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Dimensioning the Park of Mechanical Ventilators on an Intensive Care Unit of a Hospital

机译:在医院的重症监护室确定机械通气设备的空间

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It is described how the common problem of dimensioning (or resizing) a randomly requested life-support equipment can be solved, resorting not to the classic analytical methods proposed by the theory of waiting lines in Operational Research, which requires the acceptance of some simplifying assumptions, but rather to the Monte Carlo simulation technique, which allows greater flexibility in the construction of a sufficiently representative model of reality. The method is applied to an Intensive Care Unit (ICU) of a Cardiology Department of a Hospital in Lisbon, in which an increase of the number of pulmonary ventilators is believed to be necessary to meet the influx of patients.The methodology for constructing a representative model of this reality in EXCEL® is described. This model can be updated with new data at any time and provides the expected values of various performance indicators (expected occupancy rates, average and maximum waiting times, average and maximum number of waiting patients), thus providing a suitable support tool for decision making. By keeping the pertinent set of variables updated in the model, decision makers may find the most adequate solution at any time, in the long run of the service.However, the use of the Monte-Carlo simulation technique is very limited, due to the lack of its dissemination and also to the weak dominance of the underlying and necessary statistical background of potential users to discriminate between inputs and interpret the outputs of a simulation model.Aiming to contribute to the increasing dissemination of simulation techniques, as a tool for describing complex problems and for decision support, we present this communication, describing synthetically, the steps taken for the construction of a sufficiently representative model of a system composed by mechanical ventilators in the above mentioned ICU.
机译:描述了如何解决随机请求的生命支持设备的尺寸(或尺寸调整)的常见问题,而不求助于运筹学中等待线理论提出的经典分析方法,该方法需要接受一些简化的假设,而是采用蒙特卡洛(Monte Carlo)模拟技术,该技术在构建具有足够代表性的现实模型时可以提供更大的灵活性。该方法已应用于里斯本一家医院的心脏病科的重症监护病房(ICU),在该病房中需要增加肺呼吸机的数量才能满足患者涌入的需求。描述了EXCEL®中这种现实的模型。该模型可以随时使用新数据进行更新,并提供各种性能指标的预期值(预期占用率,平均和最大等待时间,平均和最大等待患者数),从而为决策提供了合适的支持工具。通过在模型中保持相关变量集的更新,决策者可能会在服务的长期运行中随时找到最合适的解决方案。但是,由于缺乏传播,也缺乏潜在用户潜在和必要的统计背景的主导地位,无法区分输入和解释模拟模型的输出,旨在促进模拟技术的传播,作为描述复杂情况的工具问题和决策支持,我们以综合的方式介绍了此通信,以描述为构建上述ICU中由机械呼吸机组成的系统的具有足够代表性的模型所采取的步骤。

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