Patterns and predictors of racial/ethnic disparities in HIV care continuum in the South

南方艾滋病毒护理连续体中种族/民族差异的模式和预测因素

• 批准号: 10618007
• 负责人: Xueying Yang
• 金额: $ 39.87万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-13 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10618007
• 关键词: AIDS prevention; Acquired Immunodeficiency Syndrome; Address; African American; Area; Attenuated; Big Data; Black race; COVID-19 pandemic; Caring; Clinical; Coin; Communities; Continuity of Patient Care; County; Data; Data Analytics; Data Sources; Diagnosis; Disparity; Ensure; Epidemic; Equity; Ethnic Origin; Funding; Geographic Locations; Geography; Goals; HIV; HIV Infections; HIV diagnosis; Health; Health Disparities Research; Health Personnel; Healthcare; Healthcare Systems; Housing; Human immunodeficiency virus test; Individual; Intervention; Lasso; Latino Population; Link; National Institute of Allergy and Infectious Disease; Neighborhoods; Occupations; Outcome; Patients; Pattern; Persons; Phase; Policies; Poverty; Race; Reporting; Research; Research Personnel; Risk; Role; Rural; Services; Shapes; Source; South Carolina; Structural Racism; Symptoms; Time; Treatment outcome; US State; United States National Institutes of Health; Variant; Viral; Work; cohort; contextual factors; data integration; ethnic disparity; ethnic health disparity; ethnic minority; ethnic minority population; experience; gender minority community; geographic difference; health care availability; health care delivery; health disparity; health equality; health equity; health equity promotion; improved; indexing; innovation; low health literacy; multiple data sources; patient population; population health; poverty reduction; predictive modeling; prevention service; programs; racial disparity; racial health disparity; racial minority; racial minority population; racial population; residential segregation; rurality; secondary analysis; segregation; service organization; sexual minority community; social; social disparities; social equality; social factors; social health determinants; social stigma; social structure; spatiotemporal; treatment services; trend

Project Summary/Abstract The HIV care continuum (HCC), a compelling framework to describe the current clinical goals for managing HIV infection, tracks the progression of people living with HIV (PLWH) from diagnosis, through linkage to care, retention in care, and ultimately to the goal of viral suppression. Unfortunately, health disparities exist at every step of the continuum among racial/ethnic minority population. Such racial/ethnic disparities may have significantly delayed the progress in HCC in the Southern US states that are strongly represented among geographic focus areas in the 2019 federal initiative titled “Ending the HIV Epidemic: A Plan for America” (EtHE). Given the unabated high levels of segregation over time in some areas of the South, it is critical to identifying drivers of health disparities in HCC outcomes and advance health equity and improve population health. A singular focus on individual-level strategies to improve health and ameliorate health disparities has been reported ineffective. Recognition of the impact of social factors, which have been coined as fundamental causes of racial/ethnic health disparities because of their role in shaping other myriad factors important for promoting health equities, has prompted a global shift in focus away from simply addressing symptoms and conditions to also considering patient social needs and lived experiences in assessment and treatment. However, limited efforts have been made to quantify the long-term spatiotemporal variations of HCC disparities and their contributing factors over time, particularly in the context of COVID-19 pandemic. With NIH support (R01AI127203) since 2017, we have been utilizing a Big Data approach to examine treatment gaps among PLWH in South Carolina (SC). The ongoing research extracted and linked longitudinal EHR data from six state agencies. The cohort in the existing project include all PLWH who were diagnosed through December 2020 in SC. To address the gaps in HCC-related health disparity research, we will leverage the exiting data from R01AI127203 project and link these data to aggregated community and social structural level data (e.g., structural racism, COVID-19 pandemic) from multiple publicly available data sources. Beyond the scope of original project, we will first identify the spatiotemporal patterns of racial disparities (e.g., exacerbating or attenuating trend) of each HCC outcome, then determine the contribution of contextual features for temporal change of disparities in HCC using the multivariable generalized regression with lasso penalty. The proposed research is innovative and significant because identifying and reducing racial/ethnic disparities in HCC outcomes is essential to understand the fundamental causes and evolving risk of poor HCC outcomes and achieve the EtHE goals in SC and other Southern states in the US. The research findings could inform state health department to promote social equality, motivate healthcare systems to address patients’ social needs as part of healthcare delivery, and devise more precise, targeted intervention strategies for socially disadvantaged areas to achieve the health equality and improve HIV treatment outcomes.

项目总结/摘要 艾滋病毒护理连续体（HCC），一个令人信服的框架，以描述目前的临床目标，管理 艾滋病毒感染，跟踪艾滋病毒感染者（PLWH）从诊断，通过联系， 护理，保持护理，并最终达到抑制病毒的目标。不幸的是， 种族/少数民族人口之间的连续性的每一步。这种种族/民族差异可能会导致 显着推迟了美国南部各州HCC的进展，这些州在美国南部各州中占有重要地位 2019年联邦题为“结束艾滋病毒流行：美国计划”的倡议的地理重点领域 （EtHE）。鉴于长期以来南方一些地区的隔离程度居高不下， 确定HCC结果中健康差异的驱动因素，并促进健康公平和改善人口 健康一个单一的重点是个人一级的战略，以改善健康和改善健康的差距， 据报道，无效。认识到社会因素的影响，这些因素被认为是 种族/族裔健康差异的原因，因为它们在形成其他无数重要因素方面的作用， 促进健康公平，促使全球的重点从简单地解决症状转变为 在评估和治疗时，还应考虑患者的社会需求和生活经验。 然而，有限的努力已经量化的长期时空变化的肝癌 随着时间的推移，特别是在COVID-19大流行的背景下，我们需要了解差异及其影响因素。与 自2017年以来，NIH支持（R 01 AI 127203），我们一直在利用大数据方法来检查治疗差距 在南卡罗来纳州的PLWH中。正在进行的研究提取并链接纵向EHR数据， 六个国家机构。现有项目中的队列包括截至12月诊断的所有艾滋病毒携带者 为了解决HCC相关健康差异研究的差距，我们将利用现有数据 从R 01 AI 127203项目，并将这些数据链接到汇总的社区和社会结构水平数据（例如， 结构性种族主义、COVID-19大流行）来自多个公开数据源。范围以外 最初的项目，我们将首先确定种族差异的时空模式（例如，恶化或 衰减趋势），然后确定上下文特征对时间的贡献。 使用多变量广义回归和套索罚分分析HCC中差异的变化。拟议 研究是创新的和重要的，因为识别和减少HCC中的种族/民族差异 结果对于了解HCC不良结果的根本原因和不断变化的风险至关重要， 在南卡罗来纳州和美国其他南部各州实现EtHE目标。研究结果可以告知国家 卫生署致力促进社会平等，推动医疗系统照顾病人社会需要， 作为医疗服务的一部分，并为社会弱势群体制定更精确、更有针对性的干预战略 实现健康平等和改善艾滋病毒治疗结果。