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dc.contributor.authorOrdu, Muhammed
dc.contributor.authorDemir, Eren
dc.contributor.authorTofallis, Christopher
dc.date.accessioned2019-01-18T16:30:03Z
dc.date.available2019-01-18T16:30:03Z
dc.date.issued2019-01-06
dc.identifier.citationOrdu , 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.issn2047-6965
dc.identifier.otherPURE: 16098103
dc.identifier.otherPURE UUID: 611a3e4c-d8bc-4b99-a0b2-8bca4dfe6930
dc.identifier.otherORCID: /0000-0001-6150-0218/work/62748532
dc.identifier.urihttp://hdl.handle.net/2299/20994
dc.description© 2019 Operational Research Society.
dc.description.abstractAccident 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.language.isoeng
dc.relation.ispartofHealth Systems
dc.rightsEmbargoed
dc.subjectDemand and capacity modelling
dc.subjectdiscrete event simulation
dc.subjectforecasting
dc.subjectaccident and emergency department
dc.subjectdecision support system
dc.subjectHealth care
dc.titleA decision support system for demand and capacity modelling of an accident and emergency departmenten
dc.contributor.institutionHertfordshire Business School
dc.contributor.institutionStatistical Services Consulting Unit
dc.description.statusPeer reviewed
dc.date.embargoedUntil2020-01-06
dc.relation.schoolHertfordshire Business School
dc.description.versiontypeFinal Accepted Version
dcterms.dateAccepted2019-01-06
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1080/20476965.2018.1561161
rioxxterms.licenseref.uriOther
rioxxterms.licenseref.startdate2020-01-06
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.date.embargo2020-01-06
herts.rights.accesstypeEmbargoed


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