A Novel Approach to Create a Machine Readable Concept Model for Validating SNOMED CT Concept Post-coordination.

Area of Science:

• Medical Informatics
• Clinical Terminology Management
• Health Data Standards

Background:

• Post-coordination in clinical reference terminologies is crucial for comprehensive content coverage and consistent clinical information representation.
• A significant challenge in post-coordination is ensuring the construction of only clinically sensible concepts.

Purpose of the Study:

• To present a novel computational approach for generating the Master Clinical Meaning Representation (MRCM).
• To facilitate adherence to existing guidelines and enhance the quality of post-coordination within SNOMED CT.

Main Methods:

• Development of a novel computational method for MRCM generation.
• Focus on improving the quality and clinical sensibility of post-coordinated concepts.

Main Results:

• A new approach for computationally generating the MRCM has been developed.
• The method aims to improve adherence to guidelines and the quality of post-coordination.

Conclusions:

• Computational MRCM generation offers a promising solution to ensure clinical sensibility in post-coordination.
• This approach can enhance the consistency and quality of clinical information representation in SNOMED CT.