Formula-based Funding Allocations
in Public Health:
Describing the Impact of
Alternate Formula Design Options
Presented by James Buehler, MD & Patrick Bernet, PhD
Presented at AcademyHealth Public Health Research Interest Group Meeting, Washington DC,
June 7, 2008.
Project team:
Emory University, Rollins School of Public Health
James Buehler, MD ▪ Lydia Ogden, MA, MPP ▪ Cynthia Zeldin, MA
Florida Atlantic University
Patrick Bernet, PhD
Johns Hopkins University, Bloomberg School of Public Health
David Holtgrave, PhD
www.HealthcareFinance.org\PHFF
Funding for this research provided by the Robert Woods Johnson Foundation,
Health Care Financing & Organization Program.
PHSR 2008.06.07
Formula-based funding allocations in public health: Describing the impact of alternate formula design options
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Formula-based Funding Allocations
• Common in federal and state
government programs
• Issues & methods
extensively reviewed but
limited attention to public
health
• Project goal: Provide
evidence base and policy
interpretation to inform
design & use in PH practice
• First step: Metrics &
approach to compare
different allocations.
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Allocation methods
• Goal: Allocate funds to advance program objectives
• Generic formula allocation:
o Amount area receives =
ƒ Guaranteed minimum for all grantees, plus
ƒ Need-based share, adjusted for
• Costs (labor, supplies, services)
• Local resources (tax revenues or taxable revenue)
• Need
o Population: total, demographic subset
o Poverty
o Disease-specific risk factors, morbidity, mortality
o Historical funding precedents
• Calculation options: weights, constraints, incentives
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Formula-based funding allocations in public health: Describing the impact of alternate formula design options
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CDC BT/Emergency Preparedness Program
• "…preparedness for and response to terrorism, pandemic influenza,
and other public health emergencies…" (www.bt.cdc.gov)
• $761 million for 2006, includes $699 million for "Base program"
o "Each state…will receive…$3.91 million, plus an amount equal to
its proportional share of the national population…"
• Test alternate data inputs for allocation:
o Straight per capita
o Poverty (<100 Federal poverty level, food stamp enrollment,
income inequality)
o Adjust for
ƒ Cost (Bureau of Labor Statistics wage index)
ƒ Resources (Total Taxable Resources [TTR])
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Metrics for comparing allocations
• Difference from baseline
o % of total allocation that changes
o Coefficient of variation of distribution
o Percentage change in cumulative distribution
• Range of percentage change for individual states
o RAND "Senate & House" indices (from NAS deliberations)
ƒ Number of states with % increase or decrease >20% ("Senate
index")
ƒ Percentage of population in states with % increase or decrease
>20% ("House index")
• Proportionality of Allocations & Percentage Change in Proportionality
of Allocations (Lorenz curve)
• Focus on descriptors of changes in allocations (not which is better)
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-1%
PHSR 2008.06.07
Formula-based funding allocations in public health: Describing the impact of alternate formula design options
Massachusetts
North Carolina
Virginia
New Jersey
Georgia
Michigan
Ohio
Pennsylvania
Illinois
Florida
Texas
New York
California
South Carolina
Kentucky
Alabama
Louisiana
Colorado
Minnesota
Wisconsin
Tennessee
Maryland
Missouri
Indiana
Washington
Arizona
Nebraska
West Virginia
Utah
New Mexico
Arkansas
Nevada
Kansas
Mississippi
Iowa
Oklahoma
Connecticut
Oregon
Wyoming
Vermont
North Dakota
Alaska
South Dakota
Delaware
Montana
Rhode Island
Hawaii
New Hampshire
Maine
Idaho
District of Columbia
Emergency Preparedness 2006 Allocations
Losses
Current allocations
Per capita allocations
9%
4%
page 6 of 16
Percent of total allocations moved from baseline
• If re-distributed current allocations according to households receiving
food stamps, 17% of all funds would shift.
• States with smaller population see their share of allocations decrease
because EP formula has a fixed portion and a per capita portion. But
none of the re-distribution models contains a fixed portion.
14%
Current allocations
Per capita allocations (0.09)
Poverty (0.13)
Food stamps (0.17)
Income Inequality (0.10)
12%
10%
Actual values
Maryland Tennessee
Allocation shares
Maryland Tennessee
Allocati ons
Populati on
5,615,727 6,038,803
Poverty
8%
16%
Food stamps
140,394 387,090
Income inequality
0.37
0.42
8%
1.86%
1.88%
1.10%
1.20%
1.55%
1.83%
2.02%
2.46%
3.30%
2.26%
6%
4%
PHSR 2008.06.07
Formula-based funding allocations in public health: Describing the impact of alternate formula design options
California
Texas
New York
Florida
Illinois
Ohio
Pennsylvania
Georgia
Michigan
New Jersey
Virginia
North Carolina
Massachusetts
Arizona
Indiana
Washington
Missouri
Maryland
Tennessee
Wisconsin
Colorado
Minnesota
Alabama
Louisiana
Kentucky
Oregon
South Carolina
Connecticut
Iowa
Oklahoma
Mississippi
Nevada
Arkansas
Utah
New Mexico
West Virginia
Nebraska
Idaho
District of Columbia
Maine
Hawaii
New Hampshire
Montana
Rhode Island
Delaware
Alaska
South Dakota
North Dakota
Vermont
Wyoming
0%
Kansas
2%
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# states, % population with change over 20%
• Senate index, House index.
• Maximum winners, minimize losers.
60%
Percent of states with increase over 20%
Percent of population in states with increase over 20%
40%
Percent of states with decrease over 20%
Percent of population in states with decrease over 20%
20%
0%
Per capita
Poverty
Food stamps
-20%
Income
Inequality
-40%
-60%
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Per capita CIPA
100%
Current
Per capita (-1.00)
Per person in poverty (0.17)
Per household getting food stamps (0.94)
Percent of allocation
80%
Income inequality (inverse) (-0.35)
60%
40%
20%
0%
0%
20%
40%
60%
Percent of population
80%
100%
• Change in per capita proportionality of allocations.
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Poverty CIPA
100%
Current
Per capita (-0.32)
Per person in poverty (-1.00)
80%
Per household getting food stamps (0.09)
Percent of allocations
Income inequality (inverse) (-0.58)
60%
40%
20%
0%
0%
20%
40%
60%
80%
100%
Percent of population living in poverty
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Conclusions & Next Steps
• Need to describe whether & how multiple inputs and adjustments
affect allocations
o Classify effects on allocations
o Assess similarities/differences or degree of effects
ƒ Impacts on individual grantees
• Characteristics of winners/losers
ƒ Impacts on overall patterns of allocations
o Correlations among:
ƒ Service "need" indicators: disease risk factors, morbidity,
mortality, and income
ƒ "Need" indicators and adjustors for costs or revnues
• Next step: test impact of alternative allocation methods using selected
actual and hypothetical federal and state programs
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Income inequality
Senate, House indices. Exploring differences
60%
Percent of states with increase over 20%
Percent of population in states with increase over 20%
40%
Percent of states with decrease over 20%
Percent of population in states with decrease over 20%
20%
0%
Per capita
-20%
Poverty
Food stamps
Income
Inequality
-40%
Poverty
Income inequality
Income inequality
-60%
Difference
Poverty
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Formula-based funding allocations in public health: Describing the impact of alternate formula design options
Poverty
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Per capita CIPA Explained
100%
Current
Per capita (-1.00)
Per person in poverty (0.17)
Per household getting food stamps (0.94)
Percent of allocation
80%
Income inequality (inverse) (-0.35)
60%
40%
Income inequality
20%
0%
0%
20%
40%
60%
Percent of population
Per capita allocation
$5
$4
80%
100%
$3
$2
$1
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Food stamps
Population
Formula-based funding allocations in public health: Describing the impact of alternate formula design options
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Poverty CIPA
100%
Current
Per capita (-0.32)
Per person in poverty (-1.00)
80%
Per household getting food stamps (0.09)
$11.50
Income inequality (inverse) (-0.58)
Current
Percent of allocations
Income inequality
Other allocation per capita
60%
40%
$6.50
20%
0%
0%
20%
40%
60%
Percent of population living in poverty
PHSR 2008.06.07
80%
100%
$1.50
$1.50
$2.50
$3.50
Poverty allocation per capita
Formula-based funding allocations in public health: Describing the impact of alternate formula design options
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Coefficient of variation: difference from baseline
• The range of change is broader for per capita allocation (1.07), and
tighter for food stamp-based allocations (0.88).
• Tighter distribution of change might be more palatable.
Per capita allocations (1.07)
Poverty (1.04)
Food stamps (0.88)
20
Frequency
Income Inequality (0.97)
10
0
-0.50% or -0.50% to -0.25% to 0.25% to
lower
-0.25%
0.25%
0.50%
0.50% to
0.75%
.75% to
1.00%
1.00% to
1.25%
1.25% to
1.50%
1.50%
and over
Distance from mean (number of percentage points change in share)
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Risk CIPA
100%
Current
Per capita (-0.12)
Per person in poverty (0.25)
80%
Per household getting food stamps (0.30)
Income inequality (inverse) (-0.29)
Percent of allocations
Diagonal
60%
40%
20%
0%
0%
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20%
40%
60%
Percent of population
80%
Formula-based funding allocations in public health: Describing the impact of alternate formula design options
100%
page 16 of 16