A joint likelihood approach to the analysis of length of stay data utilising the continuous-time hidden Markov model and Coxian phase-type distribution

Hannah J. Mitchell*, Adele H. Marshall, Mariangela Zenga

*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

The Coxian phase-type distribution is a special case of phase-type distribution which represents the time to absorption of a finite Markov chain in continuous time. The distribution is able to capture subjects’ flow through a system but is unable to highlight if there are different pathways caused by an underlying latent factor. Identifying these different pathways will give healthcare providers a deeper insight and understanding of patient flow and allow them to identify and change any potential issues. This paper combines the Coxian phase-type distribution with the continuous-time hidden Markov model to highlight these paths. The theory of combining the Coxian phase-type distribution with the continuous-time hidden Markov model shall be presented along with a simulation study and an application using Italian healthcare data.

Original languageEnglish
JournalJournal of the Operational Research Society
Early online date08 Aug 2020
DOIs
Publication statusEarly online date - 08 Aug 2020

Keywords

  • Continuous-time hidden Markov model
  • Coxian phase-type distribution
  • Healthcare

ASJC Scopus subject areas

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing

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  • A joint likelihood approach to the analysis of length of stay data utilising the continuous-time hidden Markov model and Coxian phase-type distribution

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    Licence: Unspecified

    Embargo ends: 08/08/2021

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