↓ Skip to main content

Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts

Overview of attention for article published in Drug Safety, January 2017
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
1 news outlet
twitter
39 X users
facebook
1 Facebook page

Citations

dimensions_citation
97 Dimensions

Readers on

mendeley
161 Mendeley
Title
Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts
Published in
Drug Safety, January 2017
DOI 10.1007/s40264-016-0491-0
Pubmed ID
Authors

Carrie E. Pierce, Khaled Bouri, Carol Pamer, Scott Proestel, Harold W. Rodriguez, Hoa Van Le, Clark C. Freifeld, John S. Brownstein, Mark Walderhaug, I. Ralph Edwards, Nabarun Dasgupta

Abstract

The rapid expansion of the Internet and computing power in recent years has opened up the possibility of using social media for pharmacovigilance. While this general concept has been proposed by many, central questions remain as to whether social media can provide earlier warnings for rare and serious events than traditional signal detection from spontaneous report data. Our objective was to examine whether specific product-adverse event pairs were reported via social media before being reported to the US FDA Adverse Event Reporting System (FAERS). A retrospective analysis of public Facebook and Twitter data was conducted for 10 recent FDA postmarketing safety signals at the drug-event pair level with six negative controls. Social media data corresponding to two years prior to signal detection of each product-event pair were compiled. Automated classifiers were used to identify each 'post with resemblance to an adverse event' (Proto-AE), among English language posts. A custom dictionary was used to translate Internet vernacular into Medical Dictionary for Regulatory Activities (MedDRA(®)) Preferred Terms. Drug safety physicians conducted a manual review to determine causality using World Health Organization-Uppsala Monitoring Centre (WHO-UMC) assessment criteria. Cases were also compared with those reported in FAERS. A total of 935,246 posts were harvested from Facebook and Twitter, from March 2009 through October 2014. The automated classifier identified 98,252 Proto-AEs. Of these, 13 posts were selected for causality assessment of product-event pairs. Clinical assessment revealed that posts had sufficient information to warrant further investigation for two possible product-event associations: dronedarone-vasculitis and Banana Boat Sunscreen--skin burns. No product-event associations were found among the negative controls. In one of the positive cases, the first report occurred in social media prior to signal detection from FAERS, whereas the other case occurred first in FAERS. An efficient semi-automated approach to social media monitoring may provide earlier insights into certain adverse events. More work is needed to elaborate additional uses for social media data in pharmacovigilance and to determine how they can be applied by regulatory agencies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 39 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 161 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 161 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 15%
Student > Master 21 13%
Researcher 16 10%
Student > Bachelor 14 9%
Other 12 7%
Other 33 20%
Unknown 41 25%
Readers by discipline Count As %
Medicine and Dentistry 29 18%
Pharmacology, Toxicology and Pharmaceutical Science 23 14%
Computer Science 16 10%
Social Sciences 7 4%
Nursing and Health Professions 6 4%
Other 27 17%
Unknown 53 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 40. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 September 2018.
All research outputs
#1,023,599
of 25,390,970 outputs
Outputs from Drug Safety
#80
of 1,849 outputs
Outputs of similar age
#20,635
of 421,755 outputs
Outputs of similar age from Drug Safety
#3
of 26 outputs
Altmetric has tracked 25,390,970 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,849 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.9. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 421,755 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.