Optimising the service of emergency department in a hospital

Nowadays, the rapidly increasing healthcare cost has become a serious problem because of inefficient usage of medical resources. The Emergency Department (ED) plays a vital role in the hospital system and has critical effects on the overall efficiency in a hospital. The ED deals with patient’s arrival, triage, physician assessment, imaging and laboratory studies, treatment planning, nursing procedures, decisions to discharge or admit access to inpatient beds and physicians. These activities generally occur in a sequential manner and the delayed activities of the patient flow can cause bottlenecking and reduce the service level. Optimising the service of the ED is challenging because the arrival times of patients are dynamic and their expected treatment times are volatile. This paper develops a new ED optimisation model using stochastic mathematical programming approach under limited budget and resource capacity. The objectives of the proposed model are for increasing the system efficiency, serving more patients in specific time, or providing the same quality of the service with the use of less medical resources. A numerical investigation is presented and demonstrates that high-quality solutions are obtainable for industry-scale applications in a reasonable time. Computational experiments have been conducted using CPLEX and ExtendSim to solve the ED-Stochastic Optimisation Mixed Integer Programming model and ED-Simulation model sequentially. Real data for Royal Brisbane and Women's Hospital (RBWH) is used in this paper to validate the proposed solution approach.