Satisfaction with Artificial Intelligence Among Patients and Physicians: A Scoping Review

Abstract

GOAL: The role of artificial intelligence (AI) continues to grow in healthcare. It is important to gain a deeper understanding of how patients and care providers perceive its use in patient care and whether they are satisfied with the AI experience. This study performed a scoping review of the published research on patient and physician satisfaction with AI used in healthcare delivery. METHODS: The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach guided the identification, filtering, and analysis of research published from 2003 to 2023 on patient and care provider satisfaction with AI. A standardized data abstraction form created in Microsoft Excel was used to record relevant information in the 45 articles that were selected for review. PRINCIPAL FINDINGS: Most of the 45 empirical studies included in this study focused on patient satisfaction with AI. Almost half considered AI for treatment exclusively, mostly in hospital or remote settings. Moderate to high degrees of AI satisfaction were identified in 16 of 28 (57%) studies that contained a general AI satisfaction finding of some type. In the other 12 studies, satisfaction levels expressed were lower. Overall, higher satisfaction was seen with AI in diagnostic situations compared to treatment situations. Ninety percent of studies where AI was identified as effective in patient care also found high levels of AI satisfaction. PRACTICAL APPLICATIONS: Both physicians and patients appear receptive to the integration of AI into patient care, regardless of the type of AI used. This receptivity may encourage healthcare organizations to support AI in patient care. Healthcare organizations should identify the full range of drivers of patient and physician satisfaction with AI beyond whether the technology or tool improves clinical outcomes. Future research could analyze contextual factors that may impact AI satisfaction; effects related to age, type of patient care setting, and clinical situation; and an expansion of the types of AI examined.

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