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Abstract
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.
View details for PubMedID 15831270