Abstract:
The objectives of the study are to measure the hospital efficiency of public hospitals and identify the determinants of hospital efficiency. The first stage is to measure hospital efficiency and total factor productivity (TFP) index before and after universal coverage policy using DEA. The second stage is to identify the determinants of hospitals efficiency with Tobit regression analysis. All 805 public hospitals were included in the study. It is found that they are operating at 59% level of efficiency. Only 35 (4.3%) are technically efficient hospitals that were located on the frontier. About 16% of all inefficient hospitals have efficiency scores more than 80% and 56% of those have less than 60%. The large hospitals are more efficient than small ones. The average pure technical efficiency score of all public hospitals is 67.3%. There are only 130 (16.1%) pure technically efficient hospitals. In the inefficient group, 100% of regional hospitals, 81.8% of general hospitals have scores more than 60%. While 56% of community hospitals has scores less than 60%. The average scale efficiency score of all public hospitals is 88.6%. Most hospitals are operating very close to their optimal size. Regarding the pattern of scale inefficiency, decreasing returns to scale is the predominant form of scale inefficiency observed in regional and general hospitals while about 96.2% of small community hospitals were operating on increasing return to scale. For cost efficiency analysis, the average cost, technical and allocative efficiency scores of all public hospitals are 53.1, 56.9 and 93.4% respectively. The regional and general hospitals are more cost and technical efficient than community hospitals. All levels of public hospitals are much highly allocatively efficient at efficiency score more than 90%. The results of TFP index measurement showed that the scores of overall technical efficiency change, technical change and total factor productivity change are 1.300, 0.647 and 0.841 respectively. The scores of pure technical and scale efficiency change that decomposed of overall technical efficiency change are 1.037 and 1.253 respectively. The results of Tobit regression showed that the numbers of bed, occupancy rate, geographic location and service complexity are associated with technical efficiency. All aboved information could be used as a tool to support policy formulation process for health resuorce management of health care organization. In addition, these informations could be used as a guideline for hospital management.
