A Comprehensive and Integrated Hospital Decision Support System for Efficient and Effective Healthcare Services Delivery Using Discrete Event Simulation

dc.authorscopusid 57207935311
dc.authorscopusid 15623143200
dc.authorscopusid 6603249436
dc.authorscopusid 23481897200
dc.contributor.author Ordu, M.
dc.contributor.author Demir, E.
dc.contributor.author Tofallis, C.
dc.contributor.author Gunal, M.M.
dc.date.accessioned 2025-03-10T21:19:09Z
dc.date.available 2025-03-10T21:19:09Z
dc.date.issued 2023
dc.department Fenerbahçe University en_US
dc.department-temp Ordu M., Osmaniye Korkut Ata University, Faculty of Engineering and Natural Sciences, Department of Industrial Engineering, Osmaniye, 80010, Turkey; Demir E., University of Hertfordshire, Hertfordshire Business School, Hatfield, AL10 9AB, United Kingdom; Tofallis C., University of Hertfordshire, Hertfordshire Business School, Hatfield, AL10 9AB, United Kingdom; Gunal M.M., Fenerbahce University, Faculty of Engineering and Architecture, Department of Industrial Engineering, Istanbul, 34758, Turkey en_US
dc.description.abstract The difficulty that hospital management has been experiencing over the past decade in balancing demand and capacity needs is unprecedented in the United Kingdom. Due to a shortage of capacity, hospitals cannot treat all patients. We developed a whole hospital-level decision support system to assess and respond to the needs of local populations. We integrated a comparative forecasting approach and discrete event simulation modelling using Hospital Episode Statistics and local datasets. It is clear from the literature that this level of whole hospital simulation model has never been developed before (an innovative decision support system). First, the demands of all hospital specialties were forecasted, and the forecasts were embedded into the simulation model as input. Secondly, a simulation model was developed to capture the patient pathway of all specialties. The model integrates every component of a hospital to aid with efficient and effective use of scarce resources (e.g., staff and beds). As a result, the hospital can meet the increasing demand with its current resources. According to the scenario analysis, the hospital bed occupancy rate will reach the national target (i.e., 85%), and the total hospital revenue will increase by approximately 13%, with a 10% increase in A&E and outpatient and a 20% increase in inpatient demand. In conclusion, the hospital-level simulation model can become a crucial instrument for decision-makers to provide an efficient service for hospitals in England and other parts of the world. © 2023 The Authors en_US
dc.identifier.doi 10.1016/j.health.2023.100248
dc.identifier.issn 2772-4425
dc.identifier.scopus 2-s2.0-85170411100
dc.identifier.scopusquality Q2
dc.identifier.uri https://doi.org/10.1016/j.health.2023.100248
dc.identifier.uri https://hdl.handle.net/20.500.14627/854
dc.identifier.volume 4 en_US
dc.identifier.wosquality N/A
dc.language.iso en en_US
dc.publisher Elsevier Inc. en_US
dc.relation.ispartof Healthcare Analytics en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 13
dc.subject Discrete Event Simulation en_US
dc.subject Efficiency And Productivity en_US
dc.subject Experimental Design en_US
dc.subject Forecasting en_US
dc.subject Healthcare Services Delivery en_US
dc.subject Hospital Decision Support System en_US
dc.title A Comprehensive and Integrated Hospital Decision Support System for Efficient and Effective Healthcare Services Delivery Using Discrete Event Simulation en_US
dc.type Article en_US
dspace.entity.type Publication

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