Multiple federal public health programs use funding formulas to allocate funds to states.
To characterize the effects of adjusting formula-based allocations for differences among states in the cost of implementing programs, the potential for generating in-state resources, and income disparities, which might be associated with disease risk.
Fifty US states and the District of Columbia.
Formula-based funding allocations to states for 4 representative federal public health programs were adjusted using indicators of cost (average salaries), potential within-state revenues (per-capita income, the Federal Medical Assistance Percentage, per-capita aggregate home values), and income disparities (Theil index).
Percentage of allocation shifted by adjustment, the number of states and the percentage of US population living in states with a more than 20% increase or decrease in funding, maximum percentage increase or decrease in funding.
Each adjustor had a comparable impact on allocations across the 4 program allocations examined. Approximately 2% to 8% of total allocations were shifted, with adjustments for variations in income disparity and housing values having the least and greatest effects, respectively. The salary cost and per-capita income adjustors were inversely correlated and had offsetting effects on allocations. With the exception of the housing values adjustment, fewer than 10 states had more than 20% increases or decreases in allocations, and less than 10% of the US population lived in such states.
Selection of adjustors for formula-based funding allocations should consider the impacts of different adjustments, correlations between adjustors and other data elements in funding formulas, and the relationship of formula inputs to program objectives.
This study aims to characterize the effects of adjusting formula-based allocations for differences among states in the cost of implementing programs, the potential for generating in-state resources, and income disparities, which might be associated with disease risk.
Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia (Dr Buehler); Management Programs, College of Business, Florida Atlantic University, Boca Raton, Florida (Dr Bernet); and Office of Prevention Through Healthcare, Office of the Associate Director for Policy, Office of the Director, Centers for Disease Control and Prevention, Atlanta, Georgia (Dr Ogden).
Correspondence: James W. Buehler, MD, Centers for Disease Control and Prevention, 1600 Clifton Rd, MS-E97, Atlanta, GA 30333 (firstname.lastname@example.org).
This project was funded by the Robert Wood Johnson Foundation's Health Care Financing & Organization program on Public Health Systems Research, Project ID 63615. The authors thank David Holtgrave, PhD, Chair of the Department of Health, Behavior, & Society, Bloomberg School of Public Health, Johns Hopkins University, for his thoughtful contributions to the planning of this project; and Cynthia Zeldin, MA, and Kenneth Gustely, MBA, for their assistance in compiling and documenting project data sources.
Disclosure: The authors declare no conflicts of interest.