Precision Medical Education

• Published in: Academic medicine Vol. 98; no. 7; pp. 775 - 781
• Main Authors: Triola, Marc M., Burk-Rafel, Jesse
• Format: Journal Article
• Language: English
• Published: United States Lippincott Williams & Wilkins 01-07-2023
• Subjects: Artificial Intelligence; Clinical Competence; Curriculum; Education, Medical; Humans; Internship and Residency; Learning
• ISSN: 1040-2446; 1938-808X
• DOI: 10.1097/ACM.0000000000005227

Medical schools and residency programs are increasingly incorporating personalization of content, pathways, and assessments to align with a competency-based model. Yet, such efforts face challenges involving large amounts of data, sometimes struggling to deliver insights in a timely fashion for trainees, coaches, and programs. In this article, the authors argue that the emerging paradigm of precision medical education (PME) may ameliorate some of these challenges. However, PME lacks a widely accepted definition and a shared model of guiding principles and capacities, limiting widespread adoption. The authors propose defining PME as a systematic approach that integrates longitudinal data and analytics to drive precise educational interventions that address each individual learner’s needs and goals in a continuous, timely, and cyclical fashion, ultimately improving meaningful educational, clinical, or system outcomes. Borrowing from precision medicine, they offer an adapted shared framework. In the P4 medical education framework, PME should (1) take a
proactive
approach to acquiring and using trainee data; (2) generate timely
personalized
insights through precision analytics (including artificial intelligence and decision-support tools); (3) design precision educational interventions (learning, assessment, coaching, pathways) in a
participatory
fashion, with trainees at the center as co-producers; and (4) ensure interventions are
predictive
of meaningful educational, professional, or clinical outcomes. Implementing PME will require new foundational capacitiesflexible educational pathways and programs responsive to PME-guided dynamic and competency-based progression; comprehensive longitudinal data on trainees linked to educational and clinical outcomes; shared development of requisite technologies and analytics to effect educational decision-making; and a culture that embraces a precision approach, with research to gather validity evidence for this approach and development efforts targeting new skills needed by learners, coaches, and educational leaders. Anticipating pitfalls in the use of this approach will be important, as will ensuring it deepens, rather than replaces, the interaction of trainees and their coaches.