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Mapping clinical terms to standard terminology for multi-institutional research platform: Mapping principles and
Hannah Kang1, Youngsun Park1, Yukyeong Son1
1Kakao Healthcare Corp, Seongnam-si, Gyeonggi-do, South Korea.
International Journal of Medical Informatics
|January 21, 2026
Summary
This study developed the Health data Research Suite (HRS) platform to standardize clinical terms across institutions. This improves multi-institutional research by ensuring data consistency with international terminologies like SNOMED CT.
Area of Science:
- Health Informatics
- Clinical Data Standardization
- Research Platforms
Background:
- Electronic Medical Record (EMR) data present challenges for multi-institutional research due to variations in clinical terminology.
- Standardizing clinical terms is crucial for enabling seamless data integration and analysis across different healthcare institutions.
- International terminologies like SNOMED CT, LOINC, and RxNorm provide a framework for semantic interoperability.
Purpose of the Study:
- To develop and implement a multi-institutional research platform, the Health data Research Suite (HRS).
- To standardize and integrate institutional clinical terms with international terminologies, ensuring semantic equivalency and consistency.
- To facilitate efficient multi-institutional research by connecting electronic medical record (EMR) data across diverse healthcare settings.
Main Methods:
- Implemented a hybrid mapping process combining automated and manual methods for clinical term standardization.
- Utilized domain-specific semantic restrictions and prioritized attributes for post-coordination in mapping.
- Employed cross-validation and expert consultations to resolve mapping discrepancies and ensure data alignment with SNOMED CT, LOINC, and RxNorm.
Main Results:
- Achieved enhanced mapping accuracy for SNOMED CT, LOINC, and RxNorm through semantic tags and attribute prioritization.
- The Health data Research Suite (HRS) platform demonstrated improved cohort generation and facilitated multi-institutional research.
- Advanced code search capabilities and user-friendly interfaces were integrated into the HRS platform.
Conclusions:
- A systematic mapping strategy was developed to align institutional clinical terms with international standards, overcoming semantic consistency challenges.
- The HRS platform enhances multi-institutional research efficiency and supports innovation in integrated healthcare research.
- Addressing the shortage of terminology specialists through educational programs is recommended to support workforce development for advanced health informatics.
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