Abstract

We argue that a proper distinction must be made between informed and uninformed decision making when setting empirical therapy policies, as this allows one to estimate the value of gathering more information about the pathogens and their transmission and thus to set research priorities. We rely on the stochastic version of a compartmental model to describe the spread of an infecting organism in a health care facility and the emergence and spread of resistance to two drugs. We focus on information and uncertainty regarding the parameters of this model. We consider a family of adaptive empirical therapy policies. In the uninformed setting, the best adaptive policy allowsone to reduce the average cumulative infected patient days over 2 years by 39.3% (95% confidence interval (CI), 30.3–48.1%) compared to the combination therapy. Choosing empirical therapy policies while knowing the exact parameter values allows one to further decrease the cumulative infected patient days by 3.9% (95% CI, 2.1–5.8%) on average. In our setting, the benefit of perfect information might be offset by increased drug consumption.

中文翻译：

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知情和不知情的经验疗法政策

摘要

我们认为，在制定经验性治疗政策时，必须在知情和不知情的决策之间做出适当的区分，因为这可以使人们估计收集有关病原体及其传播的更多信息的价值，从而确定研究重点。我们依靠隔室模型的随机版本来描述感染性生物在卫生保健机构中的传播以及对两种药物的耐药性的出现和传播。我们专注于有关此模型参数的信息和不确定性。我们考虑了一系列适应性的经验疗法政策。在不知情的情况下，与联合疗法相比，最佳的适应性政策允许人们将2年的平均累积感染患者天数减少39.3％（95％置信区间（CI），30.3-48.1％）。在知道确切参数值的同时选择经验疗法策略，可以使平均累积感染患者天数平均减少3.9％（95％CI，2.1-5.8％）。在我们的环境中，完美信息的好处可能会因药物消耗增加而被抵消。