The Syndemic of Sepsis, Multimorbidity, Aging, and Low Healthcare Access and Quality in the United States

项目摘要 脓毒症是一个主要的全球性健康问题-我以前的工作估计有近5000万人 2017年，全球有1100万例病例和1100万例相关死亡，占当年所有死亡人数的20%。而 脓毒症在世界上几乎每个地方都是公共卫生挑战，有强有力的证据表明某些 亚组的风险远远高于其他人群，老年人的发病率较高， 多发病者，以及那些在社区与较低的医疗服务和质量。在美国（US）， 这些风险因素密切相关，并在地理上集中在一起。我提出这项建议的总体目标是 提高对影响个体脓毒症风险的因素的理解，解释社区- 水平特征和个人健康史，以建立对脓毒症的重要新见解 预防我的中心假设是，有一个败血症，多发性硬化症，衰老，低 美国的医疗服务和质量是空间模式化的。综合征，人群聚集， 社会和健康问题，其中聚集导致不利的疾病相互作用，提供了一个“框架 疾病与疾病以及社会状况与疾病的相互作用”， 在特定人群中。为了验证我的假设，我将首次利用空间链接， 多个独特的数据源，包括个人电子健康记录、人口普查数据、社区数据 来源和全州卫生系统数据。我将通过一个社区知情的联合收割机来整合这些数据源， 模型，建立在重建流行病学动态框架（FRED）的基础上， 建模平台使用这个流行病学框架，我将通过三个具体目标来检验我的中心假设： 评估以下地区成年人败血症住院事件的空间、社会和卫生系统模式： 阿勒格尼县，宾夕法尼亚州超过8年的时间，使用多层次模型，地理连接 电子健康记录、人口普查数据和邮政编码级别的社区数据源，2）应用 在FRED基于代理的建模平台中使用syndemic框架，以测试 患者水平的老龄化和多发病特征、社区因素和卫生系统之间的关系 获得和质量，影响败血症事件的个人风险，以及3）使用社区参与模式 与脓毒症患者，家庭和医疗保健专业人员一起建立，以完善脓毒症，衰老，多发病， 以及医疗服务的可及性和质量的综合模型。这项拟议中的工作将极大地影响美国的公共卫生 政策，败血症预防工作，以及对患有慢性病的老年人的护理。由专家密切指导 在败血症和健康的社会背景特征的定量建模，这个奖项将提供必要的 先进流行病学方法的研究培训，包括多层次建模，基于代理的建模， 和社区参与的研究。这个奖项将支持我成为一个独立的整体职业目标 研究人员重点关注减少脓毒症的全球负担，重点关注健康差异。

PROJECT SUMMARY Sepsis is a major global health problem – my previous work has estimated that there were nearly 50 million cases and 11 million associated deaths worldwide in 2017, representing 20% of all deaths that year. While sepsis is a public health challenge in nearly every location in world, there is strong evidence that certain subgroups are at far higher risk than others, with higher incidence among older adults, people with multimorbidity, and those in communities with lower healthcare access and quality. In the United States (US), these risk factors are closely linked and geographically clustered. My overall objective in this proposal is to improve understanding of the factors influencing individual sepsis risk, accounting for community- level features and personal health history over time, to establish critical new insights into sepsis prevention. My central hypothesis is that there is a syndemic of sepsis, multimorbidity, aging, and low healthcare access and quality in the US that is spatially patterned. Syndemics, population-level clustering of social and health problems in which the clustering results in adverse disease interaction, provide a “framework of disease-disease and social condition-disease interactions” that can improve understanding of health conditions within a specific population. To test my hypothesis I will leverage, and spatially link for the first time, multiple unique data sources including individual electronic health records, Census data, community data sources, and statewide health systems data. I will combine these data sources through a community-informed model, building upon the Framework for Reconstructing Epidemiological Dynamics (FRED) agent-based modeling platform. Using the syndemic framework, I will test my central hypothesis via three specific aims: 1) evaluate spatial, social, and health systems-based patterns of incident sepsis hospitalizations among adults in Allegheny County, Pennsylvania over an 8-year period using multilevel models that geographically link electronic health records, Census data, and community data sources at the ZIP code level, 2) apply a syndemic framework within the FRED agent-based modeling platform to test the mechanisms that underlie the relationships between patient-level features of aging and multimorbidity, community factors, and health system access and quality, that impact individual risk for incident sepsis, and 3) use community-engaged model building with sepsis patients, families, and healthcare professionals to refine the sepsis, aging, multimorbidity, and healthcare access and quality syndemic model. The proposed work will greatly impact US public health policy, sepsis prevention efforts, and care for older adults with chronic conditions. Closely mentored by experts in sepsis and quantitative modeling of social contextual features of health, this award will provide essential research training in advanced epidemiologic methods, including multilevel modeling, agent-based modeling, and community-engaged research. This award will support my overall career goal of becoming an independent investigator focused on reducing the global burden of sepsis, with a strong focus on health disparities.