Literature DB >> 25583296

Predicting the number of emergency department presentations in Western Australia: a population-based time series analysis.

Qun Mai1, Patrick Aboagye-Sarfo, Frank M Sanfilippo, David B Preen, Daniel M Fatovich.   

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.
© 2015 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Entities:  

Keywords:  ARIMA; ED demand; VARIMA; modelling and forecasting; time series analysis

Mesh:

Year:  2015        PMID: 25583296     DOI: 10.1111/1742-6723.12344

Source DB:  PubMed          Journal:  Emerg Med Australas        ISSN: 1742-6723            Impact factor:   2.151


  6 in total

Review 1.  An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments.

Authors:  Muhammet Gul; Erkan Celik
Journal:  Health Syst (Basingstoke)       Date:  2018-11-19

2.  The association of Emergency Department presentations in pregnancy with hospital admissions for postnatal depression (PND): a cohort study based on linked population data.

Authors:  Fenglian Xu; Elizabeth A Sullivan; Roberto Forero; Caroline S E Homer
Journal:  BMC Emerg Med       Date:  2017-03-23

3.  Time series forecasting for tuberculosis incidence employing neural network models.

Authors:  Alvaro David Orjuela-Cañón; Andres Leonardo Jutinico; Mario Enrique Duarte González; Carlos Enrique Awad García; Erika Vergara; María Angélica Palencia
Journal:  Heliyon       Date:  2022-07-06

4.  Application of time series analysis in modelling and forecasting emergency department visits in a medical centre in Southern Taiwan.

Authors:  Wang-Chuan Juang; Sin-Jhih Huang; Fong-Dee Huang; Pei-Wen Cheng; Shue-Ren Wann
Journal:  BMJ Open       Date:  2017-12-01       Impact factor: 2.692

5.  Time series model for forecasting the number of new admission inpatients.

Authors:  Lingling Zhou; Ping Zhao; Dongdong Wu; Cheng Cheng; Hao Huang
Journal:  BMC Med Inform Decis Mak       Date:  2018-06-15       Impact factor: 2.796

6.  Forecasting respiratory infectious outbreaks using ED-based syndromic surveillance for febrile ED visits in a Metropolitan City.

Authors:  Tae Han Kim; Ki Jeong Hong; Sang Do Shin; Gwan Jin Park; Sungwan Kim; Nhayoung Hong
Journal:  Am J Emerg Med       Date:  2018-05-10       Impact factor: 2.469

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.