dc.contributor.author | Ordu, Muhammed | |
dc.contributor.author | Demir, Eren | |
dc.contributor.author | Tofallis, Christopher | |
dc.date.accessioned | 2019-01-18T16:30:03Z | |
dc.date.available | 2019-01-18T16:30:03Z | |
dc.date.issued | 2019-01-06 | |
dc.identifier.citation | Ordu , M , Demir , E & Tofallis , C 2019 , ' A decision support system for demand and capacity modelling of an accident and emergency department ' , Health Systems . https://doi.org/10.1080/20476965.2018.1561161 | |
dc.identifier.issn | 2047-6965 | |
dc.identifier.other | ORCID: /0000-0001-6150-0218/work/62748532 | |
dc.identifier.uri | http://hdl.handle.net/2299/20994 | |
dc.description | © 2019 Operational Research Society. | |
dc.description.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. | en |
dc.format.extent | 26 | |
dc.format.extent | 1831632 | |
dc.language.iso | eng | |
dc.relation.ispartof | Health Systems | |
dc.subject | Demand and capacity modelling | |
dc.subject | discrete event simulation | |
dc.subject | forecasting | |
dc.subject | accident and emergency department | |
dc.subject | decision support system | |
dc.subject | Health care | |
dc.subject | health care | |
dc.subject | Health Information Management | |
dc.subject | Health Policy | |
dc.subject | Health Informatics | |
dc.subject | Computer Science Applications | |
dc.title | A decision support system for demand and capacity modelling of an accident and emergency department | en |
dc.contributor.institution | Hertfordshire Business School | |
dc.contributor.institution | Statistical Services Consulting Unit | |
dc.description.status | Peer reviewed | |
dc.date.embargoedUntil | 2020-01-06 | |
dc.identifier.url | http://www.scopus.com/inward/record.url?scp=85063266136&partnerID=8YFLogxK | |
rioxxterms.versionofrecord | 10.1080/20476965.2018.1561161 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |