Continued Development and Evaluation of caTIES

caTIES 的持续开发和评估

• 批准号: 8403841
• 负责人: Rebecca S Jacobson
• 金额: $ 28.66万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8403841
• 关键词: Access to Information; Adoption; Cancer Center; Clinical; Clinical Data; Clinical Trials; Code; Communication; Communities; Community Developments; Computer software; Data; Data Reporting; Database Management Systems; Development; Diagnosis; Documentation; Ductal; Electronic Mail; Eligibility Determination; Environment; Evaluation; Funding; Future; Genetic Variation; Genomics; Grant; Information Retrieval; Institution; Malignant Neoplasms; Methods; Metric; Modeling; Modification; Natural Language Processing; Operating System; Pathology Report; Performance; Private Hospitals; Process; Report (document); Reporting; Research; Research Personnel; Services; Specimen; Structure; Surgical Pathology; System; Systematized Nomenclature of Medicine; Terminology; Testing; Text; Tissues; Training; Translational Research; Unified Medical Language System; University Hospitals; Vocabulary; Work; abstracting; base; bone; cancer Biomedical Informatics Grid; clinical phenotype; computer human interaction; ductal breast carcinoma; expectation; flexibility; improved; interest; interoperability; malignant breast neoplasm; meetings; metathesaurus; novel; open source; patient privacy; portability; repository; software development; software systems; systems research; tool; usability

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.

抽象的 我们建议进一步开发、测试、评估和支持caTIES——一个用于开发的现有软件系统 可共享的未识别身份的手术病理报告的网络存储库。 caTIES 系统创建了一个 来自大型临床语料库的去识别化、结构化和概念编码的临床报告存储库 自由文本。文档根据受控术语（例如统一医疗）自动编码 语言系统 (UMLS)、SNOMED-CT 或 NCI Metathesaurus。用户构建查询来识别特定的 基于相关临床报告的各种文件和组织标本。例如，一位研究人员 研究转移性乳腺癌的遗传变异可以识别浸润性导管癌病例 乳腺癌，随后在距原发灶三年或更长时间的间隔内发生骨转移性导管癌 诊断。 CATIES 系统还支持使用诚实经纪人模型来获取和订购组织。 通过这种机制，去识别化数据和组织访问可以在机构之间共享，从而使 多中心合作研究。 caTIES 系统已在美国七个癌症中心实施 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 的最初开发由癌症生物医学基金会资助 信息学网格（caBIG）。然而，人们对该应用程序的兴趣远远超出了我们的预期， 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展系统的功能：(a) 改进 系统的可移植性和扩展可处理的文档类型，(b) 评估 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， (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 并扩展一个高度新颖的平台，用于开发去识别化临床数据的大规模存储库， 可用于机构内部和跨机构的研究。叙述 这笔赠款将资助进一步开发和评估一个采用已确定的临床文件的系统 并将它们转换成去识别化的、概念编码的、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以用于机构内部和跨机构的研究目的。这 项目很重要，因为它将大大增加研究人员获取重要数据和材料的机会 同时维护患者隐私。

项目成果

A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens.

• DOI: 10.1158/0008-5472.can-15-1973
• 发表时间: 2015-12-15
• 期刊: Cancer research
• 影响因子: 11.2
• 作者: Jacobson RS;Becich MJ;Bollag RJ;Chavan G;Corrigan J;Dhir R;Feldman MD;Gaudioso C;Legowski E;Maihle NJ;Mitchell K;Murphy M;Sakthivel M;Tseytlin E;Weaver J
• 通讯作者: Weaver J