Mode of arrival aware models for forecasting flow of patient and length of stay in emergency departments

Basit Öğe Kaydı
dc.authoridAtaman, Mustafa Gökalp/0000-0003-4468-0020
dc.authoridsariyer, gorkem/0000-0002-8290-2248
dc.authorwosidAtaman, Mustafa Gökalp/O-4644-2017
dc.authorwosidsariyer, gorkem/AAA-1524-2019
dc.contributor.authorAtaman, Mustafa Gökalp
dc.contributor.authorSariyer, Gorkem
dc.date.accessioned2023-03-22T19:47:18Z
dc.date.available2023-03-22T19:47:18Z
dc.date.issued2022
dc.departmentBelirleneceken_US
dc.description.abstractAim: Flow of patients to emergency departments (EDs) and their stays in EDs (ED-LOS) depend significantly on their arrival modes. In this study, developing effective models for forecasting patient flow and length of stay (LOS) in EDs by considering arrival modes led better planning of ED operations. Materials and Methods: In this study, by categorizing the mode of arrival into two, self-arrived in and by ambulance, autoregressive integrative moving average (ARIMA) models are applied for forecasting four time series: daily number of patients self arrived/arrived by an ambulance and average LOS of patients self-arrived/arrived by an ambulance. The models are validated with real-life data received from a large-scaled urban ED in Izmir, Turkey. Results: While seasonal ARIMA is proper for forecasting the daily number of patients on both modes, non-seasonal models are proper for forecasting the average LOS. The mean absolute percentage errors (MAPE) for the models of four time series are 5,432%, 13,085%, 9,955% and 10.984%, respectively. Thus, daily arrivals to the EDs show seasonality patterns. Conclusion: By emphasizing the impact of mode of arrival in ED context, this study can be used to aid the strategic decision making in the EDs for capacity planning to enable efficient use of the ED resources.en_US
dc.identifier.doi10.4274/eajem.galenos.2021.27676
dc.identifier.endpage44en_US
dc.identifier.issn2149-5807
dc.identifier.issn2149-6048
dc.identifier.issue1en_US
dc.identifier.startpage34en_US
dc.identifier.trdizinid519892en_US
dc.identifier.urihttps://doi.org/10.4274/eajem.galenos.2021.27676
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/519892
dc.identifier.urihttps://hdl.handle.net/20.500.14034/598
dc.identifier.volume21en_US
dc.identifier.wosWOS:000837749400006en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.publisherGalenos Publ Houseen_US
dc.relation.journalEurasian Journal Of Emergency Medicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectEmergency departmenten_US
dc.subjectforecastingen_US
dc.subjectpatient flowen_US
dc.subjectlength of stayen_US
dc.subjectARIMAen_US
dc.subjectVisitsen_US
dc.subjectDemanden_US
dc.subjectPresentationsen_US
dc.subjectVariablesen_US
dc.subjectVolumeen_US
dc.titleMode of arrival aware models for forecasting flow of patient and length of stay in emergency departmentsen_US
dc.typeArticleen_US

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