Modeling And Staffing Optimization Of The Emergency Department In Healthcare Systems

In service operations management literature,it is well known that the variability exists in the systems and has a huge impact on service quality.Healthcare system,as a typical example of service systems,the abilities of accurately modeling its arrival process and optimizing its staffing allocation can apparently increase satisfaction of patients and reduce waste of labor.Therefore,it is of great significance to study the modeling and optimization of healthcare system to improve hospital service efficiency and management quality.In the modeling part,based on the emergency department data of an Israel hospital,we firstly build two models – NHPP(Non-homogeneous Poisson Process)model and Power-Law model – to understand the arrival pattern of patients.The results show that NHPP model behaves well while Power-Law model is just partially suitable when fitting the data.Secondly,in order to further evaluate the applicability of the two models,we do the simulation experiments,that is,using one model to test and fit the simulation data of the other model.The results show that the Power-Law model is suitable for fitting the data simulated by NHPP model,but the opposite doesn't hold.These findings suggest that different models have some inner connections and inspire us to explore different methods and approaches when solving research problems.In the optimization part,according to the NHPP model and its fitting results,we propose a probability optimization model to obtain the optimal solution of nursing levels.Furthermore,we discuss the effect of the ratio of hiring cost and waiting cost on the optimal solution.The results show that the smaller the ratio is,the larger the staffing level is.This study enriches the theories of existing research on staffing optimization problem and provides a reference for improving service quality as well as minimizing staffing costs of hospitals.