IMDSP-BSoS is a novel System-of-Systems (SoS) framework integrating Blockchain, Federated Learning, ListenFirst ML (LFML), wearable devices, and edge-cloud computing to address secure, efficient, and scalable healthcare data management. The framework employs Adaptive Privacy Sharding (APS) for advanced privacy and supports context-aware decision-making, enabling robust distributed operations. Formulated as an optimization problem, IMDSP-BSoS balances predictive performance, data security, latency, and scalability. It achieves strong results, including AUC of 0.9569 and 88% accuracy on the HCC dataset, AUC of 0.9378 and 85% accuracy for CKD, and 94% accuracy for wearable sensor-based anomaly detection. With an 80ms latency, it ensures real-time responsiveness, while stable blockchain throughput highlights scalability and robustness. Leveraging Docker and Kubernetes, the system dynamically scales under high workloads. Compared to traditional models, IMDSP-BSoS excels in security, adaptability, and efficiency, providing a transformative solution for modern healthcare data management.