Decision analysis helps evaluate competing strategies under conditions of uncertainty in a wide variety of clinical settings. Despite some limitations, decision trees and Markov models remain essential tools for medical decision analysts. These techniques allow comparison of competing management strategies in a quantitative fashion. Sensitivity analysis is an important feature of decision analytic models that identify important factors that affect the outcome of decisions under considerations. Judiciously used, decision analytic models allow a quantitative evaluation of existing data as they relate to strategies ranging from optimizing clinical management at the patient level to allocating health care resources at the societal level.
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