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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...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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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. |
format | Online Article Text |
id | pubmed-9933062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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