Population Data Use and Management (RC-PDM)

摘要/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)的首要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)和联邦医疗保险当前受益人研究(MCBS)，以支持研究，这些研究将促进我们对阿尔茨海默氏症和相关痴呆(ADRD)以及老年人及其照顾者的其他严重疾病的纵向病程的了解。这些高质量的数据来源有足够的样本量和跟踪持续时间，允许严格检查对重症老年人(包括ADRD患者、他们的照顾者、临床医生和政策制定者)至关重要的临床研究问题。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，后者提供从电子健康记录中提取的丰富的患者级别数据。在Kelley博士和Ornstein博士的领导下，RC-PDM通过向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将参与具体鼓励ADRD基于人群的研究的举措，包括实施一种经过验证的算法，以使用详细的认知和功能测量结合人口统计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，并支持一个外部项目，以收集与Medicare和Medicaid数据相关联的多样化的城市痴呆症患者队列，以检查疾病进展和临终治疗强度的预测因素。此外，区域中心-产品数据管理将利用地理空间分析为一个发展项目建立基础设施和业务支持，以审查ADRD，并通过编制一份数据集清单，为基于人口的研究提供新的基础设施和支持，其中包括老年人研究的ADRD等关键结构的协调措施。RC-PDM使用这些数据的工作将支持MS-OAIC和其他胡椒中心的研究人员，作为我们胡椒跨学科专业知识的一部分，以改善所需的老年姑息治疗(TEXTING-PC)研究网络，包括对试点研究、职业发展奖项目的分析，以及R01申请的初步数据。这些目标将通过以下活动实现：合并人口数据管理活动，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；统一ADRD和数据集中其他关键结构的措施；并确保OAIC初级教员能够获得数据，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.