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.