Continued Development and Evaluation of caTIES

描述（由申请人提供）：我们建议进一步开发、测试、评估和支持caTIES——一个现有的软件系统，用于开发可共享的去识别外科病理报告的网络存储库。caTIES系统从临床自由文本的大型语料库中创建了一个去标识化、结构化和概念编码的临床报告存储库。文档是根据统一医学语言系统（Unified Medical Language System， UMLS）、SNOMED-CT或NCI元词典等受控术语自动编码的。用户根据相关的临床报告构建查询来识别特定类型的文档和组织标本。例如，研究转移性乳腺癌遗传变异的研究人员可以识别乳腺浸润性导管癌病例，随后是骨转移性导管癌，时间间隔为3年或更久。caTIES系统还使用诚实的代理模型支持组织的获取和订购。通过这种机制，去识别数据和对组织的访问可以在机构之间共享，从而实现多中心合作研究。caTIES系统已经在七家美国癌症中心实施，并正在考虑被许多其他机构采用，包括癌症中心、大学医院和私立医院。caTIES的最初开发是由癌症生物医学信息网格（caBIG）资助的。然而，对该应用程序的兴趣远远超出了我们的预期和caBIG的限制。这笔拨款将允许我们进一步扩展系统的能力，通过(a)提高系统的可移植性和扩展可处理的文件类型，(b)评估系统的NLP性能和可用性，(c)建立用户社区来支持这个开源应用程序，以及(d)试点caTIES与其他企业和研究系统的互操作性。这项工作将保留和扩展一个高度新颖的平台，用于开发可用于机构内部和跨机构研究的大量去识别临床数据存储库。公共卫生相关性：这笔拨款将资助一个系统的进一步开发和评估，该系统将识别的临床文件转化为去识别、概念编码、结构化的数据。该系统使研究人员能够访问剩余组织和临床报告数据，用于机构内部和跨机构的研究目的。这个项目很重要，因为它将大大增加研究人员对重要数据和材料的访问，同时保持患者的隐私。

DESCRIPTION (provided by applicant): We propose to further develop, test, evaluate and support caTIES - an existing software system for developing networked repositories of sharable de-identified surgical pathology reports. The caTIES system creates a repository of de-identified, structured, and concept-coded clinical reports derived from large corpora of clinical free-text. Documents are automatically coded against a controlled terminology such as the Unified Medical Language System (UMLS), SNOMED-CT, or NCI Metathesaurus. Users construct queries to identify specific kinds of documents and tissue specimens based on the associated clinical report. For example, a researcher studying genetic variation in metastatic breast cancers can identify cases of invasive ductal carcinoma of the breast, followed by metastatic ductal cancer in bone at an interval of three years or greater from the original diagnosis. The caTIES system also supports acquisition and ordering of tissues, using an honest broker model. Through this mechanism, de-identified data and access to tissue can be shared among institutions, enabling multi-center collaborative research. The caTIES system has already been implemented at seven US Cancer Centers, and is being considered for adoption by numerous other institutions including cancer centers, university hospitals and private hospitals. Initial development of caTIES was funded by the Cancer Biomedical Informatics Grid (caBIG). However, interest in the application has far exceeded our expectations and the limitations of caBIG. This grant will allow us to further extend the capabilities of the system by (a) improving the portability of the system and extending the types of documents that can be processed, (b) evaluating the system's NLP performance and usability, (c) building a user community to support this open-source application, and (d) piloting interoperability of caTIES with other enterprise and research systems. This work will preserve and extend a highly novel platform for development of massive repositories of de-identified clinical data that can be used for research within and across institutions. PUBLIC HEALTH RELEVANCE: This grant will fund the further development and evaluation of a system that takes identified clinical documents and converts them into de-identified, concept-coded, structured data. The system enables researchers to access remainder tissues and clinical report data for research purposes within and across institution. This project is important because it will greatly increase the access of researchers to important data and materials while maintaining patient privacy.