<![CDATA[This paper provides a systematic literature review of hospital supply chain management (SCM), emphasizing variations across hospital types, methodological frameworks, the SCOR model, and technological advancements. Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, the study systematically identifies, screens, and synthesizes relevant research to ensure comprehensive and high-quality data. The article selection process was done through a multiple screening procedure by four researchers, who collaboratively assessed data quality and relevance to the research topic. Individual researchers then further evaluated each identified article to avoid bias and ensure objectivity in the selection process. It highlights unique SCM challenges public and private hospitals face, particularly in resource allocation and technology adoption. Constrained by budget limitations, public hospitals often depend on collaborations and streamlined processes to ensure essential supplies. In contrast, private hospitals leverage technological tools such as AI, IoT, and blockchain for real-time data analysis and efficiency gains. Key SCM methodologies reviewed include Deep Reinforcement Learning, Multi-Criteria Decision-Making frameworks, and simulation modeling, each offering diverse benefits in cost management, inventory control, and decision support. The SCOR frameworkâs applicability to hospitals is also discussed, emphasizing areas for process optimization and patient care improvements. The study concludes with insights into strategic SCM practices that support operational resilience, efficiency, and patient outcomes across hospital types, urging future research on scalable, technology-driven SCM solutions for healthcare institutions.]]>
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