In this primer, the reader is introduced to the concepts governing decision analysis and cost-effectiveness analysis. The construction of decision trees and Markov models is presented to provide the necessary background to critique research articles in published literature. Specific sub-topics related to cost-effectiveness analysis are discussed including quality adjustment and utilities (patient preferences for health states), discounting, and sensitivity analysis including Monte Carlo simulation. Evidence based methods to critique decision and cost-effectiveness analysis are provided, and limitations to these analytic methods are examined. In summary, the major functions of decision analysis and cost-effectiveness analysis are to provide: (1) a quantitative summary of existing data, and (2) hypothesis generation for further research.