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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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  • Hannah J. Mitchell
  • Adele H. Marshall
  • Mariangela Zenga

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.

Suggested Citation

  • Hannah J. Mitchell & Adele H. Marshall & Mariangela Zenga, 2021. "A joint likelihood approach to the analysis of length of stay data utilising the continuous-time hidden Markov model and Coxian phase-type distribution," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(11), pages 2529-2541, November.
  • Handle: RePEc:taf:tjorxx:v:72:y:2021:i:11:p:2529-2541
    DOI: 10.1080/01605682.2020.1796540
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