(untitled) (Contemporary Mathematics, 2025)
Healthcare systems worldwide play a critical role in enhancing public health, ensuring economic equity, and meeting societal expectations. The Coronavirus Disease 2019 (COVID-19) pandemic posed unprecedented challenges, disrupting the recognition and treatment of non-COVID diseases and straining healthcare resources globally. This has underscored the need to evaluate government and healthcare system performance over multiple periods. In this context, Data Envelopment Analysis (DEA) emerges as a robust tool to provide a theoretical and scientific foundation for healthcare policymaking. However, healthcare performance data often involves uncertainties due to variability in socio-cultural conditions, death rates, and expert-driven estimations. This study introduces a novel, uncertain DEA model tailored for multi-period systems to address these challenges. The proposed model simultaneously evaluates overall system and periodspecific efficiencies, offering comprehensive insights into the dynamics of healthcare performance over time. The study also provides theoretical proofs to ensure the feasibility, boundedness, and deterministic transformation of the uncertain model. The decomposition of overall efficiency into period-specific components enables the identification of inefficiency sources, providing actionable insights for decision-makers to target process improvements. A sensitivity and stability analysis is conducted to assess the robustness of the proposed method under varying conditions. The model is applied to evaluate the healthcare efficiency of 30 countries during the COVID-19 pandemic across two distinct periods. Results reveal that the uncertain DEA model outperforms traditional deterministic approaches by offering greater discrimination in ranking healthcare units. Furthermore, the analysis highlights an improvement in efficiency for most countries during the second period, potentially attributed to increased preparedness and adaptability in handling the pandemic. This study contributes to the methodological advancements in DEA and provides valuable policy recommendations for enhancing healthcare system resilience in crisis scenarios.