Measuring Lifelong Multimorbidity with Patient Perspectives: Implementing and Visualizing the Cumulative Burden Methodology Across Cohorts

项目摘要/摘要 背景：多病，定义为两种或两种以上的身体或精神慢性疾病同时发生， 在全球范围内很普遍，而且还在上升。对多种疾病的新测量提供了对光谱的独特见解， 需要多种共病情况的模式和程度。目前的措施不能提供足够的 设计、评估和实施与临床相关的多层次干预措施的背景。 目的：响应PAR-20-179，我们建议开发、可视化和应用一套新的模块化 解决目前影响多发病结果研究的关键限制的措施和工具。 具体目标：(1)在生命过程的不同阶段制定个性化的累积负担衡量标准， 基于患者角度，使用条件加权负担权重和风险因素；(2)创建一套 基于Web的可视化，供任何类型的队列使用；(3)将累积负担应用于独立的 在镰状细胞病患者队列中测试实施情况，并指导未来传播到其他队列。 研究设计：在我们现有的累积负担框架基础上建立的两项新措施将是 使用圣犹大终身队列(SJLIFE)研究的数据开发，SJLIFE是一项大型儿科临床队列研究 癌症幸存者。首先，我们将开发一种针对个人的多发病风险的个性化测量方法，使用 泊松过程的回归框架，以提供对模式和 多种慢性病的严重程度和相关的关键风险因素。二是落实包干 权重，一组特定于条件的权重，由效用权重派生而来(我们也将使用 SJLIFE数据，以便纳入患者的观点。为了使用/共享指标，敏捷方法可以 将利用软件开发来创建动态、交互式的基于网络的可视化。最后，使用 综合框架的实施研究，我们将应用累积负担法进行研究 由成人和儿童镰状细胞病患者组成的第二个队列中的多发病 国家研究优先事项，并研究其他国家如何将我们的创新措施推广到他们的群体中。 意义：我们的累积负担衡量标准是为了克服以下方面的一些紧迫困难 由PAR-20-179确定的当前多病测量。这项拟议的研究试图在我们以前的基础上 通过将个性化风险预测和患者报告的结果结合起来进行工作。此外，我们认识到 制定新的措施和公布我们的方法不足以确保广泛使用和影响。至 支持有效实施和传播，我们将创建可视化工具，帮助调查人员分享 累积负担结果，并使用实施研究其应用程序的障碍和推动因素 科学方法。我们预计我们的工作将产生一套可视化模板和模块化应用 方法资源，使临床医生、研究人员、倡导团体和决策者有机会 阐明日益严重的多发病问题，这几乎影响到我们社会的每一个亚群体。

PROJECT SUMMARY/ABSTRACT Background: Multimorbidity, defined as the co-occurrence of two or more physical or mental chronic illnesses, is prevalent and rising globally. New measures of multimorbidity that provide unique insights into the spectrum, pattern and magnitude of multiple co-morbid conditions are needed. Current measures fail to provide adequate context from which to design, evaluate, and implement multilevel clinically-relevant interventions. Objective: In response to PAR-20-179, we propose to develop, visualize and apply a modular suite of novel measures and tools to address the critical limitations currently impacting multimorbidity outcomes research. Specific Aims: (1) Develop personalized cumulative burden measures, over various stages of the life-course, based on patient perspectives using condition-weighted burden weights and risk factors; (2) Create a suite of web-based visualizations for use by any type of cohort; (3) Apply the cumulative burden to an independent cohort of sickle cell disease patients to test implementation and guide future dissemination to other cohorts. Study design: Two novel measures, which built on our existing cumulative burden framework, will be developed using data from the St. Jude Lifetime Cohort (SJLIFE) study, a large clinical cohort of pediatric cancer survivors. First, we will develop a personalized measure of multimorbidity risk for an individual using a regression framework of the Poisson process to provide insights into lifelong variations in patterns and magnitude of multiple chronic conditions and associated key risk factors. Second, we will implement burden weights, a set of condition-specific weights derived from utility weights (which we will also calculate) using SJLIFE data in order to incorporate patient perspectives. To use/share the metrics, the Agile approach to software development will be employed to create dynamic, interactive web-based visualizations. Finally, using the consolidated framework for implementation research, we will apply the cumulative burden method to study multimorbidity in a second cohort comprised of adults and children with sickle cell disease in order to advance national research priorities and study how others may our innovative measures to their cohorts. Significance: Our cumulative burden measure was created to overcome some of the pressing difficulties with current multimorbidity measures identified by PAR-20-179. This proposed study seeks to build on our prior work by incorporating personalized risk prediction and patient-reported outcomes. Additionally, we recognize that developing new measures and publishing our methods are insufficient to ensure broad use and impact. To support effective implementation and dissemination, we will create visual tools that help investigators share cumulative burden results and study the barriers and enablers of their application using an implementation science approach. We anticipate our work will yield a suite of visualization templates and modular applied method resources that will enable clinicians, researchers, advocacy groups, and policymakers an opportunity to shed light on the growing problem of multimorbidity affecting nearly every sub-group of our society.