Capacity Balancing Algorithm for Placement of Observation Patients: Assessing the Effect on ED Crowding

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dc.contributor.authorTilson, Vera
dc.contributor.authorXiao, Shiya
dc.contributor.authorPachamanova, Dessislava
dc.contributor.authorDwyer-Matzky, Keely
dc.date.accessioned2023-12-26T18:40:14Z
dc.date.available2023-12-26T18:40:14Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2023.406
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other6065bed9-1d97-4a84-b39f-f80bf48460b9
dc.identifier.urihttps://hdl.handle.net/10125/106789
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDecision Support for Healthcare Processes and Services
dc.subjectcapacity-balancing resource allocation
dc.subjected crowding
dc.subjectou admissions
dc.titleCapacity Balancing Algorithm for Placement of Observation Patients: Assessing the Effect on ED Crowding
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractWe examine the queueing performance of a real-time capacity-balancing (CB) algorithm for routing patients from the Emergency Department (ED) to an Observation Unit (OU) or to an inpatient ward. We study the significance of relative bed capacities between the ward and the OU. OUs are designed for specific patient types, with shorter expected hospital stays. By redirecting patients and reserving OU capacity for those who benefit most, overall hospital stay durations are reduced. However, high ward utilization may cause longer ED waiting times. To prevent ED crowding, implementing a CB algorithm requires careful analysis of ward and OU long-run utilization.
dcterms.extent10 pages
prism.startingpage3364

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Decision Support for Healthcare Processes and Services