Health Data Innovation

Health Data Innovation

Peter SpeyerDirector of Data Development

Institute for Health Metrics and Evaluation

The Institute for Health Metrics and Evaluation

• Global institute, Department of Global Healthat the University of Washington

• Providing independent, rigorous, and scientificmeasurements 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

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

http://www.ghdx.org

Screenshot GHDx record with file

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 Innovationis changing the game!

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

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

#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

#2: An innovation ecosystem evolves

• App challenges kick off a virtuouscycle of innovation

• New organizations provideincubation 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”

#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

#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

#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

#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

Key challenges need to be addressed

• Privacy vs. access• Data integration• Data quality assessment, standards, and documentation• Business model for health data

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 [email protected]@peterspeyer