THE IMPORTANCE OF UTILIZING BIG DATA ANALYTICS IN U.S. HEALTHCARE SUPPLY CHAIN MANAGEMENT

This study investigates the importance of utilizing Big Data Analytics (BDA) in U.S. Healthcare Supply Chain Management (HCSCM) to enhance operational efficiency, decision-making, and resource management. A literature review was conducted, analyzing 15 studies that explored the application of BDA in supply chain management, providing insights into research methods, data collection techniques, and the effectiveness of BDA in healthcare. The findings revealed that there is an increasing trend in the use of Big Data Analytics (BDA) in Supply Chain Management (SCM), particularly in the healthcare sector. The study identified several key enablers: Effective technological infrastructure, such as high-speed internet and cloud-based platforms is identified to be essential for storing and processing large volumes of healthcare data. The study also highlighted the importance of a skilled workforce, particularly data scientists and healthcare logistics professionals, to manage and analyze data effectively. Leadership support, adequate financial resources, and compliance with regulatory requirements were also key enablers found in the study. However, significant challenges were identified, including concerns over data privacy and security under HIPAA regulations, inconsistent data quality across systems, high implementation costs, and organizational resistance to change. These challenges hinder the optimal utilization of BDA in healthcare supply chains. In conclusion, the study emphasizes the transformative potential of BDA in improving healthcare supply chain management by enhancing decision-making, efficiency, and resource optimization. However, overcoming barriers such as data privacy concerns, high costs, and workforce resistance is important to fully leverage the benefits of BDA in SCM. Effective technological integration, leadership support, and investment in skilled personnel are essential for successful implementation and achieving improved operational outcomes in healthcare supply chains. KEYWORDS: Big Data Analytics, Healthcare Supply Chain, Predictive Analytics, Resource Optimization, Real-Time Monitoring, Logistics Optimization