Developing an AI Tool to Derive Social Determinants of Health for Primary Care Patients: Qualitative Findings From a Codesign Workshop.

Journal: Annals of family medicine
PMID: 39038983

Abstract

PURPOSE: Information about social determinants of health (SDOH) is essential for primary care clinicians in the delivery of equitable, comprehensive care, as well as for program planning and resource allocation. SDOH are rarely captured consistently in clinical settings, however. Artificial intelligence (AI) could potentially fill these data gaps, but it needs to be designed collaboratively and thoughtfully. We report on a codesign process with primary care clinicians to understand how an AI tool could be developed, implemented, and used in practice.

Authors

  • Stephanie Garies
    Postdoctoral fellow (at the time of writing) affiliated with the Department of Family and Community Medicine through St Michael's Hospital at Unity Health Toronto in Ontario, and with the Upstream Lab in the MAP Centre for Urban Health Solutions.
  • Simon Liang
    Family medicine resident (at the time of writing) in Department of Family & Community Medicine at St Michael's Hospital through Unity Health Toronto.
  • Karen Weyman
    Associate Professor in the Department of Family & Community Medicine at the University of Toronto in Ontario and a family physician at St Michael's Hospital.
  • Noor Ramji
    Family physician and Practice Improvement Program Director in the Department of Family and Community Medicine at the University of Toronto.
  • Mo Alhaj
    Quality Improvement Specialist at St Michael's Hospital.
  • Andrew D Pinto
    Upstream Lab, MAP/Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Canada.

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