Mid-Career Transition -- Mapping Paths to Success in Achieving Community-Level He

职业中期转型——绘制实现社区级成功的路径

• 批准号: 8599681
• 负责人: GEORGE S RUST
• 金额: $ 26.44万
• 依托单位: MOREHOUSE SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-03 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8599681
• 关键词: Mid; Career; Transition; Mapping; Paths

DESCRIPTION (provided by applicant): This career-development award will fund the investigator's transition from executive leadership to intellectual leadership in the field of healh equity research. For over twenty years, the investigator has contributed to building the Morehouse School of Medicine, one of four historically-black medical schools in the nation and recently ranked #1 in the nation for achieving a social mission. He also led development of the National Center for Primary Care, a research, training, and resource center focused on achieving health equity. This mid-career award will allow him to transition from executive leadership to focus exclusively on research that seeks to build models of success toward achieving health equity in communities across the U.S. The proposed research will provide a roadmap to success in achieving more optimal and equitable asthma outcomes for all children, with broader application to a wide range of chronic disease outcome disparities across all age groups. In the proposed progression of research, we plan to build on our experience with Medicaid data by adding more sophisticated computer simulation models of health disparities at the community level, and also to add more sophisticated datasets, including clinical data from electronic health records and social determinant data with geospatial data links. We propose to first study the causes of local-area variation in asthma outcome disparities among millions of low-income, Medicaid enrolled children and youth across 29 states. These states hold over 80% of the entire U.S. Medicaid population, and over 90% of African American and Hispanic / Latino enrollees. Specifically, we will further refine our Monte Carlo simulations and Markov modeling to assess the impact of different treatment strategies filtered through real-world patient adherence. We will use multi-level modeling and geospatial analyses to quantify the effect of patient, provider, hospital, and community factors contributing to racial-ethnic and local-area variation in outcomes. We will engage in structural equation modeling to quantify conceptual models that include latent variables such as "poverty" or "quality of care". Finally, we will exploe agent- based modeling (overlaid on community-level geospatial topography) to simulate the complex dynamics of health disparities as they evolve in space over time. We will also refine these models using clinical data from electronic health records, and assess the applicability of these models to other chronic diseases and to overall health outcome disparities. Our ultimate goal is to save lives and decrease suffering by developing computer models that reveal community- specific intervention points most likely to reduce health disparities in each community.

描述(由申请者提供)：这一职业发展奖将资助研究人员在健康公平研究领域从行政领导向知识领导的转变。二十多年来，这位调查人员为建立莫尔豪斯医学院做出了贡献，这是全国四所历史上最黑的医学院之一，最近在实现社会使命方面排名全国第一。他还领导了国家初级保健中心的发展，这是一个专注于实现卫生公平的研究、培训和资源中心。这一职业生涯中期奖项将使他从行政领导转变为专注于寻求建立成功模式的研究，以实现全美社区的健康公平。拟议的研究将提供成功的路线图，为所有儿童实现更理想和更公平的哮喘结果，并更广泛地应用于所有年龄段的广泛慢性病结果差异。在拟议的研究进展中，我们计划在我们的医疗补助数据经验的基础上，在社区层面增加更复杂的健康差距计算机模拟模型，并增加更复杂的数据集，包括来自电子健康记录的临床数据和具有地理空间数据链接的社会决定数据。我们建议首先研究29个州数百万低收入、参加医疗补助的儿童和青年哮喘结局差异的局部地区差异的原因。这些州拥有超过80%的美国医疗补助人口，以及超过90%的非裔美国人和西班牙裔/拉丁裔登记者。具体地说，我们将进一步改进我们的蒙特卡洛模拟和马尔可夫模型，以评估通过现实世界患者依从性筛选出的不同治疗策略的影响。我们将使用多层次建模和地理空间分析来量化患者、提供者、医院和社区因素对结果的种族、民族和地方差异的影响。我们将进行结构方程建模，以量化包括“贫困”或“护理质量”等潜在变量的概念模型。最后，我们将利用基于代理的建模(覆盖在社区级别的地理空间地形上)来模拟健康差异随着时间在空间中演变的复杂动态。我们还将使用电子健康记录中的临床数据来改进这些模型，并评估这些模型对其他慢性病和总体健康结果差异的适用性。我们的最终目标是通过开发计算机模型来拯救生命和减少痛苦，这些模型揭示了社区特定的干预点，最有可能减少每个社区的健康差距。