| Literature DB >> 29867290 |
Feng Chen1, Xiaoqian Jiang1, Shuang Wang1, Lisa M Schilling2, Daniella Meeker3, Toan Ong2, Michael E Matheny4,5, Jason N Doctor6, Lucila Ohno-Machado1, Jaideep Vaidya7.
Abstract
Patient health data are often found spread across various sources. However, precision medicine and personalized care requires access to the complete medical records. The first step towards this is to enable the linkage of health records spread across different sites. Existing record linkage solutions assume that data is centralized with no privacy/security concerns restricting sharing. However, that is often untrue. Therefore, we design and implement a portable method for privacy-preserving record linkage based on garbled circuits to accurately and securely match records. We also develop a novel approximate matching mechanism that significantly improves efficiency.Entities:
Keywords: EHR linkage; Garbled circuit; Privacy preserving; Secure multi-party computation
Year: 2018 PMID: 29867290 PMCID: PMC5983039 DOI: 10.1109/MIC.2018.112102542
Source DB: PubMed Journal: IEEE Internet Comput ISSN: 1089-7801 Impact factor: 2.341