PRECISE: PRivacy-preserving cloud-assisted quality improvement service in healthcare

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.