Evidence on the ability of QLQ-C30 scale scores to validly predict 15D and SF-6D utilities, and to a lesser extent, EQ-5D, has been provided. The modeling equations must be tried in future studies with larger and more diverse samples to confirm their appropriateness for estimating quality-adjusted life-year in cancer-patient trials including only the QLQ-C30.
The main objective of this study was to apply the non-parametric method of Data Envelopment Analysis (DEA) to measure the efficiency of Greek NHS hospitals between 2009–2013. Hospitals were divided into four separate groups with common characteristics which allowed comparisons to be carried out in the context of increased homogeneity. The window-DEA method was chosen since it leads to increased discrimination on the results especially when applied to small samples and it enables year-by-year comparisons of the results. Three inputs -hospital beds, physicians and other health professionals- and three outputs—hospitalized cases, surgeries and outpatient visits- were chosen as production variables in an input-oriented 2-year window DEA model for the assessment of technical and scale efficiency as well as for the identification of returns to scale. The Malmquist productivity index together with its components (i.e. pure technical efficiency change, scale efficiency change and technological scale) were also calculated in order to analyze the sources of productivity change between the first and last year of the study period. In the context of window analysis, the study identified the individual efficiency trends together with “all-windows” best and worst performers and revealed that a high level of technical and scale efficiency was maintained over the entire 5-year period. Similarly, the relevant findings of Malmquist productivity index analysis showed that both scale and pure technical efficiency were improved in 2013 whilst technological change was found to be in favor of the two groups with the largest hospitals.
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