Presenting a pragmatic model for evaluating the economic performance of hospitals in Iran based on multi-criteria decision-making

BACKGROUND: Evaluating the economic performance of hospitals is crucial for improving efficiency and aligning healthcare services with organizational missions. This study presents an operational model for assessing the economic performance of hospitals in Iran, based on a multi-criteria decision-making (MCDM) approach. METHODS: An expert panel was employed to evaluate and prioritize key economic performance indicators using the Analytic Hierarchy Process (AHP). Nine primary indicators and four criteria, including validity, alignment with hospital missions, adherence to national accreditation standards, and data availability, were used for prioritization. Pairwise comparison matrices were developed, and consistency ratios (CR) were calculated to ensure accuracy. The final model incorporates normalized scores of indicators to derive the overall economic performance of each hospital. RESULTS: The expert panel identified nine key indicators for assessing hospital economic performance. Among these, bed occupancy rate (weight = 0.219), bed turnover rate (0.167), and insurance claim rejection rate (0.141) received the highest priorities. Validity in measuring efficiency and economic performance was the most influential criterion (weight = 0.505), followed by alignment with hospital missions and objectives (0.331). The final weighted model highlights that improvements in bed utilization, patient flow, and insurance claim management have the greatest potential impact on hospitals' economic performance. Sensitivity analysis confirmed the robustness of the results, as changes in criterion weights did not substantially alter the ranking of the top indicators. CONCLUSION: The proposed model provides a reliable framework for assessing hospital economic performance in Iran. It highlights key performance indicators that align with organizational goals and economic efficiency. This model can aid hospital administrators in decision-making to improve financial sustainability.