Evaluating readmission rates and discharge planning by analyzing the length-of-stay of patients

Wanlu Gu, Neng Fan, Haitao Liao

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


The length-of-stay (LOS) is an important quality metric in health care, and the use of phase-type (PH) distribution provides a flexible method for modeling LOS. In this paper, we model the patient flow information collected in a hospital for patients of distinct diseases, including headache, liveborn infant, alcohol abuse, acute upper respiratory infection, and secondary cataract. Based on the results obtained from fitting Coxian PH distributions to the LOS data, the patients can be divided into different groups. By analyzing each group to find out their common characteristics, the corresponding readmission rate and other useful information can be evaluated. Furthermore, a comparison of patterns for each disease is analyzed. We conclude that it is important to offering better service and avoiding waste of sources, by the analysis of the relations between groups and readmission. In addition, comparing the patterns within distinct diseases, a better decision for assigning resources and improving the insurance policy can be made.

Original languageEnglish (US)
Pages (from-to)89-108
Number of pages20
JournalAnnals of Operations Research
Issue number1-2
StatePublished - May 1 2019


  • Healthcare quality
  • Length-of-stay
  • Markov chains
  • Phase-type distribution
  • Readmission rate

ASJC Scopus subject areas

  • General Decision Sciences
  • Management Science and Operations Research


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