Operational Efficiency of Clinical Departments in a Tertiary Grade A Hospital: A Super-Efficiency SBM-Tobit Model Analysis

Objective This study aims to scientifically assess the operational efficiency of 40 clinical departments in a Grade-A tertiary hospital in Foshan during 2024, with a focus on how resource allocation and service delivery align with the goals of equitable, high-quality healthcare under the Diagnosis-Related Groups (DRG) payment system. Methods We developed a department-level efficiency evaluation framework using a super-efficiency Slack-Based Measure (SBM) model that explicitly accounts for undesirable outputs—such as prolonged hospital stays—within the DRG context. This approach reflects public health concerns about balancing efficiency with care quality. A Tobit censored regression model was then applied to identify the marginal effects of key input and output indicators on departmental efficiency. Results The mean overall technical efficiency (OTE) across departments was 0.85, with pure technical efficiency (PTE) at 0.94 and scale efficiency (SE) at 0.92, indicating room for improvement in resource utilization and service organization. Pediatric Surgery (PTE = 2.21), Oral and Maxillofacial Surgery (PTE = 1.64), and Neonatology (PTE = 1.61) demonstrated the highest levels of technical efficiency. Tobit regression revealed that higher numbers of nurses ( P  = 0.02), greater bed capacity ( P  < 0.001), and longer average length of stay ( P  = 0.03) were significantly associated with lower operational efficiency—suggesting potential inefficiencies in input scaling. Conversely, total DRG weight ( P  < 0.001), Case Mix Index ( P  < 0.001), and annual outpatient visits ( P  = 0.03) showed significant positive associations with efficiency, reflecting stronger service complexity and population reach. Conclusions By integrating efficiency measurement with driver analysis, this study proposes a closed-loop framework “efficiency assessment - determinant identification - targeted optimization” that provides actionable insights for hospital administrators and health policymakers. The findings underscore the need to move beyond input expansion toward smarter, more responsive resource deployment, thereby supporting the transition to intensive, equitable, and sustainable healthcare delivery under China’s DRG-based reform agenda.