Health 2.0: Opportunities for
Research
Ida Sim, MD, PhD
March 8, 2011
Division of General Internal Medicine, and
Center for Clinical and Translational Informatics
UCSF
Copyright Ida Sim, 2011. All federal and state rights reserved for all original material presented in this course
through any medium, including lecture or print.
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Summary: (Traditional)
Research Informatics
• Clinical research fragmented, global, essentially
separate from clinical care
• Clinical research informatics ongoing in two worlds
– most still paper, commercial CTMSs mostly
document centered (PDFs) rather than data or
concept-centered
– moving towards modular component approach with
• standard variables (CDEs) and case report forms (CRFs)
• common computable protocol models (OCRe) and
interchange exchange standards (CDISC)
• Traditional clinical research informatics quite immature
• What new models of clinical research can informatics
enable?
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Health Care Quality
• Doing the right thing
– based on scientific evidence
• right
– without error
• to the right people
– e.g., blood pressure meds by ethnicity
• at the right time
– beta-blockers at hospital discharge for heart
attacks
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Learning Healthcare System
• Ideal US health care systems is
– “a Learning Healthcare System that is designed to
generate and apply the best evidence for the
collaborative health care choices of each patient
and provider; to drive the process of discovery as
a natural outgrowth of patient care” (IOM
Evidence-Based Medicine Roundtable)
• IT/informatics necessary to make this happen
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Current Research Approach
• Studies are expensive, difficult to conduct, 30-40% of studies
never accrue enough patients
– estimated 2 million pts needed/yr for US-based trials
– will be worse with personalized medicine
• Studies take years to answer limited questions in limited
populations
• Study designs and results are heterogenous, limiting ability to pool
findings or make summary interpretations
• Research questions don’t address combination treatments (e.g.,
ACEI and amlodipine)
• Research questions don’t track with front-line clinical needs
– no good data on mid- to long-term efficacy or effectiveness of
antidepressants
• Overall lack of relevance, generalizability, and sustainability
Moss, et al. NEJM 2011; 364(9):789-761
Crowley, et al. JAMA 2004; 291(9):1120-6
etc.
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Health Care Quality
• Doing the right thing
– based on scientific evidence
• right
– without error
• to the right people
– e.g., blood pressure meds by ethnicity
• at the right time
– beta-blockers at hospital discharge for heart
attacks
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Health Care Quality--Pt. View
• Stay healthy for as long as possible
• Take as few medicines as possible
– they all work, with fewest side effects
– at lowest cost
– for as short a time as possible
• I know what makes me worse and what
makes me better, and can do the right thing
• I have all my questions answered
• I know what other people are thinking, and I
feel supported in my overall health status
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Health Care Quality--Pt. View
• Stay healthy for as long as possible Wellness
• Take as few medicines as possible Individual
Therapeutic Precision and Cost-effectiveness,
Symptom Management
– they all work, with fewest side effects
– at lowest cost
– for as short a time as possible
• I know what makes me worse and what makes me
better, and can do the right thing Personalized
Trigger Discovery, Behavior Change Support
• I have all my questions answered Readable
References
• I know what other people are thinking, and I feel
supported in my overall health status Social Health
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
What “Learning” is Truly Needed?
• Population-level efficacy and effectiveness
– for more than just intermediate outcomes (e.g., secondary
analysis of EHRs)
– for patient-centered outcomes (symptoms, side effects)
• Therapeutic precision (best therapy for this patient)
– informed by, but not limited to, genomic treatment markers
– learning from experience (e.g., N-of-1 trials)
• How to promote and sustain behavior change
• What are individual predictors of worsening (e.g.,
depression, IBD, asthma)
• What are prevalence, natural hx, etc. even of rare
diseases?
• How to enable patients, families, communities, and
clinicians to maintain wellness and manage chronic
illness together? etc. etc.
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Outline
• Web 1.0 to 3.0
• Health 2.0 / Participatory Health / Medicine
2.0
– health information seeking
– internet-based examples
– mHealth-based examples
• Digital Divide
• “Graveyard of Successful Pilots”
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Internet = Network of Networks
nci.nih.gov myhome.com
amazon.com
“the cloud”
Main Trunk Cables
aol.com
local trunk cable pacbell.net
through Berkeley
Internet Service Provider (ISP)
medicine via DSL
or cable
ucsf.edu
itsa
LAN
dial-in to itsa.ucsf.edu via modem
March 8, 2011: I. Sim Mobile and Internet-Based Research
at home
Epi 206 – Medical Informatics
Internet vs. Web
• Internet = network of networks
– computers and cables all linked to one another
and talking to one another using protocols
– supports lots of different internet protocols
• e.g., http, ftp, smtp, https, rdf, doi, etc. etc.
• Web is the internet traffic that uses http
– servers send out information in HTML
• Hypertext Markup Language
– web browsers can decode HTML and display it
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Clients and Servers
nci.nih.gov Server myhome.com
amazon.com
“the cloud”
Main Trunk Cables
aol.com
local trunk cable pacbell.net
through Berkeley
Internet Service Provider (ISP)
medicine via DSL
or cable
ucsf.edu
itsa
LAN Client
dial-in to itsa.ucsf.edu via modem
March 8, 2011: I. Sim Mobile and Internet-Based Research
at home
Epi 206 – Medical Informatics
Telemedicine
• Provision of clinical/research services from a distance
– i.e., geographically separated synchronous traditional
care/research
– can be far (e.g., Singapore) or near (e.g., Walmart)
• Prop 1D 2006 approved $200m for telemedicine
infrastructure (ie wires) statewide
– “With Proposition 1D funds we will eventually be able to connect
our best hospitals and our best medical schools with clinics in
remote areas all over the state of California.” (Schwarzenegger)
– wiring up SFGH, Parnassus, Central Valley, etc.
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Interoperation Over the Stack
Administrative Clinical Care Research
Syntactic Semantic and Workflow
Practice Electronic Clinical Res.
Management Medical Management
Systems Record Systems
Medical Business Clinical Care Clinical Study
Data Model Data Model Data Models
Billing Standard Vocabulary Clinical
Communications Protocols (e.g., HL-7)
Physical Networking -- Telemedicine $
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Web X.0
• Web 1.0: web pages of static information with simple
links between them
– e.g., Wikipedia, NYTimes.com
• Web 2.0: people are as important as computers in
the network
– Facebook, Digg, Twitter, …
• Web 3.0 (Semantic Web)
– each data item is “tagged” with ontology terms so computer
can “understand” everything on the web
– I.e., the contents of HTML “buckets” are standardized, using
RDF (Resource Description Framework), OWL (Web
Ontology Language), etc.
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Web 2.0 Principles
• User-generated content
• Harness power/wisdom of crowds
• Openness
• Architecture of participation
• Niche markets
(P. Anderson, What is Web 2.0? JISC Tech and Standards Watch, Feb 2007)
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
User-Generated Content
• Anyone anywhere is a source of content
– YouTube, Flickr, Wikipedia. citizen journalism,
blogs, e.g.
– http://PatientsLikeMe.com/
– http://www.ganfyd.org/index.php?title=Main_Page
• Exists in parallel with Web 1.0 hierarchical
information sources
– NIH MedlinePlus
http://www.nlm.nih.gov/medlineplus/
– WebMD.com
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Power/Wisdom of Crowds
• Tapping into distributed intelligence of people
– wikipedia (as accurate as Encyclopedia Britannica)
– www.intrade.com: “stock market” for Qaddafi’s fall
– Google Flu http://www.google.org/flutrends/
– http://healthmap.org/en
• Use distributed machine and people resources
– parallel computing for cheap: donate your PC cycles to find
signs of intelligence from outer space
• http://setiathome.berkeley.edu/
• Crowdsourcing: e.g., http://www.answers.com/
– 549,800 questions in health
http://wiki.answers.com/Q/FAQ/431
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Openness
• Dimensions of openness
– open source: computer code open to all for wisdom of crowds
to improve (e.g., VistA VA EHR system)
– open access: no restrictions on use or distribution of content
– open participation: everyone can participate
• communal management, flat hierarchies, consensus emergent
decision-making
• Allows “mash-ups” of freed data
– http://www.googlelittrips.com/GoogleLit/Home.html for Aeneid,
Grapes of Wrath, user-generated road trips...
- e.g., Community Health Data Initiative
http://www.hhs.gov/open/datasets/communityhealthdata.html
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Architecture of Participation
• Network externalities concept: “the service
automatically gets better the more people use it” e.g.,
– fax machines, cell phones...the more the better
– Google search
• the more “link paths” people tread, the richer the data for the
Google search algorithm
– Amazon book ratings, Netflix ratings
• How important is anonymity for this to happen in
healthcare?
– whoissick.org/sickness/, http://www.curetogether.com/
– better epi data if everyone contributed to public health data
• 1-3% refuse to share clinical data for research
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Niche Markets
• “The web” is unlimited resource
– can service even extremely small market niches
• Shape of the web: the “long tail”
where traditional focus is
with infinitely long tail, majority of action is here
market niche/things being done
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Niche Markets in Health
• Rare diseases
– PatientsLikeMe
• Geographic, ethnic, other niches
– Russian-speaking boy scouts with ADHD in rural
Montana
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Outline
• Web 1.0 to 3.0
• Health 2.0 / Participatory Health / Medicine
2.0
– health information seeking
– internet-based examples
– mHealth-based examples
• Digital Divide
• “Graveyard of Successful Pilots”
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Online Health
• 61% of US adults look online for health info
• 52% of health inquiries are for someone other than
the searcher
• What are they doing?
– 41% read someone else's health commentary/blog
– 24% consulted rankings/reviews of doctors
– 24% rankings or reviews/reviews of hospitals
– 13% listened to a health/medical podcast
– ~6% post any content
• 90/9/1 rule (90 lurk, 9 infrequently post, 1 posts a lot)
Pew Internet and American Life, The Social Life of Health Information, Jun 2009
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Peer-to-Peer Health
• 18% have gone online to find others with
health concerns like theirs
– 1/4 of those with chronic health conditions (e.g.,
HTN, DM, heart problems, lung problems, cancer)
– transitions in health: new diagnosis, pregnancy,
wt. gain/loss, quitting smoking
• Particularly important for patients with rare
diseases
• Professionals still the go-to for technical
information
Fox, S. Peer-to-Peer Health, Pew Internet, Feb 2011
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Effect of Online Health Info?
• 60% say info affected a real-life medical
decision
• 56% say info changed their overall approach
to maintaining their health or the health of
someone they help take care of
• 38% say info affected decision whether to see
a doctor
• Internet is first source of info, but doctors still
more trusted (increasingly so)
Hesse, et al. NEJM, Mar 4, 2010
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Outline
• Web 1.0 to 3.0
• Health 2.0 / Participatory Health / Medicine
2.0
– health information seeking
– internet-based examples
– mHealth-based examples
• Digital Divide
• “Graveyard of Successful Pilots”
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
RCTs of Web-Based Interventions
• U-Can-Poop-Too Study
– http://ucp2.bht.virginia.edu/interest/study
• Stop Smoking
– https://www.stopsmoking.ucsf.edu/tc4/index.aspx?
src=UCSF
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Online Care
• Cognitive behavioral therapy for sleep
– www.shuti.net
• 15 min. sessions of Cognitive Bias Modification
instead of hours of talk therapy
– “all it requires is sitting in front of a computer and using a program
that subtly alters harmful thought patterns” (Economist, Mar 5,
2011, p. 85)
• Counselling
– http://www.liveperson.com/experts/professional-counseling/
• Virtual MD visits include live video chat and instant
messaging
– https://platform.hellohealth.com/PublicPortalServlet/DoctorsList.jsp
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Miscellaneous
• Gaming for health
– http://www.humanagames.com/#/home/
– http://www.gamesforhealth.org/
• Simulation and virtual reality
– http://secondlife.com/?v=1.1
• Clinician-facing
– askHermes http://www.askhermes.org/
– http://dxplain.org/dxp/dxp.pl
– http://www.isabelhealthcare.com/home/default
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Social Computing in Health
• Online support groups and networks
– e.g., http://www.patientslikeme.com/
• Exemplifies
– architecture of participation
– user-generated content
– wisdom of (peer) crowds
– niche markets for rare diseases
• What else is going on out there?1
– 41% use social media to find health info (94% use Facebook, 32%
YouTube, 18% MySpace or Twitter)
– 1/4 respondents said info “likely or very likely” to impact future
health decisions
– average age of social media for health user = 41, higher income
1National Research Corp survey, Feb 2011,
http://hcmg.nationalresearch.com/public/News.aspx?ID=9
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Outline
• Web 1.0 to 3.0
• Health 2.0 / Participatory Health / Medicine
2.0
– health information seeking
– internet-based examples
– mHealth-based examples
• Digital Divide
• “Graveyard of Successful Pilots”
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
A Phone in 73% of Pockets
147%
130%
90%
60%
75% 50%
95%
93%
A Computer in 73% of Pockets
147%
130%
90%
60%
75% 50%
95%
93%
mHealth
• using mobile
technologies for
preventive and
medical care
Corventis Piix EKG Monitor
Haiku app, for Epic EHR
AsthmaMD app
No conflicts with any product mentioned
24/7/anywhere/everyone Medicine
• Ubiquitous/pervasive computing
– small, cheap, highly networked devices, distributed
everywhere doing everything (everyware)
• http://www.ted.com/talks/eric_topol_the_wireless_fut
ure_of_medicine.html
– 00:45 to 4:15
• Embedded sensing in the home
– Kaiser Garfield Innovation Center
http://xnet.kp.org/innovationcenter/index.htm
• Environmental mapping of symptoms
– asthmamd.com mapping of PEFR of thousands of users in
real-time during Icelandic volcanic explosion
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
mHealth at Peak of Hype
Hype Cycle, Gartner Group
Outline
• Web 1.0 to 3.0
• Health 2.0 / Participatory Health / Medicine
2.0
– health information seeking
– internet-based examples
– mHealth-based examples
• Digital Divide
• “Graveyard of Successful Pilots”
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Who’s Using “ICT”?
• “ICT” = Internet and Communications
Technology
• Is/will my patient population be using ICT?
• Is Health 2.0 going to help or hurt health
disparities?
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Broadband Access
• Growth in home broadband access flat1
– 66% Americans have broadband at home
Whites African- Difference
American
2009 65% 46% 19%
2010 67% 56% 11%
• Dept. of Commerce says divide is smaller but
remains after adjustment for income and education2
• Laptop ownership about 50% for all groups
1 Home Broadband Survey, Pew Internet, August 2010
2 http://www.esa.doc.gov/Reports/exploring-digital-nation-home-broadband-internet-adoption-united-states
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
• Digital divide
– Internet use
– data from Pew Internet,
Dec 2009
• 21% of Americans do not
use Internet at all
– 48% don’t think it’s
relevant to their lives
– 60% would need
technical help getting on
the Internet
– Pew Broadband Survey,
August 2010
• 59% have wireless
access
– 47% use laptop w/ WiFi
– 40% used phone
– Pew Mobile Access, Jul
2010
Mobile Divide?
• Cell phone ownership1
– 80% among whites; 87% among AAs and Latinos
– more minorities use phone to get on Internet
• Over 75% ownership among SFGH patients
• Large minority of households are cellular only
– 9% of households in CA, 26.2% in OK in 2007-8
(CDC, Wireless Substitution, NHS Reports, Mar 2009)
1Latinos Online, Pew Internet, Sept 2010
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Social Media
• 8% of online Americans use Twitter (Pew, Dec 2010)
– 18-29 more likely to Twitter
– African-Americans (25%) and Latinos (20%) more likely than whites
(15%) to Twitter
– urban and female are other predictors
• Minorities use social media more (Tech Trends in People of Color, Pew Jan.
2011)
– Facebook via phone
• 36% Latinos 36%, Blacks 33%, Whites 19%
– Daily use of social media sites
• almost 50% of blacks, 1/3 of whites
– use social media more to learn about their own communities
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Digital Divide Not “Technological”
• Technological gap narrowing over time
– higher mobile usage in AA/Latino populations
• Hard to fill out job application on a phone
• Used for entertainment more than information
or “work”?
• Language is strong predicator
– foreign-born Latino much lower use of Internet,
English-speaking Latino equal to whites
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Outline
• Web 1.0 to 3.0
• Health 2.0 / Participatory Health / Medicine
2.0
– health information seeking
– internet-based examples
– mHealth-based examples
• Digital Divide
• “Graveyard of Successful Pilots”
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
How to Avoid Graveyard?
• Need relevance, generalizability, sustainability of ICT
“apps” and systems
• Relevance
– to those with $ (hospitals, insurers, pharma)
– to those with health / disease (patients, communities)
• Generalizability
– go beyond our 4 walls, the whole world
• Sustainability
– low development and operational cost, a cost recovery
model, maintenance and upkeep, matches workflow
– new models? “architecture of sustainability”
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Anti-depressant Efficacy
In 2005, 27 million Americans were prescribed
anti-depressants1
“…data often come from short-term (6- to 12-
week) efficacy trials that cannot show whether
treatments are effective over the medium- and
long-term”2
1Olfson, et al. Arch Gen Psych 2009;66(8):848-856
2APA Depression Guideline 2010
Learning Healthcare System
RCT of long-term
comparative effectiveness
of antidepressants in
primary care
Xing Xu 10/4/2010
427 King Rd. SF 7/21/1932
Prozac 20 mg, 1 tab PO daily, #30
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Contacted for Studies
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AntiD Study
Randomization
ePharmacy
Watch this YouTube
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consent…real-time chat
for questions…secure
sign-up for enrollment
Or at a website Masked drug(s)
AT&T
Dec 13, 2009
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Anonymization
APEX
Study DB
covariates
Large-Scale Research
In 2005, 27 million Americans were prescribed anti-depressants1
“…data often come from short-term (6- to 12-week) efficacy trials
that cannot show whether treatments are effective over the
medium- and long-term”2
Since 2005, # of subjects in all antidepressant drug trials
worldwide total <100,000 (<0.4% of 27 million)
If only 1 out of 250 antidepressant patients in the US enrolls,
would exceed total number of participants in all antidepressant
trials worldwide in last 5 years
1Olfson, et al. Arch Gen Psych 2009;66(8):848-856
2APA Depression Guideline 2010
CRC Without Walls
• Traditional clinical research centers (CRCs)
– patients came in to campus for monitoring
• Make UCSF a CRC without walls
– monitor at home, in ambient living
– use mHealth to go where health and disease are
– method to get at “phenotype” for geno-pheno,
GWAS, etc.
• Expand clinical research beyond efficacy &
effectiveness of drugs and devices to include
Implementation and Dissemination of
behavioral and system interventions
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
ICT Research Methods
• International Society for Research on Internet
Interventions
– http://www.isrii.org
• Health UnBound Evaluation Commons
– http://www.healthunbound.org/content/evaluations
-commons
• k4health mHealth Toolkit
– http://www.k4health.org/toolkits/mhealth
• mHealth data worldwide
– http://mobileactive.org/areaofpractice/Health
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics
Health 2.0 + Research Summary
• Demographic and disease trends point to
wellness and chronic care management as
priorities
• ICT can get us beyond tertiary care centers
– need to manage digital divide
• Formulate broader notion of clinical research
– build in relevance, generalizability, sustainability
– exploit Web 2.0 principles
• Generate, share, and build upon evidence-
based best practices with rapid feedback
March 8, 2011: I. Sim Mobile and Internet-Based Research
Epi 206 – Medical Informatics