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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

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Study Question

Is access to prescription drugs for near-poor elders associated with lower acute care utilization? Hospitalization Hospital days Medicare spending

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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

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10,000

20,000

30,000

40,000

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90,000 Se

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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

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vera

ge %

Med

icar

e in

patie

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atio

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-6 -4 -2 0 2 4Index Quarter

WI enrollee OH matched comparisonDifference WI - OH

% Inpatient utilization by quarter

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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

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150

0A

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edi

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-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

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