Social prescribing links patients in primary care with sources of support within the community, so that people with social, emotional or practical needs are empowered to find solutions which will improve their health and wellbeing.
Within London, the Whole Systems Integrated Care (WSIC) dataset provides a major opportunity to evaluate the impact and outcomes of personalised care across NW London, and to inform national work. Across the UK, GPs have also been increasingly using a scale called the Patient Activation Measure (PAM) to determine who could benefit from social prescribing or other forms of personalised care. PAM assesses patients’ knowledge, skills and confidence for self-managing their health and long-term conditions, with higher PAM scores associated with better health across a range of outcome measures as well as (in some settings) lower health care costs.
In this project, we have been exploring the association between PAM and health service utilisation both cross-sectionally and over time (including primary care, outpatient care, admitted patient care, and A&E care). We have also been identifying who is being offered social prescribing in Northwest London, and whether there were any systematic differences between patients who took up or declined the service.
An extension of this project involves us working with the Elemental dataset. Elemental is the most widely used social prescribing software platform in the UK. It currently contains data from 808 social prescribing hubs spread across the UK representing 16,000 prescribers (including GPs, nurses, practice managers, housing officers, local government staff and social workers), 2,886 link workers, and 148,719 patients who between them have carried out 740,594 visits to activities. As Elemental is an active platform, these numbers are growing each month. Elemental contains specific data on demographics (e.g. age, gender, socioeconomic status, geographical area, area deprivation etc), medical history (e.g. physical and mental health conditions, medication, risks), reasons for referrals (e.g. pain, mental health, social isolation etc), interventions prescribed (e.g. talking therapies, welfare/financial support, volunteering, exercise programmes, arts/cultural activities etc), and uptake and frequency of intervention engagement. However, to date, there have been no formal analyses of the Elemental data set.
Therefore, we are analysing anonymous data collected by Elemental to explore (i) what the impact of social prescribing is on individuals and the health service, (ii) which populations and patient groups are showing the greatest benefits from social prescribing, and (iii) how differences in the way social prescribing is delivered to patients affect its impact. The project has the potential to inform the design and delivery of social prescribing services in the UK, supporting the work of social prescribing service providers, healthcare professionals, clinicians and policy makers.
Dr Feifei Bu
Bu, F., Fancourt, D. (2021). How is patient activation related to healthcare service utilisation? Evidence from electronic patient records in England. BMC Health Services Research, 21 [DOI]