Connecting artificial intelligence and primary care challenges: findings from a multi stakeholder collaborative consultation

Ryan, Bridget; Terry, Amanda; Zwarenstein, Merrick; Pinto, Andrew D.; Brown, Judith Belle; Meredith, Leslie; Kueper, Jacqueline K; Bahniwal, Ravninder; Beleno, Ron; Dang, Janet; Leger, Daniel W.; McKay, Scott; Lizotte, Daniel J.

doi:10.1136/bmjhci-2021-100493

Cited by 13 publications

(18 citation statements)

References 15 publications

(24 reference statements)

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“…This enabled us to create and refine a tool which is useful to all groups, for a range of purposes specific to each. While other studies report that an artificial intelligence tool generated concerns, 23 our stakeholders reported no concerns but were unanimously supportive and enthusiastic, citing visualisation functions as its greatest strength. Stakeholders had almost no criticisms of the tool, instead recognising its potential and desiring additional features.…”

Section: Discussionmentioning

confidence: 58%

“…PPPI on health data typically focuses on artificial intelligence, 23 patient portals 24 and decision-making tools 25 and recommend problem solving by understanding the relationship between data capabilities and the role of patients and the public. 23–26 Few involvement activities have focused specifically on providing public-facing data visualisations that are also useful to researchers, data professionals and clinicians. Our work contributes to the literature by consulting with all relevant stakeholder groups and synthesising their contributions.…”

Section: Discussionmentioning

confidence: 99%

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Involving multiple stakeholders in assessing and reviewing a novel data visualisation tool for a national neonatal data asset

Lammons

Moss

Bignell

et al. 2023

BMJ Health Care Inform

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Objectives We involved public and professional stakeholders to assess a novel data interrogation tool, the Neonatal Health Intelligence Tool, for a National Data Asset, the National Neonatal Research Database. Methods We recruited parents, preterm adults, data managers, clinicians, network managers and researchers (trialists and epidemiologists) for consultations demonstrating a prototype tool and semi-structured discussion. A thematic analysis of consultations is reported by stakeholder group. Results We held nine on-line consultations (March–December 2021), with 24 stakeholders: parents (n=8), preterm adults (n=2), data managers (n=3), clinicians (n=3), network managers (n=2), triallists (n=3) and epidemiologists (n=3). We identified four themes from parents/preterm adults: struggling to consume information, Dads and data, bring data to life and yearning for predictions; five themes from data managers/clinicians/network managers: benchmarking, clinical outcomes, transfers and activity, the impact of socioeconomic background and ethnicity, and timeliness of updates and widening availability; and one theme from researchers: interrogating the data. Discussion Other patient and public involvement (PPI) studies have reported that data tools generate concerns; our stakeholders had none. They were unanimously supportive and enthusiastic, citing visualisation as the tool’s greatest strength. Stakeholders had no criticisms; instead, they recognised the tool’s potential and wanted more features. Parents saw the tool as an opportunity to inform themselves without burdening clinicians, while clinicians welcomed an aid to explaining potential outcomes to parents. Conclusion All stakeholder groups recognised the need for the tool, praising its content and format. PPI consultations with all key groups, and their synthesis, illustrated desire for additional uses from it.

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Section: Discussionmentioning

confidence: 58%

Section: Discussionmentioning

confidence: 99%

Involving multiple stakeholders in assessing and reviewing a novel data visualisation tool for a national neonatal data asset

Lammons

Moss

Bignell

et al. 2023

BMJ Health Care Inform

View full text Add to dashboard Cite

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“…7 Before widespread implementation of AI tools, we need to better understand frontline staff and providers' perceptions on using AI to help deliver optimal primary care. A recent scoping review on perceptions about increasing use of AI in health care identified only a few studies within primary care, 12 where some focused on opinions of research and policy stakeholders 13,14 and others used a survey design. 15,16 We conducted this study to inform an agenda for AI research within a province-wide primary care Learning Health Organization in Ontario, Canada.…”

Section: Introductionmentioning

confidence: 99%

Perceptions of Artificial Intelligence Use in Primary Care: A Qualitative Study with Providers and Staff of Ontario Community Health Centres

et al. 2023

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Purpose: To understand staff and health care providers' views on potential use of artificial intelligence (AI)-driven tools to help care for patients within a primary care setting.Methods: We conducted a qualitative descriptive study using individual semistructured interviews. As part of province-wide Learning Health Organization, Community Health Centres (CHCs) are a community-governed, team-based delivery model providing primary care for people who experience marginalization in Ontario, Canada. CHC health care providers and staff were invited to participate. Interviews were audio-recorded and transcribed verbatim. We performed a thematic analysis using a team approach.Results: We interviewed 27 participants across 6 CHCs. Participants lacked in-depth knowledge about AI. Trust was essential to acceptance of AI; people need to be receptive to using AI and feel confident that the information is accurate. We identified internal influences of AI acceptance, including ease of use and complementing clinical judgment rather than replacing it. External influences included privacy, liability, and financial considerations. Participants felt AI could improve patient care and help prevent burnout for providers; however, there were concerns about the impact on the patient-provider relationship.Conclusions: The information gained in this study can be used for future research, development, and integration of AI technology.

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“…This paper reports the findings from one of a series of studies designed to explore these issues [22]. This qualitative study explored the uses of AI in primary health care.…”

Section: Introductionmentioning

confidence: 99%

Is primary health care ready for artificial intelligence? What do primary health care stakeholders say?

Terry

Kueper

Beleno

et al. 2022

BMC Med Inform Decis Mak

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Background Effective deployment of AI tools in primary health care requires the engagement of practitioners in the development and testing of these tools, and a match between the resulting AI tools and clinical/system needs in primary health care. To set the stage for these developments, we must gain a more in-depth understanding of the views of practitioners and decision-makers about the use of AI in primary health care. The objective of this study was 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. Methods This study utilized a descriptive qualitative approach, including thematic data analysis. Fourteen in-depth interviews were conducted with primary health care and digital health stakeholders in Ontario. NVivo software was utilized in the coding of the interviews. Results Five main interconnected themes emerged: (1) Mismatch Between Envisioned Uses and Current Reality—denoting the importance of potential applications of AI in primary health care practice, with a recognition of the current reality characterized by a lack of available tools; (2) Mechanics of AI Don’t Matter: Just Another Tool in the Toolbox– reflecting an interest in what value AI tools could bring to practice, rather than concern with the mechanics of the AI tools themselves; (3) AI in Practice: A Double-Edged Sword—the possible benefits of AI use in primary health care contrasted with fundamental concern about the possible threats posed by AI in terms of clinical skills and capacity, mistakes, and loss of control; (4) The Non-Starters: A Guarded Stance Regarding AI Adoption in Primary Health Care—broader concerns centred on the ethical, legal, and social implications of AI use in primary health care; and (5) Necessary Elements: Facilitators of AI in Primary Health Care—elements required to support the uptake of AI tools, including co-creation, availability and use of high quality data, and the need for evaluation. Conclusion The use of AI in primary health care may have a positive impact, but many factors need to be considered regarding its implementation. This study may help to inform the development and deployment of AI tools in primary health care.

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Connecting artificial intelligence and primary care challenges: findings from a multi stakeholder collaborative consultation

Cited by 13 publications

References 15 publications

Involving multiple stakeholders in assessing and reviewing a novel data visualisation tool for a national neonatal data asset

Involving multiple stakeholders in assessing and reviewing a novel data visualisation tool for a national neonatal data asset

Perceptions of Artificial Intelligence Use in Primary Care: A Qualitative Study with Providers and Staff of Ontario Community Health Centres

Is primary health care ready for artificial intelligence? What do primary health care stakeholders say?

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