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

Louise Burns*, Adele H. Marshall

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish
Title of host publicationRecent Advances in Stochastic Modeling and Data Analysis
PublisherWorld Scientific Publishing
Pages162-171
Number of pages10
ISBN (Electronic)9789812709691
ISBN (Print)9812709681, 9789812709684
DOIs
Publication statusPublished - 01 Jan 2007

Keywords

  • Accident and emergency
  • Naive bayes classification
  • Waiting times

ASJC Scopus subject areas

  • Mathematics(all)

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    Burns, L., & Marshall, A. H. (2007). Identifying the heterogeneity of patients in an accident and emergency department using a bayesian classification model. In Recent Advances in Stochastic Modeling and Data Analysis (pp. 162-171). World Scientific Publishing . https://doi.org/10.1142/9789812709691_0020