Artificial intelligence-enabled healthcare access and user experience: comparative institutional analysis and survey evidence from China

Background Regulatory entry and public experience describe different aspects of artificial intelligence-enabled healthcare access. Methods This health policy study compares institutional arrangements in China, the United States, and the European Union, examines the coverage of equity-related evidence, and analyses an online Chinese survey. Of 480 submissions, 430 passed an attention check, including 32 respondents without reported functional contact and 398 entering the experience models. Results The institutional comparison identifies differences in regulatory objects, information recipients, and responsibility allocation. The coverage analysis distinguishes institutional information and hospital governance from measured portal use and service experience. In the survey, lower-capability respondents reported greater entry and operational barriers; 79 of 159 reported reducing or abandoning use because of barriers. Among contacted respondents, functional contact intensity was positively associated with perceived process ease (standardized β = 0.496), which was associated with perceived health-service responsiveness (standardized β = 0.381). The contact-by-capability interaction was negative (B = −0.254), contrary to the hypothesized direction. Conclusion The findings highlight entry and operational barriers alongside differences in experience among existing users, supporting evaluation of both access conditions and service encounters.