Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review

• Published in: Journal of medical Internet research 2015-07, Vol.17 (7), p.e171-e171
• Main Authors: Lardon, Jérémy, Abdellaoui, Redhouane, Bellet, Florelle, Asfari, Hadyl, Souvignet, Julien, Texier, Nathalie, Jaulent, Marie-Christine, Beyens, Marie-Noëlle, Burgun, Anita, Bousquet, Cédric
• Format: Article
• Language: English
• Subjects: Citations; Clinical information; Complications and side effects; Computational linguistics; Computer Science; Critical incidents; Data mining; Drug-Related Side Effects and Adverse Reactions - diagnosis; Drugs; Electronic health records; Extraction; Generic drugs; Generic prescribing; Humans; Internet; Internet - statistics & numerical data; Keywords; Language; Language processing; Medical personnel; Natural language interfaces; Natural language processing; Patients; Pharmaceuticals; Pharmacovigilance; Queries; Reliability; Reproducibility of Results; Review; Social media; Social Media - standards; Social networks; Surveillance; Underreporting; User behavior; User feedback; User generated content; Web 2.0; Web sites
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/jmir.4304

The underreporting of adverse drug reactions (ADRs) through traditional reporting channels is a limitation in the efficiency of the current pharmacovigilance system. Patients' experiences with drugs that they report on social media represent a new source of data that may have some value in postmarketing safety surveillance. A scoping review was undertaken to explore the breadth of evidence about the use of social media as a new source of knowledge for pharmacovigilance. Daubt et al's recommendations for scoping reviews were followed. The research questions were as follows: How can social media be used as a data source for postmarketing drug surveillance? What are the available methods for extracting data? What are the different ways to use these data? We queried PubMed, Embase, and Google Scholar to extract relevant articles that were published before June 2014 and with no lower date limit. Two pairs of reviewers independently screened the selected studies and proposed two themes of review: manual ADR identification (theme 1) and automated ADR extraction from social media (theme 2). Descriptive characteristics were collected from the publications to create a database for themes 1 and 2. Of the 1032 citations from PubMed and Embase, 11 were relevant to the research question. An additional 13 citations were added after further research on the Internet and in reference lists. Themes 1 and 2 explored 11 and 13 articles, respectively. Ways of approaching the use of social media as a pharmacovigilance data source were identified. This scoping review noted multiple methods for identifying target data, extracting them, and evaluating the quality of medical information from social media. It also showed some remaining gaps in the field. Studies related to the identification theme usually failed to accurately assess the completeness, quality, and reliability of the data that were analyzed from social media. Regarding extraction, no study proposed a generic approach to easily adding a new site or data source. Additional studies are required to precisely determine the role of social media in the pharmacovigilance system.