Evaluation of healthcare efficiency in China: a three-stage data envelopment analysis of directional slacks-based measure

Abstract

Background: A consensus on the changing pattern of healthcare efficiency in China is current absent. This study tried to identify temporal fluctuations in healthcare efficiency from 2012 to 2021, and conducted a comparative analysis on the performance of 31 regions in China using region-level balanced panel data.

Methods: Employing three-stage data envelopment analysis (DEA) as the analytical framework, we measured healthcare efficiency and its changes using the directional slacks-based measure and global Malmquist-luenberger (GML) indexes. We also decomposed the sources of healthcare inefficiency and extended our analysis to changes in healthcare efficiency across different primary medical service levels and regional economic development tiers.

Results: The average efficiency score of medical institutions (0.956) was slightly higher than that of hospitals (0.930). We found that the average GML indexes of medical institutions in China stood at 0.990, while the average technical change (TC) index was 0.995 and the average efficiency change (EC) index was 0.998 from 2012 to 2021. The GML indexes, TC indexes, and EC indexes of hospitals were 1.002, 1.009, and 0.994, respectively. The healthcare inefficiency for both inputs and desirable outputs in medical institutions was primarily attributed to the redundant numbers of institutions, outpatient visits slacks and inpatient surgery volume slacks, accounting for 50.040, 49.644, and 28.877%, respectively. The undesirable output inefficiency values of medical institutions concerning in-hospital mortality stood at 0.012, while the figure for hospital regarding the average length of stay (LOS) was 0.002. Additionally, healthcare efficiency in both medical institutions and hospitals exhibited an upward trend from 2012 to 2021, corresponding to an increase in the volume of primary medical services, primary medical staff, and the total gross domestic product (GDP).

Conclusion: Total factor productivity (TFP) of medical services declined in China from 2012 to 2021. The excessive number of medical institutions and the slack of medical service volumes were the main sources of healthcare inefficiency. Regions prioritizing primary medical services and boasting higher GDP levels exhibited superior healthcare efficiency. These findings are expected to inform policymakers' efforts in building a value-based and efficient health service system in China.

Keywords: China; directional distance function (DDF); healthcare efficiency; input-output slacks; slacks-based measure (SBM); three-stage data envelopment analysis (DEA).

Figure 1

Trend change of healthcare efficiency among medical institutions and hospitals in China.

Figure 2

Evolution trend of healthcare efficiency among medical institutions from 2012 to 2021.

Figure 3

Inefficiency analysis of China's medical service among input-output indicators in 2012–2021. The input and desirable output indicators here are in units of per 10,000 population. (A) Input inefficiencies. (B) Desirable output inefficiencies. (C) Undesirable output inefficiencies.

Figure 4

Cumulative growth of China's healthcare global malmquist-luenberger (GML) index.