This measure directs the Secretary of Veterans Affairs, through the Center for Innovation for Care and Payment, to create a grant program to fund the development of artificial intelligence (AI) predictive models that evaluate risk factors contributing to suicide among veterans. The Secretary must establish the program within one year of enactment and select at least two eligible organizations to receive grants. Eligible organizations include nonprofits, academic institutions, private research organizations, or other entities with experience in AI, health data protection and de-identification, predictive models, advanced statistics or machine learning, and Department data security and interoperability standards. Selected organizations must be able to integrate military service records under the benefits administration with clinical data under the health administration. The Secretary must consider geographic distribution, proximity to health facilities, collaboration experience, and the ability to deploy solutions in large health systems. Priority is given to organizations located in areas with high veteran suicide rates, high Veterans Crisis Line call volume, or long wait times for mental health care. Grantees must produce models that are explicable, interoperable, and clinically actionable, and agree to make models or findings available to the Secretary for department-wide implementation. The Secretary may not select more than one grantee per VISN. The authority to run the program ends on September 30, 2029. The short title is the Data Driven Suicide Prevention and Outreach Act of 2026. The measure was introduced in the House by Representatives Ryan Mackenzie and Josh Gottheimer and referred to the Committee on Veterans' Affairs.
No publicly available information on funding amounts, appropriations, or total costs. The measure requires the Secretary to award grants and to run the program through September 30, 2029, but does not state how much money will be provided or how grants will be financed.
Proponents seek to fund AI-driven predictive models that evaluate risk factors for suicide among veterans, prioritize areas with high need, require explainable and interoperable tools, and promote integration of benefits and clinical records. The measure emphasizes use of organizations with experience in federal health systems, secure data infrastructure, and multidisciplinary teams including data scientists, clinicians, and suicide prevention specialists.
No publicly available information on specific opposition or critiques in the text or metadata provided.