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Health Care Management Science

, Volume 10, Issue 1, pp 25–45 | Cite as

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

  • Nabil Channouf
  • Pierre L’Ecuyer
  • Armann IngolfssonEmail author
  • Athanassios N. Avramidis
Article

Abstract

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.

Keywords

Emergency medical service Arrivals Time series Simulation Forecasting 

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Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  • Nabil Channouf
    • 1
  • Pierre L’Ecuyer
    • 1
  • Armann Ingolfsson
    • 2
    Email author
  • Athanassios N. Avramidis
    • 1
  1. 1.DIROUniversité de MontréalMontréalCanada
  2. 2.School of BusinessUniversity of AlbertaEdmontonCanada

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