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Modeling the Movement of Coronary Patients within a Hospital by Semi-Markov Processes

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  • Edward P. C. Kao

    (Yale University, New Haven, Connecticut)

Abstract

This paper studies the use of a collection of semi-Markov processes (referred to as paths ) to describe the movement of coronary patients within a hospital. Two earlier papers by the same author [ Health Serv. Res. 7, 191–208 (1972) and IEEE Trans , on Systems, Man, and Cybernetics SMC-3, 327–336 (1973)] define the state of a patient by a specific set of care requirements dictated by his “state of health;” this paper considers a state definition based solely on the care unit in which the patient resides. This new state definition is simpler to administer, especially when patients of different diagnoses are included in the model. The paper uses field data to estimate the parameters of the underlying processes and evaluate the adequacy of using such a model. Procedures involving simple matrix operations are introduced to obtain length-of-stay and patient-day statistics in each care unit as well as in the hospital. An approach for reconstructing the original arrival distribution based on admission data is also presented with application.

Suggested Citation

  • Edward P. C. Kao, 1974. "Modeling the Movement of Coronary Patients within a Hospital by Semi-Markov Processes," Operations Research, INFORMS, vol. 22(4), pages 683-699, August.
    • Handle: RePEc:inm:oropre:v:22:y:1974:i:4:p:683-699
    DOI: 10.1287/opre.22.4.683
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    Cited by:

    1. Hideaki Takagi & Yuta Kanai & Kazuo Misue, 2017. "Queueing network model for obstetric patient flow in a hospital," Health Care Management Science, Springer, vol. 20(3), pages 433-451, September.
    2. Mabel C. Chou & Mahmut Parlar & Yun Zhou, 2017. "Optimal Timing to Initiate Medical Treatment for a Disease Evolving as a Semi-Markov Process," Journal of Optimization Theory and Applications, Springer, vol. 175(1), pages 194-217, October.
    3. Côté, Murray J. & Stein, William E., 2000. "An Erlang-based stochastic model for patient flow," Omega, Elsevier, vol. 28(3), pages 347-359, June.
    4. Natalia Yankovic & Linda V. Green, 2011. "Identifying Good Nursing Levels: A Queuing Approach," Operations Research, INFORMS, vol. 59(4), pages 942-955, August.

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