Homecare Agency-Randomized Trial of Web Implementation Strategy for Depression

描述(由申请人提供)：本申请是对PAR 10-038“卫生领域的传播和实施研究”的回应，该倡议侧重于循证干预措施的产生与其在“现实世界”中的使用之间的“差距”。这个问题在像家庭健康这样的组织中加剧，因为大多数机构都很小，分散和地理上分散。很少有人能负担得起先进的质量改进。这种情况并不是家庭健康(HH)独有的，因为全国的医疗保健都是由资源匮乏的公共和非营利机构提供的。这项研究测试了基于网络的实施策略(MHTraining-Net)在抑郁症CAREPATH上的有效性，CAREPATH是一种基于协作性抑郁症护理模式的HH干预。CAREPATH将该模式的抑郁症护理管理功能整合到HH护士的日常实践中，包括：a.监测抑郁症的严重程度；b.关于药物和/或心理治疗治疗的咨询；c.药物管理；d.教育；以及e.围绕自我护理、愉快活动和社会接触设定患者目标。MHTraining-Net使用电子学习模块、网络研讨会、电子邮件/电话咨询和社交网络技术来提供四项实施活动：1.基础设施开发，2.培训，3.监督/绩效反馈，以及4.社交学习。MHTraining-Net在实施CAREPATH方面的效果将与增强的支持条件进行比较。这项研究使用了机构随机设计，每个手臂有60个HH机构。所有HH机构都是CareAnyware公司的客户，CareAnyware公司是一家提供基于网络的临床管理软件的公司。CAREPATH协议已经被编程到该软件中，所有机构都可以访问。这项研究将分析常规收集的数据，这些数据来自大约7800名患有临床显著抑郁症的老年患者(PHQ-9和GT；15)。其目的是测试MHTraining-Net在以下方面的有效性：1.改变做法：提高护士对CAREPATH方案的依从性；2.改变患者的结局：降低抑郁的严重程度。试点数据表明，MHTraining-Net是可行的，HH机构可以接受，并对患者护理和临床结果产生积极影响。抑郁症影响了超过25%的老年HH患者，大多未被发现或治疗不当，并导致更糟糕的健康结果和更高的医疗费用。这项研究利用技术进步的优势，设计了一种可以覆盖分散的、地理上分散的机构的实施战略，以及一种将机构随机试验的力量与大规模、多样化患者群体的普适性相结合的研究战略。鉴于其广泛的影响范围，MHTraining-Net有可能显著改善老年HH患者的抑郁症护理，并减少这一人群中抑郁症的公共健康负担。

DESCRIPTION (provided by applicant): This application responds to PAR 10-038 "Dissemination and Implementation Research in Health", an initiative focused on the "gap" between the production of evidence-based interventions and their use in the "real world". This problem is exacerbated in organizations like Home Health as most agencies are small, decentralized and geographically dispersed. Few can afford advanced quality improvement. This situation is not unique to Home Health (HH) as much the nation's health care is provided by resource-poor public and not-for-profit agencies. This study tests the effectiveness of a web-based implementation strategy (MHTraining-Net) on the Depression CAREPATH, a HH intervention based on the Collaborative Depression Care model. CAREPATH integrates the model's depression care management functions into routine practice of HH nurses, including: a. Monitoring depression severity; b. Consultation about medication and/or psychotherapy treatment; c. Medication management; d. Education; and e. Patient goal setting around self care, pleasurable activities and social contact. MHTraining-Net employs e-learning modules, webinars, email/phone consultation, and social networking technology to deliver four implementation activities: 1. Infrastructure development, 2. Training, 3. Supervision/performance feedback, and 4. Social learning. The effect of MHTraining-Net on implementing CAREPATH will be compared to an Enhanced Support condition. The study uses an agency-randomized design, with 60 HH agencies per arm. All HH agencies are clients of CareAnyware, Inc, a company that provides web-based clinical management software. The CAREPATH protocol is already programmed into this software and accessible to all agencies. The study will analyze routinely collected data from an estimated 7,800 older patients with clinically significant depression (PHQ-9>15). The aims are to test the effectiveness of MHTraining-Net on: 1. Changing Practice: increasing nurse adherence to the CAREPATH protocol; and 2. Changing Patients' Outcomes: reducing severity of depression. Pilot data suggest that MHTraining-Net is feasible, acceptable to HH agencies, and positively affects both patient care and clinical outcomes. Depression affects over 25% of older HH patients, is mostly undetected or poorly treated, and leads to worse health outcomes and higher healthcare costs. The study takes advantage of technological advances to design an implementation strategy that can reach decentralized, geographically dispersed agencies, and a research strategy that couples the power of an agency-randomized trial with the generalizability of a large, diverse patient population. Given its long reach, MHTraining-Net has the potential of significantly improving care for depression in older HH patients and reducing the public health burden of depression in this population.