This study aimed to (1) explore clinicians’ perspectives of cardiovascular disease (CVD) and risk management in female patients and (2) describe clinicians’ needs and desired features in AI-enabled tools for primary prevention and management of CVD among female patients. This work employed a qualitative description design. We conducted semi-structured interviews with 12 clinicians in Montreal, Canada. We used inductive thematic analysis to interpret the data. Seven themes emerged from the analysis. Three themes were related to the first objective: complexity in clinical decision-making, limitations of CVD risk assessment tools, and resources and health literacy. Four themes were related to the second objective: AI efficiency, multilingual design, electronic medical record integration, and ease of use. Clinicians reported challenges in supporting female patients at higher risk for CVD and expressed concerns about existing decision support tools. They showed openness to AI-enabled tools like Xi-Care and provided input on desired features to ensure their usability and effectiveness. There is a demand to support clinicians in the primary prevention and management of CVD among female patients. AI-enabled tools could effectively address this demand, provided their development prioritizes clinicians' needs and perspectives to ensure safe and effective implementation.
Wang et al. (Thu,) studied this question.