Homecare Agency-Randomized Trial of Web Implementation Strategy for Depression

描述（由申请人提供）：本申请响应PAR 10-038“健康传播和实施研究”，这是一项重点关注循证干预措施的产生与其在“真实的世界”中的使用之间的“差距”的倡议。在家庭保健等组织中，这一问题更加严重，因为大多数机构规模小，权力分散，地理位置分散。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）所独有的，因为国家的医疗保健是由资源匮乏的公共和非营利机构提供的。本研究测试了基于网络的实施策略（MHTraining-Net）对抑郁症CAREPATH的有效性，这是一种基于协作抑郁症护理模型的HH干预措施。CAREPATH将模型的抑郁症护理管理功能集成到HH护士的常规实践中，包括：a.监测抑郁症的严重程度; B.有关药物和/或心理治疗的咨询; c.药物管理; d.教育; E。围绕自我护理、愉悦活动和社会接触设定患者目标。MHTraining-Net采用电子学习模块、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.基础设施建设，2。训练，3。监督/绩效反馈，以及4。社会学习。MHTraining-Net对实施CAREPATH的影响将与强化支助条件进行比较。该研究采用机构随机设计，每组60个HH机构。所有HH机构都是CareAnyware，Inc的客户，CareAnyware，Inc是一家提供基于网络的临床管理软件的公司。CAREPATH协议已经编入该软件，所有机构都可以使用。该研究将分析从估计7，800名患有临床显著抑郁症（PHQ-9>15）的老年患者中常规收集的数据。目的是测试MHTraining-Net的有效性：1。改变做法：增加护士遵守CAREPATH协议; 2。改变患者的结局：降低抑郁症的严重程度。试点数据表明，MHTraining-Net是可行的，可接受的HH机构，并积极影响患者护理和临床结果。抑郁症影响超过25%的老年HH患者，大多未被发现或治疗不当，并导致更差的健康结果和更高的医疗费用。该研究利用技术进步设计了一种实施策略，可以达到分散的，地理上分散的机构，以及一种研究策略，将机构随机试验的力量与大型，多样化患者人群的普遍性结合起来。鉴于其广泛的覆盖范围，MHTraining-Net有可能显着改善老年HH患者的抑郁症护理，并减少这一人群的抑郁症公共卫生负担。

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.