Evidence map›Paper›PMID 25270407›Full record

ArticleBMC research notes2014

Mining rich health data from Canadian physician claims: features and face validity.

Ceara Tess Cunningham, Pin Cai, David Topps, Lawrence W Svenson, Nathalie Jetté, Hude Quan

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC research notes, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
12.8field-weighted citation impact, top 1% 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

29 citing papers in PubMed, 51 citations in OpenAlex.

  1. Misclassification bias in chronic disease case ascertainment algorithms: a reclassification approach.Health promotion and chronic disease prevention in Canada : research, policy and practice · 2026
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  19. Quality of administrative health databases in Canada: A scoping review.Canadian journal of public health = Revue canadienne de sante publique · 2016
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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

6 authors at 3 institutions in 1 country.

Ceara Tess Cunningham
Pin Cai
David Topps
Lawrence W Svenson
Nathalie Jetté
Hude QuanDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Dr, NW, Calgary, Alberta T2N 4Z6, Canada. hquan@ucalgary.ca.
University of Calgary · CAAlberta Health Services · CAUniversity of Alberta · CA

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

backgroundPhysician claims data are one of the largest sources of coded health information unique to Canada. There is skepticism from data users about the quality of this data. This study investigated features of diagnostic codes used in the Alberta physician claims database.

methodsAlberta physician claims from January 1 to March 31, 2011 are analyzed. Claims contain coded diagnoses using the International Classification of Diseases, 9th revision (ICD-9), procedures, physician specialty and service-fee type. Descriptive statistics examined the diversity and frequency of unique ICD-9 diagnostic codes used and the level of code extension (e.g. 3- or 4-digit coding).

resultsA total of 7,441,005 claims by 6,601 physicians were analyzed. The average number of claims per physician was 1,079, with ranges between 1,330 for family medicine, 690 for internal medicine, 722 for surgery, 516 for pediatrics and 409 for neurology. Family physicians used an average of 121 diagnostic codes, internal medicine physicians 32, surgery 36, pediatrics 46 and neurology 27. Overall, 43.5% of claims had a more detailed diagnosis (ICD code with >3 digits). Physicians on a fee-for-service plan submitted 1,184 claims and used 88 unique diagnosis codes on average compared to 438 claims and 44 unique diagnosis codes from physicians on an alternative payment plan (APP).

conclusionsFace validity of diagnosis coded in physician claims is substantially high and the features of diagnosis codes seem to reasonably reflect the clinical specialty. Physicians submit a diverse array of ICD 9 diagnostic codes and nearly half of the ICD-9 diagnostic codes examined were more detailed than required (i.e. ICD code with >3 digits). Finally, guidelines and policies should be explored to assess the submission of shadow billings for physicians on APPs.

Indexed as

Data MiningInsurance Claim ReportingAlberta

Identifiers

PMID25270407
PMCPMC4193126
OpenAlexW2155820959

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.