1. Health Savings Accounts: Early estimations on national take-up from 2003 MMA and future policy proposals Stephen T Parente Roger Feldman Jean Abraham Jon B Christianson Funded by the Robert Wood Johnson Foundation Health Care Financing and Organization Initiative (HCFO) and the Department of Health and Human Services

2. Presentation Overview  Consumer Driven Health Plan Overview  Research Questions  Data & Analytic Approach  Plan Choice Estimation Results  MEPS Data  Policy Simulation Results  Implications  Next Steps

3. ‘Classic’ CDHP Model – Definity Health Definity Health Care Advantage Web- and Phone- Based Tools Health Tools and Resources Care management program Internet enabled Health Coverage Preventive care covered 100% Annual deductible Expenses beyond the PCA Personal Care Account (PCA) Employer allocates PCA 1 Member directs PCA Roll over at year-end Apply toward deductible 2 Annual Deductible Preventive Care 100% Health Coverage Annual Deductible 1 Employer selects which expense apply toward the Health Coverage annual deductible. 2 Paid out of employer’s general assets. PCA $$

4. The HSA Model An HSA is a special account owned by the individual where tax- free contributions to the account are used to pay for current and future medical expenses. Used with High Deductible Health Plans (HDHPs) Bush Administration has proposed refundable tax credits for individuals to purchase plans with HSAs. Qualified HDHPs now offered by: UnitedHealth, the Blues, Aetna (w/preventive meds), Cigna, Humana and Kaiser Permanente Annual Deductible Preventive Care 100% Health Coverage Annual Deductible HSA $$

5. Nearly National Appeal: States where the study employers’ 1 st year CDHP take-up was >5% >5% 0.1 - 5% 0% Take-up Data based on 6 large employers representing ~250,000 covered lives with initial year offerings from 2001 to 2oo3.

6. Research Questions  How does the introduction of Consumer Directed Health Plans (CDHPs) into mainstream health insurance affect plan choice?  What is the expected take-up rate of HSAs in the individual market from the 2003 MMA?  What is the impact of the Administration’s proposed HSA subsidies? Take-up rate of HSAs Impact on the uninsured Cost of the subsidy  What is the impact of other possible subsidy designs?

7. Data Sources  2002 health plan choice data from 3 large employers participating in a Robert Wood Johnson Foundation funded study on CDHPs Employee premium, deductible, coinsurance, worker’s age, gender, wage income, single/family coverage  2001 Medical Expenditure Panel Survey (MEPS) Household Component: All adults age 19-64 not enrolled in public insurance programs and not full-time students during Round 1  Demographic, employment, and health insurance information Linked Insurance Component: Subset of workers offered employer coverage and their plan choices  Plan type, premiums, contributions, coinsurance, copayments and deductibles  eHealthinsurance.com Individual HSA plan information

8. Estimate plan offerings using linked data Merge employer data Estimate hedonic premium regression Assign plan choices to full MEPS sample Estimate plan choice regression Use parameter estimates to predict plan choice probabilities for MEPS Re-scale take-up rates Define HSA plan design & premium Simulate impact of proposed policies Model Estimation Choice set Assignment/ Prediction Policy Simulation Analysis Design MEPS Data Sources CDHPseHealthinsurance

9. Plan Choice Model Analytic Approach  Plan Choices: HMO, 3 PPOs (low, medium, high), 2 CDHPs with Health Reimbursement Accounts (low and high)  Utility-maximization assumption where U hj =  j +  Z j +  X hj + e hj  Estimate a conditional logit model of plan choice using the pooled, employer data Explanatory variables  Plan attributes (Z) Annual tax-adjusted employee premium ($1000s dollars) Savings/reimbursement account size ($1000s dollars) Donut hole: difference between annual deductible and account size ($1000s dollars) Coinsurance rate (i.e.,.10 = 10% coinsurance)  Interactions between employee and plan attributes (X) Age, female, wage income, family contract  Plan-specific constants (  j )

10. Plan Choice – Descriptive Statistics

11. MEPS Data We used the MEPS Household Component to identify adults 19-64 who were not full-time students and not enrolled in public insurance. We then subdivided them into 2 groups: (1) non- offered adult population and (2) workers with an offer of employer group coverage. Descriptive Statistics (Means reported with SD in parentheses) Non-Offered Population (N=36,816,103) Offered Population (N=84,719,584) Age37.96 (12.6) 40.54 (10.84) Female.477 (.49).46 (.49) Income$17,974 (21,286) $40,454 (28,741) Single.56 (.49).39 (.49)

12. Price Elasticity estimates Associated with CDHP Design

13. Assigning health plans to MEPS workers with an offer of employer coverage 1.Used the MEPS linked sample (n=3,127) to estimate a model for the number of health plans (e.g., PPO, HMO) offered to eligible workers. 2.Predicted the number and types of plans available to each offered worker in the MEPS Household Component using these model estimates (max of 4 plans). 3.Assigned plan attributes based on sample distributions from MEPS linked file and developed a hedonic price model for predicting premiums for specific plan designs.

14. Policy Simulations - 1  Baseline take-up of HSAs from the Medicare Modernization Act of 2003  Simulation (1): Bush Administration’s proposal Refundable tax credit up to 90% of premium; maximum of $1000/adult, $500/child (up to two)  Subsidy for singles with no dependents phased out at $30,000 adjusted gross income and $60,000 for families  Simulation (2): Low income buy-in subsidy Set HSA premium at $0 for < $15,000 annual income; 50% of premium for incomes between $15,000-$40,000; 75% of premium for incomes between $40,000 and $60,000.

15. Policy Simulations - 2  Simulation (3): Full subsidy of HSA premium Set HSA premium to $0 for all, regardless of income.  Simulation (3a): Full subsidy of HSA premium for “generous” HSA policy  Simulation (4): Full subsidy of HSA premium for the non-working, non-public insurance population

16. Baseline Impact of MMA 2003 NOTE: Population is 19-64, non public insurance

17. Sim#1: Administration’s* Proposal NOTE: Population is 19-64, non public insurance. *Proposal as interpreted from February, 2004 U.S. Treasury Blue Book.

18. Sim #2: Low-income Buy-in Subsidy NOTE: Population is 19-64, non public insurance Income < 15K, free; 25K to 45K, 50% off; 40K to 60K, 25% off

19. Sim #3: Full Subsidy for HSAs NOTE: Population is 19-64, non public insurance

20. Sim #3A: Full Subsidy for Generous HSA NOTE: Population is 19-64, non public insurance

21. Sim #4: Full Subsidy for Non-working NOTE: Population is 19-64, non public insurance

22. Cost per newly insured Estimated reduction in uninsured Total Estimated Annual Cost Per Capita Cost Administration’s Proposal (Sim#1) 2,924,949$8,075,081,354$2,761 Low-income Buy-In (Sim#2)4,495,887$12,219,668,960$2,718 Full subsidy (Sim#3)12,819,856$69,214,319,880$5,399 Full subsidy Generous HSA (Sim#3a) 23,507,540$211,118,893,800$8,981 Full subsidy Non-working (Sim#4) 3,143,487$11,234,374,714$3,574

23. Diminishing Subsidy Returns Sim #1 Sim #2 Sim #3 Sim #4 Sim #3A

24. Policy Implications - 1  Take-up elasticity comparisons -.3 to -.4 in the non-offered population (Marquis et al, 2004) – Ours are similar.  Take-up elasticity increases as income increases. This contrasts with the literature. Why? Probability of HSA take-up is positively correlated to income (as opposed to an HMO, which is usually negatively correlated). Implication is that lower income population need more inducement to take-up an HSA  Plan design matters. Greater take-up from a reduction in the donut hole than an increase in the account size.

25. Policy Implications - 2  Other influential factors Targeting the right population  Need more targeting of subsidy – Want to avoid providing too much subsidy to the group market. Implementation complexity  Timing of tax credit distribution – needs to be available at time of premium payment. Without this, the delay could be 12 months or later.  Want to avoid unnecessary administrative eligibility barriers like those experienced in the Trade Adjustment Assistance Reform Act of 2002 Supply side embrace  Compared to Medicare Medical Savings Account in HIPAA and other past policies, insurers are willing to build a new product.

26. Caveats  Did not observe the uninsured.  Did not include health status in the plan choice model.  Assumed all consumer had opportunity for guaranteed issue.  Made assumptions about how employers would offer different plane choice sets of HRAs and HSAs.

27. Next Steps  Refine the model to account for the following: Use expenditures in CDHPs plan to recalibrate premium estimates. Offered but turned down coverage Premium inflation assumptions  Examine impact of other policy proposals and/or HSA plan designs on take-up.

28. Summary  Untouched, the 2003 MMA HSAs will have take-up of ~3.2 million.  The 2004 Administration plan would double HSA take-up and reduce the uninsured by ~2.9 million at a cost of ~$8 billion, an average of $2,761 per person.  Full subsidy of premium yields best case reduction of uninsured 86%, (~23.5 million person reduction) at a cost of ~$210 billion annually, an average of $8,981 per person.  Offering a free HSA to the non-working, non-public population reduces the uninsured, but less efficiently than income targeted subsidies.

29. Thank You For more information go to: www.ehealthplan.org or email sparente@csom.umn.edu www.ehealthplan.org

30. Supporting Slides

31. Cross price-elasticity* of uninsured take-up with respect to HSA premium subsidy * Calculated as the MEPS survey-weighted average of each person’s: - (pr uninsured|status quo - pr uninsured|Δ HSA premium) * (HSA premium @status quo/pr uninsured|status quo)

32. Cross price-elasticities of uninsured take-up with respect to “donut hole” and account

33. Price-Sensitivity Estimates from the Literature  Take-Up Non-offered population [Marquis and Long, 1995; Marquis et al. 2004]  -.3 to -.4 Offered population [Chernew et al., 1997; Shiels et al., 1999; Blumberg et al., 2001; Gruber and Washington, 2005]  -.01 to -.2

34. Impact of the Simulations by Income