Mapping clinical terms to standard terminology for multi-institutional research platform: Mapping principles and system deployment

Abstract

Objective: To develop and implement a multi-institutional research platform by standardizing and integrating clinical terms with international terminologies.

Materials and methods: This study introduces the Health data Research Suite (HRS) platform, designed to standardize and connect electronic medical record (EMR) data across institutions for efficient multi-institutional research. A hybrid mapping process-combining automated and manual methods-ensures semantic equivalency, consistency, and compliance with international standards like SNOMED CT, LOINC, and RxNorm. Key strategies included domain-specific semantic restrictions, prioritized attributes for post-coordination, and tailored mapping approaches. Cross-validation and expert consultations resolved mapping discrepancies and inactive concept issues, ensuring reliable data alignment.

Results: The study enhanced mapping accuracy in SNOMED CT, LOINC, and RxNorm by utilizing semantic tags and attribute prioritization, with expert consultations addressing any discrepancies. The HRS platform, designed with advanced code search capabilities and user-friendly interfaces, improved cohort generation and facilitated multi-institutional research.

Discussion: Challenges in maintaining inter-institutional consistency and addressing SNOMED CT's hierarchical limitations were mitigated with a detailed mapping manual, systematic validation, and expert consensus-building. However, a national shortage of trained terminology specialists in Korea underscores the need for educational programs to enhance workforce expertise. Future enhancements include advanced search options and attribute-based retrieval to further improve usability and research support.

Conclusion: This study presents a mapping strategy to align institutional clinical terms with international standards, addressing challenges in semantic consistency and system implementation. The approach enhances multi-institutional research efficiency and fosters innovation in integrated healthcare research, with potential to advance global health outcomes.

Keywords: Clinical research; Clinical terminology; Interoperability; Standardization; Terminology mapping.