Investigating the efficiency of medical and health resources and its influencing factors in the Yangtze River Delta urban agglomerations: based on the undesirable super-efficiency SBM-Malmquist-Tobit model
The medical and health resources in the Yangtze River Delta region are abundant, occupying a significant position in China’s medical and health system with wide service coverage. The efficient allocation of medical and health resources in this region is a key issue affecting the high-quality develop...
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1527424/full |
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| author | Yi Chen Yi Chen Qianlong Li Yuting Zhang Xiaoya Zhang Handong Zheng |
| author_facet | Yi Chen Yi Chen Qianlong Li Yuting Zhang Xiaoya Zhang Handong Zheng |
| author_sort | Yi Chen |
| collection | DOAJ |
| description | The medical and health resources in the Yangtze River Delta region are abundant, occupying a significant position in China’s medical and health system with wide service coverage. The efficient allocation of medical and health resources in this region is a key issue affecting the high-quality development of medical and health services. Existing research on the representative region of the Yangtze River Delta Urban Agglomeration remains relatively limited, with insufficient analysis of the efficiency of medical and health resource allocation in the area, as well as a lack of in-depth exploration into its influencing factors and barriers. This study employs the undesirable output super-efficiency SBM model to calculate the static super-efficiency values of medical and health resource allocation in 41 cities of the Yangtze River Delta urban agglomeration from 2015 to 2020. The Malmquist index is utilized to analyze the changes in dynamic efficiency, and the panel Tobit regression model is utilized to analyze the influencing factors of comprehensive efficiency of medical and health resource allocation in the Yangtze River Delta urban agglomeration. The study highlights that the Yangtze River Delta urban agglomeration confronts multiple systemic challenges, such as pronounced disparities in healthcare resource allocation, uneven dissemination of medical technological innovations, insufficiently effective policy implementation, severe pandemic-induced impacts, enduring gaps in urban–rural healthcare resources, and financial accessibility barriers in low-efficiency cities. By integrating empirical evidence from existing studies and performing comparative case analyses, this research puts forward actionable recommendations. These strategies are designed to improve the equity and efficiency of medical and health resource allocation within the region, while offering transferable insights for other regions facing similar institutional and operational challenges. |
| format | Article |
| id | doaj-art-ec1104d60e4a4881980c5b3eaacc05a8 |
| institution | OA Journals |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj-art-ec1104d60e4a4881980c5b3eaacc05a82025-08-20T02:28:20ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-05-011310.3389/fpubh.2025.15274241527424Investigating the efficiency of medical and health resources and its influencing factors in the Yangtze River Delta urban agglomerations: based on the undesirable super-efficiency SBM-Malmquist-Tobit modelYi Chen0Yi Chen1Qianlong Li2Yuting Zhang3Xiaoya Zhang4Handong Zheng5School of Business, Anhui University, Hefei, ChinaSchool of Management, Hefei University of Technology, Hefei, ChinaSchool of Business, Anhui University, Hefei, ChinaSchool of Business, Anhui University, Hefei, ChinaSchool of Business, Anhui University, Hefei, ChinaSchool of Management, Hefei University of Technology, Hefei, ChinaThe medical and health resources in the Yangtze River Delta region are abundant, occupying a significant position in China’s medical and health system with wide service coverage. The efficient allocation of medical and health resources in this region is a key issue affecting the high-quality development of medical and health services. Existing research on the representative region of the Yangtze River Delta Urban Agglomeration remains relatively limited, with insufficient analysis of the efficiency of medical and health resource allocation in the area, as well as a lack of in-depth exploration into its influencing factors and barriers. This study employs the undesirable output super-efficiency SBM model to calculate the static super-efficiency values of medical and health resource allocation in 41 cities of the Yangtze River Delta urban agglomeration from 2015 to 2020. The Malmquist index is utilized to analyze the changes in dynamic efficiency, and the panel Tobit regression model is utilized to analyze the influencing factors of comprehensive efficiency of medical and health resource allocation in the Yangtze River Delta urban agglomeration. The study highlights that the Yangtze River Delta urban agglomeration confronts multiple systemic challenges, such as pronounced disparities in healthcare resource allocation, uneven dissemination of medical technological innovations, insufficiently effective policy implementation, severe pandemic-induced impacts, enduring gaps in urban–rural healthcare resources, and financial accessibility barriers in low-efficiency cities. By integrating empirical evidence from existing studies and performing comparative case analyses, this research puts forward actionable recommendations. These strategies are designed to improve the equity and efficiency of medical and health resource allocation within the region, while offering transferable insights for other regions facing similar institutional and operational challenges.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1527424/fullefficiency of medical and health resourcesinfluencing factorsthe Yangtze River Delta urban agglomerationsundesirable super-efficiency SBM modelMalmquist indexTobit regression model |
| spellingShingle | Yi Chen Yi Chen Qianlong Li Yuting Zhang Xiaoya Zhang Handong Zheng Investigating the efficiency of medical and health resources and its influencing factors in the Yangtze River Delta urban agglomerations: based on the undesirable super-efficiency SBM-Malmquist-Tobit model Frontiers in Public Health efficiency of medical and health resources influencing factors the Yangtze River Delta urban agglomerations undesirable super-efficiency SBM model Malmquist index Tobit regression model |
| title | Investigating the efficiency of medical and health resources and its influencing factors in the Yangtze River Delta urban agglomerations: based on the undesirable super-efficiency SBM-Malmquist-Tobit model |
| title_full | Investigating the efficiency of medical and health resources and its influencing factors in the Yangtze River Delta urban agglomerations: based on the undesirable super-efficiency SBM-Malmquist-Tobit model |
| title_fullStr | Investigating the efficiency of medical and health resources and its influencing factors in the Yangtze River Delta urban agglomerations: based on the undesirable super-efficiency SBM-Malmquist-Tobit model |
| title_full_unstemmed | Investigating the efficiency of medical and health resources and its influencing factors in the Yangtze River Delta urban agglomerations: based on the undesirable super-efficiency SBM-Malmquist-Tobit model |
| title_short | Investigating the efficiency of medical and health resources and its influencing factors in the Yangtze River Delta urban agglomerations: based on the undesirable super-efficiency SBM-Malmquist-Tobit model |
| title_sort | investigating the efficiency of medical and health resources and its influencing factors in the yangtze river delta urban agglomerations based on the undesirable super efficiency sbm malmquist tobit model |
| topic | efficiency of medical and health resources influencing factors the Yangtze River Delta urban agglomerations undesirable super-efficiency SBM model Malmquist index Tobit regression model |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1527424/full |
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