RFA-DP-23-001, Simulation Model of Interventions Linking Evidence to SDOH (SMILES)

RFA-DP-23-001，将证据与 SDOH 联系起来的干预模拟模型 (SMILES)

• 批准号: 10793754
• 负责人: Amanda Honeycutt
• 金额: $ 75万
• 依托单位: RESEARCH TRIANGLE INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-30 至 2026-09-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10793754
• 关键词: RFA; DP; 23; 001; Simulation

PROJECT SUMMARY/ABSTRACT To support the Centers for Disease Control and Prevention (CDC) and states and communities in identifying programs, policies, or practices (PPP) that can reduce the ever-widening gaps in chronic disease incidence and mortality in the United States, we will develop a model to explore the impacts of social determinants of health (SDOH) factors on chronic disease incidence, mortality, and disparities over the next 5 to 30 years. We will use a systems science approach to create a mathematical simulation model that integrates risk and SDOH factors for the incidence of heart disease, stroke, diabetes, CKD, cancer, and Alzheimer’s disease, accounting for the interconnectedness and feedback loops between SDOH and chronic disease. The model will incorporate evidence-based strategies for addressing SDOH factors in each of the five priority areas for CDC’s National Center for Chronic Disease Prevention and Health Promotion: the built environment, community-clinical linkages, food and nutrition security, tobacco-free policy, and social connectedness. By generating synthetic populations to represent the SDOH-related characteristics (e.g., race/ethnicity, sex, age, income, education, and urban vs. rural status) and chronic disease risk factors of the selected county or state population, the model will produce valid results for each county and state in the United States. The model will also be calibrated to national surveillance data. We will develop a multi-user, web-based, public-use version of the model to operate on CDC’s web platforms. CDC and public health partner groups can run scenarios using the model to explore which combinations of PPPs would have the greatest impact on reducing chronic disease disparities and outcomes and how PPPs compare in terms of costs and cost- effectiveness. Results from the model will inform future public health practices related to SDOH. Moreover, the publicly available model will allow community members and public health interest groups to create scenarios and explore the impacts of various PPPs on health outcomes and disparities, thus encouraging the use of community-based participatory processes and decision-making around solutions to address SDOH and reduce disparities in chronic disease risk factors, incidence, and mortality.

项目总结/摘要 支持疾病控制和预防中心（CDC）以及各州和社区确定 可以减少慢性病发病率不断扩大的差距的计划、政策或实践（PPP） 和死亡率，我们将开发一个模型来探索社会决定因素的影响， 健康（SDOH）因素对慢性病发病率，死亡率和差距在未来5至30年。 我们将使用系统科学的方法来创建一个数学模拟模型，将风险和 心脏病、中风、糖尿病、CKD、癌症和阿尔茨海默病的发病率的SDOH因素， 解释了SDOH和慢性病之间的相互联系和反馈回路。模型 将在五个优先领域中的每一个领域纳入以证据为基础的战略， CDC的国家慢性病预防和健康促进中心：建筑环境， 社区-临床联系、粮食和营养安全、无烟政策和社会联系。通过 生成合成群体以表示SDOH相关特征（例如，种族/民族，性别， 年龄、收入、教育、城市与农村状况）和所选县的慢性病危险因素 或州人口，该模型将为美国的每个县和州产生有效的结果。 该模型还将根据国家监测数据进行校准。我们将开发一个多用户，基于网络， 该模型的公共使用版本在CDC的网络平台上运行。CDC和公共卫生伙伴团体 可以使用该模型运行情景，以探索哪些购买力平价组合将产生最大影响 减少慢性病的差异和结果，以及购买力平价在成本和费用方面的比较- 有效性该模型的结果将为未来与SDOH相关的公共卫生实践提供信息。此外，委员会认为， 公众可用的模型将允许社区成员和公共卫生利益集团创建 假设情景，并探讨各种购买力平价对健康结果和差距的影响，从而鼓励 利用基于社区的参与性进程和围绕解决办法的决策， SDOH和减少慢性病危险因素，发病率和死亡率的差异。