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Use of suicide risk prediction models can be cost-effective for U.S. healthcare systems, even with relatively low accuracy, researchers suggested.
In an analysis designed to determine accuracy thresholds needed for cost-effectiveness with a specificity of 95% or higher cognitive behavioral therapy (CBT) reached that benchmark at a sensitivity of at least 35.7% (95% CI 23.1%-60.3%), while active contact and follow-up (ACF) did so at a sensitivity of at least 17% (95% CI 7.4%-37.3%), reported Eric Ross, MD, of Massachusetts General Hospital in Boston, and colleagues.
Many statistical models have been developed in the hopes of predicting suicide risk, but it s not known how accurate these models need to be in order to warrant clinical implementation.