ArticleJournal of medical Internet research2025
Use of Artificial Intelligence-Assisted Conversational Agents to Improve Patient Experience Related to Physicians: Cross-Sectional Study in China.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Stakeholder experience with artificial intelligence in healthcare: a bibliometric study of satisfaction, trust, acceptance, and patient engagement.Frontiers in digital health · 2026Pooled it
- The double-edged sword of generative AI in dermatology: a multi-component cross-sectional study on physician burnout, patient satisfaction, and communication quality.Frontiers in medicine · 2026Article
- Reclaiming the Human Connection in Clinical Care With AI.Journal of patient experience · 2026Article
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4 authors.
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Abstract
Background: Artificial intelligence-assisted conversational agents have been applied and developed in outpatient departments to improve health services in China. However, there has been little research that evaluates the effect of artificial intelligence-assisted conversational agents on the patient experience related to physicians during outpatient visits. Objective: This study aimed to examine whether the use of artificial intelligence-assisted conversational agents improves the patient experience related to physicians during outpatient visits and to further find out the difference in the patient experience between conversational agent users and nonusers. Methods: We used the Chinese Outpatient Experience Questionnaire to survey the patient experience related to physicians during outpatient visits. A sample of 394 adult residents who sought outpatient services from tertiary public hospitals in China was selected by random sampling. The t tests were used to test the mean difference in the patient experience scores between conversational agent users and nonusers. Multiple linear regression analysis was further performed to determine whether the use of artificial intelligence-assisted conversational agents during outpatient visits was associated with a better patient experience related to physicians. Results: Conversational agent users reported significantly higher scores than nonusers in the total patient experience scores (t392=5.589, P<.001), the 19 items and 4 dimensions of physician-patient communication (t392=5.013, P=.006), health information (t392=5.758, P<.001), short-term outcome (t392=4.608, P<.001) and general satisfaction (t392=5.080, P<.001). Multiple linear regression results further showed that after controlling for other factors on participant characteristics, the use of artificial intelligence-assisted conversational agents during outpatient visits significantly influenced the total patient experience scores related to physicians (B=0.298, P=.01). And the use of artificial intelligence-assisted conversational agents averagely increased the total patient experience scores related to physicians during outpatient visits by 7.51% (0.298/3.97). Conclusions: The use of artificial intelligence-assisted conversational agents could improve the patient experience related to physicians during outpatient visits, especially in terms of making physician-patient communication better, accessing more targeted health information, ameliorating short-term outcomes, and increasing general satisfaction. Therefore, we suggest that public hospitals should consider the benefits of the artificial intelligence-assisted conversational agents and actively deploy the conversational agents in outpatient departments so as to continuously improve the patient experience related to physicians during outpatient visits.
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