Annals of Operations Research

, Volume 276, Issue 1–2, pp 89–108 | Cite as

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

  • Wanlu Gu
  • Neng FanEmail author
  • Haitao Liao
S.I.: Computational Biomedicine


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.


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



We would appreciate the University of Arizona Center for Biomedical Informatics & Biostatistics Department of Biomedical Informatics Services for providing the data. This material is based upon work supported by National Science Foundation Grants CMMI #1634282 and #1635379.


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Systems and Industrial EngineeringUniversity of ArizonaTucsonUSA
  2. 2.Department of Industrial EngineeringUniversity of ArkansasFayettevilleUSA

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