The Reinsurance Institute: Modeling, Outputs, & Implementation

1. The Reinsurance Institute:Modeling, Outputs, & Implementation Randall R. Bovbjerg, JD Principal Research Assoc. A. Bowen Garrett, PhD Senior Research Assoc. Lisa Clemans-Cope, PhD Research Associate Health Policy Center, The Urban Institute† Presentation to State Coverage Initiatives Workshop for State Officials, Denver, CO; August 3, 2007 The Reinsurance Institute is funded through the State Coverage Initiatives (SCI) program, which is a national program of the Robert Wood Johnson Foundation, administered by AcademyHealth, Washington, DC †standard disclaimer applies

2. What is the SCI Reinsurance Institute? SCI/AcademyHealth Enrique Martinez-Vidal, Director SCI Donald Cohn, Alice Burton (now working for MD) ... and three participating states (RI, WA, WI) Urban Institute HPC & Team Randall R. Bovbjerg A. Bowen Garrett Lisa Clemans-Cope Linda Blumberg Aaron Lucas Paul Masi Pool Administrators. Inc. Karl Ideman, President Richard Larose, Vice President Actuarial Research Corporation Gordon R. Trapnell, President Jim Mays, Vice President Consultants Katherine Swartz, Hvd. Sch. Pub. Hlth Patrick Collins, American Re.

3. Roadmap I. Introduction to reinsurance as part of reform II. Project roles: modeling and state consultation III. Modeling: data base construction & policy simulation IV. Modeling: state-specific results V. Face validity and other implementation issues VI. Some lessons learned VII. Can it work in my state?

4. $100K+ $25K-100K $0-25,000 Reinsurance = Insurance for InsurersSimplified Sketch: HealthyNY Allowable annual claims/person Shares for primary insurer, reinsurance primary carrier pays 100% ceiling reinsurer pays 90%, primary carrier 10% corridor: threshold primary carrier pays 100% “specific, retrospective, excess of loss”

5. Rationales for Public Reinsurance • Encourage enrollment by subsidizing cost • Targeted subsidy; ex post risk adjustment • Reduce costs of unfavorable selection, cut benefit of cream-skimming • Help new market entry by assuming high, unfamiliar risk N.B.: • Costs vary with size of population targeted, generosity of public subsidy • Impact depends partly on financing: not surcharges on targeted sector, but broad financing base

6. Simulations that Can Aid Policy • Reinsurance approach to be modeled: • HealthyNY-style end-of-year reinsurance of high claims, not individuals “ceded” at start • But, participating states target already insured, not just uninsured • Want to know costs & effects by design of policy option(s) • Why is this hard to do? Need good population data • costs, coverage, demographics, employer characteristics • health expenses in the upper tail of risk  sample size concerns • Problem: No such state datasets exit • Solution: Build a new dataset!

7. Simulation Model has Two Main Parts

8. Baseline Overview: From National to State-specific Microdata Start national, population-based data from household survey • Key: “MEPS-HC” has medical expenses, other key data • Make consistent with National Health Accounts and high-cost claims data • Re-weight to match each state's pop’n characteristics • Assign workers to "synthetic" employers, matching to state's known firm size/industry mix • Build up premiums from covered medical expenses • Benchmark to state data End  state database ready for simulating reinsurance options

9. Reweighted Distribution of Family IncomeClosely Matches CPS data (Rhode Island)

10. Total annual private health expenditures and % of population by expenditure group Total private health expenditures (in mill$) Percent of population $30k-$50k $10k-$15k $15k-$30k Up to $2.5k $5k-$10k $2.5k-$5k $50k and up Expenditure groups Source: Reweighted MEPS-HC merged data 2001-2003. Reweighted Health Expenditures for Wisconsin(shows familiar pattern)

11. Application of Reinsurance RulesPolicy Parameters Subject to Modeling • Definition of reinsured expenditures • Lower reinsurance threshold (i.e., attachment point) • Upper limit • Coinsurance retained by original insurer • Targeted eligibiles • Group market, nongroup market, or both • Firm size criteria (under 10, 10 to 24, 25-49, 50-99, 100+) • Income or wage brackets • Premium rating rules • Nongroup pooling follows state regulations • Can vary by age, health status, gender, single/family, family composition of age/gender/health status

12. Premiums, before and after Reinsurance Construction of initial premiums • Employer Sponsored Insurance (ESI) premiums: • expected expenses = blend of own experience, that of risk group • add administrative “loading’ factors by firm size • Nongroup premiums • blend own covered expenses and predicted covered expenses within appropriate rating cell, add nongroup loading factor Estimating response to reinsurance • Use “elasticities” (responsiveness of offering firms and individuals to drop in price from reinsurance subsidy) • Compute resulting costs, coverage shifts, etc. • Iterate in cycle (pictured, next)

13. Baseline data including initial premiums 1. Specify reinsurance policy parameters 5. Compute ESI/NG premiums for new risk pool 2. Recompute ESI/NG premiums 3. Compute ESI offer changes 4.Compute changes in “take-up” of ESI/NG Dynamics of ReinsuranceIterative Flow of Simulation Model

14. Effectiveness of Modeling • Model has some key limitations: • precise magnitude of behavioral effects somewhat uncertain • model does not capture admin. costs, benefit design, insurer response like exit/entry, underwriting behavior... • so, significant role remains for qualitative analysis • Model does well in addressing: • big-picture--the effects on premiums, coverages, costs • who goes where (insurance status by characteristics) • where premium savings are concentrated • how risk pools change • how composition of uninsured changes

15. Emerging State Results – Washington State Example Design • Target all small groups (<50) and nongroup markets • Corridor: $10,000 - $90,000; coinsurance: 10% Overall Effects • Small group premiums drop about 31% • Nongroup premiums declines 38% • Offer rate of small firm workers rises from 71% to 81% • Number of uninsured falls from 624K to 563K (-61K)

16. Emerging State Results – Washington State Example, State Program Costs • Small group costs: $376 Million • Nongroup costs: $224 Million Total state cost: $600 Million • Cost per newly insured: $9,800 • Reduced premiums for existing insured • Small group single policy: -$1,115 • Nongroup single policy: -$1,461 (estimates are preliminary)

17. Rating group Before After Change Pct. change Age under 25, healthy $1,859 $1,215 -$643 -35% Age 25-45, healthy $2,597 $1,691 -$906 -35% Age 45-65, healthy $5,215 $3,418 -$1,797 -35% Age 45-65, fair or poor health $14,764 $7,870 -$6,894 -47% Emerging State Results – Wash. St. Example, Changes in Nongroup Single Premiums

18. Policy (LL-UL / Coins) Premium change (single/family) Change in uninsured Program cost $35K-$75K / 10% -28% / -40% -26,400 $106 Million $15K-$75K / 20% -33% / -42% -27,600 $116 Million $20K-$75K / 20% -26% / -35% -25,500 $93 Million Emerging State Results – Wisconsin Example • Want to target smallest employer groups (1-9 employees) with subsidy of roughly $100 million (estimates are preliminary)

19. State Costs beyond Claims Administrative Costs, Start-Up • Can be high, although experience varies • Many set-up activities, from governance structure & mechanisms (e.g., board) to negotiated line of credit Administrative Costs, Ongoing • Biggest is general administration, also outside fees • Substantial fixed costs create economies of scale • Other influences include complexity of activities, number of insurers, administrative procedure rules Estimating the Total • Experience shows range of costs from 0.6% to about 3% of reinsured claims expense

20. Impacts beyond Subsidy Potential benefits reduced year-to-year claims volatility, risk premium reduced need for capital under risk-based rules reduced year-to-year turnover across plans, transaction costs lower need for/costs of private reinsurance less underwriting, lower costs Potential costs New transaction costs Moral hazard for primary insurers

21. Implementation Three Phases from Policy Idea to Program Execution • Develop general reinsurance concepts of interest • Operationalize selected concept(s) with specific program provisions, legislation • Roll out program administratively, monitor, correct

22. A. Develop General Concepts • Start with goals of reinsurance • intended beneficiaries, specific problem, logic of how interventions help, role within overall vision • Understand context • existing market, regulation, insurer behavior • accompanying interventions, e.g., “Connector” • Model expected impacts vs. intended • formally, as here, or other approach • compare with other alternatives • “Sell” concept/vision to constituencies • build shared understanding, even if not political consensus

23. B. Operationalize Concept(s) • Tailor intervention to intended beneficaries • Tailor to perceived problem(s) • high-end reinsurance plausibly helps new, small insurers, very small groups (e.g., $30-100K) • lower-corridor reinsur. helps more insurers, does more to reduce risk selection (e.g., $5-75K) • Worry about key issues • make subsidy credible, durable • track/regulate premium savings & their distribution • address moral hazard & transaction costs • HIPAA, other legal compliance issues • Write enabling legislation

24. C. Administrative Roll-Out • Budget realistically for start-up costs • Expect slow ramp-up of claims experience • Phase in functional capabilities • many nuts and bolts to assemble • plan, do roll-out, monitor, make mid-course corrections • give administrators tools & flexibility to cope with unintended consequences • Allow sufficient time to complete tasks

25. Some Lessons Learned • Starting with clarification of goals helps clarify other options as well reinsurance ones • Data bases, programming, & iterations take time • State stakeholders think existing programs & products, whereas model uses demographic, other characteristics • Achieving consistency with state data helps buy-in • Large changes require large per-uninsured subsidy • Must trade off helping uninsured and helping market • Implementation needs good information & active management

26. Can It Work in My State? • Rhode Island, Washington, and Wisconsin are all considering resinsurance, despite their different current circumstances and divergent goals • Do need to be able to make assumed effects real: • subsidy made credible, durable • premiums respond as expected • able to monitor evolving effects, make mid-course corrections • Also need to achieve buy-in, manage expectations • Data monitoring and administrative capabilities are important

27. End Time for Questions