Population Data Use and Management (RC-PDM)

总结/摘要 人口数据使用和管理资源核心（RC-PDM） 西奈山老年美国独立中心（OAIC）的总体目标是提高患有严重疾病的老年人的独立性和生活质量。人口数据使用和管理资源核心（RC-PDM）将利用一系列现有的数据源，包括健康和退休研究（HRS），国家健康和老龄化趋势研究（NHATS），和医疗保险当前受益人研究（MCBS），以支持将促进我们对阿尔茨海默病和相关痴呆症（ADRD）纵向过程的理解的研究和其他严重疾病的风险。这些高质量的数据源具有足够的样本量和随访时间，可以对严重患病的老年人（包括ADRD患者、其护理人员、临床医生和政策制定者）的重要临床研究问题进行严格检查。此外，RC-PDM利用了我们使用其他数据源的经验，包括退伍军人健康管理局（VA）数据和西奈山数据仓库，它提供了从电子健康记录中提取的丰富的患者级数据。在Kelley和Ornstein博士的领导下，RC-PDM通过为OAIC调查人员提供数据管理和操作支持，补充了人口研究与方法（RC-PRM）和测量方法与分析（RC-MMA）核心的分析和方法资源。RC-PDM将参与特别鼓励ADRD中基于人群的研究的举措，包括实施经验证的算法，以使用详细的认知和功能测量结合人口统计学和自我报告的健康特征来识别可能患有痴呆症的人，创建痴呆症患者的纵向队列，并支持外部项目，以收集痴呆症患者的多样化城市队列，与医疗保险和医疗补助数据相关联，以检查疾病进展和临终治疗强度的预测因素。此外，RC-PDM将为一个利用地理空间分析的发展项目建立基础设施和业务支持，以检查ADRD，并通过开发一个数据集清单为基于人口的研究提供新的基础设施和支持，该数据集具有关键结构的协调措施，包括用于老年人研究的ADRD。RC-PDM的工作与这些数据将支持MS-OAIC和其他胡椒中心的研究人员，作为我们的胡椒跨学科专业知识的一部分，以改善需要的老年姑息治疗（TEXTING-PC）研究网络，包括对试点研究，职业发展奖励项目的分析，以及R 01应用程序的初步数据。这些目标将通过以下活动实现：整合人口数据管理活动，获取新的数据源，建设和维护所有基础设施，并进行数据更新、清理和链接;协调数据集的ADRD措施和其他关键结构;确保OAIC初级教师能够获得数据，重点是痴呆症研究和实施科学。

SUMMARY/ABSTRACT POPULATION DATA USE AND MANAGEMENT RESOURCE CORE (RC-PDM) The overarching goal of the Mount Sinai Older American Independence Center (OAIC) is to improve independence and quality of life for older adults with serious illness. The Population Data Use and Management Resource Core (RC-PDM) will leverage a range of existing data sources including the Health and Retirement Study (HRS), the National Health and Aging Trends Study (NHATS), and the Medicare Current Beneficiaries Study (MCBS) to support research that will advance our understanding of the longitudinal course of Alzheimer’s Disease and Related Dementias (ADRD) and other serious illness for older adults and their caregivers. These high-quality data sources have sufficient sample sizes and durations of follow-up that allow for rigorous examination of clinical research questions of importance to seriously ill older adults, including those with ADRD, their caregivers, clinicians, and policy makers. Furthermore, the RC-PDM capitalizes on our experience using other data sources, including Veterans Health Administration (VA) data and the Mount Sinai Data Warehouse, which offers rich patient-level data drawn from the electronic health record. Led by Drs. Kelley and Ornstein, the RC-PDM complements the Population Research and Methods (RC-PRM) and Measurement Methods and Analyses (RC-MMA) Cores’ analytic and methodologic resources by providing data management and operational support to OAIC investigators. RC-PDM will engage in initiatives to specifically encourage population-based research in ADRD including implementing a validated algorithm to identify those with probable dementia using detailed cognitive and functional measures in combination with demographic and self-reported health characteristics, creating longitudinal cohorts of those with dementia, and supporting an external project to assemble a diverse, urban cohort of persons with dementia, linked to Medicare and Medicaid data, to examine predictors of disease progression and end-of-life treatment intensity. In addition, the RC-PDM will build infrastructure and operational support for a developmental project using geospatial analyses to examine ADRD and provide new infrastructure and support for population-based research by developing an inventory of datasets with harmonized measures of key constructs including ADRD for the study of older adults. The RC-PDM’s work with these data will support the research faculty within MS-OAIC and other Pepper Centers as part of our Pepper Trandisciplinary EXpertise To Improve Needed Geriatric Palliative Care (TEXTING-PC) research network, including analyses for pilot studies, career development award projects, and preliminary data for R01 applications. These goals will be accomplished through the following activities: consolidating population data management activities, acquiring new data sources, building and maintaining all infrastructure, and performing data updates, cleaning and linkages; harmonizing measures of ADRD and other key constructs across datasets; and ensuring that OAIC junior faculty have access to data, with emphasis on studies of dementia and implementation science.