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eHealth, electronic data capture & citizen science
in healthcare: implications for clinical trials
1/39
Jeremy Wyatt DM FRCP ACMI Fellow
Leadership chair in eHealth research,
Leeds university
With thanks to Dr Shiva Sathanandam, Institute
of Digital Healthcare, Warwick University
Agenda
Definition of eHealth
Three challenges:
1. Studying eH as an intervention: some examples
of eH studies and potential risks associated with
eH interventions
2. Using eH to support clinical trials
3. How might patients use these methods to
conduct their own clinical trials ?
Summary and conclusions
2/23
eHealth / health informatics
Aim: to improve use of information in health, social & self care
Related terms:
• mHealth, Connected health
• Telehealth, telemedicine
• Digital healthcare
• Cybermedicine, cyberhealth
Focus is on:
• Information,
• Communication, and
• Decisions of clinicians, patients, public
Cluster RCT of GP teledermatology to prevent
unnecessary referrals in 560 patients
With Depts. of Medical Informatics and Primary Care, AMC Amsterdam
Instant messaging triage by NHS Direct
nurses for deaf people
The range of eH interventions
Remote consultation by phone, Skype,
videoconference
Interactive programmes / DVDs. eg for CBT
Automated phone / SMS reminders
Tailored msgs or emails for health promotion
Web sites:
• Standard information eg. NHS Choices
• Personalised information eg. My Diabetes; stroke risk
• Interactive “serious” games
• Immersive environments – Second Life
• Virtual / augmented reality
Social media & forums, eg. SharpTalk
Apps and devices including some or all of the above 6/23
Medicom medication monitor
“Persuasive technology” – an RCT
Persuasive features:
1. Domain name uses https security, .dundee.ac.uk domain vs .com
2. University Logo
3. No advertising
4. References
5. Address & contact details
6. Privacy Statement
7. Articles are all dated
8. Site is certified (W3C and Health on the Net
RCT results - joining the NHS organ
register
889/25000 students recruited in 5 days to internet trial
Same joining rate (38%) in persuasive & control groups
Overall, 336 joined NHS organ register, including:
• 126 (49%) of 260 blood donors (HR 1.46, p=0.02)
• 65 (38%) of 173 who know a donor/recipient (NS)
• 68 (23%) of 296 who initially said “maybe”
• 22 (10%) of 232 who initially said “no” !
Interpretation:
• Fogg’s guidelines do not apply in this setting ?
• NHS should target young blood donors
Funded by NHS Chief Scientist Scotland Nind et al, JMIR 2012 (submitted)
Neuromarketing
Methods include: eye tracking, galvanic skin response, functional
MRI, facial recognition via web cam
Old
design
New
design
Telehealth devices
Implanted CardioMEMS sensor & transmitter in distal branch of descending PA
External device sending data to call centre; on screen questions and chart
Tele-health for people with
long term conditions
37 RCTs measuring impact of TH on heart
failure mortality: average 18% lower
Potential adverse effects of
using the internet
Internet phenomenon Adverse effect
Misleading / biased
website, risk calculator
Poor self care decisions; misplaced pessimism / optimism
Viruses Loss of privacy; deletion of data; threat of blackmailing
Trojans eg. keystroke
loggers
Fraudulent access to internet banking details
Addiction to eg. Second
Life
Debt (Linden Labs dollars); cyber widowhood
Flaming by trolls Bullying, anxiety, depression, harm to internet persona;
suicide
Social media eg. Friends
Reunited
Marital disharmony / break up
Forums on anorexia,
suicide
Distorted perspective, self harm
Forums on alternative
therapies
Exposure to poisons (oil of wormwood); delays in seeking
allopathic medicine
12/23
Remote robotic surgery ?
13/23
eH and the research process
Define sample
Screen Recruit Consent Baseline
data Intervene
14/23
Online
consent
Online
intervention
Remote
monitoring
Online
ADR report
Online
recruitment
Data / text
mining
Email / SMS
reminders
Is SMS data capture reliable & valid for
research in young mothers ?
Theory: young mothers are digital natives but very busy
Sent msgs to 350 young mothers in Tayside on infant
feeding every 2 weeks; free SMS responses
Reliability: compared SMS responses to:
• Duplicate msgs in 48 women 1 day later
• Phone calls to 62 women
Validity: compared SMS responses to:
• Health visitor records at 2 weeks
• Other factors correlated / not correlated with feeding method
Funded by NHS Scotland Chief Scientist
Whitford H et al, JAMIA 2012
Some confounders in
internet-based trials
These can lead to Type 1 or Type 2 errors:
• Checklist effect
• Data collection biases
• Hawthorne Effect
• Contamination
• Placebo effects
See chapter 8 in F&W 2nd edition
16/30
Consequences of internet based
studies for researchers
17/39
Pros Cons
Novel, zero cost, personalised
interventions
(Pilot first face to face to test safety)
Do they generalise to real life behaviour ?
Wider reach to participants Risk of cyberdivide (Apps, Smart TVs...)
Who regulates outside UK ? (EMEA)
Reduced opportunity for FTF counselling
Faster study accrual Unknown denominator (clickable link in email ?)
Reliable replication of intervention Unknown participant characteristics (FTF visit)
Collect data more frequently,
check data as it is collected
Unverifiable participant outcomes (home device,
FTF visit)
Study data ready to analyse Possible to falsify data (electronic signatures)
Allows rapid cycle research eg.
MOST-SMART
Allows anyone to research and publish anything
(an advantage ?)
Data ownership unclear; processing may occur
outside EU (specify EU server farm, not Cloud)
Health Citizen science &
“participatory medicine”
27% of Americans tracked own health data online, 18%
sought others with same condition [Pew Internet 2011]
Health social networking: MedHelp [12M visits / month],
PatientsLikeMe, TuDiabetes, CureTogether, Asthmapolis,
DailyStrength, 23andMe, QuantifiedSelf, DIYGenomics...
Insights:
• Near immediate speed at which findings can be tested and applied
• Researcher- and participant-organised research; diverse intended
outcomes, levels of rigor
• “Large-scale parameter-stratified cohorts” - great potential for
research beyond disease to personal ised prevention
• Buzz words: bio-citizenry, crowd funding, individual experimentation,
Health Camp, community computing...
See: Swan M. Crowd sourced health research studies. JMIR 2012; 14(6): e46
18/23
Quantified Self studies
QS: 28 founder members in SF 2008, 5524 in 42 groups
early 2012
Butter Mind study – RCT with 45 people, showed that
eating 60g of butter / day improved speed of calculation.
Methods unclear, no controlling for IQ / education etc.
Reported in blog 2010
Blueberry study – running since 1999, hundreds of
participants, said to show 1% increase in online word
recall exercises. Pub online / conf posters.
Use Genomera study platform – eBay for studies – post on
it & seek participants. Althea similar.
19/23
Patient-led Citizen science
A group of people with asthma “meet” via FaceBook, decide
to answer the question: “What happens if we take
prednisolone 40mg for 15 days instead of 5 ?”
They can:
• Define eligibility criteria
• Randomise themselves
• Purchase drugs from online pharmacies
• Measure & record end points (PEFR, admissions) using
Google Docs spreadsheet / Survey Monkey
• Collaborate on data analysis
• Publish their results online
20/23
Patients Like Me lithium study
Background: promising Italian study (16 ALS cases, 28 controls)
PLM member with ALS recruited 348 other members to try Li off
label, with doctor’s support
• No difference at study end: 149 took Li for 2m, 78 for 12m
• Confirmed in later researcher-organised comparison of 149 pts vs. 447
controls & in later RCT
Why citizen science ? Pts decided on & designed study, sought
drug, made own measures; then prompted researchers to carry
out case control study & RCT
Other PLM studies on eg.:
• Improved measures for ALS, MS
• ALS aetiology (limb use)
• Reasons for low participation in ALS studies
• Pathological gambling in ALS 21/23
Citizen Scientist accuracy & biases
Identification of non-native plant species [Jordan, Envir Man 2012]:
• 119 volunteers over 3 years, trained to count / press samples
• 97% accurate overall on 13 species – but only 50% for 3 rarer species
• Accuracy per volunteer 54%; 70% for professionals not trained on this task
Crowd sourced water level data from 17 sites via SMS [Lowry 2013]:
• 130 msgs sent by 68 observers: 85% sent just 1 SMS
• “Dr Smith Effect” - one phone sent 60 SMS relating to same meter
• 113 of 130 (87%) readings usable
• RMS error in 19 observations compared to telemetry: 0.016 feet [!]
• Location bias – most obs. nr beaver dam
Weekend bias – migratory bird arrival reports 32% more likely on
weekend days [Courter, Int J Biometerology 2012]
Geographical differences in butterfly reporting – more species
per volunteer, per day in NY vs. Chicago [Matteson 2012]
Biased detection of bird mortality by site – deaths at bird
feeders / in nest boxes overestimated 3X [Cooper 2012]
22/23
Potential pros and cons of
patient-run trials
Trial aspect Pros Cons
RCT hypothesis Real patient questions May not be original [“Us too” studies ?]
Likely to be pragmatic
cf. explanatory
May not be theory-based
Participant
recruitment, follow up
Faster wider reach ?
FU more complete ?
Volunteer effect: generalises to others?
Unknown denominator
Intervention uptake Enthusiastic - if rand.
to intervention group
Is intervention reliably replicated ?
Risk of contamination [Zelen design]
Outcome measures Real PROMs; data
often open, identified
May not be reliable, valid
Analysis of results Likely to be rapid,
focused
Risk of data dredging [pre-pub protocol,
triple blinding]
May ignore threats to validity
Trial results Ownership = uptake ? NIH effect in other groups
Other aspects Less expensive
Public engagement
Tackle new questions
May not be publishable
Risk of patient-initiated fraud ?
Risk of publication bias 23/23
Summary & conclusions
1. eHealth = healthcare at a distance
2. Benefits of eH: more frequent interaction, tailoring,
multimedia, social support – but has side effects
3. We need eH RCTs to help develop a theoretical base, study
impact on quality, safety, equity of access, resource use etc...
4. We can use eH methods to support & improve drug trials
5. Patient-designed and run RCTs are emerging: we should
engage with & help improve this health citizen science
6. Let us embrace eH and regulate proportionately, where
risks outweigh benefits [UK Better Regulation Task Force]
24/23
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