California Collaborative Network to Promote Data Driven Care and Improve Outcomes in Early Psychosis (EPI-CAL)

项目摘要 长期的精神病首次发作（FEP）而没有充分的治疗是最一致的预测因素， 临床和功能结局差1，健康结局差2和经济负担重3。基于团队 为早期精神病患者提供的“协调不窋护理”4已确立成效， 功能恢复5。EP治疗计划随着美国各地资金的增加而迅速扩大 没有培训或实施的正式协调。虽然EP程序共享许多功能，但缺乏 州和国家协调和数据基础设施限制了大规模评价的能力，或 加速传播最佳做法基于之前与30家加州（CA）EP的合作 使用移动的健康（MOBI mHealth）技术衡量个人成果的计划和经验， EP护理，加州大学戴维斯分校（UCD）团队是唯一准备创建EPI-CAL，CA网络，将有助于 每年从6个社区和6所大学系统地收集1 000多名家庭暴力方案服务对象的结果数据 EP诊所，由NIMH EPINET计划支持的国家EP网络。基于我们之前的工作 评估CA EP计划，EPI-CAL计划将在第1年参与形成性评估，以确定 协调网络输入所需的核心EP临床特征、干预目标和结果。一个“核心 电池”的基础上收集的网站，PhenX工具包7目前的措施，并扩大到涵盖所有关键 域，将在第2年通过网络安装。核心客户成果和数据使用指标， 将使用客户、项目和医疗机构的自定义MOBI mHealth数据网络收集治疗决策， 在州一级，便于数据分析、解释和传播。培训和持续监测将 在所有EPI-CAL研究中心提供，以确保适当实施。EPI-CAL将有助于去识别 向国家协调中心提供数据。使用RE-AIM实施科学框架8，9，我们将 从5个方面系统地评估MOBI对EP计划的影响：覆盖范围、有效性、采用率， 实现和维护（参见图1）。为了展示网络的研究能力，在R34中， 作为本申请的组成部分，我们建议开发和验证未治疗持续时间的衡量标准。 精神病（DUP）是可行的，用于社区设置和心理测量的声音。虽然DUP是一个 短期CSC治疗反应5和FEP长期结局10的显著预测因子， 目前存在的措施已得到严格验证，并可供社区提供者使用7，11。 我们将利用利益相关者（客户、家庭成员、学术专家和CSC工作人员）的反馈， 具有标准化DUP定义的工具，包括对精神病发作和 治疗开发这样的工具将允许对CSC的这一关键主持人进行标准化评估 整个EPINET的结果。

Project Summary A prolonged first episode of psychosis (FEP) without adequate treatment is the most consistent predictor of poor clinical and functional outcomes 1, poor health outcomes 2 and significant economic burden 3. Team-based “coordinated specialty care” (CSC)4 for early psychosis (EP) has established effectiveness in promoting clinical and functional recovery 5 . EP treatment programs have expanded rapidly with increased funding across the US without formal coordination of training or implementation. While EP programs share many features, the lack of state and national coordination and data infrastructure limits the capacity for large-scale evaluation or accelerated dissemination of best practices 6. Based on prior collaborations with 30 California (CA) EP programs and experiences using mobile health (MOBI mHealth) technology to measure individual outcomes in EP care, the UC Davis (UCD) team is uniquely poised to create EPI-CAL, a CA network that will contribute systematically collected outcomes data on over 1000 FEP clients per year, from 6 community and 6 university EP clinics, to a national EP network supported by the NIMH EPINET program. Building on our prior work evaluating CA EP programs, EPI-CAL programs will participate in a formative evaluation in Year 1 to define core EP clinical features, intervention targets, and outcomes needed to harmonize network input. A “core battery” based on current measures collected at the sites, the PhenX toolkit 7 and expanded to cover all critical domains, will be installed across the network in Year 2. Core client outcomes and metrics of data use for treatment decisions will be collected using the custom MOBI mHealth data network at the client, program, and state level to allow easy data analysis, interpretation and dissemination. Training and ongoing monitoring will be provided at all EPI-CAL sites to ensure appropriate implementation. EPI-CAL will contribute de-identified data to the national coordinating hub. Using the RE-AIM implementation science framework 8,9, we will systematically evaluate the impact of MOBI on EP programs across 5 dimensions: reach, efficacy, adoption, implementation, and maintenance (see Figure 1). To demonstrate the network’s research capacity, in the R34 component of this application, we propose to develop and validate a measure of the Duration of Untreated Psychosis (DUP) that is feasible for use in community settings and psychometrically sound. Although DUP is a significant predictor of both short-term CSC treatment response5 and long-term outcomes 10 for FEP, no measure currently exists that has been rigorously validated and is feasible for use by community providers 7,11. We will utilize stakeholder feedback (clients, family members, academic experts and CSC staff) to develop a tool with standardized DUP definitions that includes anchored assessment of psychosis onset and start of treatment. Developing such a tool will allow standardized assessment of this critical moderator of CSC outcomes across the entire EPINET.