Representing Clinical Scales in SNOMED CT: A Proposed Extension

Area of Science:

• Health Informatics
• Clinical Data Management
• Medical Terminology

Background:

• Harmonizing clinical data from daily activities is a persistent challenge in healthcare.
• While compositional systems like SNOMED CT represent much clinical data, specific domains like clinical scales remain difficult to model.
• Accurate representation of clinical scales is crucial for consistent patient assessment and data analysis.

Purpose of the Study:

• To propose and validate a pragmatic solution for representing complex clinical scales within a large public hospital consortium.
• To develop a methodology that enables the accurate capture of clinical scale data, despite potential institutional variations.

Main Methods:

• Developed a methodology based on expert consensus for representing clinical scales.
• Implemented an internally validated solution within a consortium of public hospitals.
• Focused on capturing the inherent complexity of various clinical scales.

Main Results:

• The proposed methodology provides a pragmatic and internally validated approach to representing clinical scales.
• The solution allows for the accurate capture of complex clinical scale data in a multi-institutional setting.
• The developed methodology accommodates institution-specific nuances while ensuring data representability.

Conclusions:

• A practical and validated methodology for representing clinical scales has been successfully developed and implemented.
• This approach enhances the harmonization of clinical data, particularly for complex assessment tools.
• The solution facilitates more accurate and consistent use of clinical scale data in large healthcare networks.