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Innovation in healthcare: leadership perceptions about the innovation characteristics of artificial intelligence—a qualitative interview study with healthcare leaders in Sweden
Halmstad University, School of Health and Welfare. (Healthcare Improvement group)ORCID iD: 0000-0002-2764-3722
Halmstad University, School of Health and Welfare. (Healthcare Improvement group)ORCID iD: 0000-0001-7874-7970
Halmstad University, School of Health and Welfare. (Healthcare Improvement group)ORCID iD: 0000-0002-3576-2393
Halmstad University, School of Health and Welfare. (Healthcare Improvement group)ORCID iD: 0000-0003-4438-6673
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2023 (English)In: Implementation Science Communications, E-ISSN 2662-2211, Vol. 4, article id 81Article in journal (Refereed) Published
Abstract [en]

Background: Despite the extensive hopes and expectations for value creation resulting from the implementation of artificial intelligence (AI) applications in healthcare, research has predominantly been technology-centric rather than focused on the many changes that are required in clinical practice for the technology to be successfully implemented. The importance of leaders in the successful implementation of innovations in healthcare is well recognised, yet their perspectives on the specific innovation characteristics of AI are still unknown. The aim of this study was therefore to explore the perceptions of leaders in healthcare concerning the innovation characteristics of AI intended to be implemented into their organisation.

Methods: The study had a deductive qualitative design, using constructs from the innovation domain in the Consolidated Framework for Implementation Research (CFIR). Interviews were conducted with 26 leaders in healthcare.

Results: Participants perceived that AI could provide relative advantages when it came to care management, supporting clinical decisions, and the early detection of disease and risk of disease. The development of AI in the organisation itself was perceived as the main current innovation source. The evidence base behind AI technology was questioned, in relation to its transparency, potential quality improvement, and safety risks. Although the participants acknowledged AI to be superior to human action in terms of effectiveness and precision in some situations, they also expressed uncertainty about the adaptability and trialability of AI. Complexities such as the characteristics of the technology, the lack of conceptual consensus about AI, and the need for a variety of implementation strategies to accomplish transformative change in practice were identified, as were uncertainties about the costs involved in AI implementation.

Conclusion: Healthcare leaders not only saw potential in the technology and its use in practice, but also felt that AI’s opacity limits its evidence strength and that complexities in relation to AI itself and its implementation influence its current use in healthcare practice. More research is needed based on actual experiences using AI applications in real-world situations and their impact on clinical practice. New theories, models, and frameworks may need to be developed to meet challenges related to the implementation of AI in healthcare. © 2023, The Author(s).

Place, publisher, year, edition, pages
London: BioMed Central (BMC), 2023. Vol. 4, article id 81
Keywords [en]
Artificial intelligence, Consolidated framework of implementation research, Healthcare, Healthcare leaders, Implementation, Organisational change, Qualitative methods, Stakeholders
National Category
Nursing Health Care Service and Management, Health Policy and Services and Health Economy Medical and Health Sciences
Research subject
Health Innovation, Information driven care
Identifiers
URN: urn:nbn:se:hh:diva-51411DOI: 10.1186/s43058-023-00458-8PubMedID: 37464420Scopus ID: 2-s2.0-85165293200OAI: oai:DiVA.org:hh-51411DiVA, id: diva2:1788426
Funder
Vinnova, 2019–04526Knowledge Foundation, 20200208 01H
Note

Funding: Open access funding provided by Halmstad University. The funders of this study are the Swedish Government Innovation Agency Vinnova (grant 2019–04526) and the Knowledge Foundation (grant 20200208 01H).

Available from: 2023-08-16 Created: 2023-08-16 Last updated: 2024-01-08Bibliographically approved

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Neher, MargitPetersson, LenaNygren, Jens M.Svedberg, PetraLarsson, IngridNilsen, Per

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NursingHealth Care Service and Management, Health Policy and Services and Health EconomyMedical and Health Sciences

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