Evidence map›Paper›PMID 33827567›Full record

ArticleBMC health services research2021

Exploring the differences in ICD and hospital morbidity data collection features across countries: an international survey.

Lucia Otero Varela, Chelsea Doktorchik, Natalie Wiebe, Hude Quan, Catherine Eastwood

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
8.3field-weighted citation impact, top 2% 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

25 citing papers in PubMed, 40 citations in OpenAlex.

  1. Applying the hospital administrative data quality scoring tool in 15 countries.Health information management : journal of the Health Information Management Association of Australia · 2026
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  10. Coding rules for uncertain and "ruled out" diagnoses in ICD-10 and ICD-11.BMC medical informatics and decision making · 2024
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  13. A scoping review of the methodological approaches used in retrospective chart reviews to validate adverse event rates in administrative data.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2024
    Article
  14. International Classification of Diseases clinical coding training: An international survey.Health information management : journal of the Health Information Management Association of Australia · 2024
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  15. Article
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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

5 authors at 2 institutions in 1 country.

Lucia Otero VarelaUniversity of Calgary Cumming School of Medicine, TRW 5th Floor, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4N1, Canada. lucia.oterovarela@ucalgary.ca.
Chelsea DoktorchikUniversity of Calgary Cumming School of Medicine, TRW 5th Floor, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4N1, Canada.
Natalie WiebeUniversity of Calgary Cumming School of Medicine, TRW 5th Floor, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4N1, Canada.
Hude QuanUniversity of Calgary Cumming School of Medicine, TRW 5th Floor, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4N1, Canada.
Catherine EastwoodUniversity of Calgary Cumming School of Medicine, TRW 5th Floor, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4N1, Canada. caeastwo@ucalgary.ca.
University of Calgary · CALibin Cardiovascular Institute of Alberta · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe International Classification of Diseases (ICD) is the reference standard for reporting diseases and health conditions globally. Variations in ICD use and data collection across countries can hinder meaningful comparisons of morbidity data. Thus, we aimed to characterize ICD and hospital morbidity data collection features worldwide.

methodsAn online questionnaire was created to poll the World Health Organization (WHO) member countries that were using ICD. The survey included questions focused on ICD meta-features and hospital data collection systems, and was distributed via SurveyMonkey using purposive and snowball sampling. Accordingly, senior representatives from organizations specialized in the topic, such as WHO Collaborating Centers, and other experts in ICD coding were invited to fill out the survey and forward the questionnaire to their peers. Answers were collated by country, analyzed, and presented in a narrative form with descriptive analysis.

resultsResponses from 47 participants were collected, representing 26 different countries using ICD. Results indicated worldwide disparities in the ICD meta-features regarding the maximum allowable coding fields for diagnosis, the definition of main condition, and the mandatory type of data fields in the hospital morbidity database. Accordingly, the most frequently reported answers were "reason for admission" as main condition definition (n = 14), having 31 or more diagnostic fields available (n = 12), and "Diagnoses" (n = 26) and "Patient demographics" (n = 25) for mandatory data fields. Discrepancies in data collection systems occurred between but also within countries, thereby revealing a lack of standardization both at the international and national level. Additionally, some countries reported specific data collection features, including the use or misuse of ICD coding, the national standards for coding or lack thereof, and the electronic abstracting systems utilized in hospitals.

conclusionsHarmonizing ICD coding standards/guidelines should be a common goal to enhance international comparisons of health data. The current international status of ICD data collection highlights the need for the promotion of ICD and the adoption of the newest version, ICD-11. Furthermore, it will encourage further research on how to improve and standardize ICD coding.

Indexed as

HospitalsInternational Classification of DiseasesHumansMorbiditySurveys and QuestionnairesWorld Health OrganizationData collection featuresHospital morbidity databaseInternational classification of diseasesInternational comparabilitySurveys and questionnaires

Identifiers

PMID33827567
PMCPMC8025494
OpenAlexW3145864269

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.