Evidence map›Paper›PMID 41458221›Full record

ArticleJournal of registry management2025

Evaluating Privacy-Preserving Record Linkage in Merging Cancer Registry Data and Electronic Health Records.

Adam Wilcox, Shawn Grannis, Iris Zachary, Nicole Venterisv, Zachary Abrams, John Newland, Mohammad Beheshti, Lucinda Ham, Joshua Day, Jill S Barnholtz-Sloan

Abstract read
PubMed Full text at PMC
In one paragraph

Article in Journal of registry management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Adam WilcoxWashington University, St. Louis, MO.
Shawn GrannisWashington University, St. Louis, MO.
Iris ZacharyWashington University, St. Louis, MO.
Nicole VenterisvWashington University, St. Louis, MO.
Zachary AbramsWashington University, St. Louis, MO.
John NewlandWashington University, St. Louis, MO.
Mohammad BeheshtiUniversity of Missouri, Columbia, MO.
Lucinda HamUniversity of Missouri, Columbia, MO.
Joshua DayWashington University, St. Louis, MO.
Jill S Barnholtz-SloanEmory University, Atlanta, GA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Privacy-preserving record linkage (PPRL) can improve the utility of clinical data for research and discovery by merging disparate data sources to provide a more complete record of a patient. We assess the performance of record linkage across two data sets consisting of cancer registry data and electronic health records (EHRs). Using two data sources-EHR extracts and records from the Missouri Cancer Registry (MCR)-we performed various validation exercises, including an audit by the MCR and a comparative evaluation using multiple matching algorithms. Results indicated substantial matching performance, with high recall and precision rates. We conclude that the refined data linkage process significantly supports enhanced research capabilities without compromising patient privacy, thereby enabling reliable data integration for clinical research in oncology.

Indexed as

ConfidentialityElectronic Health RecordsMedical Record LinkageNeoplasmsRegistriesAlgorithmsHumansMissouriCancer registriesEHR dataRecord linkage

Identifiers

PMID41458221
PMCPMC12742408

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.