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CHAPTER

5ADVERSE SELECTION

You know more about your likely use of health services than does your typical insurance company. As a result, you have an incentive to use this information to your best advantage. In particular, if you have some

health problem—say, heart disease—you might try to find an insurance plan that is designed for healthier people. If you were successful, you would pay a premium that was less than your expected claims experience. The insurer, on the other hand, would probably lose money on you. As you might imagine, insurers worry a good deal about this.

Adverse selection in health insurance exists when you know more about your likely use of health services than does the insurer. Insurers deal with the problem by trying to design risk classes that group similar risks together. They then charge premiums that reflect this differential risk. The same information that goes into defining risk classes can be used to identify potential marketing opportunities for insurers. If one insurer can identify an employer group that has lower claims experience, for example, it might be able to quote a premium that will attract the group away from another insurer.

The Affordable Care Act (ACA) seeks to remove adverse selection concerns from the consumer by prohibiting the use of preexisting condi- tions in setting insurance premiums. However, adverse selection does not just go away because of federal law. In this and chapters 6 and 7, we will discuss the classic adverse selection problem, see how insurers have dealt with it, and begin to understand how the ACA addresses the problem behind the scenes.

In this chapter, we explore some of the implications of adverse selec- tion in the context of the reported differences in the utilization experience of people enrolled in managed care plans (e.g., HMOs) and people enrolled in conventional insurance plans (see Adverse Selection in Pension plans). We discuss mechanisms whereby the differences could reflect efforts by the man- aged care plan to reduce utilization and efforts it might make to attract lower utilizers. This discussion leads to an examination of the insurance cost impli- cations for employers who might begin to offer the HMO. We then review the literature on the extent to which adverse selection and changes in use patterns explain actual differences in HMO and conventional utilization. An

C o p y r i g h t 2 0 2 0 . A U P H A / H A P B o o k .

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exploration of adverse selection in employer-sponsored coverage follows and, finally, we discuss some important selection issues that arise with the ACA.

Adverse Selection in Pension Plans

Adverse selection arises in many insurance markets. In the pension world, for example, you can purchase an annuity that pays out monthly until you die, or alternatively, you can buy an annuity that pays out monthly for a fixed number of years, thereby leaving money to your heirs if you die early. In a fascinating study of a large pension plan in the United Kingdom, Finkelstein and Poterba (2002) found that those people who ultimately lived longer disproportionately purchased pension plans that paid out until they died. Those who died early disproportionately purchased fixed-term annuities. The implication is that adverse selection is present in the pension markets, and people appear to know more about their likely remaining length of life than does the annuity seller.

Health Maintenance Organization Effect Versus Favorable Selection

Much of the empirical research on adverse selection in healthcare was done in the 1980s, as employers began to offer HMOs and other managed care plans. The issue arose because of substantial differences in the utilization experience of those enrolled in HMOs and those in conventional insurance plans. Miller and Luft (1994) reviewed much of the literature on the differences in utiliza- tion; see “HMO Performance” for a summary of their findings. Essentially, Miller and Luft found that people enrolled in an HMO use considerably less hospital care. The question is why.

One explanation is that HMOs do something to keep people out of hospitals. This is the so-called HMO effect, which might be the result of a number of strategies. For example, HMOs could substitute ambulatory services for inpatient services at a much more aggressive rate than do con- ventional insurers. HMOs could employ effective utilization management techniques that are designed to limit hospital use to only those most likely to benefit from it. HMOs may only affiliate with physicians who are conserva- tive in their use of hospital services, and/or they may provide financial incen- tives to physicians that lead the physicians to admit fewer patients. HMOs may provide preventive services that identify harmful conditions at an early stage and reduce hospitalizations.

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Chapter 5: Adverse Select ion 83

Health Maintenance Organization Performance

Compared to indemnity insurance, HMOs had the following:

• Admission rates: 26–37 percent lower

• Average length of stays: 1–20 percent lower

• Hospital days: 18–29 percent lower

• Office visits: Higher or equal

• Expensive services: Used less

Source: Data from Miller and Luft (1994).

Alternatively, HMOs may do nothing at all to lower the hospital utilization experience of its members. Instead, they may attract members who are low utilizers to begin with (favorable selection), which also could be accomplished in many ways. HMOs could target their enrollment efforts at younger or healthier groups by, for example, marketing to schoolteachers rather than construction workers on the theory that schoolteachers, on aver- age, are less likely to take risks in their daily lives. HMOs might contract with physician groups and hospitals that are located in suburbs populated by young, upwardly mobile professionals, believing that such proximity will disproportionately attract the residents. HMOs could offer excellent mater- nity and well-baby care in the hopes of attracting otherwise healthy young families into their plans. Similarly, they could offer abundant preventive services, expecting that those who value such services prefer to keep them- selves healthy and out of the hospital. HMOs might offer a tie-in sale—for example, enroll in the HMO and receive a substantial discount at a local gym. Indeed, some HMOs have given health credits to members who undertake healthy activities.

While these efforts could be to keep people out of the hospital, they could also be designed to attract people with healthy lifestyles. Perhaps those who are less prone to exercise will see these offers as wastes and not join the plan. HMOs may choose their panel of providers such that there is an abundance of primary care physicians but few specialists. The theory may be that an individual with chronic health problems probably has an ongoing relationship with a specialist, and if that specialist is not in the HMO’s panel of providers, the consumer is less likely to join. In this con- text, Goodman argues that insurance plans offered under the ACA in Texas exclude MD Anderson Center and those in Minnesota exclude the Mayo

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Clinic as a means of limiting enrollment by people who have expensive health problems (Goodman 2018).

Alternatively, HMOs may do none of these things. It may simply be that the philosophy of health maintenance attracts people who do not like to interact with the healthcare system. If so, even though HMOs may reach out to all members of the community, they may still attract a favorable draw of the population.1

Obviously, HMOs could seek to attract low utilizers and also to limit their use of hospitals once they join the plan. To an employer considering offering an HMO in addition to a conventional plan, however, appreciating which effect dominates is critical. If the difference in utilization is largely attributable to the HMO effect, then the plan can do something that will lower healthcare costs for the employer and employees. Potential savings can be had. On the other hand, if the difference in utilization is largely attribut- able to favorable selection, then no savings occur. The best the employer could hope for is writing two checks, one to the traditional plan and one to the HMO.2 Moreover, the employer may conceivably be even worse off because it has added the HMO.

Consider an employer that has long offered a conventional insurance plan. It now adds an HMO that achieves its lower utilization by means of favorable selection and attracts a disproportionate share of the employer’s healthy workers. As Feldman and Dowd (1982) note, it is not at all obvi- ous that the lower claims experience will be passed on to the employer and employees in the form of lower premiums. The HMO may try to set the premium just a shadow below the competitively priced conventional plan’s premium. If so, the employer and employees will effectively pay a higher pre- mium for the healthy employees than they were when only the conventional plan was offered. To make matters worse, the conventional plan may find that its claims experience now has increased and the plan will have to raise its premiums! Thus, in the face of both favorable selection and shadow pricing, the employer finds that its efforts to reduce insurance costs resulted in higher costs. A solution to the shadow-pricing problem, as we will discuss in later chapters, is competition in the HMO segment of the market.

Evidence of a Health Maintenance Organization Effect

The best evidence supporting the HMO effect is the RAND Health Insur- ance Experiment (Manning et al. 1987). This study was designed to esti- mate consumers’ price responsiveness to alternative coinsurance rates for the use of clinical services. We will discuss this study at considerable length in chapter 8. For current purposes, however, knowing that the experiment

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randomly assigned families to alternative health insurance plans is enough. The random assignment has the advantage of largely overcoming the adverse selection problem.

In one part of the experiment, people in Seattle, Washington, were alternatively assigned to Group Health Cooperative of Puget Sound (called Kaiser Permanente Washington since 2017)—a large, well-run staff model HMO—or to a conventional health insurance plan that, like Group Health at the time, had no out-of-pocket charges associated with the use of covered services (a fee-for-service plan that had no cost sharing—hereafter, the Free FFS). Thus, both plans covered an extremely wide range of health services, and both required no copays or coinsurance for the use of the covered ser- vices. Because people were randomly assigned to one plan or the other, any difference in utilization should have arisen from an HMO effect of keeping people out of the hospital.

The results are summarized in exhibit 5.1. Those in the Free FFS plan had an 85 percent chance of interacting with the healthcare system. Those randomly assigned to Group Health (this group was referred to as HMO Assigned) had an 87 percent likelihood of any use. The results are virtually identical. In contrast, the probability of one or more hospital admission was lower for the HMO-Assigned group. They had a 7 percent chance of being hospitalized, while the Free FFS group had an 11 percent chance. This sta- tistically significant difference suggests that the HMO did something to keep people out of the hospital.

The row in exhibit 5.1 titled “HMO control” reflects the experience of a group of longtime Group Health Cooperative members with demographic characteristics similar to those in each of the randomly assigned groups. This addition allows a comparison of whether the newly assigned individuals have experience different from that of longtime enrollees. The answer is that the longtime enrollees have an even lower probability of using hospital care (although the difference is not statistically significant), and they are more likely to interact with the healthcare system. This suggests that the long-term enrollees may see more substitution of ambulatory for inpatient services.

EXHIBIT 5.1 HMO EffectLikelihood of Any Use (%) One or More Admissions (%)

HMO assigned 87 7

HMO control 91 6

Free FFS 85 11

Note: HMO = health maintenance organization, FFS = fee-for-service plan.

Source: Data from Manning et al. (1987).

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While this study is the best evidence of an HMO effect, like all stud- ies it is not without limitations. The key question in this case is the extent to which differential participation rates introduced some selection bias into the study. The participation rate for those Seattle residents participating in the Free FFS plan was 93 percent, while the participation rate in the HMO- assigned plan was only 75 percent (Davies et al. 1986).

Evidence of Favorable Selection

The evidence for favorable selection into HMOs comes from a series of natural experiments that have the following framework: Suppose everyone in an employer group is enrolled in a conventional health plan that collects detailed information on employees’ use of covered health services. Then, at some open enrollment period, employees can choose to take a newly offered HMO or to remain in the existing plan. Once people have made their choices, the researcher goes back into the preceding year’s claims data and compares the health services use of those ultimately choosing the HMO with those ultimately choosing to stay in the conventional plan. If favorable selection into the HMO is present, we should see that, prior to having a choice, those who ultimately chose the HMO had lower claims experience. In contrast, if the conventional plan retained the low utilizers, the prior claims experience of its ultimate enrollees should be lower. If no favorable selection exists, then no difference in the reported levels of prior utilization should exist.

Exhibit 5.2 reports the results of one of the first of these sorts of studies. Jackson-Beeck and Kleinman (1983) reported on the experience of 11 employers who first offered an HMO in the early 1980s. They found that those ultimately enrolling in a newly offered HMO had much lower claims experience in the year prior to the choice than did those who remained in the conventional plan. The difference was $23.14 per member per month

EXHIBIT 5.2 Favorable Selection

Total Expense Institutional Expense

Professional Expense

FFS $57.35 $40.45 $16.45

HMO $34.17 $22.23 $11.45

Difference $23.14* $18.22* $ 5.00*

Notes: *Significant at the 99% confidence level. FFS = fee-for-service plan; HMO = health maintenance organization.

Source: Data from Jackson-Beeck and Kleinman (1983).

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Chapter 5: Adverse Select ion 87

(about $58 in today’s dollars). This difference was largely attributable to institutional (i.e., inpatient) services, but professional services (i.e., ambula- tory services) were also lower.

Wilensky and Rossiter (1986) reviewed the findings of a score of stud- ies that examined the issue of patient favorable selection into HMOs pub- lished between 1974 and 1986. Of the dozen most recent studies, beginning with the Jackson-Beeck and Kleinman study in 1983, eight found evidence of favorable selection into HMOs, three were inconclusive, and only one found no evidence of selection bias.

While the RAND study does offer some strong evidence of an HMO effect—at least in one large, well-run staff model HMO—the research litera- ture suggests that typically substantial favorable selection into HMOs exists. The evidence with respect to other forms of managed care plans is less defini- tive. However, limited but strong evidence suggests that preferred provider organizations (PPOs) get a less favorable draw of the population than HMOs and, in fact, appear to have become the conventional plan of the 2000s, at least with respect to selection bias (see Morrisey, Jensen, and Gabel 2003).

Favorable Selection in the Medicare Program

Adverse and favorable selection are not just concerns of private insurers; they are also significant issues for the federal Medicare program for the elderly. Since the 1970s, the Medicare program has allowed beneficiaries to be in traditional Medicare or to join a Medicare HMO. (See chapter 22 for a more complete discussion of the Medicare program and of Medicare managed care options, called Medicare Advantage.)

Until 2006, the program allowed Medicare beneficiaries to transfer to or from traditional Medicare each month. As with most HMOs, Medi- care HMOs provide a limited panel of physicians and hospitals. Traditional Medicare covers virtually all providers. However, many Medicare HMOs offer broader coverage, including prescription drug coverage and annual physicals, which were particular advantages in the days prior to Medicare Part D prescription drug coverage. The Medicare program paid its participating HMOs on a capitated basis for each covered beneficiary. The payment was essentially 95 percent of the average Medicare cost of care in the local com- munity. Medicare HMOs are required to accept all beneficiaries who choose to enroll, but if a Medicare HMO can somehow attract sufficiently low utiliz- ers of care, it could reap substantial profits.

A congressional advisory commission tasked with researching the costs to Medicare of those who choose Medicare HMOs, relative to those in traditional Medicare, used the same methodology as did the Jackson-Beeck

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and Kleinman (1983) study discussed earlier to look at Medicare claims data from 1989 to 1994. It identified those who newly enrolled in a Medicare HMO, then examined their Medicare claims experience in the six months prior to switching to the HMO and compared it with the average claims experience of all those in traditional Medicare in those months. Those who ultimately switched to a Medicare HMO had total covered claims experience that was only 63 percent of average. This finding suggests substantial favor- able selection, to say the least!

The study also examined the claims experience of those Medicare HMO enrollees who switched back to traditional Medicare. In the six months following their switchback, they had claims experience that was 160 percent of the average. It is easy to speculate that the HMOs sought out low utilizers, encouraged them to join the plan, and if they had health problems, somehow pushed them out of the plan.

However, much less pernicious scenarios also are consistent with these data. Consider a reasonably healthy, elderly, Medicare-eligible woman. She joins a Medicare HMO, perhaps because of its coverage of an annual physical or its encouragement of preventive services. Unfor- tunately, her hip has deteriorated, and she discovers that she needs a hip replacement. Her primary care doctor refers her to the plan’s orthopedic surgeon, but her children want her to see the surgeon they consider the best in town. That surgeon is not in the HMO’s panel. Under the terms of the Medicare program, the woman could disenroll from the HMO, be immediately covered by traditional Medicare, and have her surgery. Once she has recovered, she could even switch back to the HMO. If stories of this sort are common, they could explain the lower claims experience prior to joining the HMO and the higher experience after disenrollment. Other scenarios, such as the one in “An Urban Legend,” are also possible, but unethical at best.

An Urban Legend

Medicare HMOs must enroll any Medicare-eligible person who wants to enroll. The legend, alternatively described as occurring in Florida or New York, has it that the Medicare HMO sets up its enrollment office in a third-floor walkup. Any senior who can walk up three flights of stairs is enthusiastically enrolled!

More recently my colleagues and I have explored the extent of favor- able selection in the Medicare Advantage program over a ten-year period. Our results are summarized in exhibit 5.3. Using a methodology similar to that used by the Jackson-Beeck and Kleinman (1983) and Prospective

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Chapter 5: Adverse Select ion 89

Payment Assessment Commission (1994) studies, we found that in the six months prior to joining a Medicare Advantage plan, patients’ claims costs were only about 80 percent as large as those of people who remained in traditional Medicare. This relationship has been fairly stable over the entire ten-year period. Those who dropped out of a Medicare Advantage plan and returned to traditional Medicare had claims experience, in the six months after they returned, of approximately 136 percent of those who never left the traditional plan. Moreover, the relative costs of those who returned to traditional Medicare have been increasing since the early 2000s. We will have more to say about this in chapter 7.

Persistence of Favorable Selection over Time

The research strongly suggests that HMOs attract a healthier draw of the population. This trend raises the important managerial and policy question of whether favorable selection continues over time. If the experience persists over time, then all an HMO must do to remain successful is attract some low utilizers and keep them happy enough to stay in the plan (and work to prevent the entry of new HMOs into its market). On the other hand, if low utilizers quickly become average utilizers or worse, this suggests that the plan must continuously turn over its enrollment or do something to keep the enrollees healthy. From a policy perspective, if favorable selection is endur- ing, we might consider efforts to promote competition or regulate insurer

EXHIBIT 5.3 Relative Claims Experience of Those Enrolling in or Disenrolling from Medicare

1.5

1.25

0.75

0.5

19 99

20 00

20 01

20 02

20 03

20 04

20 05

20 06

20 07

20 08

1.75

1.5

1.25

0.75 19

20 00

20 01

20 02

20 03

20 04

20 05

20 06

20 07

20 08

Newly DisenrollingNewly Enrolling

Source: Data from Morrisey et al. (2013).

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practices. If the selection bias is fleeting, we might worry more about plan turnover and the quality of care provided.

Obviously, the foregoing discussion of using prior utilization as an indicator of favorable selection rests on a presumption of some persistence of behavior. In the absence of changes in incentives, two factors are likely to influence the persistence of healthcare usage. The first has to do with the chronic-versus-random nature of personal health status. If a person’s illnesses or injuries are largely random, that would suggest that particularly high or low utilization in any one year is an unusual event and that the individual would quickly revert to the average level of utilization. If the conditions are chronic, it suggests that utilization will continue at an elevated level for some time. The second factor is behavioral. For a given health condition and set of prices, one individual may seek care, and another may not. The former will be a persistently higher utilizer; the latter will be a persistently lower utilizer.

Only a handful of studies have examined healthcare utilization over more than two years. One of the problems with undertaking such an analysis is finding several years’ worth of data on a large, identifiable cohort of people who have unchanged health insurance coverage over the period. Garber, McCurdy, and McClellan (1999) undertook such a study using Medicare beneficiary data from 1987 to 1991 and 1991 to 1995. While the study focused only on those who had traditional Medicare over the period, it was not able to control for differences in supplemental coverage that the benefi- ciaries may have obtained, dropped, or changed over the years. Exhibit 5.4 summarizes the findings for the more-recent cohort.

EXHIBIT 5.4 Persistence of Expenditures for Surviving

Medicare Beneficiaries

$45,000

$40,000

$35,000

$30,000

$25,000

$20,000

$15,000

$10,000

$5,000

Ex pe

nd it

ur es

Year

1991 1992 1993 1994 1995

High Mean Middle Low

Source: Data from Garber, McCurdy, and McClellan (1999).

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Chapter 5: Adverse Select ion 91

Garber, McCurdy, and McClellan (1999) had Medicare claims data on a cohort of 37,000 Medicare beneficiaries who were alive in 1989. They divided this group into three subgroups based on their 1993 Medicare spending. The low utilizers were those in the 0 to 50th percentiles. Their average Medicare expenditure in 1993 was $211. The middle subgroup was composed of those in the 51st to 95th percentiles; they had average expendi- tures of $5,758. The high utilizers were those in the 96th+ percentiles; they had average expenditures of $41,921. (This figure shows the typical health insurance experience. A very small proportion of the covered individuals incur the vast majority of the expenditures.)

The pattern of results was clear. First, those with low expenditures in the base year (1993) had unusually low expenditures for that year; however, in the two prior years and two subsequent years, they had much higher expenditures. Analogously, those who were high utilizers in the base year had unusually high expenditures that year. Their experience was much lower in the prior and subsequent years. Second, even though their respective claims experience did revert toward the mean, low utilizers continued to be low utilizers, and high utilizers continued to be high utilizers. In short, while healthcare utilization has a large random component, sizable persistence in use exists. Selection bias tends to be enduring.

We should note that this pattern of results was observed in the 1989 to 1991 cohort as well. The study also noted the effects of deaths among the sample in the two latter years (1994 to 1995 and 1990 to 1991, respectively). Exhibit 5.4 only includes survivors in the last two years; however, the same pattern of results occurs if we include the decedents in the analysis.

Selection Bias in Employer-Sponsored Health Insurance

This chapter has focused on evidence of adverse selection in the HMO versus conventional coverage decision because that is where most of the empirical research has been conducted. The extent of any selection bias is always an empirical question and is not limited to the managed care setting. In some early work, Ellis (1985) examines the extent of selection bias in an employer group that offered a single conventional plan in 1982 but three conventional plans with differing deductibles and stop-loss features in 1983. Ellis con- cludes, “The results presented here suggest that the self-selection effects in these settings may be enormous, with high-coverage plans attracting enrollees who are as much as four times as expensive as enrollees choosing the low- coverage option.”

Recently Bundorf, Herring, and Pauly (2010) explored adverse selection in employer-sponsored health insurance plans. They used data on

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demographics, health status, employment, and insurance coverage from the 1996–2002 Medical Expenditure Panel Survey to examine the extent of adverse selection among low-, medium-, and high-income households and coverage in small-, medium-, and large-employer-sponsored insurance plans. They concluded that, “in aggregate, the likelihood of obtaining employer- sponsored coverage nearly always increases with expected health expen- ditures. The positive relationship between insurance status and expected expenditures is generally consistent across the large group, medium group and small group markets. . . . [This] is consistent with a moderate amount of adverse selection.”

On a related note, it is not at all unheard of for families and indi- viduals to “save up” their use of dental services and obtain dental cover- age only when they expect to use the services. Such actions constitute adverse selection.

The last 15 years have seen the rapid growth of consumer-directed health plans. These products encompass a high-deductible health plan and a tax-sheltered health savings account. Proponents argue that such plans give consumers strong incentives to be value-conscious purchasers of health ser- vices because they must spend their own, albeit tax-sheltered, dollars on the first $2,000 or $3,000 of services used. Consumers are expected to forego services that are not viewed as worth the cost and to shop around for provid- ers who will give them good quality at a lower price. One might expect that there could be substantial favorable selection into these plans, at least in an employer-sponsored context where people have multiple options. In a care- ful review of the empirical literature, Bundorf (2016) concludes that there is such selection based on health status, age, or both.

Adverse Selection and the Affordable Care Act

Adverse selection is also one of the key reasons why the ACA mandates that everyone above a certain income threshold must buy health insurance or pay a penalty. Under the provisions of the law, preexisting health conditions cannot be used to determine one’s insurance premium. As a consequence, people have an incentive to forgo health insurance coverage generally, and only buy it when they are sick.

Little rigorous empirical evidence can be found on the extent of adverse selection in the ACA exchanges. However, it is widely believed to have been a serious impediment to the success of insurers in the ACA market- places. Field work in five states suggest that the presence and magnitude of adverse selection varied significantly across markets. Reports from California and Michigan suggested that that they encountered few problems. California

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explained this as the result of the efforts to manage risk and premiums by CoverCalifornia, the state-based insurance exchange. Michigan attributed it to the presence of regional providers. In contrast, the Florida and Texas reports suggested major problems. Claims costs in Florida exceeded premi- ums by 99 percent, 108 percent, and 256 percent for Aetna, UnitedHealth, and Cigna, respectively. One insurer in Texas reported that it expected claims experience to be 135 percent of standard, but in fact, the claims were 170 percent of standard morbidity assumptions (Morrisey et al. 2017).

Summary

• Adverse selection arises when there is asymmetric information. One party, usually the consumer, knows more about his likely use of health services than does the other.

• Enrollees in HMOs have substantially lower utilization experience than do enrollees in traditional plans. The difference is largely attributable to differences in the use of hospitals.

• The difference in utilization can be attributable to favorable selection into HMOs, an HMO effect (whereby HMOs do something to keep people out of the hospital), or both. While evidence exists on both sides of the debate, the preponderance of data supports the favorable selection argument.

• The available evidence also suggests that the propensity to be a high or low utilizer of services regresses toward the mean over time but nonetheless persists.

• Adverse selection is a potentially large problem for insurers and has implications for Medicare, the private individual market, the employer- sponsored market, and consumer-directed health plans.

• Adverse selection in the ACA marketplaces has been a substantial problem in setting premiums, at least in some states.

Discussion Questions

1. Suppose that the difference in utilization experience between conventional insurance and managed care is attributable to favorable selection. If so, would an employer save any money if it required all of its workers and their dependents to join a managed care plan?

2. When they began offering multiple health plans instead of a single plan, employers often found that their total health insurance costs increased. How could this occur?

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3. If insurers of dental services understand that high utilizers are disproportionately likely to join their plan, what actions would you expect them to take to deal with this condition when they design their insurance plan?

4. If penalties are insufficient to keep people from forgoing required coverage under the ACA, what else might the government do to encourage people to buy coverage?

For the Interested Reader

Morrisey, M. A., A. M. Rivlin, R. P. Nathan, and M. A. Hall. 2017. Five-State Study of ACA Marketplace Competition. Brookings Institution and Rockefeller Insti- tute of Government. Published February. www.brookings.edu/wp-content/ uploads/2017/02/summary-report-final.pdf.

Newhouse, J. P., and the Insurance Experiment Group. 1993. “Results at the Health Maintenance Organization: Use of Services.” In Free for All? Lessons from the RAND Health Insurance Experiment. Cambridge, MA: Harvard University Press.

Wilensky, G. R., and L. F. Rossiter. 1986. “Patient Self-Selection in HMOs.” Health Affairs 5 (1): 66–80.

References

Bundorf, M. K. 2016. “Consumer Directed Health Plans: A Review of the Evi- dence.” Journal of Risk and Insurance 83 (1): 9–41.

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Notes

1. Given the somewhat unseemly assertions about HMO behavior in this section, the author is compelled to disclose that he has been a member by choice of one or another HMO for virtually all the past 35 years.

2. This scenario abstracts from the case in which some or all of the employees pre- fer the HMO. If that is the case, the employer may be able to give employees the HMO and somewhat lower wages than they would have, had the employer offered the traditional health plan. We defer the discussion of compensating differentials in employer-sponsored health insurance until chapter 14.

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