Vohs Jenifer L, Srihari Vinod, Vinson Alexandra H, Lapidos Adrienne, Cahill John, Taylor Stephan F, Heckers Stephan, Weiss Ashley, Chaudhry Serena, Silverstein Steve, Tso Ivy F, Breitborde Nicholas J K, Breier Alan
Department of Psychiatry, Prevention and Recovery Center for Early Psychosis (PARC), Sandra Eskenazi Mental Health Centers Indiana University School of Medicine Indianapolis Indiana USA.
Department of Psychiatry, Specialized Treatment Early in Psychosis (STEP) Yale School of Medicine New Haven Connecticut USA.
Learn Health Syst. 2024 Nov 17;9(2):e10471. doi: 10.1002/lrh2.10471. eCollection 2025 Apr.
Compared to usual care, specialty services for first-episode psychosis (FES) have superior patient outcomes. The Early Psychosis Intervention Network (EPINET), comprised of eight U.S. regional clinical networks, aims to advance the quality of FES care within the ethos of learning healthcare systems (LHS). Among these, the Academic Community (AC) EPINET was established to provide FES care, collect common data elements, leverage informatics, foster a culture of continuous learning and quality improvement, and engage in practice-based research.
We designed and implemented a novel LHS of university-affiliated FES programs within a hub (academic leadership team) and spoke (FES clinics) model. A series of site implementation meetings engaged stakeholders, setting the stage for a culture that values data collection and shared learning. We built clinical workflows to collect common data elements at enrollment and at consecutive 6-month intervals in parallel to an informatics workflow to deliver outcome visualizations and drive quality improvement efforts.
All six clinical sites successfully implemented data capture workflows and engaged in the process of designing the informatics platform. Upon developing the structure, processes, and initial culture of the LHS, a total of 614 patients enrolled in AC-EPINET, with the most common primary diagnoses of schizophrenia (32.1%) and unspecified psychotic disorders (23.6%). Visualized outcomes were delivered to clinical teams who began to consider locally relevant quality improvement projects.
AC-EPINET is a novel LHS, with a simultaneous focus on science, informatics, incentives, and culture. The work of developing AC-EPINET thus far has highlighted the need for future LHS' to be mindful of the complexities of data security issues, develop more automated informatic workflows, resource quality assurance efforts, and attend to building the cultural infrastructure with the input of all stakeholders.
与常规护理相比,首发精神病(FES)的专科服务具有更好的患者治疗效果。由美国八个地区临床网络组成的早期精神病干预网络(EPINET)旨在在学习型医疗系统(LHS)的理念下提高FES护理质量。其中,学术社区(AC)EPINET的设立是为了提供FES护理、收集通用数据元素、利用信息学、培养持续学习和质量改进的文化,并开展基于实践的研究。
我们在一个中心(学术领导团队)和多个分支(FES诊所)模式下设计并实施了一种新型的大学附属FES项目LHS。一系列现场实施会议让利益相关者参与其中,为重视数据收集和共享学习的文化奠定了基础。我们构建了临床工作流程,以便在患者入组时以及随后每6个月连续收集通用数据元素,同时构建了一个信息学工作流程,以提供结果可视化并推动质量改进工作。
所有六个临床站点都成功实施了数据捕获工作流程,并参与了信息学平台的设计过程。在建立了LHS的结构、流程和初始文化后,共有614名患者加入了AC-EPINET,最常见的主要诊断是精神分裂症(32.1%)和未特定的精神障碍(23.6%)。可视化结果已提供给临床团队,这些团队开始考虑与当地相关的质量改进项目。
AC-EPINET是一种新型的LHS,同时关注科学、信息学、激励措施和文化。到目前为止,开发AC-EPINET的工作凸显了未来LHS需要注意数据安全问题的复杂性、开发更自动化的信息学工作流程、投入资源进行质量保证工作,并在所有利益相关者的参与下致力于构建文化基础设施。