Evidence map›Paper›PMID 16776836›Full record

ArticleBMC health services research2006

Identifying priorities in methodological research using ICD-9-CM and ICD-10 administrative data: report from an international consortium.

Carolyn De Coster, Hude Quan, Alan Finlayson, Min Gao, Patricia Halfon, Karin H Humphries, Helen Johansen, Lisa M Lix, Jean-Christophe Luthi, Jin Ma and 6 more

Abstract readConsensus Statement
In one paragraph

Article in BMC health services research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 8 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

69 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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9 more citing papers are in PubMed but not listed here.

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

16 authors.

Carolyn De CosterDepartment of Community Health Sciences, University of Calgary, Calgary, Canada. decoster@ucalgary.ca
Hude Quan
Alan Finlayson
Min Gao
Patricia Halfon
Karin H Humphries
Helen Johansen
Lisa M Lix
Jean-Christophe Luthi
Jin Ma
Patrick S Romano
Leslie Roos
Vijaya Sundararajan
Jack V Tu
Greg Webster
William A Ghali

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth administrative data are frequently used for health services and population health research. Comparative research using these data has been facilitated by the use of a standard system for coding diagnoses, the International Classification of Diseases (ICD). Research using the data must deal with data quality and validity limitations which arise because the data are not created for research purposes. This paper presents a list of high-priority methodological areas for researchers using health administrative data.

methodsA group of researchers and users of health administrative data from Canada, the United States, Switzerland, Australia, China and the United Kingdom came together in June 2005 in Banff, Canada to discuss and identify high-priority methodological research areas. The generation of ideas for research focussed not only on matters relating to the use of administrative data in health services and population health research, but also on the challenges created in transitioning from ICD-9 to ICD-10. After the brain-storming session, voting took place to rank-order the suggested projects. Participants were asked to rate the importance of each project from 1 (low priority) to 10 (high priority). Average ranks were computed to prioritise the projects.

resultsThirteen potential areas of research were identified, some of which represented preparatory work rather than research per se. The three most highly ranked priorities were the documentation of data fields in each country's hospital administrative data (average score 8.4), the translation of patient safety indicators from ICD-9 to ICD-10 (average score 8.0), and the development and validation of algorithms to verify the logic and internal consistency of coding in hospital abstract data (average score 7.0).

conclusionThe group discussions resulted in a list of expert views on critical international priorities for future methodological research relating to health administrative data. The consortium's members welcome contacts from investigators involved in research using health administrative data, especially in cross-jurisdictional collaborative studies or in studies that illustrate the application of ICD-10.

Indexed as

Health PrioritiesInternational Classification of DiseasesInternational CooperationAlgorithmsAustraliaCanadaChinaChronic DiseaseComorbidityDiseaseForms and Records ControlHealth Services ResearchHumansMedical Record AdministratorsQuality of Health CareSwitzerland

Identifiers

PMID16776836
PMCPMC1513221

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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.