Connecting artificial intelligence and primary care challenges: findings from a multi stakeholder collaborative consultation
العنوان: | Connecting artificial intelligence and primary care challenges: findings from a multi stakeholder collaborative consultation |
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المؤلفون: | Jacqueline K Kueper, Amanda Terry, Ravninder Bahniwal, Leslie Meredith, Ron Beleno, Judith Belle Brown, Janet Dang, Daniel Leger, Scott McKay, Andrew Pinto, Bridget L Ryan, Merrick Zwarenstein, Daniel J Lizotte |
المصدر: | BMJ Health & Care Informatics, Vol 29, Iss 1 (2022) BMJ Health & Care Informatics |
بيانات النشر: | BMJ Publishing Group, 2022. |
سنة النشر: | 2022 |
مصطلحات موضوعية: | Information Dissemination, Computer applications to medicine. Medical informatics, R858-859.7, Health Informatics, Decision Support Systems, Clinical, Computer Science Applications, primary health care, machine learning, Health Information Management, Artificial Intelligence, Humans, Referral and Consultation, Original Research |
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 healthcare 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-centred 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. |
اللغة: | English |
تدمد: | 2632-1009 |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95bdb598758b18c2e161219c2dc46cf0 https://informatics.bmj.com/content/29/1/e100493.full |
حقوق: | OPEN |
رقم الأكسشن: | edsair.doi.dedup.....95bdb598758b18c2e161219c2dc46cf0 |
قاعدة البيانات: | OpenAIRE |
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