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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

AI-orchestrated workflow automation in cloud-based hospital information systems: Enhancing efficiency and patient outcomes

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  • AI-orchestrated workflow automation in cloud-based hospital information systems: Enhancing efficiency and patient outcomes

Venkateswara Reddi Cheruku *

SVIT Inc, USA.

Review Article

World Journal of Advanced Research and Reviews, 2025, 26(02), 1544-1554

Article DOI: 10.30574/wjarr.2025.26.2.1763

DOI url: https://doi.org/10.30574/wjarr.2025.26.2.1763

Received on 30 March 2025; revised on 09 May 2025; accepted on 11 May 2025

This technical article explores the integration of artificial intelligence technologies into enterprise-grade Hospital Information Systems and Electronic Medical Record platforms to automate clinical and administrative workflows. As healthcare organizations face increasing pressure to improve operational efficiency while enhancing patient care quality, AI-orchestrated workflow automation emerges as a transformative approach. The article examines the technical architecture, implementation challenges, and measurable benefits of these systems, highlighting successful deployments across various healthcare settings through detailed case studies. From intelligent triage to revenue cycle optimization, these AI-enabled systems demonstrate significant potential to reduce administrative burden, enhance clinical decision-making, and improve patient outcomes while addressing longstanding inefficiencies in healthcare delivery.

Artificial Intelligence; Cloud Computing; Healthcare Automation; Interoperability; Workflow Optimization

https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-1763.pdf

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Venkateswara Reddi Cheruku. AI-orchestrated workflow automation in cloud-based hospital information systems: Enhancing efficiency and patient outcomes. World Journal of Advanced Research and Reviews, 2025, 26(2), 1544-1554. Article DOI: https://doi.org/10.30574/wjarr.2025.26.2.1763

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


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