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Genetic testing in health care can provide information to help with disease prediction, diagnosis, prognosis, and treatment. Assessing the clinical utility of genetic testing requires a process to value and weight different outcomes. This article discusses the relative merits of different economic measures and methods to inform recommendations relative to genetic testing for risk of disease, including cost-effectiveness analysis and cost-benefit analysis. Cost-effectiveness analyses refer to analyses that calculate the incremental cost per unit of health outcomes, such as deaths prevented or life-years saved because of some intervention. Cost-effectiveness analyses that use preference-based measures of health state utility such as quality-adjusted life-years to define outcomes are referred to as cost-utility analyses. Cost-effectiveness analyses presume that health policy decision makers seek to maximize health subject to …