Consumer Driven Health Plans: Early Findings from the Field and Future Directions

1. Consumer Driven Health Plans:Early Findings from the Field and Future Directions Stephen T. Parente, Roger Feldman, Jon B. Christianson University of Minnesota January, 2004 Funded by the Robert Wood Johnson Foundation Health Care Organization and Financing Initiative For more information: sparente@csom.umn.edu

2. Presentation Objectives • Describe the CDHP business model. • Illustrate the mechanics of a CDHP using Definity Health as an example. • Provide an Overview of our RWJ evaluation of Definity. • Present current analysis results. • Opportunities and conundrums of CDHPs.

3. Patients Dissatisfaction with provider access Patient incentives are to consume Limited choices of benefits and providers Combative relationship with managed care companies Providers Loss of autonomy Erosion of physician/patient relationship Misalignment of physician reimbursement and incentives Employers Plan costs are increasing Employees are not happy Increase of employer administration burdens Issues Driving CDHP Creation

4. CDHP Business Enablers • ‘Ready to Lease’ Components of Health Insurance: • Electronic claims processing • National panel of physicians • National pharmaceutical benefits management firms • Consumer-friendly health data web portals • Disease management vendors • Internet • Transaction medium for claims processing • 2-way communication with members • ERISA-exemption • Lack of state oversight • Half the US commercial health insurance market is self-insured.

5. Early CDHPs in Operation • Definity • Concept developed in 1998, Funded in April, 2000 • Minnesota based • Clear first mover & dot-bomb survivor • Lumenos • Started in 2000 • Based in Virgina • Havard B-School inspired (Regina Herzlinger) • Destinty • Operating as Medical Savings Account model • In operation for 10 years in South Africa

6. Health Toolsand Resources Health Coverage $$ Annual Deductible Definity HealthCareAdvantage Web- and Phone-Based Tools Preventive Care 100% Annual Deductible Definity Health Component Details • Personal Care Account (PCA) • Employer allocates PCA1 • Member directs PCA • Section 213(d) “scope” • Roll over at year-end • Apply toward deductible2 • Health Coverage • Preventive care covered 100% • Annual deductible • Expenses beyond the PCA • Nationwide provider access • No referrals required PCA • Health Tools and Resources • Care management program • Extensive easy-to-use information and services 1 Employer selects which expense apply toward the Health Coverage annual deductible. 2 Paid out of employer’s general assets.

8. New RWJ-Funded ResearchKey Research Questions 1. Is there an ‘adverse selection’ problem? Traditionally, adverse selection is defined as the situation when healthy individuals choose Definity leaving the sick in a traditional plan that will soon implode its premiums because of disproportionate share of sick individuals in the insurance pool. 2. What is the impact on cost and utilization? Definity has been chosen as a response to rising premium prices in an attempt to make the consumer ‘drive the market’ be examining price variations and constraining their personal consumption, if possible.

9. Research Design • 2 Year study (11/1/2002 - 10/31/2004) • Six employers examined: • University of Minnesota, MN • Medtronic, National • Ridgeview Medical Center, MN • Hannaford Bros, New England • Welch-Allyn, Upstate NY (tentative) • Raytheon (New England or South Atlantic firm) • Data collected • Claims data of all utilization for all health plan choices, pre (2001) and post (2002-2003) Definity. • Employer info on flexible spending accounts and employee income • Survey information on Definity choices in 2002 & 2003 from U of M.

10. Early Results #1:Employee Choice of a Consumer Driven Health Plan in a Multi-Plan, Multi-Product Setting

11. Conceptual Model to Address Selection Question We use a choice model based on utility maximization, where utility is considered to be a function of personal attributes such as health status, health plan attributes such as price, and the interaction of price and health status, formally stated as: Uij = f(Zj,Yi,Xij), where, • i is the decision-making employee choosing among, • j health plan alternative choices, • Yi = employee personal attributes, • Zj = health plan alternative attributes and • Xij = interactions between alternative-specific and personal attributes, Xij. Follows methods used by Harris, Schultz and Feldman (2002).

12. Multivariate Analysis of Plan Choice • Focus on the University of Minnesota 2002 survey • Combine survey data with HR information including: • After tax income • Contract type • Age and Gender • Location • Medical premium choice set • Run Conditional Logistic Regression Model to predict the effects of premium price, employee characteristics and health plan feature preferences for early adopters of Definity compared to other health plans.

13. Health Plan Choices • Health Partners: Staff model HMO with direct capitation contracting at a limited number of group practices. • Patient Choice: A ‘Tiered-direct contracting’ descendent of Minnesota’s Buyers Health Care Action Group health benefit design experiment. • Definity Health: Consumer-driven Health Plan • Preferred One: Preferred Provider Organization

14. UPlan Options/Enrollment

15. Early UM Definity ExperienceYear 2002

16. Definity Age/Gender Distribution2002 University of Minnesota

17. All RespondentsSatisfaction with Plan

18. Health Plan Features Most Preferred

19. Econometric Specification • Use condition logit techniques to estimate utility: • Method is motivated by a random utility function assuming: • errors in maximization due to imperfect perception and optimization, • errors due to unobserved relevant variables. • Specified as: Phj = exp(aj + Zj + gjYh + Xhj) / exp(ak + Zk + gkYh +Xhk), where Uhj = aj + Zj + gjYh + Xhj + ehj for the k = 1,…J alternatives in the choice set, aj is an alternative-specific constant with aJ = 0, j is a vector of alternative-specific coefficients with gJ = 0, and b and q are vectors of coefficients that are invariant across alternatives.

20. Results: Premium Sensitivity • Employees are sensitive to out-of-pocket premiums, and surprisingly, employees with chronic conditions are more premium-sensitive • If Definity raised its premium by 1% it would lose 4.6 % of healthy single enrollees and 5.4% of healthy families • 1% premium boost would cause 6.9% of singles and 10.7% of families with chronic condition to leave Definity • The results depend on 100% of the premium hike being passed along to the employee (i.e, defined contribution), as is the case for the UM

21. Results: Health Status and Other Employee Characteristics • Employees and families with chronic conditions prefer the PPO, but otherwise, there is no evidence of adverse selection • Having a chronic condition is associated with a 3.2% increase in the probability of choosing PreferredOne vs. HealthPartners • Note that PreferredOne had the highest premiums ($189.51 for single coverage and $448.40 for family coverage per pay period), suggesting that the plan is experiencing adverse selection • Higher income employees chose Definity or Choice Plus, suggesting these plans may evolve as favorites of the ‘well-to-do’ • Older employees chose PreferredOne or Choice Plus

22. Early Results #2:Consumer-Driven Health Plans:Early Evidence about Utilization, Spending and Cost

23. Study Setting • Health plan choices by employees: • HMO, 2000-2002 • PPO, 2000-2002 • CDHP, 2001-2002 • Variation in cost sharing by contract • Take-up of CDHP approximately 15%. • General caveat: Each of the six employers’ experience can be quite different due to: • Alternatives offered • Plan design • Communications with employees • Sponsor’s objectives for the plan

24. Presentation of Results • Results are limited to two groups of employees who worked for their firm continuously for three years (2000-2002) where: • Employee chose the CDHP in 2001 and 2002. • Employee chose another health plan in 2001 and 2002. • This limitation removed 40% to 50% of all employees from the analysis. • Why make this limitation? We want to see both adoption and maturing impact of CDHP while controlling for prior spending. • 2000: Pre-CDHP experience controls for prior spending • 2001: CDHP adoption year • 2002: CDHP ‘maturation’ year

25. Econometric Specification • Used difference-in-difference approach • Generate unadjusted and regression-adjusted comparisons. • Regression adjustment based on two-part model • Regressors included: age, gender, illness burden, number of dependents, FSA election and income. • Subsequent tests for regression to the mean found the problem to be present, but not to a degree that would influence our results.

26. What was the gross impact on provider and patient payment? NOTE: These are results from a restricted continuously enrolled sample of 50% to 60% of the total employee population and are not a reflection of the plans’ full PMPM expenditures. Also note: 1) Patient expenditures from the Personal Care Account (PCA) are included in the employer payment category. 2) Consumer payment reflects deductibles, copayments, and coinsurance expenses.

27. CDHP, HMO versus PPO PMPM Differences for Continuously enrolled sample

28. What was the ADJUSTED impact on provider and patient payment? NOTE: These are results from a restricted continuously enrolled sample of 50% to 60% of the total employee population and are not a reflection of the plans’ full PMPM expenditures. Also note: 1) Patient expenditures from the Personal Care Account (PCA) are included in the employer payment category. 2) Consumer payment reflects deductibles, copayments, and coinsurance expenses.

29. What was the ADJUSTED impact on provider & patient payment by different services? NOTE: These are results from a restricted continuously enrolled sample of 50% to 60% of the total employee population and are not a reflection of the plans’ full PMPM expenditures.

30. Was ADJUSTED service use different for CDHPs? NOTE: These are results from a restricted continuously enrolled sample of 50% to 60% of the total employee population and are not a reflection of the plans’ full admissions and prescription drug experience.

31. Distribution of CDHP Population by PCA Usage Levels Continuously enrolled population

32. Conclusions • The most important factor affecting choice is income. • The consumer drive health plan was not disproportionately chosen by the young and the healthy (for this population). • In unadjusted dollars, CDHP cost is lower relative to a PPO, but maybe not a HMO in the long term. • In adjusted dollars, CDHP cost is the lowest of all, but only after favorable expenditure selection. • Year 3 of CDHP experience will reveal if they can stem high cost growth trajectory from years 1 & 2.

33. Policy Conundrums • How does a employer-based personal care account move with an employee? • How should CDHPs be treated in the non-ERISA marketplace? • What if CDHPs accelerate the consumer’s burden of health care spending ‘too’ quickly?

34. Policy Opportunities • Innovative means to bring consumer choice into the medical marketplace as well as consumer awareness of the trade-offs of liberal medical insurance coverage policies. • Creates foundations for infrastructure for personal, portable health care coverage. • Hybrid variants could be crafted to serve low income and part time workers.

36. Econometric Issues • How to group health plan choices? • Ideally, estimate separate choice models for: • Single employees with no dependents • Families who have no other source of health insurance • Families who have multiple choices of health insurance • Practically, we can’t identify (2) and (3), so we combine single and family contracts into one choice model through the use of plan-interacted dummy variables (Feldman & Schultz, 2001). • Considered a nested logit, but the Definity next, if weighted, was not large enough. • Correction for oversampling Definity and undersampling the other plans. Lerman-Manski correction was used obtain appropriate standard errors.

37. Impact of price, employee characteristics and health plan feature preferences on health plan choice

38. Continued: Impact of employee characteristics and health plan feature preferences on health plan choice