Distributed healthcare systems: Challenges, architecture, and future directions

The rapid evolution of healthcare information technology has led to the emergence of three transformative technologies reshaping modern healthcare delivery: edge computing, artificial intelligence, and the Internet of Medical Things. Edge computing brings processing capabilities closer to healthcare data sources, enabling reduced latency, enhanced privacy protection, improved resilience during network disruptions, and optimized bandwidth usage for data-intensive applications. Artificial intelligence and machine learning applications span clinical decision support, predictive analytics, medical imaging analysis, and natural language processing, fundamentally altering diagnostic capabilities and treatment planning. Meanwhile, the Internet of Medical Things creates interconnected ecosystems of wearable sensors, implantable devices, and smart hospital equipment that enable continuous patient monitoring, create intelligent clinical environments, support remote disease management, and automate clinical documentation workflows. Together, these technologies are establishing new paradigms for distributed healthcare systems that enhance both clinical outcomes and operational efficiency.

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Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-04-16
DOI
https://doi.org/10.30574/wjarr.2025.26.1.1155
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

Distributed healthcare systems: Challenges, architecture, and future directions

Brahmanand Reddy Bhavanam
World Journal of Advanced Research and Reviews
IoT and Edge/Fog Computing
article

Distributed healthcare systems: Challenges, architecture, and future directions

Brahmanand Reddy Bhavanam
article en

Abstract

The rapid evolution of healthcare information technology has led to the emergence of three transformative technologies reshaping modern healthcare delivery: edge computing, artificial intelligence, and the Internet of Medical Things. Edge computing brings processing capabilities closer to healthcare data sources, enabling reduced latency, enhanced privacy protection, improved resilience during network disruptions, and optimized bandwidth usage for data-intensive applications. Artificial intelligence and machine learning applications span clinical decision support, predictive analytics, medical imaging analysis, and natural language processing, fundamentally altering diagnostic capabilities and treatment planning. Meanwhile, the Internet of Medical Things creates interconnected ecosystems of wearable sensors, implantable devices, and smart hospital equipment that enable continuous patient monitoring, create intelligent clinical environments, support remote disease management, and automate clinical documentation workflows. Together, these technologies are establishing new paradigms for distributed healthcare systems that enhance both clinical outcomes and operational efficiency.

World Journal of Advanced Research and ReviewsVol. 26(1)
Openalex Percentile: Top 93%
IoT and Edge/Fog Computing
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Distributed healthcare systems: Challenges, architecture, and future directions — Brahmanand Reddy Bhavanam · World Journal of Advanced Research and Reviews (2025) | TGRS Research Map | TGRS