GALEN: a third generation terminology tool to support a multipurpose national coding system for surgical procedures

Area of Science:

• Medical Informatics
• Computational Linguistics
• Knowledge Representation

Background:

• The Generalised Architecture for Languages, Encyclopedia and Nomenclatures in Medicine (GALEN) developed advanced terminology tools.
• These tools utilize a language-independent model for semantic description, computer processing, and natural language understanding.
• The goal is to enhance sharing and maintenance of consistent medical knowledge.

Purpose of the Study:

• To apply GALEN's modeling and tools for developing a new multipurpose coding system for surgical procedures (CCAM) in France.
• To contribute to a language-independent knowledge repository and multilingual semantic dictionaries for Europe.
• To leverage artificial intelligence and natural language processing to support the creation of medical coding systems.

Main Methods:

• Utilized the CLAW (classification workbench) software to process French medical language rubrics from surgical domain experts.
• Transformed rubrics into intermediate dissections and the Grail reference ontology model representation.
• Employed the LNAT natural language generator for controlled French natural language output and the CLAW classification manager for concept categorization.

Main Results:

• Developed a language-independent conceptual model representation of surgical procedures.
• Generated linguistically validated French natural language labels for the CCAM system.
• Demonstrated the CLAW system's capability to categorize concepts and link them to electronic patient records.

Conclusions:

• The GALEN tools and AI approach significantly support the creation of medical coding systems, reducing labor.
• The developed CCAM system provides a multilingual semantic foundation for surgical procedure coding.
• This work contributes to a structured representation of medical terminology, bridging to electronic health records.