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Consumer Response to a National Marketplace for Individual Insurance

Consumer Response to a National Marketplace for Individual Insurance. Stephen T Parente University of Minnesota October 2, 2009, University of Pennsylvania

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Consumer Response to a National Marketplace for Individual Insurance

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  1. Consumer Response to a National Marketplace for Individual Insurance Stephen T Parente University of Minnesota October 2, 2009, University of Pennsylvania Contributions by co-authors Roger Feldman, Jean Abraham and Yi (Wendy) Xu as well as coordinator Ruth Taylor and Lisa Tomai of T3 Health LLC were invaluable. Critical data, software and methods were supported by the Robert Wood Johnson Foundation, AHRQ, DHHS/ASPE and HSI Network LLC

  2. Overview • Policy Proposal • ARCOLA Simulation Model • National Simulation Steps • Results • Implications

  3. Rational for Analysis • Since 1945, McCarran Ferguson act prohibits the sale of any insurance across state lines. • Since 1978, ERISA has enabled an opt-out for employers to self insure across state lines. • Currently 55%+ of non-Medicaid and non-Medicare insured receive insurance enabled by ERISA. • For the ‘median voter’ with non-public insurance, McCarran Ferguson applies no more.

  4. Policy ProposalSince 2005, members of Congress (e.g., John Shadegg [R-AZ]) has proposed that individual health insurance be offered nationally instead of in state-specific markets. The University of Minnesota was awarded a contract to study the likely effect of a national market on take-up of individual health insurance coverage. The research objective is to simulate the impact of having a national market for individual (non-group) coverage and provide advice to policymakers regarding the strengths and weaknesses ofsuch a proposal.

  5. ‘ARCOLA’ Simulation Model • ARCOLA simulates national health plan take-up from policy proposals in the individual and group markets • Unique combination of attributes: • Based on conditional logit model of health plan choice with data from 4 large employers • Includes HRA and HSA plans • Choice model includes measures of chronic illness burden at contract level • Can simulate effects of policy changes: • Premium modifications by tax deduction or credit • Full or select individual mandates • State and national market differences

  6. National Market Simulation • Background: Our model predicted take-up of HSA plans in the individual market quite accurately (Health Affairs: Feldman, Parente et al., 2005) • Population: adults in the MEPS who are aged 19-64 and are not students, not covered by public insurance, and not eligible for coverage under someone else’s ESI policy • Baseline sample uninsured & turned down: 32.3 million people nationally

  7. National Market Simulation Steps • Create a synthetic version of the MEPS that assigns people to states based on demographics • Identify minimum, moderate and maximum marginal impact of state regulations on individual-market premiums • Community rating • Guaranteed issue • Any willing provider • Mandated insurance benefits • Develop initial set of scenarios for policy • Scenario 1: Competition among 5 largest states • Scenario 2: Competition among all 50 states • Scenario 3: Competition within regions

  8. Health Insurance Regulations • Mandates require insurers to cover particular services or providers • Guaranteed issue laws require insurers to sell insurance to all potential customers • Community rating requires insurers to limit premium differences across individuals • Any willing provider (AWP) laws restrict insurers’ ability to exclude providers from their networks

  9. Literature Review • We reviewed studies of the individual insurance market • We could not find any studies that used ideal ‘dif-in-dif’ research design • Other papers looked at the effects of regulations on premiums only for people who held insurance – we ruled these out • Only 4 studies met our criteria: 3 working papers and one peer-reviewed study by Hadley and Reschovsky (Inquiry, 2003)

  10. Effects of Regulations

  11. Simulation Step #4 Select ‘target state’ in which person can buy insurance Remove the effect of regulations in home state from premiums and add the effect of regulations in target state In general, target state will have fewer regulations and lower premium Exceptions: (1) target and home state are the same; (2) high-cost person with community rating in home state may lose advantage of community rating in target state Simulate the net effect of removing regulations on health insurance take-up

  12. Details & Assumptions • Premium data: • HSA from ehealthinsurance.com for HSAs • HRA from composite of 3 of our empl0yers • Kaiser/Commonwealth for all other plan designs • State-specific premium inflators/deflators derived from Musco et al. AHIP report on individual health insurance • Individual market premiums were experience rated for age and gender (except community rated states) • Small group market (<250 employees) premiums were adjusted by state-specific regulatory effects • Employee premiums in large firms were tax-adjusted • HSA premiums include a $1K/$2K investment in accounts

  13. Scenario 1: Competition among 5 largest States 4,688,254

  14. Scenario 2: Competition among States 8,490,592

  15. Scenario 3: Competition among States in 4 Regions 7,772,544

  16. Implications • Largest insurance take-up is competition among all 50 states with one winner • Most pragmatic scenario, with good impact, is one winner in each regional market • No way to assess impact of such a migration on provider access or quality of care • Significant opportunity to reduce the number of uninsured in each scenario

  17. Ground Effects % Change in Insured (National Sim/National Sim & SOTU 2008) • New Jersey [G/C/30] +49% +79% • Pennsylvania [G/25] +7% +15% • Ohio [G/25] +10% +24% • Florida [G/38] +16% +32% • Michigan [G/19] +8% +19% • California [40] +4% +20% • Minnesota [34] +2% +16% • Washington [G/C/29] +18% +29% [Guaranteed issue/Community Rating/Mandates]

  18. Responses to Arguments Against Change in Status Quo • Insurance is local. Insurers can’t navigate this. • Self-insurance market success proves otherwise. • Physician panels and credentialing are local. • Self-insurance and FEHBP prove otherwise. • Claims information systems are incompatible. • Medicare & 1990s vintage IS for pharmaceutical benefit management firms prove otherwise. • States’ reflect local cultural/ethical standards. • Human anatomy, medical science and risk do not.

  19. Thank You! For more information, go to www.ehealthplan.org

  20. Epilogue

  21. Estimating the Impact Policies to Expand Private Coverage for New York’s Non-Poor Uninsured Sponsored by the New York State Health Foundation Albany, New York September 22, 2009

  22. Scenarios Modeled • Removing restrictions on underwriting • community rating • guaranteed issue • Allowing Health Savings Accounts into the market • Currently, these high-deductible savings plans may not be sold in the New York State individual market. • Allowing the purchase of policies issued by insurers based in and regulated by neighboring states. • Allow the sale of “mandate lite” plans

  23. ARCOLA’s strengths & weaknesses for task Strengths Weaknesses Needs survey data from a state to make estimates – Zogby provided data for this analysis Has not been bench-tested with Urban or Columbia University models with state data Works only through price effects, but that is the dominant factor affecting insurance choice • Peer-reviewed in Health Affairs • Can be used for federal & state estimates • Is based on a microeconomic model of health insurance demand published in three journals • Is supported by consumer driven health plan choice, cost & use

  24. Plan Choices in the Simulation • Direct Pay Low PPO • restrictive network • high co-pay • 15 percent coinsurance • Direct Pay Medium PPO • Lower co-pay and coinsurance than the Low PPO • Direct Pay High PPO • lowest co-pay • no coinsurance • HSA • High deductible , low account contribution

  25. What is the Impact of Eliminating Community Rating (CR) and Guaranteed Issue (GI) and Introducing Health Savings Accounts? The combined effect of No CR & GI is a 37% reduction in the Number of uninsured in NYS.

  26. What is the Impact of Interstate Market Competition? If everyone took advantage of lower premiums, there would be a 26% reduction. A 17% reduction if ¼ buy CT,PA

  27. What is the Impact of Reducing the Number of Mandates in New York? If 20 mandates were removed, the impact would be a 3% reduction in the uninsured, 9% reduction if 40 mandates removed.

  28. Summary of Simulation Results • Removing Community Rating & Guaranteed Issue has the greatest impact on reducing the number of uninsured. • Introducing HSAs into the market reduces the uninsured, but does not have nearly the impact of removing CR & GI. • Letting New Yorkers purchase insurance across state lines can lead to up a 26% reduction in the uninsured. • Reducing the number of mandates will have an impact, but not as great as interstate competition or the removal of CR & GI.

  29. Thank You! For more information, go to www.ehealthplan.org

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