1. Health Data Innovation
Peter Speyer
Director of Data Development
Institute for Health Metrics and Evaluation

2. The Institute for Health Metrics and Evaluation
• Global institute, Department of Global Health
at the University of Washington
• Providing independent, rigorous, and scientific
measurements and evaluations
• “Our goal is to improve the health of the world’s populations by
providing the best information on population health.”
• Core funding by the Bill & Melinda Gates Foundation and the state
of Washington
• Other funding through research grants
• Created in 2007
• 70 researchers, 30 staff

4. The health data environment
Health-related data
• Social determinants
• Risk factors
Population-based data
• Household/facility surveys
• Census
• Vital registration
• Registries (provider,
disease)
Facility-based data
• Health records
• Administrative data
(financial, operational)
• Research data (DSS,
clinical trials, etc.)
Missing:
Individual-based data

5. http://www.ghdx.org

6. Screenshot GHDx record with file

7. Still, health data are often difficult to find …
• Lack of transparency about existing health data
• Difficult to access
– Access vs. privacy
– Capacity, cost-benefit constraints
– Sense of ownership
• Lack of standards & documentation
… but Health Data Innovation
is changing the game!

8. Better health data are crucial for key players
Health
management
Patient
engagement
Cost
containment
Quality control
Risk prediction
Patient data
Aftermarket
studies
Preventive
medicine
ACO
requirements
Individuals Payers Providers Producers
Opportunities in
healthcare
Answer
people’s needs
Access to
timely data
Data synthesis
Big data
computing
InnovatorsAcademia
Healthcare
reform
Government
2.0
Governments

9. Health Data Initiative,
US Department of Health and Human Services
Enabling innovation with three steps
1.Publish government data
2.Make data accessible
(machine-readable)
3.Market the hell out of them
Joy's Law: "No matter who you are, most
of the smartest people work for someone
else.” (Sun Microsystems co-founder Bill Joy)
Successful examples: NOAA, GPS
US government kicked off innovation process

10. #1: Data owners open the vaults
• Governments engage in open
government and launch data portals
• Innovators build data sharing into their
model
• Scientists share more data
(NSF/funder requirement)
• Health marketplaces offer new ways to
reach data users

11. #2: An innovation ecosystem evolves
• App challenges kick off a virtuous
cycle of innovation
• New organizations provide
incubation and (seed) funding
• Innovators and established players
leverage data and create apps and tools
Source: RockHealth survey of 110 early stage digital health
entrepreneurs, “The State of Digital Health”

12. #3: Individuals get engaged
• Manage own health and create own
health data in the process
• Demand access to own health data,
potential for sharing
• Engage in treatments
• Add data to own Personal Health
Records

13. #4: Payment reform encourages the use of data
• Meaningful use of EHR data
• Focus on quality of care requires
• Timely clinical data
• Decision support
• Data mining
• Better health data exchange
• Physicians connect through social
networks

14. #5: Better tools make working with data easier
• Better ways to explore population data
• Better tools for data users
• Better ways to explore and analyze
healthcare data

15. #6: Timely data are (near) real-time
• Real-time health data enable tracking
and prediction of health outbreaks
• Real-time health data allow move from
infrequent physician visits to continuous
health monitoring
• New: epidermal electronics/
electronic skin: patch acts like a
temporary tattoo

16. Key challenges need to be addressed
• Privacy vs. access
• Data integration
• Data quality assessment, standards, and documentation
• Business model for health data

17. Health Data Innovation is a game changer
• Rapid virtuous cycle of data innovation
• More data collected, more data shared
• More timely data available
Contact me at
speyer@uw.edu
@peterspeyer