Health and social care diversity among individuals with longstanding physical and psychological health problems
Authors: Corine Driessens, David Kingdon, David Pilgrim and Peter W. F. Smith (University of Southampton)
Date: February 2020
A research project using secure data explored the differences in health and social care utilisation for individuals with physical and/or mental health problems. The findings of this project confirm the disparity in health care utilisation and newly identify a problem in labour force integration for individuals with mental health problems.
Since 2008, there has been an increase in people reporting mental health problems in the UK. This project, using the Office for National Statistics (ONS) General Lifestyle Survey data collected between 2000 and 2011, investigated the nature of inequality for individuals with longstanding illness in Britain. The findings of this study led to an offer of funding from Nuffield Foundation for further research on mental health services.
This project accessed the General Lifestyle Survey (GLF) (formerly known as the General Household Survey (GLS) until 2008) through the ONS Secure Research Service. This survey provides data on families and people living in private households in Britain. This project used the GLF/GLS to focus on participants who classified as having a physical, mental or a physical-and-mental health problem.
In the introduction of their paper the researchers mention that the data of the Labour Force Survey (another ONS Secure Research Service dataset) reveals an increase in people reporting mental health problems since the recession in 2008. The LFS is made up of 40,000 responding UK households and 100,000 individuals per quarter. It provides data on time and change estimates for various labour market outputs and related topics.
The researchers conducted a secondary analysis of the 2000 to 2011 data in the GLF. They applied a logistic regression model, which is a process to determine the probability of a discrete outcome given the input variables. For this project, logistic regression was used to describe the nature of potential associations and to determine if the relationship persisted when controlling for time and potential confounding variables.
All the data from the 11 years was pooled into one dataset with focus on survey participants who were receiving health and social care. By pooling data, the researchers gained a sample size that increased the precision of the estimators and minimised disclosure risk. Annual weights were applied to the data to make sure the annual sample was representative of the British population. Age, gender, work status and ethnicity were included as controls in the logistic regression model. Various socioeconomic indicators were also considered for the analysis, such as renting or owning housing, owning a car or a computer and job level.
This research revealed differences in labour market integration and health care utilisation between individuals with mental health problems and those with physical health problems.
From 2000 to 2011 individuals with mental health problems were less likely to receive services from secondary health care providers and were more likely to receive out-of-work disability benefits compared to those with physical health problems.
Significantly fewer individuals with mental health problems had full- or part-time employment and significantly more individuals with mental health problems were long-term unemployed compared to individuals with physical health problems. Many of those with physical health problems were encouraged into employment status transitions due to the introduction of conditional criteria in the welfare system.
The social care system was less successful at transitioning individuals with mental health problems from out-of-work benefits to paid employment than those with physical health problems.
The disparities in health care revealed by this study can be addressed by policy interventions, ensuring that health care does not only focus on medical treatment but also vocational rehabilitation. This supports the political call for a ‘parity of esteem’, which is part of the Health and Social Care Act of 2012.
Additionally, this research has highlighted the issue of irregular collection of health and social care survey data by the government. The researchers suggest that the information available in administrative data sources might be able to replace these surveys and inform policy makers as to whether the implementation of health and social care interventions had a desired effect.
Based on the findings of this report the researchers had an offer for further funding from the Nuffield Foundation to continue to explore mental health services in times of austerity within administrative data sources. In anticipation of potential linkage of Clinical Practice Research Datalink (CPRD), NHS-Digital, Department for Work and Pensions (DWP) and Care Quality Commission (CQC) data, the researchers explored Mental health service users’ perceptions on the use of administrative data for research. The findings were presented at the Administrative Data Research Network conference of 2018 and were published as part of a case study on Mental health service users’ perception of data sharing and data protection.
Publications and reports
- Community Mental Health Journal, February 2020: Health and social care diversity among individuals with longstanding physical and psychological health problems: Pooled Repeated Cross-Sectional Analysis
Presentations, blogs, news posts and awards
- Presented at the Nursing conference, Berlin, October 2017
- Presented at Douglass Bennet session of the Rehabilitation & Social Psychiatry conference, November 2017
About the ONS Secure Research Service
The ONS Secure Reseach Service is an accredited trusted research environment, using the Five Safes Framework to provide secure access to de-identified, unpublished data. If you use ONS Secure Research Service data and would like to discuss writing a future case study with us, please ensure you have reported your outputs here: Outputs Reporting Form and get in touch: IDS.email@example.com.