Ross EL, Zuromski KL, Reis BY, et al. - Researchers aimed at determining the threshold values of sensitivity, specificity, and positive predictive value that must be attained by a suicide risk prediction model to cost-effectively target a suicide risk reduction intervention to high-risk individuals. In this economic evaluation, published data on suicide epidemiology, the health care and societal costs of suicide, and the costs and efficacy of suicide risk reduction interventions were incorporated into a novel decision analytic model. Individuals at high predicted risk were delivered two possible interventions: active contact and follow-up (ACF; relative risk of suicide attempt, 0.83; annual health care cost, $96) and cognitive behavioral therapy (CBT; relative risk of suicide attempt, 0.47; annual health care cost, $1,088). For targeting a safety planning and telephone call intervention, suicide risk prediction could be achieved cost-effectively if its specificity was 95% or higher and its sensitivity was 17% or higher, corresponding to a positive predictive value of 1% or greater. Positive predictive value of 2% or greater was required for a more expensive cognitive behavioral therapy intervention. Overall findings suggest enough accuracy of existing suicide risk prediction models to be cost-effective in US health care settings.