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RadLex and SNOMED CT integration: a pilot study for standardising radiology classification
Merit Marquis1, Igor Bossenko2, Peeter Ross2
1Tallinn University of Technology, Tallinn, Estonia. merit.marquis@gmail.com.
This study developed a universal radiology procedure model to improve healthcare data exchange. The new system enhances technical and semantic interoperability for radiology procedures, paving the way for better data utilization and patient care.
Area of Science:
- Medical Informatics
- Health Data Standards
- Radiology Information Systems
Background:
- Healthcare data systems face challenges with effective communication and information exchange due to diverse coding systems and standards.
- Discrepancies and misalignments in healthcare data hinder efficient utilization.
- There is a critical need for innovative solutions to enhance interoperability in healthcare data systems.
Purpose of the Study:
- To develop a technical and semantic interoperability method for radiology procedures.
- To utilize the TermX terminology management tool for efficient healthcare data exchange.
- To create a standardized classification system for radiology procedures.
Main Methods:
- Revised the RadLex data model using SNOMED CT terminology.
- Developed a mapping guide and classification system for X-ray and angiography procedures.
- Utilized twelve design cycles for iterative refinement and validation.
Main Results:
- Created a classification system with nineteen distinct properties and value sets derived from SNOMED CT.
- Mapped 622 radiology procedures using 380 SNOMED CT concepts.
- Successfully validated a universal model for radiology procedure data capture.
Conclusions:
- The developed universal model enhances primary and secondary data collection for radiology procedures.
- The system significantly improves technical and semantic interoperability in healthcare.
- This innovation offers a pathway for future advancements in healthcare data management and patient care.
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