Previous publications have advocated that clinicians choose the most sensitive diagnostic test to rule out disease and the most specific diagnostic test to rule in disease. This paper critically examines the validity of these recommendations. First, the author finds that following these recommendations does not lead to the highest disease probability for a positive test result (thereby best ruling in disease) or the lowest disease probability for a negative test result (thereby best ruling out disease). In general, the ability of a diagnostic test to lead to the highest (rule in) or lowest (rule out) disease probability should be judged based on likelihood ratios. Next, by comparing expected utilities, the author considers whether the most specific test leads to the best clinical outcome when a rule-in strategy is clinically advisable, i.e., when the costs of false-positive results are high, and whether the most sensitive test leads to the best clinical outcome when a rule-out strategy is clinically advisable, i.e., when the costs of false-negative results are high. The author again demonstrates that the greatest clinical utility is not always achieved by using the most specific test in a rule-in decision or the most sensitive test in a rule-out decision. Tradeoffs between sensitivity, specificity, disease probability, and utilities of correct and incorrect disease classifications by the diagnostic test must be simultaneously captured to determine which strategy maximizes clinical utility.