Tracking US healthcare spending; 1996-2013 Kate Muller, MPH & Joseph Dieleman, PhD dieleman@uw.edu

Outline Introduction to IHME Introduction to the IHME disease expenditure project Spending on US healthcare: 2013 results Measuring drivers of health care spending increases

Institute for Health Metrics and Evaluation Founded in 2007 to make health metrics more accurate, independent, and comparable. 300+ faculty and staff Largest health metrics database Estimates used by NIH, BMGF, WHO, World Bank, and others Emphasize growth in staff, funding, and stature Emphasize ambition of data sourcing Emphasize growing influence

The Global Burden of Disease Study Key goals are comprehensiveness and comparability Measures all aspects of health loss 2010, 2013, 2015, and now yearly Future: more subnational estimates IHME’s flagship project Comprehensive: over 350 diseases and health risk factors; Comparability: way to compare burden of schizophrenia and liver cancer in nearly every country in the world Health loss: not just about death, but early death and disability combined

GBD 2016: Health loss in the United States DALY: IHME’s metric of overall health loss “Disability-adjusted life year” The years lost to ill health and early death in a population Takes into account the severity of non-fatal illnesses One number that captures BOTH what is killing us and what is just making us sick Preview of 2016 data – out this month in The Lancet DALYs = our metric of overall health loss Top 10 causes of DALYs haven’t changed too much in US in last 26 years Note mix of fatal and non-fatal causes Preview that some of these causes will show up in Joe’s presentation

Project preview: Congressional District Profiles FYI: I had to cut down the figure to get it to fit on the slide, so there are 7 causes instead of 10 Upcoming project we’re working on Part of move to more local estimates – counties papers leading to district profiles to be useful for policymakers Washington 7th = SLU’s district; Pramila Jayapal is the rep Note several good rankings, but worse-than-average Alzheimer/dementia ranking Hoping profiles like this will be of use to policymakers Want to get contact info of people interested in being notified when these profiles go public

Outline Introduction to IHME Introduction to the IHME disease expenditure project Spending on US healthcare: 2013 results Measuring drivers of health care spending increases IHME is not just disease burden – also expenditure. Over to Joe…

US Disease expenditure project Funded by: Total US health spending Demographic Framework – 38 age and sex groups Epidemiological Framework – 155 causes Type of Care Framework –inpatient, ED, ambulatory, dental, nursing care, pharma, home

Published disease expenditure research 1 2

Most expensive conditions of illness

US health case spending: vizhub.healthdata.org/dex/

Measuring drivers of health care spending increases $932.8 billion increase in annual spending from 1996 to 2013, from $1.2 to $2.1 trillion. Annualized rate of change (1996-2013)

Measuring drivers of health care spending increases $932.8 billion increase in annual spending from 1996 to 2013, from $1.2 to $2.1 trillion. Annualized rate of change (1996-2013)

Measuring drivers of health care spending increases Objective: measure the impact of 5 fundamental drivers causing health care spending increases. Five factors: Population growth Population aging Changes to underlying disease incidence and prevalence Service utilization Service price and intensity

Measuring drivers of health care spending increases Ambulatory care Inpatient care Prescribed pharmaceuticals Nursing facility care Emergency department care Dental care Total US health spending 1996-2013

Measuring drivers of health care spending increases Diabetes mellitus Depressive disorders Low back and neck pain Prescribed pharmaceuticals Ambulatory care Inpatient care Nursing facility care Emergency department care Other neurological Hyperlipidemia Hypertension Prescribed pharmaceuticals Ambulatory care Inpatient care Nursing facility care Emergency department care

Health spending attributable to modifiable risk factors Attributable Spending

Next steps Measure spending for each payer group, and update estimates through 2015 Measuring spending for each state Measure spending for each income group, education group, and race

Thank you dieleman@uw.edu And an enormous thank you to: Maddy Campbell Abigail Chapin Taylor Matyasz Christopher Murray Cody Horst Alex Reynolds Zhiyin Li Ellen Squires dieleman@uw.edu