Efficiency evaluation of public hospitals in China from 2010 to 2019: A data envelopment analysis (Preprint)

BACKGROUND Equality in healthcare services is a significant issue worldwide, especially in developing countries. As a developing country, China has a large population and area, and an imbalance in economic development has existed for many years. The government is making significant efforts to address this problem. Studying the efficiency of the healthcare system plays a core role in developing the level of medical services. Public hospitals shoulder the essential responsibility of supporting healthcare issues. Recently, many studies in China have assessed the efficiency of hospitals at the provincial and national levels to identify problems in equality. This study aims to evaluate the efficiency of hospitals in the whole country divided into several regions for ten years to identify the differences between regions and reasons for these to make suggestions for supporting the government’s sustained reforms. OBJECTIVE This study aims to evaluate the efficiency of hospitals in the whole country divided into several regions for ten years to identify the differences among regions and reasons for those to make suggestions for supporting the government's sustained reforms. METHODS Data envelopment analysis (DEA) is a tool for measuring the efficiency and productivity of decision-making units (DMUs) to envelop observed input-output vectors. The term “decision-making unit” was introduced to cover an agency or region. Hospital efficiency is crucial in assessing the level healthcare services. Using the data envelopment analysis (DEA) method, scale efficiency, technological efficiency, and so on were considered in the model. Moreover, the Malmquist Productivity Index (MPI) was introduced to evaluate annual changes in efficiency. These two methods showed the situation of the region’s efficiency and trend of changes over a certain period. An input-oriented model was selected for the purposes of this study. RESULTS A significant increase was evident in the three types of efficiency from 2010 to 2019. The situation regarding constant efficiency was significant for the western and eastern areas. The efficiency of the two areas was approximately 0.9, which is close to 1, indicating excellent efficiency. Regarding technical efficiency, the central area demonstrated lower efficiency. For scale efficiency, the three regions had almost the same efficiency level. The Malmquist Index’s efficiency change from 2011 to 2016 was greater than or equal to 1. For technical change, for the first ten years except for the third year, all values were greater than 1. Regarding the pure efficiency change, except for the last year, all values were greater than 1, but the value of the previous year was 0.991. CONCLUSIONS In China, the western and central areas demonstrated efficiency improvement after medical reforms were implemented. This means more health resources are concentrated in two places to meet people’s needs and decrease the inequality of allocation in health services because of the imbalance in economic development. Noteworthy is that the management of Chinese healthcare institutions was always excellent.