Evidence map›Paper›PMID 34007901›Full record

ArticleInternational journal of population data science2021

Mapping three versions of the international classification of diseases to categories of chronic conditions.

Amani F Hamad, Viktoriya Vasylkiv, Lin Yan, Ridwan Sanusi, Olawale Ayilara, Joseph A Delaney, Elizabeth Wall-Wieler, Mohammad Jafari Jozani, Pingzhao Hu, Shantanu Banerji and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of population data science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
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

8 citing papers in PubMed, 15 citations in OpenAlex.

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  5. Trend control charts for multiple sclerosis case definitions.International journal of population data science · 2024
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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

11 authors at 2 institutions in 2 countries.

Amani F HamadDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0T6.
Viktoriya VasylkivDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0T6.
Lin YanDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0T6.
Ridwan SanusiDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0T6.
Olawale AyilaraDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0T6.
Joseph A DelaneyCollege of Pharmacy, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0T5; Department of Epidemiology, University of Washington, Seattle, Washington, USA, WA 98195.
Elizabeth Wall-WielerDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0T6.
Mohammad Jafari JozaniDepartment of Statistics, University of Manitoba, Winnipeg, Manitoba, Canada, R3T2N2.
Pingzhao HuDepartment of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0J9.
Shantanu BanerjiDepartment of Internal Medicine, University of Manitoba, Winnipeg, Manitoba, Canada, R3A1R9; Research Institute in Oncology and Hematology, CancerCare Manitoba, Winnipeg, Manitoba, Canada, R3E0V9.
Lisa M LixDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada, R3E0T6.
University of Manitoba · CACancerCare Manitoba · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAdministrative health data capture diagnoses using the International Classification of Diseases (ICD), which has multiple versions over time. To facilitate longitudinal investigations using these data, we aimed to map diagnoses identified in three ICD versions - ICD-8 with adaptations (ICDA-8), ICD-9 with clinical modifications (ICD-9-CM), and ICD-10 with Canadian adaptations (ICD-10-CA) - to mutually exclusive chronic health condition categories adapted from the open source Clinical Classifications Software (CCS).

methodsWe adapted the CCS crosswalk to 3-digit ICD-9-CM codes for chronic conditions and resolved the one-to-many mappings in ICD-9-CM codes. Using this adapted CCS crosswalk as the reference and referring to existing crosswalks between ICD versions, we extended the mapping to ICDA-8 and ICD-10-CA. Each mapping step was conducted independently by two reviewers and discrepancies were resolved by consensus through deliberation and reference to prior research. We report the frequencies, agreement percentages and 95% confidence intervals (CI) from each step.

resultsWe identified 354 3-digit ICD-9-CM codes for chronic conditions. Of those, 77 (22%) codes had one-to-many mappings; 36 (10%) codes were mapped to a single CCS category and 41 (12%) codes were mapped to combined CCS categories. In total, the codes were mapped to 130 adapted CCS categories with an agreement percentage of 92% (95% CI: 86%-98%). Then, 321 3-digit ICDA-8 codes were mapped to CCS categories with an agreement percentage of 92% (95% CI: 89%-95%). Finally, 3583 ICD-10-CA codes were mapped to CCS categories; 111 (3%) had a fair or poor mapping quality; these were reviewed to keep or move to another category (agreement percentage = 77% [95% CI: 69%-85%]).

conclusionsWe developed crosswalks for three ICD versions (ICDA-8, ICD-9-CM, and ICD-10-CA) to 130 clinically meaningful categories of chronic health conditions by adapting the CCS classification. These crosswalks will benefit chronic disease studies spanning multiple decades of administrative health data.

Indexed as

Chronic DiseaseInternational Classification of DiseasesCanadaConsensusHumansSoftwareadministrative datachronic health conditionscrosswalkICD-10-CAICD-9-CMICDA-8international classification of diseasesmapping

Identifiers

PMID34007901
PMCPMC8104065
OpenAlexW3156103863

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.