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

Keith Marsolo; Daniel Kiernan; Sengwee Toh; Jasmin Phua; 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; Maryan Zirkle; Thomas Carton

doi:10.1093/jamia/ocac229

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

J Am Med Inform Assoc. 2023 Feb 16;30(3):447-455. doi: 10.1093/jamia/ocac229.

Authors

Keith Marsolo^{1

2}, Daniel Kiernan³, Sengwee Toh³, Jasmin Phua⁴, Darcy Louzao², Kevin Haynes⁵, Mark Weiner⁶, Francisco Angulo⁷, Charles Bailey⁸, Jiang Bian⁹, Daniel Fort¹⁰, Shaun Grannis¹¹, Ashok Kumar Krishnamurthy¹², Vinit Nair¹³, Pedro Rivera¹⁴, Jonathan Silverstein¹⁵, Maryan Zirkle¹⁶, Thomas Carton¹⁷

Affiliations

¹ Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA.
² Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, USA.
³ Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
⁴ Datavant, San Francisco, California, USA.
⁵ Scientific Affairs, HealthCore, Inc., Wilmington, Delaware, USA.
⁶ Department of Medicine, Weill Cornell Medicine, New York, New York, USA.
⁷ Department of Medicine, Cook County Health and Hospital System, Chicago, Illinois, USA.
⁸ Department of Pediatrics, Applied Clinical Research Center, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁹ Department of Health Outcomes and Bioinformatics, College of Medicine, University of Florida, Gainesville, Florida, USA.
¹⁰ Center for Outcomes and Health Services Research, Ochsner Health, New Orleans, Louisiana, USA.
¹¹ Regenstrief Institute, Indiana University, Indianapolis, Indiana, USA.
¹² Renaissance Computing Institute, University of North Carolina, Chapel Hill, North Carolina, USA.
¹³ Humana, Sharon, Massachusetts, USA.
¹⁴ OCHIN, Inc., Portland, Oregon, USA.
¹⁵ Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
¹⁶ Cohen Veterans Bioscience, New York, New York, USA.
¹⁷ Louisiana Public Health Institute, New Orleans, Louisiana, USA.

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.

Keywords: distributed research networks; privacy-preserving record linkage; real-world data.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computer Security
Confidentiality*
Demography
Electronic Health Records
Humans
Medical Record Linkage
Patient-Centered Care
Privacy*