Cloud Based Secure Enterprise Healthcare Software with AI Centered Risk Governance
DOI:
https://doi.org/10.15662/IJARCST.2024.0704017Keywords:
Cloud Computing, Enterprise Healthcare Systems, Artificial Intelligence, Risk Governance, Cybersecurity, Data Privacy, Electronic Health Records, Predictive Analytics, HIPAA Compliance, Healthcare IT InfrastructureAbstract
Cloud-based secure enterprise healthcare software has emerged as a transformative approach to managing clinical, administrative, and financial operations in modern healthcare systems. With the rapid digitization of medical records and integration of advanced analytics, healthcare organizations increasingly rely on cloud infrastructures to deliver scalable, interoperable, and cost-efficient services. At the same time, the proliferation of sensitive patient data and regulatory requirements necessitates robust security, privacy protection, and risk governance frameworks. Artificial Intelligence (AI) plays a critical role in enhancing cybersecurity, predictive analytics, clinical decision support, fraud detection, and compliance monitoring. This paper explores the architecture, governance structures, and risk management strategies associated with AI-centered cloud healthcare platforms. It analyzes the integration of machine learning models into enterprise systems such as electronic health records, telemedicine platforms, and population health management tools. Furthermore, it evaluates regulatory compliance frameworks including HIPAA and global data protection standards. The study proposes a comprehensive research methodology for designing and implementing secure AI-driven healthcare enterprise systems. Finally, advantages and limitations are discussed to provide a balanced understanding of technological, ethical, operational, and financial implications in contemporary healthcare ecosystems.
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