Evidence map›Paper›PMID 41587000›Full record

ArticleDrug safety2026

Assessing the Use of Medical Insurance Claims and Electronic Health Records to Measure COVID-19 Vaccination During Pregnancy.

Matthew M Coates, Stacey L Rowe, Sheena G Sullivan, Flor M Munoz, Onyebuchi A Arah, Annette K Regan

Erratum issuedAbstract read
In one paragraph

Article in Drug safety, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

6 authors.

Matthew M CoatesDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA, USA. mmcoates@ucla.edu.ORCID http://orcid.org/0000-0002-8474-4992
Stacey L RoweDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Sheena G SullivanDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
Flor M MunozDivision of Infectious Diseases, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
Onyebuchi A ArahDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA, USA.
Annette K ReganDepartment of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA, USA.

Funding

UCLA CANCER EPIDEMIOLOGY TRAINING PROGRAMT32CA009142 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ZHANG, ZUO-FENG · 1986 to 2024
$6.3M
Uptake, Safety and Effectiveness of COVID‐19 Vaccines during PregnancyR01AI169239 · NIAID · UNIVERSITY OF SAN FRANCISCO · PI REGAN, ANNETTE KARENA · 2022 to 2024
$1.3M
National Institute of Allergy and Infectious Diseases R01AI169239NCI NIH HHS CA009142NCI NIH HHS T32 CA009142NIAID NIH HHS R01 AI169239
6 · The paper itself

Abstract

introductionThe safety and effectiveness of COVID-19 vaccination during pregnancy are commonly assessed using administrative health records, which may misclassify vaccine exposures.

objectiveThe aim of this study was to compare the capture of COVID-19 vaccines in commercial insurance claims records and electronic health records (EHR) before and during pregnancy in a cohort in the United States and demonstrate the implications of observed misclassification on vaccine safety and effectiveness estimates.

methodsAnalysis of de-identified data from the Optum Labs Data Warehouse (OLDW) included pregnancies ending after December 11, 2020, and beginning before January 1, 2023, among people aged 15-54 years who were continuously enrolled in health insurance and had EHR data available. We compared the capture of COVID-19 vaccines from insurance claims and EHR databases to the combined and deduplicated doses using clinical procedure and drug codes, assessing records over time and by gestational age, dose number, vaccine manufacturer, and socioeconomic variables.

resultsFor 29,663 eligible pregnancies, we identified 25,124 COVID-19 vaccine doses (87% in claims and 35% in EHR). About 44% had received one or more doses of a COVID-19 vaccine before or during pregnancy in the combined data, compared with 41% in the insurance claims data and 16% in the EHR data. Records of vaccination relative to the combined data improved in the claims data and declined in the EHR data over time. Vaccine manufacturer information from records without procedure codes in EHR data was unreliable, and a greater proportion of combined doses were recorded in EHR when the cohort was restricted to people with more frequent EHR encounters. The magnitudes of exposure misclassification observed, particularly in EHR data, could substantially bias estimates of vaccine effectiveness and safety.

conclusionsInsurance claims data captured a larger proportion of COVID-19 vaccine doses than EHR data, and this proportion increased over time. Combining data from multiple administrative health records sources can improve COVID-19 vaccine measurement before and during pregnancy and may be important to reduce bias in studies of vaccine effects.

Indexed as

COVID-19COVID-19 VaccinesElectronic Health RecordsInsurance Claim ReviewInsurance, HealthVaccinationAdolescentAdultCohort StudiesDatabases, FactualFemaleHumansMiddle AgedPregnancyUnited StatesYoung AdultCOVID-19 Vaccines

Identifiers

PMID41587000
PMCPMC12967848

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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.