Diagnostic and modeling of elderly flow in a French healthcare institution

Fatima E. Hamdani, Malek Masmoudi*, Ahmad Al Hanbali, Fatima Bouyahia, Abdellah Ait Ouahman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


One of the highest priorities in the French health care system is to deal with the continuous growth of the percentage population older than 65 years, expected to reach 31% in 2030. This development poses enormous challenges to the operations of the health care system, especially, related to elder patients. The elderly flow in the hospital services is typically uncertain and subject to variations on the length of stay in each stage and on the path or sequence of stages followed by the patient. For that reason, we propose to model the patient flow in a hospital as a continuous-time Markov chain with an absorbing state representing the elderly discharge from the hospital. Three Markov chains are provided with different levels of details and computation complexity. The first model called aggregated provides a prediction of the length of stay per service, the second model called Coxian provides a reliable prediction of the total length of stay, and the third model called detailed provides a prediction of the length of stay per class of elderly. A classification of elderly based on multiple correspondence technique is considered before the application of the third model. Our models are fitted with the data collected from Roanne Hospital, a typical French health care structure.

Original languageEnglish
Pages (from-to)675-689
Number of pages15
JournalComputers and Industrial Engineering
StatePublished - Oct 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Ltd


  • Coxian
  • Elderly flow
  • Length of stay
  • Likelihood estimation
  • Markov model
  • Statistical techniques

ASJC Scopus subject areas

  • Computer Science (all)
  • Engineering (all)


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