A secure protocol for protecting the identity of providers when disclosing data for disease surveillance.

Abstract

Providers have been reluctant to disclose patient data for public-health purposes. Even if patient privacy is ensured, the desire to protect provider confidentiality has been an important driver of this reluctance. Six requirements for a surveillance protocol were defined that satisfy the confidentiality needs of providers and ensure utility to public health. The authors developed a secure multi-party computation protocol using the Paillier cryptosystem to allow the disclosure of stratified case counts and denominators to meet these requirements. The authors evaluated the protocol in a simulated environment on its computation performance and ability to detect disease outbreak clusters. Theoretical and empirical assessments demonstrate that all requirements are met by the protocol. A system implementing the protocol scales linearly in terms of computation time as the number of providers is increased. The absolute time to perform the computations was 12.5 s for data from 3000 practices. This is acceptable performance, given that the reporting would normally be done at 24 h intervals. The accuracy of detection disease outbreak cluster was unchanged compared with a non-secure distributed surveillance protocol, with an F-score higher than 0.92 for outbreaks involving 500 or more cases. The protocol and associated software provide a practical method for providers to disclose patient data for sentinel, syndromic or other indicator-based surveillance while protecting patient privacy and the identity of individual providers.