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、未识别的外科病理报告的网络存储库。CaTIES系统从大量的临床自由文本语料库中创建一个未识别的、结构化的和概念编码的临床报告的存储库。文档根据受控术语自动编码，如统一医学语言系统(UMLS)、SNOMED-CT或NCI Metathesaurus。用户基于相关联的临床报告构建查询以识别特定类型的文档和组织样本。例如，研究转移性乳腺癌的遗传变异的研究人员可以识别出乳腺浸润性导管癌的病例，然后是距离最初诊断三年或更长时间的骨转移导管癌。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，机构之间可以共享未识别的数据和对组织的访问，从而实现多中心协作研究。CATIES系统已经在美国七个癌症中心实施，并正在考虑被包括癌症中心、大学医院和私人医院在内的许多其他机构采用。CATIES的最初开发是由癌症生物医学信息网格(CaBIG)资助的。然而，人们对应用程序的兴趣远远超出了我们的预期和caBIG的局限性。这笔赠款将使我们能够通过以下方式进一步扩大系统的能力：(A)提高系统的便携性，扩大可处理的文件类型；(B)评价系统的自然资源规划性能和可用性；(C)建立一个支持这一开放源码应用程序的用户社区；(D)试行CATIES与其他企业和研究系统的互操作性。这项工作将保留和扩展一个非常新颖的平台，用于开发可用于机构内部和跨机构研究的大规模未识别临床数据存储库。公共卫生相关性：这笔赠款将资助进一步开发和评估一个系统，该系统采用已识别的临床文件，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。这个项目很重要，因为它将极大地增加研究人员对重要数据和材料的访问，同时保护患者隐私。

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.