LEVERAGING PREDICTIVE ANALYTICS IN BIG DATA FOR HEALTHCARE INNOVATION

Abstract

The increasing digitization of healthcare has ushered in a new era of data-driven innovation, where vast amounts of clinical, operational, and patient-generated data can be leveraged to improve health outcomes and optimize care delivery. This article explores the transformative role of big data and predictive analytics in modern healthcare systems. It begins by examining the foundations of big data in healthcare, including data sources, characteristics, and integration challenges. The discussion then shifts to predictive analytics methodologies and models that enable early disease detection, risk stratification, resource optimization, and personalized treatment planning. Real-world applications and case studies are presented to highlight the tangible impact of these technologies on patient care and system efficiency. The article also addresses key barriers to adoption like data privacy, interoperability, and ethical concerns, and offers insights into emerging solutions and future directions. Ultimately, the paper underscores the potential of big data and predictive analytics to reshape healthcare delivery into a more proactive, personalized, and value-based model