Evaluating the operational efficiency of the compact urban medical group in Qiqihar based on the three-stage DEA and Malmquist index model

Datos Bibliográficos

ID22079751
AutoresXing Ye (0000-0003-1769-6035, Huazhong University of Science and Technology), Ye Xing, Chong Tian (0000-0002-3231-9409, Huazhong University of Science and Technology), Jiayu Wang (0000-0002-3953-6270, Huazhong University of Science and Technology), Yanting Liu (0000-0001-5333-8927, Huazhong University of Science and Technology), Jun Tao (0000-0003-0610-4305, Wuhan Pulmonary Hospital), Taoyu Lin (0000-0003-0384-0331, The Fifth People’s Hospital of Suzhou), Yan Zhou (0000-0002-3659-5881, Jinan University), Yue Wang (0000-0001-8527-9175, Huazhong University of Science and Technology), Xue Bai (0000-0002-0502-7291, Huazhong University of Science and Technology, autor de correspondencia)
Año2025
Volumen13
Páginas1636769-1636769
Fecha de publicación2025-08-18
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Public Health (JOURNAL)
Identificadores de la revistaISSN: 2296-2565 • E-ISSN: 2296-2565
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1636769
PMID40900701
OpenAlexW4413297674
IdiomaEN
Citas recibidas1
Referencias citadas56

Background: Since the establishment of medical alliances, a key issue regarding their ability to better address the imbalance in China's medical resources lies in the changes in operational efficiency before and after their formation. This study focuses on urban medical groups, a reform model of medical alliances, and systematically analyzes the changes in operational efficiency before and after the group-based reform, aiming to provide empirical evidence for improving the group-based management model. Methods: This study employs a dual-method framework combining three-stage DEA for static efficiency evaluation and Malmquist index analysis for dynamic assessment. Data from 14 medical institutions inform the analysis, utilizing three carefully selected input and three output variables to comprehensively evaluate resource allocation patterns within the medical consortium. Results: The first-stage DEA evaluation of Qiqihar's 14 medical institutions reveals baseline efficiency scores with comprehensive efficiency at 0.839, pure technical efficiency at 0.950, and scale efficiency at 0.882. SFA regression identifies regional GDP as positively influencing operational performance while population density and fiscal appropriations demonstrate negative effects. After adjusting for environmental variables and random disturbances in the third-stage analysis, the recalculated efficiency metrics show significant changes. The adjusted comprehensive efficiency declines to 0.774, reflecting more accurate performance measurement after accounting for external factors. Meanwhile, pure technical efficiency improves to 0.971, suggesting strong managerial performance when isolated from environmental constraints. Scale efficiency decreases to 0.800, indicating suboptimal operational size remains a persistent challenge. Conclusion: Medical institution planning must carefully consider local healthcare resource distribution, economic conditions, population characteristics, and varying medical needs to determine appropriate operational scales and infrastructure development. Health authorities should enhance coordination among medical groups by breaking institutional barriers and promoting resource sharing to create synergistic collaborations that improve overall service quality and efficiency. Continuous infrastructure improvements remain essential for meeting evolving public healthcare demands while maintaining optimal service delivery standards

Biology · Econometrics · Economic growth · Economics · Malmquist index · Operations management · Operations research · Physics · Productivity · Statistics · Computer Science · Efficiency Analysis Using DEA · Global Health Care Issues · Healthcare Systems and Reforms · Mathematics