The digital transformation of healthcare has resulted in highly interconnected ecosystems that integrate electronic health records, telemedicine, wearable devices, and cloud-based infrastructures. While these advancements improve patient outcomes and operational efficiency, they also introduce systemic vulnerabilities that expand the attack surface of healthcare organizations. The complexity of interdependent digital components makes it increasingly difficult to identify weaknesses that adversaries may exploit. Traditional perimeter-focused cybersecurity approaches often fail to address the dynamic and adaptive nature of modern cyber threats, leaving healthcare systems exposed to significant risks including data breaches, ransomware attacks, and service disruptions. Risk modeling has emerged as a critical tool for mapping vulnerabilities and quantifying potential impacts on healthcare operations and patient safety. By simulating various threat scenarios, organizations can prioritize mitigation strategies and allocate resources more effectively. Complementing this, threat intelligence provides real-time situational awareness, enabling proactive identification of adversarial tactics, techniques, and procedures. However, static controls are insufficient against constantly evolving attack landscapes. Adaptive security mechanisms capable of learning from ongoing activity and reconfiguring defenses are necessary to maintain resilience. These approaches incorporate artificial intelligence, behavior-based monitoring, and automated incident response to strengthen defense layers. This paper explores how combining risk modeling, threat intelligence, and adaptive control mechanisms can uncover systemic vulnerabilities in healthcare digital ecosystems and enhance cybersecurity resilience. It emphasizes the importance of integrating technical defenses with governance frameworks and compliance requirements to ensure sustainable protection. By adopting a holistic approach, healthcare organizations can safeguard sensitive patient data, preserve trust, and ensure continuity of clinical operations.