Patient consent management by a purpose-based consent model for electronic health record based on blockchain technology

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Abstract

Objectives: Currently, patients’ consent is essential to use their medical records for various purposes; however, most people give their consent using paper forms and have no control over it. Healthcare organizations also have difficulties in dealing with patient consent. The objective of this research is to develop a system for patients to manage their consent flexibly and for healthcare organizations to obtain patient consent efficiently for a variety of purposes. Methods: We introduce a new e-con-sent model, which uses a purpose-based access control scheme; it is implemented by a blockchain system using Hyperledger Fabric. All metadata of patient records, consents, and data access are written immutably on the blockchain and shared among participant organizations. We also created a blockchain chaincode that performs business logic managing patient consent. Results: We developed a prototype and checked business logics with the chaincode by validating doctors’ data access with purpose-based consent of patients stored in the blockchain. The results demonstrate that our system provides a fine-grained way of handling medical staff ’s access requests with diverse intended purposes for accessing data. In addition, patients can create, update, and withdraw their consents in the blockchain. Conclusions: Our consent model is a solution for consent management both for patients and healthcare organizations. Our system, as a blockchain-based solution that provides high reliability and availability with transparency and traceability, is expected to be used not only for patient data sharing in hospi-tals, but also for data donation for biobank research purposes.

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CITATION STYLE

APA

Tith, D., Lee, J. S., Suzuki, H., Wijesundara, W. M. A. B., Taira, N., Obi, T., & Ohyama, N. (2020). Patient consent management by a purpose-based consent model for electronic health record based on blockchain technology. Healthcare Informatics Research, 26(4), 265–273. https://doi.org/10.4258/hir.2020.26.4.265

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