预测急诊科就诊情况。
Forecasting emergency department presentations.
作者信息
Champion Robert, Kinsman Leigh D, Lee Geraldine A, Masman Kevin A, May Elizabeth A, Mills Terence M, Taylor Michael D, Thomas Paulett R, Williams Ruth J
机构信息
Department of Mathematics and Statistics, La Trobe University, PO Box 199, Bendigo, VIC 3552, Australia.
出版信息
Aust Health Rev. 2007 Feb;31(1):83-90. doi: 10.1071/ah070083.
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.
目的
预测维多利亚州地区一家医院急诊科每月的就诊患者数量。
方法
预测所依据的数据是2000年至2005年急诊科每月的就诊人数。使用的统计预测方法是指数平滑法和Box-Jenkins方法，通过软件包SPSS 14.0版（SPSS公司，美国伊利诺伊州芝加哥）实现。
结果
对于特定的时间序列，在可用模型中，简单季节性指数平滑模型提供了最佳预测性能。2006年前五个月的预测与观察到的就诊数据比较吻合。
结论
时间序列分析被证明是预测急诊科需求的一种有用且易于获得的工具。这种经验中的方法和教训可能有助于其他医院和急诊科进行自身分析以辅助规划。
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