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Comparison of Knowledge Levels Required for SNOMED CT Coding of Diagnosis and Operation Names in Clinical Records

OBJECTIVES: Coding Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT) with complex and polysemy clinical terms may ask coder to have a high level of knowledge of clinical domains, but with simpler clinical terms, coding may require only simpler knowledge. However, there are few studie...

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Detalles Bibliográficos
Autores principales: Kim, Shine Young, Kim, Hyung Hoi, Shin, Kyung Hwa, Kim, Hwa Sun, Lee, Jae Il, Choi, Byung Kwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3483476/
https://www.ncbi.nlm.nih.gov/pubmed/23115741
http://dx.doi.org/10.4258/hir.2012.18.3.186
Descripción
Sumario:OBJECTIVES: Coding Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT) with complex and polysemy clinical terms may ask coder to have a high level of knowledge of clinical domains, but with simpler clinical terms, coding may require only simpler knowledge. However, there are few studies quantitatively showing the relation between domain knowledge and coding ability. So, we tried to show the relationship between those two areas. METHODS: We extracted diagnosis and operation names from electronic medical records of a university hospital for 500 ophthalmology and 500 neurosurgery patients. The coding process involved one ophthalmologist, one neurosurgeon, and one medical record technician who had no experience of SNOMED coding, without limitation to accessing of data for coding. The coding results and domain knowledge were compared. RESULTS: 705 and 576 diagnoses, and 500 and 629 operation names from ophthalmology and neurosurgery, were enrolled, respectively. The physicians showed higher performance in coding than in MRT for all domains; all specialist physicians showed the highest performance in domains of their own departments. All three coders showed statistically better coding rates in diagnosis than in operation names (p < 0.001). CONCLUSIONS: Performance of SNOMED coding with clinical terms is strongly related to the knowledge level of the domain and the complexity of the clinical terms. Physicians who generate clinical data can be the best potential candidates as excellent coders from the aspect of coding performance.