Title: Innovative methods to reduce racial and ethnic disparities in suicide risk prediction
Grant number: 1R01MH125821
Grant period: 1/1/2022 – 12/31/2025
Brief Narrative: Suicide risk prediction models are being used by health care systems to guide delivery of suicide prevention interventions, but these prediction models may not accurately identify high-risk patients in racial and ethnic subgroups that are less prevalent or have lower rates of suicide attempt and death. This project will reduce racial and ethnic disparities in suicide risk models by developing methods for prediction model estimation that optimize performance within subgroups, rather than across the whole population, and adjust for misclassification of suicide outcomes. We will also design sample size calculations that evaluate the ability of a prediction study to accurately identify high-risk individuals within racial and ethnic subgroups.
- Lead site:
- KPWA (PI Yates Coley)
- Participating sites:
- University of Washington (Co-I Noah Simon)
- KPSC (Co-I Karen Coleman)
Awarded budget (total cost): $1,622,626
Human Subjects: Reviewed by KPWA IRB, IRBNet# 1870253
Statistical methods research is underway. IRB and data use approvals are in place for all planned analyses. Current activities are focused on methods for accounting for outcome misclassification; evaluating variable importance in suicide prediction models; and designing estimation methods to optimize performance in racial/ethnic subgroups.