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  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
Talk Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Eysenbach G: Consumer health informatics.  BMJ  2000;320:1713-16
What is consumer health informatics? ,[object Object],Eysenbach G: Consumer health informatics.  BMJ  2000;320:1713-16
Other definitions of CHI ,[object Object],http://www.webcitation.org/5M5JwNilG
Other definitions of CHI ,[object Object]
A distinct subfield of medical informatics? ,[object Object],[object Object]
Public Health Informatics ,[object Object],[object Object]
First textbook on Consumer Health Informatics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Lewis, Eysenbach, Kukafka, Stavri, Jimison. Consumer Health Informatics Springer, 2005
“ Consumers” ,[object Object],[object Object],[object Object],Brennan & Safran. Chapter 2 Empowered Consumers.  In: Lewis, Eysenbach, Kukafka, Stavri, Jimison. Consumer Health Informatics Springer, 2005
Empowered consumers ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Brennan & Safran. Chapter 2 Empowered Consumers.  In: Lewis, Eysenbach, Kukafka, Stavri, Jimison. Consumer Health Informatics Springer, 2005
Empowered consumers (2) ,[object Object],[object Object],[object Object],Brennan & Safran. Chapter 2 Empowered Consumers.  In: Lewis, Eysenbach, Kukafka, Stavri, Jimison. Consumer Health Informatics Springer, 2005
Empowerment  (political science view) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Consumerism ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Disintermediation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
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/>
What is consumer health informatics? ,[object Object],Eysenbach G: Consumer health informatics.  BMJ  2000;320:1713-16
[object Object],[object Object],Source: Pew Internet & American Life Project health seekers survey, August, 2000
Canada Internet Access Statistics Source: Statistics Canada
Ministry of Health, Australia,  http://www.health.gov.au/healthconnect/pdf_docs/ehr_pta.pdf
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.
How many searches on the web? ,[object Object],[object Object],[object Object],[object Object],Eysenbach G, Köhler C. Health-Related Searches on the Internet  JAMA  2004; 291:2946   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
 
“ Screenscraping” script Database
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%.
Demand for Online Health Information ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Eysenbach G, Köhler C. Health-Related Searches on the Internet  JAMA  2004; 291:2946   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
Breakdown of health-related search engine queries by category  Eysenbach G, Köhler C. Health-Related Searches on the Internet  JAMA  2004; 291:2946
Text mining of health-related searches ,[object Object],[object Object],[object Object],[object Object]
Methods ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
Daily searches on Google.ca for “flu” or “flu symptoms”
Infodemiology: Tracking demand for health information for syndromic surveillance
 
“ 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
“ 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
Population Health Technology ,[object Object],[object Object],Eysenbach G SARS and Population Health Technology J Med Internet Res 2003;5(2):e14 <URL: http://www.jmir.org/2003/2/e14/>
“ 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
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.
One motivation: Metrics for Achievement of Public Health Policy Objectives http://www.healthypeople.gov
S. Lawrence and C. L. Giles. Accessibility of information on the web  Nature  400 (6740):107-109, 1999. ,[object Object],[object Object],[object Object],[object Object],[object Object]
What is consumer health informatics? ,[object Object],Eysenbach G: Consumer health informatics.  BMJ  2000;320:1713-16
Quality of Health Information on the Web
&quot;Be careful about reading health books. You may die of a misprint.&quot; ~  Mark Twain
 
 
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
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
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 )
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 )
„ Technical“ (disclosure / transparency) consensus quality criteria for health websites JAMA  2002; 287: 2691-2700
BMJ Theme Issue „Quality of health information“ 9 March 2002  (Volume 324, Issue 7337)
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Eysenbach G, Köhler C.  BMJ  2002; 324: 573-577   How do consumers search for and appraise health information on the World-Wide-Web? Qualitative study using focus groups, usability tests and in-depth interviews
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Credibility criteria applied by consumers Eysenbach G, Köhler C.  BMJ  2002; 324: 573-577
Mock-up websites presented to consumers with different pictures
Is a health website CREDIBLE? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Eysenbach G. Infodemiology: The epidemiology of (mis)information.  Am J Med 2002;113(0):763-765
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?
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]
What is consumer health informatics? ,[object Object],Eysenbach G: Consumer health informatics.  BMJ  2000;320:1713-16
Where clinical IS and consumer health informatics meet ,[object Object],[object Object],*Markle Foundation: Personal Health WG Final Report http://www.webcitation.org/5M5CP3Q3C
 
 
 
 
 
 
 
Chiu, Eysenbach et al. (submitted)
What can we learn from studies? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],J Med Internet Res 2004;6(2):e12 http://www.jmir.org/2004/2/e12/
Research Issues Patient Portals ,[object Object],[object Object],[object Object]
The future
The Future: Trends ,[object Object],[object Object],[object Object]
Portable Patient Health Record  PR-ICE™
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
 
http://en.wikipedia.org/wiki/Image:Web20_en.png
Source: http://web2.wsj2.com/
www.medicine20congress.com , Toronto, Sept 4-5 th , 2008
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
 
 
 
EMR “ Tethered”  PHR/ PAEHR “ stand-alone”  PHR PHR EMR Read only Read+Write/Annotate PHR PHR © Gunther Eysenbach,  CC-BY
EMR EMR PHR Different providers “ interconnected”  PHR © Gunther Eysenbach,  CC-BY PHR PHR
Records at Financial institutions Personal Finance Records © Gunther Eysenbach,  CC-BY
Tang et al, JAMIA 2006
EMR EMR PHR Different providers Health Information is tightly protected © Gunther Eysenbach,  CC-BY PHR PHR
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/>
Another example for sharing personal health information
EMR EMR PHR PHR PHR Different providers PHR 2.0 © Gunther Eysenbach,  CC-BY Community Other peoples’ PHR Other peoples’ PHR Other peoples’ PHR
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)
What does this all mean for health care / eHealth (1) ? ,[object Object],[object Object],[object Object],[object Object],[object Object]
What does this all mean for health care / eHealth (2) ? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
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”
Apomediation defined ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Eysenbach,  http://hdl.handle.net/1807/9906
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)
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
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/>
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
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/>
- Tailored Patient Education - Online Health Risk  Assessments ,[object Object],[object Object],[object Object],Health Care Providers ( Networked  ) Distributed, interoperable EHR ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],- Email follow-ups - Mobile Health reminders - Online Rx refills - Online Scheduling for Office Visits - Waiting list management Quality ratings eHealth Care 2.0 Web Search Provider Selection  based on eRatings and preferences
Thank you! ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Dr G. Eysenbach,  Email:  [email_address]  or @gmail.com, Journal: www.jmir.org

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Eysenbach: Consumer health informatics

  • 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
  • 2.
  • 3. Eysenbach G: Consumer health informatics. BMJ 2000;320:1713-16
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  • 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/>
  • 17.
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  • 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.
  • 22.
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  • 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%.
  • 26.
  • 27. Breakdown of health-related search engine queries by category Eysenbach G, Köhler C. Health-Related Searches on the Internet JAMA 2004; 291:2946
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  • 31. Daily searches on Google.ca for “flu” or “flu symptoms”
  • 32. Infodemiology: Tracking demand for health information for syndromic surveillance
  • 33.  
  • 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
  • 36.
  • 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
  • 40.
  • 41.
  • 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
  • 44.  
  • 45.  
  • 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)
  • 52.
  • 53.
  • 54. Mock-up websites presented to consumers with different pictures
  • 55.
  • 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]
  • 58.
  • 59.
  • 60.  
  • 61.  
  • 62.  
  • 63.  
  • 64.  
  • 65.  
  • 66.  
  • 67. Chiu, Eysenbach et al. (submitted)
  • 68.
  • 69.
  • 71.
  • 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
  • 74.  
  • 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
  • 79.  
  • 80.  
  • 81.  
  • 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)
  • 91.
  • 92.
  • 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”
  • 94.
  • 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/>
  • 100.
  • 101.