Post on 27-Jan-2015
description
UNIVERSITY OF WASHINGTON
Global Burden of DiseaseBig 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’spopulations 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 organizationsin 50 countries
– Published in 2012 in The Lancet
3
4
Measuring burden of diseases and injuries
DALYs (Disability-Adjusted Life Years)
Health
AgeDeath
Deaths
Averagelife
expectancy
YLLsYLLs (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
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 preventsdouble-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
Outlook
• Annual updates
• Sub-national analyses
• Disease expenditures
• Forecasts
16
UNIVERSITY OF WASHINGTON
Global Burden of DiseaseBig Data in Global Health
Peter Speyer
Director of Data Development
@peterspeyer / speyer@uw.edu