Project Summary The US Diabetes Prevention Program (DPP) has shown that a structured lifestyle intervention (SLI) can prevent or delay progression to type 2 diabetes (T2D). In 2010, Congress authorized CDC to establish and manage DPP-like SLI programs nationwide through the National DPP (NDPP), and these programs soon expanded to Medicare in 2016. However, the enrollment and completion rates of existing NDPPs were significantly lower than observed in the original DPP study, especially in minority groups. Barriers and facilitators that determine the individuals’ NDPP enrollment and completion remain unclear. Also, studies assessing the long-term effectiveness of NDPP in reducing cardiovascular disease (CVD) risk factors and incident T2D were lacking. The cost-effectiveness of NDPP in the overall enrollees and enrollee subgroups was also unknown. Filling these knowledge gaps is critical to improving the implementation of NDPP. The Veterans Health Administration (VA) MOVE! program is the largest DPP-like SLI program in the US. The program was initiated in 2005 with a curriculum developed based on the original US DPP trial and CDC’s NDPP curriculum. We have already established a large longitudinal cohort of MOVE! program enrollees (N=50,000) with electronic health records (EHR) and linked insurance claims data and the MOVE! program providers' data with a follow-up length of up to 15 years. Through this unique data source, combined with one of the most advanced diabetes microsimulation models in the US --the BRAVO diabetes model, developed by our group, we will identify barriers and facilitators to the enrollment and completion of the MOVE! program, and evaluate its long-term effectiveness and cost-effectiveness. The specific aims of the proposed study are: 1) Aim 1: Assess barriers and facilitators of enrollment and completion of MOVE! program; 2) Aim 2: Assess the long-term effectiveness of the MOVE! program; 3) Aim 3: Evaluate the long-term economic impact and cost-effectiveness of the MOVE! program. By achieving all three aims, we will be able to identify the most effective and cost-effective strategy to implement and expand the NDPP in the US. The proposed research is significant because it will fill the critical knowledge gaps in implementing the NDPP in the US. The Veteran population is a unique population and a vital piece to this nationwide NDPP research network. This study is innovative because our large SLI cohort with EHR-claims-linked data will allow us to apply cutting-edge ML methods and simulation models to tackle a series of challenging research questions.