Abstract

Hospital costs play a significant role in national budgets. To some degree, patients are suffering from lack of vacant beds and caretakers. Emergency Department (ED) crowding causes a series of negative effects, e.g. medical errors, poor patient treatment and general patient dissatisfaction. One road to improve the typical clinical system is to describe the patient flow in a model of the system and how the system is constrained by available equipment, beds and personnel. This paper focuses on modeling and simulation of the capacity of utilities and how using advanced control techniques can enable intelligent scheduling, leading to smooth patient flow to reduce emergency department crowding. By comparing different models, the most efficient ones will be identified for implementation. The idea is that hospitals can use the proposed models to predict the future resident patient number in each department/ward. The caretakers can use the predicted results with other information to make decisions of ad-mission of the intake patients, find the optimal pathway for the patients to minimize the residence time, and make intelligent scheduling to reduce the queueing length in the hospital.