ArticleBMC medical research methodology2023
Development and evaluation of an algorithm to link mothers and infants in two US commercial healthcare claims databases for pharmacoepidemiology research.
Article in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Hierarchical Algorithms for Constructing Mother-Father-Infant Linkages Under Modern Privacy Constraints.Drug safety · 2026Article
- Enabling evidence generation for extremely preterm neonates: the use of neonatal real-world data.Pediatric research · 2026Review
- PregMedNet: Multifaceted maternal medication impacts on neonatal complications.Nature communications · 2026Article
- Diarrhoea events in offspring exposed to tumour necrosis factor inhibitors and rotavirus vaccine: a population-based cohort study.Rheumatology (Oxford, England) · 2026Article
- Derivation and validation of an algorithm for maternal-child linkage in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Characterizing Perinatal Treatment Patterns and Outcomes in Myasthenia Gravis.Muscle & nerve · 2026Article
- Linking deliveries to newborns using nationwide Medicaid data.BMC medical research methodology · 2025Article
- PregMedNet: Multifaceted Maternal Medication Impacts on Neonatal Complications.medRxiv : the preprint server for health sciences · 2025Article
- Characterization of severity of hemolytic disease of the fetus and newborn due to Rhesus antigen alloimmunization.AJOG global reports · 2025Article
- Expanding the OMOP Common Data Model to Support Perinatal Research in Network Studies.Pharmacoepidemiology and drug safety · 2025Article
- Linking household members and defining relational networks using routine health data.Current opinion in pediatrics · 2025Review
- The AMerican PREGNANcy Mother-Child CohorT: description and prevalence of baseline outcomes and medication dispensing.Frontiers in pharmacology · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAdministrative healthcare claims databases are used in drug safety research but are limited for investigating the impacts of prenatal exposures on neonatal and pediatric outcomes without mother-infant pair identification. Further, existing algorithms are not transportable across data sources. We developed a transportable mother-infant linkage algorithm and evaluated it in two, large US commercially insured populations.
methodsWe used two US commercial health insurance claims databases during the years 2000 to 2021. Mother-infant links were constructed where persons of female sex 12-55 years of age with a pregnancy episode ending in live birth were associated with a person who was 0 years of age at database entry, who shared a common insurance plan ID, had overlapping insurance coverage time, and whose date of birth was within ± 60-days of the mother's pregnancy episode live birth date. We compared the characteristics of linked vs. non-linked mothers and infants to assess similarity.
resultsThe algorithm linked 3,477,960 mothers to 4,160,284 infants in the two databases. Linked mothers and linked infants comprised 73.6% of all mothers and 49.1% of all infants, respectively. 94.9% of linked infants' dates of birth were within ± 30-days of the associated mother's pregnancy episode end dates. Characteristics were largely similar in linked vs. non-linked mothers and infants. Differences included that linked mothers were older, had longer pregnancy episodes, and had greater post-pregnancy observation time than mothers with live births who were not linked. Linked infants had less observation time and greater healthcare utilization than non-linked infants.
conclusionsWe developed a mother-infant linkage algorithm and applied it to two US commercial healthcare claims databases that achieved a high linkage proportion and demonstrated that linked and non-linked mother and infant cohorts were similar. Transparent, reusable algorithms applied to large databases enable large-scale research on exposures during pregnancy and pediatric outcomes with relevance to drug safety. These features suggest studies using this algorithm can produce valid and generalizable evidence to inform clinical, policy, and regulatory decisions.
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