In Journal of the American Board of Family Medicine : JABFM
PURPOSE : To understand staff and health care providers' views on potential use of artificial intelligence (AI)-driven tools to help care for patients within a primary care setting.
METHODS : We conducted a qualitative descriptive study using individual semistructured interviews. As part of province-wide Learning Health Organization, Community Health Centres (CHCs) are a community-governed, team-based delivery model providing primary care for people who experience marginalization in Ontario, Canada. CHC health care providers and staff were invited to participate. Interviews were audio-recorded and transcribed verbatim. We performed a thematic analysis using a team approach.
RESULTS : We interviewed 27 participants across 6 CHCs. Participants lacked in-depth knowledge about AI. Trust was essential to acceptance of AI; people need to be receptive to using AI and feel confident that the information is accurate. We identified internal influences of AI acceptance, including ease of use and complementing clinical judgment rather than replacing it. External influences included privacy, liability, and financial considerations. Participants felt AI could improve patient care and help prevent burnout for providers; however, there were concerns about the impact on the patient-provider relationship.
CONCLUSIONS : The information gained in this study can be used for future research, development, and integration of AI technology.
Nash Danielle M, Thorpe Cathy, Brown Judith Belle, Kueper Jacqueline K, Rayner Jennifer, Lizotte Daniel J, Terry Amanda L, Zwarenstein Merrick
Artificial Intelligence, Canada, Family Medicine, Informatics, Qualitative Research