More “Bang for the Buck”?
Measuring the Efficiency of State
Medicaid Spending
June 29, 2010
Presentation to the AcademyHealth Annual Research Meeting
Debra Lipson ● Margaret Colby ● Tim Lake
Su Liu ● Sarah Turchin
Background

Growth in Medicaid costs consistently
y
outpaced state tax revenues over the past
decade, accelerating by 8 percent in 2009

Medicaid payments now account for an
average
g of 22 percent
p
of states’ expenditures
p

Magnitude of Medicaid spending and its share
of state budgets leads federal and state
policymakers to ask: Are Medicaid dollars
spent efficiently?
2
Some State Medicaid Programs Appear to
Get More from Their Spending than Others
PMPM = per member per month; CAHPS = Consumer Assessment of Healthcare Providers and
Systems.
CAHPS measure: In 2004, among Medicaid recipients age 18 and over who reported making an
appointment
pp
for routine care within the p
past six months, the p
percentage
g who reported
p
always
y g
getting
g
an appointment as soon as they wanted. Source: 2006 AHRQ National Healthcare Quality Report.
3
Research Questions

Study purpose: define and measure the
efficiency
ffi i
off state
t t Medicaid
M di id spending
di

Research questions:
q
– What is the relationship between Medicaid cost and
quality?
– Do
D some states
t t gett more bang
b
f th
for
their
i Medicaid
M di id
buck?
– Are certain Medicaid p
policies or program
p g
features
associated with higher value in spending?*
* Examined in case studies; results not covered in this presentation
presentation.
4
Study Framework

Efficiency, also referred to as value, in the
Medicaid program context:
– Viewed from the purchaser perspective
– Examined as total Medicaid costs per output or
outcome
– Compared across state Medicaid programs

Relative to other states, efficient Medicaid
spending produces:
– Better outcomes for same cost
– Similar outcomes for lower costs
5
Approach and Methods

Developed exploratory efficiency measures:
– For four major groups of Medicaid beneficiaries
• Children
• Adults
• People with disabilities
• Elderly
– U
Used
d currentt M
Medicaid-specific
di id
ifi quality
lit measures and
d
available data, despite limitations
– Used relevant Medicaid costs: all service and
administrative costs but not DSH or UPL add-ons

To compare states, used the median scores as
benchmarks to reduce the influence of outliers
6
Exploratory Efficiency Measures

28 sets of cost and quality measures, divided
i t five
into
fi domains
d
i
1. Adults—HEDIS and CAHPS measures
2. Children—HEDIS measures
3. Children—National Immunization Survey and National
Survey of Children’s
Children s Health
4. Disabled—National Core Indicators (annual survey of
people with developmental disabilities)
5. Elderly—Nursing Home Compare (MDS measures for
the elderly residing in nursing homes for three or more
months))
HEDIS = Healthcare Effectiveness Data and Information Set
MDS = Minimum Data Set quality indicators for nursing home residents
7
Findings: Two- to Four-Fold Variation in
State Costs

Among
g all Medicaid enrollees,, PMPM costs
varied by a factor of three ($272 to $860)

Among populations covered by quality
measures in 2006, the state variation in costs
differed by
yp
population
p
group:
g
p
– Greatest variation for those with developmental
disabilities: $
$2,495
,
to $9,113
$ ,
PMPM
– Least variation for children from birth to age 17:
$141 to $556 PMPM
8
Findings: Most quality measures had tightly
clustered scores, but some varied greatly
100 0
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o
t
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yl
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e
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ld
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o
e
ga
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cr
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P
0.0
$0
Pregnant Females Who Received at least 80% of Recommended Prenatal Care Visits (HEDIS 2007) and PMPM Costs (2006) (N=22) Elderly Long‐Stay Nursing Home Residents Who Do Not Have ‐
Moderate to Severe Pain (NHC 2006) and PMPM Costs (2006) (N = 49)
DCHI
MD
MA
NJ CT
NY RI
SC NH
ALMI
VTPA
WI
MN
NC
ND
IN
TXMO
AR
VAMI
WV
DE
LASD
FL
TN
IA
KY ID CA
IL KSGA NE
CO
NM
MT
OR
OH
WA
WY
OK
NV
la 100.0
ta
n
re
P
d
e
d
n
e
m 80.0
m
o
c
e
R
f
o
%
0
8
n
a
h
t 60.0
r
e
ta )
e
r 6
0
G0
d (2
e
vi tsi
s
e
c iV
e
R 40.0
o
h
w
s
e
la
m
e
F
t
n
a 20.0
n
g
e
r
P
f
o
e
ga
t
n
e
rc
0.0
e
P
$0
AK
UT
No Statistically Significant C ‐Quality Relationship
Cost
Q
t lit R l ti hi
$2,000
$4,000
$6,000
$8,000
$10,000
PMPM Costs
KY
WV
OH
HI
IN
CA
MD
MA
NE
NM
VA
NJ
CO
WI
DC
MN
FL
No Statistically Significant C ‐Quality Relationship
Cost
Q
t lit R l ti hi
$200
$400
$600
$800
PMPM Costs
9
RI
NY
PA
TX MI
$1,000
$1,200
$1,400
Findings: Few significant correlations
between cost and quality
 Among 28 measures, we
found only three
statistically
i i ll significant
i ifi
cost-quality relationships
–

E.g., well
well-child
child visits for children
age three to six enrolled in
capitated arrangements
Butt th
B
the three
th
did nott tell
t ll a
consistent story about the
relationship between cost
and quality
–
–
Two positive correlations (higher
costs associated with higher
quality)
One negative correlation (lower
costs associated with higher
quality)
Children Ages 3‐6 With At Least One Well‐Child Visit in ‐
the Past Year (HEDIS 2007) and PMPM costs (2006), N= 25
100.0
)
6
0
0
(2
ra
e
Y
ts
a 80.0
P
in
ti
si
V
ld
i
h
C
‐ll
e
W 60.0
e
n
O
ts
a
e
L
ta
h
ti
w
, 40.0
6
‐
3
s
e
g
A
,
n
re
d
il
h
C 20.0
f
o
e
ga
t
n
e
rc
e
P
MA
DC
NY MDRI
CA
TXWV
WV
NJ
OHMI FL HI VA
IN
NE
WI
PA
KY
MN
NM
WA
MO
CO
OR
Statistically
Significant Cost‐Quality Relationship
p < 0.05, R² = 0.204
00
0.0
$0
$100
$200
$300
PMPM Costs
10
$400
$500
Scoring State Performance on the 28
Exploratory Efficiency Measures
 Benchmarks are
based on the
median score for
each cost or
quality measure
among states with
data
State
Quality
Score
Higher-quality, lowercost states
Higher-quality,
higher-cost states
Score=1
Score=2
State
Quality
Score
BenchBench
mark
(Median)
Lower quality, lower
Lower-quality
lowercost states
Lower quality,
Lower-quality
higher-cost states
Score=2
Score=3
State Cost
Benchmark
(Median)
11
State Cost
State Domain Scores and Tiers—HEDIS
Measures for Children (2006)
Tier A
Tier B
Tier C
California
Kentucky
Michigan
Nebraska
New York
Colorado
Florida
Hawaii
Maryland
Massachusetts
New Jersey
Ohio
Rhode Island
Virginia
West Virginia
Wisconsin
D.C.
Indiana
Minnesota
Missouri
New Mexico
Oregon
Pennsylvania
Texas
Washington
15 month olds:6 or
more visits
1
1
1
1
1
2
2
3
2
2
2
2
2
2
2
2
2
2
2
3
2
3
3
3
HEDIS: Well-Child Visits
15 month olds: 4 or Children Ages 3-6:
more visits
at least one visit
1
2
1
2
2
2
1
3
1
2
2
2
2
2
3
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
2
3
2
2
3
3
2
2
3
3
3
2
3
2
2
2
12
Children ages 12-21:
at least one visit
2
2
1
2
2
2
2
1
2
2
2
2
2
2
2
2
2
2
2
3
2
3
2
1
2
State Domain Tiers—HEDIS Measures for
Children (2006)
13
Findings: Patterns Within Measure
Domains

Within each domain, state scores on
exploratory efficiency measures were
generally correlated with one another

It was rare for a state to have the highest or
lowest scores for all measures within a domain

Many states lacked data for multiple domains
– Only
y eight
g states had q
quality
y data and therefore had
measures in all five domains for 2006
14
Findings: Patterns Across Measure
Domains

Varying performance across the five domains
was common
– Few states were high or low performers in all measures
or domains; all had different strengths and
weaknesses

States that frequently
q
yp
placed in Tier A or C did
not uniformly share characteristics such as
program size, reliance on managed care, or
underlying medical costs
15
Conclusions

Because cost and q
quality
y vary
y widely
y across
states and for most measures, but do not
appear to be correlated, there may be
opportunities
t iti to—
t
– Lower or control costs without sacrificing quality
– Increase quality without increasing costs,
particularly in states whose absolute scores on
quality measures are lower than the median
16
Policy Implications

Results offer national benchmarks for
assessing the value of state Medicaid
spending relative to quality

Policymakers seeking to improve the value of
Medicaid spending must consider both sides
of the value equation:
– Lowering costs in ways that do not harm quality
– Improving
I
i quality
li for
f li
little
l or no extra cost
17
Limitations and Avenues for Future
Research

Large number of states excluded from many
measures due to lack of data
– Some measures have data from only 18 states

Comparable Medicaid quality measures or data
unavailable for many Medicaid enrollee groups

Costs in exploratory efficiency measures are
not risk-adjusted
18
For More Information

Please contact
– Debra Lipson
• dlipson@mathematica-mpr.com
– Margaret Colby
• mcolby@mathematica-mpr.com

Thanks to our sponsor
– U
U.S.
S D
Department
t
t off H
Health
lth and
dH
Human S
Services,
i
Assistant Secretary for Planning and Evaluation,
Office of Health Policy
19