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

Record type: Article

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.

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Citation

Channouf, N., L'Ecuyer, P., Ingolfsson, A. and Avramidis, A.N. (2007) The application of forecasting techniques to modeling emergency medical system calls in Calgary, Alberta. Health Care Management Science, 10, (1), pp. 25-45. (doi:10.1007/s10729-006-9006-3).

More information

Published date: 2007
Keywords: emergency medical service, arrivals, time series, simulation, forecasting
Organisations: Operational Research

Identifiers

Local EPrints ID: 55798
URI: http://eprints.soton.ac.uk/id/eprint/55798
ISSN: 1386-9620
PURE UUID: b50b2100-e37d-4a09-a7a6-5c34cbb12d4c

Catalogue record

Date deposited: 06 Aug 2008
Last modified: 17 Jul 2017 14:32

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Contributors

Author: N. Channouf
Author: P. L'Ecuyer
Author: A. Ingolfsson
Author: A.N. Avramidis

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