STFM PODCAST - Academic Medicine Leadership Lessons podcast

Bonus Conference Episode: Aims before Algorithms: A Problem-Driven Approach to AI with Amelia Sattler, MD

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Conference on Practice & Quality Improvement Second Plenary Session - Tuesday, September 1, 2026

Artificial intelligence (AI) is transforming clinical care, medical education, and research. While AI has significant potential, meaningful integration remains challenging. When AI-powered tools are developed in technology silos without close collaboration with key stakeholders, real-world impact is limited. Even the most powerful AI tools lack practical value if they aren’t conceptualized, designed and integrated to address clearly defined and meaningful problems. These challenges highlight the need for a problem-driven approach to AI development and adoption.

This session presents a practical framework for advancing AI initiatives grounded in quality improvement (QI) principles. Drawing on Dr. Sattler’s experience as a clinician and improvement-focused innovator, the session uses examples across clinical care, education and research to illustrate how AI can be applied to address real-world challenges. Emphasis is placed on identifying meaningful problems as the necessary starting point for exploring AI-enabled solutions and using iterative, small-scale testing to evaluate their impact.

This session also highlights the importance of collaboration among key stakeholders and technology developers to ensure that AI tools are responsive to real-world needs. Participants are encouraged to view themselves not as passive users of AI, but as active contributors to its thoughtful development and implementation. The session also addresses potential benefits, limitations, and risks of AI use. 

Learning Objectives:

Upon completion of this session, participants should be able to:

  • Describe practical examples for meaningfully integrating AI into clinical practice, education and research.
  • Apply a quality improvement-informed, problem-driven approach to advance a personal AI goal.
  • Evaluate potential benefits, limitations and risks of AI use.

Copyright © Society of Teachers of Family Medicine, 2026

Speaker Bio - 

Amelia Sattler, MD, is a family physician and problem-solver. Her medical training began while seated around the dinner table in rural northern California where, as a child, she was inspired by the joy that her parents experienced working as family practitioners. She ventured to Mayo Medical School in Rochester, MN, where she was “raised” in a culture of medicine that prioritizes the needs of patients. She returned to California to train at Stanford's O'Connor Family Medicine Residency Program. After residency she joined Stanford Family Medicine, where she continues to see patients.

Dr Sattler holds three leadership roles. She is an associate program director of the Stanford Healthcare AI Applied Research Team ("HEART") and works with teams to study and implement AI technologies to solve specific, practical problems in healthcare. She is the primary care program director of integrated behavioral health and is partnering with psychiatry, social work and primary care teams to build a collaborative care model at Stanford Primary Care. She is also the associate section chief for program innovation in the Division of Primary Care and Population Health where she collaborates with providers and operational leadership to amplify the impact of their 30+ innovative primary care programs. 

Website - 

https://stfm.org/stfmpodcastCPQI26second 


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