Development of a mother-child database for drug exposure and adverse event detection in the Military Health System.

PURPOSE: The aim of this study was to develop a mother-child linked database consisting of all eligible active duty military personnel, retirees, and their dependents in order to conduct medication-related analyses to improve the safety and quality of care in the Military Health System (MHS).

METHODS: Eligible women of reproductive age with at least one pregnancy-related encounter between January 2005 and December 2013 receiving care in the MHS were included in the study population. Building on previously published algorithms, we used pregnancy-related diagnostic and procedure codes, parameterized temporal constraints, and data elements unique to the MHS to identify pregnancies ending in live births, stillbirth, spontaneous abortion, or ectopic pregnancy. Pregnancies ending in live births were matched to presumptive offspring using birth dates and family-based sponsorship identification. Antidepressant and antiepileptic use during pregnancy was evaluated using electronic pharmacy data.

RESULTS: Algorithms identified 755,232 women who experienced 1,099,648 complete pregnancies with both pregnancy care encounter and pregnancy outcome. Of the 924,320 live birth pregnancies, 827,753 (90.0%) were matched to offspring. Algorithms also identified 5,663 stillbirths, 11,358 ectopic pregnancies, and 169,665 spontaneous abortions. Among the matched singleton live birth pregnancies, 7.1% of mothers were dispensed an antidepressant at any point during pregnancy, usually a selective serotonin reuptake inhibitor, (75.3%), whereas 1.3% of mothers were dispensed an antiepileptic drug.