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dc.contributor.authorAboagye-Sarfo, P.
dc.contributor.authorMai, Q.
dc.contributor.authorSanfilippo, F.
dc.contributor.authorPreen, D.
dc.contributor.authorStewart, Louise
dc.contributor.authorFatovich, D.
dc.date.accessioned2017-01-30T13:54:50Z
dc.date.available2017-01-30T13:54:50Z
dc.date.created2015-08-20T20:00:40Z
dc.date.issued2015
dc.date.submitted2015-08-21
dc.identifier.citationAboagye-Sarfo, P. and Mai, Q. and Sanfilippo, F. and Preen, D. and Stewart, L. and Fatovich, D. 2015. A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia. Journal of Biomedical Informatics. 57: pp. 62-63.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/36279
dc.identifier.doi10.1016/j.jbi.2015.06.022
dc.description.abstract

Objective: To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters’ models. Methods: Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters’ models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Results: Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters’ method. Conclusion: VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand.

dc.publisherAcademic Press
dc.subjectVARMA models
dc.subjectEmergency department demand
dc.subjectARMA models
dc.subjectModelling and forecasting medical services
dc.subjectWinters’ method
dc.subjectTime series analysis
dc.titleA comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia
dc.typeJournal Article
dcterms.dateSubmitted2015-08-21
dcterms.source.volume57
dcterms.source.startPage62
dcterms.source.endPage63
dcterms.source.issn1532-0464
dcterms.source.titleJournal of Biomedical Informatics
curtin.digitool.pid228469
curtin.pubStatusPublished
curtin.refereedTRUE
curtin.departmentCentre for Population Health Research
curtin.identifier.scriptidPUB-HEA-CPH-PB-89750
curtin.accessStatusOpen access


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