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

التفاصيل البيبلوغرافية
العنوان: Connecting Artificial Intelligence and Primary Care Challenges: Findings from a Multi-Stakeholder Collaborative Consultation
المؤلفون: Ron Beleno, Daniel Leger, Bridget L. Ryan, Scott McKay, Janet Dang, Merrick Zwarenstein, Amanda L. Terry, Ravninder Bahniwal, Jacqueline K. Kueper, Leslie Meredith, Judith Belle Brown, Daniel J. Lizotte
بيانات النشر: Cold Spring Harbor Laboratory, 2021.
سنة النشر: 2021
مصطلحات موضوعية: Data sharing, Computer science, business.industry, Interoperability, Nominal group technique, Equity (finance), Artificial intelligence, Digital divide, Location, business, Clinical decision support system, Session (web analytics)
الوصف: Despite widespread advancements in and envisioned uses for artificial intelligence (AI), few examples of successfully implemented AI innovations exist in primary care (PC) settings.ObjectivesTo identify priority areas for AI and PC in Ontario, Canada.MethodsA 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.ResultsThe 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.DiscussionFindings 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.ConclusionStudy findings can be used to inform future research and development of AI for PC, and to guide resource planning and allocation.SUMMARYWhat 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.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::d7771c44c683d340ab9d1afad71b5edc
https://doi.org/10.1101/2021.09.21.21263906
حقوق: OPEN
رقم الأكسشن: edsair.doi...........d7771c44c683d340ab9d1afad71b5edc
قاعدة البيانات: OpenAIRE