Pharmacoepidemiologic Evaluation of Birth Defects from Health‑Related Postings in Social Media During Pregnancy

 

Su Golder (1), Stephanie Chiuve (3), Davy Weissenbacher (2), Ari Klein (2), Karen O’Connor (2), Martin Bland (1), Murray Malin (3), Mondira Bhattacharya (3), Linda J. Scarazzini (3), Graciela Gonzalez‐Hernandez (2)

(1) Department of Health Sciences, University of York,
Heslington, York YO10 5DD, UK

(2) Department of Biostatistics, Epidemiology and Informatics,
Perelman School of Medicine, University of Pennsylvania,
Philadelphia, PA, USA

(3) AbbVie, North Chicago, IL, USA

 

Abstract

Introduction:

Adverse effects of medications taken during pregnancy are traditionally studied through post-marketing pregnancy registries, which have limitations. Social media data may be an alternative data source for pregnancy surveillance studies.

Objective:

The objective of this study was to assess the feasibility of using social media data as an alternative source for pregnancy surveillance for regulatory decision making.

Methods:

We created an automated method to identify Twitter accounts of pregnant women. We identified 196 pregnant women with a mention of a birth defect in relation to their baby and 196 without a mention of a birth defect in relation to their baby. We extracted information on pregnancy and maternal demographics, medication intake and timing, and birth defects.

Results:

Although often incomplete, we extracted data for the majority of the pregnancies. Among women that reported birth defects, 35% reported taking one or more medications during pregnancy compared with 17% of controls. After accounting for age, race, and place of residence, a higher medication intake was observed in women who reported birth defects. The rate of birth defects in the pregnancy cohort was lower (0.44%) compared with the rate in the general population (3%).

Conclusions:

Twitter data capture information on medication intake and birth defects; however, the information obtained cannot replace pregnancy registries at this time. Development of improved methods to automatically extract and annotate social media data may increase their value to support regulatory decision making regarding pregnancy outcomes in women using medications during their pregnancies.

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