The HIV and Alcohol Research center focused on Polypharmacy (HARP)

HARP整体项目总结 艾滋病毒和酒精研究中心专注于多药(HARP)的目标是设计和 对遭受医疗伤害的艾滋病毒(PAH)老年患者实施有效的个性化干预 来自不健康的酒精使用(风险和酒精使用障碍[AUD])和多药(5+药物)。 使用大规模的国家退伍军人医疗保健管理局电子健康记录数据(EHR数据)，我们 表现出强烈的独立、剂量-反应关系，在多药联用(药物计数和 A-PIMS)、饮酒和不良健康后果。在HARP项目1中，我们进一步探索酒精和 多药公司(AP)有使用直接酒精生物标记物(磷脂酰乙醇[PEH])的风险，考虑到遗传 易感性，并探索作为酒精相关表现的失代偿性肝硬变的相关性 肝病(AALD)。多药并存和遗传易感性也使AUD的治疗选择复杂化。在……里面 HARP项目2，我们使用遗传风险和真实世界数据来识别和评估候选药物 综合药房的背景。此外，非典型性肺炎的风险，特别是遗传责任，对 总结一下。既总结了多种风险因素的影响，又使用遗传数据来确定治疗 重新调整用途需要大规模、真实的数据、高性能计算和复杂的分析。 在我们的管理/数据分析(ADA)核心、能源部(DOE)、扩展的 Va EHR系列(VACO系列)，以及扩展的专家网络，我们将独一无二地做好准备 利用“大数据”来个性化PAH的AP风险，并评估治疗AUD的药物。最后，有效 AP风险消息的交流需要整合到基于理论的综合行为中 改变干预。我们已经组建了一个由专家组成的风险沟通核心(RCC)来促进风险 在我们的先导干预研究中进行沟通和动机访谈(MI)。核心包括杰弗里博士 健康行为改变的信息-动机-行为技能(IMB)模型的共同开发者Fisher说。在……里面 与Fisher博士合作，这一核心将指导我们应用IMB-MI模型进行沟通 在一系列相关的药剂师中，个性化风险和健康行为改变所需的其他因素- 提供试点干预措施。项目1的飞行员将比较患者对AP风险消息的反应(采用 暴露和结果的不同衡量标准)在IMB-MI干预的更大背景下交付 PAH是有风险的饮酒者；项目2的试点将纳入项目1中吸取的经验教训，并调整IMB- MI干预针对AUD的PAH，增加了一种用于AUD的重新调整用途的候选药物。

HARP OVERALL PROJECT SUMMARY The goal of the HIV and Alcohol Research center focused on Polypharmacy (HARP) is to design and implement effective personalized interventions for people aging with HIV (PAH) experiencing medical harm from unhealthy alcohol use (at risk and Alcohol Use Disorder [AUD]) and polypharmacy (5+ medications). Using large scale, national Veterans Healthcare Administration Electronic Health Record data (EHR data), we have shown strong independent, dose-response, associations between polypharmacy (medication count and A-PIMS), alcohol use, and adverse health outcomes. In HARP Project 1, we further explore alcohol and polypharmacy (AP) risks using a direct alcohol biomarker (Phosphatidylethanol [PEth]), considering genetic liability, and exploring associations with decompensated liver cirrhosis as a manifestation of alcohol-associated liver disease (AALD). Polypharmacy and genetic liability also complicate selection of treatment for AUD. In HARP Project 2, we use genetic liability and real-world data to identify and evaluate candidate medications in the context of polypharmacy. Further, AP risks, especially genetic liability, are complex and challenging to summarize. Both summarizing effects of multiple risk factors and using genetic data to identify medications for repurposing requires large-scale, real-world data, high performance computing and sophisticated analytics. With support from our Administrative/Data Analytic (ADA) Core, the Department of Energy (DOE), an extended VA family of EHR cohorts (VACo Family), and an expanded network of experts, we are uniquely poised to harness “big” data to personalize AP risks for PAH and evaluate medications for AUD. Finally, effective communication of AP risk messages needs to be integrated into a comprehensive, theory-based behavior change intervention. We have assembled a Risk Communication Core (RCC) of experts to facilitate risk communication and motivational interviewing (MI) in our pilot intervention studies. The core includes Dr. Jeffrey Fisher, co-developer of the Information-Motivation-Behavioral Skills (IMB) model of health behavior change. In collaboration with Dr. Fisher, this core will guide our application of the IMB-MI model to communicate personalized risk and other elements required for health behavior change in a linked series of pharmacist- delivered pilot interventions. Project 1 pilots will compare patient’s responses to AP risk messages (employing different measures of exposure and outcomes) delivered in the larger context of an IMB-MI intervention for PAH who are at risk drinkers; Project 2 pilots will incorporate lessons learned in Project 1 and adapt the IMB- MI intervention to target PAH with AUD, adding a candidate repurposed medication for AUD.