At our second MS Services Variance meeting, ‘Raising the Bar’, in Birmingham last week my colleague Helen Ford and I co-chaired the workstream on the social determinants of health (SDoH).
What are the SDoH?
The SDoH are life-enhancing resources, such as food supply, housing, economic and social relationships, transportation, education and health care, whose distribution across populations effectively determines length and quality of life. As MS is such a disabling disease with poor quality of life it is likely to impact on the SDoH, which in turn will feedback and make MS outcomes worse. This vicious cycle needs to be broken if we want to optimise MS outcomes; i.e. when applying the philosophy of marginal gains we can’t ignore the SDoH when managing someone with MS.
The following is a selection of slides we put together around the SDoH theme.
Do you have an example of how the SDoH can impact on a person with MS?
The study highlighted below from Sweden is an example of how MS reduces your earnings. Interestingly, the reduction in earnings even begins before MS diagnosis and clearly increases thereafter. I suspect some people who have prodromal MS have difficulty working, which impacts on the average outcome or earnings. Besides sickness absence and disability pension, educational level and type of occupation are influential determinants of earnings in pwMS. In other words, inequality plays a role in determining your earnings once you have MS. Are you surprised? I am not.
When we asked whether or not MS HCPs routinely screen for the SDoH very few hands went up in the room. The hands that went up tended to belong to occupational therapists; they clearly need to look at SDoH as part of their treatment plans. No neurologists put up their hands and therein lies a problem or a solution depending on how you look at things.
The following is a short list of some of the SDoH that may impact on MS outcomes, which we discussed.
- Level of education and health literacy
- Poverty (absolute or relative)
- Employment / unemployment
- Access to social services (personal independent payments, etc.)
- Home environment (heating, cleanliness, amenities, etc.)
- Local environment (safety, green spaces, amenities, etc.)
- Food poverty (absolute or relative)
- Transport (access and costs)
- Childcare (access and costs)
- Social isolation (social networks, access to the internet, mobile phone, data, etc.)
- Lifestyle factors (sedentary vs. active, smoking, alcohol and other addictions)
- Need to be looked after by a child (child carer) or ageing parents or other family members (aged carers)
- Cognitive impairment and hidden psychiatric comorbidities (depression and anxiety)
- Physical and emotional abuse
How do we address these issues in an MS clinic without upsetting our patients by being too overbearing? We did agree that there was a lot we could potentially do about some of these SDoH and that we had an obligation to at least consider these as part of our routine management of our patients and their families. Some ideas that emerged in our session include the following:
- Provide information about IT solutions to help pwMS.
- Start a high-risk register of patients within our service; patients on this list would need to be seen and contacted more frequently, ideally on pre-planned and regular basis.
- Start a home visit programme. Most services have had to stop home visits because of resource and staffing issues.
- Make sure our patients know that they can get hospital transport so they don’t go out of pocket or reimburse their travel costs.
- Convert were possible physical face-2-face visits with telemedicine options.
- To do a complex needs assessment similar to what is done in other disease areas to identify high-risk or vulnerable patients.
- Lobby the government to waive prescription costs for pwMS and other disabilities.
- Lobby government to create a healthy food voucher system for pwMS and other disabilities.
- Lobby government to improve social services for pwMS and other disabilities.
- Engage pwMS and include them in your service; for example, using an MS Health Champions model.
- Explore social prescribing to increase social capital.
- Enrol all patients into a lifestyle and wellness programme.
Wiberg et al. Earnings among people with multiple sclerosis compared to references, in total and by educational level and type of occupation: a population-based cohort study at different points in time. BMJ Open. 2019 Jul 11;9(7):e024836.
OBJECTIVES: To investigate earnings among people with multiple sclerosis (PwMS) before and after MS diagnosis compared with people without MS, and if identified differences were associated with educational levels and types of occupations. Furthermore, to assess the proportions on sickness absence (SA) and disability pension (DP) in both groups.
DESIGN: Population-based longitudinal cohort study, 10 years before until 5 years after MS diagnosis.
SETTING: Working-age population using microdata linked from nationwide Swedish registers.
PARTICIPANTS: Residents in Sweden in 2004 aged 30-54 years with MS diagnosed in 2003-2006 (n=2553), and references without MS (n=7584) randomly selected by stratified matching.
OUTCOME MEASURES: Quartiles of earnings were calculated for each study year prior to and following the MS diagnosis. Mean earnings, by educational level and type of occupation, before and after diagnosis were compared using t-tests. Tobit regressions investigated the associations of earnings with individual characteristics. The proportions on SA and/or DP, by educational level and type of occupation, for the diagnosis year and 5 years later were compared.
RESULTS: Differences in earnings between PwMS and references were observed beginning 1 year before diagnosis, and increased thereafter. PwMS had lower mean earnings for the diagnosis year (difference=SEK 28 000, p<0.05), and 5 years after diagnosis, this difference had more than doubled (p<0.05). These differences remained after including educational level and type of occupation. Overall, the earnings of PwMS with university education and/or more qualified occupations were most like their reference peers. The proportions on SA and DP were higher among PwMS than the references.
CONCLUSIONS: The results suggest that the PwMS’ earnings are lower than the references’ beginning shortly before MS diagnosis, with this gap increasing thereafter. Besides SA and DP, the results indicate that educational level and type of occupation are influential determinants of the large heterogeneity of PwMS’ earnings.