Integrating blockchain with healthcare data management promises enhanced privacy, security, and trust in handlingsensitive patient information. This paper reviews privacy-preserving blockchain frameworks—such as Hyperledger Fabric[1], Ethereum smart contracts [2], MediBchain, and ACHealthChain [5]—and identifies key challenges like limitedscalability, poor interoperability with existing systems, and lack of patient control [3][5][9].To overcome these issues, wepropose a modular architecture combining Hyperledger Fabric [1], off-chain encrypted storage via IPFS [5], and finegrained access using Ciphertext-Policy Attribute-Based Encryption (CP-ABE) [4][6]. Smart contracts enforce accesspolicies, enabling secure, patient-controlled data sharing without intermediaries. The architecture complies with dataprotection laws like HIPAA and GDPR [2][5], and integrates well with current clinical workflows [8][9]. Simulatedevaluation with 10,000 synthetic patient histories demonstrates improved scalability, lower latency, and strong privacy.Compared to MediBchain [5], our solution supports interoperability and secure federated learning [8], enablingcollaborative, privacy-preserving AI diagnostics. By prioritizing real-world integration, patient autonomy, and privacy, ourframework promotes a decentralized, secure, and future-ready digital health ecosystem.