SORA

Advancing, promoting and sharing knowledge of health through excellence in teaching, clinical practice and research into the prevention and treatment of illness

Implementation challenges of artificial intelligence (AI) in primary care: Perspectives of general practitioners in London UK.

Razai, MS; Al-Bedaery, R; Bowen, L; Yahia, R; Chandrasekaran, L; Oakeshott, P (2024) Implementation challenges of artificial intelligence (AI) in primary care: Perspectives of general practitioners in London UK. PLoS One, 19 (11). e0314196. ISSN 1932-6203 https://doi.org/10.1371/journal.pone.0314196
SGUL Authors: Razai, Mohammad Sharif Bowen, Liza Jane Oakeshott, Philippa Al-Bedaery, Roaa

[img]
Preview
PDF Published Version
Available under License Creative Commons Attribution.

Download (341kB) | Preview
[img] Microsoft Word (.docx) (S1 Checklist) Supplemental Material
Available under License Creative Commons Attribution.

Download (55kB)
[img] Microsoft Word (.docx) (S1 File) Supplemental Material
Available under License Creative Commons Attribution.

Download (21kB)
[img]
Preview
PDF (S2 File) Supplemental Material
Available under License Creative Commons Attribution.

Download (84kB) | Preview

Abstract

INTRODUCTION: Implementing artificial intelligence (AI) in healthcare, particularly in primary care settings, raises crucial questions about practical challenges and opportunities. This study aimed to explore the perspectives of general practitioners (GPs) on the impact of AI in primary care. METHODS: A convenience sampling method was employed, involving a hybrid workshop with 12 GPs and 4 GP registrars. Verbal consent was obtained, and the workshop was audio recorded. Thematic analysis was conducted on the recorded data and contemporaneous notes to identify key themes. RESULTS: The workshop took place in 2023 and included 16 GPs aged 30 to 72 of diverse backgrounds and expertise. Most (93%) were female, and five (31%) self-identified as ethnic minorities. Thematic analysis identified two key themes related to AI in primary care: the potential benefits (such as help with diagnosis and risk assessment) and the associated concerns and challenges. Sub-themes included anxieties about diagnostic accuracy, AI errors, industry influence, and overcoming integration resistance. GPs also worried about increased workload, particularly extra, unnecessary patient tests, the lack of evidence base for AI programmes or accountability of AI systems and appropriateness of AI algorithms for different population groups. Participants emphasised the importance of transparency, trust-building, and research rigour to evaluate the effectiveness and safety of AI systems in healthcare. CONCLUSION: The findings suggest that GPs recognise the potential of AI in primary care but raise important concerns regarding evidence base, accountability, bias and workload. The participants emphasised the need for rigorous evaluation of AI technologies. Further research and collaboration between healthcare professionals, policymakers, and technology organisations are essential to navigating these challenges and harnessing the full potential of AI.

Item Type: Article
Additional Information: Copyright: © 2024 Razai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: Humans, Artificial Intelligence, Primary Health Care, General Practitioners, Female, Male, Middle Aged, London, Adult, Aged, Attitude of Health Personnel, Humans, Attitude of Health Personnel, Artificial Intelligence, Adult, Aged, Middle Aged, Primary Health Care, London, Female, Male, General Practitioners, General Science & Technology
SGUL Research Institute / Research Centre: Academic Structure > Institute of Medical & Biomedical Education (IMBE)
Academic Structure > Institute of Medical & Biomedical Education (IMBE) > Centre for Clinical Education (INMECE )
Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: PLoS One
ISSN: 1932-6203
Language: eng
Dates:
DateEvent
21 November 2024Published
5 November 2024Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
NIHR 302007National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
PubMed ID: 39570873
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/116978
Publisher's version: https://doi.org/10.1371/journal.pone.0314196

Actions (login required)

Edit Item Edit Item