Assessing Barriers and Facilitators for Participating Structured Lifestyle Intervention and its Real-world Effectiveness and Cost-Effectiveness among US Veterans

项目摘要 美国糖尿病预防计划（DPP）表明，结构化生活方式干预（SLI）可以 预防或延缓进展为2型糖尿病（T2 D）。2010年，国会授权CDC建立和 通过国家DPP（NDPP）在全国范围内管理类似DPP的SLI项目，这些项目很快就会 在2016年扩大到医疗保险。然而，现有国家发展计划的入学率和完成率 显著低于原始DPP研究中观察到的，尤其是在少数群体中。壁垒和 决定个人NDPP注册和完成的促进者仍然不清楚。此外，研究 评估NDPP在降低心血管疾病（CVD）风险因素方面的长期有效性， 缺乏T2 D事件。NDPP在总体入组者和入组者亚组中的成本-效果 也是未知的。填补这些知识空白对于改进国家发展伙伴关系方案的执行至关重要。 退伍军人健康管理局（VA）移动！该计划是美国最大的类似DPP的SLI计划。的 该项目于2005年启动，其课程是根据最初的美国DPP试验和CDC的 NDPP课程。我们已经建立了一个大型的纵向队列MOVE！计划参与者 （N= 50，000）与电子健康记录（EHR）和链接的保险索赔数据和移动！程序 提供者的数据，随访时间长达15年。通过这个独特的数据源，结合一个 美国最先进的糖尿病微观模拟模型--BRAVO糖尿病模型，由 我们的小组，我们将确定障碍和促进者的登记和完成移动！程序和 评估其长期有效性和成本效益。 本研究的具体目标是：1）目标1：评估入组的障碍和促进因素 完成MOVE！2）目标2：评估MOVE！ 3）目标3：评估MOVE！ 程序.通过实现这三个目标，我们将能够确定最有效和最具成本效益的战略 在美国实施和扩大NDPP。 拟议的研究是重要的，因为它将填补关键的知识差距，在实施NDPP 在美国.退伍军人群体是一个独特的群体，也是全国NDPP研究的重要组成部分 网络这项研究是创新的，因为我们的大型SLI队列与EHR索赔相关的数据将使我们能够 应用尖端的机器学习方法和仿真模型来解决一系列具有挑战性的研究问题。

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.