| Summary: | 碩士 === 國立陽明大學 === 醫務管理研究所 === 104 === Objective: The purpose of this study is to examine the efficiency and productivity change of Taiwan Veteran General Hospitals from 2010 to 2014.
Methods: The studied hospitals were divided into two groups by their scales: the first group included three Veteran Medical Centers, and the second group included five branches of the three medical centers. The efficiency and productivity were evaluated by input-oriented Data Envelopment Analysis (DEA) and Malmquist Productivity Index (PMI). Seven inputs variables (number of all medical staff, number of physicians, number of nurses, number of beds, total costs, medical costs, and total assets) and eight outputs variables (Number of outpatient and acute service, number of admission day, total revenues, outpatient revenues, inpatient revenues, occupancy rates, crude death rate, and re-admitted for acute service to the same hospital within 24 hours rate) were adopted into the DEA model. In order to widely assess efficiency and productivity, we decomposed them into 4 aspects: Overall performance, medical performance, financial performance and quality performance.
Results: We found that (1) the average efficiency scores in the first group were 0.9952 on overall aspect, 0.9824 on medical aspect, 0.988 on financial aspect, and 0.7827 on quality aspect; in the second group, the scores were 0.9974 on overall aspect, 0.97 on medical aspect, 0.9285 on financial aspect, and 0.8887 on quality aspect; (2) the average PMI scores in the first group were 0.998 on overall aspect, 0.991 on medical aspect, 1.002 on financial aspect, and 0.991 on quality aspect; in the second group, the scores were 0.997 on overall aspect, 0.985 on medical aspect, 1.020 on financial aspect, and 0.980 on quality aspect; (3) the results of Spearman’s rank correlation test showed significant positive correlation between overall and medical performance in both efficiency and PMI. Significant positive correlation was also observed between medical and quality performance aspects in PMI.
Conclusion: (1) efficiency and productivity change were not always positively correlated; (2) high overall efficiency did not automatically translated into high medical or higher quality efficiency; (3) medical and quality productivity could affect overall efficiency performance; (4) the number of medical staff, number of beds, and medical service volume were variables that are crucial in assessing the productivity and efficiency of a hospital.
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