Abstract: Electronic Health Record (EHR) systems face critical challenges in security, interoperability, and patient data sovereignty. Centralized databases remain vulnerable to ransomware attacks and data breaches, while siloed systems prevent seamless provider communication. This paper presents a fully-functional, production-grade prototype integrating blockchain technology, decentralized storage via IPFS, and generative AI for intelligent clinical decision support. The system employs a novel four-layer architecture providing multi-persona web interface supporting patients, doctors, and hospital administrators, Node.js API server for orchestration and authentication, decentralized persistence layer combining Ethereum smart contracts with IPFS for scalable off-chain storage, and Google Gemini AI for real-time clinical analysis. The core innovation presents an AI-assisted prescription workflow analyzing physician drafts against complete patient medical history to generate drug-drug interaction warnings, contraindication alerts, and dosage recommendations. The system demonstrates superior security through blockchain immutability, enhanced interoperability via decentralized architecture, and improved clinical outcomes through context-aware AI analysis. The framework successfully addresses longstanding healthcare IT challenges while maintaining physician autonomy through human-in-the-loop design principles.

Keywords: Blockchain, Healthcare, Electronic Health Records, Artificial Intelligence, Clinical Decision Support, IPFS, Smart Contracts, Decentralized Applications, Medical Data Management, Web3.


Downloads: PDF | DOI: 10.17148/IJARCCE.2025.141280

How to Cite:

[1] Asha Kumari A, Vikas V, Shivakumar M A, Shivakumara D K, Yogesh B, "AI Integrated Blockchain Framework for Patient Management and Drug Recommendation," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.141280

Open chat
Chat with IJARCCE