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.

摘要 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学报告的联网储存库。CATIES系统创建了一个 从大型临床数据库中导出的去识别、结构化和概念编码的临床报告库 自由文本。文档根据受控术语自动编码，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 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乳腺癌的浸润性导管癌病例。 乳腺癌，其次是骨转移性导管癌，从最初的三年或更长的时间间隔 诊断. cATIES系统还支持组织的获取和订购，使用诚实的经纪人模型。 通过这一机制，去识别数据和组织访问可以在机构之间共享， 多中心合作研究。CATIES系统已经在七个美国癌症中心实施， 中心，并正在考虑通过许多其他机构，包括癌症中心， 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，对应用程序的兴趣远远超出了我们的预期， CABIG的局限性这笔拨款可让我们进一步扩展系统的功能，包括：（a）改善 （B）评估所述系统的可移植性并扩展可以被处理的文档的类型， 系统的NLP性能和可用性，（c）构建用户社区来支持此开源应用程序， 以及（d）试验caTIES与其他企业和研究系统的互操作性。这项工作将保持 并扩展了一个高度新颖的平台，用于开发大量去识别临床数据的存储库， 可用于机构内和机构间的研究。叙事 这笔赠款将资助进一步开发和评估一个系统， 并将其转换为去识别的、概念编码的结构化数据。该系统使研究人员能够 访问剩余组织和临床报告数据，用于机构内和机构间的研究目的。这 这个项目很重要，因为它将大大增加研究人员获得重要数据和材料的机会 同时保持患者隐私。

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