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Healthcare leaders' experiences of implementing artificial intelligence for medical history-taking and triage in Swedish primary care: an interview study.
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- Author(s): Siira, Elin; Tyskbo, Daniel; Nygren, Jens
- Source:
BMC Primary Care; 7/24/2024, Vol. 25 Issue 1, p1-15, 15p- Subject Terms:
MEDICAL history taking; FEAR; MOBILE apps; HEALTH services accessibility; QUALITATIVE research; MEDICAL technology; MEDICAL personnel; RESOURCE allocation; PATIENT safety; RESEARCH funding; LEADERSHIP; ARTIFICIAL intelligence; PRIMARY health care; EMPIRICAL research; INTERVIEWING; MEDICAL care; HEALTH; INFORMATION resources; JUDGMENT sampling; DESCRIPTIVE statistics; THEMATIC analysis; ATTITUDES of medical personnel; RESEARCH methodology; AUTOMATION; NEEDS assessment; COMPARATIVE studies; MEDICAL triage; PROFESSIONAL competence; PSYCHOSOCIAL factors - Source:
- Additional Information
- Subject Terms:
- 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. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of BMC Primary Care is the property of BioMed Central and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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