Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD).
Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD).
复制标题
用于医疗设备真实世界证据的多机构分布式数据网络:将唯一设备标识符构建为纵向数据(BUILD)。
DOI:
10.1093/jamiaopen/ooac035
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发表时间:
2022-07
期刊:
影响因子:
2.1
通讯作者:
Simard, Edgar P.
中科院分区:
文献类型:
--
作者:
Drozda, Joseph P., Jr.;Graham, Jove;Muhlestein, Joseph B.;Tcheng, James E.;Roach, James;Forsyth, Tom;Knight, Stacey;McKinnon, Andrew;May, Heidi;Wilson, Natalia A.;Berlin, Jesse A.;Simard, Edgar P.
关键词:
To support development of a robust postmarket device evaluation system using real-world data (RWD) from electronic health records (EHRs) and other sources, employing unique device identifiers (UDIs) to link to device information. To create consistent device-related EHR RWD across 3 institutions, we established a distributed data network and created UDI-enriched research databases (UDIRs) employing a common data model comprised of 24 tables and 472 fields. To test the system, patients receiving coronary stents between 2010 and 2019 were loaded into each institution’s UDIR to support distributed queries without sharing identifiable patient information. The ability of the system to execute queries was tested with 3 quality assurance checks. To demonstrate face validity of the data, a retrospective survival study of patients receiving zotarolimus or everolimus stents from 2012 to 2017 was performed using distributed analysis. Propensity score matching was used to compare risk of 6 cardiovascular outcomes within 12 months postimplantation. The test queries established network functionality. In the analysis, we identified 9141 patients (Mercy = 4905, Geisinger = 4109, Intermountain = 127); mean age 65 ± 12 years, 69% males, 23% zotarolimus. Separate matched analyses at the 3 institutions showed hazard ratio estimates (zotarolimus vs everolimus) of 0.85–1.59 for subsequent percutaneous coronary intervention (P = .14–.52), 1.06–2.03 for death (P = .16–.78) and 0.94–1.40 for the composite endpoint (P = .16–.62). The analysis results are consistent with clinical studies comparing these devices. This project shows that multi-institutional data networks can provide clinically relevant real-world evidence via distributed analysis while maintaining data privacy.
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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:
11.3
作者:
Chen, Kang-Yin;Rha, Seung-Woon;Park, Seung Jung
通讯作者:
Park, Seung Jung
DOI:
10.1016/j.hjdsi.2015.07.002
发表时间:
2016-06-01
影响因子:
2.5
作者:
Drozda, Joseph P., Jr.;Dudley, Curtis;Hutchison, Lisa
通讯作者:
Hutchison, Lisa
影响因子:
3.5
作者:
Steele, Garen D.;Fehring, Thomas K.;Nadaud, Matthew C.
通讯作者:
Nadaud, Matthew C.
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