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©2015 MFMER | slide-1 The Value of Social Media in Academic Medicine: What are the Data? R. Jay Widmer, MD/PhD Off-site attendees may email comments to: [email protected] OR use the hashtag #MayoCVGR #Gersh

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Page 1: Mayo clinic cvgr 10 21-16

©2015 MFMER | slide-1

The Value of Social Media in Academic Medicine: What are the Data?

R. Jay Widmer, MD/PhD

Off-site attendees may email comments to: [email protected]

OR use the hashtag #MayoCVGR

#Gersh

Page 2: Mayo clinic cvgr 10 21-16

©2015 MFMER | slide-2

DISCLOSURENo relevant financial relationship(s) with industry

Presenter: R. Jay Widmer , M.D./Ph.D.

Cardiovascular Grand RoundsOctober 21, 2016

Off Label Usage: None

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Faculty Disclosure of Commercial Interest/Off-Label Reference• Financial relationship(s) with industry:

None

• No financial relationship(s) with industry:Suraj Kapa Heidi Connolly, M.D.Charanjit S. Rihal, M.D.

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Pre-Test Question #1The most commonly used social media site in the US among active internet users is:

20%

0%

60%

0%

20% A. TwitterB. LinkedInC. FacebookD. InstagramE. Snapchat

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Pre-Test Question #2Among adults over the age of 65, what percentage have a social media profile:

10%

10%

30%

50%

0% A. 10%B. 20%C. 30%D. 40%E. 50%

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Pre-Test Question #3True or false: There is an industry-standard set of hashtags (#’s) for cardiovascular disease?

33%

67% A. TrueB. False

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Learning Objectives

• Understand the current social media tools and their use

• Identify current Mayo Clinic projects utilizing social media for health care research

• Review the publications using social media in academic medicine

• Integrate novel social media research tools into new and ongoing Mayo Clinic CV research interests

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Current Uses and Examples of Social Media Tools in Academic Medicine

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The Power of Networks

People Networks

Spouse/Partner

Friends

FamilyCoworkers

Health Care Provider

SourceNetworks

Books

Internet

Journals/Articles

Handouts

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#Twitter and #Academia

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Percentage of US Population with Social Media Profile

2008 2009 2010 2011 2012 2013 2014 2015 20160

20

40

60

80

100

24

34

4852

5662

6773

78% US Population

http://www.statista.com/statistics/273476/percentage-of-us-population-with-a-social-network-profile/ Accessed 4/2/16

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Social Media Demographics

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Myth: Facebook is dead

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In Health Care: Birth of Online Diagnostics

72% of internet users sought health info online 35% of US adults are

online diagnosers

Only 41% of online diagnosers seek clinical confirmation

http://www.pewinternet.org/2013/01/15/health-online-2013/ Accessed 4/15/15

Most Common: Specific diseases/conditionsTreatments/proceduresDoctors/other health providers

One in four read about/watched someone medical experience

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Online diagnostics for healthcare providers

http://pwchealth.com/ Accessed 10/15/16

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Patient initiated/engaged #hcsm

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Fellow Attitudes Regarding Social Media

Widmer, RJ, et al. Cyber and Social Networking, 2016

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Fellow Attitudes Regarding Social Media

Widmer, RJ, et al. Cyber and Social Networking, 2016

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CV/CVS Active Voices

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Competitive Analysis

Account Followers FollowingTotal Tweets

Avg. Tweets

@CLEHeartLab 17.1k 14.6k 3.5k 3/day

@dukeheartfellow 2,042 26 625 rare

@emoryheart 1,955 39 255 2-3/week

@OSUcardiofellow 76 244 170 1/week

@StanfordHCM 366 307 350 rare

@UABCardiology 336 103 1,011 1/day

@MGHeartHealth 1,114 218 1,434 sporadic

@MayoClinicCV 3,554 690 4,863 3-5/day

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Current #hcsm Projects at Mayo Clinic

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©2015 MFMER | slide-28©2011 MFME

R | slide-

28

“ Active recruitment was unnecessary because 18 women had requested study information within 7 days of IRB approval ”

Mayo Clinic Proceedings, 2011

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Burnout and Twitter

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@MayoClinicCV

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@MayoClinicCV

Widmer, RJ, et al. Cyber and Social Networking, 2016

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@MayoClinicCV – Followers

• 54% male, 46% Female

• 68% within the US (predominantly MN), including dozens of states; 22% followers from countries other than UK, Canada, Mexico, Australia, and Spain

Source: https://analytics.twitter.comWidmer, RJ, et al. Cyber and Social Networking, 2016

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@MayoClinicCV Sprinklr vs. Twitter Analytics

CategoryTwitter Analytics SprinklrTotal Per Tweet Total Per Tweet

Impressions 753,542 961 61M 35k

Engagements 10,567 13.5 2,893 1.7

Engagement Rate 10.1% NR NR NR

RTs 1,893 2.4 1,696 1.0

Replies 122 0.2 122 0.07

Favorites 1,144 1.5 1,075 0.7

Clicks 7,236 9.2 6,107 3.6

Widmer, RJ, et al. Cyber and Social Networking, 2016

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Comparison – Original vs. Repurposed

*Reported Per Tweet RT/MT (n=703)

Original (n=1000)

P-Value

Total Engagements 0.2±0.9 2.8±9.2 <.0001*

Post Likes 0.06±0.3 1.03±0.8 <.0001*

Post Comments 0.01±0.3 0.1±0.5 <.0001*

Post Shares (RT) 0.1±0.6 1.6±5.2 <.0001*

Estimated Clicks 2.5±14.6 4.4±52.5 .34

Post Reach 1,762.5±36,919.4 59,933.0±23,822.4 <.0001*

Widmer, RJ, et al. Cyber and Social Networking, 2016

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Comparison – Publication vs. Adjunct

Publication Adjunct Both P-ValueImpressions 160+1370 2571+6488* 566+3215 <.0001

Engagement 3.1+8.3 22.7+53.0* 5.2+15.4 <.0001

Engagement Rate .005+.01 .005+.008 .01+.01* .04

Retweet 1.1+2.4 4.0+7.5* .9+1.6 <.0001

Replies .1+0.4 .2+.5 .06+.25 .29

Favorites .5+1.3 2.1+4.4* .5+.9 <.0001

User Profile Click .2+0.8 1.9+5.1* .4+1.8 <.0001

URL Click .4+1.9 7.6+23.7* 1.7+5.8 <.0001

Detail Expansion 0.7+3.5 6.1+17.2 1.5+6.2 <.0001

Hashtag Click .02+.1 .2+.1 .06+.3 .29

Widmer, RJ, et al. Cyber and Social Networking, 2016

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Comparison – Conferences (per tweet)Conference Internal

Conference National P-Value

Impressions 212+390 234+942 .9

Engagement 4.5+5.3 4.5+6.9 .99

Engagement Rate .01+.02 .006+.01 .06

Retweet 1.2+1.0 1.7+2.0 .2

Replies .06+.2 .08+.3 .6

Favorites .4+.6 .9+2.1 .15

User Profile Click .2+.3 .3+.9 .54

URL Click 1.9+10.3 .4+1.3 .04

Detail Expansion 2.7+11.4 0.7+2.1 .03

Hashtag Click .4+.8 .1+.5 .03

Widmer, RJ, et al. Cyber and Social Networking, 2016

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@MayoClinicCV “Tweetations”

Widmer, RJ, et al. Cyber and Social Networking, 2016

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“Tweetations” vs. Citations

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“Tweetations” vs. Citations

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“Tweetations” vs. Citations

Eysenbach, G. JMIR, 2011

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CV Hashtag Ontology via @Symplur

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CV Hashtag Ontology via @Symplur

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Social Media Research and Cardiovascular DiseaseThe current landscape…

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The “Intention to Tweet” Trial, AHA 2014

Fox, C, et al. Circulation, 2015

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The “Intention to Tweet” Trial, AHA 2014

Fox, C, et al. Circulation, 2015

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The “Intention to Tweet” Trial, AHA 2014

Fox, C, et al. Circulation, 2015

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Mayo Clinic Proceedings and Social MediaArticles published in MCP on a per-monthly basis (3

mo)

Articles randomized 1:1 to social media strategy

for 60 days following publication (n=33)

Webpage hits and social media engagement

obtained at 60 days

Control group: non-social media

strategy (n=34)

Webpage hits and social media engagement

obtained at 60 days

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Twitter and Cardiologists

McGinnigle, E, et al. ESC, 2016.

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Twitter and Cardiologists - #esccongress

McGinnigle, E, et al. ESC, 2016.

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Twitter and Cardiovascular Disease

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JAMA Cardiology Reach

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Twitter and Cardiovascular Disease

Sinnenberg, L, et al. JAMA Cardiol, 2016.

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Twitter and Cardiovascular Disease

Sinnenberg, L, et al. JAMA Cardiol, 2016.

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#hcsm Research – Oncology

Katz, MS, et al. JAMA Oncol, 2016.

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Innovations in Healthcare Social Media (#hcsm) research (CV)

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#ACC Temporal Social Media Involvement

SymplurSignals.com, 2016.

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Physician vs. Patient sentiments, #ACC16

Most Frequent Words: Doctors Most Frequent Words: Patients

SymplurSignals.com, 2016.

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#ACC16: Network Analysis by Stakeholder

SymplurSignals.com, 2016.

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#ACC16 Sentiment Analysis

SymplurSignals.com, 2016.

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Anatomy of a Tweet

• Nice review of #ClostridiumDifficile Infection http://bit.ly/1OwkVGw, via @NEJM #InfectiousDiseases

Topic curation“health subculture”

User Curation

http://www.nejm.org/doi/full/10.1056/NEJMra1403772

If you are interested in Infectious Diseases or Clostridium Difficile or if you follow the New England Journal of Medicine, here is a link to a nice review article on Clostridium difficile infectionshttp://www.nejm.org/doi/full/10.1056/NEJMra1403772

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We ALL Tweet, and we don’t even know it…

• #Betablocker #CalciumBlocker 1st line Rx for #cvHCM symptoms squat-stand per @SteveOmmen #MayoCVBR

• #cvHCM murmur increases: #exercise, #Valsalva, squat-stand per @SteveOmmen #MayoCVBR

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Summary/Conclusions

• Social media is a ubiquitous and pervasive tool throughout the world – why not leverage such a force?

• Currently the use in Academic Medicine is emerging, however the precise value is not well studied or quantified

• The current standards for social media research in academic medicine are weak

• Collaborations to test the hypothesis that social media is beneficial in Academic Medicine are readily available, and should be explored

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Post Test Question #1The most commonly used social media site in the US among active internet users is:

0%

0%

100%

0%

0% A. TwitterB. LinkedInC. FacebookD. InstagramE. Snapchat

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Post Test Question #2Among adults over the age of 65, what percentage have a social media profile:

100%

0%

0%

0%

0% A. 10%B. 20%C. 30%D. 40%E. 50%

Page 61: Mayo clinic cvgr 10 21-16

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Post Test Question #3True or false: There is an industry-standard set of hashtags (#’s) for cardiovascular disease?

0%100%A. True

B. False

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Question & Answer

[email protected]@DrArgyle

• Off-site attendees may email comments to: [email protected]

OR use the hashtag #MayoCVGR