Connecting Artificial Intelligence and Primary Care Challenges: Findings from a Multi-Stakeholder Collaborative Consultation

Abstract

ABSTRACT Despite widespread advancements in and envisioned uses for artificial intelligence (AI), few examples of successfully implemented AI innovations exist in primary care (PC) settings. Objectives To identify priority areas for AI and PC in Ontario, Canada. Methods A collaborative consultation event engaged multiple stakeholders in a nominal group technique process to generate, discuss, and rank ideas for how AI can support Ontario PC. Results The consultation process produced nine ranked priorities: 1) preventative care and risk profiling, 2) patient self-management of condition(s), 3) management and synthesis of information, 4) improved communication between PC and AI stakeholders, 5) data sharing and interoperability, 6-tie) clinical decision support, 6-tie) administrative staff support, 8) practitioner clerical and routine task support, and 9) increased mental health care capacity and support. Themes emerging from small group discussions about barriers, implementation issues, and resources needed to support the priorities included: equity and the digital divide; system capacity and culture; data availability and quality; legal and ethical issues; user-centered design; patient-centredness; and proper evaluation of AI-driven tool implementation. Discussion Findings provide guidance for future work on AI and PC. There are immediate opportunities to use existing resources to develop and test AI for priority areas at the patient, provider, and system level. For larger-scale, sustainable innovations, there is a need for longer-term projects that lay foundations around data and interdisciplinary work. Conclusion Study findings can be used to inform future research and development of AI for PC, and to guide resource planning and allocation. SUMMARY What is already known? – The field of artificial intelligence and primary care is underdeveloped. What does this paper add? – An environmental scan without geographic location restriction identified 110 artificial intelligence-driven tools with potential relevance to primary care that existed around the time of the study. – A multi-stakeholder consultation session identified nine priorities to guide future work on artificial intelligence and primary care in Ontario, Canada. – Priorities for artificial intelligence and primary care include provider, patient, and system level uses as well as foundational areas related to data and interdisciplinary communication.

Ähnliche Arbeiten