Evidence map›Paper›PMID 38494336›Full record

ArticlePaediatric and perinatal epidemiology2024

Characterisation and validation of lactation information from structured electronic health records for use in pharmacoepidemiological studies.

Hibo H Mohamed, Kirsten Ehresmann, Elisabeth M Seburg, Gabriela Vazquez-Benitez, Ellen W Demerath, David A Fields, Kimberly K Vesco, Elyse O Kharbanda, Kristin Palmsten

Abstract readValidation Study
In one paragraph

Article in Paediatric and perinatal epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

9 authors.

Hibo H MohamedDivision of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA.
Kirsten EhresmannPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, Minnesota, USA.
Elisabeth M SeburgPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, Minnesota, USA.
Gabriela Vazquez-BenitezPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, Minnesota, USA.
Ellen W DemerathDivision of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA.
David A FieldsDepartment of Pediatrics, University of Oklahoma College of Medicine, Oklahoma City, Oklahoma, USA.
Kimberly K VescoKaiser Permanente Center for Health Research, Portland, Oregon, USA.
Elyse O KharbandaPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, Minnesota, USA.
Kristin PalmstenPregnancy and Child Health Research Center, HealthPartners Institute, Minneapolis, Minnesota, USA.ORCID https://orcid.org/0000-0002-0134-6228

Funding

Maternal Obesity, Milk Composition, and Infant GrowthR01HD080444 · NICHD · UNIVERSITY OF MINNESOTA · PI ELLEN W. DEMERATH, DAVID A FIELDS · 2014 to 2026
$6.4M
Maternal COVID-19 Vaccination and Lactation OutcomesR01HD107753 · NICHD · HEALTHPARTNERS INSTITUTE · PI PALMSTEN, KRISTIN · 2022 to 2024
$2.0M
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHD NIH HHS R01 HD080444NICHD NIH HHS R01 HD107753NIH HHS
6 · The paper itself

Abstract

backgroundBreastfeeding information stored within electronic health records (EHR) has recently been used for pharmacoepidemiological research, however the data are primarily collected for clinical care.

objectivesTo characterise breastfeeding information recorded in structured fields in EHR during infant and postpartum health care visits, and to assess the validity of lactation status based on EHR data versus maternal report at research study visits.

methodsWe assessed breastfeeding information recorded in structured fields in EHR from one health system for a subset of 211 patients who were also enrolled in a study on breast milk composition between 2014 and 2017 that required participants to exclusively breastfeed their infants until at least 1 month of age. We assessed the frequency of breastfeeding information in EHR during the first 12 months of age and compared lactation status based on EHR with maternal report at 1 and 6-month study visits (reference standard).

resultsThe median number of breastfeeding records in the EHR per infant was six (interquartile range 3) with most observations clustering in the first few weeks of life and around well-infant visits. At the 6-month study visit, 93.8% of participants were breastfeeding and 80.1% were exclusively breastfeeding according to maternal report. Sensitivity of EHR data for identifying ever breastfeeding was at or near 100%, and sensitivity for identifying ever exclusive breastfeeding was 98.0% (95% CI: 95.0%, 99.2%). Sensitivities were 97.3% (95% CI: 93.9%, 98.9%) for identifying any breastfeeding and 94.4% (95% CI: 89.7%, 97.0%) for exclusive breastfeeding, and positive predictive values were 99.5% (95% CI: 97.0%, 99.9%) for any breastfeeding and 95.0% (95% CI: 90.4%, 97.4%) for exclusive breastfeeding.

conclusionsBreastfeeding information in structured EHR fields have the potential to accurately classify lactation status. The validity of these data should be assessed in populations with a lower breastfeeding prevalence.

Indexed as

Breast FeedingElectronic Health RecordsLactationPharmacoepidemiologyAdultFemaleHumansInfantInfant, NewbornMilk, HumanReproducibility of Resultsbreastfeedingelectronic health recordsepidemiologylactationpharmacoepidemiologyvalidation study

Identifiers

PMID38494336
PMCPMC12878064

What Socratic holds

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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 Socratic graph.