{"title":"Study on the efficiency of health resource allocation in the western region of China-based on three-stage DEA and Tobit regression analysis.","authors":"Dongxue Zhao, Hua Huang, Yu Zhang, Shuanghang Li","doi":"10.1186/s12913-025-12630-y","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To analyze the allocation efficiency of health resources in the western region of China, and to explore the influence of external environmental factors on the allocation efficiency, to provide reference for optimizing the allocation of resources.</p><p><strong>Methods: </strong>In this study, we employed a three-stage Data Envelopment Analysis (DEA) model alongside Tobit regression analysis to evaluate the efficiency of health resource allocation and explore the factors that influence it across western China. This analysis focused on data from 2021, covering ten provinces. Through this combined approach, the study aimed to uncover key insights into the determinants and variations in resource allocation efficiency within western China.</p><p><strong>Results: </strong>Following the three-stage DEA analysis, the results showed that health resource allocation in western China achieved a comprehensive efficiency of 0.979, a pure technical efficiency of 0.980, and scale efficiency of 0.999. Notably, six provinces, specifically Chongqing, Guizhou, Yunnan, Tibet, Qinghai, and Ningxia, maintained efficient performance both before and after adjustment. The extensive efficiency of 3 provinces, including Sichuan, Shaanxi, and Gansu decreased. Xinjiang's comprehensive efficiency improved. The comprehensive efficiency of the southwest area was higher than that of the northwest area. The Tobit regression analysis revealed that factors such as per capita disposable income, the share of government spending in total healthcare expenditure, and the medical service price index significantly influenced the efficiency of health resource allocation in Western China.</p><p><strong>Conclusion: </strong>Environmental factors appeared to inflate the efficiency estimates of health resource allocation in China's western region, with considerable disparities across different areas. To address these issues, the government should advance reforms in medical resource distribution, enhance management practices and technology, optimize resource allocation structures, and minimize resource wastage. At the same time, strategies should be formulated according to provincial characteristics, and interregional cooperation and resource sharing should be strengthened to achieve complementary advantages and common development.</p>","PeriodicalId":9012,"journal":{"name":"BMC Health Services Research","volume":"25 1","pages":"480"},"PeriodicalIF":2.7000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11959864/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Health Services Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12913-025-12630-y","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: To analyze the allocation efficiency of health resources in the western region of China, and to explore the influence of external environmental factors on the allocation efficiency, to provide reference for optimizing the allocation of resources.
Methods: In this study, we employed a three-stage Data Envelopment Analysis (DEA) model alongside Tobit regression analysis to evaluate the efficiency of health resource allocation and explore the factors that influence it across western China. This analysis focused on data from 2021, covering ten provinces. Through this combined approach, the study aimed to uncover key insights into the determinants and variations in resource allocation efficiency within western China.
Results: Following the three-stage DEA analysis, the results showed that health resource allocation in western China achieved a comprehensive efficiency of 0.979, a pure technical efficiency of 0.980, and scale efficiency of 0.999. Notably, six provinces, specifically Chongqing, Guizhou, Yunnan, Tibet, Qinghai, and Ningxia, maintained efficient performance both before and after adjustment. The extensive efficiency of 3 provinces, including Sichuan, Shaanxi, and Gansu decreased. Xinjiang's comprehensive efficiency improved. The comprehensive efficiency of the southwest area was higher than that of the northwest area. The Tobit regression analysis revealed that factors such as per capita disposable income, the share of government spending in total healthcare expenditure, and the medical service price index significantly influenced the efficiency of health resource allocation in Western China.
Conclusion: Environmental factors appeared to inflate the efficiency estimates of health resource allocation in China's western region, with considerable disparities across different areas. To address these issues, the government should advance reforms in medical resource distribution, enhance management practices and technology, optimize resource allocation structures, and minimize resource wastage. At the same time, strategies should be formulated according to provincial characteristics, and interregional cooperation and resource sharing should be strengthened to achieve complementary advantages and common development.
期刊介绍:
BMC Health Services Research is an open access, peer-reviewed journal that considers articles on all aspects of health services research, including delivery of care, management of health services, assessment of healthcare needs, measurement of outcomes, allocation of healthcare resources, evaluation of different health markets and health services organizations, international comparative analysis of health systems, health economics and the impact of health policies and regulations.