Unlocking the Potential of Big Data Analytics for Enhanced Healthcare Decision-Making: A Comprehensive Review of Applications and Challenges

Abstract

Background: The healthcare sector is grappling with enormous volumes of data, from Electronic Health Records to real-time monitoring from wearables. Big data analytics has the potential to revolutionize healthcare by improving patient outcomes and operational efficiencies. However, the technology also poses challenges, such as data privacy concerns and a lack of skilled professionals, which inhibit its full-scale implementation.

Methods: This study employs a literature review methodology, synthesizing findings from peer-reviewed articles, whitepapers, and case studies published over the last decade. The review aims to identify key applications and challenges of big data analytics in healthcare.

Results: The analysis reveals promising applications in areas like predictive modeling and personalized medicine. However, challenges like data privacy and integration complexities remain significant hurdles. Additionally, there's a skills gap in the workforce that needs to be addressed to facilitate implementation.

Conclusion: Big data analytics offers substantial benefits in healthcare, from improved patient care to cost reduction. However, to fully realize these benefits, challenges like data privacy, data integration, and the skill gap must be overcome. Future research should focus on developing secure frameworks for data integration and training programs to equip professionals with interdisciplinary skills.