Data Analytics and Artificial Intelligence in Smart Healthcare Logistics: Building Resilient and Sustainable Systems
DOI:
https://doi.org/10.54536/ajdsai.v1i2.6024Keywords:
Artificial Intelligence, Data Analytics, Healthcare Logistics, Predictive Modeling, Smart Transportation, Sustainability, U.S. CompetitivenessAbstract
Healthcare logistics represents one of the most vital yet underappreciated fields for the utilization of artificial intelligence (AI) and data analytics. This paper proposes a conceptual framework that links AI-powered data analytics with healthcare logistics to accomplish three goals: efficiency, cost reduction, and sustainability. We assert that predictive analytics, geospatial data, and machine learning can enhance vehicle routing, optimize inventory management of medical supplies, and anticipate patient transportation needs. By analyzing existing research and industry practices, the study shows that AI is not just a technical tool but a strategic enabler that strengthens healthcare delivery and national competitiveness. Real-world examples from U.S. healthcare providers and transportation networks demonstrate how these tools are actively used to minimize waste, improve patient care, and decrease operational costs. The key contribution of this paper is to integrate AI-driven logistics applications into a structured conceptual model, providing both researchers and policymakers with a roadmap for resilient healthcare logistics.
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Copyright (c) 2025 Abdullah Sheikh, Tajbiha Mehonaj Rinvee
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