Assessment and Prioritization of AI-Enhanced Blockchain Factors in Healthcare Supply Chains: A Hybrid Multi-Criteria Decision-Making Approach

The convergence of artificial intelligence (AI) and blockchain technologies holds the potential to revolutionize healthcare supply chains by enhancing data security, operational transparency, and service quality. Blockchain offers a decentralized and secure infrastructure, while AI excels at analyzing complex datasets to uncover insights and predict treatment outcomes. This study aims to evaluate and prioritize key factors influencing the integration of AI and blockchain within healthcare supply chains by employing a hybrid Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Decision-Making Trial and Evaluation Laboratory (F-DEMATEL) methodology. Through an extensive literature review, four main criteria and twentythree sub-criteria were identified. Initially, F-AHP was utilized to rank these factors based on expert evaluations. Subsequently, F-DEMATEL was applied to examine the interrelationships among the sub-criteria, distinguishing between causal and effect factors. Results indicated that "integration of treatment processes," "provision of fair services," "health monitoring," "medical data security," and "clinical decision support" emerged as the top priorities. Furthermore, "stakeholder participation" and "technology acceptance" were identified as key causal factors, while "monitoring the treatment process" and "patient-centered treatment strategies" were found to be critical effect factors. The findings highlight the transformative potential of AIblockchain integration in optimizing healthcare supply chain management.