Autor: |
Daniel Kiernan, Thomas Carton, Sengwee Toh, Jasmin Phua, Maryan Zirkle, Darcy Louzao, Kevin Haynes, Mark Weiner, Francisco Angulo, Charles Bailey, Jiang Bian, Daniel Fort, Shaun Grannis, Ashok Kumar Krishnamurthy, Vinit Nair, Pedro Rivera, Jonathan Silverstein, Keith Marsolo |
Jazyk: |
angličtina |
Rok vydání: |
2022 |
Předmět: |
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Zdroj: |
BMC Research Notes, Vol 15, Iss 1, Pp 1-7 (2022) |
Druh dokumentu: |
article |
ISSN: |
1756-0500 |
DOI: |
10.1186/s13104-022-06243-5 |
Popis: |
Abstract Objective The aim of this study was to determine whether a secure, privacy-preserving record linkage (PPRL) methodology can be implemented in a scalable manner for use in a large national clinical research network. Results We established the governance and technical capacity to support the use of PPRL across the National Patient-Centered Clinical Research Network (PCORnet®). As a pilot, four sites used the Datavant software to transform patient personally identifiable information (PII) into de-identified tokens. We queried the sites for patients with a clinical encounter in 2018 or 2019 and matched their tokens to determine whether overlap existed. We described patient overlap among the sites and generated a “deduplicated” table of patient demographic characteristics. Overlapping patients were found in 3 of the 6 site-pairs. Following deduplication, the total patient count was 3,108,515 (0.11% reduction), with the largest reduction in count for patients with an “Other/Missing” value for Sex; from 198 to 163 (17.6% reduction). The PPRL solution successfully links patients across data sources using distributed queries without directly accessing patient PII. The overlap queries and analysis performed in this pilot is being replicated across the full network to provide additional insight into patient linkages among a distributed research network. |
Databáze: |
Directory of Open Access Journals |
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