Can Markets for Health Insurance Work?

1. Can Markets for Health Insurance Work? Jonathan Levin Gaston Eyskens Lectures November 2013

2. Roadmap Lectures • Technology and Asymmetric Information • High Risk Consumer Credit Markets • Measuring Inefficiencies from Adverse Selection • Can Markets for Health Insurance Work?

3. Introduction • Arrow (1960): healthcare as an industry where traditional notions of competition and efficiency are problematic. • Why? Uncertainty and asymmetric information. • Needs are concentrated => must have insurance • Potential for adverse selection in insurance • Moral hazard for insured individuals • Physicians asymmetrically informed about care • How well can markets for health insurance work? Should there be a major role for private market competition in a national healthcare system?

4. Private Market Solutions • Of developed countries, US has perhaps the most “privatized” healthcare / health insurance system. Source: OECD • It also has the most expensive system.

5. What Role for Markets? • Major debate in the United States, where healthcare is 18 percent of GDP, and 21 percent of federal budget. • Medicare (over 65) • Private market insurance now offered as a substitute for government insurance. Republicans propose to shift entirely to “premium support”. • Obama Health Insurance Reform (under 65) • Attempts to provide universal coverage by mandating the purchase of (subsidized) insurance, and establishing state insurance exchanges. • Some parallel debates in European countries.

6. Outline of Lecture • Describe research with Jay Bhattacharya, Vilsa Curto, LiranEinavon Medicare’s experiment with managed competition. • Motivation: current structure of US Medicare program is opportunity to compare two public / private systems operating head-to-head, fixing the population and set of healthcare providers. • Outline of lecture • Medicare and managed competition • Risk selection • Imperfect competition • Market design • Caveat: work in progress….

7. Background on US Medicare Program • Medicare program is government provided health insurance for all those over 65, plus disabled, ESRD, etc. • Individuals pay modest (≈$100) monthly premium. • Insurance covers hospital and outpatient services. • Privatized drug coverage introduced in 2006. • Traditional “fee for service” insurance (FFS) • Beneficiaries can use any doctor or hospital that accepts Medicare. Most do. Medicare reimburses for services. • Price for each service is set administratively, plus there are a complex set of hospital / facility subsidies.

8. Medicare is Expensive

9. Concerns about Medicare • Widely viewed as very inefficient • Why? Low copayments + physician incentives to “do more” => overuse of services. No constraints on spending / utilization. • Many documented distortions due to administrative pricing, e.g. bias towards procedures, specialists. • Striking geographic variation in costs • Medicare spends $13,824 to provide healthcare to someone in McAllen, TX, versus $7,766 in Rochester. • Common interpretation: indicates wide scope to provide different services, and lack of cost-efficient “standards” of care.

10. Medicare Advantage Program • US introduced private plans in 1985: beneficiaries could opt out of traditional insurance, and enroll in a private insurance plan. • Approved plans receive annual payment for each enrollee, initially 95% of local FFS costs, and updated periodically. • Hope was that private plans would allow consumer flexibility, save taxpayer dollars, and preserve quality. • But there were problems … • Low take-up – less than 15% of beneficiaries as of 2003 • Evidence of significant risk selection (cream-skimming) • Projected cost savings were not realized

11. Managed Competition • In 2003, new legislation introduced competitive bidding. • Attempt to avoid setting administrative capitation rates. • Risk adjustment added to address selection. • Based on proposals that date back to the 1970s. Some similarities to proposed state exchanges. • Risk adjustment developed between 2003-2006. • Every Medicare beneficiary scored based on disease history. • Regression model used to map diseases into predicted cost.

12. Expansion of Private Medicare

13. Questions • Selection • Do private plans manage to select relatively healthy enrollees? Is risk-adjustment successful in addressing this? • Competition • Is bidding competitive? Do bids reflect underlying costs, or does the program create substantial insurer rents? • Further questions about quality, innovation, cost growth, efficacy of consumer choices, etc..

14. Selection: enrollment by risk score High risk beneficiaries are less likely to enroll in private plans.

15. Selection: conditional on risk score Mortality notably lower among new MA enrollees.

16. Disease Classification Incentives Private plans are more aggressive in coding diseases.

17. Adjusting for Selection & Up-coding • For each private plan enrollee, we observe plan’s bid and payment, and can impute an FFS cost based on county and risk score. • Up-coding and selection adjustments (still somewhat ad hoc): • Disease classification: MA risk scores higher by 2-5% (?) • Selection: based on mortality + lagged MA costs => 1-4% (?)

18. Competition and Market Concentration • Medicare Advantage market is highly concentrated • We need to take imperfect competition seriously.

19. Medicare Advantage Rules • Country divided into local markets (3,034 counties). • Medicare sets benchmark rateB for each county. • Plans bid to provide “standard” insurance for a “standard” individual. • Individuals choose a plan in their market, or standard Medicare. Benchmark Plan Cost $ b c B b CMS pays plan b Enrollee pays 0 CMS pays plan B Enrollee pays b-B And CMS pays plan a “rebate” ¾*(B-b) that it passes to consumer in as higher benefits. • Consumer “price”:

20. Benchmarks and Bidding Incentives • Plan demand depends on . • Plan profits • Benchmark plays the role of a subsidy. • Under “perfect” competition with , .

21. Cross-Market Bid/Benchmark Relationship

22. Empirical Model of Plan Bids • Empirical model of plan j bid in year t. • A single plan bid may apply to several counties=>define • Plan benchmark = average of county benchmarks in a plan’s service area (using plan enrollment to weight). • Plan costs = average FFS costs for an r=1 individual in plan’s service area (again, plan enrollment to weight).

23. Plan Bid Estimates

24. Implications of Bid Estimates • Bids are highly responsive to benchmarks, but not closely related to FFS costs (conditional on B). • Suggestive of market power… • Ideally, would like to estimate private plan margins . • Local TM costs don’t appear be a good proxy for . • Directly measure utilization? Might be possible … not today. • Estimate demand and infer from profit-maximization.

25. Estimating Plan Demand • Assume i’s utility for plan j in county-year (market) m is • Imposing a logit error gives us the demand model • where Xs are plan and market characteristicsand we use in place of premium, with effect varying on

26. Demand Elasticity Estimates Includes characteristics: plan star rating, indicators for part D & supplementary benefits.

27. Plan Demand and Margins

28. Inferring Margins • Profit-maximization • Average bid is , so margins are • Cutting margins in half would save $10 bn a year. • Could these savings be realized? How? • Better rebate design (current DWL) • Lower benchmarks (competition with TM) • Better choice guidance for consumer (star ratings!) • Entry and greater competition

29. Market Design: Rebates • Insurer that bids receives rebate of . • Typically used to provide more generous insurance. • Why not pass the rebate directly to enrollees in cash? • Logistically challenging under current rules. • Estimates say elasticity increases => margins of $71, not $125. • What about increasing/decreasing the rebate? • If rebate then margins = $62, but taxpayers always pay … this is the premium support model Republicans want. • By lowering rebate, e.g. to 50%, reduces taxpayer cost with fixed bids, but reduces incentives for insurers to lower their bids.

30. Market Design: Benchmarks • County benchmarks are main design parameter • If bids track benchmark, then lower B means lower margins. • However, entry is also responsive to market benchmarks. • Back of envelope calculation. A $100 decrease in benchmark: • directly decreases bids by $50 • but maybe plans would exit?

31. Benchmarks and Plan Entry

32. Plan Entry and Bids

33. Choosing Benchmarks • County benchmarks are main design parameter • If bids track benchmark, then lower B means lower margins. • However, entry is also responsive to market benchmarks. • Back of envelope calculation. A $100 decrease in benchmark: • directly decreases bids by $50 • induces exit of 3.5 plans, which increases bids, but by < $5 • Based on our estimates (including margins of > $100 per month per enrollee) desirable to reduce benchmarks. • We are about to try this under Obamacare.

34. Prospects for Competition • Are private plans competing with each other, or the government? • MA/TM enrollment transitions, 2006-2010 • In markets with low private plan penetration, traditional government insurance is the primary competition. • (Note: choices also are pretty persistent … switching costs?)

35. Public “Option” as Constraint • Option to use TM appears to be an important constraint on plan bids, especially in areas with low penetration / few plans. • Interestingly, the Obamacare reform does not include a public option for insurance, although some lobbied for it. • One hypothesis is that private plan competition may not work all that well in low entry (likely rural) markets.

36. Conclusions • US is engaging in a huge national experiment with managed competition provision of health insurance. • Ongoing Medicare private plan program has grown rapidly, but at what appears to be fairly significant cost to taxpayers. • There do appear to be potential cost savings; the question is whether it is possible to realize them. • We have started to look a few possible mechanisms, but project is still at a fairly early stage…

37. Thank You!