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Cited by 29Artificial Intelligence in Healthcare and EducationElectronic Health Records SystemsHealth Policy Implementation Science

Healthcare leaders’ experiences of implementing artificial intelligence for medical history-taking and triage in Swedish primary care: an interview study

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Siira, Elin, Tyskbo, Daniel, Nygren, Jens·2024·BMC Primary Care
DOI 10.1186/s12875-024-02516-zPMC PMC11267767
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Abstract

Background: Artificial intelligence (AI) holds significant promise for enhancing the efficiency and safety of medical history-taking and triage within primary care. However, there remains a dearth of knowledge concerning the practical implementation of AI systems for these purposes, particularly in the context of healthcare leadership. This study explores the experiences of healthcare leaders regarding the barriers to implementing an AI application for automating medical history-taking and triage in Swedish primary care, as well as the actions they took to overcome these barriers. Furthermore, the study seeks to provide insights that can inform the development of AI implementation strategies for healthcare. Methods: We adopted an inductive qualitative approach, conducting semi-structured interviews with 13 healthcare leaders representing seven primary care units across three regions in Sweden. The collected data were subsequently analysed utilizing thematic analysis. Our study adhered to the Consolidated Criteria for Reporting Qualitative Research to ensure transparent and comprehensive reporting. Results: The study identified implementation barriers encountered by healthcare leaders across three domains: (1) healthcare professionals, (2) organization, and (3) technology. The first domain involved professional scepticism and resistance, the second involved adapting traditional units for digital care, and the third inadequacies in AI application functionality and system integration. To navigate around these barriers, the leaders took steps to (1) address inexperience and fear and reduce professional scepticism, (2) align implementation with digital maturity and guide patients towards digital care, and (3) refine and improve the AI application and adapt to the current state of AI application development. Conclusion: The study provides valuable empirical insights into the implementation of AI for automating medical history-taking and triage in primary care as experienced by healthcare leaders. It identifies the barriers to this implementation and how healthcare leaders aligned their actions to overcome them. While progress was evident in overcoming professional-related and organizational-related barriers, unresolved technical complexities highlight the importance of AI implementation strategies that consider how leaders handle AI implementation in situ based on practical wisdom and tacit understanding. This underscores the necessity of a holistic approach for the successful implementation of AI in healthcare.

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Authors
Siira, E., Tyskbo, D., & Nygren, J.
Affiliations
Halmstad University (SE)
Corresponding author
Nygren, Jens
ORCID
Venue
BMC Primary Care
Publisher
Springer Science and Business Media LLC
Published
2024-07-24
Volume
25
Issue
1
Pages
268-268
ISSN
  • 1471-2296 (ISSN-L)
  • 2731-4553
DOI
10.1186/s12875-024-02516-z
PMC
PMC11267767
OpenAlex
W4400958062
Cited by
29
References
13
Citations by year
2026: 15 · 2025: 13 · 2024: 1
FWCI
2.71
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Family Practice (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Halmstad University
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
Keywords
AI implementation, medical history, triage, primary care, healthcare leadership, implementation barriers, professional skepticism, resistance to AI, digital care, digital maturity, system integration, implementation strategies, practical wisdom
MeSH terms
Artificial Intelligence, Attitude of Health Personnel, Female, Humans, Interviews as Topic, Leadership, Male, Medical History Taking, Primary Health Care, Sweden, Triage, Qualitative Research

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