Authors: Deeksha M, Subhiksha N
Abstract: The rapid growth of healthcare data generated by electronic health records, medical imaging systems, wearable sensors, and telemedicine platforms has created unprecedented challenges for healthcare data management. Conventional on-premise infrastructures are increasingly unable to support the scalability, interoperability, and analytical intelligence required by modern healthcare ecosystems. Cloud computing has emerged as a promising alternative; however, its adoption in healthcare remains limited due to concerns regarding data security, regulatory compliance, interoperability, and performance reliability. This paper proposes a cloud-native intelligent healthcare data management framework that integrates secure data ingestion, standards-based interoperability, artificial intelligence–driven analytics, and automated compliance governance within a hybrid or multi-cloud environment. The framework is designed to support heterogeneous healthcare data sources while maintaining privacy, regulatory adherence, and real-time responsiveness. A detailed architectural design, data flow model, security mechanisms, and use-case-driven analysis are presented. The proposed solution demonstrates how cloud-native principles can enable scalable, secure, and intelligent healthcare data management suitable for next-generation digital health systems.
