• Jacqueline K Kueper, Mahzabeen Emu, Mark Banbury, Lise M Bjerre, Salimur Choudhury, Michael Green, Nicholas Pimlott, Steve Slade, Sian H Tsuei, and Jeff Sisler.
• Adjunct Research Professor in the Department of Epidemiology and Biostatistics in the Schulich School of Medicine and Dentistry at Western University in London, Ont.
• Can Fam Physician. 2024 Mar 1; 70 (3): 161168161-168.

ObjectiveTo understand the current landscape of artificial intelligence (AI) for family medicine (FM) research in Canada, identify how the College of Family Physicians of Canada (CFPC) could support near-term positive progress in this field, and strengthen the community working in this field.Composition Of The CommitteeMembers of a scientific planning committee provided guidance alongside members of a CFPC staff advisory committee, led by the CFPC-AMS TechForward Fellow and including CFPC, FM, and AI leaders.MethodsThis initiative included 2 projects. First, an environmental scan of published and gray literature on AI for FM produced between 2018 and 2022 was completed. Second, an invitational round table held in April 2022 brought together AI and FM experts and leaders to discuss priorities and to create a strategy for the future.ReportThe environmental scan identified research related to 5 major domains of application in FM (preventive care and risk profiling, physician decision support, operational efficiencies, patient self-management, and population health). Although there had been little testing or evaluation of AI-based tools in practice settings, progress since previous reviews has been made in engaging stakeholders to identify key considerations about AI for FM and opportunities in the field. The round-table discussions further emphasized barriers to and facilitators of high-quality research; they also indicated that while there is immense potential for AI to benefit FM practice, the current research trajectory needs to change, and greater support is needed to achieve these expected benefits and to avoid harm.ConclusionTen candidate action items that the CFPC could adopt to support near-term positive progress in the field were identified, some of which an AI working group has begun pursuing. Candidate action items are roughly divided into avenues where the CFPC is well-suited to take a leadership role in tackling priority issues in AI for FM research and specific activities or initiatives the CFPC could complete. Strong FM leadership is needed to advance AI research that will contribute to positive transformation in FM.Copyright © 2024 the College of Family Physicians of Canada.

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