ArticleHealthcare informatics research2022
Effectiveness of the Use of Standardized Vocabularies on Epilepsy Patient Cohort Generation.
Article in Healthcare informatics research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Identification of patients with epilepsy using automated electronic health records phenotyping.Epilepsia · 2023Trial
- Quantitatively assessing the impact of the quality of SNOMED CT subtype hierarchy on cohort queries.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Leveraging SNOMED CT for patient cohort identification over heterogeneous EHR data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
objectivesThis study investigated the effectiveness of using standardized vocabularies to generate epilepsy patient cohorts with local medical codes, SNOMED Clinical Terms (SNOMED CT), and International Classification of Diseases tenth revision (ICD-10)/Korean Classification of Diseases-7 (KCD-7).
methodsWe compared the granularity between SNOMED CT and ICD-10 for epilepsy by counting the number of SNOMED CT concepts mapped to one ICD-10 code. Next, we created epilepsy patient cohorts by selecting all patients who had at least one code included in the concept sets defined using each vocabulary. We set patient cohorts generated by local codes as the reference to evaluate the patient cohorts generated using SNOMED CT and ICD-10/KCD-7. We compared the number of patients, the prevalence of epilepsy, and the age distribution between patient cohorts by year.
resultsIn terms of the cohort size, the match rate with the reference cohort was approximately 99.2% for SNOMED CT and 94.0% for ICD-10/KDC7. From 2010 to 2019, the mean prevalence of epilepsy defined using the local codes, SNOMED CT, and ICD-10/KCD-7 was 0.889%, 0.891% and 0.923%, respectively. The age distribution of epilepsy patients showed no significant difference between the cohorts defined using local codes or SNOMED CT, but the ICD-9/KCD-7-generated cohort showed a substantial gap in the age distribution of patients with epilepsy compared to the cohort generated using the local codes.
conclusionsThe number and age distribution of patients were substantially different from the reference when we used ICD-10/KCD-7 codes, but not when we used SNOMED CT concepts. Therefore, SNOMED CT is more suitable for representing clinical ideas and conducting clinical studies than ICD-10/KCD-7.
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