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

Implementing privacy preserving record linkage: Insights from Australian use cases

OBJECTIVE

To describe the use of privacy preserving linkage methods operationally in Australia, and to present insights and key learnings from their implementation.

METHODS

Privacy preserving record linkage (PPRL) utilising Bloom filters provides a unique practical mechanism that allows linkage to occur without the release of personally identifiable information (PII), while still ensuring high accuracy.

RESULTS

The methodology has received wide uptake within Australia, with four state linkage units with privacy preserving capability. It has enabled access to general practice and private pathology data amongst other, both much sought after datasets previous inaccessible for linkage.

CONCLUSION

The Australian experience suggests privacy preserving linkage is a practical solution for improving data access for policy, planning and population health research. It is hoped interest in this methodology internationally continues to grow.

Privacy preserving record linkage for public health action: opportunities and challenges

OBJECTIVES

To understand the landscape of privacy preserving record linkage (PPRL) applications in public health, assess estimates of PPRL accuracy and privacy, and evaluate factors for PPRL adoption.

MATERIALS AND METHODS

A literature scan examined the accuracy, data privacy, and scalability of PPRL in public health. Twelve interviews with subject matter experts were conducted and coded using an inductive approach to identify factors related to PPRL adoption.

RESULTS

PPRL has a high level of linkage quality and accuracy. PPRL linkage quality was comparable to that of clear text linkage methods (requiring direct personally identifiable information [PII]) for linkage across various settings and research questions. Accuracy of PPRL depended on several components, such as PPRL technique, and the proportion of missingness and errors in underlying data. Strategies to increase adoption include increasing understanding of PPRL, improving data owner buy-in, establishing governance structure and oversight, and developing a public health implementation strategy for PPRL.

DISCUSSION

PPRL protects privacy by eliminating the need to share PII for linkage, but the accuracy and linkage quality depend on factors including the choice of PPRL technique and specific PII used to create encrypted identifiers. Large-scale implementations of PPRL linking millions of observations-including PCORnet, National Institutes for Health N3C, and the Centers for Disease Control and Prevention COVID-19 project have demonstrated the scalability of PPRL for public health applications.

CONCLUSIONS

Applications of PPRL in public health have demonstrated their value for the public health community. Although gaps must be addressed before wide implementation, PPRL is a promising solution to data linkage challenges faced by the public health ecosystem.

Understanding enterprise data warehouses to support clinical and translational research: impact, sustainability, demand management, and accessibility

OBJECTIVES

Healthcare organizations, including Clinical and Translational Science Awards (CTSA) hubs funded by the National Institutes of Health, seek to enable secondary use of electronic health record (EHR) data through an enterprise data warehouse for research (EDW4R), but optimal approaches are unknown. In this qualitative study, our goal was to understand EDW4R impact, sustainability, demand management, and accessibility.

MATERIALS AND METHODS

We engaged a convenience sample of informatics leaders from CTSA hubs (n = 21) for semi-structured interviews and completed a directed content analysis of interview transcripts.

RESULTS

EDW4R have created institutional capacity for single- and multi-center studies, democratized access to EHR data for investigators from multiple disciplines, and enabled the learning health system. Bibliometrics have been challenging due to investigator non-compliance, but one hub's requirement to link all study protocols with funding records enabled quantifying an EDW4R's multi-million dollar impact. Sustainability of EDW4R has relied on multiple funding sources with a general shift away from the CTSA grant toward institutional and industry support. To address EDW4R demand, institutions have expanded staff, used different governance approaches, and provided investigator self-service tools. EDW4R accessibility can benefit from improved tools incorporating user-centered design, increased data literacy among scientists, expansion of informaticians in the workforce, and growth of team science.

DISCUSSION

As investigator demand for EDW4R has increased, approaches to tracking impact, ensuring sustainability, and improving accessibility of EDW4R resources have varied.

CONCLUSION

This study adds to understanding of how informatics leaders seek to support investigators using EDW4R across the CTSA consortium and potentially elsewhere.

Ownership and Interoperability Challenges of Alzheimer Monoclonal Antibody Registries

This Viewpoint addresses the challenges that the Centers for Medicare and Medicaid Services faces to collect real-world data on the effectiveness and safety of lecanemab from external registries to achieve its coverage with evidence development objectives.

Privacy-preserving record linkage across disparate institutions and datasets to enable a learning health system: The national COVID cohort collaborative (N3C) experience

Introduction

Research driven by real-world clinical data is increasingly vital to enabling learning health systems, but integrating such data from across disparate health systems is challenging. As part of the NCATS National COVID Cohort Collaborative (N3C), the N3C Data Enclave was established as a centralized repository of deidentified and harmonized COVID-19 patient data from institutions across the US. However, making this data most useful for research requires linking it with information such as mortality data, images, and viral variants. The objective of this project was to establish privacy-preserving record linkage (PPRL) methods to ensure that patient-level EHR data remains secure and private when governance-approved linkages with other datasets occur.

Methods

Separate agreements and approval processes govern N3C data contribution and data access. The Linkage Honest Broker (LHB), an independent neutral party (the Regenstrief Institute), ensures data linkages are robust and secure by adding an extra layer of separation between protected health information and clinical data. The LHB's PPRL methods (including algorithms, processes, and governance) match patient records using "deidentified tokens," which are hashed combinations of identifier fields that define a match across data repositories without using patients' clear-text identifiers.

Results

These methods enable three linkage functions: Deduplication, Linking Multiple Datasets, and Cohort Discovery. To date, two external repositories have been cross-linked. As of March 1, 2023, 43 sites have signed the LHB Agreement; 35 sites have sent tokens generated for 9 528 998 patients. In this initial cohort, the LHB identified 135 037 matches and 68 596 duplicates.

Conclusion

This large-scale linkage study using deidentified datasets of varying characteristics established secure methods for protecting the privacy of N3C patient data when linked for research purposes. This technology has potential for use with registries for other diseases and conditions.

Use of Tokens to Unlock Greater Data Sharing in Health Care

This Viewpoint discusses the use of privacy-preserving record linkage, a token-based record linkage system, as a promising avenue for building a data infrastructure system that bridges isolated data.