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

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-31
DOI
https://doi.org/10.5281/zenodo.17310169
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

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

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
SVT Associates (United States) (US)
Openalex Percentile: Top 52%
Artificial Intelligence in Healthcare and Education
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AI-orchestrated workflow automation in cloud-based hospital information systems: Enhancing efficiency and patient outcomes · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS