Evidence map›Paper›PMID 39679575›Full record

ArticleEpidemiology (Cambridge, Mass.)2025

Validation of Lactational Mastitis Diagnosis Codes in Electronic Health Care Data.

Malini B DeSilva, Elisabeth M Seburg, Kirsten Ehresmann, Gabriela Vazquez-Benitez, Yihe G Daida, Kimberly K Vesco, Elyse O Kharbanda, Kristin Palmsten

Abstract readValidation Study
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2025. 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

What it found

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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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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Malini B DeSilvaFrom the Pregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.ORCID 0000-0003-3705-1672
Elisabeth M SeburgFrom the Pregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.
Kirsten EhresmannFrom the Pregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.
Gabriela Vazquez-BenitezFrom the Pregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.
Yihe G DaidaCenter for Integrated Health Care Research, Kaiser Permanente Hawaii, Honolulu, HI.
Kimberly K VescoKaiser Permanente Center for Health Research, Portland, OR.
Elyse O KharbandaFrom the Pregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.
Kristin PalmstenCenter for Integrated Health Care Research, Kaiser Permanente Hawaii, Honolulu, HI.

Funding

Maternal COVID-19 Vaccination and Lactation OutcomesR01HD107753 · NICHD · HEALTHPARTNERS INSTITUTE · PI PALMSTEN, KRISTIN · 2022 to 2024
$2.0M
NICHD NIH HHS R01 HD107753
6 · The paper itself

Abstract

backgroundElectronic health record data are an underused source for lactation-related research. The validity of the International Classification of Diseases, 10th Revision Clinical Modification (ICD-10-CM)-coded lactational mastitis is unknown.

methodsWe assessed lactational mastitis diagnosis code validity by medical record review. We included patients from three health care systems with a live birth between December 2020 and September 2022 whose infant had ≥1 well visit and for whom there was electronic health record documentation of lactation in patient or infant records. We used ICD-10-CM diagnosis codes (N61.0 and O91.2) to identify patients with suspected lactational mastitis and assessed antibiotic dispensings. We performed medical record reviews on a random sample to determine whether suspected lactational mastitis cases met definitions for "probable" (breast symptoms with systemic symptoms) or "possible" (breast symptoms without systemic symptoms) lactational mastitis. We report positive predictive values (PPV) with 95% confidence intervals (CI).

resultsAmong 19,660 eligible patients, 1,023 (5.2%) had either N61.0 or O91.2 diagnosis code and 768 (3.9%) had a diagnosis code and antibiotic dispensed. Chart reviews of 119 identified PPV of 76% (95% CI: 67.3, 82.9) for probable and 97% (95% CI: 91.6, 98.7) for probable or possible lactational mastitis. Restricting to those dispensed an antibiotic (n = 87), PPVs improved to 80% (95% CI: 69.6, 87.4) for probable and 100% (95% CI: 95.8, 100) for probable or possible lactational mastitis.

conclusionsDiagnosis codes alone have good PPV for lactational mastitis. PPV for lactational mastitis improves when including antibiotic data, although case numbers decrease. Future research may consider the use of ICD-10 codes alone for the identification of lactational mastitis.

Indexed as

Electronic Health RecordsInternational Classification of DiseasesLactationMastitisAdultFemaleHumansReproducibility of ResultsYoung Adult

Identifiers

PMID39679575
PMCPMC12970718

What Socratic holds

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