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Review
. 2018 Aug 9;9(10):591-599.
doi: 10.1177/2042098618789596. eCollection 2018 Oct.

Using social media in safety signal management: is it reliable?

Sue Rees  1 , Sadiqa Mian  2 , Neal Grabowski  2
Affiliations
Review

Using social media in safety signal management: is it reliable?

Sue Rees et al. Ther Adv Drug Saf. .

Abstract

Social media use is growing globally, with a reported 3 billion active users in 2017. This medium is used increasingly in a health setting by patients (and to a limited extent, healthcare professionals) to share experiences and ask advice on medical conditions as well as pharmaceutical products. In recent years, attention has turned to this huge, generally untapped, source of potential health information as a possible tool for pharmacovigilance, and in particular signal detection. In this article we explore some of the challenges of utilizing social media for safety signal detection and look at some of the pilot studies conducted to date in order to weigh the evidence for and against the utility of social media data in safety signal detection. After doing so we can conclude that the analysis of social media datasets has demonstrated a limited contribution to the signal detection and signal management process. The data available in social media can complement blind spots in traditional pharmacovigilance datasets and provide significant value for targeted investigations and studies such as those relating to abuse, misuse, use in pregnancy, and patient sentiments.

Keywords: internet; pharmacovigilance; signal detection; signal management; social media.

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Conflict of interest statement

Conflict of interest statement: Sue Rees is an employee of Amgen Ltd and Sadiqa Mian and Neal Grabowski are employees of Amgen Inc. All authors hold stock in Amgen Inc.

Figures

Figure 1.
Figure 1.
User location for a post that resembles an adverse event (proto AE).
Figure 2.
Figure 2.
User type of post that resembles an adverse event (proto AE).
Figure 3.
Figure 3.
Comparison of listedness as per the core data sheet (CDS) of social media versus FAERS. ADR, adverse drug reaction.
Figure 4.
Figure 4.
Comparison of adverse events by MedDRA system organ class (SOC) in social media versus FAERS.
Figure 5.
Figure 5.
Comparison of adverse events by seriousness (using IME 9.1 list) in social media versus FAERS. PT, preferred term.
Figure 6.
Figure 6.
Temporal comparison of social media signals of disproportionate reporting (SDRs) versus identification in signal management system.
See this image and copyright information in PMC

References

    1. Almenoff J, Tonning JM, Gould AL, et al. Perspectives on the use of data mining in pharmaco-vigilance. Drug Safety 2005; 28: 981–1007. - PubMed
    1. Dictionary OEL. https://en.oxforddictionaries.com/definition/social_media
    1. Social WA. Three billion people are now using social media, Hootesuite, 2017. https://wearesocial.com/uk/blog/2017/08/three-billion-people-now-use-soc....
    1. De Martino I, D’Apolito R, McLawhorn AS, et al. Social media for patients: benefits and drawbacks. Curr Rev Musculoskelet Med 2017; 10: 141–145. - PMC - PubMed
    1. Fehring KA, De Martino I, McLawhorn AS, et al. Social media: physicians-to-physicians education and communication. Curr Rev Musculoskelet Med 2017; 10: 275–277. - PMC - PubMed

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