ArticleNpj mental health research2025
Retraining the veterans health administration's REACH VET suicide risk prediction model for patients involved in the legal system.
Article in Npj mental health research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Predictive analytics to direct clinical attention to complex patients with elevated suicide risk: enhancement of the Veterans Health Administration REACH VET model.BMJ mental health · 2026Article
- Opportunities and Challenges in Using National EHR Networks for AI in Learning Health Systems.Learning health systems · 2026Article
- Article
- Retraining the veterans health administration's REACH VET suicide risk prediction model for patients involved in the legal system.Npj mental health research · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
Although patients with criminal legal system involvement have among the highest rates of suicide, the model that identifies patients at high risk of suicide at the United States Veterans Health Administration (VHA) does not include predictors specific to criminal legal system involvement. We explored whether the model's predictive ability would be improved (1) by retraining the model for legal-involved veterans and (2) by adding additional predictors associated with legal-involvement. For a combined outcome of suicide attempt or suicide death, the retrained models showed a positive predictive value (PPV) of 0.124 and false negative rate (FNR) of 0.527. Adding additional predictors associated with being legal-involved did not improve predictive accuracy. Retraining the VHA suicide risk prediction model for legal-involved patients improves the model's predictive ability for this group of high-risk patients, more so than adding predictors associated with being legal-involved. A similar approach for other high-risk patients is worth exploring.
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