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Integrating Predictive Modeling Into Mental Health Care: An Example in Suicide Prevention
Greg M Reger1, Mary Lou McClure1, David Ruskin1
1Mental Health Service, Veterans Affairs Puget Sound Health Care System, Seattle/Takoma, Washington (all authors); Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (G. Reger, Ruskin, M. Reger).
Abstract:
Recent advances in statistical methods and computing power have improved the ability to predict risks associated with mental illness with more efficiency and accuracy. However, integrating statistical prediction into a clinical setting poses new challenges that need creative solutions. A case example explores the challenges and innovations that emerged at a Department of Veterans Affairs hospital while implementing REACH VET (Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment), a suicide prevention program that is based on a predictive model that identifies veterans at statistical risk for suicide.
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