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dc.contributor.authorOrdu, Muhammed
dc.contributor.authorDemir, Eren
dc.contributor.authorTofallis, Chris
dc.contributor.authorGunal, Murat
dc.date.accessioned2020-02-17T02:09:04Z
dc.date.available2020-02-17T02:09:04Z
dc.date.issued2020-02-03
dc.identifier.citationOrdu , M , Demir , E , Tofallis , C & Gunal , M 2020 , ' A novel healthcare resource allocation decision support tool: A forecasting-simulation-optimization approach ' , Journal of the Operational Research Society , vol. 2021 , no. 3 , 1700186 . https://doi.org/10.1080/01605682.2019.1700186
dc.identifier.issn0160-5682
dc.identifier.otherORCID: /0000-0001-6150-0218/work/68990516
dc.identifier.urihttp://hdl.handle.net/2299/22281
dc.description© 2020 Informa UK Limited, trading as Taylor & Francis Group. This is an accepted manuscript of an article published by Taylor & Francis in Journal of the Operational Research Society on 03 Feb 2020, available online: https://doi.org/10.1080/01605682.2019.1700186.
dc.description.abstractThe increasing pressures on the healthcare system in the UK are well documented. The solution lies in making best use of existing resources (e.g. beds), as additional funding is not available. Increasing demand and capacity shortages are experienced across all specialties and services in hospitals. Modelling at this level of detail is a necessity, as all the services are interconnected, and cannot be assumed to be independent of each other. Our review of the literature revealed two facts; First an entire hospital model is rare, and second, use of multiple OR techniques are applied more frequently in recent years. Hybrid models which combine forecasting, simulation and optimization are becoming more popular. We developed a model that linked each and every service and specialty including A&E, and outpatient and inpatient services, with the aim of, (1) forecasting demand for all the specialties, (2) capturing all the uncertainties of patient pathway within a hospital setting using discrete event simulation, and (3) developing a linear optimization model to estimate the required bed capacity and staff needs of a mid-size hospital in England (using essential outputs from simulation). These results will bring a different perspective to key decision makers with a decision support tool for short and long term strategic planning to make rational and realistic plans, and highlight the benefits of hybrid models.en
dc.format.extent1613042
dc.language.isoeng
dc.relation.ispartofJournal of the Operational Research Society
dc.subjectHealthcare
dc.subjectdecision support system
dc.subjectdiscrete event simulation
dc.subjectforecasting
dc.subjectinteger linear programming
dc.subjectManagement Information Systems
dc.subjectStrategy and Management
dc.subjectManagement Science and Operations Research
dc.subjectMarketing
dc.titleA novel healthcare resource allocation decision support tool: A forecasting-simulation-optimization approachen
dc.contributor.institutionHertfordshire Business School
dc.contributor.institutionStatistical Services Consulting Unit
dc.description.statusPeer reviewed
dc.date.embargoedUntil2021-02-03
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85078948647&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1080/01605682.2019.1700186
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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