Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report.
Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report.
复制标题
DOI：
10.1093/jamia/ocab117
复制
发表时间：
2021-09-18
期刊：
影响因子：
--
通讯作者：
Drozda JP
中科院分区：
文献类型：
--
作者：
Jiang G;Dhruva SS;Chen J;Schulz WL;Doshi AA;Noseworthy PA;Zhang S;Yu Y;Patrick Young H;Brandt E;Ervin KR;Shah ND;Ross JS;Coplan P;Drozda JP
本研究旨在对国家卫生技术协调中心评估系统心脏消融导管测试用例进行信息学分析，并证明信息学方法在使用唯一器械标识符（UDI）采集真实世界数据的可行性评估中的作用。适用于电子健康记录和其他健康信息技术中2种心脏消融导管的标签扩展多中心评价系统。我们重点研究了国家卫生技术协调中心数据质量评估体系框架中的数据采集和转换以及数据质量成熟度模型。信息学分析包括4个要素：使用UDI识别器械暴露数据，使用标准化代码定义可计算表型，使用自然语言处理从临床数据系统中捕获非结构化数据元素，以及使用通用数据模型标准化数据收集和分析。我们发现，通过在3个卫生系统实施UDI，可以有效识别目标器械暴露数据，特别是针对特定品牌的器械。研究结果的可计算表型可以使用代码定义;但是，需要消融登记处、自然语言处理工具和图表审查来验证表型的数据质量。各地点的共同数据模型实施情况各不相同。关键信息技术的成熟度与数据质量成熟度模型高度一致。我们证明，信息学方法可用于获取真实数据中的安全性和有效性结局，以用于支持标签扩展的医疗器械研究。
The study sought to conduct an informatics analysis on the National Evaluation System for Health Technology Coordinating Center test case of cardiac ablation catheters and to demonstrate the role of informatics approaches in the feasibility assessment of capturing real-world data using unique device identifiers (UDIs) that are fit for purpose for label extensions for 2 cardiac ablation catheters from the electronic health records and other health information technology systems in a multicenter evaluation. We focused on data capture and transformation and data quality maturity model specified in the National Evaluation System for Health Technology Coordinating Center data quality framework. The informatics analysis included 4 elements: the use of UDIs for identifying device exposure data, the use of standardized codes for defining computable phenotypes, the use of natural language processing for capturing unstructured data elements from clinical data systems, and the use of common data models for standardizing data collection and analyses. We found that, with the UDI implementation at 3 health systems, the target device exposure data could be effectively identified, particularly for brand-specific devices. Computable phenotypes for study outcomes could be defined using codes; however, ablation registries, natural language processing tools, and chart reviews were required for validating data quality of the phenotypes. The common data model implementation status varied across sites. The maturity level of the key informatics technologies was highly aligned with the data quality maturity model. We demonstrated that the informatics approaches can be feasibly used to capture safety and effectiveness outcomes in real-world data for use in medical device studies supporting label extensions.
登录
查看更多内容
影响因子：
24
作者：
Guimaraes, Patricia O.;Krishnamoorthy, Arun;Wang, Tracy Y.
通讯作者：
Wang, Tracy Y.
影响因子：
4.8
作者：
Tcheng, James E.;Crowley, Jay;Drozda, Joseph P., Jr.
通讯作者：
Drozda, Joseph P., Jr.
影响因子：
7.4
作者：
McPadden, Jacob;Durant, Thomas J. S.;Schulz, Wade L.
通讯作者：
Schulz, Wade L.
影响因子：
2.2
作者：
Zerhouni, Yasmin A.;Krupka, Dan C.;Weissman, Joel S.
通讯作者：
Weissman, Joel S.
DOI：
10.1136/bmjsit-2019-000024
发表时间：
2020
期刊：
BMJ surgery, interventions, & health technologies
影响因子：
--
作者：
Drozda J;Zeringue A;Dummitt B;Yount B;Resnic F
通讯作者：
Resnic F