Modern healthcare increasingly relies on interconnected medical devices, clinical information systems, cloud services, and distributed‑care technologies, exposing the entire clinical workflow to heightened cyber risk. AI‑enabled vulnerability discovery and attack‑path analysis accelerate threat propagation, intensifying the need to limit compromise spread. This paper introduces a clinical‑protocol‑aware cyber‑resilience framework built on bounded clinical micro‑networks and controlled interconnections. The framework embeds clinical factors into security design, management, and evaluation, covering prevention, containment, and incident response.\n\nA parameterized Monte Carlo simulation separates technical cyber exposure from modeled clinical consequence. Experiments explore architectural connectivity, adversarial capability, security controls, protocol dependency, risk alignment, communication directionality, lifecycle integration, and response timing. Under the simulation assumptions, a connected architecture raises mean cyber exposure by 56.3% compared to a segmented one, while combined prevention and containment reduce exposure by 60.1% relative to no controls. Increasing protocol dependency lifts the modeled clinical‑impact index from 1.021 to 7.567 without changing mean exposure, demonstrating that technical exposure and clinical consequence can diverge. Risk‑alignment tests further show higher clinical impact when greater technical risk aligns with greater clinical significance.\n\nThe findings support comparative architectural analysis rather than calibrated estimates of real‑world cyber risk, control effectiveness, or patient harm. The framework offers a clinical‑context‑aware approach to security‑boundary design, control prioritization, and coordinated containment in connected healthcare settings.\n\nReview