A cross-layer risk governance model for digital healthcare safety

The digital transformation of healthcare, characterized by the widespread adoption of telemedicine, artificial intelligence (AI), electronic health records, and big data analytics, has introduced new safety challenges that are difficult to address through traditional patient safety models. Existing frameworks such as Reason’s Swiss Cheese Model remain valuable for explaining multilayered defense, but they provide limited guidance on how digital risks propagate across technical, organizational, and human subsystems. This study develops a mechanism-based cross-layer risk governance model for digital healthcare safety. The model explains how risks emerge from hardware, software, governance, and cultural layers, how they propagate across subsystems, and how adaptive feedback mechanisms support detection, response, and learning. To strengthen the operational logic of the model, the study further introduces a simplified simulation-based illustration of risk accumulation and feedback effects. The framework also identifies application pathways for telemedicine services, AI-assisted diagnostic platforms, electronic health record systems, and smart medical device networks. By linking risk propagation mechanisms with trigger conditions, responsible actors, measurable indicators, and implementation pathways, this study advances the Swiss Cheese Model from a static defense metaphor toward an adaptive governance model for digital healthcare safety.