Implementation process of social prescribing to improve primary care patients’ health and well-being

Abstract

Social prescribing (SP) is an innovative approach to tackle social determinants of health. It enables general practitioners (GPs) to address non-medical causes of ill-health by linking primary care patients with non-medical community sources of support. Despite convincing results from punctual evaluations, comprehensive evaluation of SP is needed to provide guidance on what works and evidence on its impact. A SP pilot-project started in 2018 in a primary care service in Lisbon. Its implementation process and outcomes are being evaluated through a longitudinal mixed-method evaluation study assessing patients’ wellbeing, quality of life, anxiety and depression in key stages of the intervention and stakeholders’ perspectives on facilitators/barriers to the intervention implementation. GPs refer patients to a social worker of the service, who defines with the patient the individual intervention plan using community resources. Initially, GPs and social workers were trained on SP, a network of community partners was built, SP information was distributed to patients, a referral online platform was created and a baseline study is being conducted. In the 1st semester, 130 patients were referred: 39.2% were ≥65 years old, 70.8% were female, 45.4% had foreign nationality. Over two thirds were referred for multiple reasons mostly social isolation, immigration/social integration, mental health, sedentary lifestyle, access to social benefits and employment/skills training. The project has enabling to support patients with multiple complex psychosocial needs. Regular meetings between GPs and partners have improving collaboration and patients’ supervision. The participatory approach and training emerged as facilitators of the intervention. Yet, the increased burden on social workers due to growing referral profile and some stakeholders’ scepticism toward SP need to be addressed. The triangulation of sources, methods and data provide evidence on the intervention impact and scalability.