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AI in Healthcare Supply Chain Management: Enhancing Efficiency and Reducing Costs with Predictive Analytics

Author

Listed:
  • Fardin Sabahat Khan

    (MS in Business Analytics and Information Management, University of Delaware, USA)

  • Abdullah Al Masum

    (MS Information Technology, Westcliff University, USA)

  • Jamaldeen Adam

    (MS in Business Analytics and Information Management, University of Delaware, USA)

  • Md Rashidul Karim

    (MBA in Business Analytics at Wilmington University, USA)

  • Sadia Afrin

    (MS in Computer Science, University of Texas at San Antonio, San Antonio, USA)

Abstract

This paper explores the transformative role of artificial intelligence (AI) and predictive analytics in enhancing operational efficiency within healthcare supply chains. By leveraging AI-driven business analytics, healthcare organizations can optimize inventory management, improve demand forecasting, and streamline supply chain processes. The study presents a comprehensive review of recent advancements, challenges, and opportunities in the integration of AI technologies, focusing on their application in various healthcare contexts. Through systematic analysis of existing literature, the findings emphasize the significance of adopting AI and predictive analytics for effective decision-making, cost reduction, and improved service delivery in healthcare. The research highlights the need for organizations to embrace digital transformation and foster a collaborative approach in the implementation of AI-driven solutions to enhance overall supply chain resilience.

Suggested Citation

  • Fardin Sabahat Khan & Abdullah Al Masum & Jamaldeen Adam & Md Rashidul Karim & Sadia Afrin, 2024. "AI in Healthcare Supply Chain Management: Enhancing Efficiency and Reducing Costs with Predictive Analytics," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 6(5), pages 85-93, October.
    • Handle: RePEc:alk:jcsts0:v:6:y:2024:i:5:id:8265
    DOI: 10.32996/jcsts.2024.6.5.8
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