Risk Stratification in Emergency Care: PFS-TOPSIS Hybrid Model

This study presents a multi-criteria approach to prioritizing patients in emergency departments, integrating the PFWA operator with the PFS-TOPSIS framework. Using Picture Fuzzy Sets, this model classifies patients' conditions, overcoming limitations of traditional triage systems with a data-driven assessment. Applied to simulated data, the model prioritizes patients based on critical vital signs, such as respiratory rate and oxygen saturation, aligning closely with clinical expectations for risk stratification. The results indicate that this approach may have an impact  on patient outcomes by improving the accuracy and consistency of triage decisions in emergency settings. Future research should focus on validating this approach with real data and investigating its applicability in different healthcare settings, ultimately influencing patient flow, resource allocation, and quality of care in high-demand settings.