A decision support system for demand and capacity modelling of an accident and emergency department. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Ordu, Muhammed; Demir, Eren; Tofallis, Chris
• Is Part Of: Health systems. Volume 9:Issue 1(2020)
• Page Start: 31
• Page End: 56
• Publication Date: 2020-01-02
• Subjects: Demand and capacity modelling -- discrete event simulation -- forecasting -- accident and emergency department -- health care -- decision support system; 610.285
• DOI: 10.1080/20476965.2018.1561161
• Languages: English
• ISSNs: 2047-6965

Abstract

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.