Operational Benchmarking Analysis and Construction of Managerial Decision-making Path Model for Medical Centers

Medical centers are the highest level of hospitals in the medical system of Taiwan, and they also play the leading role in regional medical system. Moreover, they are provided with higher national health insurance coverage. The scale, equipment, manpower input and provision of medical service of medical centers are superior to those of general hospitals. Therefore, if medical centers can be effectively operated, they can become a great example for management of hospitals and development of national health insurance.
This study intended to investigate the operational efficiency of medical centers from 2005 to 2009. The data sources were two major databases, Medical Care Institution’s Status, and Hospital’s Utilization, from the Department of Health. In terms of cross-sectional data analysis, models such as CRS (Constant Return Scale), VRS (Variable Return Scale), Super-Efficiency, and Context Dependent, were used to perform analyses. In terms of longitudinal data analysis, models such as Malmquist Productivity Index (MPI) and Metafrointer, were used to perform analyses. In Metafrontier, Bilateral model was used to compare the difference in technical efficiency between public and private medical centers. Moreover, nonparametric Rank-Sum Test was used to test the difference. The path diagrams of benchmarking, trend of technology gap ratio of public and private medical centers, and competitive advantages/disadvantages of hospitals were constructed based on the efficiency analysis results of various models.
The basic models (CRS and VRS) of data envelopment analysis found that approximately 43.9% of the hospitals exhibited relatively efficient performance, 57.1% of them exhibited technical efficiency, 43.9% of them exhibited significant scale efficiency, and only one hospital exhibited decreasing returns to scale (the existing scale was too large). Among 9 hospitals with efficient performance, Super-Efficiency model was used to find out the benchmark hospital with the best operational efficiency. The result showed that the operational efficiency of a private medical center in the northern Taiwan was the best. The multi-year time series analysis found that the technological reformation of most of the medical centers improved and so did their productivity index in short-term, mid-term, and long-term analyses, suggesting that the production technology of medical centers were constantly improved. Metafrontier found that average technology gap of public medical centers was lower than that of private medical centers, suggesting that the production technology of public medical centers fell behind. The Bilateral model and the Rank-Sum Test showed that the technical efficiency of public medical centers was significantly poorer than that of private ones. The Context Dependent Model showed that medical centers could be divided into four different levels according to their operational efficiency. There were 9 Level 1 hospitals, 6 Level 2 hospitals, 4 Level 3 hospitals, and 2 Level 4 hospitals. The result showed that the attractiveness of Hospital A was the strongest and other levels of hospitals were characterized by different attractiveness and improvement in progress. This study constructed three managerial decision-making path models based on the results of efficiency analysis on various models: benchmarking path, trend of technology gap ratio path, competitive advantage/disadvantage path, and analyzed the level of hospitals in various managerial decision-making path models and the paths to be improved.
This study used cross-sectional and longitudinal efficiency analysis models to analyze the operational efficiency of medical centers and constructed managerial decision-making path models. It was hoped that medical centers can yield the maximum output by using fewer resources, and their operational performance and competitiveness can be further improved from the perspectives of efficiency analysis and benchmarking, which may be more beneficial to the development of medical centers and national investment in medical care resources.