A SECURE PERSONAL HEALTH RECORD MANAGEMENT SYSTEM USING BLOCKCHAIN AND MACHINE LEARNING

Abstract

The rapid digital transformation of healthcare has significantly increased the adoption of Electronic Health Records (EHRs) and Personal Health Records (PHRs), enabling patients and healthcare providers to access medical information efficiently. However, conventional PHR management systems face critical challenges such as data breaches, unauthorized access, lack of interoperability, centralized storage vulnerabilities, and limited patient control over sensitive medical information. To address these issues, this research proposes A Secure Personal Health Record Management System Using Blockchain and Machine Learning, which combines the decentralized security of blockchain technology with the intelligent analytical capabilities of machine learning. The proposed framework stores encrypted health records on a blockchain network, ensuring data integrity, transparency, immutability, and tamper resistance while enabling patients to maintain full ownership and control over their medical data. Smart contracts automate secure access control, authentication, and permission management, allowing only authorized healthcare professionals to retrieve patient records. Machine learning algorithms are integrated to analyze medical data for disease prediction, anomaly detection, personalized healthcare recommendations, and early risk assessment, thereby improving clinical decisionmaking and patient outcomes. The system also incorporates cryptographic encryption, multifactor authentication, and secure key management to strengthen data privacy and protect against cyberattacks. Unlike traditional centralized healthcare systems, the proposed solution eliminates single points of failure and enhances scalability, interoperability, and reliability across multiple healthcare institutions. Experimental evaluation demonstrates that the proposed framework achieves high security, reduced data retrieval time, improved access efficiency, and accurate predictive analytics while maintaining compliance with healthcare privacy standards. The integration of blockchain and machine learning creates a trustworthy, intelligent, and patient-centric healthcare 91 Vol. 22, No. 2(2), 2026 https://ijerst.org/index.php/ijerst 1282 ecosystem capable of supporting secure data sharing among hospitals, laboratories, insurance providers, and patients. Overall, the proposed system provides an effective solution for modern healthcare by improving data security, privacy, accessibility, and intelligent medical analysis, making it suitable for next-generation digital healthcare infrastructures.