Citation

Ordu M, Demir E, Tofallis C. Health Syst. (Basingstoke) 2020; 9(1): 31-56.

Affiliation

Hertfordshire Business School, University of Hertfordshire, Hatfield, UK.

Copyright

(Copyright © 2020, Informa - Taylor and Francis Group)

DOI

10.1080/20476965.2018.1561161

PMID

32284850

PMCID

PMC7144331

Abstract

Accident and emergency (A&E) departments in England have been struggling against severe capacity constraints. In addition, A&E demands have been increasing year on year. In this study, our aim was to develop a decision support system combining discrete event simulation and comparative forecasting techniques for the better management of the Princess Alexandra Hospital in England. We used the national hospital episodes statistics data-set including period April, 2009 - January, 2013. Two demand conditions are considered: the expected demand condition is based on A&E demands estimated by comparing forecasting methods, and the unexpected demand is based on the closure of a nearby A&E department due to budgeting constraints. We developed a discrete event simulation model to measure a number of key performance metrics. This paper presents a crucial study which will enable service managers and directors of hospitals to foresee their activities in future and form a strategic plan well in advance.

© Operational Research Society 2019.

Language: en

Keywords

Demand and capacity modelling; accident and emergency department; decision support system; discrete event simulation; forecasting; health care