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Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD)

OBJECTIVES: 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. METHODS: To create consistent device-related EHR RWD acros...

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Autores principales: Drozda, Joseph P, 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9154019/
https://www.ncbi.nlm.nih.gov/pubmed/35663113
http://dx.doi.org/10.1093/jamiaopen/ooac035
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author Drozda, Joseph P
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
author_facet Drozda, Joseph P
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
author_sort Drozda, Joseph P
collection PubMed
description OBJECTIVES: 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. METHODS: 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. RESULTS: 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). DISCUSSION: The analysis results are consistent with clinical studies comparing these devices. CONCLUSION: 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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spelling pubmed-91540192022-06-04 Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD) Drozda, Joseph P 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 JAMIA Open Research and Applications OBJECTIVES: 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. METHODS: 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. RESULTS: 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). DISCUSSION: The analysis results are consistent with clinical studies comparing these devices. CONCLUSION: This project shows that multi-institutional data networks can provide clinically relevant real-world evidence via distributed analysis while maintaining data privacy. Oxford University Press 2022-05-25 /pmc/articles/PMC9154019/ /pubmed/35663113 http://dx.doi.org/10.1093/jamiaopen/ooac035 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research and Applications
Drozda, Joseph P
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
Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD)
title Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD)
title_full Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD)
title_fullStr Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD)
title_full_unstemmed Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD)
title_short Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD)
title_sort multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (build)
topic Research and Applications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9154019/
https://www.ncbi.nlm.nih.gov/pubmed/35663113
http://dx.doi.org/10.1093/jamiaopen/ooac035
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