AIoT in Electronic Health Records and Hospital Management Enhancing Clinical Efficiency, Patient Safety, and Decision-Making

Published: 15 July 2025| Version 1 | DOI: 10.17632/c82t7wd3x2.1
Contributor:
Ahmed AYON

Description

This paper explores the transformative role of the Artificial Intelligence of Things (AIoT) in optimizing Electronic Health Records (EHR) and hospital management systems. By integrating smart IoT sensors with AI algorithms, hospitals can monitor patients in real time, predict clinical risks, and automate administrative tasks—all from a centralized EHR interface. This seamless integration leads to increased operational efficiency, reduced human error, and improved patient safety.

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The findings indicate that AIoT can move hospitals toward predictive, personalized, and precision healthcare, minimizing inefficiencies and maximizing care quality. However, the successful deployment of AIoT in healthcare also depends on secure data governance, clinician training, and robust interoperability standards. The paper concludes with a strategic blueprint for hospitals looking to implement AIoT-based solutions and emphasizes the future potential of federated learning, blockchain-based health records, and digital twin technologies in healthcare ecosystems.

Institutions

  • Independent University
  • North South University

Categories

Health Informatics, Hospital Administration, Internet of Things, Electronic Health Record, Real-Time Process Monitoring, Clinical Decision Support System, Predictive Modeling, Artificial Intelligence of Things

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