MyDigitalHealth: Rethinking the health data management

The rapid expansion of digital health technologies—including electronic health records (EHRs), wearable devices, and mobile applications—has generated vast amounts of heterogeneous clinical data. However, current health information systems remain fragmented, poorly interoperable, and vulnerable to security breaches. These limitations hinder effective clinical decision-making, data integration, and patient autonomy. This study introduces the MyDigitalHealth (MDH) model, a patient-centric framework designed to enable secure, interoperable, and intelligent health data management. MDH aims to unify distributed clinical data sources through decentralized technologies, enforce granular consent mechanisms, and support AI-driven analytics for real-time and predictive healthcare applications. MDH employs blockchain technology and end-to-end encryption to ensure data privacy and security. The system supports granular consent management, real-time analytics, and decentralized data storage. Semantic interoperability is achieved through a domain ontology that is aligned with the HL7 FHIR and OpenEHR standards. Blockchain simulations were conducted to evaluate security and scalability. For predictive analytics, we developed and tested multimodal survival models that incorporate both structured and unstructured data. MDH demonstrated effective semantic interoperability, enabling temporal clinical queries across decentralized environments. Blockchain simulations confirmed a trade-off between block size and propagation delay, supporting the secure and scalable storage of encrypted health records. In predictive modeling, our multimodal survival model, Multimodal DynamicDeepHit, achieved a concordance index (C-index) of 0.742, substantially outperforming the unimodal DynamicDeepHit baseline (C-index: 0.584). The MDH model offers a viable solution for secure, interoperable, and intelligent clinical data management. Its integration of blockchain, semantic standards, and multimodal AI supports real-time analytics and enhances predictive performance. These results highlight MDH’s potential for real-world deployment in distributed, AI-driven healthcare systems. • Proposes MDH model, a patient-centered model for secure health data management. • MDH model integrates blockchain, interoperability standards, and AI-driven tools. • MDH model enables consent-based, auditable data sharing across health systems.