Justice-involved individuals have high rates of trait, state, and precipitating risk factors for suicide, account for a significant proportion of U.S. suicides each year, and many are not well-connected to care. The National Center for Health and Justice Integration for Suicide Prevention (NCHATS): (1) uses contact with the justice system (e.g., police contact, arrest) as a novel indicator of suicide risk in the general population; (2) demonstrates how big data systems that efficiently track justice involvement can be linked to health system records and scaled to identify individuals at risk for suicide and connect them to care; and (3) examines effectiveness and scalability of suicide prevention approaches using these methods. Center projects are hybrid effectiveness-implementation studies that examine effectiveness, cost-effectiveness, and scalability of suicide prevention activities triggered through linkage of justice and health data. Given that contact with the justice system is a sign of risk for suicide, big data integration across justice/health systems to flag movement between systems (and therefore suicide risk) provides a novel method of identifying suicide risk in the general population. This approach does not require collecting new data from this hard-to-reach population. Rather, it sets up strategies to efficiently link existing data and to test methods to respond. This is an innovative and potentially scalable approach to identify/address suicide risk for individuals not well-connected with standard health care. The Center is innovative in that it: (1) establishes a suicide prevention intervention effectiveness base for a large and high-risk target population, conducting (a) 2 of only 3 fully-powered suicide prevention RCTs in justice populations, and (b) the largest RCTs of any intervention for any condition in a justice-involved population to date; (2) develops and manualizes strategies for scalability and sustainment -- understudied areas of implementation science; (3) uses contact with the justice system as a novel indicator of suicide risk in the general population; (4) uses sociometric identification of key individuals to promote diffusion and dissemination of Center approaches; (5) demonstrates how efficient, generalizable health and justice system big data linkage is achieved and can be used to automate suicide risk identification and response across health and justice systems at scale. This is extremely rarely done in practice and never before tested as a method of improving health outcomes in justice populations. By incorporating the few cases of which we are aware into this Center, we are poised to rapidly advance the field. Center aims are to: (1) Evaluate effectiveness and cost-effectiveness of suicide prevention approaches that use justice contacts as markers of risk and health/justice system data linkage to provide scalable ways to alert providers of this risk; (2) Maximize scalability, sustainability, relevance, and...