Real-world data are not always big data: the case for primary data collection on medication use in pregnancy in the context of birth defects research.

Many examples of the use of real-world data in the area of pharmacoepidemiology include "big data," such as insurance claims, medical records, or hospital discharge databases. However, "big" is not always better, particularly when studying outcomes with narrow windows of etiologic relevance. Birth defects are such an outcome, for which specificity of exposure timing is critical. Studies with primary data collection can be designed to query details about the timing of medication use, as well as type, dose, frequency, duration, and indication, that can better characterize the "real world." Because birth defects are rare, etiologic studies are typically case‑control in design, like the National Birth Defects Prevention Study, Birth Defects Study to Evaluate Pregnancy Exposures, and Slone Birth Defects Study. Recall bias can be a concern, but the ability to collect detailed information about both prescription and over-the-counter medication use and other exposures such as diet, family history, and sociodemographic factors is a distinct advantage over claims and medical record data sources. Case‑control studies with primary data collection are essential to advancing the pharmacoepidemiology of birth defects. This article is part of a Special Collection on Pharmacoepidemiology. [ABSTRACT FROM AUTHOR]