A Secure and Patient-Centric Digital Twin–Blockchain Framework for Type 2 Diabetes Management

The management of Type 2 Diabetes Mellitus (T2DM) is increasingly challenged by fragmented healthcare information systems, reactive care models, limited interoperability, and growing concerns regarding data privacy, security, and governance. Previous research established and validated a collaborative knowledge management model for T2DM self-management, demonstrating the importance of monitoring parameters, knowledge quality, and stakeholder collaboration in supporting effective disease management. Building upon this foundation, this study proposes a conceptual Digital Twin (DT) and blockchain-enabled framework to support secure, personalized, and knowledge-driven T2DM management. Using a design-oriented approach, the framework integrates contemporary digital health technologies with established self-management principles to address both personalization and trust-related challenges. The proposed architecture comprises four interconnected layers: (i) data acquisition and integration, (ii) DT modelling and adaptive patient representation, (iii) blockchain-enabled governance, and (iv) clinical decision support. The framework incorporates standards-based interoperability through HL7 FHIR, near-real-time synchronization of patient data, adaptive DT updating mechanisms, and permissioned blockchain smart contracts for consent management, access control, auditability, and data integrity. The DT layer supports patient-specific monitoring and predictive “what-if” simulations, while the blockchain layer provides transparent and accountable governance of health information exchanges. Rather than presenting a clinical implementation, this work provides a theoretically grounded reference architecture that operationalizes a previously validated diabetes self-management model using DT and blockchain technologies. The proposed framework offers a foundation for future prototype development, simulation studies, and pilot clinical evaluations aimed at assessing clinical effectiveness, user acceptance, trust, and governance performance in secure DT-enabled chronic disease management environments.