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Forecasting emergency department presentations.
Aust Health Rev. 2007 Feb; 31(1):83-90.AH

Abstract

OBJECTIVE

To forecast the number of patients who will present each month at the emergency department of a hospital in regional Victoria.

METHODS

The data on which the forecasts are based are the number of presentations in the emergency department for each month from 2000 to 2005. The statistical forecasting methods used are exponential smoothing and Box-Jenkins methods as implemented in the software package SPSS version 14.0 (SPSS Inc, Chicago, Ill, USA).

RESULTS

For the particular time series, of the available models, a simple seasonal exponential smoothing model provides optimal forecasting performance. Forecasts for the first five months in 2006 compare well with the observed attendance data.

CONCLUSIONS

Time series analysis is shown to provide a useful, readily available tool for predicting emergency department demand. The approach and lessons from this experience may assist other hospitals and emergency departments to conduct their own analysis to aid planning.

Authors+Show Affiliations

Department of Mathematics and Statistics, La Trobe University, PO Box 199, Bendigo, VIC 3552, Australia. r.champion@latrobe.edu.auNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

17266491

Citation

Champion, Robert, et al. "Forecasting Emergency Department Presentations." Australian Health Review : a Publication of the Australian Hospital Association, vol. 31, no. 1, 2007, pp. 83-90.
Champion R, Kinsman LD, Lee GA, et al. Forecasting emergency department presentations. Aust Health Rev. 2007;31(1):83-90.
Champion, R., Kinsman, L. D., Lee, G. A., Masman, K. A., May, E. A., Mills, T. M., Taylor, M. D., Thomas, P. R., & Williams, R. J. (2007). Forecasting emergency department presentations. Australian Health Review : a Publication of the Australian Hospital Association, 31(1), 83-90.
Champion R, et al. Forecasting Emergency Department Presentations. Aust Health Rev. 2007;31(1):83-90. PubMed PMID: 17266491.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Forecasting emergency department presentations. AU - Champion,Robert, AU - Kinsman,Leigh D, AU - Lee,Geraldine A, AU - Masman,Kevin A, AU - May,Elizabeth A, AU - Mills,Terence M, AU - Taylor,Michael D, AU - Thomas,Paulett R, AU - Williams,Ruth J, PY - 2007/2/3/pubmed PY - 2007/4/25/medline PY - 2007/2/3/entrez SP - 83 EP - 90 JF - Australian health review : a publication of the Australian Hospital Association JO - Aust Health Rev VL - 31 IS - 1 N2 - OBJECTIVE: To forecast the number of patients who will present each month at the emergency department of a hospital in regional Victoria. METHODS: The data on which the forecasts are based are the number of presentations in the emergency department for each month from 2000 to 2005. The statistical forecasting methods used are exponential smoothing and Box-Jenkins methods as implemented in the software package SPSS version 14.0 (SPSS Inc, Chicago, Ill, USA). RESULTS: For the particular time series, of the available models, a simple seasonal exponential smoothing model provides optimal forecasting performance. Forecasts for the first five months in 2006 compare well with the observed attendance data. CONCLUSIONS: Time series analysis is shown to provide a useful, readily available tool for predicting emergency department demand. The approach and lessons from this experience may assist other hospitals and emergency departments to conduct their own analysis to aid planning. SN - 0156-5788 UR - https://www.unboundmedicine.com/medline/citation/17266491/Forecasting_emergency_department_presentations_ L2 - http://www.publish.csiro.au/journals/abstractHTML.cfm?J=AH&V=31&I=1&F=AH070083abs.XML DB - PRIME DP - Unbound Medicine ER -