21.06.2017 – Die Nutzbarkeit von Informationen aus den sozialen Netzwerken („Social Media“) für die Pharmakovigilanz ist ein viel diskutiertes Thema. Aufgrund der Masse an Informationen die täglich bei Facebook, Twitter und Co. gepostet werden ergibt sich ein beträchtliches Volumen potentieller Nebenwirkungen, aber wie qualitativ wertvoll sind diese Informationen und lassen sich hieraus neue Signale oder Qualitätsmängel detektieren?
Dieser Frage ist kürzlich ein Autorenteam um Bhattacharya et al. auf den Grund gegangen, welches retrospektiv die Social Media Daten von sechs Produkten über 26 Monate ausgewertet hat. Im Ergebnis konnten weder neue Signale noch Qualitätsmängel detektiert werden und die Menge an neuen Informationen war insgesamt gering. Allerdings hatte die Studie auch einige Limitierungen. Hier der Originalabstract der Autoren:
Using Social Media Data in Routine Pharmacovigilance: A Pilot Study to Identify Safety Signals and Patient Perspectives
Introduction: Social media is recognized as a new source of patient perspectives and data on adverse events (AEs) in pharmacovigilance (PV). Questions remain about how social media data can supplement routine PV surveillance.
Objectives: The objectives of this pilot were to determine whether analysis of social media data could identify (1) new signals, (2) known signals from routine PV, (3) known signals sooner, and (4) specific issues (i.e., quality issues and patient perspectives). Also of interest was to determine the quantity of ‚posts with resemblance to AEs‘ (proto-AEs) and the types and characteristics of products that would benefit from social media analysis.
Methods: AbbVie conducted a study using 26 months of retrospectively collected social media data from Epidemico, Inc., a third-party vendor, for six products. Posts were classified, interpreted, de-identified, and filtered before analysis.
Results: Analysis of social media data did not identify new or previously identified safety signals. The use of traditional PV methods to analyze social media data was unsuccessful. However, analysis of social media data did provide insights into medication tolerability, adherence, quality of life, and patient perspectives but not into device and product quality issues. The quantity of proto-AEs and new information gleaned from social media posts was small.
Conclusion: The results suggest that, for selected products, social media data analysis cannot identify new safety signals. However, social media can provide unique insight into the patient perspective. Assessment was limited by numerous factors, such as data acquisition, language, and demographics. Further research is necessary to determine the best uses of social media data to augment traditional PV surveillance.
Bhattacharya, M., Snyder, S., Malin, M. et al. Using Social Media Data in Routine Pharmacovigilance: A Pilot Study to Identify Safety Signals and Patient Perspectives. Pharm Med (2017) 31: 167. doi:10.1007/s40290-017-0186-6