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A two-level iteration approach for modeling and analysis of rapid response process with multiple deteriorating patients

Author

Listed:
  • Zexian Zeng

    (Northwestern University)

  • Zhenghao Fan

    (Tsinghua University)

  • Xiaolei Xie

    (Tsinghua University)

  • Colleen H. Swartz

    (University of Kentucky Chandler Medical Center)

  • Paul DePriest

    (Baptist Memorial Health Care Corporation)

  • Jingshan Li

    (University of Wisconsin)

Abstract

In acute care, a patient’s clinical deterioration is often a precursor to serious and often fatal outcomes. To reduce the severity and frequency of negative outcomes, care providers need to response rapidly by providing quick evaluation, triage, and treatment to patients with declining conditions. However, a provider’s availability to respond can be constrained when multiple patients are deteriorating at the same time. To study the multiple patients rapid response process, we introduce a network model with complex structures, such as split, merge, and parallel. Iterative methods are presented to evaluate the mean decision time (i.e., the average time from the detection of a patient’s declining to a physician’s treatment decision being made). It is shown that such methods lead to convergent results and high accuracy in performance evaluation. Such a model provides a quantitative tool for healthcare professionals to design and improve rapid response systems.

Suggested Citation

  • Zexian Zeng & Zhenghao Fan & Xiaolei Xie & Colleen H. Swartz & Paul DePriest & Jingshan Li, 2020. "A two-level iteration approach for modeling and analysis of rapid response process with multiple deteriorating patients," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 35-71, March.
    • Handle: RePEc:spr:flsman:v:32:y:2020:i:1:d:10.1007_s10696-019-09347-6
    DOI: 10.1007/s10696-019-09347-6
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    References listed on IDEAS

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    Cited by:

    1. Paola Cappanera & Jingshan Li & Evren Sahin & Nico J. Vandaele & Filippo Visintin, 2020. "Editorial for the special issue on “Modelling, simulation, and optimization in health care”," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 1-5, March.

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