Blockchain-Based Healthcare Data Management: Analysis and Evaluation of Security, Scalability, and Compliance for Electronic Health Records (EHRs)

The integration of blockchain technology into healthcare data management systems addresses persistent challenges such as data integrity, privacy, secure sharing of Electronic Health Records (EHRs), and compliance with regulatory standards. This study identifies the problem of centralized healthcare systems being prone to unauthorized access, data breaches, and limited scalability, hindering efficient data sharing across stakeholders. The primary objectives are to design, implement, and evaluate a blockchain-based healthcare data management framework to enhance data integrity, scalability, and access control. A multi-phase methodology was employed, including simulation testing, encryption evaluation, and benchmarking of blockchain security mechanisms. Synthetic healthcare datasets representing EHRs were used, with a sample size of 1 million transactionsprocessedundernormal,peak,andstressconditions. Techniques such as AES-256 encryption, SHA-3 hashing, and smart contracts were applied for data security and access control. Performance metrics analyzed include transaction latency, throughput, encryption efficiency, data integrity, and system resilience. The results demonstrate significant improvements, with an average transaction latency of 2.1 seconds, throughput of 1,200 TPS, 100% data integrity, and robust compliance with role-based access control mechanisms. Compared to traditional centralized systems, blockchain exhibited superior scalability, reduced error rates, and enhanced transparency in data-sharing processes. This study contributes a novel blockchain-based healthcare data framework optimized for secure, transparent, and regulatory-compliant data management. The findings show blockchain's transformative potential to revolutionize healthcare data sharing, offering a resilient and tamper-proof platform for EHR systems while addressing scalability and privacyconcerns.