Exploring Primary Care Patients’ Perspectives on Artificial Intelligence: A systematic literature review and qualitative meta-synthesis (Preprint)

Abstract

<sec> <title>BACKGROUND</title> The progression of Artificial Intelligence (AI) in healthcare holds great promise, offering the potential to alleviate physicians’ workloads and allocate more time for patient interactions. However, implementing AI in primary care also carries inherent risks and ethical obligations that must be carefully considered. Understanding patients’ perspectives on using AI in primary care is crucial for its effective integration. </sec> <sec> <title>OBJECTIVE</title> The primary objective of this qualitative meta-synthesis is to synthesize current qualitative research on primary care patients’ perspectives regarding the use of AI and Large Language Models (LLMs) in primary care. </sec> <sec> <title>METHODS</title> A qualitative meta-synthesis, using thematic analysis, was performed in accordance with PRISMA guidelines. PubMed and Scopus were searched on February 5th, 2024. Quality assessment was carried out using the Critical Appraisal Skills Program (CASP) checklist for qualitative research. </sec> <sec> <title>RESULTS</title> A total of 861 studies were screened for title and abstract, and six studies were included. Three themes emerged: “The Relationship with and Actions of a Robot”, “Implementing AI responsibly”, and “Training Physicians and Artificial Minds”. Findings indicate that while patients acknowledge the potential benefits of AI, concerns persist regarding the loss of human interaction in medical care, data security, and the ethical implications of AI implementation. </sec> <sec> <title>CONCLUSIONS</title> Patients recognized the advantages of AI in alleviating administrative tasks and enhancing physician effectiveness, yet raised substantial concerns that should be addressed prior to its adoption in primary care. Patients emphasize the importance of maintaining human interaction and advocate for strong clinician oversight, robust safety frameworks, and preserving patient choice and autonomy. Addressing patient concerns and understanding associated risks are key to ensuring AI's safe and effective use in healthcare. </sec>

Ähnliche Arbeiten