Comprehensive recommendations for the implementation of artificial intelligence in healthcare: a narrative review on facilitators and barriers

Abstract

OBJECTIVES: The integration of artificial intelligence (AI) technologies into clinical practice holds significant promise for enhancing healthcare delivery, yet substantial barriers remain to their widespread adoption. This narrative review aimed, first, to identify key facilitators and barriers to the implementation of AI technologies in patient care, and, second, to introduce a comprehensive list of evidence-based recommendations for successful AI integration in healthcare organisations. DESIGN: We conducted a narrative review across four electronic databases to identify peer-reviewed studies published within the last decade. Following the stepwise selection and review procedure, thematic content analysis was performed. SAMPLE: A total of 26 studies was included. RESULTS: We identified 55 dimensions of facilitators or barriers to AI implementation. These were classified according to the Systems Engineering Initiative for Patient Safety work system model. Key dimensions included efficiency, compatibility with local IT infrastructure, stakeholder involvement, transparency and clinician trust. Drawing upon the 25 most frequently reported dimensions of facilitators and barriers, we developed a set of recommendations. CONCLUSIONS: This review consolidates the current literature on implementation challenges of AI in everyday clinical care practice to offer insights for healthcare organisations and professionals to navigate the challenges of AI implementation. Our findings provide a comprehensive overview of the sociotechnical complexities surrounding AI adoption, and our compilation of recommendations can help to guide future efforts in leveraging AI to improve clinical workflows and patient care.

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