Commercial Online Social Network Data and Statin Side-Effect Surveillance: A Pilot Observational Study of Aggregate Mentions on Facebook.

Drug Saf

Radiology Research, Center for Optimizing Radiology Value (CORVA), Penn State Hershey Medical Center, Hershey, PA, USA.

Published: December 2017

AI Article Synopsis

  • Surveillance of drug safety post-marketing involves various methods, including provider reports and electronic records, but there are challenges in effectiveness and costs.
  • A new data-mining tool from Sysomos analyzed Facebook mentions of statins and related side effects over a month, revealing that 4.3% of mentions included these side effects.
  • While this percentage aligns with estimates of side effects in patients, the limitations of the tool, particularly a lack of full-text mining, hinder precise content analysis and categorization.

Article Abstract

Introduction: Surveillance of the safety of prescribed drugs after marketing approval has been secured remains fraught with complications. Formal ascertainment by providers and reporting to adverse-event registries, formal surveys by manufacturers, and mining of electronic medical records are all well-known approaches with varying degrees of difficulty, cost, and success. Novel approaches may be a useful adjunct, especially approaches that mine or sample internet-based methods such as online social networks.

Methods: A novel commercial software-as-a-service data-mining product supplied by Sysomos from Datasift/Facebook was used to mine all mentions on Facebook of statins and stain-related side effects in the US in the 1-month period 9 January 2017 through 8 February 2017.

Results: A total of 4.3% of all 25,700 mentions of statins also mentioned typical stain-related side effects. Multiple methodological weaknesses stymie interpretation of this percentage, which is however not inconsistent with estimates that 5-20% of patients taking statins will experience typical side effects at some time.

Conclusions: Future work on pharmacovigilance may be informed by this novel commercial tool, but the inability to mine the full text of a posting poses serious challenges to content categorization.

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Source
http://dx.doi.org/10.1007/s40264-017-0577-3DOI Listing

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