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Abstract: Precision education (PE) uses personalized educational interventions to empower trainees and improve learning outcomes. While PE has the potential to represent a paradigm shift in medical education, a theoretical foundation to guide the effective implementation of PE strategies has not yet been described. Here, the authors introduce a theoretical foundation for the implementation of PE, integrating key learning theories with the digital tools that allow them to be operationalized. Specifically, the authors describe how the master adaptive learner (MAL) model, transformative learning theory, and self-determination theory can be harnessed in conjunction with nudge strategies and audit and feedback dashboards to drive learning and meaningful behavior change. The authors also provide practical examples of these theories and tools in action by describing precision interventions already in use at one academic medical center, concretizing PE's potential in the current clinical environment. These examples illustrate how a firm theoretical grounding allows educators to most effectively tailor PE interventions to fit individual learners' needs and goals, facilitating efficient learning and ultimately improving patient and health system outcomes., (Copyright © 2023 the Association of American Medical Colleges.)

Abstract: The goal of medical education is to produce a physician workforce capable of delivering high-quality equitable care to diverse patient populations and communities. To achieve this aim amidst explosive growth in medical knowledge and increasingly complex medical care, a system of personalized and continuous learning, assessment, and feedback for trainees and practicing physicians is urgently needed. In this perspective, the authors build on prior work to advance a conceptual framework for such a system: precision education (PE).PE is a system that uses data and technology to transform lifelong learning by improving personalization, efficiency, and agency at the individual, program, and organization levels. PE "cycles" start with data inputs proactively gathered from new and existing sources, including assessments, educational activities, electronic medical records, patient care outcomes, and clinical practice patterns. Through technology-enabled analytics , insights are generated to drive precision interventions . At the individual level, such interventions include personalized just-in-time educational programming. Coaching is essential to provide feedback and increase learner participation and personalization. Outcomes are measured using assessment and evaluation of interventions at the individual, program, and organizational levels, with ongoing adjustment for repeated cycles of improvement. PE is rooted in patient, health system, and population data; promotes value-based care and health equity; and generates an adaptive learning culture.The authors suggest fundamental principles for PE, including promoting equity in structures and processes, learner agency, and integration with workflow (harmonization). Finally, the authors explore the immediate need to develop consensus-driven standards: rules of engagement between people, products, and entities that interact in these systems to ensure interoperability, data sharing, replicability, and scale of PE innovations., (Copyright © 2024 the Association of American Medical Colleges.)

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 capacities: flexible 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., (Copyright © 2023 by the Association of American Medical Colleges.)

The transition from medical student to resident is a pivotal step in the medical education continuum. For applicants, successfully obtaining a residency position is the actualization of a dream after years of training and has life-changing professional and financial implications. These high stakes contribute to a residency application and Match process in the United States that is increasingly complex and dysfunctional, and that does not effectively serve applicants, residency programs, or the public good. In July 2020, the Coalition for Physician Accountability (Coalition) formed the Undergraduate Medical Education-Graduate Medical Education Review Committee (UGRC) to critically assess the overall transition to residency and offer recommendations to solve the growing challenges in the system. In this Invited Commentary, the authors reflect on their experience as the trainee representatives on the UGRC. They emphasize the importance of trainee advocacy in medical education change efforts; reflect on opportunities, concerns, and tensions with the final UGRC recommendations (released in August 2021); discuss factors that may constrain implementation; and call for the medical education community-and the Coalition member organizations in particular-to accelerate fully implementing the UGRC recommendations. By seizing the momentum created by the UGRC, the medical education community can create a reimagined transition to residency that reshapes its approach to training a more diverse, competent, and growth-oriented physician workforce., (Copyright © 2022 by the Association of American Medical Colleges.)

Introduction: The role of medical students in catalyzing and leading curricular change in US medical schools is not well described. Here, American Medical Association student and physician leaders in the Accelerating Change in Medical Education initiative use qualitative methods to better define student leadership in curricular change. Methods: The authors developed case studies describing student leadership in curricular change efforts. Case studies were presented at a national medical education workshop; participants provided worksheet reflections and were surveyed, and responses were transcribed. Kotter's change management framework was used to categorize reported student roles in curricular change. Thematic analysis was used to identify barriers to student engagement and activators to overcome these barriers. Results: Student roles spanned all eight steps of Kotter's change management framework. Barriers to student engagement were related to faculty (e.g. view student roles narrowly), students (e.g. fear change or expect faculty-led curricula), or both (e.g. lack leadership training). Activators were: (1) recruiting collaborative faculty, staff, and students; (2) broadening student leadership roles; (3) empowering student leaders; and (4) recognizing student successes. Conclusions: By applying these activators, medical schools can build robust student-faculty partnerships that maximize collaboration, moving students beyond passive educational consumption to change agency and curricular co-creation.

Purpose: Scholarly concentration programs-also known as scholarly projects, pathways, tracks, or pursuits-are increasingly common in U.S. medical schools. However, systematic, data-driven program development methods have not been described., Method: The authors examined scholarly concentration programs at U.S. medical schools that U.S. News & World Report ranked as top 25 for research or primary care (n = 43 institutions), coding concentrations and mission statements. Subsequently, the authors conducted a targeted needs assessment via a student-led, institution-wide survey, eliciting learners' preferences for 10 "Pathways" (i.e., concentrations) and 30 "Topics" (i.e., potential content) augmenting core curricula at their institution. Exploratory factor analysis (EFA) and a capacity optimization algorithm characterized best institutional options for learner-focused Pathway development., Results: The authors identified scholarly concentration programs at 32 of 43 medical schools (74%), comprising 199 distinct concentrations (mean concentrations per program: 6.2, mode: 5, range: 1-16). Thematic analysis identified 10 content domains; most common were "Global/Public Health" (30 institutions; 94%) and "Clinical/Translational Research" (26 institutions; 81%). The institutional needs assessment (n = 468 medical students; response rate 60% overall, 97% among first-year students) demonstrated myriad student preferences for Pathways and Topics. EFA of Topic preferences identified eight factors, systematically related to Pathway preferences, informing content development. Capacity modeling indicated that offering six Pathways could guarantee 95% of first-year students (162/171) their first- or second-choice Pathway., Conclusions: This study demonstrates a generalizable, data-driven approach to scholarly concentration program development that reflects student preferences and institutional strengths, while optimizing program diversity within capacity constraints.