Objective To address the challenges of multi-source heterogeneous data from ICU medical equipment in terms of structure, semantics, and standardization, this study explores a standardized modeling approach based on openEHR. The aim is to achieve unified management and efficient utilization of data, providing a solid data foundation for smart healthcare and evidence-based medicine.

Methods This research is grounded in the dual-layer modeling architecture of openEHR. We designed and constructed medical equipment data prototypes and templates tailored for the ICU context, enabling standardized semantic expression and unified encoding of multi-source heterogeneous data. Through multi-protocol standardization mapping, we achieved unified acquisition and parsing of device data from different vendors, protocols, and data structures. Furthermore, we established a data platform for ICU medical equipment, facilitating dynamic data collection, real-time standardization processing, and semantic unification.

Results In a practical application at a tertiary hospital's ICU, we completed the modeling of 98 prototypes for 8 types of devices (including ventilators and patient monitors) and encapsulated 8 clinical scenario templates. The efficiency of device data integration was significantly improved. The time required for preparing clinical research data was reduced from an average of 4.2 hours to 0.5 hours.

Conclusion The standardized modeling method based on openEHR effectively addresses the heterogeneity issues of ICU medical equipment data. Its open model-driven architecture supports cross-device interoperability and long-term evolution, providing high-quality data foundations. This approach optimizes clinical decision-making processes and enhances data management efficiency, offering a systematic solution for the effective integration and semantic governance of multi-source heterogeneous data.