The Problem
Graduate Medical Education struggles to deliver high-quality formative feedback due to time constraints, inconsistent structure, and faculty discomfort. Existing interventions have limited success. This project addresses the persistent gap between feedback theory and practice, aiming to improve both trainee development and faculty feedback skills in competency-based medical education.
Our Solution
The project develops an LLM-based tool that transcribes faculty-trainee feedback conversations, analyzes them against ACGME competencies, and generates two reports: one for trainees summarizing feedback by competency, and one for faculty evaluating feedback quality and offering improvement suggestions. It is implemented and assessed using mixed-methods and the RE-AIM framework.
Anticipated Impact
This AI-enabled approach enhances feedback quality, supports lifelong learning, and improves faculty development. It reduces documentation burden, fosters reflective practice, and strengthens competency-based assessment. The tool offers a scalable, sustainable solution that bridges theory and practice, contributing to innovation in medical education and advancing assessment in health professions.
