Continued Development and Evaluation of caTIES

摘要 我们建议进一步开发、测试、评估和支持CATIES-一个现有的用于开发的软件系统 可共享的去识别外科病理报告的网络存储库。CaTIES系统创建一个 来自大型临床语料库的未识别、结构化和概念编码的临床报告的存储库 自由文本。文档是根据受控术语自动编码的，例如统一医疗 语言系统(UMLS)、SNOMED-CT或NCI元词库。用户构建查询以识别特定的 基于相关临床报告的各种文件和组织标本。例如，一名研究人员 研究转移性乳腺癌的基因变异可以确定浸润性导管癌的病例。 乳腺癌，然后是骨转移的导管癌，相隔三年或更长时间 诊断。CATIES系统还支持纸巾的采购和订购，采用诚实的经纪人模式。 通过这一机制，可以在各机构之间共享未经确认的数据和对组织的访问，从而使 多中心协同研究。CATIES系统已经在7个美国癌症医院实施 中心，并正在考虑被包括癌症中心在内的许多其他机构采用， 大学医院和私立医院。CATIES的最初开发是由癌症生物医学资助的 信息学网格(CaBIG)。然而，人们对这项应用的兴趣远远超出了我们的预期， CaBIG的局限性。这笔拨款将使我们能够通过：(A)改善 系统的可移植性和扩展可处理的文件类型，(B)评价 系统的NLP性能和可用性，(C)建立一个用户社区来支持这个开源应用程序， 以及(D)试行CATIES与其他企业和研究系统的互操作性。这项工作将保存 并扩展了一个高度新颖的平台，用于开发大量未识别的临床数据存储库， 可用于机构内部和跨机构的研究。叙述性 这笔赠款将用于进一步开发和评估一个记录已确定临床文件的系统。 并将其转换为未识别的、概念编码的结构化数据。该系统使研究人员能够 访问剩余的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 项目很重要，因为它将极大地增加研究人员对重要数据和材料的访问 同时保护病人的隐私。

Abstract 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. Narrative 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.