Analyzing Patient-Provider Communication to Understand Disparities in HIV Care

本研究的长期目标是了解患者与提供者沟通的差异 影响到艾滋病毒感染者获得护理方面的差距。这些知识将有助于发展 以证据为基础的干预措施，与病人和供应商，以消除这些差距。 白人和非白人之间在艾滋病毒护理方面存在各种差异， 包括可能对患者影响最大的因素， 艾滋病毒抗逆转录病毒药物。这些差异有许多根源，包括护理系统 获得、偏好或对治疗价值的信念差异以及对被污名化的人的偏见 例如注射毒品使用者。 这些差异的一个重要来源可能是病人提供者的性质和质量的差异 传播，这是一个很少受到艾滋病毒研究人员关注的话题。为了填补这一空白，我们开发了 并验证了一种编码和分析艾滋病护理中患者与提供者互动录音带的新方法， 通用医疗交互分析系统（GMIAS）。这种编码系统的一个独特之处在于， 特征化患者-提供者对话中与ARV药物依从性具体相关的话语。 我们建议使用GMIAS来分析收集的435名艾滋病毒感染者的患者-提供者访问记录 来自在巴尔的摩、纽约、底特律和波特兰4个不同护理中心执业的45名医生， 现有的研究。患者从参与医生的实践中抽样，大约一半 为白色，一半为非白色，这有助于医生内种族差异的比较。 使用GMIAS编码系统，我们提出了以下具体目标：1）比较 白色和非白色患者之间的患者-提供者沟通，2）比较ARV相关依从性 白色和非白色患者之间的对话，3）使用方差分量分析确定方差 在以病人为中心是病人和供应商之间的分区，和4）确定是否1年的艾滋病毒 结果（病毒载量和CD4计数的变化）在黑人和白人之间存在差异， 总体和依从性特定对话质量的差异解释了HIV结果的差异。 这项研究与公共卫生的相关性在于，努力消除与以下方面有关的保健差距： 种族/族裔将需要更好的数据来说明这些差异的来源。这项研究的结果将有助于 我们更好地了解患者-提供者对话如何导致艾滋病毒护理中的这些差异，并提供 消除这些差距的努力亟需证据基础。项目叙述 虽然感染艾滋病毒的白人和非白人所获得的护理之间存在重大差距， 根据记录，包括抗逆转录病毒治疗接受率的差异，这些差异的根源是 不太了解。本项目将使用一种新的方法来编码和分析提供商的录音带 沟通，以了解患者-提供者对话如何因种族和民族而异。的独特特征 这一新的编码方法允许详细评估抗逆转录病毒药物治疗的依从性。

The long-term objective of this research is to understand how differences in patient-provider communication affect disparities in the care received by persons with HIV. This knowledge will facilitate the development of evidence based interventions, with both patient and providers, to eliminate these disparities. A variety of types of disparities in HIV care between whites and non-whites have been demonstrated, including what may be the most consequential for patients, disparities in rates of initiation of and adhering to HIV antiretroviral medications (ARVs). These disparities have many root causes, including care system access, differences in preferences or beliefs about the value of treatments, and bias against stigmatized groups such as injection drug users. An important source of these disparities may be differences in the nature and quality of patient-provider communication, a topic which has received little attention from HIV researchers. To fill this gap, we developed and validated a new method to code and analysis audiotapes of patient-provider interactions in HIV care, the General Medical Interaction Analysis System (GMIAS). A unique feature of this coding system is that it can characterize utterances in patient-provider dialog that are specifically related to ARV medication adherence. We propose to use GMIAS to analyze transcripts of 435 patient-provider visits for persons with HIV collected from 45 physicians practicing at 4 different care sites in Baltimore, New York, Detroit, and Portland as part of an existing study. Patients were sampled from participating physicians' practice such that approximately half were white and half were non-white, which facilitates within-physician comparisons of racial differences. Using the GMIAS coding system, we propose the following specific aims: 1) Compare general patterns of patient-provider communication between white and non-white patients, 2) Compare ARV related adherence dialog between white and non-white patients, 3) Determine, using variance components analysis, how variance in patient-centeredness is partitioned between patients and providers, and 4) Determine whether 1-year HIV outcomes (changes in viral loads and CD4 counts) differ between blacks and whites, and the extent to which differences in overall and adherence specific dialog quality explain differences in HIV outcomes. The relevance of this research to public health is that efforts to eliminate disparities in care related to race/ethnicity will require better data about the sources of those disparities. The results of this study will help us better understand how patient-provider dialog contributes to these disparities in HIV care, and provide a much needed evidence base for efforts to eliminate these disparities. Project Narrative While important disparities between the care received by whites and non-whites with HIV infection have been documented, including differences in rates of receipt of antiretroviral therapy, the source of these disparities is poorly understood. This project will use a new method to code and analyze audiotapes of provider communication to understand how patient-provider dialogue differs by race and ethnicity. A unique feature of this new coding method is that it permits detailed assessment of antiretroviral medication adherence.