1. 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 Meeting Washington June 8, 2008 1 Schneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University 2 JEN Associates Inc.

2. 22 Research Support Centers for Medicare & Medicaid Services CMS 500-00-0031/T.O. #2 Project Officers: William Clark and Karyn Anderson

3. 33 Offset: Access to Prescription Drugs Expected to Reduce Use and Cost of other Health Services l Reduce or lessen acute illness episodes l Thus reduce health services use and cost (“offset effect”) l 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) l 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

4. 44 Study Question Is access to prescription drugs for near- poor elders associated with lower acute care utilization?  Hospitalization  Hospital days  Medicare spending

5. 55 Prescription Drug Insurance Wisconsin SeniorCare Medicaid Waiver l Started September 2002 l Age 65+ l Income < 200% Federal Poverty Level (FPL) l Not Medicaid-eligible l No previous state drug plan for seniors  Enrollees unlikely to have had previous insurance (Waiver has been reauthorized through December 2009)

6. 66 Wisconsin SeniorCare: Program Design l $30 enrollment fee l Deductible  0 for enrollees with income less than 160% of FPL  $500 for income > 160% FPL l Copayments  $15 for brand-name drugs  $5 for generic drugs l No cap on benefits l Can enroll at any time

7. 77 Coverage began September 1, 2002; Enrollment grew from 38,000 to 56,000 by December 2002

8. 88 SeniorCare enrollees differ from aged Medicare population Base Year Data (2001) Source: Medicare Enrollment Files 2001 All differences significant at p<.01

9. 99 Enrollees: slightly more average monthly service use than all Medicare beneficiaries

10. 10 Establish comparison group l Find Ohio elders who would have joined SeniorCare had it been offered to them l Age, sex, race, diagnoses l Medicare beneficiaries, not on Medicaid l Similar past health services utilization l Low income l Not insured for Rx drugs

11. 11 Matched WI enrollees to comparison beneficiaries from Ohio l “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 l 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 l From “exact match” group choose one with “nearest neighbor” propensity score

12. 12 l 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 l Outcome measures  Hospitalization- any admission  Hospital days  Total Medicare expenditures

13. 13 Three Analytic Approaches l Compare means for post-index year  Relies on match and comparable prices, access l Compare differences in annual means, pre-post l Multivariate estimate of difference in differences for quarterly values

14. 14 Hospitalization Rates Wisconsin Enrollees and Ohio Matched Comparison N = 49,724*2 ***p < 0.01

15. 15 Hospital Days Wisconsin Enrollees and Ohio Matched Comparisons N = 49,724*2 ***p < 0.01

16. 16 Total Medicare Expenditures Wisconsin Enrollees and Ohio Matched Comparison N = 49,034*2 12 Months Pre-index (Mean) *** 12 Months Post-index (Mean) Absolute Difference *** Percentage Difference *** WI Enrollees $5,197$6,159$96118.5% OH Matched Beneficiaries $4,743$6,051$1,30727.6% Difference $454$108-$346-9.1% ***p < 0.01

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20. 20 Difference in Difference Model Δ Outcome it = β 1 Z i + β 2 Δ Age squared it + β 3 Δ program it + β 4 Δ program i,t-2 + β 5 Δprogram i,t-3 + β 6 Δprogram i,t-4 + δΔquarter t + ε it l Where Z is a vector of time invariant variables (gender, race, index age, income, diabetes, coronary heart disease, cerebrovascular disease, COPD, and arthritis) l Program impact for period is computed as sum of coefficients  β 3 +β 4 +β 5 + β 6

21. 21 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 utilization Δ Inpatient days Δ Medicare Spending Δ Age squared0.000-0.000 (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) Observations867,204 864,886 R-squared0.00

22. 22 Computed Program Impact (over 4 quarters) Any Inpatient Utilization Inpatient DaysMedicare Spending -.010 *** (.002) -.064*** (.021) -188.77*** (44.40)

23. 23 Limitations l Effects limited to first year  Long-term effects expected for pharmaceutical therapies l 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 l State (OH vs. WI) health and regulatory systems differ  Could have affected both levels and differences l Matching limited to observed variables  Proxies only for low income status l Beneficiaries who died are included– answers program cost question, but needs more thought

24. 24 Conclusions l Even in one year, near-poor enrollees in a pharmacy insurance program experienced reduced hospital use and Medicare savings l However, savings ($350 per year) are small relative to program cost (about $1030 per year) l Decline in services use suggests positive impact on health and wellbeing

25. 25 Implications: Policy l For low-income seniors not previously covered by prescription drug insurance Medicare Part D coverage likely has a valuable health payoff l Savings in Medicare expenditures are unlikely to exceed program cost for beneficiaries in year one

26. 26 Implications: Research l Impacts on health and services use over a longer time period may be larger  Extend studies to longer time frame l Advance matching methods: Use of income proxies is a contribution, but needs more work  SSA status  SSA payment amount  Census block distribution

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