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dc.contributor.advisorZhou, Yuan
dc.contributor.advisorChen, Victoria
dc.creatorSuley, Eniola Oluwasola
dc.date.accessioned2022-09-15T14:01:09Z
dc.date.available2022-09-15T14:01:09Z
dc.date.created2022-08
dc.date.issued2022-08-04
dc.date.submittedAugust 2022
dc.identifier.urihttp://hdl.handle.net/10106/30977
dc.description.abstractThe purpose of this research is to examine methods for minimizing the influence of boarding on emergency department (ED) crowding outcomes. To accomplish this purpose, this research uses a hybrid systems model framework by combining agent-based simulation, predictive and optimization models to improve ED outcomes such as length-of-stay and left-without-being-seen rates. For the research, different types of simulation models were examined (discrete event and agent-based/discrete event combination) to identify the most parsimonious for studying ED boarding. Predictive models using simulation output were developed to understand the factors that influence future boarding levels as well as generate predictions. Research has previously highlighted how valuable bed assignment/management strategies can be in ensuring minimal length-of-stays in healthcare systems. Such research is limited for EDs specifically, however. This research contributes by directly leveraging the predictions of future boarding levels to develop a bed assignment strategy that can optimize fast track bed capacity to ensure improved ED outcomes.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectEmergency department
dc.subjectHybrid systems modeling
dc.subjectSimulation
dc.subjectBoarding
dc.subjectForecasting
dc.subjectOperations research
dc.titleA HYBRID SYSTEMS MODEL FOR EMERGENCY DEPARTMENT BOARDING MANAGEMENT
dc.typeThesis
dc.degree.departmentIndustrial and Manufacturing Systems Engineering
dc.degree.nameDoctor of Philosophy in Industrial Engineering
dc.date.updated2022-09-15T14:01:09Z
thesis.degree.departmentIndustrial and Manufacturing Systems Engineering
thesis.degree.grantorThe University of Texas at Arlington
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy in Industrial Engineering
dc.type.materialtext
dc.creator.orcid0000-0003-3630-0585


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