In Journal of the American Board of Family Medicine : JABFM
BACKGROUND : Artificial intelligence (AI) implementation in primary care is limited. Those set to be most impacted by AI technology in this setting should guide it's application. We organized a national deliberative dialogue with primary care stakeholders from across Canada to explore how they thought AI should be applied in primary care.
METHODS : We conducted 12 virtual deliberative dialogues with participants from 8 Canadian provinces to identify shared priorities for applying AI in primary care. Dialogue data were thematically analyzed using interpretive description approaches.
RESULTS : Participants thought that AI should first be applied to documentation, practice operations, and triage tasks, in hopes of improving efficiency while maintaining person-centered delivery, relationships, and access. They viewed complex AI-driven clinical decision support and proactive care tools as impactful but recognized potential risks. Appropriate training and implementation support were the most important external enablers of safe, effective, and patient-centered use of AI in primary care settings.
INTERPRETATION : Our findings offer an agenda for the future application of AI in primary care grounded in the shared values of patients and providers. We propose that, from conception, AI developers work with primary care stakeholders as codesign partners, developing tools that respond to shared priorities.
Upshaw Tara L, Craig-Neil Amy, Macklin Jillian, Gray Carolyn Steele, Chan Timothy C Y, Gibson Jennifer, Pinto Andrew D
2023-Mar-22
Artificial Intelligence, Canada, Family Medicine, Qualitative Research
