Introduction
Patient experience is a core measure of health care quality, reflecting how patients perceive and interact with health services. Recent policy push in China has accelerated the adoption of artificial intelligence (AI) in health care, including AI-assisted conversational agents (AA-CAs) that collect patient information before visits and streamlines communication with physicians. This study investigates whether AA-CAs used during outpatient visits can improve the patient experience related to physicians in tertiary public hospitals across economically developed regions of China.
Background
Conversations between patients and physicians influence satisfaction, safety, and clinical outcomes. Traditional outpatient workflows often constrain time for thorough history-taking and explanation. AI-assisted conversational agents can pre-collect symptom data, disease history, and medication lists, delivering structured information to physicians prior to consultation. While prior reviews suggest potential efficiency gains, quantitative evidence linking AA-CAs to improved patient experience specifically related to physicians has been limited. This study addresses that gap by comparing patient experiences between AA-CA users and nonusers during outpatient visits.
Methods
We surveyed adult residents who recently sought outpatient care at tertiary public hospitals in China (past two weeks). The instrument was a Chinese Outpatient Experience Questionnaire focusing on four dimensions related to physicians: physician-patient communication, health information access, short-term outcomes, and general satisfaction (19 items in total). We added a question to identify AA-CA use during the visit. Data were collected via Credamo from April 1–15, 2025, and analyzed with descriptive statistics, t-tests, and multiple linear regression, controlling for demographics and visit characteristics. Statistical significance was assessed with Benjamini-Hochberg adjusted P values.
Key Findings
Among 394 eligible respondents, about half used AI-assisted conversational agents during their outpatient visit. AA-CA users reported higher experiences across all four physician-related dimensions and the 19 questionnaire items compared with nonusers. In the adjusted model, using an AA-CA was a significant predictor of better total patient experience scores related to physicians, even after accounting for sex, education, income, health status, and physician title. Specifically, AA-CA use corresponded to an average increase in the total physician-related patient experience score equivalent to roughly 7.5% of the scale.
Self-rated health status also emerged as a significant factor: participants rating their health as very good tended to report more positive experiences. The regression model explained about a quarter of the variance in physician-related patient experience, with multicollinearity not detected among predictors.
Interpretation
The findings indicate that AA-CAs can meaningfully enhance the outpatient experience as it relates to physicians. How might this occur in practice? First, pre-consultation chatbots gather comprehensive history and concerns, enabling physicians to begin with a clearer picture. Second, structured data provided to physicians supports more efficient, targeted questioning during the visit, potentially shortening waiting times and improving communication quality. Third, patients gain greater access to tailored health information, contributing to higher satisfaction and perceived quality of care.
Implications for Policy and Practice
China’s digital health policy encourages smart hospitals and AI-enabled services. To scale benefits, hospitals in major cities should integrate AA-CAs into existing mobile health apps, align them with electronic health records, and promote user-friendly interfaces to sustain uptake. However, disparities in resources across regions warrant targeted public funding to extend AA-CA deployment to less-developed areas. Training for both patients and clinicians on effectively using AA-CAs could further improve outcomes and acceptance.
Limitations
Self-reported data and recall bias are possible. The sample may over-represent digitally literate individuals with recent outpatient experiences. The observational design cannot prove causality, though associations were robust after adjustment for confounders. Future longitudinal studies or randomized trials could better establish causal effects and illuminate mechanisms behind improved patient experience.
Conclusions
Across tertiary public hospitals in economically developed regions of China, AI-assisted conversational agents used during outpatient visits were associated with improved patient experience related to physicians — notably in communication, information access, short-term outcomes, and overall satisfaction. Policymakers and hospital leaders should consider broader, equitable deployment of AA-CAs to sustain gains in patient experience and, potentially, health outcomes.
