Evidence map›Paper›PMID 41396243›Full record

ArticleCanadian journal of public health = Revue canadienne de sante publique2026

Identifying patients with obesity from health administrative data: Diagnostic accuracy of surgical billing claims.

Maria C Cusimano, Nancy N Baxter, Rahim Moineddin, Maria Chiu, Lena Nguyen, Suriya Aktar, Ning Liu, Andrea N Simpson, Christina Johnson, Sarah E Ferguson

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Article in Canadian journal of public health = Revue canadienne de sante publique, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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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

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Maria C CusimanoDepartment of Obstetrics & Gynecology, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-1661-4846
Nancy N BaxterICES (Formerly the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada.
Rahim MoineddinICES (Formerly the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada.
Maria ChiuICES (Formerly the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada.
Lena NguyenICES (Formerly the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada.
Suriya AktarICES (Formerly the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada.
Ning LiuICES (Formerly the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada.
Andrea N SimpsonDepartment of Obstetrics & Gynecology, University of Toronto, Toronto, ON, Canada.
Christina JohnsonLahey Hospital & Medical Center, Beth Israel Lahey Health, Burlington, MA, USA.
Sarah E FergusonDepartment of Obstetrics & Gynecology, University of Toronto, Toronto, ON, Canada. sarah.ferguson@uhn.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesObesity (body mass index, BMI ≥ 30 kg/m

methodsWe performed a cross-sectional study of adult patients who had undergone major abdominopelvic, neck, and hip surgery in Ontario from 2011 to 2019, and had also reported their BMI on either the Canadian Community Health Survey or the Ontario Health Study. Physician billing claims for class III obesity were compared to self-reported BMI, and measures of diagnostic accuracy with 95% confidence intervals were calculated.

resultsWe identified 52,515 patients who had undergone surgery (80.6% abdominopelvic; 19.4% neck/hip) with median age 57 years and median BMI 26 (range 15-108); 2189 patients (4.2%) reported a BMI > 40. When self-reported BMI was collected within 1 year of surgery, billing claims submitted by either the surgeon, surgical assistant, or anaesthetist had sensitivity 82.9% (95% CI 79.1-86.7), specificity 95.5% (95.0-96.0), positive predictive value 52.9% (50.1-58.5), and negative predictive value 98.9% (98.7-99.2) for the identification of BMI > 40. Positive predictive value for the identification of BMI > 30 was 95.4% (93.7-97.0).

conclusionPhysician billing claims are specific and sensitive for the identification of patients with BMI > 40 undergoing surgery, enable accurate selection of a population with BMI > 30, and are valid for use in studies conducted with health administrative data.

Indexed as

Insurance Claim ReviewObesitySurgical Procedures, OperativeAdolescentAdultAgedBody Mass IndexCross-Sectional StudiesDatabases, FactualFemaleHumansMaleMiddle AgedOntarioSelf ReportYoung AdultAnaesthetistsBody mass indexObesityPredictive value of testsRoutinely collected health dataSurgeons

Identifiers

PMID41396243
PMCPMC13536496

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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.