A quality of service-centric framework for enhancing reliability and prioritization of critical data in TCP/IP-based healthcare networks

The rapid expansion of digital health ecosystems has intensified the dependence of hospitals, diagnostic laboratories, and telemedicine platforms on TCP/IP-based networks for real-time data transmission, interoperability, and clinical decision-making. However, as patient monitoring systems, imaging modalities, laboratory automation platforms, and electronic health records generate increasingly heterogeneous and latency-sensitive traffic, traditional best-effort TCP/IP communication struggles to guarantee predictable performance. Congestion, packet loss, bandwidth contention, and nondeterministic delay directly impair clinical workflows, leading to delayed alarms, incomplete data streams, and reduced diagnostic accuracy. Addressing these challenges requires a shift toward Quality of Service (QoS)-centric network architectures capable of differentiating, prioritizing, and safeguarding critical healthcare data streams. This study proposes a comprehensive QoS-centric framework designed to enhance reliability, deterministic behavior, and context-aware prioritization in healthcare communication networks. The framework integrates advanced traffic classification, medical device profiling, dynamic flow scheduling, and adaptive congestion control into a unified management layer. It further incorporates cross-layer signaling between application, transport, and network layers to ensure that life-critical data such as vital-sign telemetry, infusion pump updates, clinical alarms, remote surgery feeds, and real-time imaging maintains precedence over routine administrative traffic. The proposed model additionally embeds fault-tolerance features, including redundancy-aware routing, microburst detection, and automated failover mechanisms tailored to the unique constraints of hospital network topologies. To validate performance, the framework is evaluated through simulated and empirical healthcare workloads reflecting ICU operations, PACS imaging bursts, tele-ICU video telemetry, and HL7/FHIR-based data exchange. Results demonstrate substantial gains in throughput stability, latency reduction, and packet delivery fidelity compared with conventional TCP/IP configurations. Overall, this QoS-centric architecture provides a scalable and implementation-ready pathway for healthcare organizations seeking to modernize network infrastructures, mitigate risk, and ensure uninterrupted delivery of mission-critical clinical information.