Artificial Intelligence–Informed Patients and the Transformation of Doctor–Patient Communication: Evidence from a Mixed-Methods Study in Georgian Outpatient Clinics

Abstract

This article presents an exploratory mixed-methods study examining how artificial intelligence (AI)–generated health information influences doctor–patient communication in outpatient clinical practice in Kutaisi, Georgia. The study combines quantitative survey data from 127 patients with qualitative interviews of 45 physicians to analyse patterns of AI-based health information use, physician perceptions, and communication dynamics in AI-informed consultations. The findings indicate that AI-informed patients are increasingly common in clinical practice, with physicians frequently encountering patients who have consulted conversational AI systems prior to medical visits. While AI-generated information is often perceived as informative, it is generally considered only partially accurate and requires professional interpretation within clinical contexts. The study also identifies a communication gap, as many patients do not disclose their use of AI tools during consultations. The results suggest that AI technologies are reshaping the informational environment of clinical encounters and contributing to an evolving role for physicians as interpreters of externally generated health information. The study provides empirical evidence from a real-world clinical setting and highlights implications for medical education, health communication, and digital health policy.

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