Data Envelopment Analysis and Super Efficiency Assessment of the Healthcare Industry

Abstract

This study assesses the present efficiency level of the Indian healthcare industry and suggests the areas in which it can improve operational and financial performance. The study uses panel data from 19 decision-making units (DMUs) from 31^st March 2016 to 31^st March 2020. These data samples have been derived from the company’s income and financial statements. We employ an input-oriented DEA (Data envelopment analysis) mechanism, i.e., Cost and input minimization, instead of an output-oriented DEA emphasising profit and Production maximization. The DEA was performed through SPSS 26 version, DEA Excel Solver Pro, and R-3.4.1 software to analyze the companies' efficiency levels. The Malmquist productivity index (MPI) and Tobit regression were used to assess and compare the companies' performance during the period under consideration. Super efficiency has also been calculated using eight different prototypes based on orientation, radially, and slacks using non-parametric rank statistics, namely Mann-Whitney U-test (MW), Kolmogorov-Smirnov test (KS), and Kruskal-Wallies test (KW). Overall, we find from the technical efficiency, pure technical, and scale efficiency scores that out of 19 companies, four companies are technically efficient using the CCR and the BCC model. Further results show that 12 companies are technically efficient for the period under review using the BCC model. Few known studies have used input-oriented DEA models to assess the efficiency level of Indian healthcare. According to our information, this study is unique in examining the efficiency level of the Indian healthcare sector over five years. In addition, the Tobit results show that domestic institutional investors and mutual funds significantly impact efficiency scores.