The rise of online fake news on social media highlights an increasing problem. This talk, given at University of Michigan, explores why health professionals have a professional obligation to ensure patients get accurate, understandable health information.

1. Cancer Care in a
Post-Truth World
A Call for Clear Voices
Matthew Katz, MD
March 2017

2. Disclosures
 Medical Director of Radiation Medicine, Lowell General
Hospital
 Founder, nonprofit blog Radiation Nation
 Cofounder, #radonc journal club
 Communications Committee, Massachusetts Medical
Society
 Volunteer for ASTRO, ASCO
 No financial disclosures

3. Who Do You Trust in Cancer Care?

4. Who Do You Trust in Cancer Care?
http://bit.ly/2mQwRYU

5. Fake News in 2016 Presidential Election
 Fake news traffic
disproportionately by
social media
 156 fake articles shared
37.9 million times
 Fake news itself not
enough to change
outcome
Allcott and Gentzkow, http://stanford.io/2mYjJjC 2017

6. Challenge of a Post-Truth World

7. Hippocrates
“I will use treatment to help the
sick according to my ability
and judgment, but never with a
view to injury or wrong-doing”
“Into whatsoever houses I
enter, I will enter to help the
sick”
Maimonides
“Grant me the strength, time
and opportunity always to
correct what I have acquired,
always to extend its domain;
for knowledge is immense and
the spirit of man can extend
indefinitely to enrich itself daily
with new requirements.”

8. Why Doctors Need to Be Online
• Patients and caregivers are increasingly
online, seeking help and support
• If clinicians don’t engage online, expect more
influence on health decisions by
• Peers and family
• Fearmongerers, opportunists
• Industry (Direct-to-consumer)
• Government

9. Patient Hierarchy of Needs
Source: Matthew Katz, flickr.com

10. WHO Definition of Health

11. Elements of Shared Decision-Making
 Patient knowledge
 Explicit encouragement of patient participation
 Appreciation of the patient's ability to play an active
role in decision
 Awareness of choice
 Time
Fraenkel & McGraw, J Gen Intern Med. 2007

12. Barriers for Patients & Caregivers
 Access
 Accuracy
 Anecdote
 Fake News
 Celebrity Endorsement
 Information Overload
 Privacy Breaches

13. Access

14. Where People Share Their Care

15. Access issues
 Poor broadband access with
lower age, higher income,
education
 More likely smartphone
dependent if non-white, lower
income, <HS education

16. Poor Access to Us  Internet
 Cancer patients often
report getting too little
information
 15.9% of 32K surveyed
had at least one barrier to
access
 43% used internet for
health information; linked
to lack of access
Amante et al, J Med Internet Res 2015

17. Googling Cancer
 Varies by country (highest in U.S.), some
topics rising 2004-2014 on Google Trends
 “symptoms of cancer”
 “stage 4 cancer”
 “signs of cancer”
 >45% have used internet for self-diagnosis
Foroughi et al, JMIR Cancer 2016
Moore et al, http://scholarlyrepository.miami.edu/

18. Anecdote
 Powerful stories can drive decisions
 Blogs, online forums are common places to
find anecdotes
 Online stories tilt toward negative outcomes

19. Anecdote ~ Selection Bias?

20. Who is Prone to Anecdote?
 Analysis of 2012 Pew survey focused on
who searched for anecdotal data
 1895 of 3014 (62.8%) answered yes or no;
other 37.2% refused and excluded
 Binomial logistic regression analysis for
sociodemographic data, health status,
information seeking behavior
Mathadil et al, Proc Human Factors Ergonomics 2014

21. Independent Factors for Looking at
Anecdotal Information Online
Category Variable OR Chi-square
Gender Male 0.95
21.73
Female 1
Age Older (1yr) 0.98 204.37
Education ≤ High school 0.48
164.43Some college 0.64
College 4 yrs+ 1
Health Status Poor 1
23.64
Fair 0.85
Good 0.72
Excellent 0.61
Public report seeking Yes 3.53
718.42
No 1
Mathadil et al, Proc Human Factors Ergonomics 2014

22. Fake News
 Fabricated stories create confusion
 64% say great amount, 88% some or great
 More confusion for
 Higher income, higher education, younger age
 61% only somewhat or not confident they can
identify fake news
 23% have shared fake news (7% deliberately)
Source: Pew Research, 12/2016
N=1002

23. Source: Katie Forster, http://www.independent.co.uk/
• >50% of top 20 stories on Facebook with “cancer” in headline were false
• Top = dandelions can boost immune system, cure cancer

24. Jesse James Principle
Source: Barthel et al, http://pewrsr.ch/2mrnTRH Source: Gottfried& Shearer, http://pewrsr.ch/2lTpstQ
N=2035
N=4654

25. Celebrity Opinion Matters
Source: Twitter.com

26. Where are healthcare’s voices?
Group % on
Twitter
Followers Tweets % on
Facebook
Likes % on
YouTube
State Medical
Societies
90%
1094 (0-
36116)
1540 (0-
28493)
84%
478 (0-
7934)
26%
State Hospital
Associations
82%
1524 (0-
10462)
1067 (0-
28549)
50%
489
(0-13267)
34%
Natl. Orgs 98%
15672 (0-
875K)
6434
(0-21116)
92%
21190
(0-556K)
92%
Hospitals 100% 10562 (562-
1.26M)
7251 (474-
29197)
98%
24393
(0-1.5 M)
100%
Industry 96%
22298
(0-926K)
2758
(0-40514)
70%
33057
(0-6.97M)
86%
Source: Matthew Katz, Feb 2017 (unpublished)
N=250 organizations, 50 each category
- Data collected Feb 2016

27. Information Overload
Jessica Hagy, thisisindexed.com, 10/9/2009

28. Overload is common
 More access = less overload
 27% in 200620% 2016
 Big divide by
 education (44% ≤HS vs. 24% College+)
 income (46% <$30K vs. 27% ≥$75K
# Access
Modes
Overload Trouble finding
information
Confident in ability to
find information
0 37% 50% 30%
1 25% 47% 76%
2 14% 35% 91%
3 14% 24% 97%
Pew Internet, http://pewrsr.ch/2mjqOyI
Access = broadband, tablet, mobile phone N=1520

29. Cancer information overload (CIO)
 HINTS survey of 6369 subjects in 2003
 148-item survey
 3011 cancer information seekers
 62% with personal or family history of cancer
 91% w/health insurance
 75% 35+ years old
 68% women
 Logistic regression evaluating CIO
Kim et al, Information Res 2007

30. Univariate Predictors of CIO
Variable Higher risk of CIO X2
p-value
Education ≤ High school vs Some College vs
College grad
45.3 <0.001
Household income <$25K vs 25-50K vs >50K 21.3 <0.001
Employment Out of work, Retired vs Employed/Student 19.2 <0.01
Perceived
health status
Poor vs Good vs Excellent 24.0 <0.001
Depression High vs Moderate vs None/Low 30.5 <0.001
Media attentiveness Low vs High 10.5 <0.001
Knowledge about
cancer
Low vs High 15.3 <0.001
Cancer literacy Low vs High 100 <0.001
Concern re: quality of
cancer information
Some/Strong vs Little/None 95.3 <0.001
Search expertise Low vs High 101.1 <0.001
Search Frustration High vs Low 76.3 <0.001
Kim et al, Information Res 2007

31. Multivariate Predictors of CIO
Variable Odds Ratio p-value
Education (any college vs none) 0.62 (0.38-0.86) <0.001
Concern about information quality
(high vs low) 1.61 (1.41-1.81) <0.001
Search expertise (high vs. low) 0.64 (0.42-0.87) <0.001
Cancer literacy (high vs low) 0.55 (0.31-0.79) <0.001
Kim et al, Information Res 2007
Caveat: Older data, before social media

32. You are what you
Surf Share
flowingdata.com

33. You aren’t anonymous
 Internet searches may
expose your
information
 65% had tracking
elements, avg 6-7
 Result = exposure to
targeted ads (DTCA)
Entity Has 3rd
party
tracking
Shares search
terms w/3rd
parties
New York Times Yes Yes
Fox News: Health Yes Yes
Drugs.com Yes Yes
Men’s Health Yes Yes
Health.com Yes Yes
Weight Watchers Yes No
WebMD Yes No
Nat’l Institutes Health No No
FDA No No
CDC Yes No
Nat’l Cancer Institute Yes No
PubMed Yes No
MedlinePlus Yes No
Medscape No No
MedicalNewsDaily Yes Yes
Mayo Clinic No No
NEJM No No
JAMA No No
JAMA Internal Medicine No NoHuesch MD, JAMA Internal Med 2013

34. De-Anonymity on Social Networks
 Can link browsing
history to social media
profiles
 72% success in de-
anonymizing 374
people
 86% with 50-75 URLs
 71% with 25-50 URLs
 Easier with G+,
Facebook
Geekculture.com, http://bit.ly/2lJzoWa Su J et al, World Wide Web conference 2017

35. Micro-targeting your biases for $
Source: Forbes.com

36. DTCA undercuts Provider Trust
 Survey at Dana-Farber of 348 patients w/breast,
hematologic malignancies
 86% were aware of cancer-related direct-to-
consumer advertising (DTCA)
 21% via internet vs. >2/3 for TV, magazine
 Ads were easy to understand (89%) but
 11% less confident in their provider
 Only 17% discussed DTCA with treating clinician
Abel et al, J Clin Oncol 2009

37. We are not innocent
 Cancer centers: $173M on ads
in 2014
 35 NCI-cancer centers:
$900 - $13.9M
 Ads highlight benefits more
than risks (27% vs 2%)Vater et al, Annals Int Med 2014
Vater et al, Annals Int Med 2016
Organization $M in 2014
Cancer Treatment Ctrs of
America
101.7
MDACC 13.9
MSKCC 9.1
Fox Chase 3.5
Texas Oncology 3.4

38. Possible Impact of #Ryancare*
 Poor have less money to
afford better access
 Less iPhones = less access
 esp. non-white, lower
income, <HS education
 As people get sicker, more
prone to anecdotal
information
 More digital targeting of
wealthier patients for $
 Employers get your genetic
health information
 GINA repeal, no replace?
* #Ryancare = House GOP bill, American Health Care Act, 3/12/17

39. What patients and doctors* deserve
Mr. John Doe ( General Manager )
Source: subatomicdoc, Flickr.com
Any social media tool should improve or preserve this covenant

40. Hippocrates Maimonides
“I will use treatment to help the
sick according to my ability and
judgment, but never with a view
to injury or wrong-doing”
“Into whatsoever houses I enter,
I will enter to help the sick”
“Grant me the strength, time
and opportunity always to
correct what I have acquired,
always to extend its domain;
for knowledge is immense
and the spirit of man can
extend indefinitely to enrich
itself daily with new
requirements.”
Your oath holds true online,
wherever you extend your domain

41. What the Public Expects of Us
• Quality as clinician
• Workmanship
• Citizenship
Professionalism based upon
• Confident
• Reliable
• Composed
• Accountable
• Dedicated
Doctors* expected to be
* Applies to all professionals
Chandratilake et al, Clin Med 2010

42. We are trusted
 People may connect
better with people, not
organizations
 Individuals’ voices can
humanize
 Clinical information
 Research news
 Institutional messages
 Nurses #1 for 15 years
straight

43. What can we do?
 Individually
 Listen
 Demonstrate integrity
 Simplify access
 Share the truth effectively
 Collectively
 Organize the internet
 Organize ourselves
 Inoculation

44. Listening starts with your patients
 Ask if they’ve been online at the time of consultation
 Do a health information review of systems
 http://bit.ly/2mQxFNo
 Listening helps you understand how to talk in plain
language, not medical-ese

45. Listening Well = Diversity + Civility
 Learn from
 Cancer patients with no medical
background
 People who fundamentally
disagree with you
 Interacting only w/ similar
people = confirmation bias silo
 Avoid coming across as
 Elitist
 Biased
 Intolerant of other opinions
 Out of touch

46. Demonstrate Integrity
 Ethics before metrics
 Online should represent
our best selves
 Use digital tools, don’t be one

47. Humility Saves Lives
Simon Wardley, blog.gardeviance.org

48. More Honey, Less Vinegar
 Calm, Respectful
 Avoid trash talk
 Initiating
 Responding
 Haters be haters
 Don’t become one
 Don’t feed the trolls
Tom Brady, circa 1998

49. Focus
 Pick one topic you would
defend in any forum
 Patient education
 Genetic testing for breast cancer
 Trials for N1 prostate cancer
 Supportive care
 Patient-centered works better
than professional-centered

50. Transparency
 86% of NCCN authors have
industry support
 Mean $10K general payments
 Mean $230K research funding
 83% of advocacy nonprofits
have industry funding
 37% focused on cancer
 36% have industry executive
on governing board
 Oncologists using Twitter
more likely to have COIs
@charlesornstein et al, http://bit.ly/Dollars4Docs
Mitchell et al, JAMA Oncol 2016
McCoy et al, NEJM 2017
Tao et al, JAMA Int Med 2017

51. Simplify Access, Lessen Overload
 Curate content for
your patients with a
single link
 Pick sites that don’t
track
 Improves trust
Source: https://www.one-tab.com/
Real source: Patricia Anderson, @pfanderson

52. Communicate Truth Effectively
Starts by listening well
Plain language, not
medical-ese
Learn mechanics of
marketing
Tell stories…but careful if
about your patients
Stick to the truth!
 Libel is a “thing”
Pamela Wible, idealmedicalcare.org http://bit.ly/2mTD7iD

53. Continuing Medical Education
New University of Washington course

54. Speak Truth to Power...with Data
Source: Twitter.com

55. Present Information Clearly
Define key actionable
decisions
Provide data visually
Test and use evidence-
based methods
Zikmund-Fisher et al, Med Decis Making 2010
Fagerlin et al, JNCI 2011

56. Organizing the Internet for Health
Internet
Wild
West Health
Information
Nature’s laws affirm
instead of prohibit. If you
violate her laws you are
your own prosecuting
attorney, judge, jury and
hangman.
- Luther Burbank

57. Hashtags on Twitter
 Used to identify specific
data
 Twitter started using for
trending topics in 2010
 “Narrowcasting” on a
channel – but interactive
 Can coordinate live chats
on a specific topic
Source: weknowmemes.com http://bit.ly/1lwUQ7S

58. #bcsm – Breast Cancer & Social
Media
 Weekly live Twitter chats since July 4, 2011
 Organized by two advocates, breast surgeon
 Focus on advocacy, survivorship, support,
metastatic breast cancer, new research

59. Symplur.com, http://bit.ly/1cAmuR7New chat+tag = #gencsm for genetic cancers/cancer risk

60. Cancer-Specific Content on
Twitter
 High signal:noise ratio
 760K tweets, 117K users
Katz et al, JAMA Oncol 2016
* Katz et al, unpublished via Symplur.com
 Update* = 1.33 M tweets by 190K
Twitter users
 ~681K (51%) shared hyperlinks to
more information

61. Organizing Ourselves
 Cancer professionals can
curate, support online
health information
 Develop virtual teams
 #DoYourJob

63. http://bit.ly/1w01D3D

65. Twitter at Annual Meetings, 2016
Matthew Katz, Symplur.com

66. Share beyond the meeting
Bik HM, Goldstein MS. PLOS Biol 2013

67. Fake News Vaccination
 Tested what inaccurate
‘countermessages’ spread
misinformation on climate change
(N=1000)
 Randomized survey to assess if
sharing scientific consensus
could counteract misinformation
 2167 surveyed
 Covered 20 topics, only climate
change topic randomized
 Pre and post test on 0-100 scale
for confidence in opinion
Van der Linden et al, Global Challenges 2017 http://bit.ly/Inoculate

68. Fake News Vaccination
 Consensus,
countermessage had
expected effect
 Neutralize each other given
together
 Inoculation message worked
 More detail = more effective
 Republicans bigger
response to consensus
alone but two together =
negative, not neutral
 Democrat, Independent
behaved similar to generalVan der Linden et al, Global Challenges 2017 http://bit.ly/Inoculate

69. Tyranny of Fake News if We’re Silent
 Should be tested with
health information
 Can’t eliminate the
negative
 Must accentuate the
positive

70. Legitimate risks, not enough to stop us
QuantiaMD.com, 2011 http://bit.ly/OKR00w

71. Derivative Benefits of Doing Good
Online engagment may help you:
 Coordinate Care
 Collaboration
 Networking
 Education
 Career Opportunity
 Reputation Management
All are secondary to helping your patients and covenant of trust

72. Summary
Cancer patients deserve reliable
health information
Fake or inaccurate news is
widespread
Health care professionals are
trusted by the public
We can communicate better, in
clinic and online
More research, teamwork needed
“The secret of the care of the patient
is in caring for the patient” – Francis Peabody

73. Thank You
 Dr. Ted Lawrence, Dr. Reshma Jagsi, Stephanie Carroll
 Patricia Anderson
 Hashtag friends and research collaborators

74. Questions?
You’re invited to contact me:
 Twitter: @subatomicdoc
Slide deck available with others on Slideshare
http://bit.ly/subatomicdocTalks