Performance Measurement in Health Systems: A SEA Model Reinterpretationof System Capacity, Saturation, and Collapse

Abstract

Performance measurement has long served as a central mechanism for evaluating health systems, primarily
through indicators of efficiency, quality, and access. However, existing frameworks provide limited insight into how health systems approach structural limits, experience saturation, or transition toward collapse.
This study aims to reinterpret health system performance measurement by examining its ability to capture system capacity, saturation dynamics, and collapse risk through the Stability–Efficiency–Adaptability (SEA) model. To achieve this, a conceptual–analytical approach was adopted, building on a comparative review of 32 performance evaluation and excellence models. The models were systematically analyzed to identify their coverage of key performance domains and subsequently reclassified within the SEA framework to assess imbalances across stability, efficiency, and adaptability dimensions. The findings indicate that dominant performance models disproportionately emphasize efficiency and
process optimization while underrepresenting adaptive capacity and systemic stability. These structural imbalances obscure early warning signals of system saturation, including declining responsiveness,
workforce strain, and policy rigidity. From a SEA perspective, such imbalances contribute to cumulative systemic stress, increasing the likelihood of saturation and eventual collapse. This study contributes a novel reinterpretation of performance measurement by linking model-level gaps to system-level dynamics of saturation and collapse, offering a structured analytical lens for identifying hidden vulnerabilities in health
systems.