Configuration Analysis of Influencing Factors of Technical Efficiency Based on DEA and fsQCA: Evidence from China's Medical and Health Institutions

Risk Manag Healthc Policy. 2021 Jan 8:14:49-65. doi: 10.2147/RMHP.S282178. eCollection 2021.

Abstract

Purpose: This paper aims to measure the technical efficiency of China's medical and health institutions from 2012 to 2017 and outline the path to achieve high-quality development.

Methods: The DEA-Malmquist was used to evaluate the total factor productivity of medical and health institutions in 31 provinces. A fuzzy set Qualitative Comparative Analysis (fsQCA) was used for configuration analysis of determinants affecting technical efficiency.

Results: The average total factor productivity (TFP) of those institutions was 0.965, namely TFP declined averagely by 3.5% annually. The efficiency change and the technical change were 0.998 and 0.967, respectively. The realization paths of high technical efficiency are composed of high fatality rate and high financial allocation-led, high population density and high GDP-led. Low dependency ratio and low financial allocation-led, low fatality rate and low financial allocation-led are the main reasons for low technical efficiency.

Conclusion: Due to advanced medical technology and economic development, major cities like Beijing, Shanghai, and Guangdong have attracted a large number of high-level health personnel, achieving long-term and stable health business growth. Hubei, Anhui, and Sichuan also have made rapid development of health care through appropriate financial subsidies and policy supports. The technical changes in Qinghai, Yunnan, and Inner Mongolia are higher than the national average, but the operation and management level of the medical and health institutions is relatively weak. Henan, Jiangxi, and Heilongjiang have a prominent performance in the efficiency change, but the technical change is weaker than the national average.

Keywords: China’s medical and health institutions; DEA-malmquist; configuration; efficiency; fsQCA.

Grants and funding

This study was funded by Anhui Social Science under Grant No. AHSKQ2019D110.