Efficiency and Productivity of Public Hospitals in Serbia Using DEA-Malmquist Model and Tobit Regression Model, 2015-2019.

Aleksandar Medarević,Dejana Vuković

doi:10.3390/ijerph182312475

Abstract

Improving productivity within health systems using limited resources is a matter of great concern. The objectives of the paper were to evaluate the productivity, efficiency, and impact of environmental factors on efficiency in Serbian hospitals from 2015–2019. Data envelopment analysis, Malmquist index and Tobit regression were applied to hospital data from this period, and public hospitals in Serbia exhibited a great variation regarding their capacity and performance. Between five and eight hospitals ran efficiently from 2015 to 2019, and the productivity of public hospitals increased whereas technical efficiency decreased in the same period. Tobit regression indicated that the proportion of elderly patients and small hospital size (below 200 beds) had a negative correlation with technical efficiency, while large hospital size (between 400 and 600 beds), the ratio of outpatient episodes to inpatient days, bed turnover rate and the bed occupation rate had a positive correlation with technical efficiency. Serbian public hospitals have considerable space for technical efficiency improvement and public action must be taken to improve resource utilization.

Highlights

The primary drive in efficiency was scale efficiency, whereas pure technical efficiency decreased in the observed period
These results show a technological improvement resulting from year-over-year technological change (TECH) growth in 23 hospitals from 2015 to 2016 and 37 hospitals from 2018 to 2019
Using the data envelopment analysis (DEA) method, Malmquist total factor productivity index, and the Tobit regression model, our study has empirically shown that there is a large margin for improvement in efficiency in Serbian hospitals

Summary

Introduction

In the case of hospital system performance, this requires accounting for the activities of other health care institutions, legal regulations, dominant service delivery practices, the health status of the population from which the users of health services come, and general sociocultural, socio-economic, and other social factors [2,3]. This complex network of variables affecting hospital performance raises several questions about which factors have the most influence on performance, how these missing links can be uncovered, and how a better understanding of these factors can improve decision-making. In the Serbian context, much of this understanding is currently missing and needs to be examined in order to help strengthen hospital performance across the country

Objectives

Methods

Results

Discussion

Conclusion