Real-World Applicability of Multiple International Terminology Systems in Oncology: Mapping Study of Clinical Terms for Cancer Diagnosis and Treatment
4 affiliations
- 1Cancer Data Center, National Cancer Control Institute, National Cancer Center, Goyang, South Korea
- 2Department of Medical Information Management, National Cancer Center, Goyang, South Korea
- 3Department of Public Health and Artificial Intelligence, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, South Korea
- 4Department of Internal Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro 173beon-gil, Seongnam, 13620, South Korea, +82-31-787-7863
Abstract
Background: With the rapid expansion of health care data, multiple international standardized terminology systems have been developed and refined to ensure semantic interoperability, which is a crucial factor in facilitating collaborative use.
Objective: This study aimed to evaluate the real-world use and applicability of standardized terminology systems by mapping clinical terms from routine cancer care and to propose guidelines that optimize mapping.
Methods: Clinical terms generated during cancer care at the National Cancer Center Korea were extracted and mapped to multiple target terminology systems: the Korean Standard Classification of Diseases; International Classification of Diseases, 9th Revision, Clinical Modification; Logical Observation Identifiers Names and Codes; RxNorm; Anatomical Therapeutic Chemical classification; and Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). A multidisciplinary working group of health care information managers, data experts, and oncologists verified the mapping outcomes, calculated the cross-verification discordance rate, and compared the coverage across systems.
Results: A total of 3472 source terms were identified across 7 domains: chief complaint, diagnosis, laboratory test, imaging test, surgery/procedure, medication, and radiation therapy. With postcoordination and predefined mapping guidelines, SNOMED CT achieved high overall mapping rates (98.3%‐100%) across domains. Applying postcoordination as needed substantially improved exact semantic match rates, which exceeded 90% in most domains. However, more than 40% of source terms were broadly mapped in the imaging test and radiation therapy domains because procedural details such as imaging technique and radiation field configuration could not be represented in SNOMED CT. The cross-verification discordance rate between mappers, defined as the proportion of source terms with disagreement, remained low (0.3%‐1.3%). RxNorm and Logical Observation Identifiers Names and Codes showed complementary strengths within their specialized domains, adding detail or specificity where SNOMED CT was less complete.
Conclusions: Standardized terminology systems are feasible and effective in encoding clinical terms for cancer care. SNOMED CT was the most comprehensive, and predefined mapping guidelines provide a structured framework for mapping and consensus resolution. Domain-specific systems should be used alongside SNOMED CT, and all systems should be updated regularly to reflect evolving clinical practice.
Related
- Self-aggregated photo-heterostructures enhancing fluorescence for cancer diagnosis and treatment monitoring
- Microfluidic Profiling of an Immune Cell‐Associated Extracellular Vesicle Signature for Active Tuberculosis Diagnosis and Treatment Monitoring
- From “synthetic” to defined microbial communities for clearer terminology
- A discussion of cryo-EM terminology as the outreach and number of PDB entries expand
- QSAR-Guided In Silico Design of Piperazinylanthranilamide Factor Xa Inhibitors: Applicability-Domain Assessment, ADMET Profiling, Molecular Docking, Molecular Dynamics, and MM/GBSA
BibTeX
@article{jang2026realworld,
title = {{Real-World Applicability of Multiple International Terminology Systems in Oncology: Mapping Study of Clinical Terms for Cancer Diagnosis and Treatment}},
author = {Boyun Jang and Eunhye Park and Sangwon Lee and Eunbi Ju and Yewon Jang and In Hae Kwak and Kui Son Choi and Hyun-Joo Kong and Hyo Soung Cha and Hyun-Jin Kim and Heejung Chae},
journal = {JMIR Medical Informatics},
year = {2026},
month = oct,
doi = {10.2196/96548},
url = {https://doi.org/10.2196/96548},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Real-World Applicability of Multiple International Terminology Systems in Oncology: Mapping Study of Clinical Terms for Cancer Diagnosis and Treatment
AU - Boyun Jang
AU - Eunhye Park
AU - Sangwon Lee
AU - Eunbi Ju
AU - Yewon Jang
AU - In Hae Kwak
AU - Kui Son Choi
AU - Hyun-Joo Kong
AU - Hyo Soung Cha
AU - Hyun-Jin Kim
AU - Heejung Chae
PY - 2026
DA - 2026/10/27
JO - JMIR Medical Informatics
DO - 10.2196/96548
UR - https://doi.org/10.2196/96548
AB - Background: With the rapid expansion of health care data, multiple international standardized terminology systems have been developed and refined to ensure semantic interoperability, which is a crucial factor in facilitating collaborative use. Objective: This study aimed to evaluate the real-world use and applicability of standardized terminology systems by mapping clinical terms from routine cancer care and to propose guidelines that optimize mapping. Methods: Clinical terms generated during cancer care at the National Cancer Center Korea were extracted and mapped to multiple target terminology systems: the Korean Standard Classification of Diseases; International Classification of Diseases, 9th Revision, Clinical Modification; Logical Observation Identifiers Names and Codes; RxNorm; Anatomical Therapeutic Chemical classification; and Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). A multidisciplinary working group of health care information managers, data experts, and oncologists verified the mapping outcomes, calculated the cross-verification discordance rate, and compared the coverage across systems. Results: A total of 3472 source terms were identified across 7 domains: chief complaint, diagnosis, laboratory test, imaging test, surgery/procedure, medication, and radiation therapy. With postcoordination and predefined mapping guidelines, SNOMED CT achieved high overall mapping rates (98.3%‐100%) across domains. Applying postcoordination as needed substantially improved exact semantic match rates, which exceeded 90% in most domains. However, more than 40% of source terms were broadly mapped in the imaging test and radiation therapy domains because procedural details such as imaging technique and radiation field configuration could not be represented in SNOMED CT. The cross-verification discordance rate between mappers, defined as the proportion of source terms with disagreement, remained low (0.3%‐1.3%). RxNorm and Logical Observation Identifiers Names and Codes showed complementary strengths within their specialized domains, adding detail or specificity where SNOMED CT was less complete. Conclusions: Standardized terminology systems are feasible and effective in encoding clinical terms for cancer care. SNOMED CT was the most comprehensive, and predefined mapping guidelines provide a structured framework for mapping and consensus resolution. Domain-specific systems should be used alongside SNOMED CT, and all systems should be updated regularly to reflect evolving clinical practice.
SN - 2291-9694
ER -