Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada.
J Am Med Inform Assoc. 2011 May 1;18(3):212-7. doi: 10.1136/amiajnl-2011-000100.
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.
医疗服务提供者一直不愿意出于公共卫生目的披露患者数据。即使能确保患者隐私，保护提供者的保密性的愿望也一直是他们不愿意披露的重要原因。
我们定义了满足提供者对保密性的需求并确保对公共卫生有用的监测协议的六个要求。作者使用 Paillier 密码系统开发了一种安全多方计算协议，允许披露分层病例计数和分母，以满足这些要求。作者在模拟环境中评估了该协议在计算性能和检测疾病爆发集群方面的能力。
理论和实证评估表明，该协议满足所有要求。一个实施该协议的系统在计算时间方面按提供者的数量线性扩展。对于来自 3000 个实践的数据，执行计算的绝对时间为 12.5 s。考虑到报告通常以 24 h 的间隔进行，这是可以接受的性能。与非安全分布式监测协议相比，检测疾病爆发集群的准确性保持不变，对于涉及 500 个或更多病例的爆发，F 分数高于 0.92。
该协议和相关软件为提供者提供了一种实用的方法，可以在保护患者隐私和个人提供者身份的同时，披露患者数据进行哨点、症状监测或其他基于指标的监测。
