Addressing racial/ethnic geographic disparities in COVID-19 health services and outcomes among nursing home residents with ADRD

解决患有 ADRD 的疗养院居民在 COVID-19 卫生服务和结果方面的种族/民族地理差异

• 批准号: 10679243
• 负责人: JOE SILVA
• 金额: $ 4.77万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10679243
• 关键词: 2019-nCoV; Address; Affect; Alzheimer' s disease related dementia; Attenuated; Biostatistical Methods; Black race; COVID-19; COVID-19 disparity; COVID-19 pandemic; COVID-19 vaccine; Caring; Centers for Disease Control and Prevention (U.S.); Characteristics; Computerized Medical Record; Data; Data Analyses; Data Reporting; Databases; Disparity; Elderly; Electronic Health Record; Environment; Epidemiologist; Ethnic Origin; Ethnic Population; Future; Geographic Locations; Geography; Geriatrics; Gerontology; Goals; Health; Health Care Research; Health Services; Hispanic; Incidence; Individual; Infection; Infectious Disease Epidemiology; Interdisciplinary Study; Knowledge; Learning; Link; Measures; Mediator; Medicare claim; Methodology; Methods; Modeling; Nursing Homes; Outcome; Persons; Policies; Policy Maker; Population; Population Heterogeneity; Principal Investigator; Procedures; Public Health Schools; Quality of Care; Race; Research; Research Personnel; Services; Severities; Standardization; Statistical Methods; Training; Training Activity; United States Centers for Medicare and Medicaid Services; Universities; Vaccination; Vaccines; Work; analytical method; career; data resource; demographics; effective intervention; ethnic disparity; ethnic diversity; ethnic health disparity; ethnic minority population; experience; geographic disparity; health disparity; health equity; health equity promotion; improved; innovation; marginalization; mortality; multilevel analysis; novel; outcome disparities; pandemic disease; poor health outcome; racial disparity; racial diversity; racial health disparity; racial minority; racial population; residence; simulation; skills

PROJECT SUMMARY Racial/ethnic health disparities exist for a wide array of nursing home (NH) services and health outcomes. These disparities directly impact the care received by older adults in NHs. Alzheimer's Disease and Related Dementias (ADRD) serve as a “disparity multiplier,” in that Black and Hispanic NH residents have worse health outcomes and these differences are more pronounced for residents with ADRD. The importance of the intersection and severity of racial/ethnic health disparities and ADRD has been highlighted by the COVID-19 pandemic, which has disproportionately impacted NH residents and those with ADRD. The pandemic has also revealed how significantly these disparities may vary by geography. Despite the differences in COVID-19 outcomes by race/ethnicity and geography, and the potential exacerbation of these disparities by ADRD status, little evidence exists to reveal exactly how or to what extent race/ethnicity, geography, and ADRD status intersect to jointly impact the health outcomes of older NH residents. Additionally, the optimal methods for estimating wide-ranging health disparities between racially/ethnically diverse subpopulations of varying sizes and demographics across geographic units remain unclear. The long-term objective of the proposed research is therefore to develop a causal inference framework for studying racial/ethnic health disparities across different geographic units. Aim 1 will identify the most appropriate analytic approaches for quantifying racial/ethnic disparities across geographic units by conducting a simulation study comparing several existing biostatistical methods. Aim 2 will leverage these results to quantify health disparities in COVID-19 vaccine use and outcomes by racial/ethnic status, ADRD status, and geography through the use of a first-of-its-kind database of electronic medical records linked to Medicare claims data from approximately 10,000 US NHs. This research will provide some of the first empirical evidence for policymakers and other stakeholders that can be used to improve health equity for COVID-19 and other conditions. It will also establish unique methods that can be used broadly to conduct accurate, timely, and relevant future studies of disparities among NH residents and other populations. These proposed studies will be completed by the principal investigator with support from collaborators with deep expertise in advanced statistical methods, health disparities, infectious disease epidemiology, geriatrics, and ADRD. The principal investigator is supported by a collaborative and interdisciplinary research environment that includes the Center for Gerontology and Health Care Research at the Brown University School of Public Health. The training activities detailed in this application are focused on advancing quantitative computational skills and developing a deep contextual knowledge of racial/ethnic health disparities and the care of older adults with ADRD; they will prepare the principal investigator for a career as an independent epidemiologist and health services researcher.

项目摘要 种族/民族的健康差异存在广泛的养老院（NH）服务和健康结果。这些 差异直接影响到老年人在NHS中接受的护理。阿尔茨海默病及相关痴呆 （ADRD）作为“差距乘数”，因为黑人和西班牙裔NH居民的健康状况更差 这些差异在ADRD患者中更为明显。十字路口的重要性， 种族/民族健康差异和ADRD的严重性已被COVID-19大流行所突显， 对NH居民和ADRD患者的影响尤为严重。大流行病还揭示了 重要的是，这些差异可能因地域而异。尽管COVID-19的结果存在差异， 种族/民族和地理，以及ADRD状态可能加剧这些差异，证据很少 存在，以揭示种族/民族，地理和ADRD状态如何或在多大程度上相互交叉， 影响老年NH居民的健康结果。此外，估计宽范围的最佳方法 不同规模和人口统计数据的不同种族/族裔亚群之间的健康差距 地理单位仍不清楚。因此，拟议研究的长期目标是开发一种 因果推理框架，用于研究不同地理单位的种族/民族健康差异。要求1 将确定最适当的分析方法，以量化地理区域内的种族/民族差异， 单位进行模拟研究，比较现有的几种生物统计方法。Aim 2将利用 这些结果用于量化COVID-19疫苗使用的健康差异和按种族/民族状况、ADRD 通过使用第一个同类的电子病历数据库， 医疗保险索赔数据来自大约10，000个美国国家卫生机构。这项研究将提供一些第一个实证 为政策制定者和其他利益相关者提供可用于改善COVID-19健康公平性的证据， 其他条件。它还将建立独特的方法，可广泛用于进行准确，及时， 相关的未来研究之间的差距NH居民和其他人群。这些拟议的研究将 由主要研究者在具有高级统计学专业知识的合作者的支持下完成 方法、健康差异、传染病流行病学、老年病学和ADRD。主要研究者 由包括老年学中心在内的协作和跨学科研究环境支持 和布朗大学公共卫生学院的卫生保健研究。本报告中详细介绍的培训活动 应用程序的重点是推进定量计算技能和开发一个深刻的上下文 了解种族/民族健康差异和老年ADRD患者的护理;他们将准备 作为一名独立的流行病学家和卫生服务研究员的职业生涯的首席研究员。