Evidence map›Paper›PMID 36085203›Full record

ArticleBMC medical informatics and decision making2022

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

Amanda L Terry, Jacqueline K Kueper, Ron Beleno, Judith Belle Brown, Sonny Cejic, Janet Dang, Daniel Leger, Scott McKay, Leslie Meredith, Andrew D Pinto and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Atencion primaria · 2026
    Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Article
  7. Navigating the ethical and legal landscape of artificial intelligence in dentistry.Journal of advanced periodontology & implant dentistry · 2026
    Article
  8. Article
  9. Review
  10. Article
  11. AI and Primary Care: Scoping Review.Journal of medical Internet research · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
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  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Amanda L TerryDepartment of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond Street, London, ON, N6A 3K7, Canada. aterry4@uwo.ca.
Jacqueline K KueperDepartment of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond Street, London, ON, N6A 3K7, Canada.
Ron BelenoAge-Well NCE, Toronto Rehabilitation Institute, Toronto, ON, Canada.
Judith Belle BrownDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Sonny CejicDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Janet DangLondon Middlesex Primary Care Alliance, London, ON, Canada.
Daniel LegerDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Scott McKayDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Leslie MeredithDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Andrew D PintoUpstream Lab, MAP/Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Canada.
Bridget L RyanDepartment of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond Street, London, ON, N6A 3K7, Canada.
Moira StewartDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Merrick ZwarensteinDepartment of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond Street, London, ON, N6A 3K7, Canada.
Daniel J LizotteDepartment of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, 1151 Richmond Street, London, ON, N6A 3K7, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEffective 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.

methodsThis 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.

resultsFive 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.

conclusionThe 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.

Indexed as

Artificial IntelligenceSoftwareClinical CompetenceData AccuracyHumansPrimary Health CareArtificial intelligenceFamily medicinePrimary health careQualitative research

Identifiers

PMID36085203
PMCPMC9461192

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.