PRECISE:PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare.
PRECISE:PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare.
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DOI：
10.1109/isb.2014.6990752
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发表时间：
2014-10
期刊：
影响因子：
--
通讯作者：
Jiang X
中科院分区：
文献类型：
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作者：
Chen F;Wang S;Mohammed N;Cheng S;Jiang X
质量改进（QI）需要系统和持续的努力，以提高医疗服务。医疗保健提供者可能希望将当地的统计数据与其他机构的统计数据进行比较，以确定问题并制定干预措施，以提高护理质量。然而，机构隐私可能会阻碍机构信息的共享，因为公布此类统计数据可能会导致尴尬甚至经济损失。在这篇文章中，我们提出了一个PRIVACY-Preserving的云辅助质量改进服务在hEalcraft（PRECISE），其目的是使跨机构的医疗统计数据的比较，同时保护隐私。所提出的框架依赖于一组最先进的密码协议，包括同态加密和姚的乱码电路计划。通过安全地汇集来自不同机构的数据，PRECISE可以对加密的统计数据进行排名，以促进参与机构之间的QI。我们使用MIMIC II数据库进行了实验，并证明了所提出的PRECISE框架的可行性。
Quality improvement (QI) requires systematic and continuous efforts to enhance healthcare services. A healthcare provider might wish to compare local statistics with those from other institutions in order to identify problems and develop intervention to improve the quality of care. However, the sharing of institution information may be deterred by institutional privacy as publicizing such statistics could lead to embarrassment and even financial damage. In this article, we propose a PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare (PRECISE), which aims at enabling cross-institution comparison of healthcare statistics while protecting privacy. The proposed framework relies on a set of state-of-the-art cryptographic protocols including homomorphic encryption and Yao’s garbled circuit schemes. By securely pooling data from different institutions, PRECISE can rank the encrypted statistics to facilitate QI among participating institutes. We conducted experiments using MIMIC II database and demonstrated the feasibility of the proposed PRECISE framework.