A secure and scalable blockchain-based model for electronic health record management

Area of Science:

• Computer Science
• Health Informatics
• Cybersecurity

Background:

• Storing Electronic Health Records (EHR) on open platforms poses significant security and privacy risks.
• Standardizing clinical deployment models is crucial for addressing these challenges.

Purpose of the Study:

• To propose a robust model for secure EHR storage, addressing security, privacy, access control, and ownership transfer.
• To enhance the Quality-of-Service (QoS) and scalability of EHR systems.

Main Methods:

• Incorporated data collection for clinical needs assessment and deployment-level checks for network attack mitigation.
• Employed a Modified Genetic Algorithm to improve blockchain scalability.
• Introduced mechanisms for database integrity, external attack mitigation, and enhanced usability.

Main Results:

• The proposed model supports platform modularization, access control, department-specific configurations, and patient-level confidentiality.
• Demonstrated superior performance over existing systems in ease of use, deployment delay, complexity, and module efficiency.

Conclusions:

• The model offers a highly suitable solution for implementing secure, customized clinic security systems using EHR.
• It effectively addresses critical security and privacy concerns in digital health records.