understanding changes in local public health spending glen mays, phd, mph department of health...
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Understanding Changes Understanding Changes in Local Public Health Spendingin Local Public Health Spending
Glen Mays, PhD, MPHDepartment of Health Policy and ManagementUniversity of Arkansas for Medical Sciences
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Longitudinal change in spending and mortalityLongitudinal change in spending and mortality
•Half of all gains attributable to medical spending •$36,300 per year of life gained•What can we say about public health spending?
Cutler et al. NEJM 2006
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Geographic variation in spending and mortalityGeographic variation in spending and mortality
Medical spending varies by a factor of more than 2 across local areas
Medicare enrollees in high-spending regions receive more care but do not experience lower mortality
What can we say about public health spending?
Fisher et al. Annals 2003
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Some research questions of interest…Some research questions of interest…
How does public health spending vary across communities and change over time?
Are changes in spending associated with changes in population health outcomes?
What is the value of public health spending?
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Variation in Local Public Health SpendingVariation in Local Public Health Spending
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%1
0%
15
%
Fra
ctio
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f A
ge
nci
es
$0 $50 $100 $150 $200
Expenditures per capita, 2005
Gini = 0.472
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Change in Local Public Health Spending, Change in Local Public Health Spending, 1993-20051993-2005
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%1
0%
15
%
Fra
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f A
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–$50 $0 $50
Change in Per Capita Spending (Current Dollars)
–$10–$20–$30–$40 $40$30$20$10
35%
65%
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The problem with public health spendingThe problem with public health spending Federal & state funding sources often targeted to
communities based in part on disease burden, risk, need
Local funding sources often dependent on local economic conditions that may also influence health
Public health spending may be correlated with other resources that influence health
Medicaid9%
Medicare2%
Fees6%
Federal direct
7%
Federal pass-thru
13%
State direct23%
Other12% Local
28%
Sources of Local Public Health Agency Revenue, 2005
NACCHO 2005
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Example: cross-sectional association Example: cross-sectional association between PH spending and mortalitybetween PH spending and mortality
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Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Quintile of public health spending/capita
Pub
lic h
ealth
spe
ndin
g/ca
pita
Public health spending/capitaHeart disease mortality
Deaths per 100,000
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Example: cross-sectional association Example: cross-sectional association between PH spending and Medicare spendingbetween PH spending and Medicare spending
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Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5
Med
ical
spen
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/per
son
($)
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Publ
ic h
ealt
h sp
endi
ng/c
apita
($)
.
Quintiles of public health spending/capita
Public health spending/capita
Medicare spending per recipient
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Addressing the problem with spendingAddressing the problem with spending
1. Cross-sectional regression: control for observable confounders
2. Fixed effects: also control for time-invariant, unmeasured differences between communities
3. IV: use exogenous sources of variation in spending
4. Discriminate between causes of death amenable vs. non-amendable to PH intervention
PH spending Mortality
Unmeasured disease burden,
risk
Unmeasured economic
distress
+ +
+_
Approaches
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Data used in empirical workData used in empirical work
Financial and institutional data collected on the national population of local public health agencies (N≈3000) in 1993, 1997, and 2005
Residual state spending estimates from US Census of Governments
Residual federal spending estimates from Consolidated Federal Funding Report
Community characteristics obtained from Census and Area Resource File (ARF)
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Analytical approachAnalytical approach
Dependent variables– Age-adjusted mortality rates, conditions sensitive to
public health interventions (infant mortality, heart disease, cancer, diabetes, influenza)
– Counterfactual mortality rates (alzheimer’s, unintentional injuries)
Independent variables of interest– Local spending per capita, all sources– Residual state spending per capita
(funds not passed thru to local agencies)– Direct federal spending per capita
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Analytical approach: IV estimationAnalytical approach: IV estimation Identify exogenous sources of variation in
spending, unrelated to outcomes– Governance structures: local boards of health– Centralized state-local PH administration
Controls for unmeasured factors that jointly influence spending and outcomes
PH spending Mortality
Unmeasured disease burden,
risk
Unmeasured economic
distress
Governance
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Analytical approachAnalytical approach
Agency characteristics: type of government jurisdiction, scope of services offered, governance, state-local administration
Community characteristics: population size, rural-urban, poverty, education, age distributions, physicians per capita, CHC funding per low income
State characteristics: Private insurance coverage, Medicaid coverage, state fixed effects
Other Variables Used in the Models
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Factors associated with local public health Factors associated with local public health spendingspending
Variable Coefficient 95% CI
Local board of health (1=Yes) 0.145** (0.099, 0.196)
Centralized structure (1=Yes) -0.234** (-0.364, -0.102)
Population size (log) -0.136*** (-0.168, -0.103)
Income per capita (log) 0.196** (0.001, 0.392)
Local tax burden (% of income) 0.234** (0.032, 0.436)
**p<0.05 ***p<0.01Hierarchical logistic regression estimates controlling for community-level and state-level characteristics
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Multivariate estimates of association Multivariate estimates of association between spending and mortalitybetween spending and mortality
*p<0.10 **p<0.05 ***p<0.01
Cross-sectional model
Fixed-effects model
Outcome Elasticity St. Err. Elasticity St. Err. Elasticity St. Err.
Infant mortality 0.0516 0.0181 ** 0.0234 0.0192 -0.6854 0.2668 ***
Heart disease -0.0003 0.0051 -0.0103 0.0040 ** -0.3216 0.1600 **
Diabetes 0.0323 0.0187 -0.0487 0.0174 *** -0.1439 0.0605 **
Cancer 0.0048 0.0029 * -0.0075 0.0240 -0.1131 0.0566 **
Influenza -0.0400 0.0200 ** -0.0275 0.0107 ** -0.0252 0.0362
Alzheimer’s 0.0024 0.0075 0.0032 0.0047 0.0051 0.0472
Injury 0.0007 0.0083 0.0004 0.0031 0.0013 0.0086
IV model
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ConclusionsConclusions
Local public health spending varies widely across communities
Governance and administrative structures appear influential in spending decisions– Local governing boards – Decentralized administrative structures
Growth in spending is associated with reductions in mortality from leading preventable causes of death
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LimitationsLimitations
Aggregate spending measures– Average effects– Role of allocation decisions?
Mortality – distal measures with long incubation periods
Confounding—unmeasured factors tightly correlated with public health spending?