Mental Health Services Data Set (MHSDS) - for the purposes of Statistics and Statistical Research, under section 45A of the Statistics and Registration Services Act 2007 as amended by the Digital Economy Act 2017

The Statistics Board requires access to Mental Health Services Dataset (MHSDS) held by NHS England to carry out its functions in accordance with the Statistics and Registration Service Act 2007 (SRSA) - Section 20: Production, Publishing, and providing advice on Statistics produced under S20 Official statistics .

The purpose is restricted to these specific projects uses:

1. The feasibility of producing estimates of disability status and general health as part of its research into developing an Administrative Data Based Census (Project 1)

To achieve this, a range of health and non-health admin datasets, and Census 2021, are being linked to explore the correlation between information that might indicate disability or general health status on these admin sources, and self-reported disability status and general health as recorded on Census 2021. By providing a more complete picture of mental health, MHSDS will help improve this work.

This work may also allow us to improve our healthy life expectancy statistics which are currently based on survey data. These statistics help guide decisions by Local Authorities (LAs) about the distribution and prioritisation of services, and more granular and accurate they are, the better they will allow LAs to target interventions to reduce health inequalities.

2. Evaluation of Mental Health Conditions and Service use (within MHSDS) on labour market outcomes (Project 2).

This project will link MHSDS, Census, deaths, Hospital Episodes Statistics (HES), Emergency Care Dataset (ECDS) and income and benefits data from HM Revenue and Customs (HMRC) and Department for Work and Pensions (DWP) to produce statistics on the impact of mental health and mental health services (including but not limited to; Individual Placement and Support and Neurodiversity Services) on employment, earnings, benefits receipt and hospital utilisation.

There is government support in analysis which aligns with the Kickstart economic growth mission and Get Britain Working White Paper. There has been a commitment by government to expand the IPS service to increase access to people with severe mental illnesses and neurodiversity services are also a key focus within government with interest from DHSC and DWP in investigating this link further.

3. Quantitative evaluation of mental health support for young people (Project 3).

This analysis will link MHSDS data with NHSTT and 2021 Census data to understand the demographic and services use of young people attending services. The aim of this work is to explore the characteristics of young people seeking treatment for symptoms of anxiety and depression who are accessing different mental health services, and which services result in improved mental health and functioning outcomes for young people.

This research aims to improve access to timely mental health support for young adults in the UK. It also has the potential to generate strategies to improve access to early mental health support for young people from minoritised groups, who are currently less likely to access community-based mental health care.

The projects listed above have undergone an ethical self-assessment and have been signed off by the data ethics team (projects 1 and 3). Where indicated by the self-assessment tool and upon advice from the data ethics team, a full ethics application was taken to the National Statistician’s Data Ethics Advisory Committee (NSDEC) – (project 2).

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

NHS England will provide the MHSDS Data to ONS.

The Data will contain directly identifying data items which are required to link the Data at record level with data already held by the recipient.

The Data is transferred to the ONS Secure Estate, where it undergoes virus scanning before being ingested into one of the Trusted Research Environments (TRE)s within the security controlled ONS analysis environment.

Identifiable data is managed by a small group of security cleared, highly trained specialists. They are responsible for de-identifying, cleaning, and, where required, linking the data to other sources before relocating it to a secure area within the security controlled ONS analysis environment.

ONS personnel, who use the data to carry out statutory functions, access only de-identified data within a designated workspace.

The security controlled ONS analysis environment provides the security controls required for secure data storage, management, and linkage. These controls include:

•Access to the data is restricted to individuals granted access on the basis of a justified need to access the data

• Controlled ingest and export of data into/out from the environment

• Controlled account access using unique credentials based on job role

• Logged and monitored access of user activity within the environment

• Secure build configuration for infrastructure

• Vulnerability tested infrastructure with appropriate remediation and patching

• Compliance checks against security enforcing controls

• Architectural review against standards and best practice

• Staff security cleared to the appropriate level based on their supervised and/or unsupervised access to sensitive data in accordance with ONS clearance policies and data access processes

• Education and awareness of environment users covering security policies and secure working practices

• Operational support processes to securely manage the environment

• Risk assessment to identify security risks and mitigation actions to reduce this risk

Amazon Web Services (AWS) and Google Cloud Platform (GCP) provide IT hosting services to ONS and will store the data as contracted by ONS as a processor.

ONS will never seek to intentionally re-identify this Data.

ONS personnel may access the data in the following ways:

• provided through assured organisational connectivity from an approved office environment that meets required assurance standards

• provided through assured organisational homeworking arrangements where organisational technical controls have been approved

The data will be used to produce official statistics. These will be released on the ONS website in the form of a statistical bulletin and statistically disclosure controlled aggregate data tables, and potentially in peer-reviewed scientific journals. Headline results may also be published on social media, and within a blog on the ONS website.

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.

Statistical Research and Health Analyses

Mental health is a high priority in government policy. Co-morbidities between mental and physical health, as well as inequalities in mental health, are of increasing interest within health policy.

ONS currently uses IAPT and HES data to explore the relationship between mental and physical health, understand the demographic context of mental health outcomes and investigate inequalities. MHSDS captures more extreme cases of mental health care, thus would enable a fuller picture of mental health diagnoses and outcomes and enhance research in all these fields.

Investigating the links between mental health, mortality, and co-morbidity has clear benefits for the public. By determining physical and mental health conditions that commonly co-occur, the government can target its health services to better meet the needs of patients resulting in a better patient experience, and ultimately could saves lives. For example, it may be that a particular cause of death has an increased prevalence in patients with mental health conditions compared to the general population; by ensuring policy makers and clinical staff are aware of this, prevention and intervention could be more targeted.

Mental health problems disproportionately affect people living in poverty, those who are unemployed and who already face discrimination. The King’s Fund found that people with long term physical health problems and co-morbid mental illness disproportionately live in deprived areas. Analyses of these data allows for detailed geographical mapping of those with a mental health condition who died from particular causes, and by deprivation deciles.

Other demographic variables could also be used for inequalities analysis to investigate any difference in premature mortality in certain demographic groups of mental health care receiver (age, sex, or occupation) versus the general population. Obtaining this information will benefit the public by allowing healthcare providers to target groups who may be disproportionately affected by physical and mental health problems, and subsequently reduce premature mortality due to co-morbidities.

Successful production of more robust healthy life expectancy, disability and general health statistics would support better decision making around where to set the state pension age, and planning of health and social care services:

Evidence of this includes the Cridland report, 2017 which was commissioned by government to independently review the state pension age, and made the following statement:

(https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/611460/independent-review-of-the-state-pension-age-smoothing-the-transition.pdf)

“We believe more work is needed to understand healthy life expectancy, as it affects a range of policy areas. Projecting healthy life expectancy into the future is not currently possible, but would be valuable for future Reviews, as well as in work around health and caring.”

The report also notes:

• Developments in Healthy Life Expectancy and Health State Transitions will have a notable impact on the demand for social care and different types of medical care, for instance the number of trained dementia nurses required in 40 years’ time

• In order to manage budgets and allocate funding effectively, there is a need to understand what the main patterns of key diseases will be, and what the distribution of these illnesses across the population will look like

• It is likely that the prevalence of diseases which affect the oldest old such as cancer and dementia will increase

• If social care and health care provision needs to be increased, the national budget will need to be changed to reflect this which may result in other services seeing cuts.

Linking health states and mortality at the individual level over time, and for a greater proportion of the population will allow more granular analysis. Linking to Census and other sources to add in other characteristics, could inform interventions to support tackling inequalities at the local level.

Yielded Benefits is not a requirement for new applications.