Task Shifting Model of Depression Treatment to Unleash HIV Public Health Benefits

描述（由申请人提供）：为响应NIH/PEPFAR RFA的实施科学和影响评估，本申请涉及以下优先领域：整合HIV初级保健和常见的合并症（抑郁症），并检查抑郁症治疗作为促进HIV护理依从性和预防传播的手段。我们的研究强调了抑郁症在若干公共卫生领域阻碍抗击艾滋病毒疾病的努力中的作用，以及尽管我们观察到抗抑郁药对艾滋病毒/艾滋病患者（PLHA）有效，但在撒哈拉以南非洲（SSA）的艾滋病毒护理计划中抑郁症治疗的相对缺失，基于此，拟议的项目将评估一种任务转移方法，以建立可持续的抑郁症治疗能力。缺乏训练有素的精神卫生专家是提供治疗的主要障碍，然而，克服人力资源限制的任务转移方法已成功地扩大了SSA的抗逆转录病毒治疗，并以协作护理模式向非艾滋病毒患者提供抑郁症治疗；然而，拟议的研究可能是首次对PLHA和SSA进行此类模型的研究。我们将测试一个基于算法、护士驱动的抗抑郁治疗管理模型，该模型包括：(1)在每次就诊时对所有患者进行常规抑郁症筛查，从而促进病例识别；(2)培训护士，通过进行初步评估、监测症状和副作用，并根据算法提出剂量建议，协助初级保健提供者实施抗抑郁治疗。(3)由精神科专家进行层层监督和监测，以确保护理的安全和质量。使用聚类随机化设计，任务转移模型将在六个诊所实施，而其他六个诊所将使用标准的医生驱动模型。在每个地点，将随机抽取150名医学上稳定的抑郁症筛查呈阳性的患者进行12个月的随访，以评估两种治疗模式在抗抑郁药物治疗吸收和抑郁症变化的护理质量指标上是否存在差异。我们还将评估抑郁症的改变是否与关键的经济和公共卫生结果有关，包括工作能力和养家能力、一贯使用避孕套和坚持艾滋病毒治疗。时间和动作评估将在治疗模式开始前的两周，以及治疗模式开始后的一年和两年，对每个地点随机选择的100名患者的新样本进行评估，以评估对诊所效率和患者流量的影响。如果我们证明这种任务转移治疗抑郁症的方法是可行的，有效的，并且很好地融入了临床系统，它将建立一个模型，解决人力资源挑战，建立可持续的抑郁症治疗能力。

DESCRIPTION (provided by applicant): In response to the NIH/PEPFAR RFA for implementation science and impact evaluation, this application addresses these priority areas: integration of HIV primary care and a common co-morbidity (depression), and examining depression treatment as a means to promote HIV care adherence, and prevention of transmission. Building on our research that highlights the role of depression in thwarting efforts to combat HIV disease on several public health fronts, and the relative absence of depression treatment in HIV care programs throughout sub-Saharan Africa (SSA) despite our observed efficacy of antidepressants with persons living with HIV/AIDS (PLHA), the proposed project will evaluate a task-shifting approach to building the capacity for sustainable depression treatment. Lack of trained mental health specialists is a major barrier to provision of treatment, yet task-shifting approaches to overcoming human resource limitations have been successful for ART scale-up in SSA, as well as provision of depression treatment in collaborative care models with non-HIV patients; however, the proposed study may be the first study of such a model with PLHA, and in SSA. We will test an algorithm-based, nurse-driven model for managing antidepressant treatment that includes (1) case identification facilitated by routine depression screening at each clinic visit for all patients, (2) training nurses to assist primary care provides in implementing antidepressant treatment by performing the initial evaluation, monitoring symptoms and side effects, and making algorithm-based dose recommendations, and (3) layers of supervision and monitoring by psychiatric specialists to ensure safety and quality of care. Using a cluster- randomization design, the task-shifting model will be implemented at six clinics, while six other clinics will use the standard physician-driven model. At each site, a random sample of 150 medically stable patients who screen positive for depression will be followed for 12 months to assess whether the two models of treatment differ on the quality of care indicators of antidepressant treatment uptake and change in depression. We will also assess whether change in depression is associated with key economic and public health outcomes including ability to work and provide for one's family, consistent condom use, and HIV care adherence. Time-and-motion assessments will be done with new samples of 100 randomly selected patients at each site during two week periods before, and one and two years after, initiation of the treatment models to assess impact on clinic efficiency and patient flow. If we demonstrate that this task-shifting approach to depression treatment is feasible, effective and well incorporated into clinic systems, it will establish a model that addresses the human resource challenges to building the capacity for sustainable depression treatment. PUBLIC HEALTH RELEVANCE: This study is important to public health as its findings could demonstrate that the task-shifting approach to depression treatment is feasible, effective and well incorporated into clinic systems-hence, establishing a model that addresses the human resource challenges to building the capacity for sustainable depression treatment. The findings will also reveal the role of depression and its treatment in unleashing the public benefits of HIV treatment, and thus inform public policy on the importance of integrating depression treatment into HIV care programs.