Evidence map›Paper›PMID 24130696›Full record

SynthesisPloS one2013

Systematic review and meta-analysis of validation studies on a diabetes case definition from health administrative records.

Aaron Leong, Kaberi Dasgupta, Sasha Bernatsky, Diane Lacaille, Antonio Avina-Zubieta, Elham Rahme

Abstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 7 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

53 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Validating exacerbations of asthma in electronic health records: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2026
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  18. Estimating the completeness of physician billing claims for diabetes case ascertainment: a multiprovince investigation.Health promotion and chronic disease prevention in Canada : research, policy and practice · 2023
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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.

Aaron LeongResearch Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Kaberi Dasgupta
Sasha Bernatsky
Diane Lacaille
Antonio Avina-Zubieta
Elham Rahme

Funding

Canadian Institutes of Health Research SSD-83167
6 · The paper itself

Abstract

objectivesHealth administrative data are frequently used for diabetes surveillance. We aimed to determine the sensitivity and specificity of a commonly-used diabetes case definition (two physician claims or one hospital discharge abstract record within a two-year period) and their potential effect on prevalence estimation.

methodsFollowing Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Medline (from 1950) and Embase (from 1980) databases for validation studies through August 2012 (keywords: "diabetes mellitus"; "administrative databases"; "validation studies"). Reviewers abstracted data with standardized forms and assessed quality using Quality Assessment of Diagnostic Accuracy Studies (QUADAS) criteria. A generalized linear model approach to random-effects bivariate regression meta-analysis was used to pool sensitivity and specificity estimates. We applied correction factors derived from pooled sensitivity and specificity estimates to prevalence estimates from national surveillance reports and projected prevalence estimates over 10 years (to 2018).

resultsThe search strategy identified 1423 abstracts among which 11 studies were deemed relevant and reviewed; 6 of these reported sensitivity and specificity allowing pooling in a meta-analysis. Compared to surveys or medical records, sensitivity was 82.3% (95%CI 75.8, 87.4) and specificity was 97.9% (95%CI 96.5, 98.8). The diabetes case definition underestimated prevalence when it was ≤10.6% and overestimated prevalence otherwise.

conclusionThe diabetes case definition examined misses up to one fifth of diabetes cases and wrongly identifies diabetes in approximately 2% of the population. This may be sufficiently sensitive and specific for surveillance purposes, in particular monitoring prevalence trends. Applying correction factors to adjust prevalence estimates from this definition may be helpful to increase accuracy of estimates.

Indexed as

Databases, FactualDiabetes MellitusHumansMedical Records Systems, Computerized

Identifiers

PMID24130696
PMCPMC3793995

What OpenQuestion holds

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LicenceCC BY
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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.