Behind the prominence of Electronic Health Records (EHRs) in improving healthcare efficiency, their reliance on centralized infrastructure imposes significant challenges in security vulnerabilities, limited interoperability, and privacy concerns. To address these challenges, this study introduces a Decentralized Medical Record (DMR) model. The proposed model utilizes the decentralized nature of blockchain and integrates composable Non-Fungible Tokens (NFTs) to enable granular data access control. While the integration of blockchain has been studied, the integration of composable NFT in medical records is yet to be explored. The modular design of composable NFT leaves the potential to prevent unnecessary data exposure, ensuring medical data is secure and interoperable throughout treatment collaboration among diverse stakeholders while preserving patient privacy. By incorporating insurance participation in the healthcare ecosystem, this model enables personalized risk assessment. Through Multi-Criteria Analysis (MCA), the model evaluation focuses on six key aspects: functionality, benefit, potential, accessibility, credibility, and continuity. Using Simple Additive Weighting (SAW) under this methodology, we analyze stakeholder inputs and achieve an overall score of 0,868 indicating a positive rating in addressing stakeholder needs. Our findings contribute to medical data management by demonstrating a novel application of composable NFTs within a structured DMR framework, detailing its mechanism, NFT hierarchy, database architecture, and workflow.