THE URBAN INSTITUTE 2100 M STREET, N.W. / WISCONSIN D.C. 20037
TO: Milda Aksamitauskas FROM: A. Bowen Garrett, Paul Masi, Lisa Clemans-Cope, and Randall R. Bovbjerg DATE: December 26, 2007 SUBJ: Summary of Reinsurance Institute Work with Wisconsin and Final Modeling Results
Background and Motivation
Thank you for your help in improving our understanding of insurance markets in Wisconsin, along with the state’s plans for using reinsurance as part of health insurance reform. We have also benefited from available public documents, other data from you and others, as well as our discussions during the course of the Reinsurance Institute. This memo summarizes and specifically documents our replies to the final data requests you made in August 2007. Those led to our agreed scope of work for simulation modeling on the impacts of publicly funded reinsurance that we subsequently established with you.
Our understanding of Wisconsin’s policy goals began with a review of Governor Jim Doyle’s Healthy Wisconsin proposal and the deliberations and report submitted by the Healthy Wisconsin Council that he created to develop an action plan to effectuate his vision of coverage expansion and other goals.1 As you explained, Wisconsin wished to explore how different reinsurance policy configurations would perform in concert with your other health reforms. It was most helpful to meet with you and your colleagues in Madison last January and to conduct a few background interviews with key informants.
Our project work and this memo mainly use simulation modeling to estimate the costs and benefits of using public funds to reinsure the smallest category of firms in the existing small group market. This market segment was the focus of the Healthy Wisconsin Council and its report.2 We present some descriptive statistics relevant to much broader, catastrophic reinsurance meant to assure, per Governor Doyle’s 2006 State of the State address, that “no family should have to go bankrupt if they get sick.” Finally, we offer some qualitative commentary on related or tangential issues of insurance coverage, cost, and pricing.
For simulation, our main task was to explore how different configurations of state-subsidized reinsurance would affect premium levels and coverage. We initially generated information to
1 Healthy Wisconsin Council Report, Reducing Wisconsin’s Uninsured Rate and Lowering Health Care Costs for Businesses and Families, January 9, 2007
Page 1 THE URBAN INSTITUTE Wisconsin Requests of Reinsurance Institute provide a fuller picture of the baseline demographic and employer composition of the state relevant to reinsurance. You requested a variety of statistics describing the population. These estimates were meant to help guide thinking about targeting reinsurance policies, as well as inform decision making on other state health reforms.
At your request, we also generated information on the distribution of insured health expenditures within the state. The estimates were made in two ways—expenditures within various expenditure categories and number of people with expenditures within different categories.
The last requested quantitative output from the reinsurance model was presentation of a number of results in finer detail. These included estimates of how different reinsurance policy configurations would affect the offer rate of health insurance, take-up rate of insurance, coverage status and premiums across different sub-populations by firm size and non-group cohort. Qualitative input was also provided to help narrow the focus of reinsurance policy proposals to a well-defined set of policies that could be implemented practically within the state, considering the specific state conditions of demography and regulatory practice.
Over the course of the project, as described throughout this memo, we on the Reinsurance Institute team consulted with policymakers in Wisconsin in benchmarking our estimates of state population and insurance markets,3 delivered estimates of the demographic and employer characteristics to help guide policymakers’ deliberations with regard to different reinsurance policies, and estimated the costs and distributional impacts of the policy options you requested.
We also appreciate your review of numerous prior draft results and the feedback we received regarding their consistency with state impressions of the reality in coverage markets and with state goals.
Summary Statistics on Medical Spending
One set of requests was for estimated expenditure distributions of different sub-populations. Early on, we provided initial estimates of the share of total insured expenditures of the state’s population under age 65 years which fall within different expenditure categories.4 These data were provided as a spreadsheet file, and they illustrated the relative costs of different potential reinsurance corridors.
Later, after we finished benchmarking our state-level expenditure estimates to Wisconsin’s demographic and employer characteristics, and health insurance rating regulations (next section), we created estimates of the distribution of insured expenditures in the small group market across expenditure categories defined in $5,000 increments. These corridors allowed spreadsheet users
3 In addition to the authors of this memo, the team included Jim Mays of Actuarial Research Corporation and Karl Ideman of Pool Administrators, Inc. Benchmarking efforts included Office of the Insurance Commissioner, Wisconsin, Health Insurance For Small Employers and Their Employees, Dec. 2006
Page 2 THE URBAN INSTITUTE Wisconsin Requests of Reinsurance Institute to approximate the amount of funding needed to reinsure expenditures falling within any grouping of these corridors, for different populations of interest. (Note: for the estimations, the small group market is taken to be firms with 2 through 49 employees. The reason is that our key data source, the Medical Expenditure Panel Survey- Household Component (MEPS-HC) draws the line between firm size categories below size 50 rather than including size of 50 with other small employer sizes, although the latter might be preferred for insurance market analysis.)
To the cost data by corridor, we added a count of the number of people in Wisconsin estimated to have expenditures within each of corridor. These data were provided in a spreadsheet format, which allowed rough calculations of the amounts of insured expenditures within different expenditure corridors, across different markets. This ability provided you with an idea of how much different reinsurance policies would cost, based on selected reinsurance corridors, and a coinsurance rate—although the spreadsheet lacked the richness of a full simulation of behavior responses by employers and employees. A revised, final spreadsheet file is being delivered along with this summary memo.
At different times, you also requested detailed demographic and employer statistics of the overall workforce, all employees in the sector of interest (ages 19-64 and privately employed), and the subset of such employees who worked in small firms (see Appendix Table 1). Using our final Wisconsin dataset, we estimated the percentage of workers in these different populations that fall within certain age brackets (19 to 24 years, 25 to 34 years, 35 to 44 years, 45 to 54 years, and 55 to 64 years), family income as a percent of the federal poverty level (FPL) (0 to 99%, 100 to 199%, 200 to 399%, and 400+% FPL), coverage status, the number reporting their health status as fair or poor, and the number of workers whose employer made an offer of health insurance. Another request was that we estimate the number of workers in these different populations who are dependents, and the firm size of the policyholder providing them with coverage. We estimated that Wisconsin’s small group workers tend to be younger, have lower income, are slightly less likely to have an employer who offers health insurance, and are slightly more likely to report their health status as fair or poor than is the overall privately employed workforce of ages 19 to 64 years.
Configuring the Reinsurance Simulation Model for Wisconsin
To provide our best possible estimates of the impacts of a wide variety of reinsurance policies for Wisconsin, it was essential to create an underlying database which closely approximated the demographic and employer profile of the state.5 After the initial reweighting of our national MEPS data to match the Wisconsin demographic profile, we consulted with your survey data administrator to verify that our estimates were consistent with internal state estimates. In this phone consultation, state staff explained that they were comfortable with our estimates of their population’s profile, and that any discrepancies between the two sets of estimates were within an acceptable confidence interval.
5 Much more detail on modeling methods appears in our overall final project report to the State Coverage Initiatives program.
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Another adjustment to the initial dataset took account of insurance rules in the state. Wisconsin regulations do not allow “groups of one person” to be eligible for group coverage in the small group market. There was no intent to change this regulation with insurance reform, and at your request we separated out workers who report being in a firm of size one. This involved re-coding our baseline dataset to place these individuals into their own category, and also removing them from all of the “synthetic” small firms created within our simulation model so as to more accurately reflect your state’s insurance pricing.
Another task in creating a valid baseline dataset was to benchmark preliminary premium estimates from the model to information about premiums in Wisconsin. This involved the Medical Expenditure Panel Survey- Insurance Component (MEPS-IC), an employer survey, as well as review of available documents and team interviews with key informants in the state.
Consultation to Sharpen Focus of Reinsurance Policies to be Modeled
Throughout the Reinsurance Institute’s operations, we enjoyed our lively exchange with you in Wisconsin, as the state considered aspects of reform including narrow and broad corridors of reinsurance, different coinsurance rates, merging of small group and direct pay markets, implementing a basic, catastrophic coverage plan or a reinsurance corridor without an upper limit. Throughout, you requested information on the impacts, distributional effects, and feasibility of these different policies. We were pleased to be able to consult in-person, over the phone, and through email about such issues.
The ultimate request was that we model the impact of three types of reform—a narrow reinsurance corridor, a broad reinsurance corridor, and the impact of reinsuring health plans against catastrophic claims. While the term “catastrophic” has been used in previous literature to describe health expenditures that are both extremely high and abnormal for a particular individual, in the context of this analysis we describe a reinsurance program reimbursing costs for any individual with costs over $14,000 as “catastrophic,” regardless of health expenditures in previous years.These modeling exercises were performed for the smallest of the small group market, firms of 2 through 9 employees.6
Wisconsin Requests: Addressing Very Broad Catastrophic Coverage
To help inform Wisconsin’s consideration of policies that would provide catastrophic coverage to a very broad population, we were asked to describe the distribution of health care expenditures for the nonelderly population under 65 years old who are not enrolled in Medicare. We also exclude individuals with other sources of public coverage, including Medicaid and SCHIP, because we assume that any new catastrophic coverage program would seek to augment rather than displace existing forms of public coverage. We report the results in Figure 1, which shows the estimated total annual insured health expenditures by expenditure category (in $5,000 increments). (Note: here and elsewhere, dollars are stated as 2007$ values.)
6 Again, we appreciate that the Council report addressed small firms with 10 or fewer workers, but data limitations led us to proxy this group as 2 through 9.
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As an example, Figure 1 indicates that the annual total of insured health expenditures of $100,000 and above per person in a year totals more than $492 million. A level of $100,000 per person in a year is one way to define catastrophic. Lowering the threshold would cost correspondingly more, as the Figure shows. Figure 1 does not include out-of-pocket expenditures by the insured or expenses of the uninsured; moreover it merely indicates the order of magnitude involved in paying for very high medical expenses for a very broad WI population. Much more specificity would be needed to cost out a finished policy option.
Wisconsin Requests: Outputs from the Reinsurance Institute Simulation Model
Per your requests, microsimulation modeling of reinsurance policies was focused on reinsurance for the smallest firms, those with 2 to 9 employees. Specifically, we were asked to provide options for publicly-funded reinsurance policies that would total approximately $100 million per year when fully implemented. We presented preliminary estimates for three such policies at the Reinsurance Institute final meeting on July 19, 2007. We have since revised the baseline database for Wisconsin as well as the reinsurance microsimulation model itself, and we present our revised and final estimates below.
Table 1 reports selected population characteristics of Wisconsin as measured in the reinsurance model’s baseline file. As requested, we reported separate estimates for workers in firms with 2 to 9 employees and their dependents. The baseline file for Wisconsin shows an estimated 524,000 uninsured individuals in the state. Firms with 2 to 9 employees employ an estimated 244,000 workers, of whom 42,000 are uninsured. Employees in the targeted small firms have an estimated 97,000 dependents, of whom 7,000 are uninsured. The reinsurance policies that we model, therefore, have the potential of affecting up to 49,000 uninsured individuals associated with the smallest firms.
Table 2 reports the number of employees and employers by firm size as reflected in the baseline file for Wisconsin. These figures are based on estimates from both the Current Population Survey and Statistics of U.S. Businesses. Where there were discrepancies, our estimates reflect the midpoint between the two data sources. We estimate there are 38,100 firms with 2 to 9 employees in Wisconsin that employ the estimated 244,000 people discussed above.
Using the Reinsurance Institute Microsimulation Model, we searched for reinsurance corridors and carrier retention percentages that led to a publicly-funded reinsurance policy targeting workers in firms with 2 to 9 employees that would cost the state an estimated $100 million annually.7
7 Without a mechanism allowing the carriers to retain some of the risk within the reinsurance corridor, reinsurance programs could create disincentives to manage cases efficiently by shifting risk away from carriers within the corridor. This could potentially increase total health spending among those eligible for reinsurance, which could lead to unexpectedly large government program costs or could lead to a reduction in the desired impact of the program on premiums. See Collins, Patrick L., et al. 2005 (January). “Medical Reinsurance: Considerations for Designing a Government-Sponsored Program.” American Academy of Actuaries. http://www.actuary.org.
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We identified three separate reinsurance policy configurations which we list in Table 3. The three configurations have reinsurance corridors of increasing widths, labeled as the “narrow,” “broad,” and “catastrophic” options.8
We summarize the overall effects of the three configurations in Table 4. Each of the options, costing around $100 million, are estimated to reduce the number of uninsured in Wisconsin by around 5,850 persons—a 1.1 percent reduction in the number of uninsured. In the narrow option, single premiums would fall by about 20 percent and family premiums would fall by about 19 percent for employees of the targeted small firms with 2-9 employees. In contrast, single premiums would fall by only 7 percent and family premiums would fall by about 34 percent in the two broader options. This difference in premium impact occurs because adults with single policies tend to be younger and healthier than adults with family policies.9 While each of the three policies have similar overall effects on the level of uninsurance, it is important to note that government costs would tend to have more annual variability in the policies with a higher attachment point, because the number of individuals with very high expenses in any particular year is inherently more volatile than the number of individuals with moderately-high expenses.
Table 5 provides detailed results for the changes in premiums we estimate for the broad reinsurance configuration, with a corridor of $15,000 to $75,000. Along with the decline in ESI premiums already discussed in Table 4, the model predicts that nongroup premiums would tend to decline slightly as individuals who are more costly than the average nongroup enrollee in each nongroup rating cell leave the nongroup market to take up new or existing offers of ESI coverage.
Table 6 provides detailed results for the changes in coverage we estimate for the broad policy configuration. We estimate that the number of employers who are ESI policy holders would increase by about 6,700 and the number of ESI dependents would increase by 2100. While most of the increase in ESI coverage is driven by reducing the number uninsured, we estimate that about 3000 persons would switch from nongroup coverage to ESI coverage as ESI premiums fall, more small employers offer coverage, and more employees take-up coverage. We estimate that the share of small firms that offer would rise from 62.4 percent to 66.1 percent with the reinsurance policy, while the percent of employees who take-up coverage when employers offer would rise from 63.8 percent to 64.8 percent.
Additional Qualitative Observations and Concluding Discussion
The data and simulation results presented in this memo describe the main impacts of a program in which the government reinsures the small group health insurance market for employers with 2
8 While the term “catastrophic” has been used in previous literature to describe health expenditures that are both extremely high and abnormal for a particular individual, in the context of this analysis we label a reinsurance policy reimbursing costs for any individual with costs over some particular threshold as “catastrophic,” regardless of expenditures in previous years. 9 The reinsurance model does not include a cross-subsidy between the single and family coverage products but rather assumes the two types of policies are rated separately. If there were a cross-subsidy, the differences in premium changes for single and family policies would likely be more similar.
Page 6 THE URBAN INSTITUTE Wisconsin Requests of Reinsurance Institute through 9 employees. We model three scenarios of attachment points, upper limits, and carrier retention rates, each of which we estimate will cost (as requested) about $100 million in state funding per year once fully implemented in 2007 dollars and given current health care costs. Under each scenario, the number of uninsured would fall by about 5,850 individuals—about 12 percent of these employers’ 49,000 uninsured workers and dependents, or about 1 percent of all uninsured people in Wisconsin.
Most of the benefit of this reinsurance would flow to very small firms and their workers and dependants who already have coverage. Their premiums would be lowered by about 20 percent, on average. Considering that these very small employers are disadvantaged in purchasing health insurance coverage by facing an administrative load of around 36 percent, a reinsurance policy of the type we have modeled could offset much of the burden of these higher loads. If one instead ignores benefits to the already insured and considers all reinsurance spending as a cost of insuring new people, the estimated reinsurance cost per newly insured person would be about $17,100.
As for catastrophic reinsurance that would protect all Wisconsin residents but those with public coverage against medical bankruptcy, only preliminary assessment is feasible. Details on the target population and specific reinsurance terms are lacking. We also lack information on bankruptcy circumstances in Wisconsin and also on families’ net assets. As an initial indicator of the likely scale of resources needed, we have estimated existing insured medical costs by increment of spending (figures 1 & 2). For example, it would likely cost some $500 million or more to cover all insured medical costs above $100,000 a year for everyone without public coverage. A narrower catastrophic reinsurance program aimed only at out-of-pocket spending would cost less.
Several other issues of interest in Wisconsin constitute comments upon the data or simulations presented or else are not suitable for modeling but merit some qualitative discussion:10
Some observers have noted that reinsurance programs such as those modeled in this report produce a “one-time” reduction in insurance premiums for the groups or individuals eligible for the program.11 If the state subsidy is maintained over time, it will result in the same private savings each year. Overall health spending would not be reduced as a result of this program, although their distribution would be, and it is not known to what extent new efficiency disincentives would accelerate the preexisting upward trend in health costs. In addition, compared to commercial reinsurance, a government-funded reinsurance program is particularly vulnerable to inefficiencies; in commercial reinsurance, carriers have incentives to manage large claims since commercial reinsurance premiums are typically adjusted each year to reflect the primary carrier’s claims experience.
10 Some of these points are specific to Wisconsin, others have general application. Many of the latter are discussed further in our report to SCI or in other sources, such as the American Academy of Actuaries report referenced below. 11Collins, P (May 24, 2007) in testimony for “Hearing on Increasing Competition, Reducing Costs, and Expanding Small Business Health Insurance Coverage Using the Private Reinsurance Market.” Available at http://www.actuary.org/pdf/health/reinsurance_may07.pdf
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Another consideration is that the simulations presented here hold some movements in coverage fixed. For example, public health insurance program enrollment is constant. Under the simulations modeled above, it is possible that some individuals currently in public programs such as Medicaid may gain an affordable offer of ESI or non-group coverage. Financial protection under Medicaid is generally greater than that of private insurance; therefore we would expect a relatively small movement of coverage from Medicaid to private health insurance. However, some coverage changes away from public coverage may result as other health insurance options become relatively more attractive than under current law.12 In addition, the simulations above also do not allow for movement from large group coverage to non-group coverage, or from large group coverage to small group coverage. The latter could occur, for example, when a family can choose between ESI offers received from employers of two parents, one from a small the other from a large employer.13
The simulations also assume that all savings to reinsured health plans from the state subsidy received will be passed through to purchasers of health coverage. Savings consist of both the direct reduction in cost of claims and proportionate reductions in insurers’ “loads” or associated expenses including return on capital. This important simplifying assumption needs some qualification.
Perhaps most importantly, we assume that either regulation or competition will drive insurance prices (premiums) down to new, lower cost levels after the subsidies are received. Wisconsin appears to rely much more on competition than on insurance regulation to assure buyers of reasonable pricing. The insurance department’s guide shows that many insurers sell small group coverage, and it is evidently believed that the market is sufficiently competitive. Given that the reinsurance subsidies discussed in this memo are public monies, however, and also that they will go to sellers of insurance but are meant to benefit buyers, it may be that the state will want to consider at least a new cost and price monitoring function to make sure that the intended price reductions are actually implemented.
Another pricing observation is that implementing a new reinsurance subsidy will create some new costs for insurers to submit claims and resolve disputes. On the other hand, it can be argued that reinsurance will reduce variation in high-end claims and hence the “risk premium” that insurers need to charge. For purposes of the estimations made here, we consider such new costs and savings to be offsets and do not attempt to include either in the modeling. There will also be some new costs of administration for the state or its agent to operate a new system of receiving and paying claims. The percentage load imposed by these new costs will likely depend upon the corridor selected, which will affect the ratio of subsidy amount to number of claims. Based on experience of Pool Administrators, Inc., as noted at the July Reinsurance Institute meeting, these
12 For an analysis of the extent to which changes in the availability of ESI influences disenrollment from Medicaid in California, see Perreira KM. Crowd-in: the effect of private health insurance markets on the demand for Medicaid. Health Serv Res 2006 Oct;41(5):1762-81. 13 Due to the large differences in administrative costs between these markets, in addition to other factors such as benefit package generosity, these movements may be relatively modest.
Page 8 THE URBAN INSTITUTE Wisconsin Requests of Reinsurance Institute are apt to be in the very low single digits as a percentage of premiums even with a very low threshold for reinsurance coverage.
Another administrative observation is that introducing reinsurance will create moral hazard among primary insurers analogous to that created for enrollees by primary coverage. The incentives to economize appropriately in administering health benefits may be reduced where a reinsurer will pay 90% of the expense. A particular issue arises if reinsurance is open-ended, as it sometimes seems to be under expansive descriptions of protection against catastrophically high medical spending. Primary health plans and their customers may create benefit packages with higher annual or lifetime limits on total payouts if the state is paying for most of the resulting medical claims expense. This issue does not arise for reinsurance done as a corridor, with an upper limit. The requirement of a coinsurance percentage or retention of risk by the primary insurer maintains some incentive to economize appropriately, but likely some specific counter measures will be needed in practice, as is discussed more in our SCI report.
Additional policy design issues to consider in addressing carrier incentives include the following issues, as highlighted by the American Academy of Actuaries.14
1. Carriers and health plans that negotiate larger price discounts with physicians and hospitals may benefit relatively less from a reinsurance policy with a fixed reinsurance corridor; a reinsurance program may encourage these carriers to renegotiate fees paid to hospitals and physicians. Changes in carrier price discounts are not modeled in the simulations in this report; accounting for changes in these discounts would likely increase estimated government costs. 2. Mandatory reinsurance for carriers may lead to inefficiency as some carriers may then have too much reinsurance coverage, while others may have too little. 3. If the upper limit of the reinsurance corridor is set relatively high, carriers may have incentives to pay claims that they previously would have rejected or disputed through litigation. The simulation model in this report does not account for these potential behavioral changes; accounting for changes in these discounts would likely increase estimated government costs 4. Disease management programs may also be integrated into a reinsurance program, in order to offset disincentives for carriers to manage risk of high-cost individuals. However, disease management programs may themselves have costs to the government, and consideration must be given as to how and in which cases to integrate these programs into existing health insurance plans.
Distributional issues of perceived fairness across different recipients of reinsurance subsidy may call for more political than technical analysis.
14 Collins et al. 2005. Several additional policy design parameters discussed in the American Academy of Actuaries paper include: (1) indexing the attachment point of the reinsurance corridor in order to decrease the leveraging effect that would cause the state’s costs to rise faster than the overall rise in health expenditures; (2) varying the attachment point of the reinsurance corridor to account for geographic cost variation; (3) including claim adjustment expenses, including payments to business that help carriers reduce claim costs, as a reimbursable loss for carriers.
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This memo has not assessed sources of revenue to pay for reinsurance to promote increases in health coverage, but one observation is appropriate. It is often noted that some existing expenditures for uninsured health care might be redirected to help finance the reinsurance program. Wisconsin’s expenditures on uncompensated care are one example of such funds. Hadley and Holahan (2004) found that government is the primary source of funding for uncompensated care, and approximately one-third of government spending nationally for uncompensated care comes from state governments.15 It is our impression, however, that Wisconsin ranks relatively low in disproportionate share hospital (DSH) payments that are the major state mechanism for such uninsured spending. Moreover, while uncompensated care costs will fall somewhat if coverage increases, it is likely that providers would strongly resist redirection of subsidies for an incremental reform like the reinsurance programs simulated here, because so many residents would remain uninsured.
The Council Report and conversations and email exchanges with you have raised other issues that are tangential to the type of publicly funded reinsurance addressed by this project, but we can offer brief commentary here. Another type of reinsurance, for larger small groups that are simulated to receive state subsidy is to operate a state reinsurance pool that would essentially assess market participants pro rata and from the proceeds cover high-end claims for all. The intent includes moderating fluctuations in high end claims expense across group and from year to year as well as reducing the incentives for risk segmentation.
We do not model this strategy but have three comments: First, it appears that such pooling is meant to be mandatory. This is consistent with the experience of small group reform reinsurance pooling where unless participation is mandatory, many market participants have opted not to participate, often those with large market share. Second, in the absence of new state subsidy for this small group market sector, the overall price level will be little if at all changed by even a mandatory pooling arrangement. (Potential savings from reduction in risk premium, as above, are likely offset by new costs.) Hence, some “winners” from this pooling might see lower prices but only to the extent that others see higher prices. Any effects on offer and take-up rates for coverage and on the number of uninsured seem likely to be very small.
Third, it is not clear whether the primary intent of the pool is to reinsure very high, unusual claims that can have large impacts on average losses within small risk pools or instead to reinsure a lower corridor of claims exposure (like Healthy New York), such that the impact is lessened of a small workplace’s having enrollees with chronic diseases like diabetes that generate above average but non catastrophic spending year after year. In either case, the size of transfers to the pool needed to offset medical claims in the reinsured corridor of primary insurer expense could be substantial. For example, in terms of medical payouts only (not counting insurer load), 90% of costs in the $15,000 - $75,000 corridor noted above would constitute one quarter of all medical expense—thus implying very large transfer payments, likely in the hundreds of millions of dollars. Such issues deserve more careful analysis than is possible under this project as well as careful political consideration. 15 Hadley J. and J. Holahan. 2004. “The Cost of Care for the Uninsured: What Do We Spend, Who Pays, and What Would Full Coverage Add to Medical Spending?” Kaiser Commission on Medicaid and the Uninsured, Issue Update, May 2004, accessible from http://www.kff.org/uninsured/7084.cfm (updating 2003 Health Affairs article).
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Finally, the issue has been raised of using insurance regulation rather than reinsurance to maintain insurability for small groups. In particular, it would be legally feasible to require guaranteed issue of insurance for the small group market plus stronger community rating than is now achieved by today’s “rating bands” that restrict variation in rates from low to high. Instead of paying for high cost claims through reinsurance, as simulated in this project, such rating rules would require that higher projected costs be shared across all enrollees. This would create price increases and disincentives to insure among today’s lower rated groups with adverse but unquantified impacts on their rates of offer and take-up of insurance coverage. Again, this calls for careful consideration of actuarial impacts and prior political experience in other states that go beyond the scope of this reinsurance project.
Page 11 Figure 1. Estimated Annual Insured Health Expenditures by Expenditure Category, Wisconsin Population under Age 65 Not Publicly-Insured
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T 802 1,000 589 447 492 311 248 205 157 139 125 108 95 83 66 57 54 50 41 0 Exp. $1,000s
Note: All amounts are estimates of total annual insured health expenditures by expenditure category. Estimates do not include administrative expenses of reinsur. program or primary insurers' loading costs. Source: Urban Institute tabulations from the Reinsurance Model estimated with 2001-2003 Medical Expenditure Panel Survey data, re-weighted to reflect the Wisconsin population. All dollars inflated to 2007$s, and benchmarked to external estimates of state premiums. Sample is Wisconsin population ages 0-64 not enrolled in Medicare or Medicaid. Urban Institute estimates from the Reinsurance Model are for state use. Suggested citation for further calculations by Wisconsin: "Wisconsin calculations using Urban Institute estimates of state health expenditures, produced for the Reinsurance Institute."
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Figure 2. Share of Total Annual Insured Health Expenditures, by Expenditure Category, Wisconsin Privately-Insured (Group and Non-Group) Population, Revised 6 December 2007 100%
90%
80% s e r u t i
d 70% n e p x E 60% h t l a e H
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Note: All amounts are estimates of the share of total annual insured health expenditures by expenditure category. Estimates do not include administrative expenses of reinsur. program or primary insurers' loading costs. Source: Urban Institute tabulations from the Reinsurance Model estimated with 2001-2003 Medical Expenditure Panel Survey data, re- weighted to reflect the Wisconsin population. All dollars inflated to 2007$s. Sample is Wisconsin population under 65 years old, privately insured with employer-sponsored insurance or non-group. Urban Institute estimates from the Reinsurance Model are for state use. Suggested citation for further calculations by Wisconsin: "Wisconsin calculations using Urban Institute estimates of state health expenditures, produced for the Reinsurance Institute."
Page 13 Table 1 Baseline population characteristics for Wisconsin Baseline Estimate (thousands)
Total Wisconsin Population 5,638
Number of uninsured 524
Eligible for Reinsurance Policy Targeting Firms with 2-9 Employees 341
Adult, private employees in firms with 2-9 employees (Age 19-64 years) 244
Uninsured 42
Insured 202
All dependents of private employees in firms with 2-9 employees (Age 0-64 years) 97
Uninsured 7
Insured 90
Source: Urban Institute analysis, Reinsurance Institute 2007.
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Table 2 Estimated number of employees and employers for Wisconsin
Baseline Estimate
Number of private employees, age 19-64 years, by firm size category
2-9 employees 244,318 Uninsured 42,434 (17.4%) Insured 201,884 (82.6%)
10-24 employees 190,829 Uninsured 41,455 (21.7%) Insured 149,374 (78.3%)
25-49 employees 132,632 Uninsured 20,294 (15.3%) Insured 112,338 (84.7%)
50-99 employees 220,430 Uninsured 18,346 (8.3%) Insured 202,084 (91.7%)
100 or more employees 1,360,784 Uninsured 122,309 (9.0%) Insured 1,238,475 (91.0%)
Total 2,148,992
Number of firms by firm size category
2-9 employees 38,100
10-24 employees 15,197
25-49 employees 8,124
50-99 employees 7,160
100 or more employees 38,915
Total 107,496 Source: Urban Institute analysis, Reinsurance Institute 2007. Note: For the purposes of this simulation model, a firm is defined as that part of an enterprise within a particular state and industry, following definitions provided by the SUSB (http://www.census.gov/epcd/susb/introusb.htm ). The number of employees in a firm includes only those employees in the state, while the firm size category is determined by the number of employees in the firm across all states. In addition, the number of employees of a firm in a particular industry includes only those employees in the industry in the state, while the firm size category is
Page 15 THE URBAN INSTITUTE Wisconsin Requests of Reinsurance Institute determined by the number of employees in the firm across all industries and states. Thus, while this firm definition is necessary for our simulation model, summing the firms across state and industries would overstate the number of unique firms. Therefore, in our data, counterintuitive results are possible. For example, there may be only 90 employees in a firm of a particular industry even when the firm is categorized as a firm with 100 employees or more.
Table 3 Alternative configurations of publicly-funded reinsurance in Wisconsin simulated for the Reinsurance Institute
Reinsurance Configurations Eligible populations by policy parameters "Narrow" "Broad" "Catastrophic"
Firms with 2 to 9 employees $5,000 to $15,000 to Reinsurance Corridor (in 2007 $) $17,500 $75,000 $14,000 and up Carrier retention percentage (%) 10% 10% 20%
Page 16 Wisconsin Requests The Urban Institute
Table 4 Post-reform changes for three configurations of publicly-funded reinsurance available to firms with 2 to 9 employees in Wisconsin State
Reinsurance Configurations "Narrow" "Broad" "Catastrophic" Reinsurance Corridor ($) $5,000 to $17,500 $15,000 to $75,000 $14,000 and up Carrier retention percentage (%) 10% 10% 20%
Changes in uninsured (number of people) -5,865 -5,865 -5,831 (percentage change in number of uninsured) -1.1% -1.1% -1.1%
Changes for firm size: 2 to 9 employees Change in single premiums (2007 $) -$919 -$323 -$334 (percentage change) -19.9% -7.0% -7.2%
Change in family premiums (2007 $) -$2,690 -$4,838 -$4,977 (percentage change) -18.7% -34.0% -34.5%
Change in firms offering ESI (number of firms) 1,659 1,291 1,291 (percentage point change) +9.9% +7.7% +7.7%
Government cost* (in Millions, 2007 $) $100.1 $98.8 $101.0
Note: Urban Institute analysis for the Reinsurance Institute, 2007. * It is important to note that variability in state government costs increases as the attachment point increases.
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Table 5 Post-reform changes for broad configuration of publicly-funded reinsurance Eligible population: Firms with 2 to 9 employees in Wisconsin "Broad" Policy: Reinsurance Corridor $15,000 to $75,000 with Carrier retention percentage 10%
Baseline Post Reform Percentage (in 2007$) (in 2007$) Change Single Group Premiums by firm size 2 to 9 employees 4,616 4,293 -7.0% 10-24 employees 4,536 4,536 0.0% 25-49 employees 4,574 4,574 0.0% 50-99 employees 4,788 4,788 0.0% 100 or more employees 4,610 4,610 0.0% Average 4,629 4,594 -0.8%
Family Group Premiums by firm size 2 to 9 employees 14,408 9,570 -34.0% 10-24 employees 12,889 12,889 0.0% 25-49 employees 13,197 13,197 0.0% 50-99 employees 12,853 12,853 0.0% 100 or more employees 12,834 12,834 0.0% Average 12,930 12,703 -1.8%
Single Non-group Premiums, by characteristics of individual Healthy, male, under 25 years 1,089 1,089 0.0% Healthy, male, 25-44 years 1,878 1,885 0.4% Healthy, male, 45-64 years 3,374 3,390 0.5% Healthy, female, under 25 years 2,794 2,777 -0.6% Healthy, female, 25-44 years 2,560 2,491 -2.7% Healthy, female, 45-64 years 5,755 5,535 -3.8% Fair/poor health, male, under 25 years 339 339 -0.1% Fair/poor health, male, 25-44 years 1,671 1,672 0.0% Fair/poor health, male, 45-64 years 3,532 3,550 0.5% Fair/poor health, female, under 25 years 2,541 2,569 1.1% Fair/poor health, female, 25-44 years 1,976 1,925 -2.6% Fair/poor health, female, 45-64 years 9,996 9,993 0.0% Average 2,840 2,796 -1.5% (table continues)
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Table 5 (continued)
Family Non-group premiums, by Characteristics of Family Healthy, no 15-44, none older than 44 2,012 1,935 -3.8% Healthy, no 15-44, one older than 44 7,399 7,256 -1.9% Healthy, no 15-44, two older than 44 7,444 6,799 -8.7% Healthy, 15-44, none older than 44 8,741 7,925 -9.3% Healthy, 15-44, one older than 44 8,232 8,076 -1.9% Healthy, 15-44, two older than 44 5,047 5,007 -0.8% Fair/poor health, no 15-44, none older than 44 2,842 2,769 -2.6% Fair/poor health, no 15-44, one older than 44 3,738 3,277 -12.0% Fair/poor health, no 15-44, two older than 44 22,669 21,543 -5.0% Fair/poor health, 15-44, none older than 44 3,499 3,389 -3.2% Fair/poor health, 15-44, one older than 44 27,180 27,031 -0.5% Fair/poor health, 15-44, two older than 44 . . . Average 8,525 7,890 -7.5%
Total Government Costs $98,772,992 Government costs due to non-group coverage 0
Government costs due to group coverage $98,772,992
Source: Urban Institute analysis, Reinsurance Institute 2007. Note: Components may not add to totals due to rounding.
Page 19 THE URBAN INSTITUTE Wisconsin Requests of Reinsurance Institute
Table 6 Post-reform changes for broad configuration of publicly-funded reinsurance Eligible population: Firms with 2 to 9 employees in Wisconsin "Broad" Policy: Reinsurance Corridor $15,000 to $75,000 with Carrier retention percentage 10%
Change (Percentage is percentage point Baseline Post Reform change) Health Insurance Coverage Employer-Sponsored Insurance, as Policy- holder 1,727,438 1,734,187 6,749 Column percent (%) 31.2% 31.3% 0.1% Employer-Sponsored Insurance, as Dependent 1,540,523 1,542,665 2,142 Column percent (%) 27.8% 27.9% 0.0% Non-group 223,788 220,762 -3,026 Column percent (%) 4.0% 4.0% -0.1% Medicaid/SCHIP 657,764 657,764 0 Column percent (%) 11.9% 11.9% 0 Medicare 758,030 758,030 0 Column percent (%) 13.7% 13.7% 0 Other public 104,924 104,924 0 Column percent (%) 1.9% 1.9% 0 Uninsured 524,263 518,398 -5,865 Column percent (%) 9.5% 9.4% -0.1% Total 5,536,730 5,536,730 0
Firm's health insurance offer rate by firm size (%) 2 to 9 employees 41.1% 48.3% 7.2% 10-24 employees 69.3% 69.3% 0.0% 25-49 employees 83.6% 83.6% 0.0% 50-99 employees 89.3% 89.3% 0.0% 100 or more employees 98.0% 98.0% 0.0% Total 72.1% 74.7% 2.6%
Employee offer rate by firm size (%) 2 to 9 employees 62.4% 66.1% 3.7% 10-24 employees 61.4% 61.4% 0.0% 25-49 employees 73.3% 73.3% 0.0% 10-24 employees 80.3% 80.3% 0.0% 100 or more employees 80.8% 80.8% 0.0% Total 72.1% 74.7% 2.6% (table continues)
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Table 6 (continued)
Employee take-up rate (conditional on offer) by firm size (%) 2 to 9 employees 63.8% 64.8% 1.1% 10-24 employees 80.7% 80.9% 0.2% 25-49 employees 75.9% 76.3% 0.3% 50-99 employees 81.4% 82.4% 0.9% 100 or more employees 79.3% 81.6% 2.4% Total 57.8% 59.5% 1.6%
Source: Urban Institute analysis, Reinsurance Institute 2007.
Appendix Table 1.
Page 21 THE URBAN INSTITUTE Wisconsin Requests of Reinsurance Institute
Wisconsin Summary Statistics of Income, Age and Health Coverage by Employee Type Target Whole All Target Emp's Population Employees Employees1 Firms 1-49 Total Number 5,637,806 2,621,461 2,114,562 560,942 Income 0-99% FPL 14.4% 2.3% 2.6% 3.7% 100-199% FPL 17.3% 10.4% 10.7% 14.7% 200-399% FPL 32.4% 35.2% 37.4% 45.8% 400%+ FPL 35.9% 52.2% 49.3% 35.8% Mean yearly wage ($) - 41,684 42,450 34,975 Age 19-24 years 7.5% 10.9% 12.4% 16.0% 25-34 years 11.8% 20.9% 22.6% 22.2% 35-44 years 14.7% 26.0% 28.9% 33.1% 45-54 years 14.9% 26.5% 25.1% 18.9% 55-64 years 10.4% 10.9% 10.9% 9.8% Health Coverage ESI-policyholder 31.3% 59.0% 60.8% 49.1% ESI-dependent 27.9% 15.0% 14.9% 14.6% Non-group 4.0% 5.8% 6.9% 12.6% Medicaid 11.9% 2.6% 3.0% 3.7% Medicare 13.7% 5.4% 1.2% 0.7% Other Public 1.9% 2.2% 1.8% 1.6% Uninsured 9.4% 9.9% 11.4% 17.6% Health Status Fair/poor health 10.0% 3.8% 4.0% 4.7% Offer % with employer offer2 - 71.6% 70.3% 54.1%
Number with dependent coverage: - - - 82,172 Number with dependent coverage and policyholder is in firm with >100 employees: - - - 15,372 Number with dependent coverage and policyholder is in firm with <100 employees: - - - 37,598 Number with dependent coverage and firm size not ascertained: - - - 29,203
Source: Urban Institute tabulations of the reinsurance model's baseline file for Wisconsin, estimated with national 2001-2003 Medical Expenditure Panel Survey data, re-weighted to reflect the 2004/2005 Wisconsin population as estimated by the Current Population Survey (CPS) and Statistics of United States Business (SUSB). 1Private employees, ages 19-64. 2Employee received offer of employer-sponsored insurance.
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