CrowdMed: A Blockchain-Based Approach to Consent Management for Health Data Sharing

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Abstract

The need for greater health data sharing is widely acknowledged in the healthcare industry. The provision of healthcare services and attempts to harness Big Data analytics are adversely affected by the fragmentation of medical data across healthcare providers. However, attempts to encourage greater data sharing have been unsuccessful due to privacy concerns and lack of motivation for patients to share their data. We propose CrowdMed, a medical data management framework to facilitate greater data sharing, empowering patients with full control over access to their medical data. The framework is fully transparent, ensuring that patients have full knowledge over how who has access to their data, and how their data is being used. Using blockchain as the foundation for consent management, patients can trust that only parties with permission can view their data. Permissions are also finely specified, and can be revoked or modified according to the patient’s wishes. Following these permissions, data is transferred automatically between parties, conveniently and efficiently alleviating the problem of data fragmentation. CrowdMed also addresses the lack of motivation for data sharing, incentivising patients to share more of their data for research purposes through reward tokens and an innovative pricing mechanism. The framework integrates fully with existing data storage architecture, aiding in its widespread adoption.

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APA

Shah, M., Li, C., Sheng, M., Zhang, Y., & Xing, C. (2019). CrowdMed: A Blockchain-Based Approach to Consent Management for Health Data Sharing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11924 LNCS, pp. 345–356). Springer. https://doi.org/10.1007/978-3-030-34482-5_31

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