Preventable health conditions account for more than 75 percent of annual health care expenditures in the U.S., yet less than 5 percent of these expenditures are devoted to public health programs and services that are designed to prevent and control disease and injury rather than to treat the downstream consequences of these conditions. This study examined data on local public health spending and area-level Medicare expenditures over a 20-year period from 1993 to 2013. Between 1993 and 2013, local public health spending increased from $32 to $55 per capita for the average community. Nearly two thirds of communities experienced positive growth in per capita public health spending of nearly $4, unfortunately a third of the communities though suffered a loss of more than $11 per capita. Findings indicate that the degree of inequality in local public health spending closely mirrors the level of income inequality observed among U.S. households such that the public health spending levels ranged from less than $1 per capita to as high as $400 per capita. The results indicate a 10 percent increase in local public health spending per capita is associated with a 0.8 percent reduction in Medicare expenditures per person after 1 year and a 1.1 percent reduction after 5 years. These results suggest Medicare could recover an average of $1.10 for each dollar invested in public health activities after 5 years. If the spending offsets we estimate in this study apply to other populations beyond Medicare, the societal return on investment could be even larger. Finally, results also showed that Medicare spending offsets are more pronounced in low-resource communities, such as areas with higher poverty, lower rates of health insurance coverage, and substantial health professional shortages.
- Glen P. Mays, PhD
- Cezar B. Mamaril, PhD
Multivariate, fixed-effects, and instrumental-variables regression models were used to estimate how area-level Medicare spending changes in response to changes in local public health spending, while controlling for observed and unmeasured confounders.
Primary Investigator: Glen Mays