Preferences for implementing training program among primary care physicians in prescribing and deprescribing for...

Primary care physicians (PCPs) have great needs of receiving training and potential to improve their capacities of prescribing and deprescribing for patients with multimorbidity. However, limited studies focused on PCPs' preferences for how training program is implemented. This study used a discrete choice experiment (DCE) to investigate PCPs' preferences for implementing training program in prescribing and deprescribing for patients with multimorbidity.

This study surveyed PCPs in eastern China from October 10 to December 5, 2024 using an electronic questionnaire. Eight attributes and levels in a DCE were identified based on implementation science theory: instructor composition, teaching model, training location, participant enrollment, session duration, training frequency, assessment methods, and theoretical basis of the course. DCE data were analyzed using a mixed logit model to explore respondents' attribute preferences. Relative importance scores and predicted changes in training implementation selection rates were calculated.

The preference model included 2,976 choice observations from 248 respondents. These respondents were 50.4% male and the overall average age was 37.7 years. They showed significant preferences for five attributes, ranked in order of relative importance score: training frequency (37.29%), session duration (27.23%), instructor composition (16.29%), participant enrollment (10.23%), and theoretical basis of the course (8.95%). Scenario analysis revealed that optimizing high-preference attributes (e.g., shorter duration, multidisciplinary instructors) could increase acceptance of weekly training by up to 66.75%.

PCPs prioritize time-efficient, high-quality training featuring monthly 45-min sessions, autonomous enrollment, multidisciplinary mentoring, and the use of clinical practice guidelines. Autonomy and flexible formats may increase PCPs' participation, and a modular, interdisciplinary and demand-driven approach is needed to optimize prescribing competencies in multimorbidity care.