Evidence map›Paper›PMID 33369725›Full record

ArticlePharmaceutical medicine2021

Building a Data Linkage Foundation for Mother-Child Pharmacoepidemiology Research.

Christine C Whitmore, R Eric Hawley, Jea Young Min, Ed Mitchel, James R Daugherty, Marie R Griffin, Carlos G Grijalva

Abstract read
PubMed Publisher
In one paragraph

Article in Pharmaceutical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 19% of its field
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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Derivation and validation of an algorithm for maternal-child linkage in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2026
    Article
  4. Article
  5. Article
  6. 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

7 authors at 1 institution in 1 country.

Christine C WhitmoreDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA. christine.whitmore@vanderbilt.edu.ORCID 0000-0002-8419-963X
R Eric HawleyDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA.
Jea Young MinDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA.ORCID 0000-0001-9328-6922
Ed MitchelDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA.
James R DaughertyDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA.
Marie R GriffinDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA.ORCID 0000-0001-7114-7614
Carlos G GrijalvaDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA.ORCID 0000-0002-2329-7797
Vanderbilt University · US

Funding

FDA HHS HHSF2223014000421
6 · The paper itself

Abstract

backgroundExpanding our understanding of the effects of maternal medication exposure through research is a public health priority and will help inform both clinical and policy decision making, ultimately improving outcomes for pregnant women and their children.

objectiveOur objective was to describe a linked-data research platform that facilitates studies of pregnancy medication exposures and policy changes on maternal and child health outcomes.

methodsMothers receiving Medicaid benefits were probabilistically linked with newborns in the Tennessee Medicaid program (TennCare) through three distinct linkage processes. Medicaid claims data and state birth and fetal death certificate records (vital records) were used to identify and link potential mothers, deliveries, and newborn children. The linkage process started with the creation of a merged pool of potential mothers and eligible deliveries, which was linked to vital records and to children's records. In the last step, linked records from the preceding steps were combined into the final Mother-child linked records. For each data linkage step, rubrics and scoring systems for exact and partial matches and mismatches among key linkage fields were applied and used to examine the strength of the probabilistic linkages. Summary linkage yields for year 2013 are reported for illustration purposes.

resultsAmong the 84,253 potential deliveries, 1,761,557 eligible potential mothers, and 51,400 eligible children identified in Tennessee Medicaid records in 2013, a total of 60,265 of these records were uniquely linked to vital records, including 46,172 (77%) with linked mother-child-vital records. Among the 51,400 eligible children records identified in Tennessee Medicaid for that year, 97% (50,053) had at least one link to vital records or a mother-delivery record. In linked records, the median maternal age was 24 years, and the median gestational age was 39 weeks. About 33% of pregnant women underwent cesarean birth, and 1% of births were classified as complicated deliveries.

conclusionsSupplementing existing Medicaid claims data with birth certificate records complements administrative claims information and allows for detailed assessments of pregnancy exposures and policy changes on mother and child outcomes.

Indexed as

Medical Record LinkagePharmacoepidemiologyAdultBirth CertificatesFemaleHumansInfantInfant, NewbornInformation Storage and RetrievalMother-Child RelationsPregnancyUnited StatesYoung Adult

Identifiers

PMID33369725
OpenAlexW3116349419

What OpenQuestion 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 OpenQuestion graph.