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      Social Media Impact of the Food and Drug Administration's Drug Safety Communication Messaging About Zolpidem: Mixed-Methods Analysis

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          Abstract

          Background

          The Food and Drug Administration (FDA) issues drug safety communications (DSCs) to health care professionals, patients, and the public when safety issues emerge related to FDA-approved drug products. These safety messages are disseminated through social media to ensure broad uptake.

          Objective

          The objective of this study was to assess the social media dissemination of 2 DSCs released in 2013 for the sleep aid zolpidem.

          Methods

          We used the MedWatcher Social program and the DataSift historic query tool to aggregate Twitter and Facebook posts from October 1, 2012 through August 31, 2013, a period beginning approximately 3 months before the first DSC and ending 3 months after the second. Posts were categorized as (1) junk, (2) mention, and (3) adverse event (AE) based on a score between –0.2 (completely unrelated) to 1 (perfectly related). We also looked at Google Trends data and Wikipedia edits for the same time period. Google Trends search volume is scaled on a range of 0 to 100 and includes “Related queries” during the relevant time periods. An interrupted time series (ITS) analysis assessed the impact of DSCs on the counts of posts with specific mention of zolpidem-containing products. Chow tests for known structural breaks were conducted on data from Twitter, Facebook, and Google Trends. Finally, Wikipedia edits were pulled from the website’s editorial history, which lists all revisions to a given page and the editor’s identity.

          Results

          In total, 174,286 Twitter posts and 59,641 Facebook posts met entry criteria. Of those, 16.63% (28,989/174,286) of Twitter posts and 25.91% (15,453/59,641) of Facebook posts were labeled as junk and excluded. AEs and mentions represented 9.21% (16,051/174,286) and 74.16% (129,246/174,286) of Twitter posts and 5.11% (3,050/59,641) and 68.98% (41,138/59,641) of Facebook posts, respectively. Total daily counts of posts about zolpidem-containing products increased on Twitter and Facebook on the day of the first DSC; Google searches increased on the week of the first DSC. ITS analyses demonstrated variability but pointed to an increase in interest around the first DSC. Chow tests were significant ( P<.0001) for both DSCs on Facebook and Twitter, but only the first DSC on Google Trends. Wikipedia edits occurred soon after each DSC release, citing news articles rather than the DSC itself and presenting content that needed subsequent revisions for accuracy.

          Conclusions

          Social media offers challenges and opportunities for dissemination of the DSC messages. The FDA could consider strategies for more actively disseminating DSC safety information through social media platforms, particularly when announcements require updating. The FDA may also benefit from directly contributing content to websites like Wikipedia that are frequently accessed for drug-related information.

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          Most cited references28

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          Digital disease detection--harnessing the Web for public health surveillance.

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            Utilizing social media data for pharmacovigilance: A review.

            Automatic monitoring of Adverse Drug Reactions (ADRs), defined as adverse patient outcomes caused by medications, is a challenging research problem that is currently receiving significant attention from the medical informatics community. In recent years, user-posted data on social media, primarily due to its sheer volume, has become a useful resource for ADR monitoring. Research using social media data has progressed using various data sources and techniques, making it difficult to compare distinct systems and their performances. In this paper, we perform a methodical review to characterize the different approaches to ADR detection/extraction from social media, and their applicability to pharmacovigilance. In addition, we present a potential systematic pathway to ADR monitoring from social media.
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              Timing of new black box warnings and withdrawals for prescription medications.

              Recently approved drugs may be more likely to have unrecognized adverse drug reactions (ADRs) than established drugs, but no recent studies have examined how frequently postmarketing surveillance identifies important ADRs. To determine the frequency and timing of discovery of new ADRs described in black box warnings or necessitating withdrawal of the drug from the market. Examination of the Physicians' Desk Reference for all new chemical entities approved by the US Food and Drug Administration between 1975 and 1999, and all drugs withdrawn from the market between 1975 and 2000 (with or without a prior black box warning). Frequency of and time to a new black box warning or drug withdrawal. A total of 548 new chemical entities were approved in 1975-1999; 56 (10.2%) acquired a new black box warning or were withdrawn. Forty-five drugs (8.2%) acquired 1 or more black box warnings and 16 (2.9%) were withdrawn from the market. In Kaplan-Meier analyses, the estimated probability of acquiring a new black box warning or being withdrawn from the market over 25 years was 20%. Eighty-one major changes to drug labeling in the Physicians' Desk Reference occurred including the addition of 1 or more black box warnings per drug, or drug withdrawal. In Kaplan-Meier analyses, half of these changes occurred within 7 years of drug introduction; half of the withdrawals occurred within 2 years. Serious ADRs commonly emerge after Food and Drug Administration approval. The safety of new agents cannot be known with certainty until a drug has been on the market for many years.
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                Author and article information

                Contributors
                Journal
                JMIR Public Health Surveill
                JMIR Public Health Surveill
                JPH
                JMIR Public Health and Surveillance
                JMIR Publications (Toronto, Canada )
                2369-2960
                Jan-Mar 2018
                05 January 2018
                : 4
                : 1
                : e1
                Affiliations
                [1] 1 Program On Regulation, Therapeutics, And Law Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine Brigham and Women's Hospital and Harvard Medical School Boston, MA United States
                [2] 2 College of Computer and Information Science Northeastern University Boston, MA United States
                [3] 3 Computational Epidemiology Group Boston Children's Hospital Boston, MA United States
                [4] 4 Health Services Management and Policy College of Public Health The Ohio State University Columbus, OH United States
                [5] 5 Food and Drug Administration Silver Spring, MD United States
                Author notes
                Corresponding Author: Aaron S Kesselheim akesselheim@ 123456partners.org
                Author information
                http://orcid.org/0000-0002-9165-8611
                http://orcid.org/0000-0002-6281-219X
                http://orcid.org/0000-0001-8568-5317
                http://orcid.org/0000-0003-2710-913X
                http://orcid.org/0000-0002-3016-241X
                http://orcid.org/0000-0002-5120-1940
                http://orcid.org/0000-0003-4608-6850
                http://orcid.org/0000-0003-4874-5864
                http://orcid.org/0000-0002-8585-9505
                http://orcid.org/0000-0003-0717-1497
                http://orcid.org/0000-0003-0255-2346
                http://orcid.org/0000-0002-8867-2666
                Article
                v4i1e1
                10.2196/publichealth.7823
                5775485
                29305342
                fbd8db18-91eb-4177-b525-b7c29f48ccc5
                ©Michael S Sinha, Clark C Freifeld, John S Brownstein, Macarius M Donneyong, Paula Rausch, Brian M Lappin, Esther H Zhou, Gerald J Dal Pan, Ajinkya M Pawar, Thomas J Hwang, Jerry Avorn, Aaron S Kesselheim. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 05.01.2018.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included.

                History
                : 5 April 2017
                : 12 July 2017
                : 29 September 2017
                : 30 October 2017
                Categories
                Original Paper
                Original Paper

                food and drug administration,drug safety communications,surveillance,epidemiology,social media,twitter,facebook,google trends

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