A Fuzzy Hybrid MCDM Approach for Assessing the Emergency Department Performance during the COVID-19 Outbreak

Area of Science:

• Healthcare Management
• Operations Research
• Public Health

Background:

• Emergency departments (EDs) are critical in healthcare systems, especially during the COVID-19 pandemic.
• Increased ED utilization has led to significant challenges, including overcrowding and long waiting times.
• Effective strategies are needed to enhance ED performance and patient flow.

Purpose of the Study:

• To develop and validate a hybrid fuzzy multicriteria decision-making (MCDM) model for evaluating emergency department performance.
• To identify key performance criteria and their interdependencies within EDs.
• To provide a framework for targeted interventions to improve ED operations.

Main Methods:

• Utilized a hybrid fuzzy MCDM approach combining Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) and Intuitionistic Fuzzy Decision Making Trial and Evaluation Laboratory (IF-DEMATEL).
• IF-AHP was used to determine the priorities of performance criteria under uncertainty.
• IF-DEMATEL analyzed the cause-and-effect relationships between criteria, followed by the Combined Compromise Solution (CoCoSo) for ranking EDs.

Main Results:

• Emergency Room (ER) facilities were identified as the most critical performance criterion (14.4%).
• Procedures and protocols demonstrated the highest positive D+R value (18.239), indicating a significant influence on ED performance.
• The model successfully ranked EDs and pinpointed weaknesses for improvement interventions.

Conclusions:

• The hybrid fuzzy MCDM model offers a robust method for assessing ED performance in complex, uncertain environments.
• Prioritizing ER facilities and optimizing procedures and protocols are crucial for enhancing ED efficiency.
• This approach supports data-driven decision-making for improving healthcare system resilience during pandemics.