Integration Difusion for SMI Service Delivery

描述（由申请人提供）：该资助旨在描述和评估通过多部门服务网络为严重精神III型成年人提供整合传播的过程。尽管在过去的二十年里，要求一体化的呼声一直很普遍，但随着新自由委员会发表的报告《实现承诺》，对一体化的兴趣重新燃起。尽管过去在解决服务提供网络中的整合水平方面做出了实证努力，但在了解整合在网络中传播的过程以及我们如何期望心理健康以外的服务部门的机构对心理健康服务和客户作出反应并与之互动方面，完成的工作很少。这方面的知识将有助于决策者和行政人员更有效地执行一体化战略，并对其网络内各机构之间的合作产生切合实际的期望。该项目使用了CMHS“获得社区护理和有效服务支持（Access）”项目的辅助数据，该项目提供资金，在9个站点（另外9个比较站点）为无家可归的严重精神疾病成年人提供综合服务。我们将利用来自这些分析的一些社会网络数据以及其他组织变量来确定整合在这九个网络中传播的模式，并评估组织变量的任何特定组合是否有助于阻碍或帮助网络中整合实践的吸收。分析将使用重复测量回归技术完成。

DESCRIPTION (provided by applicant): This grant seeks to describe and assess the process by which integration spreads through a multi sector service delivery network for Seriously Mentally III adults. Although calls for integration have been widespread over the past twenty years, a renewed interest in integration has emerged with the New Freedom Commission's published report, "Achieving the Promise". Despite past empirical efforts to address the integration levels in service delivery networks, little work has been completed to understand the process by which integration spreads in a network and how we might expect agencies from service sectors other than mental health to react to and interact with the mental health services and clients. This knowledge will aid policy makers and administrators to more effectively implement integration strategies and to create realistic expectations about the cooperation among agencies within their networks. This project uses secondary data from the CMHS' Access to Community Care and Effective Service Supports (ACCESS) program that provided funds to integrate services in nine sites (with an additional nine comparison sites) for homeless seriously mentally ill adults. We will utilize some social network data from these analyses along with additional organizational variables to determine the pattern through which integration spread within these nine networks, as well as to evaluate whether any specific combinations of organizational variables serve to impede or aid the uptake of integration practices within the networks. Analysis will be completed using repeated measures regression techniques.