BMIR Research Colloquium Webinar: Toward a National Strategy for Implementing Artificial Intelligence and Machine Learning in Primary Care - Steven Lin, MD

 RESEARCH COLLOQUIUM

“Toward a National Strategy for Implementing Artificial Intelligence and Machine Learning in Primary Care”

Stevin Lin, MD
Clinical Associate Professor
Medicine - Primary Care and Population Health
Stanford Health Care

Thursday, February 10^th, 2022 12:00 to 1:00 pm

Due to the recent COVID surge this event will be virtual.

Livestream: https://stanford.zoom.us/j/91316729197?pwd=RWJ6dnJOYU5vUzdKbXdHRHdDVVNXZz09

Webinar Passcode: 403428 

Abstract:

Research in artificial intelligence and machine learning (AI/ML) in healthcare is accelerating at a breathtaking pace. As the largest care delivery platform in the United States, primary care is where the power, opportunity, and future of AI/ML are most likely to be realized in the broadest and most ambitious scale. However, even though 52% of all healthcare visits take place in primary care, only 14% of AI/ML research papers includes a primary care author, and just 1% of federally funded research is in primary care. Ensuring that healthcare AI/ML works for (and not against) the interests, values, and core functions of primary care requires more engagement from primary care researchers, as well as significant infrastructure upgrades to support AI/ML research in primary care. This vision could be advanced by establishing a national research strategy for primary care AI/ML, toward which early proposals are being developed but none adopted. Drawing inspiration from the National Academies’ “Implementing High-Quality Primary Care – Rebuilding the Foundation of Health Care” 2021 report, a framework for such a strategy is presented. It includes five pillars: (1) Automate data collection systems; (2) Optimize/federate data architecture; (3) Sensemake data for actionable care; (4) Plan-do-study-act implementations; and (5) Remedy unintended consequences. Examples of primary care AI/ML research are explored. Primary care can (and should) play a leading role in healthcare AI/ML research in support of patients, clinicians, and the health of the nation.

Learning Objectives

At the end of this session, participants will be able to:

1. Explain the current barriers preventing primary care from playing a larger role in healthcare AI/ML research
2. Describe the recipe for a national strategy to advance primary care AI/ML research and implementation
3. Identify contemporary examples of primary care AI/ML research

Biosketch

Dr. Steven Lin is the Founder and Executive Director of the Stanford Healthcare AI Applied Research Team (HEA₃RT). He is a practicing clinician, educator, researcher, and health system leader in the specialty of family medicine. Dr. Lin earned his MD from Stanford University School of Medicine and completed his training at Stanford’s family medicine residency program. He has received numerous national awards and is recognized among the top family physicians in the US.

Dr. Lin is the Family Medicine Service Chief and the Head of Technology Innovation for the Division of Primary Care and Population Health at Stanford Medicine. His focus is on the intersection of care delivery innovation, digital health, and emerging technologies, specifically artificial intelligence and machine learning in healthcare. Dr. Lin is the James C. Puffer/American Board of Family Medicine Fellow at the National Academy of Medicine. He is the author of over 300 scholarly publications and conference presentations.