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HIV/AIDS治疗的临床有效性和成本。因此，确保获得抗逆转录病毒疗法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）为那些无法获得其他药物的人提供ART。ADAP主要服务于低收入、无保险的少数群体，为历史上得不到充分服务的人口提供护理。随着艾滋病毒感染者存活率的增加，适应艾滋病毒的行动方案正处于危机之中。计划面临着关于优先考虑ART资源的困难决定。在ADAP等待名单上的患者中存在显著的、可预防的发病率。此外，随着HCV治疗变得更加有效，ADAP将面临向HIV/HCV合并感染患者提供HCV治疗的压力，这威胁到许多人获得ART的稳定性。这种情况突出了艾滋病毒护理系统对结果的影响问题。在这个K 01辅导职业奖的应用程序，我建议使用离散事件模拟，一种创新的数学建模方法，来估计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资源优先级策略的影响。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并验证HIV感染的离散事件模拟模型。2.使用经验证的模型来估计与几个艾滋病药物援助计划资源优先级策略相关的结果，包括改变资格规则，重组药物处方集和改善成本预测。3.扩展该模型以包括HIV/HCV合并感染，并使用它来比较HCV资源分配的潜在策略范围下的结果。为了补充这些研究工作，我将追求先进的生物统计学，运筹学，以及对健康公平的制度结构的影响课程工作。这项研究和教学经验将为R 01基金奠定基础，以调查大规模的，计划性的资源分配决定对艾滋病毒和丙型肝炎病毒临床结果的影响。该K 01奖将导致一个新的，独立的研究轨迹，并将告知艾滋病毒和丙型肝炎病毒的护理和政策在美国。

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.