Exploring Clinician Perspectives on Artificial Intelligence in Primary Care: a qualitative systematic review and meta synthesis (Preprint)

Abstract

<sec> <title>BACKGROUND</title> Recent advances have highlighted the potential of artificial intelligence (AI) systems in assisting clinicians with administrative and clinical tasks, but concerns regarding biases, lack of regulation, and potential technical issues pose significant challenges. The lack of a clear definition of AI, combined with a limited focus on qualitative research exploring clinicians' perspectives has limited the understanding of perspectives on AI in primary healthcare settings. </sec> <sec> <title>OBJECTIVE</title> This review aims to synthesize the current qualitative research on the perspectives of clinicians on artificial intelligence in primary care settings. </sec> <sec> <title>METHODS</title> A qualitative systematic review and meta synthesis using thematic analysis was performed, adhering to PRISMA guidelines. Searches were conducted in PubMed and Scopus. The Critical Appraisal Skills Program checklist for qualitative research was used for quality appraisal. </sec> <sec> <title>RESULTS</title> Twelve articles were included. Three themes emerged: the human-machine relationship, the technologically enhanced clinic, and the societal effects of AI. </sec> <sec> <title>CONCLUSIONS</title> Clinicians view AI as a technology that either could enhance or complicate primary healthcare. While AI can provide substantial support, its integration into healthcare requires careful consideration of ethical implications, technical reliability, and the maintenance of human oversight. More in-depth qualitative research on the effects of AI on clinicians’ careers and autonomy could prove helpful for the future development of AI systems. </sec>

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