Identification and dating of pregnancies in administrative healthcare claims databases: An updated, transparent, and transportable algorithm

Abstract

Studies using routinely collected healthcare data are essential for understanding the benefit–risk profile of medications in pregnancy. However, reproducibility is limited by the lack of shared pregnancy identification algorithms, and generalizability is constrained by their development primarily in commercial insurance databases. A previously developed pregnancy identification algorithm was updated for ICD-10-CM and translated into a standardized format to support transport across diverse databases. Algorithm implementation characteristics were evaluated in three US health insurance claims databases (2000-2025), including commercially and publicly insured populations. Overall, 5.8 million and 3.0 million pregnancies were identified in two commercial databases (Merative™ and Optum) and 2.3 million pregnancies in Merative™ MarketScan® Multi-State Medicaid Database (MDCD). Across databases, live birth prevalence ranged from 76–83%, miscarriage/abortion 15–23%, ectopic pregnancy 1%, and stillbirth ≤0.5%, with a higher proportion of live births in MDCD. Pregnancy dating methods varied substantially across coding eras: use of gestational age records increased from 4-9% in the ICD-9-CM era to 87–92% during the ICD-10-CM era, with greater use in MDCD. Using a standardized algorithm, this study demonstrates how database characteristics and coding transitions influence pregnancy identification and dating in healthcare data, highlighting methodological considerations for reproducible pregnancy research across data sources.