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. 2019 Dec 2;16(23):4847.
doi: 10.3390/ijerph16234847.

Has the Efficiency of China's Healthcare System Improved after Healthcare Reform? A Network Data Envelopment Analysis and Tobit Regression Approach

Guangwen Gong  1   2 , Yingchun Chen  1   2 , Hongxia Gao  1   2 , Dai Su  1   2 , Jingjing Chang  1   2
Affiliations

Has the Efficiency of China's Healthcare System Improved after Healthcare Reform? A Network Data Envelopment Analysis and Tobit Regression Approach

Guangwen Gong et al. Int J Environ Res Public Health. .

Abstract

Background: A healthcare system refers to a typical network production system. Network data envelopment analysis (DEA) show an advantage than traditional DEA in measure the efficiency of healthcare systems. This paper utilized network data envelopment analysis to evaluate the overall and two substage efficiencies of China's healthcare system in each of its province after the implementation of the healthcare reform. Tobit regression was performed to analyze the factors that affect the overall efficiency of healthcare systems in the provinces of China.

Methods: Network DEA were obtained on MaxDEA 7.0 software, and the results of Tobit regression analysis were obtained on StataSE 15 software. The data for this study were acquired from the China health statistics yearbook (2009-2018) and official websites of databases of Chinese national bureau.

Results: Tobit regression reveals that regions and government health expenditure effect the efficiency of the healthcare system in a positive way: the number of high education enrollment per 100,000 inhabitants, the number of public hospital, and social health expenditure effect the efficiency of healthcare system were negative.

Conclusion: Some provincial overall efficiency has fluctuating increased, while other provincial has fluctuating decreased, and the average overall efficiency scores were fluctuations increase.

Keywords: Tobit regression; efficiency; healthcare reform; healthcare system; network data envelopment analysis.

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Conflict of interest statement

The data used in this study were public data, did not involve any primary data collection and no individual privacy data is included. This work was supported by the National Science Foundation of China, grant number (71673101). The funders had no role in the study design, data collection, and analysis; decision to publish; or preparation of the manuscript. The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Annual averages of overall efficiency and efficiency for the sub-stages.
See this image and copyright information in PMC

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