Evidence map›Paper›PMID 40989252›Full record

ArticleFrontiers in digital health2025

Sustainable service quality assessment of Chinese healthcare e-government: a multi-criteria decision framework based on SERVQUAL model and entropy-weight TOPSIS method.

Yilin Xia, Bei Li, Jian Yang, Weixi Guo, Jianwei Sun, Xu Zeng, Jing Zheng

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Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Yilin XiaDepartment of Biomedical Informatics, School of Life Science, Central South University, Changsha, China.
Bei LiDepartment of Biomedical Informatics, School of Life Science, Central South University, Changsha, China.
Jian YangDepartment of Biomedical Informatics, School of Life Science, Central South University, Changsha, China.
Weixi GuoDepartment of Biomedical Informatics, School of Life Science, Central South University, Changsha, China.
Jianwei SunShenzhen Health Development Research and Data Management Center, Shenzhen, China.
Xu ZengShenzhen Health Development Research and Data Management Center, Shenzhen, China.
Jing ZhengShenzhen Health Development Research and Data Management Center, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Healthcare e-government plays a vital role in advancing the United Nations 2030 Agenda for Sustainable Development, by disseminating vital information and delivering essential services, particularly during the coronavirus disease 2019 (COVID-19) pandemic. China faces challenges within the context of health care, such as limited infrastructure and equitable healthcare access, underscoring the necessity of evaluating and improving the quality of healthcare e-government services. Methods: This study proposes a novel multicriteria decision-making framework for systematically evaluating the quality of healthcare e-government services. The framework structurally extends the SERVQUAL model into 5 first-level and 31 s-level dimensions tailored to digital governance and integrates it with the entropy weight method and the technique for order of preference by similarity to ideal solution. This hybrid methodology enables objective, scalable, and theory-based assessment. To validate its effectiveness, the model was empirically applied to 17 Chinese municipal health commission websites in the period of 2019-2024 to validate its effectiveness. Results: The results revealed that empathy represents the most critical quality gap among the evaluated healthcare e-government services, while cross-platform interoperability has become a strategic focus for system improvement. These results highlighted that sustainable service quality is contingent on both robust technical infrastructure and human-centric factors. Discussion: The proposed framework can offer policymakers a replicable decision-support tool by bridging the gap between operational performance and sustainable service delivery, particularly in developing regions. This provides practical insights into achieving digital healthcare transformation, contributing to the United Nations Sustainable Development Goals, offers a scalable evaluation approach for comparative research in digital governance, and promotes global e-government systems.

Indexed as

healthcare e-governmentMCDMSDGsSERVQUALTOPSIS

Identifiers

PMID40989252
PMCPMC12450976

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