Winners of the AMA’s new Transforming Lifelong Learning Through Precision Education grant program plan to harness and make sense of big data and apply augmented intelligence (AI) to provide medical students and residents in training, as well as practicing physicians, with individualized learning pathways in medical education.
Data and AI will enable precision education systems to identify and respond to the unique needs of each learner, improving training by enhancing personalization, increasing efficiency, and empowering the learner. Precision education systems provide valuable real-time feedback, helping learners stay engaged and progress at an optimal pace.
“Technology and AI have the potential to reshape the way physicians learn, practice, and care for their patients, and these grants will help realize that potential,” AMA CEO John Whyte, MD, MPH, said in a statement. “As new tools emerge, we have an opportunity to create 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 collectively awarded $1.1 million in grants to 11 institutions engaging more than 80 collaborating partner organizations. The investment builds on more than a decade of leadership from the AMA through its ChangeMedEd® initiative, which has provided nearly $50 million in funding to transform medical education across the continuum.
“We purposefully curated a rich mix of projects, spanning all levels of learners, multiple clinical disciplines, and applying a variety of technology approaches,” said Kimberly D. Lomis, MD, AMA vice president for innovations in medical education.
Teams will explore technical challenges related to data: the security and protections they will need to create, and how to monitor errors and biases in data sets. Many grants are multi-institutional and several examine the performance of an entire specialty, meaning they will address the challenges and benefits of sharing data across sites.
Several projects will use ambient AI technology in creative ways to enhance learning from clinical encounters. By capturing interactions with patients, trainees and doctors will receive feedback and coaching on their performance to improve skills such as communication and clinical reasoning, Dr. Lomis said. Other teams are creating on-demand tools to practice essential skills like communication.
“We’re going to learn more about the technology, but also about the qualities of the physician or trainee who responds well to this type of data-driven approach,” Dr. Lomis emphasized.
From AI implementation to digital health adoption and EHR usability, the AMA fights to make technology work for the benefit of physicians, ensuring it is an asset to physicians. This includes the recent launch of the AMA Center for Digital Health and AI, to give physicians a powerful voice in determining how AI and other digital tools are leveraged to improve the patient and clinician experience.
Catalyzing change in medical education
The AMA’s $12 million Precision Teaching Grant Program awards funding to institutions pursuing innovative applications of precision teaching principles in medical schools, medical residency programs, and continuing medical education.
Winners will use these funds, spread over four years, to transform learning systems and assess and elevate the skills most important to serving patients.
Sanjay Desai, MD, MACPis the academic director of the AMA. He and his colleagues conceived the idea for the awards following the conclusion of the AMA Reimagining Residency grant program.
“We met with visionaries from across the country to understand how best to catalyze change for the future we aspire to in medical education,” said Dr. Desai.
Stakeholders realized that the rapid evolution of technology provided a unique opportunity to address legacy challenges in medical education.
“Specifically, we can develop tools that leverage data and technology, including AI, to personalize education, increase learner agency, and reduce unnecessary friction within the system. We believe these new precision education systems are the future of lifelong learning,” he said.
Here’s how the 11 winners plan to leverage data and AI.
University of Cincinnati School of Medicine: Grantees will use ambient data capture technology to provide feedback through ongoing, personalized assessment of clinical reasoning and communication skills. They will develop AI algorithms for providing feedback, test the technology’s usefulness with approximately 600 trainees across two sites, and move from simulation to authentic patient encounters. A subset of participants will test the feasibility of heads-up displays to provide information during meetings.
University of Illinois College of Medicine: This team brings together multiple collaborating organizations to develop, scale, and evaluate the UME-GME AI-driven precision learning system. They will leverage big data to identify assessments from each participating school that are most aligned with initial GME performance, which will then inform automated, personalized, and accurate feedback and facilitate the setting of learner goals for each medical student, thereby improving 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 supports the medical student, resident, or fellow as they engage in patient care. 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 to 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 improving learner engagement, goal setting and teacher coaching using AI insights and real-time data.
Mount Sinai Morningside/West: This institution offers a precision education system in an outpatient setting that leverages ambient listening and natural language processing to provide personalized, two-way feedback. Residents will receive feedback on communication skills related to EHR-derived patient outcomes. Teachers will receive feedback on teaching effectiveness.
University of Pennsylvania Perelman School of Medicine: 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 in clinical settings. It will provide learners with authentic, contextualized feedback to guide skill advancement 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 teaching strategies help identify and address educational gaps for all students, regardless of their learning profiles and backgrounds.
University of Michigan: This project will leverage the Perioperative Outcomes Group’s multicenter registry and precision analysis of 36 anesthesia programs to create an interactive dashboard that provides a visual narrative of each resident’s training to develop 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 aims to improve vascular surgery training programs by generating comprehensive profiles of graduate performance early in their careers. 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 and scalable sensor technology approach in collaboration with the American Board of Surgery and the American Board of Medical Specialties. The technology will allow faculty to quantitatively define skills and mastery of clinical procedures at a level of detail that is not possible with human observation alone and provide data-driven coaching.
