An interval type-2 fuzzy multi-criteria decision-making approach for patient bed allocation.

Effective inpatient bed management is critical for optimizing healthcare resource utilization and ensuring high-quality patient care. The growing imbalance between bed capacity and patient demand underscores the need for robust, patient-centered prioritization frameworks. However, existing approaches often neglect patient-specific characteristics, interdependencies among criteria, and uncertainty inherent in decision-making processes. To address these challenges, this study proposes a hybrid multi-criteria decision-making framework that integrates interval type-2 fuzzy sets, the DEMATEL method, and the VIKOR method. Interval type-2 fuzzy sets are used to manage linguistic uncertainty; DEMATEL identifies causal relationships among evaluation criteria; and the 2-tuple linguistic VIKOR method enables comprehensive ranking of patient admission alternatives by balancing clinical urgency, operational efficiency, and fairness. Empirical analysis demonstrates that medical urgency, diagnosis type priority and wait time are the most influential criteria, emphasizing their critical role in patient prioritization. The proposed framework effectively models interdependencies and provides transparent, structured rankings, offering a robust tool for equitable and efficient resource allocation in capacity-constrained healthcare settings. This study contributes to healthcare operations research by delivering a flexible and interpretable method for improving patient admission decision-making.