Federated queries of clinical data repositories: balancing accuracy and privacy

Abstract

Researchers use large federated clinical data networks that connect dozens of healthcare organizations to access data on millions of patients. However, because patients often receive care from multiple sites in the network, queries frequently double-count patients. Using the probabilistic streaming algorithm HyperLogLog and adding obfuscation, we developed a scalable method for estimating the number of distinct lives that match a query, which balances accuracy and privacy in a "tunable" way.