Applied Sciences
| Open Access |
DOI: Data-Driven Healthcare: The Role of Business Intelligence Tools in Optimizing Clinical and Operational Performance
Mahzabin Binte Rahman , Master of Science in Business Analytics, Trine University, Detroit, Michigan, USA Maham Saeed , Master of Science in Healthcare Management, St. FRANCIS COLLEGE, Brooklyn, New York Kami Yangzen Lama , Department of Information Technology, Washington University of Science and Technology (wust), 2900 Eisenhower Ave, Alexandria, VA 22314, USA Keya Karabi Roy , Master of Science in Healthcare Management, St. FRANCIS COLLEGE, Brooklyn, New YorkAbstract
With the rise of the digital transformation era, healthcare organizations are getting more inclined toward using Business Intelligence (BI) tools as a means of improving clinical outcomes and operational efficiency. This article explores the diverse nature of BI in the healthcare system in the optimization of data-driven decisions. Through secondary data analysis (mixed-method approach with the empirical case studies), the research focuses on the ways of implementing the BI tools (dashboards, predictive analytics platforms, and real-time reporting systems) to enhance clinical diagnostics, workflow efficiency, and operational cost-reduction. The study notes the application of BI to Electronic Medical Records (EMRs), hospital performance dashboards, and administrative systems to deliver actionable insights by analysing huge, disparate data sources. Results of recent large-scale studies show that BI implementation may help shorten patient wait time by as much as 35 percent, reduce hospital readmission rates by 20 percent and help optimize staff use by 25 percent, Friends, leading to enhanced patient satisfaction and reduced costs. Besides, the comparative examination illustrates that, owing to the resourcefulness, the adoption of BI in the private sector hospitals is nimbler than that of the governmental counterparts. Also, the essential obstacles recognized in the study include data silos, change resistance, and interoperability. The paper is able to contribute to the developing literature because it is able to synthesize the real-world applications and evaluate their practical effects on care delivery. The results point towards the importance of strategic BI investments and strong data governance models. Healthcare organizations can take a step forward to transparent, informed, and value-based care by fixing these problems. The study does not only address a major gap but also provides a valuable guide on how BI can be integrated in the future in healthcare environments worldwide.
Keywords
Business Intelligence, Healthcare Analytics, Clinical Performance, Operational Efficiency, Data-Driven Decision-Making
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