HIV Testing, Linkage and Retention in Care: Contextual Factors and Disparities

描述(由申请人提供)：这项研究的目的是确定人们获得医疗保健的环境(即医疗保健环境)或生活环境(即居住环境)与五种结果(艾滋病毒检测、TES结果的接收、与艾滋病毒/艾滋病护理的联系、保留在艾滋病毒护理中和艾滋病毒病毒载量)之间是否存在关联。少数族裔(特别是黑人和拉丁裔)和老年人(即50岁及以上)中艾滋病毒/艾滋病的流行情况表明，他们可能会遇到障碍，导致在艾滋病毒早期发现和预后方面存在差异。因此，我们还将按种族/民族和年龄(年龄&>50岁)检查结果的差异。利用社会行为科学，这项研究将为临床实践提供信息，以促进不同群体、社区条件和成年阶段的护理公平。这项研究的主要目标是：(1)基于初级保健患者的电子病历，使用具有随机效应的Logistic回归多水平模型来检验初级保健就诊期间医疗保健背景、居住背景与艾滋病毒检测之间的关系；以及(2)使用具有随机效应的多水平Logistic回归和Cox比例风险模型，分别检验卫生保健背景、居住背景与艾滋病毒检测结果的接收之间的关系以及与艾滋病毒/艾滋病护理的联系。第二个具体目标是确定在这些关系中是否存在种族/族裔或年龄相关的差异(即50岁与50岁)。在我们艾滋病毒检测和护理工作的基础上，以及 在整合了公共卫生关键竞赛实践和医疗保健利用行为模型的指导下，这项为期四年的研究基于该地区最大的管理型医疗组织登记的成年人的电子病历(EMR)。我们将在五年内(2007-2011年)收集数据，以检查所有接受初级保健的患者的艾滋病毒检测结果，并检查艾滋病毒检测结果的接收情况、与艾滋病毒/艾滋病护理的联系和保留情况以及所有新诊断为艾滋病毒阳性的患者的艾滋病毒病毒载量。这项研究将包括四个多层次的分析，即患者的居住环境(例如，社区艾滋病毒流行情况)和医疗环境(例如，患者人口的特征)与艾滋病毒检测期间的关系(目标1)、初级保健就诊(目标1)、艾滋病毒检测结果的接收以及与艾滋病毒/艾滋病护理的联系(目标2)、在艾滋病毒/艾滋病护理中的保留时间和诊断后长达一年的艾滋病毒RNA病毒载量。我们将使用EMRS中的个人和地理空间代码链接到：(1)包含每个提供者的详细信息(例如，人口统计、专业)的文件；(2)疾病控制和预防中心关于每个邮政编码的艾滋病毒流行率和艾滋病毒检测地点的公共数据；(3)每个邮政编码的2010年人口普查社会经济数据(例如，集中贫困人口)；以及(4)全球定位系统软件，以计算患者家到提供者的距离。这种跨学科、跨机构的合作利用了一支由新的和经验丰富的调查人员组成的多样化团队的专业知识。

DESCRIPTION (provided by applicant): The purpose of this study is to determine if associations exist between the contexts in which people obtain healthcare (i.e., healthcare context) or live (i.e., residential context) and each of five outcomes (HIV testing, receipt of tes results, linkage to HIV/AIDS care, retention in HIV care and HIV viral load). The epidemiology of HIV/AIDS among racial/ethnic minorities (specifically, Blacks and Latinos) and older adults (i.e., 50 and older) suggests they may encounter barriers that contribute to disparities in early detection of HIV and in their prognoses. Hence, we will also examine disparities in the outcomes by race/ethnicity and older age (age >50). Drawing on the socio-behavioral sciences, the study will inform clinical practice in ways that promote equity in care across diverse groups, neighborhood conditions and stages of adulthood. The study's primary Specific Aims are to: (1) Examine relations between healthcare context, residential context and HIV testing during primary care visits using logistic regression multilevel models with random effects based on primary care patients' electronic medical records; and, (2) Examine relations between healthcare context, residential context and receipt of HIV test results and linkage to HIV/AIDS care, respectively, among managed care enrollees newly diagnosed as HIV-positive using multilevel logistic regression and Cox proportional hazards models with random effects. The secondary Specific Aim is to determine if racial/ethnic- or age-related (i.e., aged <50 vs. >50 years) disparities exist in these relationships. Building on our work on HIV testing and care, and guided by a model integrating the Public Health Critical Race Praxis and Behavioral Model of Healthcare Utilization, the four-year study based on the electronic medical records (EMRs) of adults enrolled in the largest managed care organization in the region. We will pool data over five years (2007-2011) to examine HIV testing among all patients presenting for primary care, and to examine receipt of HIV test results, linkage to and retention in HIV/AIDS care as well as HIV viral load among all patients newly diagnosed as HIV-positive. The study will comprise four multilevel analyses of patients' residential contexts (e.g., neighborhood HIV prevalence) and healthcare contexts (e.g., characteristics of the patient population) relative to HIV testing durin primary care visits (Aim 1), receipt of HIV test results and linkage to HIV/AIDS care among those diagnosed as HIV-positive (Aim 2), retention in HIV/AIDS care and HIV RNA viral load up to one-year post diagnosis. We will use personal and geospatial codes in the EMRs to link to: (1) files containing detailed information on each provider (e.g., demographics, specialty); (2) public data from the Centers for Disease Control and Prevention on HIV prevalence and HIV test sites in each zip code; (3) 2010 Census socioeconomic data (e.g., concentrated poverty) for each zip code; and, (4) global positioning system software to calculate the distance from a patient's home to their provider. This interdisciplinary, inter- institutional collaboration leveraes the expertise of a diverse team of new and seasoned investigators.