Real-Time Clinical Decision Support: Enhancing BI with Smart Analytics

Satya Manesh Veerapaneni

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 2, 1969-1982

Abstract: The integration of Business Intelligence with Clinical Decision Support Systems represents a transformative development in healthcare delivery, shifting from retrospective analysis to real-time decision making at the point of care. This technological evolution bridges critical temporal gaps between data collection and clinical intervention, enabling healthcare professionals to access actionable insights when they matter most. Advanced implementations demonstrate significant improvements across various clinical domains, including early sepsis detection, medication interaction tracking, and hospital readmission risk stratification. Despite promising outcomes, healthcare organizations face substantial implementation challenges, including alert fatigue, clinical accuracy concerns, workflow integration complexities, and data latency issues. Successful implementation strategies emphasize user-centered dashboard design, workflow-embedded analytics, adaptive learning systems, and approaches that augment rather than replace clinical expertise. As these technologies mature, future applications will likely include advanced predictive modeling for disease progression, increasingly personalized treatment recommendations, and integration with genomic information to enable precision medicine approaches that fundamentally transform healthcare delivery.

Keywords: Artificial Intelligence; Clinical Workflow; Decision Support; Predictive Analytics; Real-Time Analytics (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT23112557
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i2:id:1256

DOI: 10.32628/CSEIT23112557

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