Data Analytics in U.S. Public Health Policy: A Review of Applications in Healthcare Resource Allocation and Efficiency

This review explores the critical role of data analytics in shaping U.S. public health policy, with a focus on healthcare resource allocation and efficiency. It examines the historical context and current applications of data-driven approaches in optimizing the distribution of medical resources, such as hospitals, staff, and supplies, particularly during public health crises like the COVID-19 pandemic. The paper also highlights how predictive analytics improves preparedness by anticipating future healthcare needs. Additionally, the review discusses how big data streamlines healthcare processes, reduces inefficiencies, and enhances patient outcomes through data-driven decision-making. Key stakeholders—including government agencies, healthcare institutions, and data scientists—are identified for their contributions to the field. The paper concludes with recommendations for policymakers on improving data infrastructure, training, and ethical frameworks to maximize the potential of data analytics in public health.