Awardees in the AMA’s new Transforming Lifelong Learning Through Precision Education Grant Program plan to leverage and make sense of big data and apply augmented intelligence (AI) to give medical students and residents in training, as well as practicing physicians, individualized learning pathways in medical education.
Data and AI will enable precision education systems to identify and address the unique needs of each learner, improving training by boosting personalization, increasing efficiency and giving agency to the learner. Precision education systems provide valuable feedback in real time, helping learners stay engaged and progress at an optimal rate.
“Technology and AI have the potential to reshape how physicians learn, practice, and care for their patients, and these grants will help bring that potential to life,” AMA CEO John Whyte, MD, MPH, said in a statement. “As new tools emerge, we have an opportunity to build learning environments that are more engaging, more adaptable, and better aligned with the realities of practicing medicine. Our goal is to ensure that innovation strengthens the physician experience and creates a future where every physician is fully equipped to meet the needs of patients.”
The AMA has collectively awarded $1.1 million in grants to 11 institutions engaging over 80 collaborating partner organizations. The investment builds on more than a decade of AMA leadership through its ChangeMedEd® Initiative, which has provided nearly $50 million in funding to transform medical education across the continuum.
“We deliberately curated a rich mix of projects, spanning all levels of learners, multiple clinical disciplines and applying a variety of technological approaches, said Kimberly D. Lomis, MD, the AMA’s vice president for medical education innovations.
Teams will be exploring technical challenges around data—the security and protections they will need to create, and how to monitor for error and bias in datasets. Many of the grants are multi-institutional, and several are looking at performance across an entire specialty, meaning they’ll be addressing the challenges and benefits of sharing data across sites.
Several projects will use AI ambient technology in creative ways to enhance learning from clinical encounters. By capturing interactions with patients, trainees and physicians will get feedback and coaching about their performance to improve skills such as communication and clinical reasoning, said Dr. Lomis. Other teams are creating on-demand tools to practice critical skills such as communication.
“We’re going to learn not only about the technology, but about the attributes of the physician or trainee who responds well to this kind of data-driven approach,” noted Dr. Lomis.
From AI implementation to digital health adoption and EHR usability, the AMA is fighting to make technology work for physicians, ensuring that it is an asset to doctors. That includes recently launching the AMA Center for Digital Health and AI to give physicians a powerful voice in shaping how AI and other digital tools are harnessed to improve the patient and clinician experience.
Catalyzing change in med ed
The AMA’s $12 million precision education grant program awards funds to institutions pursuing innovative applications of precision education principles in medical school, medical residency programs and continuing medical education.
Awardees will use these funds, distributed over four years, to transform learning systems and assess and elevate competencies that matter most in serving patients.
Sanjay Desai, MD, MACP, is the AMA's chief academic officer. He and his colleagues conceived the idea for the awards following the conclusion of AMA Reimagining Residency grant program.
“We met with visionaries across industries in the country to understand how best to catalyze change for the future we aspire in medical education,” Dr. Desai said.
Stakeholders realized that rapidly accelerating inflection in technology offered a unique opportunity to address legacy challenges in medical education.
“Specifically, we can develop tools leveraging data and technology, including AI, to personalize education, increase learner agency, and reduce unnecessary friction in the system. We believe these new systems of precision education are the future of lifelong learning,” he said.
Here is how the 11 awardees plan to leverage data and AI.
University of Cincinnati College of Medicine: The grantees will use ambient data-capture technology to provide feedback through a continuous, personalized assessment of clinical reasoning and communication skills. They will develop AI algorithms for feedback delivery, test the tech’s usefulness across approximately 600 trainees at two sites, and scale from simulation to authentic patient encounters. A subset of the participants will test the feasibility of heads-up display to deliver insights during encounters.
University of Illinois College of Medicine: This team brings together multiple collaborating organizations to develop, scale and evaluate the AI-Based Precision Learning UME-GME System. They will leverage big data to identify which assessments at each participating school are most aligned with early performance in GME, which will then inform automated personalized, precision feedback and facilitate learner goal setting for individual medical students, enhancing learner preparation and successful transitions to residency.
Louisiana State University Health Sciences Center: The Compassion in Motion project is a virtual communication learning tool that travels with the medical student, resident, or fellow as they engage in patient caring. The app consists of an AI-generated communication coach and a cast of virtual patient characters, tailored to the immediate needs of the learner.
University of Hawaii John A. Burns School of Medicine: To address Hawaii’s physician shortage and improve health outcomes for its most underserved populations, this project will develop an AI-enhanced, culturally responsive precision education and precision coaching program to train medical students for practice in rural communities.
Georgia Academy of Family Physicians: This initiative will implement a data-integrated residency navigation tool across 12 family medicine residency programs in Georgia, linking EHR-derived clinical performance and quality measures to inform structured, learner co-developed individualized learning plans. The project will advance precision education by enhancing learner engagement, goal setting, and faculty coaching utilizing AI insights and real time data.
Mount Sinai Morningside/West: This institution proposes a precision education system in the outpatient setting that leverages ambient listening and natural language processing to deliver personalized, bidirectional feedback. Residents will receive feedback around communication skills linked to EHR-derived patient outcomes. Faculty will be provided with insights about teaching effectiveness.
Perelman School of Medicine at the University of Pennsylvania: The Clinical Reasoning Insights for Shaping Performance project combines ambient listening with EHR data to assess reasoning as it happens: in individual decisions, team interactions, and across clinical settings. It will provide learners with authentic, contextualized feedback to guide advancing skills over time.
Meritus School of Osteopathic Medicine: This new medical school will create an integrated data platform to support learning. The project will evaluate how specific precision education strategies aid in the identification and remediation of educational gaps for all its students, across diverse learning profiles and backgrounds.
University of Michigan: This project will leverage the Multicenter Perioperative Outcomes Group registry and precision analytics across 36 anesthesia programs to create an interactive dashboard that provides a visual narrative of each resident’s training to build master adaptive learning skills and support appropriate progressive autonomy through digital prompts and data-enhanced coaching.
University of Wisconsin School of Medicine and Public Health: This multi-institutional project is focused on enhancing vascular surgery training programs by generating comprehensive profiles of graduates’ early career performance. The team will map patient outcomes and performance gaps among graduates against training program characteristics and assessment practices to inform programmatic improvements.
Stanford University: The team at Stanford’s Technology Enabled Clinical Improvement Center will expand its mobile, scalable sensor technology approach in collaboration with the American Board of Surgery and the American Board of Medical Specialties. The technology will enable faculty to quantitatively define competency and mastery in clinical procedural skill at a level of detail that is not possible with human observation alone and provide data-driven coaching.
