Improving HIV and HCV outcomes in U.S. AIDS Drug Assistance Programs

描述(由申请人提供)：抗逆转录病毒疗法(ART)增加了艾滋病毒/艾滋病治疗的临床有效性和成本。因此，确保获得抗逆转录病毒治疗的美国医疗保健计划没有足够的资源为所有可能受益的人提供治疗。美国艾滋病药物援助计划(ADAP)为那些没有其他途径获得药物的人提供抗逆转录病毒治疗。ADAP主要服务于低收入、没有保险的少数群体，为历史上服务不足的人群提供护理机会。随着艾滋病毒携带者存活率的增加，ADAP正处于危机之中。项目面临着对艺术资源进行优先排序的艰难决定。在ADAP等待名单上的患者中，有显著的、可预防的发病率。此外，随着丙型肝炎病毒治疗变得更加有效，ADAP将面临越来越大的压力，要求向艾滋病毒/丙型肝炎合并感染的患者提供丙型肝炎病毒治疗，威胁到许多人获得抗逆转录病毒治疗的稳定性。这种情况突出了有关艾滋病毒护理系统对结果的影响的问题。在这份K01指导职业奖申请中，我建议使用离散事件模拟，这是一种创新的数学建模方法，以评估资源优先排序战略对艾滋病毒和艾滋病毒/丙型肝炎发病率、死亡率和获得护理的影响。这三个具体目标是：1.在美国艾滋病药物援助计划的背景下，建立和验证HIV感染的离散事件模拟模型。2.使用经过验证的模型来估计与几个艾滋病药物援助计划资源优先排序策略相关的结果，包括改变资格规则、调整药物处方和改进成本预测。3.将模型扩展到包括艾滋病毒/丙型肝炎病毒混合感染，并使用它来比较分配丙型肝炎病毒资源的各种潜在战略下的结果。为了补充这些研究努力，我将继续在高级生物统计学、运筹学和机构结构对卫生公平的影响方面的课程工作。这项研究和教学经验将为R01基金奠定基础，以调查大规模、程序性资源分配决定对艾滋病毒和丙型肝炎临床结果的影响。这一K01奖项将导致一条新的、独立的研究轨迹，并将为美国的艾滋病毒和丙型肝炎病毒护理和政策提供参考。

DESCRIPTION (provided by applicant): Antiretroviral therapy (ART) increases both the clinical effectiveness, and cost of HIV/AIDS treatment. As a result, U.S. health care programs ensuring access to ART do not have sufficient resources to provide therapy to all who might benefit. U.S. AIDS Drug Assistance Programs (ADAPs) provide ART to those with no other access to medications. ADAPs serve primarily low-income, uninsured, minorities, providing access to care to historically underserved populations. As survival with HIV increases, ADAPs are in crisis. Programs face difficult decisions about prioritizing ART resources. There is significant, preventable morbidity among patients on ADAP waitlists. Further, as HCV treatment becomes more effective, pressure will build on ADAPs to provide HCV therapy to HIV/HCV co-infected patients, threatening the stability of ART access for many. This situation highlights questions about the impact of the HIV-care system on outcomes. In this K01 mentored career award application, I propose using discrete event simulation, an innovative mathematical modeling method, to estimate the impact of resource prioritization strategies on HIV and HIV/HCV morbidity, mortality, and access to care. The three specific aims are: 1. To build and validate a discrete event simulation model of HIV infection in the context of U.S. AIDS Drug Assistance Programs. 2. To use the validated model to estimate outcomes associated with several AIDS Drug Assistance Program resource prioritization strategies including altering eligibility rules, restructuring drug formularies, and Improving cost projections. 3. To expand the model to include HIV/HCV co-infection and use it to compare outcomes under spectrum of potential strategies for allocating HCV resources. To complement these research efforts, I will pursue course-work in advanced biostatistics, operations research, and the impact of institutional structures on health equity. This research and didactic experience will lay the foundation for R01 funding to investigate the implications of large-scale, programmatic resource allocation decisions on clinical outcomes in HIV and HCV. This K01 award will lead to a novel, independent trajectory of research, and will inform HIV and HCV care and policy in the United States.