2017
DOI: 10.1007/s40290-017-0186-6
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Using Social Media Data in Routine Pharmacovigilance: A Pilot Study to Identify Safety Signals and Patient Perspectives

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Cited by 22 publications
(48 citation statements)
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“…Most other work in this area has focused on identifying and optimising the recognition of single adverse events from social media [ 5 , 7 , 8 , 20 , 21 ], while relatively few papers focused on the actual assessment of utility of social media in providing evidence for ADRs relative to traditional data sources [ 6 , 22 ]. Other studies do focus on the possible uses of social media above and beyond spontaneous reporting systems, but do not provide specific comparisons in performance [ 9 ].…”
Section: Discussionmentioning
confidence: 99%
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“…Most other work in this area has focused on identifying and optimising the recognition of single adverse events from social media [ 5 , 7 , 8 , 20 , 21 ], while relatively few papers focused on the actual assessment of utility of social media in providing evidence for ADRs relative to traditional data sources [ 6 , 22 ]. Other studies do focus on the possible uses of social media above and beyond spontaneous reporting systems, but do not provide specific comparisons in performance [ 9 ].…”
Section: Discussionmentioning
confidence: 99%
“…Past investigations into the utility of social media for signal detection have been somewhat limited in the scope of methods, products and events (e.g. abuse or misuse) [ 3 – 6 ], or focused on the recognition of adverse events in single posts [ 7 , 8 ]. In contrast, this work aims to present a comprehensive analysis of the use of social media for the detection of safety signals for a wide range of products using statistical methods.…”
Section: Introductionmentioning
confidence: 99%
“…Social media data are increasingly recognised as a valid source of patient perspectives and data on adverse events (AEs) in pharmacovigilance [61]. This information is in abundance and is timely, relevant and often publicly available.…”
Section: Type 2: Unsolicited Reporting (Social Media Monitoring)mentioning
confidence: 99%
“…A recent pilot study by Bhattacharya et al [61] suggests that the use of traditional pharmacovigilance methods to analyse social media data is ineffective. Mao et al [119] note that frequency data should not serve as prevalence of the adverse effects/reactions, but as a measure of which symptoms may be the most salient to patients on a day-to-day basis.…”
Section: Analysis Of Social Datamentioning
confidence: 99%
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