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An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals
Artificial intelligence (AI) in the domain of healthcare is increasing in prominence. Acceptance is an indispensable prerequisite for the widespread implementation of AI. The aim of this integrative review is to explore barriers and facilitators influencing healthcare professionals’ acceptance of AI...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257646/ https://www.ncbi.nlm.nih.gov/pubmed/37301946 http://dx.doi.org/10.1038/s41746-023-00852-5 |
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author | Lambert, Sophie Isabelle Madi, Murielle Sopka, Saša Lenes, Andrea Stange, Hendrik Buszello, Claus-Peter Stephan, Astrid |
author_facet | Lambert, Sophie Isabelle Madi, Murielle Sopka, Saša Lenes, Andrea Stange, Hendrik Buszello, Claus-Peter Stephan, Astrid |
author_sort | Lambert, Sophie Isabelle |
collection | PubMed |
description | Artificial intelligence (AI) in the domain of healthcare is increasing in prominence. Acceptance is an indispensable prerequisite for the widespread implementation of AI. The aim of this integrative review is to explore barriers and facilitators influencing healthcare professionals’ acceptance of AI in the hospital setting. Forty-two articles met the inclusion criteria for this review. Pertinent elements to the study such as the type of AI, factors influencing acceptance, and the participants’ profession were extracted from the included studies, and the studies were appraised for their quality. The data extraction and results were presented according to the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The included studies revealed a variety of facilitating and hindering factors for AI acceptance in the hospital setting. Clinical decision support systems (CDSS) were the AI form included in most studies (n = 21). Heterogeneous results with regard to the perceptions of the effects of AI on error occurrence, alert sensitivity and timely resources were reported. In contrast, fear of a loss of (professional) autonomy and difficulties in integrating AI into clinical workflows were unanimously reported to be hindering factors. On the other hand, training for the use of AI facilitated acceptance. Heterogeneous results may be explained by differences in the application and functioning of the different AI systems as well as inter-professional and interdisciplinary disparities. To conclude, in order to facilitate acceptance of AI among healthcare professionals it is advisable to integrate end-users in the early stages of AI development as well as to offer needs-adjusted training for the use of AI in healthcare and providing adequate infrastructure. |
format | Online Article Text |
id | pubmed-10257646 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102576462023-06-12 An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals Lambert, Sophie Isabelle Madi, Murielle Sopka, Saša Lenes, Andrea Stange, Hendrik Buszello, Claus-Peter Stephan, Astrid NPJ Digit Med Review Article Artificial intelligence (AI) in the domain of healthcare is increasing in prominence. Acceptance is an indispensable prerequisite for the widespread implementation of AI. The aim of this integrative review is to explore barriers and facilitators influencing healthcare professionals’ acceptance of AI in the hospital setting. Forty-two articles met the inclusion criteria for this review. Pertinent elements to the study such as the type of AI, factors influencing acceptance, and the participants’ profession were extracted from the included studies, and the studies were appraised for their quality. The data extraction and results were presented according to the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The included studies revealed a variety of facilitating and hindering factors for AI acceptance in the hospital setting. Clinical decision support systems (CDSS) were the AI form included in most studies (n = 21). Heterogeneous results with regard to the perceptions of the effects of AI on error occurrence, alert sensitivity and timely resources were reported. In contrast, fear of a loss of (professional) autonomy and difficulties in integrating AI into clinical workflows were unanimously reported to be hindering factors. On the other hand, training for the use of AI facilitated acceptance. Heterogeneous results may be explained by differences in the application and functioning of the different AI systems as well as inter-professional and interdisciplinary disparities. To conclude, in order to facilitate acceptance of AI among healthcare professionals it is advisable to integrate end-users in the early stages of AI development as well as to offer needs-adjusted training for the use of AI in healthcare and providing adequate infrastructure. Nature Publishing Group UK 2023-06-10 /pmc/articles/PMC10257646/ /pubmed/37301946 http://dx.doi.org/10.1038/s41746-023-00852-5 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Lambert, Sophie Isabelle Madi, Murielle Sopka, Saša Lenes, Andrea Stange, Hendrik Buszello, Claus-Peter Stephan, Astrid An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals |
title | An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals |
title_full | An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals |
title_fullStr | An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals |
title_full_unstemmed | An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals |
title_short | An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals |
title_sort | integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257646/ https://www.ncbi.nlm.nih.gov/pubmed/37301946 http://dx.doi.org/10.1038/s41746-023-00852-5 |
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