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A Stochastic Model to Measure Patient Effects Stemming from Hospital-Acquired Infections

Author

Listed:
  • George T. Kastner

    (Instituto de Estudios Superiores de Administration, Caracas, Venezuela)

  • Richard H. Shachtman

    (University of North Carolina, Chapel Hill, North Carolina)

Abstract

We introduce a Markov chain model to represent a patient's path in terms of the number and type of infections s/he may have acquired during a hospitalization period. The model allows for categories of patient diagnoses, surgery, the four major types of nosocomial (hospital-acquired) infections, and discharge or death Data from a national medical records survey including 58,647 patients enable us to estimate transition probabilities and, ultimately, perform statistical tests of fit, including a validation test. Novel parameterizations (functions of the transition matrix) are introduced to answer research questions on time-dependent infection rates, time to discharge or death as a function of patient diagnostic groups and conditional infection rates reflecting intervening variables (e.g., surgery).

Suggested Citation

  • George T. Kastner & Richard H. Shachtman, 1982. "A Stochastic Model to Measure Patient Effects Stemming from Hospital-Acquired Infections," Operations Research, INFORMS, vol. 30(6), pages 1105-1133, December.
    • Handle: RePEc:inm:oropre:v:30:y:1982:i:6:p:1105-1133
    DOI: 10.1287/opre.30.6.1105
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    Cited by:

    1. Côté, Murray J. & Stein, William E., 2000. "An Erlang-based stochastic model for patient flow," Omega, Elsevier, vol. 28(3), pages 347-359, June.

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