Gaps and similarities in research use LOINC codes utilized in Korean university hospitals: Towards achieving semantic interoperability for patient care

초록

Background-Aim The Logical Observation Identifiers Names and Codes (LOINC) system was recently introduced by several institutions in Korea to build a Common Data Model (CDM) for research use. However, due to the complexity and abundance of LOINC codes, precise mapping is challenging. We aimed to assess the gap and similarity in interoperability when using existing LOINC mappings in real patient care. Methods We gathered data on local test codes and LOINC code mappings from seven university hospitals over two-months (September to October 2023). The study focused on high-frequency laboratory tests, excluding clinical microbiology and molecular tests. Nationwide proficiency testing codes conducted by the Korean Association of External Quality Assessment Service (KEQAS) were used as intermediary codes for comparison. A research team, comprising 19 members, including clinical pathologists and terminology experts, consulted the LOINC guide and reached a consensus through a collaborative process to determine the optimal LOINC codes. Results Out of a total of 961 LOINC codes corresponding to 164 tests provided by 7 institutions, 792 (82 %) codes were found to be consistent. LOINC codes were not applicable for ABO subgrouping and Rh CcEe antigen tests because LOINC codes were only designated for specific results of these tests. A total of 29 test items, including 25 urine tests, had two LOINC codes as the optimal code, mostly because properties such as quantitative/qualitative or differences in units were not described in the test name. Among the six LOINC parts, inconsistencies were most prevalent in the analyte with 38 (33 %), followed by methods with 33 (29 %), and properties with 13 (11 %). Inconsistencies from other than the LOINC parts included discourage codes, a “W Reflex” code, challenge test codes, and special situation codes. Conclusions This study highlights a notable inconsistency rate exceeding 15 % among research use LOINC mappings in university hospitals, emphasizing the need for verification by experts to ensure interoperability for real patient care.