this issue to provide a contribution to the debate, policies may be made without a detailed understanding of who needs and uses health services. It is necessary to use the MHCYP data as it is the best available information on general population patterning in mental disorder and self-harm behaviours in children and young people in England, to examine prevalence and identify factors associated with mental disorder and treatment and service use in children and young people. There is the necessity to ensure government have an accurate understanding about population trends in need and can prioritise and plan services accordingly. Individual interests are balanced with legitimate interests and individual interests are unlikely to over-ride legitimate interests as all participants were recruited via a random sample of households in England using standard techniques used in high quality survey research. The survey data were collected directly from individuals. The data were collected explicitly and only for research purposes. Survey participants were told that this was a survey and were given an information leaflet about MHCYP. The way that their data are used was explained to respondents when the survey was carried out. An initial report has been published using the data.

This project will ensure that the public have an accurate understanding of child mental health. Understanding patterns of child mental health is key to understanding a) the reach of existing services, b) the demand for additional services, c) factors and context that prevention programmes should target or address. Without such information on resources are allocated, services designed and commissioned, public behaviour and concern will be based on outdated and incorrect information,

This agreement uses pseudonoymised information from respondents to minimise the risks of individuals being identified. Risks are further minimised by the process of statistical disclosure control where potentially disclosive findings are suppressed and not disseminated. The findings will describe the prevalence of poor mental health in children and young people aggregated at population and sub-population levels and pose low level risk of harm to the public.

The MHCYP 2017 and MHCYP 2020 follow up survey are unique. They are the first surveys of its kind for more than a decade, and so no other recent dataset is available. NatCen would be unable to achieve the aims of the research without these data. These data will yield national representative findings of the mental health of children and young people, exploring mental health and the risk factors underpinning it at a granular level exploring a vast range of mental health outcomes and their antecedents which is not available in any other data source. The high-level findings of the MHCYP 2017 were published in 2018.

NatCen has an agreement to access the pre-release version of the MHCYP 2017 survey data for use on unfunded research projects. The data will only be used by NatCen for the purposes of understanding temporal trends and inequalities in mental disorder and service use in children and young people.

This agreement is for a single purpose, to explore temporal trends and inequalities in mental disorder and service use in children and young people in England pre and post Covid pandemic, should access be granted. The data will be used as part of a NatCen-led programme of research into understanding temporal trends and inequalities in mental disorder and service use in children and young people. NatCen will control and process the data at all times. Involvement of other parties will extend to intellectual collaboration and assistance with formulating hypotheses and devising research questions to achieve the as specified aim: understanding temporal trends and inequalities in mental disorder and service use in children and young people.

18,029 children and young people (aged 2 to 19 years old) in England were asked to take part in the 2017 survey. Contact details were obtained from the NHS Patient Register. Information on 9,117 children and young people was collected from parents, children and teachers, and was examined by a team of clinical raters. Respondents which consented to recontact were followed up during the Covid pandemic of 2020. Sample numbers are not available at this point.
This agreement and subsequent access to data is to support quantitative analysis of the MHCYP 2017 and MHCYP survey 2020 follow up survey, to document in a nationally representative population of England . Attention will be paid to how the mental health of 2-19 year olds might vary and how individual outcomes may cluster together. Health inequalities will be explored by stratifying outcomes and clusters by sociodemographic profiles which can be targeted for intervention to improve quality of life by diminishing the impacts of poor mental health in childhood into adulthood.

The MHCYP 2017 and MHCYP 2020 follow up survey are unique. They are the first surveys of its kind for more than a decade, and so no other recent dataset is available. NatCen would be unable to achieve the aims of the research without these data. These data will yield national representative findings of the mental health of children and young people, exploring mental health and the risk factors underpinning it as a granular level which is not available elsewhere.

This agreement uses pseudonymised information from respondents to minimise the risks of individuals being identified.

NatCen require the MHCYP 2017 and MHCYP 2020 follow up data. It will not be possible to explore the impact of the Covid pandemic on the mental health of children and young people unless NatCen have data collected pre- and post-pandemic.

NatCen require nationally representative data to inform robust, evidence-based policy making. National data also provides the greatest sample size, minimising risk of disclosure of individuals as data will be aggregated by outcomes and population sub-groups.

The data requested has already been collected and therefore respondents will face no burden of research by this agreement. NatCen could not achieve the same purpose by processing less data. The methods are not intrusive as NatCen are not able to directly identify any individual in the data that NatCen process. Nothing identifiable is published.

The data is available as a single extract. Any identifying information pertaining to respondents has been removed from the extract prior to being archived and finalised.

NatCen is the data controller and data processor.

NatCen have generated research proposals/ideas and Mind (the mental health charity) have offered to support that with some funding to answer some specific policy-based research questions. Ultimately, responsibility for the findings and interpretation of the data will be solely NatCen’s - Mind are not a data controller.

Expected Benefits:

Health and social care service providers need to understand how many children in the population experience symptoms and whether this has changed following the Covid 19 pandemic. Importantly, this project will identify what proportion - and which sub-groups of the population - receives treatment or support now compared to prior to the pandemic. Without this basic understanding of changing demands on existing services it is hard for health and education services to prioritise and plan services in a post-pandemic world.

More efficient and equitable provision of mental health services and early identification of children and young people before they enter mental health care systems will significantly reduce the transfer of poor mental health from childhood to adulthood freeing up resource to the wider health concerns and needs of the general population.

These outputs will identify the characteristics of children and young people who have existing mental health needs, and highlight how these needs might cluster and interact to form more severe mental illness and greater levels of costly service provision. Additional attention can be paid to these high risk groups by allocation of more resource, or diversion of resource away from other groups with lesser needs with scope for reduction in service provision. The findings will highlight which children and young people are at greatest risk of these poor outcomes, and identify who was under-served by existing services and who will be under-served by the post-Covid context.

There is no other data source available in any UK context that can provide this detail at a nationally representative level on the mental health needs of children and young people. Further, this data has already been collected and its exploitation confers no additional research burden on the participants. To not exploit these data is to fail the respondents who voluntarily shared their information for research purposes.

These outputs will provide mental health service providers the evidence they need to plan for servicing the existing mental health needs of children and young people as well offer them early insight into emerging trends from the effects of the Covid 19 pandemic. The benefits are social, moral and economic. The benefits are social - 75% of mental health problems in adult life (excluding dementia) start by the age of 18. Failure to support children and young people with mental health needs costs lives and money. Early intervention avoids young people falling into crisis and avoids expensive and longer term interventions in adulthood. There is also the moral obligation to do, as a society, what it can to ensure that all members have a decent quality of life and that they have the capability to fulfill their capacity. Early life poor mental health hinders that goal, but these data can inform who is most at risk of poor mental health, why, and what might be put in place to alleviate ill health as well as protect others. The cost savings at re-tuning existing services in terms of content or scale will be of considerable benefit to the Treasury. The economic cost of poor mental health in young people’s has been estimated at 5.3 billion pounds for a single cohort of children in the UK (Future in Mind, 2015).

These findings will be disseminated to existing stakeholder groups who already have strong lobbying position with politicians and policymakers. Evidence of benefit of this research will be seen in emerging policy announcement which are increasingly reliant on data to back their approaches. The anticipated returns on this evidence production are expected within the next 5 years as the impact of the Covid pandemic on a generation of young people becomes fully evident, as does the toll it has taken on their mental health which these data will describe.

This study will be completed by existing employees at NatCen Social Research; there is no student involvement.

Outputs:

What will be produced as a result of the data processing.

a. Reports
A single 30 page report outlining key findings supported by additional data tables which have been checked by researchers accredited with the safe handling of secure data to reduce risks of data disclosure. The report will be published by the funding agency, Mind, and hosted on the NatCen website. The anticipated publication date is February 2021.

NatCen will work with Mind on a stakeholder engagement event, convening existing networks such as the Children and Young People's Mental Health Coalition, the Association for Young People’s Health, Young Minds and the Centre for Mental Health. The aim is to publicise these findings through these stakeholder media channels to raise public awareness and for the public to learn about the young people’s mental health and how it can be promoted and protected. The further aim is to use this stakeholder network to reach policymakers with the means to implement changes which will improve on and protect the young lives of children and young people who have or are vulnerable to poor mental health.

Submissions to peer reviewed journals.

NatCen will submit the findings to peer-reviewed journals (if applicable) with anticipated publication Winter 2021.

b. Presentations
NatCen intended to present findings to the charity Mind and its trustees who are aiming at influencing policymakers through their existing networks. NatCen researchers often attend and present to Parliamentary APPGs and will target attendees at the APPG on Mental Health. Anticipated Spring 2021.
c. Conferences
NatCen will engage researchers through academic conferences and will target the annual conference of the Royal College of Paediatrics and Child Health and the MQ Mental Health annual conference. Anticipated Autumn 2021.
d. Dashboards
All findings will be hosted on the NatCen website.

Outputs will be aggregated at population and population sub-group levels (e.g. age groups, ethnicity, gender). Cell counts below 25 are routinely supressed for publication via case borrowing across cells, collapsing into neighbouring cells or through simple exclusion whereby cell counts cannot be deduced from other published findings.

This research will deploy conventional epidemiological statistical methods. NatCen do not anticipate any technological innovation during this project. Funders do not expect innovation or knowledge transfers.

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 ie: employees, agents and contractors of the Data Recipient who may have access to that data)”

There will be no flow of data between Natcen and NHS Digital. NatCen prepare the MHCYP datasets on behalf of NHS Digital - therefore access can be facilitated internally subject to a valid data sharing agreement being in place.
Data will be downloaded from the UKDS (UK Data Service)

NatCen will receive the whole standard datasets as there is no facility to select individual variables. Access will be permitted for the period specified within the DSA and NatCen must securely destroy all local copies of the dataset when the DSA expires and notify DARS in line with standard procedures.

For both datasets, all identifying information has been removed prior to being archived in the final dataset. Should any potentially disclosive information be uncovered during processing then these data will be suppressed from publication; no further data linkage shall take place.

NatCen researchers accessing the data have been trained in statistical disclosure control by the ONS and NatCen confirm that no attempts to de-identify respondents will be made.

No third parties will have access to the datasets.

All data will be securely contained on NatCen servers which are inaccessible to all except employees or contracted associates. Remote access to NatCen IT systems is available to employees via the NatCen encrypted Virtual Private Network. Data will not be stored by any organisation not named on the data agreement.

NatCen is responsible for processing data at the single stage and will store these data securely for the agreed period and not share it with any third parties. Data will only be accessed by individuals within NatCen who have authorisation to access the data for the purposes described, all of whom work for NatCen.
How the data is being processed at each stage/what is being done with the data to achieve the stated purpose

-What will be done with the data:
1.The data will not be linked with any other data outside of the MHCYP surveys.
2.There will be no requirement nor attempt to re-identify individuals from the data.
3.The data will not be made available to any third parties except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.

MHCYP and the Covid-19 follow up are only available as full datasets, though minimisation has taken place centrally prior to the dataset being made available. In addition, the full dataset is required in order to cover all of England (national analyses) and to be able to control for a range of factors in the analyses. A range of conditions will be examined in the analyses.

Data management and variable derivation will be done in SPSS and Stata statistical software packages. Analyses will be conducted in Stata and R, using survey weights and controlling for complex survey design. All patterns reported on will be tested for statistical significance.

Simple descriptive analyses will be used to generate prevalence rates and produce cross-tabulations. These will be presented in tabulations (using percentages and means, and showing base sizes), bar charts, and line graphs. Trend data (from comparisons with earlier surveys in the series) will be based on consistently defined age-ranges and geography for comparability across years. Multiple regression analyses will be carried out to examine association between risk factors and mental health outcomes or service and treatment access when other factors are controlled for, and to identify the role of different potential mediators or explanatory factors. Population attributable fractions may be calculated to compare risk factors with variable extent and variable strength of association. NatCen will examine different options for testing what risk factors may be driving any changes in rate or distribution of mental illness or treatment and service use access. Latent class analyses may be conducted to profile how different and multiple adversities across mental health and other life circumstances cluster together.

While the focus of the study is the mental health and service and treatment use of children and young people, these patterns will be considered in relation to family, neighbourhood and school context. Where available in the dataset, analyses will be conducted on data from children, parents and teachers, so that comparisons can be made. All of the information on family, neighbourhood and school context (teachers) is in the data already. No linkage is made to any other data.

The scope of the analyses will be entirely conducted by NatCen and the data will only be used for the purposes described in this agreement.