E-patients Communities and Chronic Illness

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Brodeur Parnters and UNC School of Social Work -- Needs assessment and design implications of breast cancer, multiple sclerosis and Marfan syndrome health e-communities. Posted on Regulations.gov …

Brodeur Parnters and UNC School of Social Work -- Needs assessment and design implications of breast cancer, multiple sclerosis and Marfan syndrome health e-communities. Posted on Regulations.gov public docket FDA-2009-N-0441 on 12/10/09.

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  • the aim of this study was to explore commonalities and diver- gences in seeking online health information among patients in three chronic dis- ease e-communities: metastasized breast cancer, multiple sclerosis, and Marfan syndrome.

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  • 1. E-patients Communities and Chronic Illness: Needs assessment and design implications of breast cancer, multiple sclerosis and Marfan syndrome health e-communities
  • 2. Exploratory Study: Aims
    • Understand e-health information and support seeking behavior among diverse types of chronic disease patients
    • Assess patients’ preferences for Web 2.0 resources
    • Inform design of future web-based support communities
  • 3. Method
    • Interactive web-based survey (May-June 2008)
    • Recruitment targets: approximately 12 e-health communities, 9 of which responded to our initial request
    • Convenience sample: Members of 3 e-health communities: metastatic breast cancer (n=62), multiple sclerosis (n=31), and Marfan syndrome (n=35)
      • 154 unique starts/ 127 completed (82%)
    • Analyses
      • Whole group descriptive analyses
      • Planned between group comparisons
  • 4. Survey Topics
    • Participant characteristics
      • Age, gender, education, employment status,, support network characteristics
    • Self reports of chronic condition(s) and health self ratings
    • Recent Internet searches for information on own chronic condition(s) in past 30 days
    • Ease or difficulty finding information on
      • Treatments, information from experts, health-related support, and other relevant types of information
    • Activities patients would like to be able to do online to enhance their coping with chronic condition(s)
    • Willingness to have personal information shared
    • Preferences for different kinds of web functionality
  • 5. Convenience sample tapped a wide range of chronic illness experiences
    • Relatively common--rare diseases
    • Risk factors: environmental--heritable
    • Ages of onset: birth--later adulthood
    • Systems affected
    • Expected life spans
    • Sources of uncertainty
      • Difficulties in diagnosing
      • Patterns of disease progression
  • 6. Sample characteristics Characteristics % (N=127) Female 96% Adults: 40-59 y,o. 62% Euro-American 96% Education: High school diploma or higher 98% Employment Full time 31.0% Part time 9.5% Unemployed 29.4% Retired/Disabled 31.0% Health status Self rating: Fair 54.4% Chronic disease co-morbidity 39.3% >1 diagnosis
  • 7. Commonalities in e-health information and support seeking experiences
    • Few significant differences in:
      • Health information seeking experiences
        • Overall, Marfan patients reported somewhat more difficulty finding the information they needed
      • E-health community support
      • Desire to find true patient peers
      • Interest in sharing “patient wisdom” with broader healthcare community
  • 8. Results: Health information seeking N=127 Item (n=number who searched) n Fairly/Very Easy to Find % Fairly/Very Hard to Find % Current treatments 111 77.5% 22.5 % Treatment side effects 111 74.8% 25.2 % Managing multiple chronic conditions 66 57.6% 42.4% Recommendations for health care providers 53 28.3% 71.7% Clinical trials 51 62.7% 37.3%
  • 9. Results: Searching for different types of online health information and resources ( N=127) Item ( n=number who searched ) n Fairly/Very Easy to Find % Fairly/Very Hard to Find % Comprehensive health info websites 110 84% 16% Scientific articles in online journals 84 90% 10% News articles 60 69% 31% Products and services 54 57% 44% Health insurance 38 21% 79% Doctors’ presentations on the Web 33 43% 57%
  • 10. Social Contexts of e-Health Seeking: Sources of Support (N=127) Other sources: neighbors, coworkers, in-home health care providers, unspecified others
  • 11. Results: Searching for Online Social Support (N=127) Item (n=number who searched)* n Fairly/Very Easy to Find % Fairly/Very Hard to Find % HeCs for my chronic condition 105 81% 19% People going through same experiences 103 19% 81% HeCs for my combination of multiple chronic conditions 46 65% 35% People coping with depression and other chronic conditions 46 65% 35%
  • 12. Interest in Apomediated Activities (N=127) Activity (n=number of respondents) n Already doing % Interested % Unsure or Uninterested % Share knowledge with a broader e-health community 110 83% 9% 8% Buy products 110 17% 42% 41% Write or contribute to a blog 112 15% 15% 70% Create personal health profile 110 14% 32% 55% Create detailed ehealth record 110 13% 40% 48% Rate HC providers 110 7% 59% 34%
  • 13. Limitations
    • Small, convenience sample
    • Pilot survey
    • Sources of bias: gender, race, education
    • Participants were all members of e-health communities
    • Did not probe on existing social networks, Twitter, other social media sites
  • 14. Conclusions
    • Health seeking behavior was similar across diverse chronic disease groups
    • Patients in all groups want more specific, individualized and timely information
    • Most patients were interested in participating in apomediated activities, but fewer were doing them
  • 15. Verbatims: Participants value what they can learn from each other
    • Patients want : “sites that are collecting and publicizing patient recommendations for improvement of care”… “patient recommendations for doctors”… “data on underreported side effects.”
    • Patients value: “I have found the unedited, uncensored and non-statistical (e.g. anecdotal info available on [my HeC] to be as helpful or more helpful than the general sites (e.g, WebMD) because it is first hand, individual and specific.
    • Patients know the difference: “There is a glut of inspirational sites [with illness stories]. I would like to see sites that are collecting and publicizing patient recommendations for improving care…and other advocacy.”
  • 16. Patients recognize limitations, risks of “patient wisdom” and e-health resources
    • “ I don’t believe privacy could be protected [with health record data] but I would still be willing to participate.”
    • “ You will have major issues of selection bias. People who post are very different from those who don’t.”
  • 17. Implications for health e-community designs
    • Information sharing opportunities with “true patient peers”
      • Searchable, rich personal profiles
      • Presence functionality to detect members “like me”
      • Integration of social networks with PHR/EMR
      • Enablers of recruitment and formation of subgroups (e.g., combinations of chronic conditions)
  • 18. Implications for health e-community designs
    • Improved access to current research findings
      • Public access to peer-reviewed literature
      • Multimedia formats for communicating health information (i.e., YouTube videos, interactive webinars)
      • Access to research experts (webinars, Q&A)
    • Integrated research tools
      • HeC member-initiated research
      • Clinical research studies
  • 19. Implications for health e-community designs
    • Information about and access to relevant products, services, and treatments
      • HCP rating systems
      • Clinical trials
      • Contextual e-advertising
  • 20. Questions, comments or feedback?
    • All welcome!
    • Email: [email_address]
            • ameier@email.unc.edu
          • Thank you!
          • Andrea Meier, Bret Shaw, Judy Feder, & Eulàlia Puig Abril