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

机译:多种劣化患者快速响应过程建模与分析的两级迭代方法

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摘要

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.
机译:在急性护理中,患者的临床劣化通常是严重和经常致命的结果的前兆。 为了减少负面结果的严重程度和频率,护理提供者需要通过向患者提供快速的评估,分类和治疗条件下降的患者来迅速响应。 但是,当多个患者同时恶化时,提供者可以受到限制的可用性。 为研究多名患者快速响应过程,我们介绍了一种复杂结构的网络模型,例如分裂,合并和并行。 提出了迭代方法以评估平均决策时间(即,从检测到医生治疗决定的患者拒绝的平均时间)。 结果表明,这些方法导致了会聚结果和性能评估的高精度。 这种模型为医疗保健专业人员提供了设计和改进快速响应系统的定量工具。

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