Evidence map›Paper›PMID 41878154›Full record

ArticleInternational journal of population data science2026

Mapping Different Versions of the International Classification of Diseases: A Scoping Review.

Nasiba M Ahmed, Mina Nouredanesh, Lisa M Lix, Amani F Hamad

Abstract readScoping Review
In one paragraph

Article in International journal of population data science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Nasiba M AhmedCollege of Community and Global Health, University of Manitoba, Winnipeg, Manitoba, Canada R3E 0W3.
Mina NouredaneshCollege of Community and Global Health, University of Manitoba, Winnipeg, Manitoba, Canada R3E 0W3.
Lisa M LixCollege of Community and Global Health, University of Manitoba, Winnipeg, Manitoba, Canada R3E 0W3.
Amani F HamadCollege of Community and Global Health, University of Manitoba, Winnipeg, Manitoba, Canada R3E 0W3.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The International Classification of Diseases (ICD) is used to report medical diagnoses and procedures in most electronic health databases. Periodic revisions and region/country-specific adaptations reflect advances in medical knowledge and local needs. Therefore, health databases often include multiple ICD versions. Comprehensive and accurate mapping between different ICD versions and adaptations is necessary to facilitate research over time and across regions and populations. Objective: This scoping review describes published literature about methods to map diagnosis codes between different versions or adaptations of the ICD system. Methods: A systematic search across MEDLINE, EMBASE, Scopus and Web of Science Core Collection from inception until June 21, 2024, was performed. Primary research and review articles describing the mapping methods were included. Information was extracted on article characteristics, data characteristics (e.g., versions of ICD codes mapped), mapping methods, and measures to assess mapping quality. Study data were descriptively analysed using frequencies and percentages. Results: Among 1359 articles identified from the search, 25 were included in the review; 13 (52%) articles were published between 2020 and 2023. Two-thirds of the articles used US electronic health databases. Mappings were most frequently (48%) created between ICD-9-CM (i.e., 9th revision, clinical modification) and ICD-10-CM (i.e., 10th revision, clinical modification). Mapping methods were mostly (88%) manual, relying primarily on expert review and existing resources to generate mappings and assess their quality. Only 36% of the articles implemented at least two or more strategies to mitigate loss of information due to mapping. Conclusion: We identified several methods to map different ICD version, all methods relied on expert review to assess accuracy of the mappings. The application of automated approaches through the utilization of AI tools could represent an opportunity for future research.

Indexed as

Databases, FactualInternational Classification of DiseasesHumanscode translationdiagnosis codesreview study

Identifiers

PMID41878154
PMCPMC13007851

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Registered trials

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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.