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Resource and Cost Adjustment in the Design of Allocation Funding Formulas in Public Health Programs
Resource and Cost Adjustment in the Design of Allocation Funding Formulas in Public Health Programs
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Resource and Cost Adjustment in the Design of Allocation Funding Formulas in Public Health Programs
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Resource and Cost Adjustment in the Design of Allocation Funding Formulas in Public Health Programs
Resource and Cost Adjustment in the Design of Allocation Funding Formulas in Public Health Programs

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Resource and Cost Adjustment in the Design of Allocation Funding Formulas in Public Health Programs
Resource and Cost Adjustment in the Design of Allocation Funding Formulas in Public Health Programs
Journal Article

Resource and Cost Adjustment in the Design of Allocation Funding Formulas in Public Health Programs

2012
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Overview
Context: Multiple federal public health programs use funding formulas to allocate funds to states. Objective: 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. Setting: Fifty US states and the District of Columbia. Intervention: 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). Main Outcome: 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. Results: Each adjuster 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 adjusters 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. Conclusions: Selection of adjusters for formula-based funding allocations should consider the impacts of different adjustments, correlations between adjusters and other data elements in funding formulas, and the relationship of formula inputs to program objectives.