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

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 cau...

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Bibliographic Details
Published inThe Journal of the Operational Research Society Vol. 72; no. 11; pp. 2529 - 2541
Main Authors Mitchell, Hannah J., Marshall, Adele H., Zenga, Mariangela
Format Journal Article
LanguageEnglish
Published Taylor & Francis 02.11.2021
Subjects
Continuous-time hidden Markov model
Coxian phase-type distribution
Healthcare
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Summary: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.
ISSN:0160-5682
1476-9360
DOI:10.1080/01605682.2020.1796540