Abstract
Health care spending in the U.S. grew two trillion dollars from 1987 to 2010, a 400% increase, but our understanding of the value of that increase is limited. In this paper we estimate the net value of spending for thirty chronic diseases between 1987 and 2010 by assigning a monetary value to changes in health outcomes and relating it to the costs of treating each disease. Changes in health outcomes are measured using a newly-available time series of disability adjusted life years (DALYs) data from the Institute for Health Metrics and Evaluation. Spending on treatments are determined using health care expenditure data from nationally representative surveys. We find the net value of treatment has grown substantially for several diseases. Overall, 20 of the 30 chronic conditions studied experienced an increase in health outcomes over the period, with 8 of those 20 showing a decrease in per-patient spending. Our estimates of net value of health spending using DALYs data are simple to apply and results are generally consistent with previous estimates which usually involve onerous data collection methods to study a single disease. The DALYs data have potential to be a useful, low-cost way to measure changes in health outcomes. However, challenges remain in using DALYs data to accurately measure the changing value of health care spending on the treatment of disease.
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References
Aizcorbe, A., Bradley, R., Greenaway-McGrevy, R., Herauf, B., Kane, R., Liebman, E., Pack, S., & Rozental, L. (2011). Alternative price indexes for medical care: Evidence from the MEPS survey. U.S. Bureau of Economic Analysis working paper WP2011-01, Washington, DC.
Aizcorbe, A., Liebman, E., Cutler, D. M., & Rosen, A. B. (2012). Household consumption expenditures for medical care: An alternate presentation. Survey of Current Business,92(6), 34–48.
Alzheimer’s Association, Thies, W., & Bleiler, L. (2011). 2011 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association,7(2), 208–244.
Berry, S., Ngo, L., Samelson, E., & Kiel, D. (2010). Competing risk of death: An important consideration in studies of older adults. Journal of the American Geriatrics Society,58(4), 783–787.
Bunker, J. P. (2001). The role of medical care in contributing to health improvements within societies. International Journal of Epidemiology,30(6), 1260–1263.
Centers for Medicare and Medicaid Services. (2017). National health care spending in 2016. Office of the Actuary, National Health Statistics Group. Retrieved October 24, 2018, from https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NationalHealthAccountsHistorical.html.
Cutler, D. M., McClellan, M., Newhouse, J. P., & Remler, D. (1998). Are medical prices declining? Evidence from heart attack treatments. The Quarterly Journal of Economics,113(4), 991–1024.
Cutler, D. M., McClellan, M. B., Newhouse, J. P., & Remler, D. (2001). Pricing heart attack treatments. In D. M. Cutler & E. R. Berndt (Eds.), Medical care output and productivity (pp. 305–362). Chicago: University of Chicago Press.
Cutler, D., Rosen, A. B., & Vijan, S. (2006). The value of medical spending in the United States, 1960–2000. New England Journal of Medicine,355(9), 920–927.
Deuschl, G., Schade-Brittinger, C., Krack, P., Volkmann, J., Schäfer, H., Bötzel, K., et al. (2006). A randomized trial of deep-brain stimulation for Parkinson’s disease. New England Journal of Medicine,355(9), 896–908.
Eggleston, K. N., Shah, N. D., Smith, S. A., Berndt, E. R., & Newhouse, J. P. (2011). Quality adjustment for health care spending on chronic disease: Evidence from diabetes treatment, 1999–2009. The American Economic Review,101(3), 206–211.
Fasano, A., Daniele, A., & Albanese, A. (2012). Treatment of motor and non-motor features of Parkinson’s disease with deep brain stimulation. The Lancet Neurology,11(5), 429–442.
Hall, A. E., & Highfill, T. (2013). Calculating disease-based medical care expenditure indexes for medicare beneficiaries: A comparison of method and data choices. National Bureau of Economic Research working paper no. 19720, Cambridge, MA.
Institute for Health Metrics and Evaluation. (2010). The global burden of disease. University of Washington.
James, B. D., Leurgans, S. E., Hebert, L. E., Scherr, P. A., Yaffe, K., & Bennett, D. A. (2014). Contribution of Alzheimer disease to mortality in the United States. Neurology,82(12), 1045–1050.
Medical Expenditure Panel Survey. (2010). Agency for healthcare research and quality. Household full year file, 2010. [Internet]. Rockville, MD: AHRQ.
Murray, C. J., Abraham, J., Ali, M. K., Alvarado, M., Atkinson, C., Baddour, L. M., et al. (2013). The state of US health, 1990–2010: Burden of diseases, injuries, and risk factors. Journal of the American Medical Association,310(6), 591–608.
National Medical Expenditure Survey. (1987). Household survey, health status questionnaire, and access to care supplement [public use tape 9] (ICPSR 9674) [Internet]. Ann Arbor, MI: University of Michigan Institute for Social Research.
National Research Council. (2005). Principles and practices for a federal statistical agency: Third edition. Washington, DC: The National Academies Press. https://doi.org/10.17226/11252.
Olazaran, J., Reisberg, B., Clare, L., Cruz, I., Pena-Casanova, J., Del Ser, T., et al. (2010). Nonpharmacological therapies in Alzheimer’s disease: A systematic review of efficacy. Dementia and Geriatric Cognitive Disorders,30(2), 161–178.
Organisation for Economic Co-operation and Development, Statistics Directorate. (2010). Towards measuring the volume output of education and health services: A handbook. Working paper number 31.
Porter, M. E. (2010). What is value in health care? New England Journal of Medicine,363(26), 2477–2481.
Roehrig, C., Miller, G., Lake, C., & Bryant, J. (2009). National health spending by medical condition, 1996–2005. Health Affairs,28(2), w358–w367.
Rosen, A. B., Aizcorbe, A., Highfill, T., Chernew, M. E., Liebman, E., Ghosh, K., et al. (2018). Attribution of health care costs to diseases. Measuring and Modeling Health Care Costs,76, 173.
Shapiro, I., Shapiro, M. D., & Wilcox, D. (2001). Measuring the value of cataract surgery. In D. M. Cutler & E. R. Berndt (Eds.), Medical care output and productivity (pp. 411–438). Chicago: University of Chicago Press.
Siegel, R., Naishadham, D., & Jemal, A. (2012). Cancer statistics, 2012. CA: A Cancer Journal for Clinicians,62(1), 10–29.
Skinner, J. S., Staiger, D. O., & Fisher, E. S. (2006). Is technological change in medicine always worth it? The case of acute myocardial infarction. Health Affairs,25(2), w34–w47.
Stewart, S., Cutler, D. M., & Rosen, A. B. (2013). US trends in quality-adjusted life expectancy from 1987 to 2008: Combining national surveys to more broadly track the health of the nation. American Journal of Public Health,103(11), e78–e87.
World Health Organization. (2001). National burden of disease studies: A practical guide. Global program on evidence for health policy. WHO, Geneva. Edition 2.0, October 2001.
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Highfill, T., Bernstein, E. Using disability adjusted life years to value the treatment of thirty chronic conditions in the U.S. from 1987 to 2010: a proof of concept. Int J Health Econ Manag. 19, 449–466 (2019). https://doi.org/10.1007/s10754-019-09266-x
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DOI: https://doi.org/10.1007/s10754-019-09266-x