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

Zexian Zeng (), Zhenghao Fan (), Xiaolei Xie (), Colleen H. Swartz (), Paul DePriest () and Jingshan Li ()
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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

Flexible Services and Manufacturing Journal, 2020, vol. 32, issue 1, No 3, 35-71

Abstract: 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.

Keywords: Rapid response; Decision time; Mean waiting time; Multiple patients; Patient deterioration; Iterations (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10696-019-09347-6

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