Building the business case for work interventions to support people with musculoskeletal diseases

This programme at the University of Manchester aims to understand the factors relevant for informing the business case of workplace interventions to support those with musculoskeletal diseases (MSDs).

Rheumatic and musculoskeletal disease (RMD) -focussed interventions have can have a broad range of work-related impacts. The costs of implementing these interventions might be borne by employers, employees, public/charitable funds or a combination of these.  Given this, the decision about whether to invest in an intervention can be made by determining, from the relevant perspective, if the benefits outweigh the costs of implementation. Economic evaluation approaches such as cost-benefit analysis, cost-effectiveness analysis and budget impact assessment exist to aid this decision-making.

From the perspective of the NHS, for example, there exist formal approaches to economic evaluation in order to determine if an intervention is cost-effectives based on a pre-defined threshold of acceptability. Previous work has explored the extent to which decision-makers in health care systems use and value economic evidence (Hoffmann, 2002). More broadly, from an employers’ perspective, there is no commonly agreed set of decision rules and little is known about what types of economic evidence would be valued by employers to aid decisions about whether to invest in such interventions.

Workpackage 2

The aim of this workpackage is to support decision-making around implementing interventions for MSDs (in this case arthritis) by providing evidence of any causal relationship identified between arthritis and labour market outcomes. 

More specifically, this work will look to assess the relationship between arthritis and specific labour market measures, including:

  • Sickness absence

  • Occupation or job transitions

  • Unemployment, retirement, or other periods of economic inactivity

We will also conduct additional analyses in order to assess whether there is heterogeneity in the effect of arthritis in relation to:

  • Employer type (for example, public vs private sector)

  • Inequalities (including factors such as gender, ethnicity or social and economic deprivation)

Aims

This programme consists of two workpackages, each with it own distinct aims:

Workpackage 1

Using a combination of literature review methods and qualitative interviews, Workpackage 1 is aimed at understanding:

  1. What types of evidence have been used previously to aid employers’ decisions with regards employees with MSDs

  2. What types of evidence might be valued by employers for future decision-making around RMD-focussed interventions

What will this research involve?

Workpackage 1

This workpackage consists of two phases - firstly we will undertake a review of the existing literature, before then conducting a series of interviews with employers and / or company representatives.

The literature review will consist of a scoping review in order to understand the evidence base regarding what, if any, types of evidence have been used previously to aid employers’ decisions with regards implementing interventions for employees with MSDs.

We will then conduct semi-structured interviews with employers and / or representatives of companies to understand what types of evidence employers want to inform decisions about the introduction of interventions to help workers living with long-term conditions.

Workpackage 2

In Workpackage 2, we will first perform a scoping review of relevant literature and existing datasets in order to understand the evidence base around the relationship between arthritis and labour market conditions, and to identify the most appropriate existing dataset for further analysis.

Previous studies have explored the relationship between health and work in the context of mental health conditions (Garcia-Gomez, Jones and Rice, 2010; Whittaker et al., 2012; Whittaker and Sutton, 2015),  we will take a similar approach with large cohorts (we have identified the UK Household Longitudinal Survey) to explore the relationship between sickness absence, retirement, unemployment, inactivity, occupation/job changes and MSDs. Analyses will take account of inequalities, co-morbidities (such as mental ill health), and other relevant factors.

Using the chosen dataset, we will conduct econometric analyses in order to examine the relationship between arthritis and labour market measures, such as sickness absence, job transitions, and unemployment or retirement. We will also conduct additional analyses to see whether there is any heterogeneity in the effect of arthritis in relation to the type of employer (for example, public or private sector) and any known social inequality factors such as gender, ethnicity or deprivation.

What has the study found so far?

Workpackage 1

The scoping review of the literature is now complete, and we have identified key themes in the evidence base:

  • There is a difference in attitude towards support for employees with MSDs across different types of organisations (for example, between small and large companies)

  • The underlying beliefs and rationales behind these attitudes are complex, and can act either as drivers of, or barriers to, implementation

  • There is unlikely to be one type of economic evidence which will be required by all companies to inform decisions over whether or not to invest in workplace initiatives

  • Complex systems theory is a potentially useful theoretical framework from which to conduct our qualitative analysis

We have now also completed our interviews for this workpackage with 13 participants, including 5 directors, 3 line managers, and 4 people with a specific remit for workforce health. Results from this have now been published as an abstract and were presented at the EULAR Annual European Congress of Rheumatology 2023. You can read the abstract from this work here:

Workpackage 2

The scoping review phase of Workpackage 2 is now complete, and we have made the following key findings:

  • There is limited evidence with regards longitudinal analyses of the relationship between arthritis and labour market outcomes. Longitudinal data (i.e. data which has been followed up over time rather than just at a specific time point) enables assessment of any changes which in turn enables us to better identify relationships of causation rather than association)

  • We identified the UK Household Longitudinal Survey (UKHLS) as the most appropriate dataset to use for our analyses, as it consists of longitudinal data and contains a broader age group and a rich set of labour market measures when compared to other datasets we identified

Our econometric analyses are ongoing, with our preliminary analyses indicating:

  • People with arthritis were less likely to be employed or self-employed and more likely to be retired or on long-term sick.

  • Arthritis appears to have a limited impact on sickness absence or unemployment, but does appear to be associated with transitions out of employment and to long-term sick. In particular, employment becomes increasingly less likely in the run up to an arthritis diagnosis and long-term sickness becomes increasingly more likely in the run up to an arthritis diagnosis.

The team are continuing the analyses to adjust for potential confounding factors and will be assessing whether these relationships are similar depending on the type of job and employer.

Results from our initial analyses have now been published as an abstract and were presented at the EULAR Annual European Congress of Rheumatology 2023. You can read the abstract from this work here:

Study team

Chief investigator
Dr Suzanne Verstappen (University of Manchester)


Co-investigator
Professor Katherine Payne (University of Manchester)


Associated research staff
Mr Martin Eden (University of Manchester)
Dr James Higgerson (University of Manchester)
Dr William Whittaker (University of Manchester)

Centre institutions

Further information

For any queries related to Workpackage 1, please contact martin.eden@manchester.ac.uk

For any queries related to Workpackage 2, please contact william.whittaker@manchester.ac.uk