Evidence map›Paper›PMID 41355391›Full record

ArticleEpidemiology (Cambridge, Mass.)2026

Comparison of Lactation Information from Electronic Health Records with Survey Data Across Five US Health Systems.

Gregory P Jansen, Elisabeth M Seburg, Gabriela Vazquez-Benitez, Kirsten Ehresmann, Hibo H Mohamed, Lyndsay A Avalos, Sonya Negriff, Amy M Loree, Connor K Howick, Yihe G Daida and 1 more

Abstract readComparative Study
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Gregory P JansenFrom the Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN.
Elisabeth M SeburgPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.
Gabriela Vazquez-BenitezPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.
Kirsten EhresmannPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.
Hibo H MohamedPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.
Lyndsay A AvalosDivision of Research, Kaiser Permanente Northern California, Oakland, CA.
Sonya NegriffKaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA.
Amy M LoreeCenter for Health Policy & Health Services Research, Henry Ford Health, Detroit, MI.
Connor K HowickCenter for Integrated Health Care Research, Kaiser Permanente Hawaii, Honolulu, HI.
Yihe G DaidaCenter for Integrated Health Care Research, Kaiser Permanente Hawaii, Honolulu, HI.
Kristin PalmstenPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, MN.ORCID 0000-0002-0134-6228

Funding

Treatment Initiation for New Episodes of Depression in Pregnant WomenR01HD100579 · NICHD · HEALTHPARTNERS INSTITUTE · PI PALMSTEN, KRISTIN · 2021 to 2025
$3.1M
Maternal COVID-19 Vaccination and Lactation OutcomesR01HD107753 · NICHD · HEALTHPARTNERS INSTITUTE · PI PALMSTEN, KRISTIN · 2022 to 2024
$2.0M
NICHD NIH HHS R01 HD100579NICHD NIH HHS R01 HD107753
6 · The paper itself

Abstract

backgroundData on lactation status for research are often collected through surveys. Information on human milk feeding collected at routine healthcare visits and stored in electronic health records (EHR) is an emerging source of data for lactation research. We compared information on milk feeding obtained from structured EHR fields with survey data.

methodsWe included participants from five US healthcare systems in the Managing Our Mood survey. Individuals had a live birth (March 2022-October 2023), depression diagnosis during pregnancy, and ≥1 record of human milk feeding information in their or their infant's EHR. We compared information from EHR data up to ten months after delivery with survey data collected 3-4 months after delivery as the reference. We assessed agreement on lactation status (human milk feeding ever and at survey) using percent agreement, Cohen's kappa, sensitivity, specificity, positive predictive value, and negative predictive value overall and by characteristics.

resultsAccording to survey data, the prevalence of human milk feeding ever was 93.2% and was 73.0% at the time of survey among 281 eligible individuals. Agreement between data sources for ever and for human milk feeding at the survey was ≥92% with kappas ≥0.77. EHR and survey data agreed on human milk feeding ever for 97.3% (95% confidence interval: 94.6%, 98.7%) and on human milk feeding at the time of the survey for 98.0% (95% confidence interval: 95.1%, 99.2%) of those who reported yes to these practices on the survey. These measurements were lower among individuals with fewer records.

conclusionsThere was substantial agreement on lactation status between EHR and survey data. These findings suggest that lactation information from structured EHR may be used for epidemiologic research.

Indexed as

Breast FeedingElectronic Health RecordsLactationAdultFemaleHumansPregnancySurveys and QuestionnairesUnited StatesYoung AdultBreastfeedingElectronic health recordsEpidemiologyHuman milkValidation studies

Identifiers

PMID41355391
PMCPMC13576411

What Socratic holds

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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 Socratic graph.