Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

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

Authors
Park KuenyoulKim Min-SunOh YeJinRim John HoonYu ShinaeRyu HyejinCho Eun-JungLee KyunghoonKim Ha NuiChun InhaKwon AeKyungKim SollipChung Jae-WooChae HyojinOh Ji SeonPark Hyung-DooKang MiraYun Yeo-MinLim Jong-BaeckLee Young KyungChun Sail
Issue Date
Jan-2025
Publisher
대한의학회
Keywords
Common Data Model; LOINC; Harmonization; Interoperability; Standardization; Terminology
Citation
Journal of Korean Medical Science, v.40, no.1, pp 1 - 11
Pages
11
Indexed
SCIE
SCOPUS
KCI
Journal Title
Journal of Korean Medical Science
Volume
40
Number
1
Start Page
1
End Page
11
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/56821
DOI
10.3346/jkms.2025.40.e4
ISSN
1011-8934
1598-6357
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
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Medicine > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Chung, Jae Woo photo

Chung, Jae Woo
Graduate School (Department of Medicine)
Read more

Altmetrics

Total Views & Downloads

BROWSE