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Hospitals Evaluation Using Restricted Data Envelopment Analysis With Canonical Correlation Analysis Limits

机译:使用典型相关分析限制使用受限制数据包络分析的医院评估

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This study presents an approach for the definition of weight restrictions in Data Envelopment Analysis (DEA). To this end, the results of a Canonical Correlation Analysis (CCA) developed with the same DEA variables are used as restrictions for DEA weight calculation. Thus, in this approach the limits of the Wong-Beasley DEA method are chosen without interference from a decision maker. As an example, weight restrictions for a DEA model (Constant Returns to Scale (CRS)-model) were obtained through the Wong-Beasley method, which was applied to a dataset of 12 general hospitals in the city of Rio de Janeiro-Brazil, 2016. The DEA had as inputs the variables number of deaths and days of stay; and as outputs number of admissions and number of beds, and the rankings of a “restricted” and an “unrestricted” model were compared by a Spearman correlation procedure. The CCA had R = 0.92; and the Spearman correlation between methods was 0.82; p < 0.01. No “zero weight” coefficient was obtained by the new procedure. In conclusion, a better discrimination was achieved, and a problem that would have arisen in the classical CRS implementation (variables receiving zero weight) was avoided, allowing for a better classification procedure for the evaluated units.
机译:本研究提出了一种关于数据包络分析(DEA)中重量限制的方法的方法。为此,用相同的DEA变量开发的规范相关分析(CCA)的结果用作DEA重量计算的限制。因此,在这种方法中,选择了Wong-Beasley DEA方法的限制而不从决策者干扰。作为示例,通过Wong-Beasley方法获得DEA模型的重量限制(常量返回到比例(CRS)-MODEL),该方法应用于12位Rio de Janeiro-Brazil市12张综合医院的数据集, 2016年。DEA有输入变量的死亡人数和逗留日期;并且作为产出的录取数和床的数量,并通过Spearman相关过程进行了“限制”和“无限制”模型的排名。 CCA有r = 0.92;方法之间的Spearman相关性为0.82; P <0.01。通过新程序获得“零重量”系数。总之,实现了更好的歧视,避免了在经典CRS实现(接收零重量的变量)中出现的问题,允许评估单元的更好分类过程。

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