TY  - JOUR
PY  - 2020//
TI  - A decision support system for demand and capacity modelling of an accident and emergency department
JO  - Health systems (Basingstoke, England)
A1  - Ordu, Muhammed
A1  - Demir, Eren
A1  - Tofallis, Chris
SP  - 31
EP  - 56
VL  - 9
IS  - 1
N2  - 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.<br><br>© Operational Research Society 2019.<p />  <p>Language: en</p>
LA  - en
SN  - 2047-6965
UR  - http://dx.doi.org/10.1080/20476965.2018.1561161
ID  - ref1
ER  -