Evidence map›Paper›PMID 39979792›Full record

ArticlePharmacoepidemiology and drug safety2025

Development of a Pregnancy Cohort in Commercial Insurance Claims Data: Evaluation of Deliveries Identified From Inpatient Versus Outpatient Claims.

Jacob C Kahrs, Katelin B Nickel, Mollie E Wood, Sascha Dublin, Michael J Durkin, Sarah S Osmundson, Dustin Stwalley, Elizabeth A Suarez, Anne M Butler

Abstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Jacob C KahrsDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0001-7171-2652
Katelin B NickelDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID 0000-0003-4116-512X
Mollie E WoodDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-9302-2641
Sascha DublinKaiser Permanente Washington Health Research Institute, Seattle, Washington, DC, USA.ORCID 0000-0002-6649-3659
Michael J DurkinDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID 0000-0003-4652-7089
Sarah S OsmundsonDivision of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0002-7626-9992
Dustin StwalleyDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID 0000-0002-6427-0590
Elizabeth A SuarezCenter for Pharmacoepidemiology and Treatment Science, Rutgers Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.ORCID 0000-0001-8989-7878
Anne M ButlerDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID 0000-0001-7307-6864

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Identifying Optimal Antibiotic Regimens to Treat Urinary Tract Infections During PregnancyR01HD107083 · NICHD · WASHINGTON UNIVERSITY · PI Anne Mobley Butler · 2022 to 2026
$3.4M
Comparison of Antimicrobial Safety and Effectiveness for the Treatment of Urinary Tract Infections During PregnancyF31HD115361 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAHRS, JACOB · 2024 to 2025
$81k
AbbVieAstellasBoehringer IngelheimGSKNational Institute of Child Health and Human Development R01HD107083NCATS NIH HHS UL1 TR002345NICHD-funded predoctoral fellowship F31HD115361NICHD NIH HHS F31 HD115361NICHD NIH HHS R01 HD107083SareptaTakedaUCB
6 · The paper itself

Abstract

purposeStudies using insurance claims data to identify pregnancies are rarely able to directly assess the validity of the pregnancy/delivery. Inpatient versus outpatient delivery claims may provide different levels of evidence, but more stringent requirements could result in exclusion of true pregnancies. We identified delivery codes from the inpatient and outpatient settings and examined possible confirmatory evidence suggesting that a delivery truly occurred.

methodsUsing a US commercial insurance database (2006-2021), we identified potential pregnancies by presence of delivery claims from a provider and/or facility. We classified deliveries as inpatient (claim date during inpatient admission) or outpatient (claim date not during inpatient admission). We identified possible confirmatory evidence for each delivery including: (1) Presence of both provider and facility delivery codes; (2) presence of both diagnosis and procedure delivery codes; (3) labor and delivery revenue codes; (4) gestational age diagnosis codes; (5) pregnancy-related care codes; (6) linkage to an infant claim; and (7) infant insurance enrollment and linkage to a birthing parent. We quantified the proportion of deliveries with confirmatory evidence by delivery setting. Among deliveries with ≥ 1 piece of confirmatory evidence, we compared patient characteristics by apparent delivery setting.

resultsAmong 4 084 474 delivery episodes, 96.4% were classified as inpatient and 3.6% outpatient. 99.9% of inpatient and 94.0% of outpatient deliveries had ≥ 1 piece of confirmatory evidence. Pregnancy-related care codes were the most common type of confirmatory evidence (99.0% inpatient, 85.7% outpatient). Deliveries classified as inpatient occurred among patients who were older and more clinically complex (i.e., more pregnancy complications, chronic diseases, and prescription medications).

conclusionsThe vast majority of deliveries had confirmatory evidence regardless of apparent setting. Patient characteristics differed by delivery setting. Inclusion of apparent outpatient deliveries may increase the sample size of the study population and improve the generalizability of study results.

Indexed as

Delivery, ObstetricInpatientsInsurance Claim ReviewOutpatientsAdultCohort StudiesDatabases, FactualFemaleHospitalizationHumansInsurance, HealthPregnancyUnited StatesYoung Adultadministrative datahealthcare claimspharmacoepidemiologypregnancy

Identifiers

PMID39979792
PMCPMC11844750

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

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.