The increasing digitalization of healthcare has led to the generation of vast volumes of health-related data from electronic health records, medical devices, administrative systems, and patient-generated sources. Big data analytics has emerged as a powerful tool for transforming healthcare system management by enabling data-driven decision-making and strategic planning. The objective of this study is to examine the role of big data analytics in improving healthcare system management and service delivery. A descriptive and analytical approach was used to assess the application of big data tools in areas such as resource allocation, population health management, quality improvement, and cost control. The analysis demonstrates that big data analytics enhances operational efficiency by identifying patterns, predicting demand, and optimizing workforce and infrastructure utilization. It supports proactive management of public health risks, improves clinical outcomes through predictive modeling, and strengthens performance monitoring across healthcare organizations. Additionally, data-driven insights enable healthcare managers to design targeted interventions, reduce inefficiencies, and improve patient safety and quality of care. From a system-level perspective, big data analytics contributes to improved transparency, accountability, and evidence-based policymaking. However, challenges such as data quality issues, interoperability limitations, data privacy concerns, and the need for skilled personnel remain significant barriers to effective implementation. In conclusion, big data analytics plays a crucial role in modern healthcare system management by transforming raw data into actionable insights. Successful integration requires robust data governance frameworks, advanced technological infrastructure, and workforce capacity building. When effectively implemented, big data analytics can enhance efficiency, sustainability, and responsiveness of healthcare systems in an increasingly complex digital healthcare environment.

Big Data Analytics, Healthcare System Management, Digital Health, Data-driven Decision-making, Health Information Systems, Healthcare Quality