The role of artificial intelligence and machine learning in optimizing U.S. healthcare supply chain management
1 Whitman School of Management, Syracuse University, USA.
2 Fordham University, New York, USA.
3 C.T. Bauer College of Business, University of Houston, USA.
4 Klerconsult, El Paso, TX, USA.
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(02), 1996–2002
Publication history:
Received on 29 September 2024; revised on 09 November 2024; accepted on 11 November 2024
Abstract:
This paper aims to review the role of Artificial Intelligence and Machine Learning in managing the healthcare supply chain in the United States. Healthcare supply chains face several challenges such as fragmentation, lack of real-time visibility, and inventory management issues. However, there are solutions with the help of AI and machine learning, including the availability of predictive analytics to improve demand forecasting, optimization algorithms for inventory and logistics, and automated quality control. Application areas demand forecasting, supplier selection, logistics optimization, quality control, and real-time tracking. The applications of AI in healthcare supply chains have the potential to improve the healthcare supply chain in terms of reduced costs, increased efficiency, optimized decision-making, and better patient outcomes. However, the implementation experience has shown several challenges such as data quality, privacy concerns, regulatory compliance, and workforce adaptation within organizations. Successful implementations in various health organizations in the US give valuable insights into how AI could be well implemented. The future presents several opportunities for supply chain optimization with the rise of blockchain and Internet of Things (IoT) integration. For healthcare supply chains to adopt AI, organizations should have specific AI plans, start with pilot projects in high-impact areas, invest in data infrastructure, and ensure strong leadership support. As AI becomes increasingly critical for competitive advantage, it has the potential to create more resilient, efficient, and patient-centric supply chains in the US healthcare system.
Keywords:
Healthcare Supply Chain; Artificial Intelligence; Machine Learning; Predictive Analysis; Inventory optimizatio
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