An Early Warning Framework for Healthcare System Collapse

Abstract

Healthcare systems are increasingly exposed to sustained internal pressures that extend beyond episodic shocks. While resilience has been widely studied, the concept of healthcare system collapse remains weakly theorized and rarely operationalized, particularly in relation to saturation and adaptive capacity loss.

 This study aims to explore healthcare system collapse as a saturation-driven process using the Stability–Efficiency–Adaptability (SEA) framework and to identify key determinants and early warning key performance indicators (KPIs).

 A qualitative exploratory design was employed, integrating semi-structured interviews with 12 experts from health policy, academia, and health information systems, alongside a targeted review of international literature. A common interview guide covering seven thematic domains was used for all participants. Data were analyzed thematically and mapped onto the SEA framework to redefine collapse factors and develop SEA-aligned KPIs.

Result shows that Seven core determinants of healthcare system collapse were identified. Stability and efficiency related factors were found to create cumulative stress and saturation conditions, while loss of adaptability emerged as an integrative system-level outcome. Based on these findings, a structured set of KPIs was developed across the Stability, Efficiency, and Adaptability dimensions, with adaptability indicators capturing early warning signals of impending collapse. Healthcare system collapse is best understood as a progressive outcome of sustained imbalance within the SEA framework, driven by saturation and culminating in loss of adaptability. The proposed SEA-aligned KPIs provide a theoretically grounded approach for early detection of collapse-prone conditions and support anticipatory health system governance.