Informed and uninformed empirical therapy policies

Abstract

We argue that a proper distinction must be made between informed and uninformed decision making when setting empirical therapy policies, as this allows to estimate the value of gathering more information and 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 policies. In the uninformed setting, the best adaptive policy allows to reduce the average cumulative infected patient-days over two years by 39.3% (95% CI: 30.3% -48.1%) compared to the combination therapy. Choosing empirical therapy policies while knowing the exact parameter values allows to further decrease the cumulative infected patient-days on average by 3.9% (95% CI: 2.1% -5.8%). In our setting, the benefit of perfect information might be offset by increased drug consumption.

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