AI-Enhanced Hospital Information Systems: A Comprehensive Analysis of Patient Care Improvements Across Global Healthcare Settings

Abstract

Artificial Intelligence (AI) integrated with Hospital Information Systems (HIS) offers a transformative pathway to improved patient outcomes, efficiency, and cost reduction. This study analyzes the implementation of AI and HIS in 108 hospitals globally to measure enhancements in patient care and system performance. Data was collected from diverse healthcare settings across North America, Europe, Asia, and developing regions. Results indicate a substantial improvement in patient safety, with mortality rates reduced by <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{7}-\mathbf{2 2 \%}$</tex> and diagnostic accuracy increasing by <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$15-30 \%$</tex>. Operational efficiency improved by <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$20-40 \%$</tex>, and economic analysis projects a strong ROI, with AI-powered radiology systems potentially yielding 451 % returns over five years. We identified seven major application fields, including predictive analytics and clinical decision support. Success depends on leadership, stakeholder engagement, and robust data infrastructure. This study provides practical guidelines for organizations integrating AI into HIS.

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