BMC Primary Care (Feb 2023)
Consultation frequency and general practitioners’ and practices’ characteristics
Abstract
Abstract Background High workloads generated by a few patients who consult very frequently can become huge burdens for general practitioners (GPs). Patient-related factors have been repeatedly associated with frequent consultations, but there is evidence that GPs can also influence that frequency. We investigated how patients, GPs and their practices’ organisational characteristics were associated with consultation frequency. Methods Data came from the SPAM Prev (Swiss Primary Health Care Active Monitoring, Prevention in primary care) national, cross-sectional survey conducted in 2015–16, including 167 GPs and 1105 patients. GPs completed an online questionnaire focused on practice organisation. Patients randomly recruited in general practices completed a questionnaire with fieldworkers. Factors predicting consultation frequency were investigated using multilevel Poisson regression models. Results Negative associations with consultation frequency were found for females (Incidence Rate Ratio (IRR) 0.94, 95%CI [0.88–1.01]), less compliant patients (IRR 0.91, 95%CI [0.84–0.98]), high self-perceived health status (IRR 0.8, 95%CI [0.75–0.84]) and physical exercise (IRR 0.87, 95%CI [0.81–0.94]). Consultation frequencies were higher among patients with sleeping problems (IRR 1.08, 95%CI [0.96–1.23]), psychological distress (IRR 1.66, 95%CI [1.49–1.86]), chronic diseases (IRR 1.27, 95%CI [1.18–1.37]) and treatment with medication (IRR 1.24, 95%CI [1.12–1.37]). Positive associations with consultation frequency were found among GPs working longer hours (IRR 1.21, 95%CI [1.01–1.46]). Using shared medical records (IRR 0.79, 95%CI [0.67–0.92]) were negatively associated with consultation frequency. Conclusion GPs’ practices’ characteristics, like patients’, are predictive of patients’ consultation frequency, but those associations’ underlying mechanisms require further qualitative investigation. These new findings could help optimise intervention strategies and reduce healthcare costs.
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