Identifying the heterogeneity of patients in an accident and emergency department using a bayesian classification model

This paper considers the analysis of waiting times in a hospital Accident and Emergency department, in particular the waiting time from the clinician’s decision to admit until actual ward admission. A model is developed which employs a nave Bayes classifier for identification of patients who will require admission to ospital and thus experience such a waiting time. Such waiting times are found to be adequately represented by a lognormal model. Potential exists to expand such a model to include patient covariates.