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A Validation Tool (VaPCE) for Postcoordinated SNOMED CT Expressions: Development and Usability Study.

Tessa Ohlsen^1,2, Viola Hofer³, Josef Ingenerf¹

¹Section for Clinical Research IT, Institute of Medical Biometry and Statistics, University of Luebeck and University Hospital Schleswig-Holstein, Luebeck, Germany.

JMIR Medical Informatics

|February 28, 2025

Summary

This summary is machine-generated.

This study introduces a tool to validate SNOMED CT postcoordinated expressions, offering automated correction guidance. The tool enhances data accuracy and semantic interoperability in digital health records.

Keywords:

FHIR Fast Healthcare Interoperability Resource PCE SNOMED CT postcoordinated expression postcoordination validation

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Area of Science:

Medical Informatics
Health Data Standards

Background:

Digital health necessitates efficient data exchange and semantic interoperability.
SNOMED Clinical Terms (SNOMED CT) supports this but has limitations for complex cases.
Postcoordination in SNOMED CT allows concept combination but faces challenges in validation due to complex rules.

Purpose of the Study:

Develop a tool to validate SNOMED CT postcoordinated expressions (PCEs).
Provide automated, detailed correction instructions for syntactic and semantic errors.
Enhance user-friendliness and actionability of PCE validation.

Main Methods:

Utilized FHIR $validate-code service and Ontoserver for PCE correctness checking.
Processed SNOMED CT Concept Model (JSON) to categorize errors.
Generated specific correction suggestions based on predefined error categories.
Integrated the tool into a web application for individual and bulk validation.

Main Results:

13.2% of validated PCEs contained errors, primarily invalid attribute values.
Successfully replaced inactive concepts in 20.9% of evaluated OncoTree codes.
User feedback indicated satisfaction with error categorization and correction suggestions, noting potential for enhanced detail.

Conclusions:

The validation tool improves PCE accuracy by identifying errors and providing detailed correction guidance.
Supports healthcare professionals in creating syntactically and semantically valid PCEs.
Enhances overall data quality and interoperability in healthcare systems.