Why all the Fuss about Prescription Drug Coverage? Out-of-Pocket Health Care Expenditures

1. Why all the Fuss about Prescription Drug Coverage?Out-of-Pocket Health Care Expenditures Edward C. Norton University of North Carolina at Chapel Hill

2. Acknowledgments • Hua Wang • National Center for Health Statistics • Sally C. Stearns • UNC at Chapel Hill • Funding from National Institute on Aging • R01-AG16600

3. Health Care Expenditures • Long literature in health economics • Predict health expenditures • At individual and national level • Focus is on total or public expenditures • Concern is with public finance and resources

4. Out-of-Pocket Expenditures • Little research on OOP expenditures • No one keeps track, hard to calculate • Important • For elderly Americans, OOP risk is high • Distributional consequences of public insurance • Affects economic behavior

5. Two Striking Graphs • First shows out-of-pocket health care expenditures by age • Second shows out-of-pocket health care expenditures as a fraction of income by age

6. Figure 1

7. Figure 1 • Mean OOP expenditures rise with age • $85 per month at age 66 • $485 per month at age 95 • Division between LTC and non-LTC • All increase is due to LTC • Young and old elderly face different risk • Different magnitude • Different composition

8. Figure 2

9. Figure 2 • What fraction spend at least half income on health care? • >10% at age 81 • >25% at age 90

10. Who and What? • Who faces the highest OOP expenditure risk? • What are the implications?

11. Outline of Talk • Medicare and Medicaid • Data • Regression Results • Implications • Distributional • Behavioral

12. Non-LTC Insurance • Inpatient, physician, pharmaceuticals • Medicare is fairly comprehensive • Many have Medigap policies • Medicaid for poorest 15% • Private for about 67%

13. Who Pays non-LTC? • Predictors • Health shocks, health status • Insurance (e.g., Medicaid pays for much of pharmaceuticals) • Some access issues (e.g., urban/rural) • Hypotheses • Low R-squared • Demographics should not predict well

14. LTC Insurance • Nursing homes (long-term and skilled) • Medicare provides minimal insurance • Medicaid is safety net • Deductible = wealth - $2000 • Co-payment = income - $30 • Little private insurance

15. Who Pays LTC? • Predictors • Health shocks, health status, disabilities • Substitutes: spouse, child • Ethnicity • Hypotheses • High R-squared • Demographics should predict well

16. Methods • Predict Pr($OOP/month > Threshold) • Non-LTC $100, $500 • LTC $100, $1000 • Control for age, sex, race and ethnicity, education, income, rural, marital status, year, census region

17. Other Methods • Threshold gets at most relevant variation • Two-part models: no action in first part for non-LTC, no action in second part for LTC • Looked at components of non-LTC (inpatient, physician, pharmaceuticals) • Looked at OOP/income

18. Data • Medicare Current Beneficiary Survey • 1992-1998 • Focus on aged 65 and older • ~10,000 people per year • Advantages • Linked to Medicare claims • Detailed diaries for all other expenditures

19. Data • Data on 24,636 unique people and 709,413 person months • OOP expenditures per month • Overall mean is $151 (highly skewed) • Mean of $70 for LTC • Mean of $28 for pharmaceuticals • Average age is 75 • 40% men, 89% white, 37% widowed • 13% Medicaid eligible

20. Regression Results • Hypotheses confirmed • Low R-squared for non-LTC (<.03) • High R-squared for LTC (>.26) • Age, sex, race, marital status all predict LTC extremely well, as expected

21. Implications: Distributional • Focus on the implications, not regressions • Distributional • Not much for non-LTC • Public LTC insurance incomplete, suboptimal • Spousal impoverishment

22. Implications: Behavioral • Behavioral • Savings over life cycle • Red herring, end-of-life expenditures • Changing longevity and savings • Flat-of-the curve medicine • Alternative motivation for exchange • Political economy

23. Distributional (1) • Not much consequence for non-LTC insurance • No one group seems greatly affected by OOP expenditures

24. Distributional (2) • Medicaid incomplete LTC insurance • Brown and Finkelstein (NBER 2004) • Medicaid structured in a way that discourages private insurance • Implicit tax • Elderly buy less LTC insurance than they want • Elderly have less consumption smoothing • This affects certain groups more: oldest-old, women, widows, whites, unmarried

25. Distributional (3) • Married persons pay less LTC • Perhaps spouse and child are substitutes • Or Medicare Catastrophic Coverage Act of 1988 works • Spousal impoverishment not repealed • More wealth and income protected if spouse • Lowers cost of nursing home care • As predicted, in MCBS, married persons have lower OOP payments conditional on NH entry

26. Behavioral (1) • Savings over life cycle • Hubbard, Skinner, Zeldes (1995) • Means-tested public insurance affects savings • Some will save less than otherwise • The longer you live, the higher the risk • Hard to balance precautionary savings, optimal consumption

27. Behavioral (2) • “Red Herring” literature • Importance of age in predicting end-of-life expenditures • There are two stories here, not one • Story for LTC expenditures is different • Age effect huge even after controlling for time until death (although endogenous) • Delicate relationship between disability, longevity, end-of-life, substitutes to NH

28. Behavioral (3) • Recent gains in longevity, especially for men • If unanticipated, then savings too low • Greater longevity means higher eventual OOP expenditures for many than anticipated

29. Behavioral (4) • Flat-of-the-curve medicine • Marginal benefits low, below average cost • This is more likely a problem for highly insured services, not LTC

30. Behavioral (5) • Literature on intergenerational transfers • If informal care is substitute (Van Houtven and Norton 2004) • If elderly parent has much wealth • May be reason to provide informal care, even if no exchange, only bequest, to preserve wealth

31. Behavioral (6) • Political science • Why did Congress pass the Medicare Modernization Act? • Focus on prescription drugs • Relatively little OOP on drugs • For young elderly bigger issue, they VOTE

32. Future Research • Other countries • Less economic research on long-term care in non-US countries than in US • Issues no less important • Hope that this conference, iHEA, better data sets, will lead to more research

33. Out-of-Pocket Expenditures • People respond to what hits their wallet • Expenditure risk high for LTC • Expenditure risk generally low for other • Many behavioral implications