Balancing risks and benefits: another approach to optimizing diagnostic tests
Abstract
In our last two articles, we showed that one can quantify the reduction in uncertainty that results from diagnostic testing, an insight that allowed us to describe a method for optimizing the performance of a test by choosing a cutoff that maximizes its information yield. Although minimizing uncertainty is an important feature of diagnostic testing, there are many situations in which diagnostic tests are most appropriately used to balance risks and benefits associated with the various possible courses of action available to a clinician. This article shows how tests can be used to maximize the "expected utility" associated with a clinical decision.
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