Productivity change and its driving forces in Chinese healthcare sector

Abstract

Since the last medical reform in 2009, China’s public hospitals have been facing the changes in the institutional environment. However, the effects of reforms have not been received enough attention to deliver evidence-based implications. In this paper, we first assess the efficiency of regional public hospitals from 2011 to 2018, employing a proposed method based on an additive indicator and an aggregate directional distance function (DDF). The method applied allows for decomposing total factor productivity (TFP) indicator into three components, including technical efficiency change (TEC), total productivity (TP) and scale efficiency change (SEC). Second, following the efficiency assessment, we carry post-efficiency analysis to identify the determinants of efficiency of the public hospitals. The results show that annual average TFP growth rate is 1.38%, which is driven mainly by TEC. Regional disparities of public hospitals’ performance are expanding. Almost 75% of the regions considered show a positive TFP growth. The regression results show that the significant determinants of efficiency of regional public hospitals include the price of and demand for health services.

Estimating the efficiency of primary health care services and its determinants: evidence from provincial panel data in China

“…As can be seen from Table 6, the efficiency in the eastern region declined the mainly due to having the smallest decline in TC, and the central region declined the most, by 5.2%, which is contrary to the findings of Chen et al that TFP growth was higher in the interior provinces than in the western region (37). Despite slower economic development, a level of medical resource reserves has been accumulated in recent years in the western region from perennial national counterpart assistance and policy preferences.…”

Performance evaluation for health‐care sectors using a dynamic network data envelopment analysis approach

“…Owing to the easy accessibility of research data, the majority of current papers are using provincial data (Chen, Valdmanis, & Yu, 2020; Ding et al, 2018; Du, 2018; Gong et al, 2019; Guo et al, 2021; Wu et al, 2015). Chen, Chen, et al (2020) employed a proposed method based on an additive indicator and an aggregate directional distance function (DDF) to evaluate the efficiency of public hospitals in China from 2011 to 2018. They followed the regional perspective and considered the provinces as DMUs.…”