The key rule for evaluating options that include outcomes that are uncertain is the expectation principle: the value of being exposed to the possibility of an outcome is determined by the value of the outcome and the frequency with which it would be experienced if you were exposed to the possibility repeatedly. For example, facing an one-in-twelve chance of losing a year of life expectancy should be evaluated as facing a certain loss of one month (1/12th of a year) of life expectancy. The expected value of such an option is loss of a month of life.

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One major strategy for managing uncertainty is seeking additional information about the likelihood of outcomes. New information may enable a patient to reduce their uncertainty directly, as when new research studies provide more insight into patient outcomes and suggest increase the likelihood that a particular treatment will or will not be beneficial. Even when new information does not yield greater certainty about outcomes, however, it may serve to narrow the range of the uncertainty.

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Every guide to decision making emphasizes the importance of goals. Decision makers must clarify their goals when making a decision, lest they make choices that will not serve their ends. To consider alternatives without knowing one’s goals is to let the tail wag the dog.

Practically speaking, most medical decision models don’t (and perhaps can’t) consider patient goals directly. Good clinicians, however, must (and do).

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