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Costs of Diabetes in the US: 1996-2030

Costs of Diabetes in the U.S.: 1996-2030

HONGYU CHEN, MANU V. VENKAT, LISA S. ROTENSTEIN, JESSICA P. DONG, NINA RAN, MARK YARCHOAN, RICHARD KAHN, KELLY L. CLOSE, San Francisco, CA, Boston, MA, Philadelphia, PA

Diabetes is responsible for substantial healthcare expenditure in the U.S., and prevalence continues to rise. More robust data on the past and future costs of diabetes are needed to inform public health policy and influence cost management strategies.

The purpose of this study was to assess U.S. healthcare costs directly attributable to diabetes from 1996 to 2010, and to forecast future cost trends through 2030. Expanding upon the strong methodology of the ADA’s five-year cost-of-illness studies, we calculated more granular cost data for every year from 1996 through 2010, drawing from the most robust longitudinal data sources available. We used this data to forecast future costs of diabetes through 2030.

Our analysis showed that the total annual healthcare costs directly attributable to diabetes in the U.S. rose from $64 billion in 1996 to $167 billion in 2010; we project costs to reach $494 billion by 2030. Broken down by components, we found that inpatient hospitalization declined from 58% of all costs in 1996 to 46% in 2010; we project a further decrease to 36% in 2030. The fastest growing cost segments were non-insulin prescription medications (7% in 1996, 16% in 2010, and a projected 26% in 2030) and diabetes supplies (3% in 1996, 10% in 2010, and a projected 12% in 2030). To explore the effects of diabetes prevention, we modeled the impact of a 1%, 5%, and 10% reduction in annual diabetes incidence from 2010 through 2030. Such reductions would save a cumulative projected total of $87 billion, $427 billion, and $798 billion, respectively, during that time period.

We conclude that, based on historical trends, the future costs attributable to diabetes in the U.S. will climb significantly, to levels greater than those projected by existing literature. Stemming this rise will likely require more successful diabetes prevention, as the total costs of diabetes are proportional to the size of the affected population. The dataset developed in this analysis opens exciting opportunities to study costs segmented by population demographics, complications, and care setting.

excerpt from Late Breaking Abstracts from ADA 2014