caCDE-QA: A Quality Assurance Platform for Cancer Study Common Data Elements
caCDE-QA: A Quality Assurance Platform for Cancer Study Common Data Elements
批准号:
9110905
负责人:
Guoqian Jiang
金额:
$32.92万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-15 至 2018-01-31
关键词:
AddressAdoptedAlgorithmsClinicalClinical DataClinical ResearchCollaborationsCommon Data ElementCommunitiesCommunity ServicesDataData ElementData QualityData Storage and RetrievalDetectionDictionaryFaceFosteringGoalsHealthLife Cycle StagesMalignant NeoplasmsMetadataMethodsModelingNational Cancer InstituteNetwork-basedOnline SystemsOutcomePerformancePublishingResearchSemanticsServicesStandardizationStructureTechnologyTestingThe Cancer Genome AtlasUnified Medical Language SystemValidationbasecomputer based Semantic Analysiscostdata sharingdesigninformation modelnovelquality assurancerepositoryresearch studytoolusabilityweb portal
中文摘要
描述(由申请人提供):特定领域的公共数据元素(CDE)正在成为一种基于标准的临床研究数据存储和检索的有效方法,并已被广泛采用。例如,国家癌症研究所根据国际标准化组织/国际电工委员会11179元数据储存库标准创建了癌症数据标准储存库。然而,癌症临床研究社区面临着与CDE建模的可扩展性、管理和数据质量相关的重大挑战。特别是,缺乏可靠的、有原则的和自动化的QA算法会导致CDE内容错误,这可能会对下游CDE的使用产生重大负面影响。我们的总体目标是建立一个新的质量保证(QA)框架,以克服在公共数据元素(CDE)建模中的错误检测、重复或相似CDE的识别以及CDE可用性方面的方法学和计算挑战,从而为癌症临床研究产生高质量的CDE。我们提出的方法是设计、开发和评估一个称为caCDE-QA的综合平台,该平台实现了一套QA工具来审计以语义Web框架表示的实验性癌症研究CDE,部署了一个带有标准语义服务的QA Web门户网站,用于社区协作。我们的具体目标是:(1)开发一套用于验证和协调癌症研究CDE的QA工具。(2)应用QA工具对以语义网框架表示的实验性癌症研究CDE进行审计。我们还将通过与NCI caDSR和CIMI社区中存在的基准工具进行比较,评估QA工具在效率、准确性和可用性方面的性能。(3)部署和评估质量保证门户网站,以进行CDE协作审查和协调。我们将协调基于社区的努力,征求关于癌症研究、CDE发现和协调的要求,并促进公共数据元素服务(CDES)标准的规范。我们将与临床数据交换标准联盟(CDISC)和CIMI社区合作,传播和测试新开发的QA方法和工具。该项目将为癌症研究CDE的验证和语义协调贡献新的QA方法和工具。这具有重要意义,因为它将使高效的CDE建模和产生高质量的可重复使用的CDE,这对于促进癌症临床研究数据共享和加快系统的临床结果捕获至关重要。
英文摘要
DESCRIPTION (provided by applicant): Domain-specific common data elements (CDEs) are emerging as an effective approach to standards-based clinical research data storage and retrieval and have been broadly adopted. For example, the National Cancer Institute (NCI) created the Cancer Data Standards Repository (caDSR) based on the ISO/IEC 11179 standard for metadata repositories. However, cancer clinical research community faces significant challenges related to scalability, governance, and data quality for CDE modeling. In particular, the lack of robust, principled and automated QA algorithms contributes to CDE content errors that can have a significant negative impact on downstream CDE uses. Our overall goal is to build a novel quality assurance (QA) framework to overcome methodological and computational challenges with respect to error detection in the modeling of common data elements (CDEs), recognition of duplicates or similar CDEs, and CDE usability, thereby producing high-quality CDEs for cancer clinical research studies. Our proposed approach is to design, develop and evaluate an integrative platform known as caCDE-QA that implements a suite of QA tools to audit experimental cancer study CDEs represented in a semantic web framework, deploying a QA web-portal with standard semantic services for community collaboration. Our specific aims are: (1) To develop a suite of QA tools for validation and harmonization of cancer study CDEs. (2) To apply the QA tools to audit experimental cancer study CDEs represented in a semantic web framework. We will also evaluate the performance of the QA tools in terms of efficiency, accuracy and usability by comparing with the baseline tools that exist in the NCI caDSR and CIMI communities. (3) To deploy and evaluate a QA web-portal for collaborative CDE review and harmonization. We will coordinate community-based efforts soliciting requirements regarding cancer study CDE discovery and harmonization and fostering a specification of the common data element services (CDES) standard. We will disseminate and test the newly developed QA methods and tools in collaboration with the Clinical Data Interchange Standards Consortium (CDISC) and CIMI Communities. This project will contribute novel QA methods and tools for validation and semantic harmonization of cancer study CDEs. This is of great significance in that it will be enabling efficient CDE modeling and producing high-quality reusable CDEs, which are critical for facilitating cancer clinical research data sharing and accelerating systematic clinical outcomes capturing.
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DOI:
--
发表时间:
2018
期刊:
AMIA ... Annual Symposium proceedings. AMIA Symposium
影响因子:
--
作者:
[H. Solbrig;Na Hong;S. Murphy;Guoqian Jiang]
通讯作者:
H. Solbrig;Na Hong;S. Murphy;Guoqian Jiang
Developing a Standards-Based Information Model for Representing Computable Diagnostic Criteria: A Feasibility Study of the NQF Quality Data Model.
开发基于标准的信息模型来表示可计算的诊断标准:NQF 质量数据模型的可行性研究。
DOI:
--
发表时间:
2015
期刊:
Studies in health technology and informatics
影响因子:
--
作者:
[Jiang,Guoqian, Solbrig,HaroldR, Pathak,Jyotishman, Chute,ChristopherG]
通讯作者:
Chute,ChristopherG
A Semantic Web-based System for Mining Genetic Mutations in Cancer Clinical Trials.
用于挖掘癌症临床试验中基因突变的基于语义网络的系统。
DOI:
--
发表时间:
2015
期刊:
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
影响因子:
--
作者:
[Priya,Sambhawa, Jiang,Guoqian, Dasari,Surendra, Zimmermann,MichaelT, Wang,Chen, Heflin,Jeff, Chute,ChristopherG]
通讯作者:
Chute,ChristopherG
Using an artificial neural network to map cancer common data elements to the biomedical research integrated domain group model in a semi-automated manner.
使用人工神经网络以半自动方式将癌症常见数据元素映射到生物医学研究集成域组模型。
DOI:
10.1186/s12911-019-0979-5
发表时间:
2019
期刊:
BMC medical informatics and decision making
影响因子:
3.5
作者:
[Renner,Robinette, Li,Shengyu, Huang,Yulong, vanderZijp-Tan,AdaChaeli, Tan,Shaobo, Li,Dongqi, Kasukurthi,MohanVamsi, Benton,Ryan, Borchert,GlenM, Huang,Jingshan, Jiang,Guoqian]
通讯作者:
Jiang,Guoqian
Modeling and validating HL7 FHIR profiles using semantic web Shape Expressions (ShEx).
使用语义网络形状表达式 (ShEx) 建模和验证 HL7 FHIR 配置文件。
DOI:
10.1016/j.jbi.2017.02.009
发表时间:
2017-03
期刊:
Journal of biomedical informatics
影响因子:
4.5
作者:
[Solbrig HR, Prud'hommeaux E, Grieve G, McKenzie L, Mandel JC, Sharma DK, Jiang G]
通讯作者:
Jiang G
共 11 条
FHIRCat: Enabling the Semantics of FHIR and Terminologies for Clinical and Translational Research
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批准号:10401244
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项目类别:
-
资助金额:$67.82万
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财政年份:2021
-
负责人:Guoqian Jiang
-
依托单位:
FHIRCat: Enabling the Semantics of FHIR and Terminologies for Clinical and Translational Research
-
批准号:10091916
-
项目类别:
-
资助金额:$69.3万
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财政年份:2021
-
负责人:Guoqian Jiang
-
依托单位:
FHIRCat: Enabling the Semantics of FHIR and Terminologies for Clinical and Translational Research
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批准号:10005525
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项目类别:
-
资助金额:$60.1万
-
财政年份:2019
-
负责人:Guoqian Jiang
-
依托单位:
Tools for standardizing clinical research metadata using HL7 FHIR
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批准号:9353446
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项目类别:
-
资助金额:$47.7万
-
财政年份:2016
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负责人:Guoqian Jiang
-
依托单位:
caCDE-QA: A Quality Assurance Platform for Cancer Study Common Data Elements
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批准号:8765818
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项目类别:
-
资助金额:$35.51万
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财政年份:2014
-
负责人:Guoqian Jiang
-
依托单位:
caCDE-QA: A Quality Assurance Platform for Cancer Study Common Data Elements
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批准号:8913908
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项目类别:
-
资助金额:$41.24万
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财政年份:2014
-
负责人:Guoqian Jiang
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依托单位:
海外基金