Abstract

This systematic review explores the role of Business Intelligence and Analytics (BI&A) in healthcare, focusing on its applications, benefits, and challenges. Using the PRISMA framework, a total of 52 peer-reviewed studies published between 2010 and 2023 were analyzed to identify key BI&A tools, such as Clinical Decision Support Systems (CDSS), predictive analytics, and data visualization platforms, and their impact on healthcare outcomes. The findings show that BI&A significantly enhances clinical decision-making, improves patient outcomes, and optimizes operational efficiency, with 19 studies highlighting the effectiveness of CDSS and 16 studies demonstrating the value of predictive analytics in reducing patient readmissions and improving early disease detection. However, challenges such as data integration issues, privacy concerns, and resistance to technology adoption were evident across 25 studies, limiting the broader adoption of BI&A. The review also identifies gaps in the literature, particularly the need for more longitudinal studies and research on emerging technologies like artificial intelligence (AI) and machine learning (ML). Future research should focus on addressing these challenges to fully unlock the potential of BI&A in healthcare.

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