Terminology for Automatic Alerts in the Early Rescue Chain

Area of Science:

• Emergency response systems
• Information science
• Medical informatics

Background:

• Current emergency communication relies on manual, natural language-based systems.
• Future autonomous systems necessitate standardized machine-to-machine communication for early rescue.
• Existing systems lack a unified terminology for diverse adverse events.

Purpose of the Study:

• To propose a mono-hierarchical, multi-axial terminology for adverse events.
• To ensure semantic operability in machine-to-machine emergency communication.
• To facilitate integration with existing medical classification systems like ICD-11.

Main Methods:

• Development of a structured terminology with axes for event and location.
• Inclusion of specific sub-axes for transport type (traffic accidents) and room type (indoor locations).
• Planning for integration with the International Classification of Diseases (ICD) framework.

Main Results:

• A novel terminology framework for classifying adverse events has been developed.
• The proposed terminology supports multi-axial categorization, enhancing specificity.
• The system is designed for seamless integration into future automated emergency response protocols.

Conclusions:

• A standardized terminology is crucial for effective machine-to-machine emergency communication.
• The proposed mono-hierarchical, multi-axial system offers a scalable solution for adverse event classification.
• Integration with ICD-11 will bridge emergency response and medical data, improving patient outcomes.