Educational Needs and Level of Knowledge in Standard Healthcare Terminology Use in Korea: A Cross-Sectional Survey

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Authors: Ahjung Byun, Hyeoun Ae Park, Jiyeon Yu, Sumi Sung
Cited by: 0
References: 15

Abstract

OBJECTIVES: This study aimed to investigate the experience, knowledge, and educational needs regarding standard healthcare terminologies-specifically Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), Logical Observation Identifiers Names and Codes (LOINC), and the International Classification of Diseases/Korean Classification of Diseases (ICD/KCD)-among professionals in the clinical, industrial, and academic sectors in Korea. METHODS: A descriptive survey was conducted using an online questionnaire distributed between November 21 and December 5, 2023. The questionnaire included items on participants' experiences with, self-reported knowledge of, and educational needs for standard terminologies. A total of 325 responses were analyzed. RESULTS: Participants reported the highest levels of experience and knowledge with ICD/KCD, whereas knowledge of SNOMED CT and LOINC was relatively low. Statistically significant differences in knowledge were observed across professional groups (p < 0.05), with terminology experts reporting higher levels than others. Educational needs were greatest for ICD/KCD and SNOMED CT, particularly in data collection and use case application. The most frequently cited barriers to adopting standard terminologies were a lack of training programs, the cost and time required for training, and the structural complexity of the terminologies. CONCLUSIONS: These findings underscore the importance of customized and systematic educational strategies to promote the use of standard terminologies. Policy-level support, standardized training materials, and the preparation of qualified trainers are essential to enhance semantic interoperability and data utilization in Korean healthcare.

Fields of Study & Subjects

Medical Coding and Health Information Biomedical Text Mining and Ontologies Electronic Health Records Systems

Publication details

Journal / source
Healthcare Informatics Research
Volume
32
Issue
1
Pages
50–58
Publication date
31 January 2026
Language
EN