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.

dc.contributor.author

Marsolo, Keith

dc.contributor.author

Kiernan, Daniel

dc.contributor.author

Toh, Sengwee

dc.contributor.author

Phua, Jasmin

dc.contributor.author

Louzao, Darcy

dc.contributor.author

Haynes, Kevin

dc.contributor.author

Weiner, Mark

dc.contributor.author

Angulo, Francisco

dc.contributor.author

Bailey, Charles

dc.contributor.author

Bian, Jiang

dc.contributor.author

Fort, Daniel

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Grannis, Shaun

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Krishnamurthy, Ashok Kumar

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Nair, Vinit

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Rivera, Pedro

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Silverstein, Jonathan

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Zirkle, Maryan

dc.contributor.author

Carton, Thomas

dc.date.accessioned

2026-03-10T15:58:45Z

dc.date.available

2026-03-10T15:58:45Z

dc.date.issued

2023-02

dc.description.abstract

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.
dc.identifier

6855148

dc.identifier.issn

1067-5027

dc.identifier.issn

1527-974X

dc.identifier.uri

https://hdl.handle.net/10161/34287

dc.language

eng

dc.publisher

Oxford University Press (OUP)

dc.relation.ispartof

Journal of the American Medical Informatics Association : JAMIA

dc.relation.isversionof

10.1093/jamia/ocac229

dc.rights.uri

https://creativecommons.org/licenses/by-nc/4.0

dc.subject

Humans

dc.subject

Medical Record Linkage

dc.subject

Confidentiality

dc.subject

Demography

dc.subject

Privacy

dc.subject

Computer Security

dc.subject

Patient-Centered Care

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Electronic Health Records

dc.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.

dc.type

Journal article

duke.contributor.orcid

Marsolo, Keith|0000-0002-4416-1549

duke.contributor.orcid

Louzao, Darcy|0009-0008-4725-5672

pubs.begin-page

447

pubs.end-page

455

pubs.issue

3

pubs.organisational-group

Duke

pubs.organisational-group

School of Medicine

pubs.organisational-group

Staff

pubs.organisational-group

Basic Science Departments

pubs.organisational-group

Institutes and Centers

pubs.organisational-group

Biostatistics & Bioinformatics

pubs.organisational-group

Duke Clinical Research Institute

pubs.organisational-group

Population Health Sciences

pubs.organisational-group

Biostatistics & Bioinformatics, Division of Translational Biomedical

pubs.publication-status

Published

pubs.volume

30

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