Freifeld C.C.,Boston University |
Brownstein J.S.,Childrens Hospital Informatics Program |
Brownstein J.S.,Harvard University |
Menone C.M.,Epidemico Inc. |
And 5 more authors.
Drug Safety | Year: 2014
Background: Traditional adverse event (AE) reporting systems have been slow in adapting to online AE reporting from patients, relying instead on gatekeepers, such as clinicians and drug safety groups, to verify each potential event. In the meantime, increasing numbers of patients have turned to social media to share their experiences with drugs, medical devices, and vaccines. Objective: The aim of the study was to evaluate the level of concordance between Twitter posts mentioning AE-like reactions and spontaneous reports received by a regulatory agency. Methods: We collected public English-language Twitter posts mentioning 23 medical products from 1 November 2012 through 31 May 2013. Data were filtered using a semi-automated process to identify posts with resemblance to AEs (Proto-AEs). A dictionary was developed to translate Internet vernacular to a standardized regulatory ontology for analysis (MedDRA®). Aggregated frequency of identified product-event pairs was then compared with data from the public FDA Adverse Event Reporting System (FAERS) by System Organ Class (SOC). Of the 6.9 million Twitter posts collected, 4,401 Proto-AEs were identified out of 60,000 examined. Automated, dictionary-based symptom classification had 72 % recall and 86 % precision. Similar overall distribution profiles were observed, with Spearman rank correlation rho of 0.75 (p < 0.0001) between Proto-AEs reported in Twitter and FAERS by SOC. Conclusion: Patients reporting AEs on Twitter showed a range of sophistication when describing their experience. Despite the public availability of these data, their appropriate role in pharmacovigilance has not been established. Additional work is needed to improve data acquisition and automation. © 2014 The Author(s). Source
Conover M.M.,University of North Carolina at Chapel Hill |
Howell J.O.,University of North Carolina at Chapel Hill |
Wu J.M.,University of North Carolina at Chapel Hill |
Kinlaw A.C.,University of North Carolina at Chapel Hill |
And 3 more authors.
Pharmacoepidemiology and Drug Safety | Year: 2015
Objective: Compare incidence of opioid-managed pelvic pain within 12months after hysteroscopic and laparoscopic sterilization. Methods: Using administrative claims, we identified women aged 18-49years without recent history of childbirth who underwent hysteroscopic or laparoscopic sterilization between 2005 and 2012. We defined the outcome as ≥2 diagnoses for pelvic pain and ≥2 prescription fills for opioids. We calculated adjusted hazard ratios (HR) using Cox models and propensity score methods (matching and inverse-probability-of-treatment-weighting [IPTW]). Results: We identified 71875 eligible women (hysteroscopic n=26927 [37.5%], laparoscopic n=44948 [62.5%]). Of those, 236 (0.88%) hysteroscopic patients and 420 (0.93%) laparoscopic patients experienced the outcome (crude HR=0.97, 95%CI: [0.83, 1.14]). Adjusted analyses also yielded near-null results (matched HR=1.08, 95%CI [0.90, 1.31]; IPTW HR=0.97, 95%CI [0.80, 1.18]). While most sensitivity analyses generated results close to the null, hazard ratios estimated using propensity score matching ranged from 0.65 to 1.53. Conclusions: Among women without recent history of childbirth, we did not find compelling evidence of a clinically meaningful increase in the incidence of pelvic pain requiring opioids during the year after hysteroscopic sterilization. However, effects observed in sensitivity analyses may merit further investigation. © 2015 John Wiley & Sons, Ltd. Source
Bahk C.Y.,Epidemico Inc. |
Goshgarian M.,Facebook |
Donahue K.,Facebook |
Freifeld C.C.,Epidemico Inc. |
And 6 more authors.
Pharmaceutical Medicine | Year: 2015
Background: Preparing and submitting a voluntary adverse event (AE) report to the US Food and Drug Administration (FDA) for a medical device typically takes 40 min. User-friendly Web and mobile reporting apps may increase efficiency. Further, coupled with strategies for direct patient involvement, patient engagement in AE reporting may be improved. In 2012, the FDA Center for Devices and Radiologic Health (CDRH) launched a free, public mobile AE reporting app, MedWatcher, for patients and clinicians. During the same year, a patient community on Facebook adopted the app to submit reports involving a hysteroscopic sterilization device, brand name Essure®. Methods: Patient community outreach was conducted to administrators of the group “Essure Problems” (approximately 18,000 members as of June 2015) to gather individual case safety reports (ICSRs). After agreeing on key reporting principles, group administrators encouraged members to report via the app. Semi-structured forms in the app mirrored fields of the MedWatch 3500 form. ICSRs were transmitted to CDRH via an electronic gateway, and anonymized versions were posted in the app. Data collected from May 11, 2013 to December 7, 2014 were analyzed. Narrative texts were coded by trained and certified MedDRA coders (version 17). Descriptive statistics and metrics, including VigiGrade completeness scores, were analyzed. Various incentives and motivations to report in the Facebook group were observed. Results: The average Essure AE report took 11.4 min (±10) to complete. Submissions from 1349 women, average age 34 years, were analyzed. Serious events, including hospitalization, disability, and permanent damage after implantation, were reported by 1047 women (77.6 %). A total of 13,135 product–event pairs were reported, comprising 327 unique preferred terms, most frequently fatigue (n = 491), back pain (468), and pelvic pain (459). Important medical events (IMEs), most frequently mental impairment (142), device dislocation (108), and salpingectomy (62), were reported by 598 women (44.3 %). Other events of interest included loss of libido (n = 115); allergy to metals (109), primarily nickel; and alopecia (252). VigiGrade completeness scores were high, averaging 0.80 (±0.15). Reports received via the mobile app were considered “well documented” 55.9 % of the time, compared with an international average of 13 % for all medical products. On average, there were 15 times more reports submitted per month via the app with patient community support versus traditional pharmacovigilance portals. Conclusions: Outreach via an online patient community, coupled with an easy-to-use app, allowed for rapid and detailed ICSRs to be submitted, with gains in efficiency. Two-way communication and public posting of narratives led to successful engagement within a Motivation-Incentive-Activation-Behavior framework, a conceptual model for successful crowdsourcing. Reports submitted by patients were considerably more complete than those submitted by physicians in routine spontaneous reports. Further research is needed to understand how biases operate differently from those of traditional pharmacovigilance. © 2015, The Author(s). Source
Powell G.E.,Glaxosmithkline |
Seifert H.A.,Glaxosmithkline |
Reblin T.,Glaxosmithkline |
Burstein P.J.,Glaxosmithkline |
And 10 more authors.
Drug Safety | Year: 2016
Introduction: Post-marketing safety surveillance primarily relies on data from spontaneous adverse event reports, medical literature, and observational databases. Limitations of these data sources include potential under-reporting, lack of geographic diversity, and time lag between event occurrence and discovery. There is growing interest in exploring the use of social media (‘social listening’) to supplement established approaches for pharmacovigilance. Although social listening is commonly used for commercial purposes, there are only anecdotal reports of its use in pharmacovigilance. Health information posted online by patients is often publicly available, representing an untapped source of post-marketing safety data that could supplement data from existing sources. Objectives: The objective of this paper is to describe one methodology that could help unlock the potential of social media for safety surveillance. Methods: A third-party vendor acquired 24 months of publicly available Facebook and Twitter data, then processed the data by standardizing drug names and vernacular symptoms, removing duplicates and noise, masking personally identifiable information, and adding supplemental data to facilitate the review process. The resulting dataset was analyzed for safety and benefit information. Results: In Twitter, a total of 6,441,679 Medical Dictionary for Regulatory Activities (MedDRA®) Preferred Terms (PTs) representing 702 individual PTs were discussed in the same post as a drug compared with 15,650,108 total PTs representing 946 individual PTs in Facebook. Further analysis revealed that 26 % of posts also contained benefit information. Conclusion: Social media listening is an important tool to augment post-marketing safety surveillance. Much work remains to determine best practices for using this rapidly evolving data source. © 2016, Springer International Publishing Switzerland. Source