Employee Choice of a Consumer Driven Health Plan in a Multi-Plan, Multi-Product Setting Stephen T. Parente, Roger Feldman, Jon B. Christianson University of Minnesota Presented at the National Bureau of Economic Research August 1, 2003 Funded by the Robert Wood Johnson Foundation Health Care Organization and Financing Initiative For more information:

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 plan choice descriptive and multivariate results. List the policy opportunities and conundrums of CDHPs. Outline the next steps in our analysis.

Issues Driving CDHP Creation  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

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.

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

Definity Health Component Details Definity Health Care Advantage Web- and Phone- Based Tools Health Tools and Resources Care management program Extensive easy-to-use information and services Health Coverage Preventive care covered 100% Annual deductible Expenses beyond the PCA Nationwide provider access No referrals required Personal Care Account (PCA) Employer allocates PCA 1 Member directs PCA Section 213(d) “scope” 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 $$

Annual Deductible Health Coverage Annual Deductible Member Responsibility How Definity Health Works Members use the PCA—provided by their employer—to pay for healthcare expenses throughout the year Covers traditional services May cover non-traditional services Unused balance rolls over at year-end—motivates saving Member Responsibility—creates true “consumer thinking” Healthcare expenses that exceed the PCA are covered under Health Coverage—offers security to members Definity Health Care Advantage Web- and Phone- Based Tools Health Tools and Resources Preventive Care 100% PCA $$ Preventive Care expenses are covered 100%—encourages healthy lifestyles

Definity Market Penetration 2001 Aon (pilot group) Medtronic (pilot group) Ridgeview Medical Center 2002 Aon (rollout) Dade Behring Inc. Hannaford Brothers Co. Medtronic (rollout) Raytheon Textron University of Minnesota Wise Business Solutions, Inc. Broadband/Video Service Co. ECS Designer/Manufacturer Charter Communications Budget Inc. Medical Products Co.

2003 Definity Experience

New RWJ-Funded Research Key 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.

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

For this Paper: Focus on University of Minnesota Preliminary Results from the Survey Survey goals: Record taste for health plan features and general experience data. Obtain Definity-specific feature experience data. Survey administered in April to June 2003, to report on 2002 health plan experience. 503 Non-Definity Health Plan respondents (73.3% response rate) 433 Definity Health Plan respondents (62.6% response rate) Interviewers were University human resource staff trained specifically for this research project.

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).

New Results from a 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.

Health Plan Choices 1.Health Partners: Staff model HMO with direct capitation contracting at a limited number of group practices. 2.Patient Choice: A ‘Tiered-direct contracting’ descendent of Minnesota’s Buyers Health Care Action Group health benefit design experiment. 3.Definity Health: Consumer-driven Health Plan 4.Preferred One: Preferred Provider Organization

UPlan Options/Enrollment

Early UM Definity Experience Year 2002

Definity Age/Gender Distribution 2002 University of Minnesota

All Respondents Satisfaction with Plan

Definity Respondents Use of Internet Tools

Health Plan Features Most Preferred Definity Health Plan Members Only

Health Plan Features Most Preferred

Usual Source of Care and Chronic Illness

Health Plan Benefit Knowledge

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: P hj = exp(  j +  Z j +  j Y h +  X hj ) / exp(  k +  Z k +  k Y h +  X hk ), where U hj =  j +  Z j +  j Y h +  X hj + e hj for the k = 1,…J alternatives in the choice set,  j is an alternative-specific constant with  J = 0,  j is a vector of alternative-specific coefficients with  J = 0, and b and  are vectors of coefficients that are invariant across alternatives.

Econometric Issues How to group health plan choices? Ideally, estimate separate choice models for: 1.Single employees with no dependents 2.Families who have no other source of health insurance 3.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.

Table 2: Variables Used in the Analysis (n=915)

Table 4: Impact of price, employee characteristics and health plan feature preferences on health plan choice

More Table 4: Impact of employee characteristics and health plan feature preferences on health plan choice

Table 5: Premium Elasticity Estimates for Definity and Health Partners

Conclusions The consumer drive health plan was not disproportionately chosen by the young and the healthy (for this population). Income is positively associated with CDP choice suggesting the plan may evolve as a favorite of the ‘well-to-do’. Health plan features of CDP-choosers most preferred are: national provider panel, access to my doctor, and no prior authorizations. Greater premium price elasticity is observed for those with chronic illness or family contracts.

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. Provides consumers and providers with an alternative to more restrictive managed care.

Policy Conundrums How does a employer-based personal care account move with an employee? What if ERISA is modified to doom the current CDHP practice? How should CDHPs be treated in the non- ERISA marketplace? What if CDHPs accelerate the consumer’s burden of health care spending ‘too’ quickly?

Next Steps Collect and analyze claims data –Examine effect on cost and utilization Employer, health plan and human resource consultant interviews Second year of survey for 2003 experience and/or 2004 health plan choices. New result venues: –Robert Wood Johnson Foundation meeting on CDHPs in DC, 9/15/2003 –AEA meeting in January, 2004