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. 2015 Sep;105(9):1935-42.
doi: 10.2105/AJPH.2015.302737. Epub 2015 Jun 11.

Predictive Modeling and Concentration of the Risk of Suicide: Implications for Preventive Interventions in the US Department of Veterans Affairs

John F McCarthy  1 , Robert M Bossarte  1 , Ira R Katz  1 , Caitlin Thompson  1 , Janet Kemp  1 , Claire M Hannemann  1 , Christopher Nielson  1 , Michael Schoenbaum  1
Affiliations

Predictive Modeling and Concentration of the Risk of Suicide: Implications for Preventive Interventions in the US Department of Veterans Affairs

John F McCarthy et al. Am J Public Health. 2015 Sep.

Abstract

Objectives: The Veterans Health Administration (VHA) evaluated the use of predictive modeling to identify patients at risk for suicide and to supplement ongoing care with risk-stratified interventions.

Methods: Suicide data came from the National Death Index. Predictors were measures from VHA clinical records incorporating patient-months from October 1, 2008, to September 30, 2011, for all suicide decedents and 1% of living patients, divided randomly into development and validation samples. We used data on all patients alive on September 30, 2010, to evaluate predictions of suicide risk over 1 year.

Results: Modeling demonstrated that suicide rates were 82 and 60 times greater than the rate in the overall sample in the highest 0.01% stratum for calculated risk for the development and validation samples, respectively; 39 and 30 times greater in the highest 0.10%; 14 and 12 times greater in the highest 1.00%; and 6.3 and 5.7 times greater in the highest 5.00%.

Conclusions: Predictive modeling can identify high-risk patients who were not identified on clinical grounds. VHA is developing modeling to enhance clinical care and to guide the delivery of preventive interventions.

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Figures

FIGURE 1—
FIGURE 1—
Prediction sample over 12 months, with top tiers of predicted probability for (a) suicide risk concentration and (b) suicide rate: Veterans Health Administration, United States, 2008–2011.
See this image and copyright information in PMC

References

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