Exponentional smoothing models for demand forecasting in health care

The main goal of this paper is to present advantages that can be obtained by using quantitative methods to aid demand forecasting in health care sector, specially addressing the ambulance service. In this paper we will use exponential smoothing methods to obtain the most accurate forecast of number of ambulance rides per day. The data set provides us information about the number of ambulance rides per day for three years period. Results show that additive Holt-Winters exponential smoothing method is the most suitable for forecasting the number of ambulance rides per day.