Novel use of a hash-based tokenization for sharing sickle cell disease data without sharing protected health information

Clinical Snapshot

Key Findings

• P Value: Not applicable for this methodology study

• Effect Size: 1,080 unique individuals identified across multiple datasets from 8,026 total records

• Primary Outcome: Successful privacy-preserving linkage of three major SCD registries

• Nnt Or Sensitivity: 13.5% overlap rate between registries (1,080/8,026)

• Confidence Interval: Not reported

Clinical Application

High - methodology uses standard cryptographic techniques implementable in most healthcare IT environments Highly relevant for Australian rare disease registries under Privacy Act 1988 and NHMRC guidelines. Could enhance National Rare Disease Registry coordination while maintaining privacy compliance. Sickle cell disease patients in registry-based research settings

Abstract

Efforts to improve care for people living with sickle cell disease (SCD) have led to the development of several registries; however, many are dependent on time-limited funding and lack coordination. Consequently, existing data sets are fragmented and do not provide the comprehensive, longitudinal insights achievable through well-integrated registries. Although relevant data exist within electronic medical records across institutions, aggregation is limited by poor interoperability, inconsistent use of common data elements, and poor translation of natural language into codified data. These barriers hinder population-level research and contribute to gaps in understanding the lifelong progression of SCD. Creating a new common data system risk losing years of valuable data, highlighting the need to optimize existing data resources. This study aimed to develop a privacy-preserving method to securely link 3 of the largest SCD data collection efforts in the United States. Conducted at the University of Alabama at Birmingham Lifespan Sickle Cell Center, the study leveraged institutional review board-approved access to the Sickle Cell Data Collection project, the American Society of Hematology Research Collaborative Data Hub, and the Globin Research Network for Data and Discovery. Identity tokens were generated and hashed using Secure Hash Algorithm (SHA)-256 to enable secure linkage without sharing protected health information. A total of 8026 records were identified across the 3 registries. Deterministic matching of hashed tokens identified 1080 unique individuals appearing in at least 2 data sets. This study demonstrates the first privacy-preserving linkage of multiple SCD registries. Secure data integration enhances interoperability and enables richer longitudinal analyses critical for advancing SCD research and treatment development.

References

1. 1.Galadanci, N. A., Hellemann, G., Washko, S., Abrams, C. S., Torres, K., & Kanter, J. (2026). Novel use of a hash-based tokenization for sharing sickle cell disease data without sharing protected health information. Blood Advances. https://doi.org/10.1182/bloodadvances.2025019450