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Two NEW FDA DRAFT Guidances On the Use of Social Media and Online Promotions of Devices and Drugs

After five years in the making, the FDA is on a roll. Following the publication of the previous draft guidance on the use of social media for “post-marketing submissions for post marketing submissions of interactive promotional media“, the agency has published two new guidances of conduct of medical device and pharma companies in social media.

The first seems easier to understand and implement than the second.

Draft Guidance I: Correcting independent third-party misinformation about prescription drugs and medical devices

Imagine the following: You work as a sales representative in a medical device company. It has come to your attention that a blogger wrote a post that contains inaccurate information about your medical device. On the same day, you learn of a patient that has shared personal experiences with your device on a forum and misinformed other patients about the device’s use. You believe that the way that both these stories are represented may be harmful to the public health. You start typing away at your answer, informing the blogger and forum members of their mistakes. FDA guidance suggests that you should stop first and ask yourself: is it worth your while?

The FDA maintains that you have no obligation to correct any information published by a third party who is not under the firm’s control or influence. This is regardless of whether the firm owns or operates the platform on which the communication appears.

The FDA leaves this to the discretion of the pharma company or medical devices company. If the company chooses to engage in the correction of misinformation, it needs to adhere to certain approaches outlined in the guidance – for instance it cannot only correct negative misinformation written about the medical device while ignoring an overstatement of the benefits of the product.

Download complete draft FDA social media guidance on Correcting Independent Third-Party Misinformation about Prescription Drugs and Medical Devices.

Draft Guidance II: Internet/social media platforms with character space limitations

This FDA draft guidance is more comprehensive than the first and seems more complicated to execute. The guidance describes the FDA’s current thinking about how medical devices and drug manufacturers and marketers should present benefit and risk information of promotional materials in channels that have “character space limitations” (mainly Twitter, and “sponsored links” on search engines such as Google). The guidance does not include platforms such as Facebook and YouTube where there are no space limitations.

The main takeaway: Risk information must appear alongside risk information. Both must be presented in the same message. The FDA clearly states that having risk information on only a Twitter cover photo is insufficient and that main risk information should be included in the short message as well. If a medical company concludes that adequate benefit and risk information, as well as other required information, cannot all be communicated within the same character-space-limited communication, then the firm should reconsider using that platform for the intended promotional message. To many companies, this will be the case. To make matters more complicated, a link should be should be supplied that brings visitors to a page that is solely dedicated to risk information.

The guidance on how promotional materials should be prepared and presented goes on at length in its recommendation – using the example of a fictional drug they call NoFocus (And some people say that the FDA has no humor….).

The use of so many examples shows how complex this field is and the extent to which the FDA does not have a clear grasp of the way it should be managed.

Download complete draft FDA social media guidance on Internet/Social Media Platforms with Character Space Limitations— Presenting Risk and Benefit Information for Prescription Drugs and Medical Devices

A new study led by Jenine K. Harris, PhD, examined the use of the hashtag #childhoodobesity in tweets to track Twitter conversations about the issue of overweight kids.

The study noted that conversations involving childhood obesity on Twitter don't often include comments from representatives of government and public health organizations that likely have evidence relating to how best to approach this issue. The authors think maybe they should.

Twitter use is growing nationwide. In its 2014 Twitter update, the Pew Research Center found that Twitter is used more by those in lower-income groups, which traditionally are more difficult to reach with health information.

While younger Americans also are more likely to use Twitter, it is used equally across education groups and is used more by non-white Americans than whites.

This, Harris said, is one of the reasons Twitter is an avenue that the academic and government sources with accurate health information should consider taking advantage of in order to reach a wide variety of people.

"I think public health so far doesn't have a great game plan for using social media, we're still laying the foundation for that," she said. "We're still learning what works.

"Public health communities, politicians, and government sources -- people who really know what works -- should join in the conversation. Then we might be able to make an impact," she said.

more at http://www.sciencedaily.com/releases/2014/07/140710151723.htm

Big data analytics technology has been able to find patterns and pinpoint disease states more accurately than even the most highly-trained physicians.

The human brain may be nature’s finest computer, but artificial intelligences fed on big data are making a convincing challenge for the crown. In the realm of healthcare, natural language processing, associative intelligence, and machine learning are revolutionizing the way physicians make decisions and diagnose complex patients, significantly improving accuracy and catching deadly issues before symptoms even present themselves.

In this case study examining the impact of big data analytics on clinical decision making, Dr. Partho Sengupta, Director of Cardiac Ultrasound Research and Associate Professor of Medicine in Cardiology at the Mount Sinai Hospital, has used an associative memory engine from Saffron Technology to crunch enormous datasets for more accurate diagnoses.

Using 10,000 attributes collected from 90 metrics in six different locations of the heart, all produced by a single, one-second heartbeat, the analytics technology has been able to find patterns and pinpoint disease states more quickly and accurately than even the most highly-trained physicians.

more at http://healthitanalytics.com/2014/07/07/case-study-big-data-improves-cardiology-diagnoses-by-17/