Health Insurance Demand Responses from New Price Structures Offered by Consumer Directed Health Plans

1. Health Insurance Demand Responses from New Price Structures Offered by Consumer Directed Health Plans Stephen T Parente$,# Roger Feldman# Jean Abraham# Jon B Christianson# University of Minnesota Department of Finance$ and Division of Health Policy and Management# 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 • New (and early) Plan Choice Estimation Elasticity Results • Limitations • Summary • Next Steps

3. Health Toolsand Resources Health Coverage $$ Annual Deductible Definity HealthCareAdvantage Web- and Phone-Based Tools Preventive Care 100% Annual Deductible ‘Classic’ CDHP Model – Definity Health • Health Reimbursement Account (HRA) • Employer allocates HRA1 • Member directs HRA • Roll over at year-end • Apply toward deductible2 • Health Coverage • Preventive care covered 100% • Annual deductible • Expenses beyond the HRA HRA • Health Tools and Resources • Care management program • Internet enabled 1 Employer selects which expense apply toward the Health Coverage annual deductible. 2 Paid out of employer’s general assets.

4. Economic Analysis Motivation • ‘Donut hole’ and savings account are new ‘prices’ to consider in the demand for health insurance with expected negative and positive responses, respectively. • Price sensitivity to different benefit options (i.e., premium, account, donut, coinsurance) could significantly affect take-up of CDHPs. • Builds on existing literature of high deductible health plans (HDHPs) (Keeler, Newhouse, Phelps, 1977). CDHPs (and in particular HSAs) introduce a new kink in the budget constraint.

5. Money b a CDHP Budget c Coinsurance Plan Budget Medical Care Low Use Medium Use High Use Conceptual Model of CDHP

6. Data Sources • 2002-3 health plan choice data from 4 large employers participating in a Robert Wood Johnson Foundation funded study on CDHPs with national representation. • Employee premium • CDHP Account contribution • Deductible • Coinsurance • Employee characteristics: Worker’s age, gender, wage income, single/family coverage

7. Plan Choice Model Analytic Approach • Plan Choices: HMO, 3 PPOs (low, medium, high), 3 CDHPs with Health Reimbursement Accounts (low and high) • Utility-maximization assumption where Uhj = aj + Zj + Xhj + ehj • 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 (aj )

8. Plan Choice – Descriptive Statistics Notes: Chronic illness measure is for the household. Income is wage income.

9. Price elasticity estimates from the plan choice Model 1: Use only prices and plan effects

10. Price elasticity estimates from the plan choice Model 2: Add income, dependents, gender, age

11. Price elasticity estimates from the plan choice Model 3: Add health status and interact w/prices

12. Results from full plan choice model • Compared to a low option PPO: • Age affects • Positive High option PPO effect • Negative CDHP effect • Income effects • CDHP has greatest positive relationship • All plans are positive compared to low option PPO • Gender effects • Positive High option PPO effect • Negative CDHP effect • Chronic illness effects • CDHP has greatest and large positive relation • High option PPO has negative effect • Family coverage effects • Negative relationships across the board compared to low option PPO. • Strongest negative effect in low-option PPO.

13. Limitations • These are early results and are contrary to our previous findings (e.g., only income was highly correlated to CDHP choice). • Need to use nested logit approach to deal with IIA. • Claims based risk adjustors could have missing data issues. • Firm specific effects may be in plan that we not accounted for. Why – we are using this model for CDHP simulation in combination with MEPS. • Low premium elasticity needs to be thoroughly examined. • Is this a real effect of increasing the price of employer-offered insurance through deductibles and copayments. • If real, this may explain the very low take-up in CDHPs with significant cost-sharing benefit design attributes. • Don’t account for cross-price elasticity effects.

14. Summary • Premium, coinsurance and Donut can and ALL should be modeled when looking at CDHPs. • They produce different and significant effects. • Across the largest set of employers examined to date, we evidence of some favorable election to CDHPs in with respect to age, but not chronic illness. • Policy proposals will need to consider price effects to develop effective welfare improving social policy.

15. Next Steps CDHP & PPO Branches for Nested Logit Design. Examine impact of other policy proposals and/or HSA plan designs on take-up. Refresh model with 2004-2005 choices currently being collected, including HSA choice in the FEHBP population.

16. Thank YouFor more information go to:www.ehealthplan.orgor email sparente@csom.umn.edu

17. Plan Choice – Conditional Logit (1 of 3) Adjusted r-square: 0.43458 , Reference PPO_Low

18. Plan Choice – Conditional Logit (2 of 3) Adjusted r-square: 0.43458 , Reference PPO_Low

19. Plan Choice – Conditional Logit (3 of 3) Adjusted r-square: 0.43458 , Reference PPO_Low