Coxian Phase-Type Regression Models for Understanding the Relationship Between Patient Attributes, Overcrowding, and Length of Stay in Hospital Emergency Departments

Laura M. Boyle*, Adele H. Marshall, Mark Mackay

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Hospital emergency departments (EDs) operate under significant pressure worldwide. Overcrowding is a frequent occurrence, caused by a combination of high presentation numbers, and long delays in the admission of patients due to a lack of availability of hospital beds. Understanding the factors which influence length of stay (LoS) in the ED is a vital aspect of any strategy to improve patient flow. The determinants of ED patient flow are complex and varied, due to the diverse population of patients competing for limited resources. This research uses Coxian phase-type distributions to cluster patients into groups by their LoS, using a unique diagram for improved communication of patient flow issues. A novel application of survival analysis is presented to simultaneously evaluate the effect of patient attributes, system factors, and overcrowding on ED LoS. The approach is demonstrated with an application to data from a hospital in South Australia.

Original languageEnglish
Title of host publicationHealth Care Systems Engineering (HCSE 2019): Proceedings
EditorsValerie Belanger, Nadia Lahrichi, Ettore Lanzarone, Semih Yalcindag
PublisherSpringer
Pages53-64
Number of pages12
ISBN (Print)9783030396930
DOIs
Publication statusPublished - 16 Apr 2020
Event4th International Conference on Health Care Systems Engineering, HCSE 2019 - Montréal, Canada
Duration: 30 May 201901 Jun 2019

Publication series

NameSpringer Proceedings in Mathematics and Statistics
Volume316
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017

Conference

Conference4th International Conference on Health Care Systems Engineering, HCSE 2019
CountryCanada
CityMontréal
Period30/05/201901/06/2019

Keywords

  • Coxian phase-type distributions
  • Emergency department overcrowding
  • Hospital length of stay
  • Patient flow

ASJC Scopus subject areas

  • Mathematics(all)

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