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ORIGINAL RESEARCH article

Front. Public Health

Sec. Health Economics

Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1651744

This article is part of the Research TopicIntegrating Economics into Population Health: Assessing Policies and OutcomesView all 13 articles

Efficiency Divergence and Convergence in China's Hospital Sector: Empirical Insights from Guangdong Province Using a Multi-Method Approach

Provisionally accepted
Jianxin  YuJianxin Yu1Yongyi  XuYongyi Xu2Jingdong  WuJingdong Wu1Zijuan  ZhangZijuan Zhang3Baoling  WUBaoling WU2Weizhang  HuangWeizhang Huang2*Hanxiang  GongHanxiang Gong2*
  • 1First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
  • 2Guangzhou Medical University Second Affiliated Hospital, Guangzhou, China
  • 3Southern Medical University Stomatological Hospital, Guangzhou, China

The final, formatted version of the article will be published soon.

Background: Since the launch of China's new round of healthcare system reforms in 2009, improving service efficiency has become a critical focus for enhancing the equitable allocation of medical resources and overall healthcare quality. Guangdong Province, as one of China's most economically dynamic regions, faces significant challenges in addressing disparities in hospital service efficiency and optimizing resource utilization.This study aims to comprehensively analyze the differences, dynamic evolution, and influencing factors of service efficiency among healthcare institutions in Guangdong Province. The goal is to provide scientific evidence for narrowing efficiency gaps between hospitals, enhancing overall service quality, and informing policy development.Methods: A comprehensive evaluation system for hospital service efficiency in Guangdong Province was constructed. Data Envelopment Analysis (DEA) was employed to measure efficiency levels. The Dagum Gini coefficient decomposition method was used to examine the sources of efficiency disparities among different hospital categories. Kernel density estimation was employed to investigate the dynamic distribution of service quality, while the Tobit regression model was used to identify key factors influencing healthcare service efficiency.The findings indicate that significant differences in service efficiency existed among various categories of hospitals in Guangdong Province from 2018 to 2022. Specialty hospitals demonstrated the highest average overall efficiency, whereas general hospitals recorded the lowest efficiency and growth rates. The performance of healthcare institutions in terms of pure technical efficiency, scale efficiency, and overall efficiency showed fluctuations, but a general trend of recovery was observed. The Dagum Gini coefficient decomposition revealed a relatively high degree of internal efficiency inequality within general hospitals, peaking in 2021, reflecting heterogeneity in scale, management, and resource allocation. The Gini coefficient between specialty and general hospitals was also comparatively high.Kernel density estimation indicated a bimodal distribution in service efficiency, highlighting the heterogeneity of efficiency levels and an increase in hospital categories with lower service quality. TheThis study aims to comprehensively analyze the differences, dynamic evolution, and influencing factors of service efficiency among healthcare institutions in Guangdong Province. The goal is to provide scientific evidence for narrowing efficiency gaps between hospitals, enhancing overall service quality, and informing policy development.

Keywords: Guangdong Province, Healthcare institutions, Service efficiency, tertiary public hospitals, performance evaluation

Received: 22 Jun 2025; Accepted: 26 Aug 2025.

Copyright: © 2025 Yu, Xu, Wu, Zhang, WU, Huang and Gong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Weizhang Huang, Guangzhou Medical University Second Affiliated Hospital, Guangzhou, China
Hanxiang Gong, Guangzhou Medical University Second Affiliated Hospital, Guangzhou, China

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