Big Data Analytics for Population Health Management

Population Health Management (PHM) focuses on improving the health outcomes of a group by monitoring and identifying individual patients within that group. With the exponential growth of healthcare data from sources such as electronic health records (EHRs), wearable devices, insurance claims, and genomics, Big Data Analytics (BDA) has emerged as a transformative tool in PHM. This paper explores the role of big data in enabling proactive, predictive, and personalized healthcare. We review current literature and systems in place, examine methodologies for analyzing population-level data, and propose a data-driven framework for optimizing health outcomes, resource allocation, and early disease detection. Our approach integrates machine learning, cloud computing, and real-time analytics to address the challenges in population health management.