Inter- and intrastate
variation in Medicaid
expenditures
Rick Kronick, Ph.D.
Todd Gilmer, Ph.D.
University of California, San Diego
Supported by a grant from HCFO/RWJ
Research Questions
 Does interstate variation in Medicaid spending result
primarily from variation in the volume of services or in
the price per unit of service?
 How do inter- and intrastate variation in Medicaid
utilization and spending compare to variation in
Medicare spending and utilization?
 Is more better for Medicaid beneficiaries?
Data
Medicaid Analytic eXtract (MAX) data for CY 20012005 for all 50 states and DC
MAX data starts with data from the Medicaid Statistical
Information System (MSIS), and is then massaged by
CMS to create person-level
person level analytic files
Complete claims and eligibility data on approximately
280 million beneficiaries (not necessarily unique) over
five years
Methods
Exclude partial benefits beneficiaries (SLMBs, QMBs, family planningonly, etc)
Focus on Cash
Cash-Assistance,
Assistance Medicaid-Only,
Medicaid Only fee
fee-for-service,
for service
beneficiaries with Disabilities (CAMODs)
– Restrict to cash disabled because uniform national eligibility standard for
SSI increases comparability of the analysis sample across states
– Restrict
R t i t to
t Medicaid-only
M di id l ((eliminate
li i t d
duall eligibles)
li ibl ) tto gett a complete
l t view
i
of utilization and expenditures
– Restrict to FFS because encounter data are incomplete for beneficiaries in
managed care
In analyses of spending on CAMODs, exclude five states (AL, AZ, DE,
MD, and ND) because managed care penetration is too high or other
data anomalies
Distribution of Medicaid Beneficiaries and Expenditures, 2001‐2005
Beneficiaries
Total Expenditures
Acute
LTC 47.2 million
$234.6 billion
$149.2 billion
$74.8 billion
Cash Assistance, Medicaid‐only, Disabled (CAMOD
Other disabled
Aged
Adults
Children
Correlation Coefficients, State-level Expenditures per Beneficiary
and Expenditures per CAMOD, 2001-2005
ndardized expenditures per beneficiary
enditures per CAMOD
te expenditures per CAMOD
C expenditures per CAMOD
Standardized
Expenditures per
Beneficiary
1.00
0.86
0.81
0.81
Expenditures
per CAMOD
Acute
expenditures
per CAMOD
LTC
expenditures
per CAMOD
—
1.00
0.96
0.93
—
—
1.00
0.81
—
—
—
1.00
urce: 2001-2005 MAX data. N=46 (excludes AL, AZ, DE, MD, and ND).
RESULTS
Distribution of State‐level per Beneficiary Acute and LTC
Spending on CAMODs, 2001–2005
Distribution of State‐level per Beneficiary Acute Care Medicaid Spending on CAMODs, 2001–2005, by Type of Service
The relationship between
Medicare and Medicaid
utilization and spending
Distribution of state‐level 2004 Medicare spending per beneficiary, and 2001‐2005 acute care Medicaid spending per CAMOD
2004 Medicare spending per beneficiary and 2001‐2005 acute
care Medicaid spending per CAMOD
2004 Medicare admissions/1,000 and 2001‐2005 Medicaid admissions
per CAMOD
2004 Medicare Part B spending, and 2001‐2005 Medicaid 'Part B' spending
2004 Medicare spending per beneficiary and 2001‐2005 acute care Medicaid spending per CAMOD, by HRR, selected states
2004 Medicare spending per beneficiary and 2001-2005 acute
care Medicaid spending per CAMOD, by HRR, California
HRR-level regressions on selected outcomes
Medicaid Hospital Stays 30 Day Readmissions
e Hospital Stays
d Hospital Stays
+++
n/a
are Beds / 1000
ysician Visits
Ambulatory Care Sensitive Hospitalizations
Diabetes
COPD
CHF
Asthma
n/a
+++
n/a
+++
n/a
n/a
+++
n/a
+++
-----
+++
+++
++
+++
---
armacy Fills
rugs
ns per 1,000
of MDs in primary
++
+++
ed
0.39
+++
--0.53
+++
+
++
+++
++
+
+++
--
---
--
---
0.45
0.21
0.47
0.68
-
p < 0.01
p < 0.05
p < 0.10
essions are HRR-level regressions, and all Medicaid variables are measured on cash-assistance, Medicaid-only, FFS
d, using MAX data from 2001-2005. Table entries show significance level and direction of the parameter estimates.
spitali ations are
spitalizations
a e measured
meas ed among beneficiaries
beneficia ies with
ith the diagnosis (diabetes,
(diabetes COPD,
COPD etc.)
etc ) during
d ing a CY period.
pe iod
Conclusions
There is wide variation across states in
spending per Medicaid beneficiary
For example, NY spends more than twice as much per
beneficiary than CA on acute care
Spending is generally lower in the South, and higher in the
Mid Atlantic New England
Mid-Atlantic,
England, and the upper Midwest
Inpatient utilization only partially follows the contours of
acute care spending
p
g
 Low in New England; high in FL, LA, TX, and OK
There is much more interstate variation in mental health and
‘other acute’ spending than in inpatient, MD/OPD/Clinics, or
Rx, and much more variation in LTC than in acute spending
Volume of services drives relative
positioning, unit price is secondary
High-spending and low-spending states are different
from the national average primarily because of volume
(2/3), and only secondarily because of price (1/3)
 Inpatient, mental health, and other spending contribute
approximately
i
l equally,
ll while
hil variation
i i iin MD/OPD/Cli
MD/OPD/Clinic
i
has very little effect
 Inpatient
p
spending
p
g varies approximately
pp
y equally
q
y because
of volume and price, while MH and drugs variation is
driven almost entirely by volume
At the state level, Medicaid and
M di
Medicare
spending
di are unrelated
l t d
There is a weak relationship between Medicare and
Medicaid inpatient admissions/1,000
There is no relationship between Medicare Part B and
Medicaid outpatient spending
Inpatient hospital spending is a much larger component
of Medicare spending than of Medicaid spending
Within most states, Medicaid and Medicare
spending are strongly related at the HRR level
Inpatient admissions strongly related
Outpatient spending very weakly related
California a notable exception, with no relationship
between Medicare and Medicaid within state
Making sense of the MedicareM di id relationship
Medicaid
l ti
hi
Virtually
y zero state-level correlation in spending,
p
g and very
y
small correlation in inpatient admissions suggest that
Medicaid policy variables mediate the supply-utilization
relationship
p suggested
gg
by
y the Dartmouth Atlas
Relatively strong within-state relationship at the HRR level
for inpatient admissions suggests that, holding Medicaid
policy constant, supply of resources affects Medicare and
Medicaid utilization similarly
Very weak within-state relationship on outpatient spending
requires more investigation
Is more better in Medicaid?
At the state level,, some suggestion
gg
that more p
physician
y
visits are associated with lower readmission and lower
ACS rates
Strong association between larger fraction of primary
care physicians and lower hospitalization, and ACS
rates
At the state level, little indication that a higher volume
of mental health services or more prescription drug fills
are associated with lower hospitalization rates