Using Social Media Data in Routine Pharmacovigilance: A Pilot Study to Identify Safety Signals and Patient Perspectives

被引：19

作者：

Bhattacharya M. ^{[1
]}

Snyder S. ^{[1
]}

Malin M. ^{[1
]}

Truffa M.M. ^{[1
]}

Marinic S. ^{[1
]}

Engelmann R. ^{[1
]}

Raheja R.R. ^{[1
]}

机构：

[1] Pharmacovigilance and Patient Safety, AbbVie Inc., 1 Waukegan Road, North Chicago, 60044, IL

来源：

Pharmaceutical Medicine | 2017年 / 31卷 / 3期

关键词：

Social Media; Safety Signal; Tofacitinib; System Organ Class; Social Media Data;

D O I：

10.1007/s40290-017-0186-6

中图分类号：

学科分类号：

摘要：

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. © 2017, Springer International Publishing Switzerland.

引用

页码：167 / 174

页数：7

共 17 条

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