In collaboration with Audun Utengen and Thomas Lee from Symplur LLC, we explore the usage of digital and social media data to inform research in novel ways and discover emerging health trends, disease communities and outreach mechanisms.
This presentation is part of the Digital Scholar Training Series at USC and CHLA.
Learn more about the initiative: http://sc-ctsi.org/digital-scholar/
News story: http://sc-ctsi.org/index.php/news/new-digital-scholar-training-initiative-helps-researchers-better-utilize-we#.VDhIWWK9mKU
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Utilize Digital and Social Media Data to Inform Your Research in Novel Ways
1. Utilize Digital & Social
Media Data to Inform
Your Research
Workshop 4 of the Digital Scholar Training Series
Katja Reuter1, PhD; Audun Utengen2, MBA; Thomas Lee2, BS, NHA
1Southern California Clinical and Translational Science Institute (SC CTSI) at the University of Southern
California and Children's Hospital Los Angeles
2Symplur LLC, a healthcare social media consultancy
2. Today’s Goals
1. Understand how to use social media data
in support of research and study participant
recruitment
2. Understand how to use Symplur Signals
3. Workshop Outline
Introduction: Web-Based Disease
Communities, PHI, Online Recruitment,
Online Consent
Using Social Media Data from Twitter
The Healthcare Hashtag Project
Using Symplur Signals
4. The Opportunity
R e s e a r c h p r o f e s s i o n a l s a r e a b l e t o …
…learn about
emerging health/
disease topics
…identify active
online disease
communities &
start a dialogue
…identify, and
engage/recruit
potential research
participants
ON L IN E
U s e r s S e a r c h , V i e w , a n d C o n t r i b u t e O n l i n e
5. Internet and Social Media Usage
80%+ of Americans seek health information online
Nearly 70% of all Internet users in the U.S. use
(Pew Research Center, 2013, 2014)
digital and social media
40% of 18-29 year old African Americans who use
the Internet say that they use Twitter
Latinos go online from mobile devices and use
social networking sites at similar – and sometimes
higher – rates than do other Americans
6. L.A. County
Medical
Enterprise
Research
Enterprise
Internet/Web
Social Media
Mobile Technologies
7. L.A. County – Digital Divide
Medical
Enterprise
Research
Enterprise
Internet/Web
Social Media
Mobile Technologies
CAVEAT: DIGITAL DIVIDE
>35% of Angelenos either do not have
access to broadband or cannot afford it.
BUT: High Penetration of mobile
technologies among low-income
and underserved populations (e.g.,
more than 75% of Latinos).
89% of U.S. Hispanics log on to
Facebook every day, 78% via mobile
device (US Hispanics and Facebook, The
Generation of Growth, 2014)
8. L.A. Users on Twitter
June 2012 - Oct 2014
13,372 users that self-identified
as located in Los
Angeles
Sent 35,295 messages on
Twitter using the word
“diabetes”
In more than a dozen
languages, including English,
Spanish, Tagalog, Haitian, Korean,
and Vietnamese
(Symplur Signals database)
9. Data Source: Twitter
https://blog.twitter.com/2014/introducing-twitter-data-grants
11. Research Studies that Successfully
Leverage Digital Data
Group 1
Q u e s t i o n s
How did they engage research participants?
What did they ask participants to do?
How long did they recruit?
Describe the online consent method.
Group 2
Describe the digital data the research team
used.
What did they learn?
12. Online Data Usage in Research
Things to keep in mind…
Protected health information (PHI)
De-identification Vs. Anonymization
13. Online Recruitment
Things to keep in mind…
1. The creator of a social media page is responsible for the content.
Link to site with more information (Institutional Clinical Trials Dircetory or
ClinicalTrials.gov)
2. Abide by institution’s media guidelines
3. Consult IRB (meet institutional and state definitions of advertising)
4. Refrain from providing significant details of any trial – focus on
basic study information
5. Beware of proprietary information
6. Avoid making claims of treatment efficacy or side effects. Use
disclaimers to reduce risk.
7. Establish monitoring mechanism to protect against HIPAA violations
and inappropriate posting
8. Avoid disclosure of preliminary results or non-public information
9. Bloggers involved in study conduct should not write about trial or
drug (could be viewed as advertising)
http://www.ncbi.nlm.nih.gov/pubmed/24857086
14. Online Consent & Signatures
Things to keep in mind…
In minimal risk research, requires IRB approval
Office of Human Research Protections (OHRP): “If properly obtained, an
electronic signature can be considered ‘original’ for the purposes of
recordkeeping.”
Federal Electronic Signatures in Global and National Commerce Act
(eSIGN) and California’s Uniform Electronic Transactions Act (UETA):
Require that subjects agree to use the electronic format (by clicking a
“You agree” icon) and that subjects be informed about their rights to
obtain the electronic consent in non-electronic form and a description
of any procedures that must be followed to withdraw their agreement
to use an electronic record.
FDA-regulated: Electronic documents would be subject to a specialized
set of requirements found at 21 CFR Part 11.
15. Symplur
A healthcare social media consultancy, creator of “The Healthcare
Hashtag Project”
Audun Utengen, MBA,
Co-founder, Symplur
LLC
Thomas Lee, BS, NHA,
Co-founder, Symplur
LLC
16. The Start of a Healthcare Communications Revolution
2006 - Twitter Created
2007 - First use of hashtags on Twitter
2009 - First healthcare related tweet chat - #hcsm
2010 - The Healthcare Hashtag Project started
17. The Healthcare Hashtag Project
A structured organization of healthcare social media
An open social project
Millions of tweets – thousands of untold stories
18. The Rise of Patient Communities on Twitter
22 month study
100 million tweets
A surprise discovery
http://www.symplur.com/shorts/the-rise-of-patient-
communities-on-twitter-visualized/
19. The Dynamics of a Twitter Patient Community
A look at a Rheumatoid Arthritis community - #rheum
Dynamic network centrality
analysis
1 month timeline
http://www.symplur.com/shorts/dyna
mics-twitter-patient-community-network-
centrality-analysis/
20.
21.
22.
23.
24. The True Audience of Healthcare Conferences
3,190 healthcare conferences in the database
The physical attendees VS. the whole audience
Dissemination of healthcare information
25.
26.
27. A Dive into Healthcare Social Media
Very high growth: 1M tweets a day
Types of hashtags:
Tweet Chats: 377
Diseases: 390
Conferences: 3,190
Others: 1,402
Demo: http://www.symplur.com/healthcare-hashtags/
28. Where and How to Find Digital and Social Media Data?
Public VS. Private Social Networks
Platform APIs
Aggregate sources:
Gnip
Datasift
Analytics Providers (1,000+)
Most well known: Radian6 (Salesforce)
Symplur Signals only one healthcare focused
29. Open Social Network Data
Twitter
Tumblr
Foursquare
WordPress
Disqus, Intensedebate
31. Limitations of Digital Data
Biases
Population adoption of networks
Personal Identity (Facebook VS. Twitter)
Functional Identity (Doctors VS. Patients)
Patient role (open VS private, job-to-be-done of
network)
Historic access
32. Symplur Signals
Requests for research and
data
A treasure trove of insights
and stories
3rd parties need access
33. Symplur Signals Data
Not only 5,000+ healthcare hashtags
10,000+ healthcare topics
Thousands of high impact stakeholders
doctors
pharma
hospitals
Drug names, infectious disease terms, etc.
34. Example Insights to Extract:
What are the top healthcare articles being shared by
Radiation Oncologists this week?
Who are the most influential bloggers that are talking
about statin drugs?
When has the topic of “flu” begun to trend and peak
over the last two years?
What are the trending topics today in the Diabetes
communities?