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

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  • Marco D. Huesch

    (Penn State Hershey Medical Center
    Penn State College of Medicine)

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.

Suggested Citation

  • Marco D. Huesch, 2017. "Commercial Online Social Network Data and Statin Side-Effect Surveillance: A Pilot Observational Study of Aggregate Mentions on Facebook," Drug Safety, Springer, vol. 40(12), pages 1199-1204, December.
    • Handle: RePEc:spr:drugsa:v:40:y:2017:i:12:d:10.1007_s40264-017-0577-3
    DOI: 10.1007/s40264-017-0577-3
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    References listed on IDEAS

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    1. Viroj Wiwanitkit, 2017. "Comment on: “Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts”," Drug Safety, Springer, vol. 40(8), pages 755-755, August.
    2. Abeed Sarker & Karen O’Connor & Rachel Ginn & Matthew Scotch & Karen Smith & Dan Malone & Graciela Gonzalez, 2016. "Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter," Drug Safety, Springer, vol. 39(3), pages 231-240, March.
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    Cited by:

    1. Lathan, Hannah Stuart & Kwan, Amy & Takats, Courtney & Tanner, Joshua P. & Wormer, Rachel & Romero, Diana & Jones, Heidi E., 2023. "Ethical considerations and methodological uses of Facebook data in public health research: A systematic review," Social Science & Medicine, Elsevier, vol. 322(C).

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