Understanding Changes
in Local Public Health Spending
Glen Mays, PhD, MPH
Department of Health Policy and Management
University of Arkansas for Medical Sciences
Longitudinal 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
Geographic variation in spending and mortality

Medical spending varies by a
factor of more than 2 across
local areas

Medicare enrollees in highspending regions receive more
care but do not experience
lower mortality

What can we say about public
health spending?
Fisher et al. Annals 2003
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?
15%
Variation in Local Public Health Spending
0
Fraction of Agencies
5%
10%
Gini = 0.472
$0
$50
$100
$150
Expenditures per capita, 2005
$200
10%
5%
65%
35%
0
Fraction of Agencies
15%
Change in Local Public Health Spending,
1993-2005
–$50
–$40 –$30 –$20
–$10
$0
$10
$20
$30
$40
$50
Change in Per Capita Spending (Current Dollars)
The problem with public health spending

Federal & state funding sources often targeted to
communities based in part on disease burden, risk, need

Local funding sources often dependent on local
economic conditions that may also influence health

Public health spending may be correlated with other
resources that influence health
Sources of Local Public Health Agency Revenue, 2005
Fees
6%
Medicare
2%
Other
12%
Local
28%
Medicaid
9%
Federal
direct
7%
Federal
pass-thru
13%
State direct
23%
NACCHO 2005
Example: cross-sectional association
between PH spending and mortality
120
205
200
100
195
80
190
60
185
180
40
175
20
170
0
165
Quintile 1
Quintile 2
Quintile 3
Quintile 4
Quintile 5
Quintile of public health spending/capita
Deaths per 100,000
Public health spending/capita
Public health spending/capita
Heart disease mortality
Example: cross-sectional association
between PH spending and Medicare spending
7200
Public health spending/capita
100
7000
Medicare spending per recipient
6800
80
6600
60
6400
40
6200
20
6000
0
5800
Quintile 1
Quintile 2
Quintile 3
Quintile 4
Quintile 5
Quintiles of public health spending/capita
Medical spending/person ($) .
Public health spending/capita ($) .
120
Addressing the problem with spending
_
Unmeasured
economic
distress
+
Mortality
PH spending
+
Approaches
Unmeasured
disease burden,
risk
+
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. nonamendable to PH intervention
Data 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)
Analytical 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
Analytical 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
Governance
Unmeasured
economic
distress
Mortality
PH spending
Unmeasured
disease burden,
risk
Analytical approach
Other Variables Used in the Models

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
Factors associated with local public health
spending
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<0.01
Hierarchical logistic regression estimates controlling for community-level and state-level characteristics
Multivariate estimates of association
between spending and mortality
Cross-sectional
model
Outcome
Elasticity
St. Err.
IV model
Elasticity
St. Err.
Elasticity
St. Err.
0.0234
0.0192
-0.6854
0.2668 ***
Infant mortality
0.0516
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 **
-0.0400
0.0200 **
-0.0275
0.0107 **
-0.0252
0.0362
Influenza
0.0181 **
Fixed-effects
model
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
*p<0.10
**p<0.05
***p<0.01
Conclusions

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
Limitations

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?