Integrating Bayesian reasoning into medical education using smartphone apps

Abstract

Diagnostic reasoning is an important topic in medical education, and diagnostic errors are increasingly recognized as large contributors to patient morbidity and mortality. One way to improve learner understanding of the diagnostic process is to teach the concepts of Bayesian reasoning and to make these concepts practical for clinical use. Many clinician educators do not fully understand Bayesian concepts and they lack the tools to incorporate Bayesian reasoning into clinical practice and teaching. The authors developed an interactive workshop using visual models of probabilities and thresholds, clinical cases, and available smartphone apps to teach learners about Bayesian concepts. Evaluations from 3 years of workshops at a national internal medicine chief resident conference showed high satisfaction, with narrative comments suggesting learners found the visual and smartphone tools useful for applying the concepts with future learners. Visual models, clinical cases, and smartphone apps were well received by chief residents as a way to learn and teach Bayesian reasoning. Further study will be needed to understand if these tools can improve diagnostic accuracy or patient outcomes.