Prehospital Triage Classification Using Regional Patient Data Models

The patent replaces traditional mechanical checklist-based triage systems with a computerized model that processes patient data. The system uses a trained classifier (such as random forest or neural network) to automatically determine triage categories, substituting human judgment and manual checklist evaluation with automated computational analysis, thereby improving accuracy while maintaining ease of operation through simple data input interfaces

The patent changes the parameters used for triage from simple checklist items to multiple patient attributes including vital signs, demographics, and injury characteristics. The computerized model analyzes these parameters in combination rather than using discrete checklist criteria, allowing for more nuanced and accurate triage decisions that reduce over-triage while maintaining operational simplicity

The patent creates a universal computerized triage system that can be applied across multiple geographic regions and trauma centers. The same trained model processes patient data consistently regardless of location, providing standardized accurate triage decisions. This multi-functional approach improves resource utilization efficiency by ensuring appropriate patient-facility matching while maintaining manageable system complexity through a unified platform

The triage system performs self-service by automatically processing patient data and generating triage category recommendations without requiring complex manual intervention. The trained model independently analyzes patient attributes and determines appropriate triage levels, reducing the need for highly trained specialists to make triage decisions and thereby improving overall system productivity and resource efficiency