Cancer Care in a Post Truth World

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

Cancer Care in a Post Truth World

Cancer Care in a Post Truth World

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