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Gaps and Similarities in Research Use LOINC Codes Utilized in Korean University Hospitals: Towards Semantic Interoperability for Patient Care

Authors
 Kuenyoul Park  ;  Min-Sun Kim  ;  YeJin Oh  ;  John Hoon Rim  ;  Shinae Yu  ;  Hyejin Ryu  ;  Eun-Jung Cho  ;  Kyunghoon Lee  ;  Ha Nui Kim  ;  Inha Chun  ;  AeKyung Kwon  ;  Sollip Kim  ;  Jae-Woo Chung  ;  Hyojin Chae  ;  Ji Seon Oh  ;  Hyung-Doo Park  ;  Mira Kang  ;  Yeo-Min Yun  ;  Jong-Baeck Lim  ;  Young Kyung Lee  ;  Sail Chun 
Citation
 JOURNAL OF KOREAN MEDICAL SCIENCE, Vol.40(1) : e4, 2025-01 
Journal Title
JOURNAL OF KOREAN MEDICAL SCIENCE
ISSN
 1011-8934 
Issue Date
2025-01
MeSH
Electronic Health Records ; Hospitals, University* ; Humans ; Logical Observation Identifiers Names and Codes* ; Patient Care ; Republic of Korea ; Semantics
Keywords
Common Data Model ; Harmonization ; Interoperability ; LOINC ; Standardization ; Terminology
Abstract
Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings.

Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes.

Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests. Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%).

Conclusion: This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.
Files in This Item:
T202500848.pdf Download
DOI
10.3346/jkms.2025.40.e4
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Laboratory Medicine (진단검사의학교실) > 1. Journal Papers
Yonsei Authors
Rim, John Hoon(임정훈) ORCID logo https://orcid.org/0000-0001-6825-8479
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/204406
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