Preparing future physicians for drug-related clinical decisions: a pedagogical approach to clinical decision support systems training

Digital medical databases are essential for evidence-based clinical decision-making, yet their adoption is hindered by multitasking demands, time constraints, and knowledge gaps. This study evaluates the integration of Clinical Decision Support Systems (CDSS) into medical curricula as a structured approach to developing digital competencies, critical appraisal skills, and clinical reasoning. A quasi-experimental study was conducted across four student cohorts ( n = 112) in an elective course. Students in the intervention group received structured CDSS training during their final preclinical semester, while untrained peers served as a comparison group for follow-up during their clinical years. The course incorporated case-based learning with CDSS tools, requiring students to complete assignments on drug mechanisms, interactions, and guideline-based recommendations. Physicians provided additional insights into CDSS use in clinical practice. Attitudes, confidence, and CDSS utilization were assessed using validated surveys before, during, and after the course, with longitudinal follow-up extending into clinical rotations for up to several years. Both physicians and medical students in clinical rotations strongly supported integrating CDSS education into medical curricula. Despite frequent CDSS use, 91% of untrained students reported low confidence in utilizing these tools, highlighting a critical gap in formal training. Post-course assessments revealed significant improvements in confidence and competence, with trained students demonstrating a sustained shift from general search engines to validated medical databases. Longitudinal follow-up confirmed that trained students relied more consistently on evidence-based resources during clinical practice compared to their untrained peers. Structured CDSS training in medical education enhances digital literacy, critical appraisal, and evidence-based decision-making, addressing a key gap in preclinical training. These findings support the integration of technology-driven curricula to better prepare future clinicians for data-driven healthcare. Beyond medical education, this model has the potential for broader implementation across health professions, fostering interdisciplinary adoption of digital decision-support tools to meet the evolving demands of modern medicine. ISRCTN12503667, registered 24/06/2026. Retrospectively registered.