title: Decision analysis: a primer and application to pain-related studies.
abstract: Decision analysis is a quantitative approach to decision making under uncertainty that explicitly states all relevant components of the decision, including statement of the problem, identification of the perspective of the decision maker, alternative courses of action and their consequences, and a model that illustrates the decision-making process. Decision trees and Markov models are used to provide a simplified version of complex clinical problems to help decision makers understand the risks and benefits of several clinical options. This article provides an introduction to decision analysis by describing the construction of decision trees and Markov models and employing examples from the recent literature.
authors.affiliation: Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, Utah, USA.
authors.forename: Jaewhan
authors.initials: J
authors.lastname: Kim
authors.forename: Richard
authors.initials: R
authors.lastname: Nelson
authors.forename: Joseph
authors.initials: J
authors.lastname: Biskupiak
mesh_terms: D003661:Decision Support Techniques; D003663:Decision Trees; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical; D059408:Pain Management / Q000379:methods / Q000706:statistics & numerical data*