RESUMEN
Context: The effective deployment of artificial intelligence (AI) in primary health care requires a match between the AI tools that are being developed and the needs of primary health care practitioners and patients. Currently, the majority of AI development targeted toward potential application in primary care is being conducted without the involvement of these stakeholders. Objective: To identify key issues regarding the use of AI tools in primary health care by exploring the views of primary health care and digital health stakeholders. Study Design: A descriptive qualitative approach was taken in this study. Fourteen in-depth interviews were conducted with primary care and digital health stakeholders. Setting: Province of Ontario, Canada Population studied: Primary health care and digital health stakeholders Outcome Measures: N/A Results: Two main themes emerged from the data analysis: Worth the Risk as Long as You Do It Well; and, Mismatch Between Envisioned Uses and Current Reality. Participants noted that AI could have value if used for specific purposes, for example: supporting care for patients; reducing practitioner burden; analyzing existing evidence; managing patient populations; and, supporting operational efficiencies. Participants identified facilitators of AI being used for these purposes including: use of relevant case studies/success stories with realistic uses of AI highlighted; easy or low risk applications; and, end user involvement. However, barriers to the use of AI included: data quality; digital divide/equity; distrust of AI including security/privacy issues; for-profit motives; need for transparency about how AI works; and, fear about impact on practitioners regarding clinical judgement. Conclusion: AI will continue to become more prominent in primary health care. There is potential for positive impact, however there are many factors that need to be considered regarding the implementation of AI. The findings of this study can help to inform the development and deployment of AI tools in primary health care.
RESUMEN
CONTEXT: Artificial intelligence (AI) is increasingly being recognized as having potential importance to primary care (PC). However, there is a gap in our understanding about where to focus efforts related to AI for PC settings, especially given the current COVID-19 pandemic. OBJECTIVE: To identify current priority areas for AI and PC in Ontario, Canada. STUDY DESIGN: Multi-stakeholder engagement event with facilitated small and large group discussions. A nominal group technique process was used to identify and rank challenges in PC that AI may be able to support. Mentimeter software was used to allow real-time, anonymous and independent ranking from all participants. A final list of priority areas for AI and PC, with key considerations, was derived based on ranked items and small group discussion notes. SETTING: Ontario, Canada. POPULATION STUDIED: Digital health and PC stakeholders. OUTCOME MEASURES: N/A. RESULTS: The event included 8 providers, 8 patient advisors, 4 decision makers, 3 digital health stakeholders, and 12 researchers. Nine priority areas for AI and PC were identified and ranked, which can be grouped into those intended to support physician (preventative care and risk profiling, clinical decision support, routine task support), patient (self-management of conditions, increased mental health care capacity and support), or system-level initiatives (administrative staff support, management and synthesis of information sources); and foundational areas that would support work on other priorities (improved communication between PC and AI stakeholders, data sharing and interoperability between providers). Small group discussions identified barriers and facilitators related to the priorities, including data availability, quality, and consent; legal and device certification issues; trust between people and technology; equity and the digital divide; patient centredness and user-centred design; and the need for funding to support collaborative research and pilot testing. Although identified areas do not explicitly mention COVID-19, participants were encouraged to think about what would be feasible and meaningful to accomplish within a few years, including considerations of the COVID-19 pandemic and recovery phases. CONCLUSIONS: A one-day multi-stakeholder event identified priority areas for AI and PC in Ontario. These priorities can serve as guideposts to focus near-term efforts on the planning, development, and evaluation of AI for PC.