The rapid convergence of Internet of Things (IoT) technologies, digital twin modeling, and distributed ledger systems has inaugurated a new era of cyber-physical integration, particularly within the healthcare sector. As healthcare systems transition toward Industry 4.0 paradigms, the deployment of virtual replicas for patient monitoring, diagnostic processes, and resource optimization offers unprecedented opportunities for precision medicine. However, this transition is fraught with significant architectural challenges, including data integrity, computational latency, and the vulnerability of peer-to-peer networks to adversarial threats. This article provides a comprehensive analysis of the security imperatives within cyber-physical healthcare ecosystems. We examine the role of blockchain oracles in bridging the gap between off-chain physical sensor data and on-chain immutability, while simultaneously addressing the emerging threat of quantum computing to cryptographic standards. Furthermore, we investigate the necessity of hybrid cloud-edge computing architectures to facilitate real-time predictive analytics while maintaining patient privacy and data sovereignty. Through a synthesis of existing literature, this work proposes a multidimensional framework for securing digital twin-driven health systems, emphasizing the need for standardized anomaly-based intrusion detection and robust task-offloading strategies. The study concludes that the future of resilient healthcare systems lies in the adoption of standardized, AI-enabled governance models that can dynamically respond to both internal performance drifts and external malicious actors, ensuring the continuity and safety of patient-centric care in an increasingly interconnected global infrastructure.