This document discusses consumer health informatics, which analyzes consumers' needs for health information, studies how to make information accessible to consumers, and integrates consumer preferences into medical information systems. It provides definitions of consumer health informatics from various sources and discusses how it relates to public health informatics. It also outlines topics covered in a textbook on consumer health informatics, including empowering consumers and the role of the internet in potentially "disintermediating" health professionals by providing consumers direct access to information.

1. Associate Professor Department of Health Policy, Management and Evaluation, University of Toronto; Senior Scientist , Centre for Global eHealth Innovation, Division of Medical Decision Making and Health Care Research; Toronto General Research Institute of the UHN, Toronto General Hospital, Canada Visiting Professor, Faculty of Behavioral Sciences University of Twente, NL Gunther Eysenbach MD MPH Gunther Eysenbach MD MPH Consumer Health Informatics Consumer Health Informatics

3. Eysenbach G: Consumer health informatics. BMJ 2000;320:1713-16

16. Patient data External evidence General health information Personal health information Literature Mass Media Internet Health Record relevant Information Patient Patient accessible electronic health records Medical knowledge Disintermediation Physician (health professionals, librarians) as infomediary Eysenbach G, Jadad AR. Consumer health informatics in the internet age. <URL: http://www.jmir.org/2001/2/e19/>

19. Canada Internet Access Statistics Source: Statistics Canada

20. Ministry of Health, Australia, http://www.health.gov.au/healthconnect/pdf_docs/ehr_pta.pdf

21. What is the prevalence of health-related searches on the web? Eysenbach G, Köhler C. What is the Prevalence of Health-related Searches on the World Wide Web? Qualitative and Quantitative Analysis of Search Engine Queries on the Internet. Proc AMIA Annu Fall Symp ; 2003: 225-229 Eysenbach G, Köhler C. Health-Related Searches on the Internet JAMA , Jun 2004; 291: 2946.

24. “ Screenscraping” script Database

25. An automatic scoring method (“Google score”) to determine the “health-relatedness” of a query Eysenbach G, Köhler C. What is the Prevalence of Health-related Searches on the World Wide Web? Qualitative and Quantitative Analysis of Search Engine Queries on the Internet. Proc AMIA Annu Fall Symp ; 2003: 225-229 For example, the word house (entered as “+house” into Google) is found 186 Million times in Google, if combined with the word health (“+house +health”) we find 40.7 Million hits; the resulting Google score is 40.7/186=21%. The word hospital is found 54.5 Million times on Google, if combined with health we find 28.3 Million hits; the resulting Google score is 28.3/54.5=51.9%.

27. Breakdown of health-related search engine queries by category Eysenbach G, Köhler C. Health-Related Searches on the Internet JAMA 2004; 291:2946

31. Daily searches on Google.ca for “flu” or “flu symptoms”

32. Infodemiology: Tracking demand for health information for syndromic surveillance

34. “ Infodemiology” the epidemiology of information Describing and analyzing determinants and distribution of health information & communication and its impact on populations The science of distribution and determinants of disease in populations Epidemiology Public Health Professionals Policy Makers Policy Decisions Population Health Status The notion of “infodemiology” (measuring demand and supply of health information and drawing conclusions for public health) G. Eysenbach. Infodemiology. American Journal of Medicine , 2002;113(0):763-765 Publicly available Information/ICT

35. “ Infodemiology” the epidemiology of information Describing and analyzing health information & communication and its impact on populations Demand Metrics Supply Metrics Gunther Eysenbach Infodemiology: the epidemiology of (mis)information American Journal of Medicine , 2002;113(0):763-765

37. “ Infodemiology” the epidemiology of information Describing and analyzing health information & communication and its impact on populations Demand Metrics Supply Metrics Gunther Eysenbach Infodemiology: the epidemiology of (mis)information American Journal of Medicine , 2002;113(0):763-765

38. Global Public Health Intelligence Network (GPHIN) GPHIN monitors global media sources (such as news wires and web sites ), then gathers and disseminates relevant information on such topics as disease outbreaks, infectious diseases, contaminated food and water, bio-terrorism and exposure to chemical and radio-nuclear agents, and natural disasters. It also monitors issues related to the safety of products, drugs and medical devices.

39. One motivation: Metrics for Achievement of Public Health Policy Objectives http://www.healthypeople.gov

42. Quality of Health Information on the Web

43. &quot;Be careful about reading health books. You may die of a misprint.&quot; ~ Mark Twain

46. Eysenbach G, Powell J, Kuss O, Sa ER. Empirical studies assessing the quality of health information for consumers on the World Wide Web: A systematic review. JAMA 2002; 287: 2691-2700 Meta-analysis of information quality on the web

47. 100% 0% Inaccurate / non-evidence based information on the web Systematic review of studies evaluating health information on the web (Eysenbach et al., 2002. JAMA 2002; 287: 2691-2700 ) n=1781 websites 27 studies

48. 100% 0% Inaccurate / non-evidence based information on the web n=1781 websites 27 studies Cancer ~5% inaccurate Systematic review of studies evaluating health information on the web (Eysenbach et al., 2002. JAMA 2002; 287: 2691-2700 )

49. 100% 0% Inaccurate / non-evidence based information on the web n=1781 websites 27 studies Nutrition ~45% inaccurate Diet ~89% inaccurate Systematic review of studies evaluating health information on the web (Eysenbach et al., 2002. JAMA 2002; 287: 2691-2700 )

50. „ Technical“ (disclosure / transparency) consensus quality criteria for health websites JAMA 2002; 287: 2691-2700

51. BMJ Theme Issue „Quality of health information“ 9 March 2002 (Volume 324, Issue 7337)

54. Mock-up websites presented to consumers with different pictures

56. Your question (yes/no statement which you want to check): Your hypothesized answer – ( ) yes ( ) no ( ) other: Find answers: Identify answers on 3 websites and write down the URL, source, and answer (Worksheet column 1) NO – revise keywords YES NO – revise question Check credibility: Check CREDIBLE criteria for the 3 websites / sources (Worksheet column 2) Check trustworthiness: Enter the 3 sources in Google and check their reputation, i.e. see what others are saying about them (Worksheet column 3) The Internet FACCCCT checking algorithm (Find Answers and Compare – Check Credibility – Check Trustworthiness) An algorithm for consumers to check facts on the web Eysenbach & Thomson (Medinfo, 2007) YES YES YES NO NO Eliminate sources with negative reputation Eliminate sources with CREDIBLE score <=2 NO YES Step 1 Step 2 Step 3 Final answer – ( ) yes ( ) no ( ) other: Your Google keywords: Found relevant websites? Is the question “answerable”? Compare the answers: Are the three answers the same? Select the sites with the highest scores – are the answers the same? Select the remaining sites – are the answers the same?

57. URL: http://................................................................... Quote about source A: ………………………………... Deems A not reputable (-1) / neutral (0) / reputable (+1) Answer A URL: http://.................................................................... Source A: ……………………………………………………. Author A:… ……………………………………. Organization A:…………………………………...…………. Quote: ……………………………………………………...... ……………………………………………………… .. Compare answers - bottom line: ( ) no consensus ( ) consensus answer: …………………. Current : n (-1) ( 0) y (+1) References : n (-1) ( 0) y (+1) Explicit purpose : n (-1) ( 0) y (+1) Disclosure : n (-1) ( 0) y (+1) Interest conflict :n (-1) ( 0) y (+1) Balanced : n (-1) ( 0) y (+1) LEvel of evidence* : e (-1) ( 0) t (+1) CREDIBLE score:………………. Step 2: check how CREDIBLE the documents are Step 1: Enter search terms reflecting the question into Google. Find answers on multiple sites and compare results. Eliminate sites with score 2 or less, compare answers on remaining sites: ( ) no consensus ( ) consensus answer: …………………. Step 3: check the source trustworthiness (reputation) Enter source/author/organization in Google Document A Document B Document C URL: http://................................................................... Quote about author A: ………………………………... Deems A not reputable (-1) / neutral (0) / reputable (+1) URL: http://................................................................... Quote about organization A: ………………………………... Deems A not reputable (-1) / neutral (0) / reputable (+1) Reputation Score: URL: http://................................................................... Quote about source B: ………………………………... Deems B not reputable (-1) / neutral (0) / reputable (+1) URL: http://................................................................... Quote about author B: ………………………………... Deems B not reputable (-1) / neutral (0) / reputable (+1) URL: http://................................................................... Quote about organization B: ………………………………... Deems B not reputable (-1) / neutral (0) / reputable (+1) Reputation Score: URL: http://................................................................... Quote about source C: ………………………………... Deems C not reputable (-1) / neutral (0) / reputable (+1) URL: http://................................................................... Quote about author C: ………………………………... Deems C not reputable (-1) / neutral (0) / reputable (+1) URL: http://................................................................... Quote about organization C: ………………………………... Deems C not reputable (-1) / neutral (0) / reputable (+1) Reputation Score: Eliminate sites with negative reputation, compare answers on remaining sites: ( ) no consensus -> repeat search or add hits ( ) consensus answer: …………………. Answer B URL: http://.................................................................... Source B: ……………………………………………………. Author B:… ……………………………………. Organization B:…………………………………...…………. Quote: ……………………………………………………...... ……………………………………………………… .. Answer C URL: http://.................................................................... Source B: ……………………………………………………. Author B:… ……………………………………. Organization B:…………………………………...…………. Quote: ……………………………………………………...... ……………………………………………………… .. *[e=experiential, t=trials] Current : n (-1) ( 0) y (+1) References : n (-1) ( 0) y (+1) Explicit purpose : n (-1) ( 0) y (+1) Disclosure : n (-1) ( 0) y (+1) Interest conflict :n (-1) ( 0) y (+1) Balanced : n (-1) ( 0) y (+1) LEvel of evidence* : e (-1) ( 0) t (+1) CREDIBLE score:………………. *[e=experiential, t=trials] Current : n (-1) ( 0) y (+1) References : n (-1) ( 0) y (+1) Explicit purpose : n (-1) ( 0) y (+1) Disclosure : n (-1) ( 0) y (+1) Interest conflict :n (-1) ( 0) y (+1) Balanced : n (-1) ( 0) y (+1) LEvel of evidence* : e (-1) ( 0) t (+1) CREDIBLE score:………………. *[e=experiential, t=trials]

67. Chiu, Eysenbach et al. (submitted)

70. The future

72. Portable Patient Health Record PR-ICE™

73. Writing in the July 28, 2005 edition of the New England Journal of Medicine, John Halamka, M.D., chief information officer at BIDMC and Harvard Medical School and an emergency room physician, says the chip implanted in his arm would allow anyone with a handheld reader to scan his arm and obtain his 16-digit medical identifier. Any authorized health care worker can visit a secure Web site hosted by the chip manufacturer and retrieve information about his identity and that of his primary care physician, who could provide medical history details. Implantable Chips

75. http://en.wikipedia.org/wiki/Image:Web20_en.png

76. Source: http://web2.wsj2.com/

77. www.medicine20congress.com , Toronto, Sept 4-5 th , 2008

78. Medicine 2.0 (“next generation medicine”) Full paper will appear as: Gunther Eysenbach. Medicine 2.0. J Med Internet Res 2008 (in press) http://dx.doi.org/ 10.2196/jmir.1030 DOI: 10.2196/jmir.1030 Consumer / Patient Health Professionals Biomedical Researchers Science 2.0 Peer-review 2.0 Personal Health Record 2.0 Virtual Communities (peer-to-peer) Professional Communities (peer-to-peer) Health 2.0 HealthVault Google Health HealthBook Sermo WebCite CiteULike MDPIXX WiserWiki eDoctr BioWizard Dissect Medicine E-learning PLoS One BMC JMIR Wikis Blogs RSS RDF, Semantic Web Virtual Worlds Web 2.0 Technologies & Approaches Apomediation Participation Social Networking Collaboration XML AJAX Openess Revolution Health PatientsLikeMe PeerClip Connotea ALIVE HealthMap caBIG

82. EMR “ Tethered” PHR/ PAEHR “ stand-alone” PHR PHR EMR Read only Read+Write/Annotate PHR PHR © Gunther Eysenbach, CC-BY

83. EMR EMR PHR Different providers “ interconnected” PHR © Gunther Eysenbach, CC-BY PHR PHR

84. Records at Financial institutions Personal Finance Records © Gunther Eysenbach, CC-BY

85. Tang et al, JAMIA 2006

86. EMR EMR PHR Different providers Health Information is tightly protected © Gunther Eysenbach, CC-BY PHR PHR

87. What these models neglect: People want to SHARE some of their personal information Meier A, Lyons EJ, Frydman G, Forlenza M, Rimer BK How Cancer Survivors Provide Support on Cancer-Related Internet Mailing Lists J Med Internet Res 2007;9(2):e12 <URL: http://www.jmir.org/2007/2/e12/>

88. Another example for sharing personal health information

89. EMR EMR PHR PHR PHR Different providers PHR 2.0 © Gunther Eysenbach, CC-BY Community Other peoples’ PHR Other peoples’ PHR Other peoples’ PHR

90. What does this all mean for health care / eHealth (1) ? “ [People from the] Google Generation are impatient and have zero tolerance for delay, information and entertainment needs must be fulfilled immediately ( e.g. Johnson, 2006: Shih and Allen 2006)” Information Behaviour of the Researcher of the Future – The Literature on Young People and Their Information Behavior URL:http://www.ucl.ac.uk/slais/research/ciber/downloads/GG%20Work%20Package%20II.pdf. Accessed: 2008-04-09. (Archived by WebCite ® at http://www.webcitation.org/5WxqwuH4g)

93. Patient data External evidence General health information Personal health information Literature Mass Media Internet Health Record Relevant +credible Information Patient Patient accessible electronic health records Medical knowledge Disintermediation / Apomediation Physician (health professionals, librarians) as intermediary Irrelevant inaccurate Irrelevant Information “ Apomediaries”

95. Knowledge Self-efficacy Autonomy Empowerment - decreased reliance on experts Apomediation replacing the intermediary Success Failure Intermediary reliance on authorities/ experts Gunther Eysenbach. Credibility of Health Information and Digital Media: New Perspectives and Implications for Youth. In: Miriam J. Metzger & Andrew J. Flanagin (eds.). Digital Media, Youth, and Credibility. MacArthur Foundation Series on Digital Media and Learning. MIT Press 2007 www.mitpressjournals.org/doi/pdf/10.1162/dmal.9780262562324.123 Dynamic Intermediation/Disintermediation/Apomediation (DIDA) Model (Eysenbach, 2007)

96. Take two in the morning and don’t ask questions Holy land of the knowing Hole of ignorance physician patient Eysenbach G, Jadad AR. Consumer health informatics in the internet age. <URL: http://www.jmir.org/2001/2/e19/> No trespassing

97. Let me educate* you *(ex ducere = to lead out) Hole of ignorance physician patient No trespassing without professional guidance Holy land of the knowing Eysenbach G, Jadad AR. Consumer health informatics in the internet age. <URL: http://www.jmir.org/2001/2/e19/>

98. WWW email Self-support physician patient Eysenbach G, Jadad AR. Consumer health informatics in the internet age. <URL: http://www.jmir.org/2001/2/e19/> No trespassing without professional guidance

99. Welcome! Watch your step Consumer Health Informatics physician patient Eysenbach G, Jadad AR. Consumer health informatics in the internet age. <URL: http://www.jmir.org/2001/2/e19/>