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

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

0.00 Avg rating0 Votes
Article ID: iaor20081849
Country: Netherlands
Volume: 10
Issue: 1
Start Page Number: 25
End Page Number: 45
Publication Date: Feb 2007
Journal: Health Care Management Science
Authors: , , ,
Keywords: time series & forecasting methods, statistics: inference
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.

Reviews

Required fields are marked *. Your email address will not be published.