Type-2 Neutrosophic Set with MCDM Methodology for Fire Safety Estimation in Healthcare Services

Fire safety represents a critical priority in healthcare facilities, where complex infrastructures and the vulnerability of patients present significant challenges to evacuation and emergency response. Traditional fire risk assessment methods often fall short in addressing the linguistic variability, uncertainty, inconsistency, and indeterminacy inherent in expert evaluations. While fuzzy and Neutrosophic approaches have been applied in broader healthcare decision-making contexts, no existing study has utilized Type-2 Neutrosophic Numbers Sets (T2NNs) for prioritizing hospital departments based on fire risk. To address this gap, this study introduces a novel multi-criteria decision-making (MCDM) framework that integrates T2NNs for expert modeling, the Entropy method for objective criteria weighting, and the Root Assessment Method (RAM) for robust alternative ranking. The proposed framework enables precise and sustainable prioritization of fire safety across hospital departments by effectively capturing expert judgment under uncertainty. It enhances early risk detection, supports targeted evacuation planning, and promotes long-term safety management. A real-world case study involving 25 hospital departments, and 12 fire safety criteria validates the framework’s practical relevance. To assess the robustness of the proposed model, a structured sensitivity analysis was conducted by systematically varying the criteria weights across 13 scenarios, confirming the stability of the prioritization of hospital departments. By applying T2NNs to hospital fire safety for the first time, this research provides a scalable and structured decision-support tool for healthcare stakeholders. The model also lays the groundwork for future enhancements, including the integration of more advanced Neutrosophic approaches to support staff preparedness and patient evacuation logistics.