The application of forecasting techniques to modeling emergency medical system calls in Calgary, Alberta

被引：105

作者：

Channouf N. ^{[1
]}

L'Ecuyer P. ^{[1
]}

Ingolfsson A. ^{[2
]}

Avramidis A.N. ^{[1
]}

机构：

[1] DIRO, Université de Montréal, Montréal, Que.

[2] School of Business, University of Alberta, Edmonton

来源：

Health Care Management Science | 2007年 / 10卷 / 1期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Arrivals; Emergency medical service; Forecasting; Simulation; Time series;

D O I：

10.1007/s10729-006-9006-3

中图分类号：

学科分类号：

摘要：

We develop and evaluate time-series models of call volume to the emergency medical service of a major Canadian city. Our objective is to offer simple and effective models that could be used for realistic simulation of the system and for forecasting daily and hourly call volumes. Notable features of the analyzed time series are: a positive trend, daily, weekly, and yearly seasonal cycles, special-day effects, and positive autocorrelation. We estimate models of daily volumes via two approaches: (1) autoregressive models of data obtained after eliminating trend, seasonality, and special-day effects; and (2) doubly-seasonal ARIMA models with special-day effects. We compare the estimated models in terms of goodness-of-fit and forecasting accuracy. We also consider two possibilities for the hourly model: (3) a multinomial distribution for the vector of number of calls in each hour conditional on the total volume of calls during the day and (4) fitting a time series to the data at the hourly level. For our data, (1) and (3) are superior. © 2006 Springer Science+Business Media, LLC.

引用

页码：25 / 45

页数：20

共 37 条

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