AI-Powered RPM Data Platform for Nurse Time Optimization: Reducing Alert Fatigue and Enhancing Efficiency

Authors

  • Avani Nandini Indian Institute of Technology Kanpur, India

DOI:

https://doi.org/10.32996/jcsts.2025.7.2.22

Keywords:

Artificial Intelligence, Healthcare Workforce, Patient Monitoring, Remote Healthcare, Operational Efficiency, Clinical Efficiency

Abstract

This article explores the application of an AI-driven remote patient monitoring (RPM) data platform in optimizing nurse workflows and reducing alert fatigue. By integrating data from wearable devices and electronic health records, the platform utilizes artificial intelligence algorithms to filter and prioritize alerts, ensuring nurses focus on critical patient needs. The article demonstrates how this platform reduced false-positive alerts, enabling nurses to allocate more time to direct patient care and strategic decision-making. The article also emphasizes the platform's scalability and real-time monitoring capabilities, which support proactive interventions and improved patient outcomes while addressing workforce challenges in healthcare settings.

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Published

2025-04-23

Issue

Section

Research Article

How to Cite

Avani Nandini. (2025). AI-Powered RPM Data Platform for Nurse Time Optimization: Reducing Alert Fatigue and Enhancing Efficiency. Journal of Computer Science and Technology Studies, 7(2), 228-239. https://doi.org/10.32996/jcsts.2025.7.2.22