• Ms. Nisha Prasad
• Mr. Parimal Chaudhary

The integration of artificial intelligence (AI) with remote patient monitoring (RPM) represents a paradigmatic shift from reactive to predictive healthcare delivery. As healthcare systems face mounting pressures from aging populations and rising chronic disease prevalence, AI-powered remote patient care emerges as a transformative solution enabling continuous health monitoring with actionable clinical insights. This analysis examines applications, benefits, challenges, and future directions of AI-enhanced remote patient monitoring systems, evaluating their impact on patient outcomes, healthcare costs, and care accessibility. A systematic review of peer-reviewed literature, industry reports, and real-world case studies was conducted, analyzing AI applications in remote patient care across multiple healthcare domains. Evidence was synthesized from successful implementations, comparative outcome studies, and regulatory frameworks. AI-enhanced remote patient monitoring demonstrates significant clinical and economic benefits, with studies showing up to 76% reductions in hospital readmissions for heart failure patients and diagnostic accuracy exceeding 93% through machine learning algorithms. Key applications include predictive analytics for early health deterioration detection, AI-driven diagnostics and triage, personalized treatment optimization, and chronic disease management. Real-world implementations report substantial cost savings, with healthcare systems achieving $2.5-5 million annually through reduced readmissions and operational efficiencies. Patient engagement improvements of 42-49% and clinical reporting time reductions of 35% demonstrate system effectiveness. AI-powered remote patient monitoring offers transformative potential for healthcare delivery, enabling proactive, personalized care that improves outcomes while reducing costs. Successful implementation requires addressing technical integration challenges, ethical considerations including algorithmic bias and privacy protection, and evolving regulatory frameworks. Future directions include integration with IoT ecosystems, 5G networks, and digital twin technologies. Sustained investment in infrastructure, workforce development, and collaborative policy frameworks is essential for realizing AI-enhanced remote patient care's full potential in creating resilient, equitable healthcare systems.

Artificial intelligence, remote patient monitoring, telemedicine, predictive analytics, healthcare outcomes, digital health, machine learning, chronic disease management

"AI-Enhanced Remote Patient Monitoring: Transforming Healthcare Delivery Through Predictive Analytics and Smart Technology", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 10, page no.a61-a76, October-2025, Available :http://www.jetir.org/papers/JETIR2510009.pdf

"AI-Enhanced Remote Patient Monitoring: Transforming Healthcare Delivery Through Predictive Analytics and Smart Technology", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 10, page no. ppa61-a76, October-2025, Available at : http://www.jetir.org/papers/JETIR2510009.pdf