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

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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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-16
DOI
https://doi.org/10.5281/zenodo.19057370
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Ilia Nadareishvili, Irine Pkhakadze, Mari Rodonaia, Giorgi Pkhakadze et al.
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

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

Ilia Nadareishvili, Irine Pkhakadze, Mari Rodonaia, Giorgi Pkhakadze, Tamari Talakvadze
article en

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.

Zenodo (CERN European Organization for Nuclear Research)
David Tvildiani Medical University (GE), State Healthcare Institution "Regional Clinical Oncological Dispensary" (RU), Akaki Tsereteli State University (GE)
Quality Education
Openalex Percentile: Top 22%
Artificial Intelligence in Healthcare and Education
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