An integrated algorithm for performance evaluation and optimization of resilience engineering factors in healthcare systems
There is a huge and increasing amount of public resources dedicated to healthcare. In order to discover and improve potential inefficiencies, designing a system to assess healthcare performance is necessary. This paper presents a framework for assessment performance of 25 hospitals have been evaluated with respect to resilience factors. The integrated approach of this paper is based on data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT). 11 traditional indicators and 6 resilience factors are identified and selected. In the first step performance of DMUs have been evaluated considering traditional inputs and outputs (type 1). In the next step, resilience factors have been added to the variables of type 1 (type 3). Weighted goal programming and weighted DEA are performed to rank the DMUs according to their efficiencies. The weights are achieved by the effects of each factor in DEA, PCA and NT. The result shows that weighted Goal programming with the weights provided by PCA performs better than weights provided by DEA.
Index Terms - DEA, Healthcare, Performance evaluation, Resilience engineering