title: Predicting the number of emergency department presentations in Western Australia: a population-based time series analysis.
abstract: OBJECTIVE
  To predict the number of ED presentations in Western Australia (WA) in the next 5 years, stratified by place of treatment, age, triage and disposition.
  
  
  METHODS
  We conducted a population-based time series analysis of 7 year monthly WA statewide ED presentation data from the financial years 2006/07 to 2012/13 using univariate autoregressive integrated moving average (ARIMA) and multivariate vector-ARIMA techniques.
  
  
  RESULTS
  ED presentations in WA were predicted to increase from 990,342 in 2012/13 to 1,250,991 (95% CI: 982,265-1,519,718) in 2017/18, an increase of 260,649 (or 26.3%). The majority of this increase would occur in metropolitan WA (84.2%). The compound annual growth rate (CAGR) in metropolitan WA in the next 5 years was predicted to be 6.5% compared with 2.0% in the non-metropolitan area. The greatest growth in metropolitan WA would be in ages 65 and over (CAGR, 6.9%), triage categories 2 and 3 (8.3% and 7.7%, respectively) and admitted (9.8%) cohorts. The only predicted decrease was triage category 5 (-5.3%).
  
  
  CONCLUSIONS
  ED demand in WA will exceed population growth. The highest growth will be in patients with complex care needs. An integrated system-wide strategy is urgently required to ensure access, quality and sustainability of the health system.
authors.affiliation: Clinical Modelling, Health System Improvement Unit, Innovation and Health System Reform, Department of Health Western Australia, Perth, Western Australia, Australia; Centre for Health Services Research, School of Population Health, The University of Western Australia, Perth, Western Australia, Australia.
authors.forename: Qun
authors.initials: Q
authors.lastname: Mai
authors.forename: Patrick
authors.initials: P
authors.lastname: Aboagye-Sarfo
authors.forename: Frank M
authors.initials: FM
authors.lastname: Sanfilippo
authors.forename: David B
authors.initials: DB
authors.lastname: Preen
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Fatovich
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D005544:Forecasting / Q000379:methods; D006301:Health Services Needs and Demand / Q000639:trends; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D014218:Triage / Q000706:statistics & numerical data; D014904:Western Australia; D055815:Young Adult
keywords: ARIMA; ED demand; VARIMA; modelling and forecasting; time series analysis