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Overcoming barriers and enabling artificial intelligence adoption in allied health clinical practice: A qualitative study
Journal article   Open access   Peer reviewed

Overcoming barriers and enabling artificial intelligence adoption in allied health clinical practice: A qualitative study

Jane Hoffman, Rachel Wenke, Rebecca L. Angus, Lucy Shinners, Brent Richards and Laetitia Hattingh
Digital health, Vol.11, pp.1-14
08/2025
PMID: 39906878
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Published (Version of record) Open CC BY-NC-ND V4.0
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Published (Version of record) Open CC BY-NC-ND V4.0

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Abstract

allied health artificial intelligence hospital digital health behaviour change
Background: Artificial intelligence (AI) has the potential to revolutionise healthcare. If the implementation is successful it has the potential to improve healthcare outcomes for patients and organisations. Little is known about the perceptions of allied health professionals (AHPs) towards AI in healthcare. Objective: This study investigated barriers and enablers to AI implementation in the delivery of healthcare from the AHPs perspective. Methods: Qualitative methodology informed by behaviour change theory using focus groups with AHPs at a health service in Queensland, Australia. Results: Twenty-four barriers and 24 enablers were identified by 25 participants across four focus groups. Barriers included: lack of AI knowledge, explainability challenges, risk to professional practice, negative impact on professional practice, and role replacement. Enablers include AI training and education, regulation, reputation, understanding the healthcare benefits of AI and engaging clinical champions. Conclusions: AHPs have concerns about the impact and trustworthiness of AI and the readiness of organisations to support its use. Organisations must take a proactive approach and adopt targeted and multifaceted strategies to address barriers. This may include workforce upskilling, clear communication of the benefits of AI use of local champions and ongoing research.

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