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Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet(®), the National Patient-Centered Clinical Research Network

OBJECTIVE: This article describes the implementation of a privacy-preserving record linkage (PPRL) solution across PCORnet(®), the National Patient-Centered Clinical Research Network. MATERIAL AND METHODS: Using a PPRL solution from Datavant, we quantified the degree of patient overlap across the ne...

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Autores principales: Marsolo, Keith, Kiernan, Daniel, Toh, Sengwee, Phua, Jasmin, Louzao, Darcy, Haynes, Kevin, Weiner, Mark, Angulo, Francisco, Bailey, Charles, Bian, Jiang, Fort, Daniel, Grannis, Shaun, Krishnamurthy, Ashok Kumar, Nair, Vinit, Rivera, Pedro, Silverstein, Jonathan, Zirkle, Maryan, Carton, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9933062/
https://www.ncbi.nlm.nih.gov/pubmed/36451264
http://dx.doi.org/10.1093/jamia/ocac229
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author Marsolo, Keith
Kiernan, Daniel
Toh, Sengwee
Phua, Jasmin
Louzao, Darcy
Haynes, Kevin
Weiner, Mark
Angulo, Francisco
Bailey, Charles
Bian, Jiang
Fort, Daniel
Grannis, Shaun
Krishnamurthy, Ashok Kumar
Nair, Vinit
Rivera, Pedro
Silverstein, Jonathan
Zirkle, Maryan
Carton, Thomas
author_facet Marsolo, Keith
Kiernan, Daniel
Toh, Sengwee
Phua, Jasmin
Louzao, Darcy
Haynes, Kevin
Weiner, Mark
Angulo, Francisco
Bailey, Charles
Bian, Jiang
Fort, Daniel
Grannis, Shaun
Krishnamurthy, Ashok Kumar
Nair, Vinit
Rivera, Pedro
Silverstein, Jonathan
Zirkle, Maryan
Carton, Thomas
author_sort Marsolo, Keith
collection PubMed
description OBJECTIVE: This article describes the implementation of a privacy-preserving record linkage (PPRL) solution across PCORnet(®), the National Patient-Centered Clinical Research Network. MATERIAL AND METHODS: Using a PPRL solution from Datavant, we quantified the degree of patient overlap across the network and report a de-duplicated analysis of the demographic and clinical characteristics of the PCORnet population. RESULTS: There were ∼170M patient records across the responding Network Partners, with ∼138M (81%) of those corresponding to a unique patient. 82.1% of patients were found in a single partner and 14.7% were in 2. The percentage overlap between Partners ranged between 0% and 80% with a median of 0%. Linking patients’ electronic health records with claims increased disease prevalence in every clinical characteristic, ranging between 63% and 173%. DISCUSSION: The overlap between Partners was variable and depended on timeframe. However, patient data linkage changed the prevalence profile of the PCORnet patient population. CONCLUSIONS: This project was one of the largest linkage efforts of its kind and demonstrates the potential value of record linkage. Linkage between Partners may be most useful in cases where there is geographic proximity between Partners, an expectation that potential linkage Partners will be able to fill gaps in data, or a longer study timeframe.
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spelling pubmed-99330622023-02-17 Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet(®), the National Patient-Centered Clinical Research Network Marsolo, Keith Kiernan, Daniel Toh, Sengwee Phua, Jasmin Louzao, Darcy Haynes, Kevin Weiner, Mark Angulo, Francisco Bailey, Charles Bian, Jiang Fort, Daniel Grannis, Shaun Krishnamurthy, Ashok Kumar Nair, Vinit Rivera, Pedro Silverstein, Jonathan Zirkle, Maryan Carton, Thomas J Am Med Inform Assoc Research and Applications OBJECTIVE: This article describes the implementation of a privacy-preserving record linkage (PPRL) solution across PCORnet(®), the National Patient-Centered Clinical Research Network. MATERIAL AND METHODS: Using a PPRL solution from Datavant, we quantified the degree of patient overlap across the network and report a de-duplicated analysis of the demographic and clinical characteristics of the PCORnet population. RESULTS: There were ∼170M patient records across the responding Network Partners, with ∼138M (81%) of those corresponding to a unique patient. 82.1% of patients were found in a single partner and 14.7% were in 2. The percentage overlap between Partners ranged between 0% and 80% with a median of 0%. Linking patients’ electronic health records with claims increased disease prevalence in every clinical characteristic, ranging between 63% and 173%. DISCUSSION: The overlap between Partners was variable and depended on timeframe. However, patient data linkage changed the prevalence profile of the PCORnet patient population. CONCLUSIONS: This project was one of the largest linkage efforts of its kind and demonstrates the potential value of record linkage. Linkage between Partners may be most useful in cases where there is geographic proximity between Partners, an expectation that potential linkage Partners will be able to fill gaps in data, or a longer study timeframe. Oxford University Press 2022-11-30 /pmc/articles/PMC9933062/ /pubmed/36451264 http://dx.doi.org/10.1093/jamia/ocac229 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research and Applications
Marsolo, Keith
Kiernan, Daniel
Toh, Sengwee
Phua, Jasmin
Louzao, Darcy
Haynes, Kevin
Weiner, Mark
Angulo, Francisco
Bailey, Charles
Bian, Jiang
Fort, Daniel
Grannis, Shaun
Krishnamurthy, Ashok Kumar
Nair, Vinit
Rivera, Pedro
Silverstein, Jonathan
Zirkle, Maryan
Carton, Thomas
Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet(®), the National Patient-Centered Clinical Research Network
title Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet(®), the National Patient-Centered Clinical Research Network
title_full Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet(®), the National Patient-Centered Clinical Research Network
title_fullStr Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet(®), the National Patient-Centered Clinical Research Network
title_full_unstemmed Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet(®), the National Patient-Centered Clinical Research Network
title_short Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet(®), the National Patient-Centered Clinical Research Network
title_sort assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in pcornet(®), the national patient-centered clinical research network
topic Research and Applications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9933062/
https://www.ncbi.nlm.nih.gov/pubmed/36451264
http://dx.doi.org/10.1093/jamia/ocac229
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