Acceptability of a task sharing and shifting model between family physicians and physiotherapists in French multidisciplinary primary healthcare centres: a cross-sectional survey

OBJECTIVES: The rising prevalence of musculoskeletal disorders increases pressure on primary care services. In France, patients with musculoskeletal disorders are referred to physiotherapist (PT) by family physician (FP). To improve access to musculoskeletal care, a new model of task sharing and shifting is implemented between FPs and PTs for patients with acute low back pain. This new model enables French PTs to expand their usual scope of practice by receiving patients as first-contact practitioner, diagnosing low back pain, prescribing sick leave and analgesic medication. The aim of this study is to investigate the acceptability of FPs and PTs regarding this new model. DESIGN: A cross-sectional survey design was used. Acceptability was measured using a questionnaire on the perception of the model and the perception of PTs’ skills to manage low back pain. Descriptive analyses were performed to compare results among participants. SETTING: French FPs and PTs working in multidisciplinary primary healthcare centres were invited to complete an online survey. PARTICIPANTS: A total of 174 respondents completed the survey (81 FPs and 85 PTs). RESULTS: A majority of participants had a positive perception of the task sharing and shifting model. A majority of the participants were mostly or totally favourable towards the implementation of the model (FPs: n=46, 82% and PTs: n=40, 82%). The perceived level of competencies of PTs to manage acute low back pain was high. The confidence level of FPs was higher than that of PTs regarding PTs’ ability to adequately diagnose low back pain, refer patient to physiotherapy and prescribe sick leave or analgesic medication. CONCLUSION: Based on this limited sample of participants, there appears to be good acceptability of the task sharing and shifting model for acute low back pain. Additional studies are needed to better determine the factors affecting the acceptability of such a model.