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UNIVERSITY OF WASHINGTON
Global Burden of Disease
Big Data in Global Health
Peter Speyer
Director of Data Development
@peterspeyer / speyer@uw.edu
Institute for Health Metrics and Evaluation (IHME)
• Independent research center at the University of Washington
• Core funding by Bill & Melinda Gates Foundation and State of Washington
• 160 faculty, researchers and staff
• Providing independent, rigorous, and scientific measurement and evaluations
Health outcomes
Performance of health systems, programs & interventions
Maximizing resources
• “Our goal is to improve the health of the world’s
populations by providing the best information
on population health”
The Global Burden of Disease Study
• A systematic scientific effort
to quantify the comparative magnitude of
health loss due to diseases, injuries and risk factors
• Concept created by Christopher Murray and Alan Lopez
for a study by WHO and World Bank in 1991
• GBD 2010
– 291 causes in 187 countries for 1990, 2005 and 2010
by age and sex
– Collaboration with 488 individuals from 300 organizations
in 50 countries
– Published in 2012 in The Lancet
3
Measuring burden of diseases and injuries
4
DALYs (Disability-Adjusted Life Years)
Health
AgeDeath
Deaths
Average
life
expectancy
YLLs
YLLs (Years of Life Lost)
YLDs YLDs
YLDs (Years Lived with Disability)
Disability Weight
Measuring burden by risk factor
• Measure impact of risk factors on diseases and injuries
• Examples: diet, alcohol consumption, physical activity, blood pressure
• Key for prevention
• Based on
– Risk exposure in the population
– Relative risk per unit of exposure
– Theoretical minimum exposure
5
GBD data inputs: it’s big data
6
• Surveys
• Censuses
• Vital registration
• Verbal autopsy
• Disease registries
• Mortuaries / burial sites
• Police records
Variety Volume Velocity
• Hospital /
ambulatory / primary
care records
• Claims data
• Surveillance
systems
• Sensor data
• Administrative data
• Literature reviews
• Data updates
The Global Health Data Exchange (GHDx.org)
7
8
Data & Model Flow
Results: over 1 billion data points
• 4 key metrics: deaths, YLLs, YLDs,
DALYs
• 187 countries
• 1990, 2005 and 2010
• 291 causes / 1160 specific outcomes
• 66 risk factors plus risk factor attribution
by cause
• 20 age groups
• Male / female
9
10
11
12
13
Strengths of the GBD approach
• Synthesis of all available data
• Innovative, peer reviewed methods
• Consistent methods make results comparable
• Uncertainty bounds for all metrics
• Coverage of all causes prevents
double-counting,
e.g. mortality, anemia
• Fully imputed dataset
14
Uses of GBD
• Global agenda setting
• Benchmarking
• Performance tracking
• Priority setting
• Resource allocation
• Analysis for any population
• Market sizing
15
Outlook
• Annual updates
• Sub-national analyses
• Disease expenditures
• Forecasts
16
UNIVERSITY OF WASHINGTON
Global Burden of Disease
Big Data in Global Health
Peter Speyer
Director of Data Development
@peterspeyer / speyer@uw.edu

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Global Burden of Disease - Big Data in Global Health

  • 1. UNIVERSITY OF WASHINGTON Global Burden of Disease Big Data in Global Health Peter Speyer Director of Data Development @peterspeyer / speyer@uw.edu
  • 2. Institute for Health Metrics and Evaluation (IHME) • Independent research center at the University of Washington • Core funding by Bill & Melinda Gates Foundation and State of Washington • 160 faculty, researchers and staff • Providing independent, rigorous, and scientific measurement and evaluations Health outcomes Performance of health systems, programs & interventions Maximizing resources • “Our goal is to improve the health of the world’s populations by providing the best information on population health”
  • 3. The Global Burden of Disease Study • A systematic scientific effort to quantify the comparative magnitude of health loss due to diseases, injuries and risk factors • Concept created by Christopher Murray and Alan Lopez for a study by WHO and World Bank in 1991 • GBD 2010 – 291 causes in 187 countries for 1990, 2005 and 2010 by age and sex – Collaboration with 488 individuals from 300 organizations in 50 countries – Published in 2012 in The Lancet 3
  • 4. Measuring burden of diseases and injuries 4 DALYs (Disability-Adjusted Life Years) Health AgeDeath Deaths Average life expectancy YLLs YLLs (Years of Life Lost) YLDs YLDs YLDs (Years Lived with Disability) Disability Weight
  • 5. Measuring burden by risk factor • Measure impact of risk factors on diseases and injuries • Examples: diet, alcohol consumption, physical activity, blood pressure • Key for prevention • Based on – Risk exposure in the population – Relative risk per unit of exposure – Theoretical minimum exposure 5
  • 6. GBD data inputs: it’s big data 6 • Surveys • Censuses • Vital registration • Verbal autopsy • Disease registries • Mortuaries / burial sites • Police records Variety Volume Velocity • Hospital / ambulatory / primary care records • Claims data • Surveillance systems • Sensor data • Administrative data • Literature reviews • Data updates
  • 7. The Global Health Data Exchange (GHDx.org) 7
  • 9. Results: over 1 billion data points • 4 key metrics: deaths, YLLs, YLDs, DALYs • 187 countries • 1990, 2005 and 2010 • 291 causes / 1160 specific outcomes • 66 risk factors plus risk factor attribution by cause • 20 age groups • Male / female 9
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  • 14. Strengths of the GBD approach • Synthesis of all available data • Innovative, peer reviewed methods • Consistent methods make results comparable • Uncertainty bounds for all metrics • Coverage of all causes prevents double-counting, e.g. mortality, anemia • Fully imputed dataset 14
  • 15. Uses of GBD • Global agenda setting • Benchmarking • Performance tracking • Priority setting • Resource allocation • Analysis for any population • Market sizing 15
  • 16. Outlook • Annual updates • Sub-national analyses • Disease expenditures • Forecasts 16
  • 17. UNIVERSITY OF WASHINGTON Global Burden of Disease Big Data in Global Health Peter Speyer Director of Data Development @peterspeyer / speyer@uw.edu