Evidence map›Paper›PMID 39695792›Full record

ArticlePopulation health metrics2024

Applying an ICD-10 to ICD-11 mapping tool to identify causes of death codes in an Alberta dataset.

Chelsea Doktorchik, Danielle A Southern, James A King, Hude Quan

Abstract read
In one paragraph

Article in Population health metrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Chelsea DoktorchikFaculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, Canada.
Danielle A SouthernCentre for Health Informatics, Cumming School of Medicine, University of Calgary, CWPH 5E43, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada. dasouthe@ucalgary.ca.
James A KingCentre for Health Informatics, Cumming School of Medicine, University of Calgary, CWPH 5E43, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada.
Hude QuanCentre for Health Informatics, Cumming School of Medicine, University of Calgary, CWPH 5E43, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe most recent and 11th revision of the International Classification of Disease (ICD-11) is in use as of January 2022, and countries around the globe are now preparing for the implementation of ICD-11 and transition from the 10th revision (ICD-10). Translation of current coding is required for historical comparisons.

methodsWe applied the World Health Organization (WHO) mapping tables to current Centers for Disease Control and Prevention (CDC) Lists of ICD-10 coding of underlying causes of death to assess what ICD-11 codes look like in an Alberta sample of causes of death (COD). We prepared frequency tables for a single year of COD in Alberta based on the CDC grouping of COD.

resultsThe mapping success rate at the ICD-10 code level for the adult population (> 18 years) was 96.6% and 100% for children (1-17 years) and infants (< 1 year). The mapping success rate by patient was 99.5% for the adult population patient deaths and 100% for children and infants. We mapped ICD-11 codes to identify the ten most frequently reported underlying COD in Alberta for 24,645 deaths in adults, children, and infants in 2017.

conclusionsApart from two codes, all ICD-10 codes could be mapped to ICD-11 for underlying COD. These findings suggest that the ability to translate from the two iterations of coding will be feasible for future applications of health services data.

Indexed as

Cause of DeathInternational Classification of DiseasesAdolescentAdultAgedAlbertaChildChild, PreschoolFemaleHumansInfantMaleMiddle AgedWorld Health OrganizationYoung AdultICD11International Classification of DiseasesMortality

Identifiers

PMID39695792
PMCPMC11658050

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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.