Fuzzy logic applied to a Patient Classification System

The optimization of the clinical staff resources is a very complicated task that can be supported by a set of tools called Patient Classification Systems (PCS). These methods allow the evaluation of the correct number of nurses and healthcare workers needed in order to guarantee an appropriate care level. In this study a PCS tool called MAP is presented, able both to support the staff allocation and to assess the complexity level of each single patient. This method, applicable in all clinical fields, is based on the analysis of the patient state by means of a set of physiological variables characterizing his clinical conditions and his environment. Moreover, we introduce an evolution of MAP based on Fuzzy Logic, in order to produce an instrument more suitable to the daily clinical applications.