Continued Development and Evaluation of caTIES

caTIES 的持续开发和评估

基本信息

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
项目类别：
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

项目摘要

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——一个现有的软件系统，用于开发可共享的去识别化手术病理报告的网络存储库。 caTIES 系统创建了一个源自大型临床自由文本语料库的去识别化、结构化和概念编码的临床报告存储库。文档根据统一医学语言系统 (UMLS)、SNOMED-CT 或 NCI Metathesaurus 等受控术语自动编码。用户构建查询以根据相关的临床报告识别特定类型的文档和组织样本。例如，研究转移性乳腺癌遗传变异的研究人员可以识别出乳腺浸润性导管癌病例，然后从最初诊断的时间间隔三年或更长时间识别出骨转移性导管癌病例。 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，从而实现多中心协作研究。 caTIES 系统已在七个美国癌症中心实施，并且正在考虑被包括癌症中心、大学医院和私立医院在内的许多其他机构采用。 CATIES 的最初开发由癌症生物医学信息网格 (caBIG) 资助。然而，对该应用程序的兴趣远远超出了我们的预期和caBIG 的限制。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) 提高系统的可移植性并扩展可处理的文档类型，(b) 评估系统的 NLP 性能和可用性，(c) 构建用户社区支持这一开源应用程序，(d) 试点 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，用于开发可用于机构内部和跨机构研究的去识别化临床数据的大规模存储库。公共卫生相关性：这笔赠款将资助一个系统的进一步开发和评估，该系统获取已识别的临床文档并将其转换为去识别化、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，以用于机构内部和跨机构的研究目的。该项目很重要，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。