Kesici, BüşraDuzdar, Irem2025-10-112025-10-11202597983693443479798369344330https://doi.org/10.4018/979-8-3693-4433-0.ch010https://hdl.handle.net/20.500.12684/21405One of the important sectors that need to keep up with digital transformation quickly is healthcare. Given its direct impact on human lives, it is crucial to conduct studies to improve service quality in this sector. Considering the effects of the lean management approach in the healthcare sector on digital transformation in the supply chain is the first important research question for this study. Another research question is the contribution of artificial intelligence (AI) and machine learning (ML) approaches developed in recent years to digital transformation in the healthcare sector. The necessity of digital transformation tools, including artificial intelligence and machine learning, in healthcare services and the challenges faced during their implementation were identified as criteria and a weighting analysis was conducted with the help of multi-criteria decision-making (MCDM) analysis. Step-Wise Weight Assessment Ratio Analysis (SWARA) was used to determine the importance weights of the evaluation criteria. Strategies were defined with Enterprise Resource Planning (ERP) as a solution to the important weights of the challenges. The aim is to reduce costs while increasing supply chain efficiency and effectiveness by identifying practices and strategies that incorporate expert feedback from the industry. © 2025 Elsevier B.V., All rights reserved.en10.4018/979-8-3693-4433-0.ch010info:eu-repo/semantics/closedAccessContrastive LearningDecision MakingHuman Resource ManagementLean ProductionResource AllocationArtificial Intelligence LearningDigital TransformationDirect ImpactHealthcare SectorsHuman LivesLean ManagementMachine Learning ApproachesMachine-learningResearch QuestionsService QualityEnterprise Resource PlanningLean Digital Transformation in Health Supply Chain: Identifying Barriers to Machine Learning and AI Applications and Strategies to OvercomeBook Part2392692-s2.0-105006952861N/A