Artificial intelligence-enabled healthcare access and user experience: comparative institutional analysis and survey evidence from China
Abstract
BackgroundRegulatory entry and public experience describe different aspects of artificial intelligence-enabled healthcare access.MethodsThis 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.ResultsThe 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.ConclusionThe findings highlight entry and operational barriers alongside differences in experience among existing users, supporting evaluation of both access conditions and service encounters.
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BibTeX
@article{tang2026artificial,
title = {{Artificial intelligence-enabled healthcare access and user experience: comparative institutional analysis and survey evidence from China}},
author = {Hui Tang and Shuhui Li and Qi Wang},
journal = {Frontiers in Public Health},
year = {2026},
month = nov,
doi = {10.3389/fpubh.2026.1977062},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1977062},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Artificial intelligence-enabled healthcare access and user experience: comparative institutional analysis and survey evidence from China
AU - Hui Tang
AU - Shuhui Li
AU - Qi Wang
PY - 2026
DA - 2026/11/02
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1977062
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1977062
AB - BackgroundRegulatory entry and public experience describe different aspects of artificial intelligence-enabled healthcare access.MethodsThis 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.ResultsThe 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.ConclusionThe findings highlight entry and operational barriers alongside differences in experience among existing users, supporting evaluation of both access conditions and service encounters.
SN - 2296-2565
ER -