Application of grey entropy weight cluster in clinical department sorting

Purpose The purpose of this paper is to explore the method of clinical department classification in comprehensive hospital to provide a scientific management reference in performance evaluation. Design/methodology/approach In order to perform the classification of clinical departments, a grey cluster model was constructed. In this model, the benefit index of each clinical department was analyzed using grey associative analysis, and a superior index was chosen to incorporate in this model. Through the relevancy degree of superior index, the authors confirmed the weight of index, and the quintile threshold was calculated by a quintile method and whitening weight functions were constructed. Findings This model, based on grey entropy weight cluster, can reasonably distinguish the merits of clinical departments. From the case we study, neurology?/Cardiovasology?/Integrated disease and Emergency were the optimum assessing department. Originality/value The results demonstrated that the index selection, weight determination, whitening weight functions and model construction in this study could provide technique's reference and application for hospital administrators. It avoids the subjective discrimination and reduces the influence of sample noise, and it is easy to perform while conducting performance evaluation in a comprehensive hospital.