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Medicare Savings Due to Prescription Drug Coverage for Near-poor Elders
Christine Bishop, Ph.D.1
Andrew Ryan, M.A.1
Daniel Gilden, M.S.2
Cindy Parks Thomas, Ph.D. 1
Joanna Kubisiak, M.S.2
Donald Shepard, Ph.D. (PI)1
AcademyHealth Annual Research MeetingWashingtonJune 8, 2008
1Schneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University
2JEN Associates Inc.
22
Research Support
Centers for Medicare & Medicaid Services
CMS 500-00-0031/T.O. #2Project Officers:
William Clark and Karyn Anderson
33
Offset: Access to Prescription Drugs Expected to Reduce
Use and Cost of other Health Services Reduce or lessen acute illness episodes Thus reduce health services use and cost (“offset
effect”) However, findings of previous research are mixed-e.g.
Significant or modest cost offsets: Shang (2005), Yang (2004) No significant savings: Stuart (2004), Briesacher (2005) Increased health services spending! Gilman (2004)
Studies of specific conditions are more likely to find offsets from providing Rx coverage
See Cindy Parks Thomas, “How Prescription Drug Use Affects Health Utilization and Spending by Older Americans: A Review of the Literature“
http://assets.aarp.org/rgcenter/health/2008_04_rx.pdf
44
Study Question
Is access to prescription drugs for near-poor elders associated with lower acute care utilization? Hospitalization Hospital days Medicare spending
55
Prescription Drug Insurance Wisconsin SeniorCare Medicaid Waiver
Started September 2002 Age 65+ Income < 200% Federal Poverty Level (FPL) Not Medicaid-eligible No previous state drug plan for seniors
Enrollees unlikely to have had previous insurance
(Waiver has been reauthorized through December 2009)
66
Wisconsin SeniorCare: Program Design
$30 enrollment fee Deductible
0 for enrollees with income less than 160% of FPL $500 for income > 160% FPL
Copayments $15 for brand-name drugs $5 for generic drugs
No cap on benefits Can enroll at any time
77
Coverage began September 1, 2002;Enrollment grew from 38,000 to 56,000 by December 2002
-
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000 Se
p-02
Nov
-02
Jan-
03
Mar
-03
May
-03
Jul-0
3
Sep-
03
Nov
-03
Jan-
04
Mar
-04
May
-04
Jul-0
4
88
SeniorCare enrollees differ from aged Medicare populationBase Year Data (2001)
Source: Medicare Enrollment Files 2001
All differences significant at p<.01
SeniorCare WI Medicare 5%
Ratio
N 59,201 29,395
Female 75.4% 58.9% 1.28
65-69 15.7% 25.3% 0.62
70-74 21.7% 25.5% 0.85
75-79 24.9% 21.3% 1.17
80-84 20.5% 15.3% 1.34
85 and older 17.2% 12.7% 1.35
White 98.0% 97.0% 1.01
Black 1.3% 2.0% 0.66
Rural 53.3% 39.5% 1.35
Using LTC in Community 0.7% 0.3% 2.05
Nursing Home 0.5% 5.6% 0.09
99
Enrollees: slightly more average monthly service use than all Medicare beneficiaries
2001 Medicare Claims SeniorCare Medicare 5% Ratio
Acute Care Hospital $155 $148 1.05
Home Health $11 $9 1.22
Hospice $1 $3 0.33
Physician $77 $74 1.04
Skilled Nursing Facility $25 $33 0.76
Medicare Part A $201 $201 1
Medicare Part B $156 $153 1.02
Medicare Total $358 $354 1.01
Patient Co-Pay $55 $56 0.98
Patient Deductible $18 $13 1.38
Third Party Payment $3 $5 0.6
1010
Establish comparison group
Find Ohio elders who would have joined SeniorCare had it been offered to them
Age, sex, race, diagnoses Medicare beneficiaries, not on Medicaid Similar past health services utilization Low income Not insured for Rx drugs
1111
Matched WI enrollees to comparison beneficiaries from Ohio
“Propensity score” (probability of enrollment) fitted on all WI beneficiaries with SSA income less than threshold – by SSA status group --all demographics plus Health services use in 3 months prior to enrollment Census block income distribution SSA payments
For each WI enrollee -- locate OH beneficiaries with exact match on 5-year age range, sex, race, urban-rural Prior Medicaid eligibility, prior HMO enrollment Nursing home status, index month Social Security family status variables
From “exact match” group choose one with “nearest neighbor” propensity score
1212
Time frame: Need full-year post-enrollment
Medicare data available through December 2003 only
Therefore include if enrolled through December 2002
Enrolled in first 4 months
Outcome measures Hospitalization- any admission Hospital days Total Medicare expenditures
1313
Three Analytic Approaches
Compare means for post-index year Relies on match and comparable prices, access
Compare differences in annual means, pre-post
Multivariate estimate of difference in differences for quarterly values
1414
Hospitalization RatesWisconsin Enrollees and Ohio Matched Comparison
N = 49,724*2
12 Months Pre-index
(Mean)***
12 MonthsPost-index
(Mean)***
Absolute Difference
***
Percentage Difference
WI Enrollees 0.221 0.247 0.026 11.8%
OH Matched Beneficiaries 0.184 0.225 0.041 22.3%
Difference 0.037 0.022 -0.015 -10.5%
***p < 0.01
1515
Hospital DaysWisconsin Enrollees and Ohio Matched Comparisons
N = 49,724*2
12 Months Pre-index
(Mean)***
12 MonthsPost-index
(Mean)***
Absolute Difference
***
Percentage Difference
WI Enrollees
1.77 2.26 0.49 27.7%
OH Matched Beneficiaries
1.46 2.15 0.69 47.3%
Difference 0.31 0.11 -0.2 -64.5%
***p < 0.01
1616
Total Medicare ExpendituresWisconsin Enrollees and Ohio Matched Comparison
N = 49,034*2
12 MonthsPre-index
(Mean)***
12 MonthsPost-index
(Mean)
Absolute Difference
***
Percentage Difference
***
WI Enrollees $5,197 $6,159 $961 18.5%
OH Matched
Beneficiaries $4,743 $6,051 $1,307 27.6%
Difference $454 $108 -$346 -9.1%
***p < 0.01
1717
0.0
2.0
4.0
6.0
8A
vera
ge %
Med
icar
e in
patie
nt u
tiliz
atio
n
-6 -4 -2 0 2 4Index Quarter
WI enrollee OH matched comparisonDifference WI - OH
% Inpatient utilization by quarter
1818
0.2
.4.6
Ave
rage
inpa
tient
day
s
-6 -4 -2 0 2 4Index Quarter
WI enrollee OH matched comparisonDifference WI - OH
Inpatient days by quarter
1919
05
001
000
150
0A
vera
ge M
edi
care
spe
ndin
g in
dol
lars
-6 -4 -2 0 2 4Index Quarter
WI enrollee OH matched comparisonDifference WI - OH
Medicare spending by quarter
2020
Difference in Difference Model
Δ Outcome it = β1 Zi + β2 Δ Age squaredit +
β3 Δ programit + β4 Δ programi,t-2 + β5Δprogrami,t-3 + β6
Δprogram i,t-4 + δΔquartert + εit
Where Z is a vector of time invariant variables (gender, race, index age, income, diabetes, coronary heart disease, cerebrovascular disease, COPD, and arthritis)
Program impact for period is computed as sum of coefficients β3 +β4 +β5 + β6
2121
Wisconsin and Matched Ohio Comparison Difference In Difference Analysis (4 post-enrollment quarters)
Robust standard errors in parentheses * p<.1 *** p<.001
Quarter Indicators and patient characteristics included
(1) (2) (3)Coefficient Δ Any inpatient
utilizationΔ Inpatient days Δ Medicare
SpendingΔ Age squared 0.000 -0.000 -0.000
(0.000) (0.000) (0.000)
Δ program it -0.003 -0.011 -65.819
(0.002) (0.018) (40.630)
Δ program it-1 0.000 -0.028 -57.286
(0.002) (0.020) (40.934)
Δ program it-2 -0.003 -0.002 -10.978
(0.002) (0.022) (41.414)
Δ program it-3 -0.004* -0.023 -54.447
(0.002) (0.022) (41.712)
Σ Δ program -.010 *** (.002)
-.064*** (.021)
-188.530*** (45.692)
Observations 867,204 867,204 864,886R-squared 0.00 0.00 0.00
2222
Computed Program Impact (over 4 quarters)
Any InpatientUtilization
Inpatient Days MedicareSpending
-.010 *** (.002)
-.064*** (.021)
-188.77*** (44.40)
2323
Limitations
Effects limited to first year Long-term effects expected for pharmaceutical therapies
Have not yet fully accounted for selection into SeniorCare First month enrollees were on wait list to join Later month enrollees may have been impelled by new illness
State (OH vs. WI) health and regulatory systems differ Could have affected both levels and differences
Matching limited to observed variables Proxies only for low income status
Beneficiaries who died are included– answers program cost question, but needs more thought
2424
Conclusions Even in one year, near-poor enrollees in a
pharmacy insurance program experienced reduced hospital use and Medicare savings
However, savings ($350 per year) are small relative to program cost (about $1030 per year)
Decline in services use suggests positive impact on health and wellbeing
2525
Implications: Policy
For low-income seniors not previously covered by prescription drug insurance Medicare Part D coverage likely has a valuable health payoff
Savings in Medicare expenditures are unlikely to exceed program cost for beneficiaries in year one
2626
Implications: Research
Impacts on health and services use over a longer time period may be larger Extend studies to longer time frame
Advance matching methods: Use of income proxies is a contribution, but needs more work SSA status SSA payment amount Census block distribution
2727