Optimizing HIV care for patients with substance use disorders using predictive analytics in a mobile health application

项目摘要 现在人们普遍认为，通过扩大抗逆转录病毒疗法（ART）的规模来降低社区病毒载量， 减少艾滋病毒在吸毒者中的传播。然而，实现持久的病毒抑制， 患有药物使用障碍的患者是临床提供者和卫生系统面临的主要挑战。患者 患有药物使用障碍的人不断面临复发和其他破坏性生活事件的风险。这可能导致 抗逆转录病毒治疗经常失误，随后病毒反弹，增加了健康风险， 与艾滋病毒有关的问题以及将艾滋病毒传染给他人的风险。该项目解决了以下问题： 通过测试创新的移动的医疗（mHealth）系统的有效性， 旨在支持正在接受艾滋病毒护理的艾滋病毒感染者和药物使用障碍者。的 移动健康干预，称为A-CHESS，是一种基于证据的智能手机应用程序， 通过改善社会联系，减少物质使用并提高成瘾治疗的保留率， 内在动机和应对能力。在这个2阶段的交叉临床试验中，我们将提供 运行A-CHESS应用程序的智能手机对150名HIV阳性患者进行了测试，这些患者过去一年有 酒精、阿片类药物或兴奋剂使用障碍。在第一阶段，参与者将使用A-CHESS应用程序， 在6个月内，以真实的时间报告数据，描述他们的药物使用，情绪，社会支持和其他因素 生态瞬时评估（EMA）研究。这些数据将用于开发和验证预测 该人群的治疗不依从性模型。6个月后，所有患者都将进入第二阶段。 研究阶段，在此期间，将使用 A-CHESS平台同时，A-CHESS捕获的数据描述了参与者的治疗风险， 失效将传达给患者的提供者和临床支持人员，以便及时和集中 支持干预。干预措施对提高病毒抑制率的有效性将是 使用混合效应logistic回归模型进行评估。这个项目有可能产生巨大的影响 因为它确定了吸毒患者艾滋病毒护理失误的关键时变决定因素， 并将这些不同的输入转换为可操作的、针对患者的警报，以提供给临床提供者。

PROJECT SUMMARY It is now well-accepted that lowering community viral load through scale-up of antiretroviral therapy (ART) can reduce HIV transmission among people who use drugs. However, achieving durable viral suppression among patients with substance use disorders is a major challenge for clinical providers and health systems. Patients with substance use disorders are continuously at risk for relapse and other disruptive life events. This can lead to frequent lapses in antiretroviral treatment and subsequent viral rebound, which increases the risk of health problems related to HIV and the risk of transmitting HIV to others. This project addresses the problem of lapses in antiretroviral treatment by testing the effectiveness of an innovative mobile health (mHealth) system designed to support people living with HIV and substance use disorders who are receiving HIV care. The mHealth intervention, called A-CHESS, is an evidence-based smartphone application previously shown to reduce substance use and improve retention in addiction treatment by improving social connectedness, intrinsic motivation and coping competence. In this 2-stage, crossover clinical trial, we will provide smartphones running the A-CHESS application to 150 HIV-positive patients who have a past-year history of alcohol, opioid, or stimulant use disorder. In the first phase, participants will use the A-CHESS application to report data in real time describing their drug use, mood, social support, and other factors during a 6-month ecologic momentary assessment (EMA) study. These data will be used to develop and validate a predictive model of treatment non-adherence in this population. After 6 months, all patients will cross over to the second study phase, during which the full, multi-component, tailored mHealth intervention will be delivered using the A-CHESS platform. Simultaneously, data captured by A-CHESS describing participants' risk of treatment lapse will be communicated to patient's providers and clinical support staff, allowing timely and focused support interventions. The effectiveness of the intervention for improving the rate of viral suppression will be assessed using a mixed effects logistic regression model. This project has the potential for high impact because it identifies the critical time-varying determinants of lapses in HIV care for substance using patients, and translates these diverse inputs into actionable, patient-specific alerts to clinical providers.