Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias (ADRD)

摘要 2020-2022年的一系列面对面研讨会中的两个将在杜克大学举办，以提供有关如何 现有和新近开发的分析方法可用于详细的总体和临床数据分析 为了在了解与健康相关的差异的原因和机制方面取得进展 阿尔茨海默病(AD)、相关痴呆症(ADRD)和其他与年龄相关的突出疾病。长的- 本系列的学期目标是提供一个资源，重点是在以下方面传播方法论知识 展示新开发的方法的功能，扩展 应用成熟和熟悉的方法，促进正确使用来自 方法和伦理前景，并为对以下问题感兴趣的专家和新手提供论坛 健康差距和与年龄相关的疾病，讨论他们的想法并促进他们的研究。领航员公爵- 2019年2月在杜克大学举行的NIA系列讲习班成功地吸引了广泛的 对这一专题产生了科学兴趣，并为目前的提议提供了背景。第一个的重点 讲习班(计划在2020/2021年冬季举行)将展示如何利用既定的行政管理进行研究 医疗数据资源，如医疗保险索赔数据库与创新的分析方法相结合 例如分割分析、基于时间序列预测/预测方法和随机过程 模型可以用来揭示这一研究领域以前被忽视和/或未被研究的方面。 将讨论的具体议题包括：i)AD/ADRD和其他年龄段的风险和存活率的差异- 相关疾病；二)AD/ADRD和其他与年龄有关的疾病的发病率和死亡率的预测方法 疾病；iii)分析医疗保险和其他基于行政索赔的数据。第二个的重点是 讲习班(计划于2021年/2022年冬季举行)将扩大这一范围，以包括例行收集的健康记录数据 在医院或大学医疗中心(例如，杜克临床数据仓库)，并展示 已建立的和新的分析方法可以严格地应用于这些数据，以有助于识别 美国特定人群之间持续健康差距的原因和狭义定义 病人阶层。具体专题将扩大到包括：一)分析方法，以确定和量化 与治疗相关和与医疗护理获得相关的因素对以下结果差异的贡献 AD/ADRD和其他与年龄有关的疾病；二)共病、多发病、与治疗有关的、社会和遗传的 造成AD/ADRD和其他年龄相关疾病健康结果差异的因素；三) 预测健康结果和分析潜在健康干预措施的方法。诉讼程序 将在研讨会网站上进行现场直播，并以文本和视频形式免费提供演示文稿 在事实发生后。

Abstract Two of a series of in-person workshops in 2020-2022 will be hosted at Duke to provide new knowledge on how existing and recently developed analytic methods can be used for detailed population and clinical data analysis in order to make progress in understanding the causes and mechanisms of health-related disparities in Alzheimer’s disease (AD), related dementias (ADRD), and other prominent age-related diseases. The long- term goal of the series is to provide a resource focused on diffusing methodological know-how in terms of demonstrating the capabilities of newly developed methodologies, expanding on the rigor and range of application of well-established and familiar methods, promoting correct use of big health data both from a methodological and ethical prospective as well as providing a forum for experts and newcomers interested in health disparities and age-related diseases to discuss their ideas and promote their research. The pilot Duke- NIA workshop of the series held in February 2019 at Duke University was successful in drawing broad scientific interest to the topic and generated the background for the current proposal. The focus of the first workshop (planned in Winter 2020/2021) will be on demonstrating how studies using established administrative health data resources such as the Medicare claims database combined with innovative analytic approaches such as partitioning analyses, time-series based methods of projection/forecasting, and stochastic process models can be used to uncover previously overlooked and/or understudied aspects in this area of research. Specific topics to be discussed will include: i) disparities in risks and survival of AD/ADRD and other age- related diseases; ii) forecasting approaches for prevalence and mortality of AD/ADRD and other age-related diseases; iii) analysis of Medicare and other administrative claim-based data. The focus of the second workshop (planned in Winter 2021/2022) will extend this to include the health records data routinely collected in hospitals or University medical centers (e.g., the Duke Clinical Data Warehouse) and demonstrate how well- established and new analytic methods can be rigorously applied to such data to contribute to identifying the causes of persistent health disparities between specific groups of the U.S. population and narrowly defined patient strata. Specific topics will be expanded to include: i) analytic approaches to identify and quantify the contribution of treatment-related and medical care access-related factors to disparities in outcomes of AD/ADRD and other age-related diseases; ii) comorbidity, multimorbidity, treatment-related, social and genetic factors as sources of disparities in health outcomes of AD/ADRD and other age-related diseases; iii) forecasting of health outcomes and approaches for analyses of potential health interventions. The proceedings will be streamed live on the workshop website and presentations will be freely available in text and video form after the fact.