Abstract
Background
Improving efficiency in the Ethiopian health sector is a national priority, particularly in light of declining external resources and the push toward Universal Health Coverage (UHC). Secondary-level hospitals, each expected to serve between one and 1.5 million people, represent a critical tier of the health system, yet no prior efficiency analysis had been conducted at this level.
Objective
This study aimed to estimate the technical and scale efficiency of secondary-level hospitals in Ethiopia and to quantify potential input savings achievable without compromising current service output levels.
Methods
A facility-based, retrospective costing study was conducted across a nationally representative sample of 12 secondary hospitals. Costs were measured using an ingredient-based micro-costing approach. Data Envelopment Analysis (DEA) was applied using input-oriented models under both Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) assumptions. Inputs included human resources, drugs and medical supplies, depreciated equipment, and indirect costs. Outputs were expressed as outpatient equivalent visits using department-specific conversion factors.
Results
Only 2 of the 12 hospitals (17%) were technically efficient. The mean technical efficiency score (VRS) was 0.66, implying that inefficient hospitals could, on average, reduce inputs by 34% without reducing outputs. The average scale efficiency was 0.15, indicating potential to increase outputs by approximately 85% within existing capacity. Total potential cost savings across the 10 inefficient hospitals amounted to approximately 192.5 million Ethiopian Birr (ETB), with human resources and medical supplies accounting for more than half of this figure.
Conclusions
The majority of Ethiopian secondary hospitals are technically and scale inefficient. Targeted interventions in human resource management and medical supply utilization, combined with strategies to increase service utilization, can yield significant efficiency gains. These findings have direct relevance for evidence-based resource allocation and health financing policy.