Measuring Efficiency of Regional Healthcare: Application of the DEA Approach

Purpose of the study: Comparative analysis of the efficiency of regional healthcare systems in the Russian Federation. Research methods: The research is based on a two-stage Data Envelopment Analysis (DEA). First, efficiency is estimated using DEA models. Then, a Tobit regression is used to identify exogenous (environmental) factors that significantly impact efficiency levels. Two DEA models were applied: an output-oriented model and an input-oriented model, both with variable returns to scale. The results were then compared. Results. Eighteen regions of the Russian Federation were found to be efficient according to both DEA models, while 67 others were identified as inefficient. The rank, as well as the set of reference decision-making units (DMUs) for the inefficient DMUs, depend largely on the model chosen. According to both models, the healthcare system of the Chukotka Autonomous Okrug demonstrates the lowest efficiency of all. Regression analysis revealed that lifestyle factors significantly impact the efficiency of regional healthcare systems. This highlights the importance of efforts to encourage a culture of self-preservation behaviour in Russian society. Conclusion. The DEA approach used in this study has several advantages. It enables estimating the technical efficiency of DMUs, along with producing a set of reference DMUs and quantitative estimates of input and output slacks. This makes it particularly well-suited for estimating healthcare efficiency. For this approach to be adopted more widely, however, the choice of inputs, outputs and model specification must be rigorously justified.