predicting bed demand in a hospital using neural networks and ARIMA models: a hybrid approach.
MARK P. JOY, Simon Jones · 2005
Abstract. In this paper we describe an investigation into the prediction of emergency bed demand- bed demand due to non-scheduled admissions- within a NHS 1 hospital in South London, U.K. A hybrid methodology, incorporating a neural network and an ARIMA model was used to predict a time series of bed demand. A thorough statistical analysis of the data set was performed as a preliminary phase of the research from which a classical linear predicting model was developed. The prediction errors or residuals from this model were then used as input to a neural network. These methods represent a novel approach to the problem of e±cient bed resource management for hospitals. 1