consumer health data—potential, promise, and problems
TRANSCRIPT
Consumer Health Data – Potential, Promise and Problems
…and an introduction to the Health Data Exploration ProjectSupported by the Robert Wood Johnson Foundation
November 17, 2014
Panel Members
Kevin Patrick, MD, MS - University of California, San Diego
John Brownstein, PhD - Harvard Medical School
Martin Coulter, CEO - PatientsLikeMe
Andrew Rosenthal, Group Manager Wellness+ Platform - Jawbone
Ann Waldo, JD, Partner - Witte, Letsche and Waldo, LLP
“Health happens where we live, learn, work and play.”
Randomized controlled trials
EMRsBiomarkers
Traditional Health ResearchSurveillance
Wearable devices for tracking health-related states
Patients sharing information about their disease…
Digital traces of everyday life…
An increasingly diverse & expanding ecosystem of devices,apps, and services generating vast amounts of data…
Based upon this background, in 2013 we began the Health Data Exploration Project
hdexplore.calit2.net
New models of inquiry
Ethical Issues
Address Disparities
Runaway Costs
How can we use this data to
improve health research and
promote the public good?
Personal Health Data (PHD) Ecosystem
Next Step: Building a Network
• Newly funded by Robert Wood Johnson Foundation• Network of innovators in PHD to catalyze the use of personal
data for the public good– Companies, researchers, and strategic partners
• Core Research, Policy and Network Development Efforts• Agile Research Projects leveraging network members
Info at: hdexplore.calit2.net
Health Data Exploration ProjectCore Advisors & Steering Committee
John Brownstein, PhD Harvard Medical School
@johnbrownstein
Digital Disease Detection
Social media to quantify population health
Spelling VariationsCombined or invented wordsImplied phrasesInternet Vernacular Translation
lost their eyesight
seeing weird colorseeing weird colour
doublevision
uldn’t seedouble vision
blindgoogley eyed
blurry vision
changes in visiocross eyedseeing weird
vision changeblindness
cross visionvisual snow
googly eyedseeing double
making me eat like a mousenorexic
st appetite
#notevenhungryappetite is nonexistent
apetite surpressed
didn’t get hungry
dont want to eat
killed my apetite
miss feeling hungry
killed my appetitecan’t eatlost apetite
lost my appetiteno appetitey
lack of apetitestomach small
lost teh appetite
never hunever want to eat
cant eat
coucrosseyed
blurry
apetite surpressed
killed my apetitelost apetite
lack of apetite
lost teh appetite
Typos
seeing weird colorseeing weird colour
googley eyed
googly eyed
#notevenhungry
no appetitey
making me eat like a mouse
never want to eat
Visual impairmentMedDRA 10047571
Visual impairmentSNOMED 397540003
Decreased appetiteMedDRA 10061428
Loss of appetiteSNOMED 79890006
making me eat like a mousenorexic
st appetite
#notevenhungryappetite is nonexistent
apetite surpressed
didn’t get hungry
dont want to eat
miss feeling hungry
killed my appetitecan’t eatlost apetite
lost my appetiteno appetitey
lack of apetitestomach small
lost teh appetite
never hunever want to eat
cant eat
lost their eyesight
seeing weird colorseeing weird colour
doublevision
uldn’t seedouble vision
blindgoogley eyed
blurry vision
changes in visiocross eyedseeing weird
vision changeblindness
cross visionvisual snow
googly eyedseeing double
coucrosseyed
blurry
killed my apetite
Areas where social media can help
Drug diversion & abuse
Infectious diseaseChronic diseaseDrug safetyPatient experience
PatientsLikeMe
Live better, together
Patients use PatientsLikeMe to create online health profiles comprised of data captured via validated clinical scales, health assessment tools, and other innovative consumer-friendly instruments
PatientsLikeMe Partners with Patients to Advance Science and Care
24
What Sets PatientsLikeMe Apart
Dedicated to a long-term program that is fundamentally and overridingly aligned to the patient’s best interests
Equal focus on individual outcomes and science
Captures real-timestructured data
Driven by a patient agenda
Leverages solid science
Tuned to patient experience
Collects insights amenable to re-use across multiple research scenarios
Conformed to existing scientific ontologies and classification standards
Applies rigorous scientific approaches to advance knowledge of a disease via peer review quality rigor
Supports rapid inquiry and testing
Engages patients with compelling benefits that improve their daily quality of life and address immediate clinical, socialand emotional needs
25
Elevating the Patient Voice to theLevel of Medical Evidence
300,000+unique attribution linked data elements and coded to ICD-10+ others
40,000+
publications in peer-reviewed journals50+
clinical endpoints recorded on a daily basis 5,320+
million forum posts containing rich patient-to-patient dialogue
2+
million structured data points: Tx, Sx, SEs, etc. 20+
members who can contribute data and share health outcomes
A unique health outcomes network Creating a patient-centric system
26
Characterizing Disease & Patient Status Requires a Holistic Philosophy
A Holistic Patient Understanding• PLM aims to quantify and understand the
variables that impact living with disease
• By making the human condition computable, quantifying current and future status is enabled
• Evolving measures via sensors, wearables, and other remote monitoring technology are key inputs into the system
• Combining objective sensor data with patient-reported data increases disease understanding
• Sensors can also motivate behavior change and increased activation
27
The Sensors Market is Growing, However Evidence and Medical Context is Lacking
Current market challenges • Lack of evidence about what works, and for
whom
• Consumer devices are largely accessible but come with little data about their benefit and utility
• Regulated devices have more data and research rigor, but are largely inaccessible
• Lack of systematic methods by which to engage with patients around sensor dev’t and validation
• The role of peer-to-peer interactions in sensor utilization and long term value
Trends impacting sensor dev’t
Cheaper, smaller sensors
New communication
standards
Ubiquitous low power mobile
computingAdvances in
materials science
Patient engagement and
participation
Expectation of UX from other consumer tech
Outcomes based reimbursement Penalties for
readmission
28
Leveraging the Network to Generate Evidence and Insight
Activated PLM members
Carefully selected consumer & medical technology
+ +
PLM engagement framework
• Passively collected characterization of patient experience• Direct utility to patients via improved self-management• Improved provider-patient interactions via objective data• First hand glance at patient need and value-add sensor features • Novel understanding of disease through digital phenotypes & biosignatures
1 2 3
29
What Have We Learned About the Utility of PGD
Learnings to date
Process: PLM members are engaged and want to participate in research
Patient engagement: Sensors help increase patient engagement, activation, and data donation
Doctor relationship: Members share sensor data with their physicians
Disease: Objectively captured sensor data correlates with measures of functional disability as reported subjectively by patients
Stakeholders: Pharma is systematically learning from patients and applying learnings to current business needs
Using voice-recording sensors to understand and track progression of neuro-degenerative disease
Using activity and physiologicalmonitoring in respiratory diseases to explore remote monitoring utility
Current PLM studies with sensors
Using activity measurements to remotely monitor and learn about neuro-degeneration
Generally, between 10-30% of PLM patients are using sensor technology
30
Ann B. Waldo, JD, CIPPWittie, Letsche & Waldo, LLP
Washington, DC
Legal Frameworks for Health Data
HIPAA
• Scope - Covered Entities and Business Associates
• Data – PHI (Protected Health Information)• Enforced by HHS and AGs• Extremely complex• Highly prescriptive; document-heavy
• Substantial fines and onerous HHS settlements
• “Data culture” – highly resistant to sharing, even with patients
Consumer Protection Law (Non-HIPAA)
• Scope – Every entity
• Data – All health info• Enforced by FTC and AGs• General, vague, high-level requirements• “Reasonableness” and “unfairness”
standards (moving targets)• Substantial state fines and onerous FTC
settlements• More open to data sharing and innovation
Line between HIPAA and Consumer Health Law
• Line between HIPAA and Consumer Health law is historical – not logical! – Not rational or intuitive– If unsure whether covered by HIPAA, don’t guess!
Mrs. J to grocery clerk five feet away:“I have a raging sore
throat. Where are Sucrets?”
Mrs. J to pharmacy clerk in grocery store: “I have a raging sore throat. Where are Sucrets?”
Mike types symptoms and exercise data into cardiologist’s patient portal
Mike types symptoms and exercise data into online cardiac patient community
Challenges Presented by Divergent Legal Frameworks
• Explosion of new health data sources outside HIPAA• Anxiety about possible harm from misuse of consumer health data• PGHD (Patient-Generated Health Data) is created by patients, flows
into EHRs and back out --- changing HIPAA status along the way• Uncertainty among innovators as to rules of the road outside HIPAA
• What can be shared freely?• What requires user permission?• How to anonymize?• Potential penalties and “Monday morning quarterbacking”
Big Questions – What to Do
• Stick with status quo – divergent HIPAA and consumer law• Extend HIPAA to consumer health data?
► NO. Bad fit. Too strict and too loose. And HIPAA’s extreme complexity would impose severe burden on innovation
• Manage and protect consumer health data responsibly• Respect consumer trust• Protect data like currency• Wise use of consent – seek permission where appropriate, without overburdening
consumer experience• Borrow sound principles from HIPAA• Anonymize to HIPAA standards• Make, and stick to, public promises about privacy
New self-regulatory framework for consumer health data – time to explore?
Resources
“So You’ve Concluded Your New Health Startup is Outside HIPAA…Now What?” by Ann Waldo, Nov. 2012, available at http://cdn.privacyanalytics.ca/wp-content/uploads/2013/07/rb-november-2012.pdf
Consumer Health Data – Potential, Promise and Problems
…and an introduction to the Health Data Exploration ProjectSupported by the Robert Wood Johnson Foundation
Discussion & Questions