Uncover the predictive structure of healthcare efficiency applying a bootstrapped data envelopment analysis

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One of the main problems in efficiency analysis is to determinate the environmental variables that have an impact on the production process. This paper shows that applying bootstrap to data envelopment analysis (DEA) before performing classification and regression trees (CART) increase the quality of the results. In particular, employing data on the Italian Health System, the paper highlights that bias corrected DEA allows to individuate variables affecting health efficiency which would remain undiscovered when the traditional DEA model is applied.

论文关键词:Bootstrap,Data envelopment analysis (DEA),Classification and regression trees,Environmental variables,Health policy,Efficiency,Patient mobility

论文评审过程:Available online 22 February 2012.

论文官网地址:https://doi.org/10.1016/j.eswa.2012.02.074