Health systems efficiency in China and ASEAN, 2015-2020: a DEA-Tobit and SFA analysis application.

OBJECTIVE: To evaluate the health systems efficiency in China and Association of Southeast Asian Nations (ASEAN) countries from 2015 to 2020. DESIGN: Health efficiency analysis using data envelopment analysis (DEA) and stochastic frontier approach analysis. SETTING: Health systems in China and ASEAN countries. METHODS: DEA-Malmquist model and SFA model were used to analyse the health system efficiency among China and ASEAN countries, and the Tobit regression model was employed to analyse the factors affecting the efficiency of health system among these countries. RESULTS: In 2020, the average technical efficiency, pure technical efficiency and scale efficiency of China and 10 ASEAN countries' health systems were 0.700, 1 and 0.701, respectively. The average total factor productivity (TFP) index of the health systems in 11 countries from 2015 to 2020 was 0.962, with a decrease of 1.4%, among which the average technical efficiency index was 1.016, and the average technical progress efficiency index was 0.947. In the past 6 years, the TFP index of the health system in Malaysia was higher than 1, while the TFP index of other countries was lower than 1. The cost efficiency among China and ASEAN countries was relatively high and stable. The per capita gross domestic product (current US$) and the urban population have significant effects on the efficiency of health systems. CONCLUSIONS: Health systems inefficiency is existing in China and the majority ASEAN countries. However, the lower/middle-income countries outperformed high-income countries. Technical efficiency is the key to improve the TFP of health systems. It is suggested that China and ASEAN countries should enhance scale efficiency, accelerate technological progress and strengthen regional health cooperation according to their respective situations.

Balanced scorecard-based performance evaluation of Chinese county hospitals in underdeveloped areas.

Objective Since the Guangxi government implemented public county hospital reform in 2009, there have been no studies of county hospitals in this underdeveloped area of China. This study aimed to establish an evaluation indicator system for Guangxi county hospitals and to generate recommendations for hospital development and policymaking. Methods A performance evaluation indicator system was developed based on balanced scorecard theory. Opinions were elicited from 25 experts from administrative units, universities and hospitals and the Delphi method was used to modify the performance indicators. The indicator system and the Topsis method were used to evaluate the performance of five county hospitals randomly selected from the same batch of 2015 Guangxi reform pilots. Results There were 4 first-level indicators, 9 second-level indicators and 36 third-level indicators in the final performance evaluation indicator system that showed good consistency, validity and reliability. The performance rank of the hospitals was B > E > A > C > D. Conclusions The performance evaluation indicator system established using the balanced scorecard is practical and scientific. Analysis of the results based on this indicator system identified several factors affecting hospital performance, such as resource utilisation efficiency, medical service price, personnel structure and doctor-patient relationships.

Equity in health financing of Guangxi after China's universal health coverage: evidence based on health expenditure comparison in rural Guangxi Zhuang autonomous region from 2009 to 2013.

BACKGROUND: Healthcare financing should be equitable. Fairness in financial contribution and protection against financial risk is based on the notion that every household should pay a fair share. Health policy makers have long been concerned with protecting people from the possibility that ill health will lead to catastrophic financial payments and subsequent impoverishment. A number of studies on health care financing equity have been conducted in some provinces of China, but in Guangxi, we found such observation is not enough. What is the situation in Guagnxi? A research on rural areas of Guangxi can add knowledge in this field and help improve the equity and efficiency of health financing, particularly in low-income citizens in rural countries, is a major concern in China's medical sector reform. METHODS: Socio-economic characteristics and healthcare payment data were obtained from two rounds of household surveys conducted in 2009 (4634 respondents) and 2013 (3951 respondents). The contributions of funding sources were determined and a progressivity analysis of government healthcare subsidies was performed. Household consumption expenditure and total healthcare payments were calculated and incidence and intensity of catastrophic health payments were measured. Summary indices (concentration index, Kakwani index and Gini coefficient) were obtained for the sources of healthcare financing: indirect taxes, out of pocket payments, and social insurance contributions. RESULTS: The overall health-care financing system was regressive. In 2013, the Kakwani index was 0.0013, the vertical effect of all the three funding sources was 0.0001, and some values exceeded 100%, indicating that vertical inequity had a large influence on causing total health financing inequity. The headcount of catastrophic health payment declined sharply between 2009 and 2013, using total expenditure (from 7.3% to 1.2%) or non-food expenditure (from 26.1% to 7.5%) as the indicator of household capacity to pay. CONCLUSION: Our study demonstrates an inequitable distribution of government healthcare subsidies in China from 2009 to 2013, and the inequity was reduced, especially in rural areas. Future healthcare reforms in China should not only focus on expanding the coverage, but also on improving the equity of distribution of healthcare benefits.