Can Secure MultiParty Computation be Used to Create Clinical Trial Cohorts based on Blockchain Notarized Private Patient Data?
Bruno Ferreira, Rafael Borges, Carlos Machado Antunes, Marisa da Silva Maximiano, Ricardo Gomes, Vitor Távora, Manuel Dias, Ricardo Correia · Procedia Computer Science · 2025
Healthcare faces some challenges regarding its privacy-preserving collaboration about the sharing of patients’ data, since healthcare providers and researchers need to guarantee that they can securely analyze patients’ data without revealing sensitive information, guaranteeing compliance with the privacy regulations. Nowadays, with the large amounts of stored healthcare data, the use of technology that can facilitate joint calculations on data, especially when obtaining informed consent by the patient can create some investigation opportunities. Therefore, finding a way to allow researchers to perform secure analyses across multiple parties while maintaining patient privacy is mandatory. Secure MultiParty Computation (SMPC) is a cryptographic technology that allows multiple parties to collaboratively compute functions using their private data while preserving confidentiality. In this work it is analyzed the use of SMPC in enhancing data sharing, collaboration, and privacy in a healthcare case study, which has allowed us to identify that SMPC is a valuable approach for handling large amounts of sensitive patient data. The principal outcome of this study is an architectural proposal using SMPC in creating clinical trial cohorts based on queries performed on confidential health records. This approach requires the overcoming of the challenge on multi-entity collaboration but can guarantee the preservation of patient privacy and health data confidentiality.