The siren song of simple tools that predict mortality.

Hippocrates recognized that determining a patient’s prognosis is one of physicians’ most important responsibilities.1 Although research on prognosis has been outpaced by that on etiology and therapy, scientists have made great strides in characterizing the risk factors for death across all areas of medicine.2 However, this deeper understanding of prognosis comes at the expense of simplicity; in many cases providers must now integrate dozens of factors—implicitly or explicitly—to accurately estimate an individual’s prognosis. Since surmounting this complexity is challenging, providers often use heuristics or rules of thumb to reduce prognostic assessments to simple judgments.3 These heuristics, although helpful in many situations, may lead to biased estimates of prognosis.3,4 For example, a provider may turn to a recent memory of a patient with pneumonia who fared well when estimating the risk of death for a patient with pneumonia she is caring for today (ie, availability bias).3,4 Even if a provider avoids heuristics and assimilates the necessary information needed to determine an individual’s risk of death, he must then overcome his own biases (eg, age, experience, religion), which may unduly influence his estimate of the risk of death.5-7 For these reasons, providers are in great need of tools, such as predictive models or decision aids that can objectively incorporate complex information and provide mortality estimates that are reproducible and immune to bias. This need for objective measures is particularly relevant to critical care where illness is highly complex, evolves rapidly, and commonly results in poor outcomes.