Real-Time Healthcare Analytics: How BI Architecture Supports Faster Decision-Making

The integration of real-time healthcare analytics through robust Business Intelligence architecture represents a transformative force in modern healthcare delivery, simultaneously accelerating clinical decision-making while raising important societal considerations. This article examines how advanced BI frameworks enable healthcare professionals to leverage instantaneous insights from electronic health records, connected medical devices, and predictive models to enhance diagnostic accuracy, optimize resource allocation, and improve patient outcomes. While these technological advancements promise greater healthcare accessibility and enhanced public health monitoring capabilities, they also necessitate careful navigation of ethical challenges, including data privacy concerns, algorithmic fairness, and equitable access across diverse populations. By exploring both the revolutionary benefits and potential pitfalls of real-time analytics implementation, this article provides a comprehensive analysis of how BI-driven healthcare solutions are reshaping society and outlines essential strategies to ensure these powerful tools serve all communities equitably while maintaining the highest standards of patient care and data stewardship.

Authors

Publication Details

Journal
European Journal of Computer Science and Information Technology
Published
2025-04-15
DOI
https://doi.org/10.37745/ejcsit.2013/vol13n123451
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Real-Time Healthcare Analytics: How BI Architecture Supports Faster Decision-Making

Srimurali Krishna Chillara
European Journal of Computer Science and Information Technology
Artificial Intelligence in Healthcare
article

Real-Time Healthcare Analytics: How BI Architecture Supports Faster Decision-Making

Srimurali Krishna Chillara
article en

Abstract

The integration of real-time healthcare analytics through robust Business Intelligence architecture represents a transformative force in modern healthcare delivery, simultaneously accelerating clinical decision-making while raising important societal considerations. This article examines how advanced BI frameworks enable healthcare professionals to leverage instantaneous insights from electronic health records, connected medical devices, and predictive models to enhance diagnostic accuracy, optimize resource allocation, and improve patient outcomes. While these technological advancements promise greater healthcare accessibility and enhanced public health monitoring capabilities, they also necessitate careful navigation of ethical challenges, including data privacy concerns, algorithmic fairness, and equitable access across diverse populations. By exploring both the revolutionary benefits and potential pitfalls of real-time analytics implementation, this article provides a comprehensive analysis of how BI-driven healthcare solutions are reshaping society and outlines essential strategies to ensure these powerful tools serve all communities equitably while maintaining the highest standards of patient care and data stewardship.

European Journal of Computer Science and Information TechnologyVol. 13(12)
Openalex Percentile: Top 89%
Artificial Intelligence in Healthcare
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.