Weighted technical and scale efficiency of Greek public general hospitals grouped by bed capacity: a DEA analysis (2019–2023)

Purpose This study examines the weighted technical efficiency and scale efficiency of Greek public general hospitals within the National Health System during the period 2019–2023, grouping hospitals by capacity size (small ≤ 200 beds, medium 201–400 beds, large ≥ 401 beds). The analysis investigates efficiency differentials across hospital size categories and the evolution of operational performance before and after the COVID-19 pandemic in a context of sustained fiscal pressure on public health systems. Design/methodology/approach Efficiency is assessed using Data Envelopment Analysis (DEA), applying Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) models. Indicators of technical efficiency, pure technical efficiency and scale efficiency (SE = CRS/VRS) are estimated using the MaxDEA Lite software. Weighted annual efficiency scores are calculated by hospital size group, enabling consistent intertemporal comparisons and a clearer interpretation of structural performance differences across hospital categories. Findings The results reveal variations in technical and scale efficiency across hospital size groups and differences in operational performance during the study period. Overall, efficiency shows a gradual post-pandemic improvement, indicating enhanced managerial adaptability and more effective resource utilisation, although structural differences between hospital size categories remain evident. Research limitations/implications The study is subject to certain limitations. First, the analysis relies on administrative input–output data and does not incorporate indicators of quality of care, case severity, or clinical outcomes. Second, the results may be influenced by the exceptional conditions of the COVID-19 pandemic, which affected hospital operations and demand patterns. Third, spatial and demographic factors are not explicitly captured in the model, potentially affecting efficiency estimates. Future research could incorporate quality indicators, extend the analysis to other contexts, and apply complementary methodologies for a more comprehensive evaluation. Practical implications The findings provide actionable insights for policymakers and hospital administrators by highlighting the need for differentiated strategies based on hospital size and scale efficiency. Large hospitals operating under decreasing returns to scale may benefit from service reorganization and improved internal coordination, while smaller and medium-sized hospitals require targeted investments in infrastructure and human resources. The results also support the adoption of performance monitoring systems, benchmarking practices, and digital health technologies to enhance efficiency, transparency, and long-term sustainability within the Greek public health system. Social implications The findings highlight disparities in efficiency across hospital size groups, particularly affecting smaller and remote hospitals, which may affect equitable access to healthcare services. Strengthening these units through targeted support and collaborative arrangements can help reduce regional inequalities and improve service availability. Enhancing operational efficiency and resource allocation contributes to better quality of care and supports the long-term sustainability of the public health system. Originality/value The study provides empirical evidence on hospital efficiency in Greece and demonstrates the usefulness of weighted DEA for analysing heterogeneous hospital systems. The findings support targeted resource allocation, strengthened collaboration among hospital units and the development of benchmarking mechanisms to improve operational efficiency and long-term system sustainability.