Global Burden of Disease - Big Data in Global Health

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Presentation of GBD at Strata Rx with overview of the study, explanation of burden of disease, and introduction of data visualizations of results

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Global Burden of Disease - Big Data in Global Health

  1. 1. UNIVERSITY OF WASHINGTON Global Burden of Disease Big Data in Global Health Peter Speyer Director of Data Development @peterspeyer / speyer@uw.edu
  2. 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. 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. 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. 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. 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. 7. The Global Health Data Exchange (GHDx.org) 7
  8. 8. 8 Data & Model Flow
  9. 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. 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. 15. Uses of GBD • Global agenda setting • Benchmarking • Performance tracking • Priority setting • Resource allocation • Analysis for any population • Market sizing 15
  16. 16. Outlook • Annual updates • Sub-national analyses • Disease expenditures • Forecasts 16
  17. 17. 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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