Forecasting the Demand for Emergency Medical Services

dc.contributor.author Steins, Krisjanis
dc.contributor.author Matinrad, Niki
dc.contributor.author Granberg, Tobias
dc.date.accessioned 2019-01-02T23:57:44Z
dc.date.available 2019-01-02T23:57:44Z
dc.date.issued 2019-01-08
dc.description.abstract Accurate forecast of the demand for emergency medical services (EMS) can help in providing quick and efficient medical treatment and transportation of out-of-hospital patients. The aim of this research was to develop a forecasting model and investigate which factors are relevant to include in such model. The primary data used in this study was information about ambulance calls in three Swedish counties during the years 2013 and 2014. This information was processed, assigned to spatial grid zones and complemented with population and zone characteristics. A Zero-Inflated Poisson (ZIP) regression approach was then used to select significant factors and develop the forecasting model. The model was compared to the forecasting model that is currently incorporated in the EMS information system used by the ambulance dispatchers. The results show that the proposed model performs better than the existing one.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2019.225
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59625
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Service Analytics
dc.subject Decision Analytics, Mobile Services, and Service Science
dc.subject Ambulance management, Emergency Medical Services, Forecasting, Statistical modeling
dc.title Forecasting the Demand for Emergency Medical Services
dc.type Conference Paper
dc.type.dcmi Text
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