Trial reportInternational journal of medical informatics2019
Using SNOMED CT-encoded problems to improve ICD-10-CM coding-A randomized controlled experiment.
Trial report in International journal of medical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Emergency Department Syndromic Surveillance Diagnostic Code Selection for Assessing Severity of Seasonal Influenza in New South Wales, Australia.Influenza and other respiratory viruses · 2026Article
- Variation in multimorbidity estimates due to clinical coding: a cross-sectional study of 7.2 million adults in England.BMJ public health · 2026Article
- Diagnostic Concordance Between Clinical and Histopathologic Diagnoses of Oral Mucosal Lesions: A Retrospective Study.Cureus · 2025Article
- Article
- Promoting interoperability between SNOMED CT and ICD-11: lessons learned from the pilot project mapping between SNOMED CT and the ICD-11 Foundation.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Improving Quality of ICD-10 (International Statistical Classification of Diseases, Tenth Revision) Coding Using AI: Protocol for a Crossover Randomized Controlled Trial.JMIR research protocols · 2024Article
- Concept Coverage Analysis of Ophthalmic Infections and Trauma among the Standardized Medical Terminologies SNOMED-CT, ICD-10-CM, and ICD-11.Ophthalmology science · 2023Article
- Introduction of Systematized Nomenclature of Medicine-Clinical Terms Coding Into an Electronic Health Record and Evaluation of its Impact: Qualitative and Quantitative Study.JMIR medical informatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
objectiveClinical problems in the Electronic Health Record that are encoded in SNOMED CT can be translated into ICD-10-CM codes through the NLM's SNOMED CT to ICD-10-CM map (NLM Map). This study evaluates the potential benefits of using the map-generated codes to assist manual ICD-10-CM coding.
methodsDe-identified clinic notes taken by the physician during an outpatient encounter were made available on a secure web server and randomly assigned for coding by professional coders with usual coding or map-assisted coding. Map-assisted coding made use of the problem list maintained by the physician and the NLM Map to suggest candidate ICD-10-CM codes to the coder. A gold standard set of codes for each note was established by the coders using a Delphi consensus process. Outcomes included coding time, coding reliability as measured by the Jaccard coefficients between codes from two coders with the same method of coding, and coding accuracy as measured by recall, precision and F-score according to the gold standard.
resultsWith map-assisted coding, the average coding time per note reduced by 1.5 min (p = 0.006). There was a small increase in coding reliability and accuracy (not statistical significant). The benefits were more pronounced in the more experienced than less experienced coders. Detailed analysis of cases in which the correct ICD-10-CM codes were not found by the NLM Map showed that most failures were related to omission in the problem list and suboptimal mapping of the problem list terms to SNOMED CT. Only 12% of the failures was caused by errors in the NLM Map.
conclusionMap-assisted coding reduces coding time and can potentially improve coding reliability and accuracy, especially for more experienced coders. More effort is needed to improve the accuracy of the map-suggested ICD-10-CM codes.
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