Continued Development and Evaluation of caTIES

caTIES 的持续开发和评估

• 批准号: 7999244
• 负责人: Rebecca S Jacobson
• 金额: $ 30.49万
• 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/7999244
• 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; Health; 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; 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

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.

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 -一种现有的软件系统，用于开发可共享的去识别外科病理学报告的网络存储库。cATIES系统创建了一个从大型临床自由文本语料库中导出的去识别、结构化和概念编码的临床报告库。文档根据统一医学语言系统（UMLS）、SNOMED-CT或NCI元词库等受控术语自动编码。用户根据相关临床报告构建查询以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确定乳腺浸润性导管癌的病例，然后在最初诊断的三年或更长时间间隔内发现骨转移性导管癌。cATIES系统还支持组织的获取和订购，使用诚实的经纪人模型。通过这种机制，去识别数据和组织访问可以在机构之间共享，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，并正在考虑由许多其他机构，包括癌症中心，大学医院和私立医院采用。cATIES的最初开发是由癌症生物医学信息网格（caBIG）资助的。然而，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进一步扩展系统的功能，通过（a）提高系统的可移植性，并扩展可以处理的文档类型，（B）评估系统的NLP性能和可用性，（c）建立一个用户社区，以支持这一开源应用程序，以及（d）试验cATIES与其他企业和研究系统的互操作性。这项工作将保留和扩展一个非常新颖的平台，用于开发可用于机构内和跨机构研究的大量去识别临床数据库。公共卫生关系：这笔赠款将资助进一步开发和评估一个系统，该系统将识别临床文件并将其转换为去识别，概念编码，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。该项目非常重要，因为它将大大增加研究人员对重要数据和材料的访问，同时维护患者隐私。