首页|University of Victoria Reports Findings in Artificial Intelligence (Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Rev iew)
University of Victoria Reports Findings in Artificial Intelligence (Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Rev iew)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Victoria, Canada, by NewsRx journalists, research stated, “Artificial intelligence (AI) use cases in health care are on the rise, with the potential to improve operational effic iency and care outcomes. However, the translation of AI into practical, everyday use has been limited, as its effectiveness relies on successful implementation and adoption by clinicians, patients, and other health care stakeholders.” The news correspondents obtained a quote from the research from the University o f Victoria, “As adoption is a key factor in the successful proliferation of an i nnovation, this scoping review aimed at presenting an overview of the barriers t o and facilitators of AI adoption in health care. A scoping review was conducted using the guidance provided by the Joanna Briggs Institute and the framework pr oposed by Arksey and O’Malley. MEDLINE, IEEE Xplore, and ScienceDirect databases were searched to identify publications in English that reported on the barriers to or facilitators of AI adoption in health care. This review focused on articl es published between January 2011 and December 2023. The review did not have any limitations regarding the health care setting (hospital or community) or the po pulation (patients, clinicians, physicians, or health care administrators). A th ematic analysis was conducted on the selected articles to map factors associated with the barriers to and facilitators of AI adoption in health care. A total of 2514 articles were identified in the initial search. After title and abstract r eviews, 50 (1.99%) articles were included in the final analysis. Th ese articles were reviewed for the barriers to and facilitators of AI adoption i n health care. Most articles were empirical studies, literature reviews, reports , and thought articles. Approximately 18 categories of barriers and facilitators were identified. These were organized sequentially to provide considerations fo r AI development, implementation, and the overall structure needed to facilitate adoption. The literature review revealed that trust is a significant catalyst o f adoption, and it was found to be impacted by several barriers identified in th is review. A governance structure can be a key facilitator, among others, in ens uring all the elements identified as barriers are addressed appropriately. The f indings demonstrate that the implementation of AI in health care is still, in ma ny ways, dependent on the establishment of regulatory and legal frameworks. Furt her research into a combination of governance and implementation frameworks, mod els, or theories to enhance trust that would specifically enable adoption is nee ded to provide the necessary guidance to those translating AI research into prac tice.”
VictoriaCanadaNorth and Central Amer icaArtificial IntelligenceEmerging TechnologiesMachine Learning
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