An alternative formulation of Coxian phase-type distributions with covariates: Application to emergency department length of stay: Application to emergency department length of stay

Jean Rizk, Cathal Walsh, Kevin Burke

Research output: Contribution to journalArticlepeer-review

Abstract

In this article, we present a new methodology to model patient transitions and length of stay in the emergency department using a series of conditional Coxian phase-type distributions, with covariates. We reformulate the Coxian models (standard Coxian, Coxian with multiple absorbing states, joint Coxian, and conditional Coxian) to take into account heterogeneity in patient characteristics such as arrival mode, time of admission, and age. The approach differs from previous research in that it reduces the computational time, and it allows the inclusion of patient covariate information directly into the model. The model is applied to emergency department data from University Hospital Limerick in Ireland, where we find broad agreement with a number of commonly used survival models (parametric Weibull and log-normal regression models and the semiparametric Cox proportional hazards model).

Original languageEnglish
Pages (from-to)1574-1592
Number of pages19
JournalStatistics in Medicine
Volume40
Issue number6
DOIs
Publication statusPublished - 15 Mar 2021

Keywords

  • covariates
  • Coxian phase-type distributions
  • emergency department
  • length of stay
  • predictions

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