Evidence map›Paper›PMID 32364236›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

The new International Classification of Diseases 11th edition: a comparative analysis with ICD-10 and ICD-10-CM.

Kin Wah Fung, Julia Xu, Olivier Bodenreider

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  16. A Transformative Innovation to Clinical Coding for Better Data and Less Burden.Advances in health information science and practice · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kin Wah FungLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
Julia XuLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
Olivier BodenreiderLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.

Funding

Clinical and Informatics Research in Medical TerminologiesZIALM010013 · NLM · NATIONAL LIBRARY OF MEDICINE · PI FUNG, KIN WAH · 2018 to 2020
$1.6M
Evaluating the quality and interoperability of biomedical terminologiesZIALM010010 · NLM · NATIONAL LIBRARY OF MEDICINE · PI BODENREIDER, OLIVIER · 2018 to 2020
$1.2M
6 · The paper itself

Abstract

objectiveTo study the newly adopted International Classification of Diseases 11th revision (ICD-11) and compare it to the International Classification of Diseases 10th revision (ICD-10) and International Classification of Diseases 10th revision-Clinical Modification (ICD-10-CM). MATERIALS AND

methods: Data files and maps were downloaded from the World Health Organization (WHO) website and through the application programming interfaces. A round trip method based on the WHO maps was used to identify equivalent codes between ICD-10 and ICD-11, which were validated by limited manual review. ICD-11 terms were mapped to ICD-10-CM through normalized lexical mapping. ICD-10-CM codes in 6 disease areas were also manually recoded in ICD-11.

resultsExcluding the chapters for traditional medicine, functioning assessment, and extension codes for postcoordination, ICD-11 has 14 622 leaf codes (codes that can be used in coding) compared to ICD-10 and ICD-10-CM, which has 10 607 and 71 932 leaf codes, respectively. We identified 4037 pairs of ICD-10 and ICD-11 codes that were equivalent (estimated accuracy of 96%) by our round trip method. Lexical matching between ICD-11 and ICD-10-CM identified 4059 pairs of possibly equivalent codes. Manual recoding showed that 60% of a sample of 388 ICD-10-CM codes could be fully represented in ICD-11 by precoordinated codes or postcoordination.

conclusionIn ICD-11, there is a moderate increase in the number of codes over ICD-10. With postcoordination, it is possible to fully represent the meaning of a high proportion of ICD-10-CM codes, especially with the addition of a limited number of extension codes.

Indexed as

International Classification of DiseasesClinical CodingHumansWorld Health Organizationcontrolled medical vocabulariesICD-10ICD-10-CMICD-11medical terminologies

Identifiers

PMID32364236
PMCPMC7309235

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.