Accelerating Privacy-Preserving Medical Record Linkage: A Three-Party MPC Approach

TL;DR

This paper introduces a three-party secure computation method for privacy-preserving medical record linkage that significantly accelerates the process while maintaining high linkage quality, enabling faster and scalable data integration in healthcare.

Contribution

The paper presents a novel three-party MPC framework that improves the speed of privacy-preserving record linkage without compromising accuracy, outperforming existing solutions.

Findings

Up to 14 times faster linkage performance.

Linking 10,000 records in under 9 seconds on high-speed networks.

Scalable linkage in slower network conditions within 28 seconds.

Abstract

Record linkage is a crucial concept for integrating data from multiple sources, particularly when datasets lack exact identifiers, and it has diverse applications in real-world data analysis. Privacy-Preserving Record Linkage (PPRL) ensures this integration occurs securely, protecting sensitive information from unauthorized access. This is especially important in sectors such as healthcare, where datasets include private identity information (IDAT) governed by strict privacy laws. However, maintaining both privacy and efficiency in large-scale record linkage poses significant challenges. Consequently, researchers must develop advanced methods to protect data privacy while optimizing processing performance. This paper presents a novel and efficient PPRL method based on a secure 3-party computation (MPC) framework. Our approach allows multiple parties to compute linkage results without exposing their private inputs and significantly improves the speed of linkage process compared to existing privacy-preserving solutions. We demonstrated that our method preserves the linkage quality of the state-of-the-art PPRL method while achieving up to 14 times faster performance. For example, linking a record against a database of 10,000 records takes just 8.74 seconds in a realistic network with 700 Mbps bandwidth and 60 ms latency. Even on a slower internet connection with 100 Mbps bandwidth and 60 ms latency, the linkage completes in 28 seconds, highlighting the scalability and efficiency of our solution.