Assessment of efficiencies of group B public hospitals with TWO hundred and above beds

Efficiency is expressed as the capacity to reach the maximum results with minimum effort or cost. Measuring efficiency ensures that almost all of the inputs' capacities are converted to output with minimal loss. One of the objectives of the Ministry of Health is to focus on improving the efficiency of public hospitals. In this study, it was aimed to evaluate the activities of 44 group B public hospitals with 200 and more beds in 2013 and 2016 specificaly. Financial and service delivery data of hospitals were used as input and output variables of this study. The efficiencies were analyzed in four different models (M1-M4), with one of the basic methods of Data Envelopment Analysis, input-oriented constant returns to scale method. In addition, Shapiro-Wilk test was used to determine normality and Wilcoxon, Kruskal-Wallis and Friedman tests were used to analyze the statistical significance of other comparisons. As a result of the assessment of the hospitals, in 2013 the efficiency percentage of hospitals were varied between 50.0% and 79.5%. In contrast, the efficiency percentage of hospitals in 2016 were also varied between 34.1% and 70.5%. In the yearly assessment, compared to 2013, the number of efficient hospitals and the average of efficiency points of hospitals in 2016 decreased in M1, M3 and M4. However, in M2 on the contrary both the number of efficient hospitals and the average of efficiency points increased in 2016 compared to 2013. But, for both cases the difference was found to be statistically insignificant. In order for hospitals to be effective in both years (2013, 2016), the variables that need to be changed the most were "Non-Labor Fixed Expenses, Other Fixed Expenses" in M1 and M3 and "Total Closed Area (m2)" in M2 and M4. The differences that arise by comparing the results of the models, with only financial or service delivery variables, which are applied in this study, brought different dimentions to assess the efficiency of hospitals and different intervention areas accordingly. Keywords: Public hospitals, efficiency, data envelopment analysis (DEA)