title: A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia.
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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Clinical Modelling, Health System Improvement Unit, System Policy and Planning, Department of Health, Western Australia, Australia.
authors.forename: Patrick
authors.initials: P
authors.lastname: Aboagye-Sarfo
authors.affiliation: Clinical Modelling, Health System Improvement Unit, System Policy and Planning, Department of Health, Western Australia, Australia. Electronic address: Qun.Mai@health.wa.gov.au.
authors.forename: Qun
authors.initials: Q
authors.lastname: Mai
authors.affiliation: Clinical Epidemiology Unit, School of Population Health, The University of Western Australia, Australia.
authors.forename: Frank M
authors.initials: FM
authors.lastname: Sanfilippo
authors.affiliation: Centre for Health Services Research, School of Population Health, The University of Western Australia, Australia.
authors.forename: David B
authors.initials: DB
authors.lastname: Preen
authors.affiliation: Centre for Population Health Research, Curtin University, Australia.
authors.forename: Louise M
authors.initials: LM
authors.lastname: Stewart
authors.affiliation: Emergency Medicine, Royal Perth Hospital, The University of Western Australia, Australia.
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Fatovich
mesh_terms: D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005544:Forecasting; D006779:Hospitals, Public; D006801:Humans; D008962:Models, Theoretical; D014904:Western Australia
keywords: ARMA models; Emergency department demand; Modelling and forecasting medical services; Time series analysis; VARMA models; Winters’ method