Prioritization of health distributed ledger technology use cases using fuzzy sine trigonometric based decision-making model

The transformative potential of Distributed Ledger Technology (DLT), particularly blockchain, is increasingly recognized in the healthcare sector for its ability to enhance security, transparency, and operational efficiency. This study introduces a novel decision-making framework, the fuzzy Sine Trigonometric COmplex PRo-portional ASsessment (fuzzy ST-COPRAS) model, to prioritize health DLT applications amidst the inherent complexity and uncertainty of healthcare data. The prioritization process is based on a comprehensive evaluation of multi-disciplinary criteria, including economic viability, technological maturity, cybersecurity, and other critical factors. The ranking and prioritization of selected health DLT use cases-such as electronic health records (EHR) management, clinical trial oversight, pharmaceutical supply chain tracking, and telemedicine-are performed using the proposed algorithm, which incorporates tailored survey methods applied to experts in the field. The outcomes of this study are particularly valuable for standardization bodies, companies aiming to invest in DLT for healthcare, and governmental authorities seeking to allocate efficient support mechanisms and develop informed strategies. By identifying high-impact use cases, the findings provide actionable insights that facilitate strategic implementation, resource allocation, and policy development. Furthermore, the study highlights the alignment of blockchain-based solutions with regulatory requirements and techno-economic considerations, fostering trust and compliance. Overall, this research underscores the potential of DLT to revolutionize healthcare through secure, transparent, and efficient systems, driving significant advancements in patient care and system optimization.