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Perfectly Secure and Efficient Two-Party Electronic-Health-Record Linkage
Feng Chen1, Xiaoqian Jiang1, Shuang Wang1
1Health System Department of Biomedical Informatics, UC San Diego, La Jolla, CA, 92093.
IEEE Internet Computing
|June 6, 2018
Summary
This study introduces a privacy-preserving method for linking patient health records across different locations. It uses garbled circuits and approximate matching for secure and efficient data integration, crucial for precision medicine.
Area of Science:
- Health Informatics
- Computer Science
- Cryptography
Background:
- Patient health data is fragmented across multiple sources, hindering comprehensive medical records.
- Precision medicine and personalized care necessitate integrated health data for accurate patient profiles.
- Existing record linkage methods fail when data is decentralized or faces privacy restrictions.
Purpose of the Study:
- To design and implement a portable, privacy-preserving method for linking distributed patient health records.
- To enable accurate and secure matching of medical records across different sites.
- To improve the efficiency of record linkage through a novel approximate matching mechanism.
Main Methods:
- Utilized garbled circuits for privacy-preserving computation during record linkage.
- Developed a novel approximate matching algorithm to enhance linkage efficiency.
- Implemented a portable solution adaptable to various data sharing scenarios.
Main Results:
- Successfully demonstrated a secure and accurate method for linking patient health records.
- Achieved significant efficiency improvements in record linkage using the approximate matching mechanism.
- Validated the portability and effectiveness of the privacy-preserving linkage approach.
Conclusions:
- The developed method offers a viable solution for secure and efficient health record linkage.
- This approach supports the goals of precision medicine by enabling access to complete patient data.
- Garbled circuits and approximate matching are effective techniques for privacy-preserving data integration in healthcare.
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