Abstract: The integration of Artificial Intelligence (AI), data analytics, and cloud computing in healthcare has revolutionized Medicaid services, predictive analytics, interoperability, and workforce training. This paper explores scalable AI solutions, machine learning applications, and cloud-enabled healthcare advancements. It emphasizes AI-driven predictive analytics for Electronic Health Record (EHR) management and blockchain-enabled data interoperability in Medicaid systems. The study highlights challenges in AI ethics, operational barriers, and security concerns. By leveraging AI-powered decision-making and IoT-enabled smart healthcare frameworks, Medicaid optimization enhances accessibility, cost efficiency, and population health management. Future directions in AI-driven healthcare, including robotic automation, generative AI, and real-time predictive analytics, present opportunities to further streamline Medicaid operations and improve patient outcomes.
Keywords: Artificial Intelligence (AI), Data Analytics, Cloud Computing, Medicaid Optimization, Predictive Analytics, Blockchain Interoperability, Electronic Health Records (EHR), Federated Learning, IoT in Healthcare, AI Ethics, Healthcare Decision-Making, Machine Learning, Security Challenges, Population Health Management, AI-driven Automation.
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DOI:
10.17148/IJARCCE.2025.14319
