Inclusion of the Internet of Things (IoT) based technologies in healthcare systems has brought a tremendous change in the real time monitoring and diagnosis of patients. This has however come with significant cybersecurity challenges which are compromising the confidentiality, integrity and availability of patients’ sensitive data. This paper provides a comprehensive survey on various existing IoT-enabled healthcare monitoring systems and examines the prevalent security challenges they encounter such as device level threats, network attacks, application-level vulnerabilities, and human-centric risks. To address these challenges, we propose a layered patient data protection approach which includes secure device provisioning, end-to-end encryption, AI/ML based anomaly detection, block motion for data integrity and identity and access management (IAM). We provide a comparison of the related work which shows the improvement of our approach in scalability, latency, detection rate, and privacy preservation. The framework is also validated with real-world examples of the healthcare data breaches, which demonstrates the practical relevance and feasibility of our approach. The objective of this effort is to fill an existing void in the Iot healthcare cybersecurity space and help guide secure IOT deployment in digital healthcare ecosystems.