Advanced Development and Dissemination of EMERSE for Cancer Phenotyping from Medical Records

项目总结 全国癌症中心越来越多地使用电子健康记录(EHR)，导致 包含非结构化、自由文本备注的存储库急剧增长。这些笔记包括临床 在EHR的其他地方找不到的概念，而这些概念是描述 患者特定的“表型”。拥有如此多的电子格式数据，提供了前所未有的 推进临床和转化性癌症研究的机会，但许多研究人员没有 获取实用工具，以帮助识别和提取这些笔记中的概念。要解决这个问题 问题，密歇根大学综合癌症中心信息学核心开发的信息 检索工具Emerse-电子病历搜索引擎-已经实现了广泛的本地化 成功地支持了数百项癌症研究，并导致了120多份同行评议的出版物。 Emerse提供支持研究的创新功能，包括可视化结果、可重复使用的患者 列表，以及促进更多可重现搜索的可共享搜索项集(“捆绑包”)。这个项目 建议在Emerse内部发展创新能力，并广泛发展基础设施 将Emerse传播到全国的癌症中心。该提案中的软件创新包括(1) 安全地连接Emerse实例以实现跨癌症中心的搜索，这对 罕见的癌症，并与日益增长的国家数据共享倡议保持一致；(2)利用联网的 出现以存储的搜索项束的形式在机构之间共享搜索知识的实例， 促进跨站点和研究范围内搜索的重现性；(3)支持搜索 完全识别的或未识别的临床记录，取决于用户的凭证和预期用途， 它是跨机构搜索所需的；(4)支持包含本地化的自定义词典或 用于查询扩展的本体。技术和协作基础设施以支持 将广泛传播Emerse，包括形成Emerse Research 信息学网络(ERIN)。五个癌症中心，每个中心都有不同的健康信息技术 环境，将加入Erin这个项目并在本地实现Emerse，使其可用于他们的 研究人员。实施将是交错的，因此从一个站点实施中学到的经验教训可以 用于改进文档并应用于未来的站点。实施细节将包括如何 解决监管、机构审查委员会、安全和合规问题。来自中国的集体知识 这些最初的实施者将被整合到路线图指南中，以帮助未来的癌症中心和其他 各机构轻松实施Emerse。Emerse将通过各种方式被提升到其他癌症中心 机械装置。这项工作的影响和效果将从多个方面进行评估，包括 信息检索指标、可用性、实施、采用、满意度和效用。

PROJECT SUMMARY The increasing use of electronic health records (EHRs) by cancer centers nationwide has led to the tremendous growth of repositories containing unstructured, free text notes. These notes include clinical concepts that cannot be found anywhere else in the EHR, and these concepts are needed to characterize a patient’s specific ‘phenotype’. Having so much data available in electronic format provides unprecedented opportunities for advancing clinical and translational cancer research, yet many researchers do not have access to practical tools to assist with identifying and extracting the concepts from these notes. To address this problem, the University of Michigan Comprehensive Cancer Center Informatics Core developed the information retrieval tool EMERSE—electronic medical record search engine—which has achieved widespread local success in supporting hundreds of cancer studies and has led to over 120 peer-reviewed publications. EMERSE provides innovative features that enable research including visualization of results, reusable patient lists, and shareable sets of search terms (“Bundles”) that promote more reproducible searches. This project proposes to develop innovative capabilities within EMERSE and develop the infrastructure to widely disseminate EMERSE to cancer centers nationwide. The software innovations in this proposal include (1) securely networking the EMERSE instances to enable searches across cancer centers, which is important for rare cancers and is in alignment with growing national data sharing initiatives; (2) leveraging the networked EMERSE instances to share search knowledge between institutions in the form of stored search term Bundles, promoting the reproducibility of searches across sites as well as within studies; (3) supporting search with either fully identified or de-identified clinical notes, depending on the users’ credentials and intended use, which is needed for cross-institutional searching; (4) supporting the inclusion of localized custom dictionaries or ontologies to be used for query expansion. The technical and collaborative infrastructure to support the widespread dissemination of EMERSE will be developed, including formation of the EMERSE Research Informatics Network (ERIN). Five cancer centers, each with varying health information technology environments, will join ERIN for this project and locally implement EMERSE, making it available to their researchers. Implementations will be staggered so that lessons learned from implementing at one site can be used to improve the documentation and be applied to future sites. Implementation details will include how to address regulatory, institutional review board, security, and compliance issues. The collective knowledge from these initial implementers will be integrated into a ‘roadmap’ guide to help future cancer centers and other institutions implement EMERSE with ease. EMERSE will be promoted to other cancer centers through various mechanisms. The impact and effectiveness of this work will be evaluated across multiple dimensions including information retrieval metrics, usability, implementation, adoption, satisfaction, and utility.