Analysis of Employer Mandate

A requirement that all or some subset of employers offer health insurance to all or some subset of their employees. Proposals often include a "pay-or-play" provision - which means that employers may choose to offer health insurance to their employees (the "play" option) or pay a fee or tax into a public fund that is used to cover uninsured workers.

These are the nine performance dimensions against which we measured Employer Mandate:

Spending

An employer mandate will not have a discernible effect on total health care spending:

  • Using our model, we estimate that aggregate health care spending will increase $890 million to $2.01 billion (which is less than 0.1 percent of total spending), depending on the design of the employer mandate. Read more below
  • From our model, we estimate that firms newly offering coverage will spend $9.12 to $17.89 billion on premium contributions, and penalty payments will be $4.23 to $12.48 billion. Read more below
  • Our model predicts a negligible change in both consumer out-of-pocket spending and Medicaid expenditures. Read more below
  • Employer mandates have been tried in only two states; estimates from the literature are sensitive to the design of the mandate. Read more below

Using our model, we estimate that aggregate health care spending will increase $890 million to $2.01 billion (which is less than 0.1 percent of total spending), depending on the design of the employer mandate.

Employer mandates would not create a discernible change in aggregate national health expenditures. The magnitude of the effect will depend on the design of the policy option, but in all of our modeled estimates, this effect is indistinguishable from no change in spending.

We modeled an employer mandate with the following design:

  • The mandate is not combined with any other policy changes.
  • Firms above a certain size are required to offer health insurance to their workers. We considered three different minimum firm sizes: 5, 10, and 25 workers.
  • Firms that do not offer health insurance are subject to a penalty, which is calculated as a percentage of payroll. We considered three penalty levels: 5, 10, and 20 percent (about 50 percent of firms that currently offer insurance spend more than 11 percent of payroll on health care).
  • We allowed people currently on Medicaid or who are purchasing non-group policies to switch to employer sponsored coverage.
  • We did not use the revenues generated by the penalty to fund other policy options, such as subsidizing premiums for low income workers in firms that are newly offering coverage.

We made the following assumptions in modeling the employer mandate:

  • Firms that newly offer insurance will include plans that have the same actuarial values as plans from similar firms that already offer coverage.
  • Newly offering firms will use the same eligibility rules of firms that currently offer insurance (about 80 percent of workers will be eligible for the insurance offer).
  • Firms that newly offer insurance will provide the same level of premium cost sharing as similar firms that already offer insurance.
  • The take-up, or participation, rate among workers who are newly offered insurance is the same as the take-up rate among similar workers in similar firms who already have an insurance offer.
  • Firms will offer insurance in response to the mandate if the cost of providing coverage is equal to or less than the value of insurance to the workers (the penalty is included in the cost calculation). The value of insurance to workers is calculated using a regression model that is estimated based on our simulated status quo population.

Table 1 shows the results of our modeling on changes in aggregate health spending that would occur under an employer mandate, comparing the three minimum firm sizes.

Table 1

Category of Spending Minimum Firm Size
25 workers 10 workers 5 workers
Change in national health spending due to increased utilization ($billion) $0.89 $1.52 $2.01

SOURCE: RAND COMPARE microsimulation modeling results, December 30, 2008.

Overall, a stand-alone employer mandate with a penalty of 5 percent of payroll for failure to offer insurance would lead to negligible changes in aggregate national health expenditures ($890 million to $2.01 billion) because relatively few people would newly acquire insurance under this policy change. We tested the sensitivity of these findings to the size of the penalty and found that, with a 10 percent penalty, aggregate spending would increase $1.24 billion to $3.1 billion, reflecting the larger number of firms that choose to offer insurance in the face of a higher penalty. Although we also tested a 20 percent penalty, which would increase spending from $1.8 billion to $4.47 billion, we believe this option is politically infeasible and does not alter our conclusion that an employer mandate has no effect on aggregate spending.

From our model, we estimate that firms newly offering coverage will spend $9.12 billion to $17.89 billion on premium contributions, and penalty payments will be $4.23 billion to $12.48 billion.

The largest effect of an employer mandate will be on the firms that are subject to the mandate (Table 2). Among those firms that choose to offer insurance, we estimate that total premium payments will be $9.12 billion to $17.89 billion (an increase of 1.3 to 2.5 percent). Among firms that elect to pay the penalty, revenue generated will be $4.23 billion to $12.48 billion. Our analysis does not include any specific use for the revenues generated by the penalty.

Table 2: Effect of an Employer Mandate with a 5 Percent Payroll Penalty on Premium Expenditures and Penalty Payments Among Affected Firms, by Minimum Firm Size

Category of Spending Minimum Firm Size
25 workers 10 workers 5 workers
Change in premium contributions among firms newly offering insurance ($billion) $9.12 $13.52 $17.89
Penalty payments by firms not offering insurance ($billion) $4.23 $7.67 $12.48

SOURCE: RAND COMPARE microsimulation modeling results, December 30, 2008.

Our model does not estimate future labor market effects that might result from an employer mandate. Research on the labor market effects of providing employer sponsored health insurance suggests that the cost of providing coverage would be passed on to employees in affected firms in the form of a reduction in future wages (Klerman and Goldman, 1994). Employers might also take steps to avoid the mandate, such as hiring more temporary workers (who might be exempt from the mandate) or reducing employment levels to qualify for an exemption. Previous health insurance policy changes targeted at small businesses had the effect of influencing firm size; businesses essentially grew in order to avoid regulation (Kapur et al., 2006). Although the long term consequences for the labor market of a health insurance mandate are uncertain, shifts in firm size and tactics used to avoid the mandate would further weaken this policy option's effect.

Our model predicts a negligible change in both consumer out-of-pocket spending and Medicaid expenditures.

Table 3 shows estimates from our model for the changes in Medicaid expenditures and government cost per net newly insured that result from an employer mandate.

Table 3: Effect of an Employer Mandate with a 5 Percent Payroll Penalty on Medicaid Spending and Government Cost Per Net Newly Insured Person, by Minimum Firm Size

Category of Spending Minimum Firm Size
25 workers 10 workers 5 workers
Change in Medicaid spending ($billion) ($1.5) ($2.7) ($2.7)
Government spending per net newly insured person ($) ($800-$1,000) ($800-$1,000) ($800-$1,000)

SOURCE: RAND COMPARE microsimulation modeling results, December 30, 2008. NOTE: Dollar amounts in parentheses represent reductions in spending.

We found reductions in out-of-pocket spending that were close to zero (results not shown) and reflect offsetting effects of the decrease in premium payments among those switching from non-group insurance to group insurance and the increase in premium payments for those switching from Medicaid to group insurance and those becoming newly insured.

The reductions in Medicaid spending of $1.5 billion to $2.7 billion (0.5 to 0.8 percent) are a result of 550,000 to 890,000 people who switch from Medicaid to group (employer sponsored) insurance.

We also calculated the government spending per net newly insured person and found a small savings, shown as a range in Table 3, which can be explained by the reduction in Medicaid costs.

Employer mandates have been tried in only two states; estimates from the literature are sensitive to the design of the mandate.

Until recently, Hawaii was the only state that had enacted an employer health insurance mandate. Hawaii's law, which was adopted in 1974, requires employers to offer health insurance to all employees working 20 hours per week or more (Oliver, 2004). Employers are required to pay at least 50 percent of the premium, and employees cannot be required to pay more than 1.5 percent of wages toward their premium. Employers can opt to offer a more generous plan that does not include an employer contribution for dependent coverage or a less generous plan that requires a 50 percent contribution for dependent coverage.

In 2006, Massachusetts passed a comprehensive bill aimed at providing universal coverage for residents of the state. The law combines many policies, including Medicaid expansions, the creation of a state sponsored purchasing pool, and an individual mandate (McDonough et al., 2006). The policy change also includes employer provisions that may be considered a mandate. Employers with more than ten employees must either make a "fair and reasonable" contribution to their employees' insurance (defined as one-third of the cost of coverage) or pay a fee called a Fair Share Contribution (in 2007, $295 per employee annually) (Gabel, Whitmore, Pickreign, 2008). This provision was not framed as a pay-or-play policy but resembles one.

Given that employer mandates have been implemented in only two states and that the Massachusetts mandate went into effect only recently, there is very little empirical evidence regarding the effects of such policies on spending. Therefore, much of the evidence on the effects of employer mandates is based on simulation models (Zedlewski, Acs, and Winterbottom, 1992; Burkhauser and Simon, 2007; Lambrew and Gruber, 2006/2007). The design of these simulation models and the policies that have been evaluated vary widely, making direct comparisons between these and the COMPARE results difficult. Burkhauser and Simon (2007) focused on the distributional effects of employer mandates and found that those most likely to benefit from this policy change have incomes that are 200 percent of the federal poverty level (FPL) or higher. They do not provide estimates of the effect of an employer mandate on spending. Lambrew and Gruber (2006/2007) combined an employer mandate with Medicaid eligibility expansion, tax credits for low income persons, and access to a purchasing pool for small employers, estimating that federal costs will increase $64 billion to $116 billion (in 2003 dollars), depending on the generosity of the subsidy. Zedlewski and colleagues (1992) evaluated an employer mandate with a 7 or 9 percent payroll tax penalty, but they also included access to a public sponsored insurance plan (similar to a national insurance exchange). They predicted increased spending of $64.6 billion to $70.1 billion (in 1990 dollars), depending on the size of the penalty and whether premiums remained the same or increased.

References

Burkhauser RV, Simon KI, "Who Gets What from Employer Pay or Play Mandates?" Cambridge, Mass.: National Bureau of Economic Research, NBER Working Paper 13578, November 2007. As of November 7, 2008: http://www.nber.org/papers/w13578

Gabel JR, Whitmore H, Pickreign J, " Report from Massachusetts: Employers Largely Support Health Care Reform, and Few Signs of Crowd-Out Appear," Health Affairs, Web Exclusives [Epub November 14, 2007], Vol. 27, No. 1, January/February 2008, pp. w13–w23.

Kapur K, Karaca-Mandic P, Gates SM, Fulton B, Do Small Group Health Insurance Regulations Influence Small Business Growth? Santa Monica, Calif.: RAND Corporation, WR-351-ICJ, 2006. As of May 11, 2009: http://www.rand.org/pubs/working_papers/WR351/

Klerman JA, Goldman DP, "Job Loss Due to Health Insurance Mandates," Journal of the American Medical Association, Vol. 272, No. 7, August 17, 1994, pp. 552–556.

Lambrew JM, Gruber J, "Money and Mandates: Relative Effects of Key Policy Levers in Expanding Health Insurance Coverage to All Americans," Inquiry, Vol. 43, No. 4, Winter 2006/2007, pp. 333–344.

McDonough JE, Rosman B, Phelps F, Shannon M, "The Third Wave of Massachusetts Health Care Access Reform," Health Affairs [Epub September 14, 2006], Vol. 25, No. 6, November/December 2006, pp. w420–w431.

Oliver T, "State Employer Health Insurance Mandates: A Brief History," Oakland, Calif.: California HealthCare Foundation, March 2004. As of March 16, 2009: http://www.chcf.org/topics/healthinsurance/coverageexpansion/index.cfm?itemID=110242

Zedlewski SR, Acs GP, Winterbottom CW, "Pay-or-Play Employer Mandates: Potential Effects," Health Affairs, Vol. 11, No. 1, Spring 1992, pp. 62–83.

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Consumer Financial Risk

An employer mandate will not change the proportion of income spent on health care by the non-elderly population, but it will increase the proportion of income spent on health care among persons who are newly insured:

  • We estimate that there will be no change in the median percentage of income spent on health care by the non-elderly population as a result of an employer mandate because of the small number of people who would newly become insured. Read more below
  • From our model, we estimate that the median proportion of income spent on health care will increase among persons who are newly insured by this policy change, because they will pay a share of premiums and will have higher utilization. Read more below
  • We estimate that the proportion of newly insured families who spend more than 10 percent of their income on health care will increase substantially. Read more below

We estimate that there will be no change in the median percentage of income spent on health care by the non-elderly population as a result of an employer mandate because of the small number of people who would newly become insured.

As shown in Table 1, about half of the non-elderly spend more than 6 percent of their income on health care. This spending includes the employee share of premium costs (average: 16 percent for individuals and 26 percent for families), deductibles, copayments, and services that are not covered. After an employer mandate, we estimate no real change in the median percentage of income spent out of pocket in the overall non-elderly population. This is not surprising because we estimate that only 1.8 to 3.4 million people (3 to 5 percent of the non-elderly population) would become newly insured under this policy change.

Table 1: Median Percentage of Income Spent on Health Care by the Non-Elderly Before and After an Employer Mandate with a 5 Percent Penalty, by Minimum Firm Size

Median Percentage of Income Spent on Health Care Minimum Firm Size
25 workers 10 workers 5 workers
Before employer mandate 5.96 5.96 5.96
After employer mandate 5.94 5.93 5.94

SOURCE: RAND COMPARE microsimulation modeling results, December 30, 2008.

Another way of evaluating the effect of a policy change on households is to estimate the proportion that would be likely to spend more than 10 percent of their income on health care. There is no defined threshold for excessive spending on health care; however, 10 percent has been used by others to identify a level at which spending on other household needs (food, housing, transportation) may be threatened (Schoen et al., 2005). Table 2 shows that, for the general non-elderly population, the employer mandate does not affect the proportion of families likely to spend more than 10 percent of their income on health care.

Table 2: Proportion of Non-Elderly Families Spending More Than 10 Percent on Health Care Before and After an Employer Mandate with a 5 Percent Penalty, by Minimum Firm Size

Proportion Spending More Than 10 Percent of Income on Health Care Minimum Firm Size
25 workers 10 workers 5 workers
Before employer mandate 26.4 26.4 26.4
After employer mandate 26.2 26.2 26.1

SOURCE: RAND COMPARE microsimulation modeling results, December 30, 2008.

From our model, we estimate that the median proportion of income spent on health care will increase among persons who are newly insured by this policy change, because they will pay a share of premiums and will have higher utilization.

An employer mandate does not affect the overall estimate of consumer financial risk; however, among those who become newly insured, we estimate that the median percentage of income spent on health care will increase substantially (see Table 3). Before the policy change, half of the uninsured spent less than 2 percent of income on health care. For a family of four with an income of $21,200 (100 percent of the federal poverty level or FPL), this amounts to about $424 annually. After the policy change, about half of the newly insured will spend more than 7 percent on health care—about $1,484 annually for a family of four with an income of $21,200.

Table 3: Median Percentage of Income Spent on Health Care by the Newly Insured Before and After an Employer Mandate with a 5 Percent Penalty, by Minimum Firm Size

Median Percentage of Income Spent on Health Care Minimum Firm Size
25 workers 10 workers 5 workers
Before employer mandate 1.34 1.34 1.85
After employer mandate 7.67 6.93 7.37

SOURCE: RAND COMPARE microsimulation modeling results, December 30, 2008.

We estimate that the proportion of newly insured families who spend more than 10 percent of their income on health care will increase substantially.

As shown in Table 4, the newly insured are also much more likely under the policy change to spend more than 10 percent of their income on health care. For a family of four with an annual income of $21,200, this would mean spending more than $2,120 annually on a combination of premiums, deductibles, copayments, and services that are not covered. We estimate that, after the policy change, about 80 percent of such spending will be attributable to the premium share. Based on the Kaiser Family Foundation and the Health Research and Educational Trust (2008) survey, family premiums for employer sponsored coverage averaged $12,680 annually, of which families paid an average of $3,354, or about 26 percent of income for a family of four at 100 percent of FPL.

Table 4: Proportion of Newly Insured Families Spending More Than 10 Percent on Health Care Before and After an Employer Mandate with a 5 Percent Penalty, by Minimum Firm Size

Proportion Spending More Than 10 Percent of Income on Health Care Minimum Firm Size
25 workers 10 workers 5 workers
Before employer mandate 20.4 18.1 18.6
After employer mandate 64.6 66.2 73.4

SOURCE: RAND COMPARE microsimulation modeling results, December 30, 2008.

These findings underscore the reason that previous modeling efforts almost always included some type of subsidy in combination with an employer mandate. Such a subsidy would decrease the burden on consumers, particularly those with incomes at the lower end of the income distribution. However, to fund the publicly provided subsidies, revenue must be raised from some source (e.g., income taxes).

References

Kaiser Family Foundation and Health Research and Educational Trust, Employer Health Benefits: 2008 Summary of Findings, Menlo Park, Calif.: Kaiser Family Foundation, 2008. As of January 5, 2009: http://ehbs.kff.org/images/abstract/7791.pdf

Schoen C, Doty MM, Collins SR, Holmgren AL, "Insured But Not Protected: How Many Adults Are Underinsured?" Health Affairs, Web Exclusives, July 14, 2005, pp. w5289–w5302.

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Waste

An employer mandate will have no effect on waste because of the small number of people who would newly become insured:

  • No empirical studies directly evaluate the relationship between employer mandates and waste, and related evidence is mixed. Read more below
  • From our model estimates, which show only a small decrease in the number of uninsured persons, we conclude that employer mandates will have no effect on waste. Read more below

No empirical studies directly evaluate the relationship between employer mandates and waste, and related evidence is mixed.

No empirical studies directly examine whether decreasing the number of the uninsured would reduce waste, and empirical studies are mixed in their assessment of the utilization patterns of the uninsured in costly settings, such as the emergency department (ED). Walls, Rhodes, and Kennedy (2002) found that lack of insurance predicted ED use as a patient's usual source of care, whereas Begley et al. (2006) found that primary care related ED use was strongly associated with uninsurance and poverty. Billings, Parikh, and Mijanovich (2000) found that self-pay and Medicaid insured children in New York City were more likely to use the ED for non-emergent and primary care treatable conditions than commercially insured children. Self-pay adults, however, used the ED for such conditions at approximately the same rate as those who were commercially insured, and less than those with Medicaid. Other studies have pointed out that, although the uninsured may use the emergency room more for primary care, the number of ED visits among the uninsured is not greater overall than that among the insured (Hunt, 2006; Cunningham, 2006b; Weber et al., 2005; Cunningham and May, 2003).

Some studies have concluded, based on cross-sectional comparisons, that if an uninsured person gets access to insurance, inappropriate ED use might decrease. For example, Cunningham and Hadley (2004) found that communities with higher insurance rates had lower use of hospital EDs, and Cunningham (2006a) found that a decrease in Medicaid/State Children's Health Insurance Program (SCHIP) enrollment would lead to an increase in ED visits by the uninsured. Johnson and Rimsza (2004) found that uninsured children were substantially more likely to use the ED than insured children, but that increased access to pediatric care was associated with a decrease in ED use regardless of insurance status. In contrast, Kwack et al. (2004) did not find any significant decrease in ED use after a group of uninsured patients was enrolled in a managed care plan.

Regarding whether insurance status affects administrative burden, Friedman et al. (2004) found that hospital profitability for the uninsured was 9 percent lower than for privately insured individuals. Medicaid patients, however, were 14 percent less profitable than privately insured patients. Anecdotal experience discussed in a report by the Healthcare Financial Management Association and ARC Group Associates (2006) suggests that collections on self-pay claims are more expensive than collections for Medicaid, Medicare, or private insurance.

From our model estimates, which show only a small decrease in the number of uninsured persons, we conclude that employer mandates will have no effect on waste.

We estimate that an employer mandate would newly cover 1.8 to 3.4 million persons, less than 1 percent of the U.S. population. This level of change is unlikely to lead to a major change in the amount of waste in the U.S. health care system. Further, the empirical literature does not provide a strong evidence base from which to conclude that an employer mandate would have any discernible effect on waste.

References

Begley CE, Vojvodic, RW, Seo M, Burau K, "Emergency Use and Access to Primary Care: Evidence from Houston, Texas," Journal of Health Care for the Poor and Underserved, Vol. 17, No. 3, August 2006, pp. 610–624.

Billings J, Parikh N, Mijanovich T, Emergency Room Use: The New York Story, New York, N.Y.: The Commonwealth Fund, Issue Brief #434, November 2000.

Cunningham PJ, "Medicaid/SCHIP Cuts and Hospital Emergency Department Use," Health Affairs, Vol. 25, No. 1, January/February 2006a, pp. 237–247.

Cunningham PJ, "What Accounts for Differences in the Use of Hospital Emergency Departments Across U.S. Communities?" Health Affairs, Web Exclusives [Epub July 18, 2006], Vol. 25, No. 5, September/October 2006b, pp. w324–w336.

Cunningham P, Hadley J, "Expanding Care Versus Expanding Coverage: How to Improve Access to Care," Health Affairs, Vol. 23, No. 4, July/August 2004, pp. 234–244.

Cunningham PJ, May JH, Insured Americans Drive Surge in Emergency Department Visits, Washington, D.C.: Center for Studying Health Systems Change, Issue Brief No. 70, October 2003, pp. 1–6.

Friedman B, Sood N, Engstrom K, MacKenzie D, "New Evidence on Hospital Profitability by Payer Group and the Effects of Payer Generosity," International Journal of Health Care Finance & Economics, Vol. 4, No. 3, November 29, 2004, pp. 231–246.

Healthcare Financial Management Association and ARC Group Associates, Understanding Your True Cost to Collect, Westchester, Ill., January 2006. As of May 12, 2009: http://www.hfma.org/library/revenue/billing/Understanding_True_Cost_Collect.htm

Hunt KA, "Characteristics of Frequent Users of Emergency Departments," Annals of Emergency Medicine [Epub March 30, 2006], Vol. 48, No. 1, July 2006, pp. 1–8.

Johnson WG, Rimsza ME, "The Effects of Access to Pediatric Care and Insurance Coverage on Emergency Department Utilization," Pediatrics, Vol. 113, No. 3, March 2004, pp. 483–487.

Kwack H, Sklar D, Skipper B, Kaufman A, Fingado E, Hauswald M, "The Effect of Managed Care on Emergency Department Use in an Uninsured Population," Annals of Emergency Medicine, Vol. 43, No. 2, February 2004, pp. 166–173.

Walls CA, Rhodes KV, Kennedy JJ, "The Emergency Department as Usual Source of Medical Care: Estimates from the 1998 National Health Interview Survey," Academic Emergency Medicine, Vol. 9, No. 11, November 2002, pp. 1140–1145.

Weber EJ, Showstack JA, Hunt KA, Colby DC, Callaham ML, "Does Lack of a Usual Source of Care or Health Insurance Increase the Likelihood of an Emergency Department Visit? Results of a National Population Based Study," Annals of Emergency Medicine [Epub October 24, 2004], Vol. 45, No. 1, January 2005, pp. 4–12.

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Reliability

An employer mandate will have no effect on reliability, given the small number of people who would be newly insured under this policy change.

  • In view of our model estimates of the number of people newly insured under an employer mandate and the mixed evidence in the literature, we do not expect to see an effect on reliability. Read more below

In view of our model estimates of the number of people newly insured under an employer mandate and the mixed evidence in the literature, we do not expect to see an effect on reliability.

There are two ways to consider the effect of an employer mandate on reliability—that is, on the likelihood that patients will receive necessary care. The first is whether the policy change directly affects the way the health care delivery system functions. The second is whether individuals who become newly insured are more likely to receive appropriate services.

Regarding the heath care delivery system perspective, we have no evidence to suggest that an employer mandate will affect the way health services are delivered. Our estimates suggest that a relatively small number of people will become newly insured under this policy change (1.8 to 3.4 million, or less than 1 percent of the U.S. population), making it extremely unlikely that the system would change significantly.

For individuals who obtain insurance under this policy, the likelihood that they will receive appropriate care may increase, although the evidence for this possibility is mixed. Some evidence suggests that health insurance improves access to care and quality of care. Several studies have found substantial differences in quality measures between uninsured and insured populations. Ayanian et al. (2000) found that uninsured adults were less likely to see a physician when needed. Ross, Bradley, and Busch (2006) found that the uninsured used fewer recommended health services. Buchmueller and colleagues' (2005) review suggests that utilization for all types of services increases when coverage is expanded. There is also evidence that expanding insurance reduces avoidable hospitalizations for children (Buchmueller et al., 2005).

For those services for which access is the primary determinant of the likelihood that appropriate care will be delivered, such as screening or preventive care, improved access may increase the reliability of care for the individual. However, strong evidence suggests that the health care system has significant deficiencies experienced by everyone who seeks health care, and there is no reason to believe that newly insured individuals will not experience those same deficiencies. The most comprehensive study of health care quality in the United States found that, among those with at least one visit in two years, everyone was at risk for poor quality care (Asch et al., 2006). Leape et al. (1999) found no overall differences in underuse of coronary revascularization between uninsured and insured people. Young et al. (2001) found that "insurance and income had no effect on receipt of appropriate care for depressive and anxiety disorders." Harman, Edlund, and Fortney (2004) found disparities in initiation of depression treatment between the uninsured and the insured, but no differences in quality of care once treatment was initiated.

We do not know how the reliability of care for individuals who were previously uninsured will change when they acquire insurance; reliability will depend on their health care needs, their own care-seeking behavior before and after the change in insurance status, and the quality of care delivered in the places they go for care.

References

Asch SM, Kerr EA, Keesey J, Adams JL, Setodji CM, Malik S, McGlynn EA, "Who Is at Greatest Risk for Receiving Poor-Quality Health Care? New England Journal of Medicine, Vol. 354, No. 11, March 16, 2006, pp. 1147–1156.

Ayanian JZ, Weissman JS, Schneider EC, Ginsburg JA, Zaslavsky AM, "Unmet Health Needs of Uninsured Adults in the United States," Journal of the American Medical Association, Vol. 284, No. 16, October 25, 2000, pp. 2061–2069.

Buchmueller TC, Grumbach K, Kronick R, Kahn JG, "The Effect of Health Insurance on Medical Care Utilization and Implications for Insurance Expansion: A Review of the Literature," Medical Care Research and Review, Vol. 62, No. 1, February 1, 2005, pp. 3–30.

Harman JS, Edlund MJ, Fortney JC, "Disparities in the Adequacy of Depression Treatment in the United States," Psychiatric Services, Vol. 55, No. 12, December 2004, pp. 1379–1385.

Leape LL, Hilborne LH, Bell R, Kamberg C, Brook RH, "Underuse of Cardiac Procedures: Do Women, Ethnic Minorities, and the Uninsured Fail to Receive Needed Revascularization?" Annals of Internal Medicine, Vol. 130, No. 3, February 2, 1999, pp. 183–192.

Ross JS, Bradley EH, Busch SH, "Use of Health Care Services by Lower-Income and Higher-Income Uninsured Adults," Journal of the American Medical Association, Vol. 295, No. 17, May 3, 2006, pp. 2027–2036.

Young AS, Klap R, Sherbourne CD, Wells KB, "The Quality of Care for Depressive and Anxiety Disorders in the United States," Archives of General Psychiatry, Vol. 58, January 2001, pp. 55–61.

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Patient Experience

The existing literature provides some evidence that, because the uninsured encounter difficulty in obtaining care, the newly insured might have a better experience with care than they previously did:

  • No empirical studies directly analyze the relationship between an employer mandate and changes in patient experience. Read more below
  • Theory suggests that the patient experience of formerly uninsured individuals will improve if those individuals acquire insurance. Read more below

No empirical studies directly analyze the relationship between an employer mandate and changes in patient experience.

We do not have much systematic information about patient experiences among the uninsured: Most of the routine measurements of patient experience are conducted among those with insurance (private, Medicaid, Medicare). We also do not know how patients' experiences change when they go from being uninsured to being insured. Nor do we know whether patients who newly acquire insurance are likely to change the places they go for care and thus may have a different experience than when they were uninsured. Given the small number of people who newly acquire insurance under the employer mandate option, we would not expect to see major aggregate differences in patient experience before and after the policy change.

Theory suggests that the patient experience of formerly uninsured individuals will improve if those individuals acquire insurance.

The uninsured population encounters considerable difficulties in both access to and continuity of care. To the extent that this policy option would allow people to move from being uninsured to having insurance, we expect that the patient experience will improve as people have greater access to care and are able to develop relationships with primary care physicians. Those who had coverage prior to the policy change may not see any change in patient experience.

The effect of this policy on patient experience may be somewhat tempered by the ability of the newly insured to obtain care. The individuals who obtain insurance under the policy we modeled have lower incomes and may live and work in areas with limited capacity. The policy option could result in people obtaining insurance but not gaining better access to care, resulting in patient experience that is poor.

This policy change would also affect people who were previously purchasing insurance in the non-group market and who now would have some portion of their premium costs paid by their employer. They would be unlikely to dramatically change the places they go for care. So we would expect that their experiences with financial aspects of care improve but that they would see little or no change in other dimensions of patient experience.

Information from the existing literature provides some evidence that the newly insured might have better experience with care than they formerly had. Multiple studies confirm that people without insurance have more negative experiences of care than do those with insurance. Schoen and DesRoches (2000) compared the experience of the continuously insured population with that of the uninsured and the discontinuously insured. The authors found that those individuals who experienced a gap in coverage and uninsured individuals were at higher risk of going without needed care and of having problems paying medical bills, and that they rated care more negatively than those with continuous insurance. Schoen et al. (1997) compared low income uninsured adults with those with public or private coverage and found that the uninsured were less likely to have a regular provider and rated care more negatively than those with insurance. Newacheck, Hughes, and Stoddard (1996) found that uninsured children were twice as likely to lack a usual source of care and twice as likely to wait 60 minutes or more for a health care visit than were insured children. Zyzanski et al. (1998) found that high volume providers suffered from "lower rates of preventive services delivery, lower patient satisfaction, and a less positive doctor-patient relationship."

References

Newacheck PW, Hughes DC, Stoddard JJ, "Children's Access to Primary Care: Difference by Race, Income and Insurance Status," Pediatrics, Vol. 97, No. 1, January 1996, pp. 26–32.

Schoen C, DesRoches C, "Uninsured and Unstably Insured: The Importance of Continuous Coverage," Health Services Research, Vol. 35, No. 1, Pt. 2, April 2000, pp. 187–206.

Schoen C, Lyons B, Rowland D, Davis K, Puleo E, "Insurance Matters for Low-Income Adults: Results from a Five-State Survey," Health Affairs, Vol. 16, No. 5, September/October 1997, pp. 163–171.

Zyzanski SJ, Stange KC, Langa D, Flock SA, "Trade-Offs in High Volume Primary Care Practice," Journal of Family Practice, Vol. 46, No. 5, May 1998, pp. 397–402.

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Health

We estimate a small gain in life years among those newly insured under an employer mandate:

  • We estimate an increase of 220,000 to 400,000 life years, depending on the design of the employer mandate. Read more below
  • Theory and published studies suggest that, if an employer mandate increases rates of coverage, the health of some groups should improve. Read more below
  • The magnitude of the effect on health may depend on the health of an individual before gaining insurance and on other socioeconomic factors, as well as on changes in access afforded by health insurance and the reliability of care received. Read more below

We estimate an increase of 220,000 to 400,000 life years, depending on the design of the employer mandate.

We modeled a stand-alone policy that required employers to offer health insurance to their employees. The two key design variables that we used to estimate the effect of the policy were the minimum firm size of an employer that would be targeted by the mandate (5, 10, or 25 workers) and the size of the penalty for not offering insurance (5, 10, or 20 percent of payroll). The policy change does not substantially increase the number of people with insurance (range: 1.8 to 3.4 million); thus, all other effects on the system are likely to be small. We estimate that this policy would result in an increase in total life years of 220,000 to 400,000 annually (see the table).

Expected Total Gains in Life Years with an Employer Mandate with a 5 Percent Penalty for Not Providing Insurance

Change in Life Years Attributable to Policy Minimum Firm Size
25 workers 10 workers 5 workers
Millions of life years 0.22 0.31 0.40

SOURCE: RAND COMPARE modification of Future Elderly Model, December 30, 2008.

We assumed that individuals who obtain coverage under this policy option would retain that coverage continuously until they become eligible for Medicare at age 65. We further assumed that those who obtain insurance would experience a change from the expected mortality rate observed for the uninsured to the expected mortality rate observed for the insured. We observed no difference in mortality among the population over age 65 based on their insurance status prior to becoming eligible for Medicare; therefore, we assumed that all of the effect of becoming newly insured occurs between becoming insured and age 65, a mortality difference of 9.06 percent. We assumed that there are no changes in rates of treatment or in the effectiveness with which medical care is delivered as a result of this policy change.

The results presented here are based on microsimulation analyses, which use what is known from the literature about the relationship between health (in this case, mortality rates) and insurance to estimate the effect of a policy change. However, published studies to date are generally cross-sectional comparisons, and we have no experimental or longitudinal data on which to estimate how a change in insurance status affects a population of individuals.

Theory and published studies suggest that, if an employer mandate increases rates of coverage, the health of some groups should improve.

Consistent with our modeling results, the literature suggests that there may be a modest relationship between insurance status and health outcomes, but methodological issues have made it difficult to make an accurate quantitative estimate. The RAND Health Insurance Experiment (Newhouse and Insurance Experiment Group, 1993) randomly assigned families to health plans, providing an opportunity to assess how benefit generosity affected health outcomes in a setting in which health was unrelated to insurance choice. Overall, the study found that benefit generosity had a negligible influence on health outcomes for the general population, although there were some benefits for low income participants who were in poor health at the beginning of the study. However, since everyone in the RAND Health Insurance Experiment had at least minimal health coverage, that population cannot necessarily be used to gauge the effect of becoming insured.

Levy and Meltzer (2008) reviewed the literature on the relationship between health insurance and health and drew several conclusions. First, most studies were not able to establish a causal relationship between health insurance and health because they did not account for the multiple other factors that affect these two variables or the fact that health itself affects insurance status. Second, there is substantial evidence that health insurance improves health in vulnerable populations, such as infants, children, individuals with HIV, and some low income adults, but there is less evidence of this relationship for other groups. Finally, Levy and Meltzer suggest that it may be difficult to generalize the results of the studies thus far.

Hadley (2003) reviewed the literature from the past 25 years on this subject and found that the general consensus among studies was that providing the uninsured with health insurance would result in improved health. Hadley's "best guess" is that mortality would decrease between 4 and 25 percent for previously uninsured people. Our modeled estimate of 9.06 percent is contained within this range. Although Hadley cites methodological difficulties within these studies, he acknowledges the consistency in the findings of improved health with insurance in many populations and disease states.

The magnitude of the effect on health may depend on the health of an individual before gaining insurance and on other socioeconomic factors, as well as on changes in access afforded by health insurance and the reliability of care received.

Medical care represents only one of the many determinants of health (others being behavior, socioeconomic status, education, and genetics, for example); consequently, improved access to medical care via insurance changes may have only a modest effect on health. McGinnis, Williams-Russo, and Knickman (2002) suggest that only 10 to 15 percent of preventable deaths are attributable to problems with medical care. In addition, there are other important determinants of access apart from health insurance coverage.

Estimating how insurance affects health poses significant methodological challenges. In particular, insurance status and health are not independent; that is, health can directly affect the ability or desire to obtain coverage. Healthy people may be less likely to purchase insurance because they anticipate having minimal health expenditures. Sick individuals may be unable to purchase individual policies. Other unobservable characteristics may also influence both health and insurance status. Thus, when researchers attempt to study differences in health based on health insurance status, it can be difficult to discern whether having insurance really causes improved health.

References

Buchmueller TC, Grumbach K, Kronick R, Kahn JG, "The Effect of Health Insurance on Medical Care Utilization and Implications for Insurance Expansion: A Review of the Literature," Medical Care Research and Review, Vol. 62, No. 1, February 1, 2005, pp. 3–30.

Hadley J, "Sicker and Poorer—The Consequences of Being Uninsured: A Review of the Research on the Relationship Between Health Insurance, Medical Care Use, Health, Work, and Income," Medical Care Research and Review, Vol. 60, No. 2 Suppl, June 1, 2003, pp. 3S–75S.

Levy H, Meltzer D, "The Impact of Health Insurance on Health," Annual Review of Public Health, Vol. 29, April 2008, pp. 399–409.

McGinnis JM, Williams-Russo P, Knickman JR, "The Case for More Active Policy Attention to Health Promotion," Health Affairs, Vol. 21, No. 2, March/April 2002, pp. 78–93.

Newhouse JP, Insurance Experiment Group, Free for All? Lessons from the RAND Health Insurance Experiment, Cambridge, Mass.: Harvard University Press, 1993.

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Coverage

Using our model, we estimate a small increase in the number of people who become newly insured as a result of this policy change:

  • We estimate that 1.8 to 3.4 million people would become newly insured under the stand-alone employer mandate option we modeled. Read more below
  • Published estimates of the magnitude of the increase vary widely and depend on assumptions about the design of the mandate. Read more below

We estimate that 1.8 to 3.4 million people would become newly insured under the stand-alone employer mandate option we modeled.

Employer mandates would lead to a small increase in the number of people with insurance. The magnitude of the effect will depend on the design of the policy option.

We modeled an employer mandate with the following design:

  • The mandate is not combined with any other policy changes.
  • Firms above a certain size are required to offer health insurance to their workers. We considered three different minimum firm sizes: 5, 10, and 25 workers.
  • Firms that do not offer health insurance are subject to a penalty that is calculated as a percentage of payroll. We considered three penalty levels: 5, 10, and 20 percent (about 50 percent of firms that currently offer insurance spend more than 11 percent of payroll on health care).
  • We allowed people currently on Medicaid or who are purchasing non-group policies to switch to employer sponsored coverage.
  • We did not use the revenues generated by the penalty to fund other policy options, such as subsidizing premiums for low income workers in firms that are newly offering coverage.

We made the following assumptions in modeling the employer mandate:

  • Firms that newly offer insurance will offer plans that have the same actuarial values as plans offered by similar firms that already offer coverage.
  • Newly offering firms will use the same eligibility rules used by firms that currently offer insurance (about 80 percent of workers will be eligible for the insurance offer).
  • Firms that newly offer insurance will provide the same level of premium cost sharing as similar firms that already offer insurance.
  • The take-up, or participation, rate among workers who are newly offered insurance is the same as the take-up rate among similar workers in similar firms who already have an insurance offer.
  • Firms will offer insurance in response to the mandate if the cost of providing coverage is equal to or less than the value of insurance to the workers (the penalty is included in the cost calculation). The value of insurance to workers is calculated with a regression model that is estimated using our simulated status quo population.

Table 1 shows the results of our modeling on changes in coverage that would occur under an employer mandate, comparing three minimum firm sizes.

Table 1: Changes in Coverage Resulting from an Employer Mandate with a 5 Percent Penalty for Not Offering Insurance, by Minimum Firm Size

Coverage Changes (in millions) Minimum Firm Size
25 workers 10 workers 5 workers
Newly insured 1.8 2.7 3.4
Switch from non-group to group 0.6 0.9 1.3
Switch from Medicaid to group 0.6 0.8 0.9

SOURCE: COMPARE microsimulation modeling results, December 30, 2008.

Requiring employers to offer coverage will result in both a small reduction in the number of people without insurance and a change from non-group or Medicaid coverage to the newly offered employer coverage.

The relatively small effect of this policy is a function of the number of firms that choose to offer insurance, the small number of people who lack insurance in those firms, and the assumption made in our model that the take-up rate among those who are newly offered insurance would be similar to that observed in our simulated status quo. We tested our results' sensitivity to the size of the penalty and found that, if the penalty for not providing coverage was 10 percent of payroll, the number of those newly insured would be 2.4 to 5.1 million. Table 2 shows the maximum number of workers and dependents who could benefit from this policy change.

Table 2: Maximum Number of Persons Who Could Benefit from an Employer Mandate, by Minimum Firm Size

Category of Target Population (in millions) Minimum Firm Size
25 workers 10 workers 5 workers
Workers newly offered insurance and their dependents 7.7 11.5 15.5
Workers newly offered insurance and their dependents without access to group insurance 4.4 6.5 8.9
Workers newly offered insurance and their dependents who are currently uninsured 2.5 3.8 5.2
Workers newly offered insurance and their dependents who are on Medicaid 1.1 1.6 2.0

SOURCE: COMPARE microsimulation modeling results, December 30, 2008.

We found that an employer mandate would extend offers of employer sponsored insurance to about 8 to 15 million persons (about 17 to 33 percent of the uninsured). Among those with a new employer offer, about 43 percent currently have access to group insurance, generally through a spouse. Among those with new offers of insurance, only about one-third are currently uninsured (about 5 to 11 percent of the uninsured).

This finding is sensitive to the firm behavior that we model. An additional 10 to 26 million workers and dependents are in firms that choose, in our model, to pay a penalty rather than offer insurance. A similar proportion of workers and dependents in these firms (43 percent) already have access to group insurance. If the penalty were increased to 10 percent, almost twice as many firms with 5 or more employees would elect to offer coverage rather than pay the penalty. Unlike some other analysts, we do not include in our model the use of the revenue generated by the penalty to provide subsidies to those individuals whose firms do not offer coverage; the availability of subsidies would likely increase the number of people covered under this policy option.

Published estimates of the magnitude of the increase in coverage vary widely and depend on assumptions about the design of the mandate.

Previous literature supports our finding that employer mandates are not expected to have a large effect on health insurance because employers that do not offer health insurance tend to be small (Claxton et al., 2007), and small businesses are typically exempted from proposals for employer health insurance mandates.

The employer mandate in the state of Hawaii, which requires that employers offer health insurance but does not require workers to enroll, has been only partially successful in reducing the number of people without insurance. In 2006, 10 percent of the non-elderly population in Hawaii was uninsured. Hawaii's uninsurance rate is low relative to the national average of 18 percent; however, it is comparable to uninsurance rates in several states without employer mandates, including Pennsylvania, Minnesota, and Wisconsin (see The Henry J. Kaiser Family Foundation and StateHealthFacts.org, not dated).

The experience in Massachusetts with the comprehensive coverage policy may be too new to completely evaluate, but an early report suggests that, whereas employers in Massachusetts are more likely than those nationally to offer insurance (73 percent versus 60 percent), the proportion of employees who have employer based coverage is similar (57 percent in Massachusetts compared with 59 percent nationally) (Gabel, Whitmore, and Pickreign, 2008). The authors attribute this discrepancy to a lower rate of take-up in Massachusetts, possibly due to higher than average premium prices in the state. As with Hawaii, Massachusetts had relatively low rates of uninsurance when the policy change was implemented.

Most estimates of the effect of an employer mandate come from microsimulation models developed by other researchers. The findings from those studies are difficult to compare with our results because of significant variability in the way the employer mandate is modeled. Most other studies evaluated a combined set of policies that include an employer mandate, but the overall effect is likely the result of other elements in the modeled options. As such, those studies find that employer mandates are more effective in reducing the rate of uninsurance than we do.

One study from the early 1990s evaluated an employer mandate coupled with a nationally available, publicly sponsored insurance plan with a substantial subsidy (Zedlewski, Acs, Winterbottom, 1992). This study found that 58 to 78 percent of the uninsured would be covered under the new public plan. Lambrew and Gruber (2006/2007) modeled an employer mandate with subsidies and access to a purchasing pool and found that the employer mandate reduced the number of uninsured by 75 to 82 percent, depending on the level of the subsidy. Most of the newly insured (73 percent) would elect employer sponsored coverage. Burkhauser and Simon (2007) modeled an employer mandate targeted at firms with at least 25 employees and designed around the New York State approach, which tied financial incentives to the hourly wages of workers. They also allocated the revenues generated through the penalty to providing insurance to workers in firms not offering coverage. They found that 46.2 percent of workers would receive employer sponsored insurance under the mandate, 46.05 percent would not have insurance because they were in firms excluded from the mandate, and 6.84 percent would have to pay the full premium for their insurance.

References

Burkhauser RV, Simon KI, "Who Gets What from Employer Pay or Play Mandates?" Cambridge, Mass.: National Bureau of Economic Research, Working Paper 13578, November 2007.

Claxton G, Gabel J, DiJulio B, Pickreign J, Whitmore H, Finder B, Jacobs P, Hawkins S, "Health Benefits in 2007: Premium Increases Fall to an Eight-Year Low, While Offer Rates and Enrollment Remain Stable," Health Affairs, Vol. 26, No. 5, September/October 2007, pp. 1407–1416.

Gabel JR, Whitmore H, Pickreign J, "Report from Massachusetts: Employers Largely Support Health Care Reform, and Few Signs of Crowd-Out Appear," Health Affairs, Web Exclusives [Epub November 14, 2007], Vol. 27, No. 1, January/February 2008, pp. w13–w23.

The Henry J. Kaiser Family Foundation and StateHealthFacts.org, Health Insurance Coverage of Nonelderly 0–64, States (2006–2007), U.S. (2007), Menlo Park, Calif.: The Henry J. Kaiser Family Foundation, not dated. As of May 13, 2009: http://www.statehealthfacts.org/comparebar.jsp?ind=126&cat=3

Lambrew JM, Gruber J, "Money and Mandates: Relative Effects of Key Policy Levers in Expanding Health Insurance Coverage to All Americans," Inquiry, Vol. 43, No. 4, Winter 2006/2007, pp. 333–344.

Zedlewski SR, Acs GP, Winterbottom CW, "Pay-or-Play Employer Mandates: Potential Effects," Health Affairs, Vol. 11, No. 1, Spring 1992, pp. 62–83.

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Capacity

An employer mandate is not expected to change the overall capacity of the health care system:

  • We would not expect this policy option to change the capacity of the overall health system because of the small number of people who become newly insured. Read more below
  • No empirical studies directly evaluate the effect of employer mandates on capacity. Read more below

We would not expect this policy option to change the capacity of the overall health system because of the small number of people who become newly insured.

Capacity refers to the human resources (personnel and their productivity) and capital (medical equipment, hospitals, etc.) of the health care system. There is no direct connection between the capacity of the health care system and coverage. Further, based on the design of the policy option we modeled, relatively few people would become newly insured, resulting in little change in the demand for services or in the amount of money available to pay for those services (see discussion under Coverage).

We estimated relatively small changes in the net number of newly insured people, so we do not expect that the resulting small changes in utilization will create a major change in market conditions. The size of any resulting change in utilization depends on assumptions about the extent to which demand for services will increase because of coverage, as well as the extent to which utilization patterns will change if formerly uninsured people substitute preventive, primary, and chronic care for acute care. We also assumed that the supply of health care resources would not adjust quickly to changes in demand.

We do not know whether any geographic areas will experience a significant change in market conditions based on significant local improvement in the proportion of people with insurance coverage whose utilization increases significantly. Nor do we know whether other trends in capacity (e.g., changes in availability of hospital supply, primary care physicians, retail clinics) will affect the ability of newly insured individuals to access care.

No empirical studies directly evaluate the effect of employer mandates on capacity.

Empirical evidence suggests that increased coverage leads to increased health care utilization, which could, in turn, affect capacity. Many studies have shown that uninsured people use fewer health care services than insured people, and that changes in coverage are associated with changes in health care utilization. Buchmueller et al.'s (2005) review suggests that utilization for all types of services increases when coverage is expanded. However, this review presents some evidence that expanding insurance reduces avoidable hospitalizations for children. The authors note that the effect of utilization may be overstated, since utilization will vary across subgroups. For example, if coverage is expanded primarily to young, healthy individuals, we would not expect a large increase in utilization.

References

Buchmueller TC, Grumbach K, Kronick R, Kahn JG, "The Effect of Health Insurance on Medical Care Utilization and Implications for Insurance Expansion: A Review of the Literature," Medical Care Research and Review, Vol. 62, No. 1, February 1, 2005, pp. 3–30.

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Operational Feasibility

An employer mandate to provide health insurance would present a moderate degree of challenge for implementation:

  • An employer health insurance mandate should be less burdensome to implement than other policy options since the most likely mechanism for implementation, the federal tax system, is already in place. Read more below
  • Enforcement of an employer mandate would require penalties for noncompliance as well as expansion and improvement of some mechanisms used to administer existing tax laws, which would add complexity and difficulty to implementation. Read more below
  • Previous experience with an employer mandate is limited and cannot be readily extrapolated to assess the operational feasibility of the mandate we modeled. Read more below

An employer health insurance mandate should be less burdensome to implement than some policy options since the most likely mechanism for implementation, the federal tax system, is already in place.

For several reasons, it is likely that an employer health insurance mandate would be administered through the federal tax system (Hevener and Kerby, 2008). First, options for implementing an employer mandate, including those we modeled, typically require employers that do not offer health insurance to pay a penalty to the government (which may be calculated as a percentage of payroll or as a flat fee per worker). This requirement is similar to employers' existing payroll tax obligations. Second, it is possible that an employer mandate would be accompanied by an individual mandate or subsidies to assist employees in purchasing insurance. To the extent that these options are also administered through the tax system, the argument for using the tax system to implement the employer mandate would be further strengthened. Finally, using the Internal Revenue Service (IRS) to administer the mandate would allow procedures to be used that are already familiar to employers and the IRS. As with tax law, the mandate would rely primarily on "voluntary compliance" by employers (which would provide information necessary to assess compliance) and monitoring and imposition of penalties by the IRS (which would implement penalties if noncompliance were detected).

In the remainder of this discussion, we will assume that the IRS will administer the mandate.

Use of resources and systems. An employer mandate administered through the federal tax system can make use of existing public (i.e., the IRS) and private (i.e., employer) resources and systems. Employers are currently required to withhold both income and payroll taxes from wages paid to employees, and to report information regarding wages and tax withholding to the IRS and to employees. Employers are also subject to both federal and state minimum wage requirements and other legal obligations regarding their employees, including contractual payroll obligations. By making use of resources and systems associated with these obligations, an employer mandate should be less burdensome to administer than health insurance policies involving entirely new institutional structures.

Costs. Using IRS and private taxpayer resources now devoted to the federal tax system, and building upon the experience gained with tax laws applicable to employers, should result in economies of scale and thereby minimize the cost of implementing the mandate. The mandate would, however, also impose new obligations on employers, which are discussed below.

Constitutionality. Some commentators have argued that the U.S. Constitution may bar the federal government from imposing an employer mandate (or an individual mandate) to purchase health insurance. Among the issues raised is whether the Constitution grants Congress the power to impose such a mandate. Congressional power to legislate must derive from one of the enumerated powers specified in the Constitution. Since the United States has never had a federal health insurance mandate, the courts, including the U.S. Supreme Court, have never directly addressed this issue (Hall, 2009). The legal analysis of this issue differs from the analysis of state legislative power to impose a mandate, which would arise under state constitutions and the states' broad "police powers."

The most extensive scholarly discussion to date of the constitutional issues raised by insurance mandates concluded that Congress would have the authority to impose an employer mandate under the Interstate Commerce Clause (Hall, 2009). If the employer mandate gives employers the alternative of paying a penalty, and if such penalties are enforced as tax obligations and administered by the IRS, the constitutionality of the mandate would also be supported by Congress's power of taxation. While Supreme Court decisions in the 1990s emphasized that congressional power under the Interstate Commerce Clause is not unlimited, in general, congressional powers have been broadly upheld under both the Commerce Clause and regarding the power of taxation (Hall, 2009).

Enforcement of an employer mandate would require penalties for noncompliance as well as expansion and improvement of some mechanisms used to administer existing tax laws, which would add complexity and difficulty to implementation.

Extent of employer compliance. The feasibility of an employer mandate depends in part on the extent to which employers would be willing to comply. Under the employer mandate option we modeled, employers would have the legal options of either providing insurance to their employees or paying a portion of payroll as penalty, as well as a third, illegal option of neither offering insurance nor paying a penalty.

Employers would be motivated to comply with an employer mandate to the extent that the costs of noncompliance, including penalties, exceed the costs of compliance. The costs of compliance depend on the net cost of the insurance to employers subject to the mandate and the administrative costs of compliance. The costs of noncompliance depend on the probability of detection and the penalties imposed if noncompliance is detected (Holtzblatt, 2008).

Higher penalties generally increase the likelihood of compliance (Glied, Hartz, and Giorgi, 2007). On the other hand, penalties that are too high may be perceived as meaningless. A key consideration in compliance is the likelihood that penalties will be imposed. Effective enforcement efforts combined with sufficiently large penalties will increase compliance. Ideally, the penalty should be large enough and enforcement should be effective enough to ensure high rates of voluntary compliance.

Employer reporting obligations. As noted above, taking advantage of resources already used to enforce compliance with existing tax laws can minimize the costs of enforcing the mandate. A part of the existing infrastructure is the reporting requirements for employers; reporting would have to be expanded to support the employer mandate, including:

  • whether the employer offers health insurance
  • whether the coverage offered satisfies the mandate (e.g., benefit package, employer share of premium)
  • the number and identity of employees not offered or not eligible for coverage (e.g., part-time)
  • the amount of payments necessary under the mandate in lieu of coverage (Hevener and Kerby, 2008).

A mandate might allow employers to satisfy their obligation by showing that an employee has health insurance from other sources. This would require employers to obtain such information from employees, and presumably both employers and the IRS would need to verify such information.

Verification of insurance coverage. The IRS would need to obtain information from insurance companies or, in the case of self-insured employees, plan administrators to verify that individuals have appropriate coverage. Massachusetts, which imposes an individual insurance mandate under health reform legislation enacted in 2006, addresses a similar problem by requiring health insurance providers to send information reports to insured individuals and the Massachusetts Department of Revenue annually. These reports state the name and identification number of the insurance company, as well as the names, subscriber numbers, dates of birth, and start and end dates of coverage for those covered under the policy (Holtzblatt, 2008). Coordinating information reporting from employers, employees, and insurance companies in this manner would, however, create new administrative responsibilities for the IRS.

Avoiding misuse of exemptions to the mandate. Employers may try to avoid compliance with the mandate by misusing exemptions provided under law. Employer mandate proposals usually provide exemptions for smaller and/or lower-wage employers, presumably because such employers may find it more difficult to purchase health insurance at a reasonable cost, because their employees may have lower wages (which are therefore unable to absorb the embedded cost of insurance), or both. For example, the employers' "Fair Share Contribution" rule adopted by Massachusetts exempts employers with ten or fewer employees (Gabel, Whitmoore, and Pickreign, 2008). Exemptions for smaller employers may generate incentives for employers above the compliance threshold to qualify by limiting the number of people they employ or their payroll size. In some cases, this may be accomplished by changing business structures (e.g., dividing one company into two separate companies). Rules to counter these strategies can be designed, but would add to complexity of administration and enforcement (Hevener and Kerby, 2008).

For similar reasons, imposition of an employer mandate would also increase incentives for employers to characterize workers as independent contractors rather than employees. According to Hevener and Kerby (2008), the IRS currently devotes relatively little effort to and has had limited success in challenging worker classifications. Enforcement of an employer mandate might necessitate dedicating additional resources for this purpose.

Need for additional IRS resources. The IRS would likely need additional resources to administer and enforce an employer mandate. The IRS has a low budget relative to the magnitude of the revenues it collects and programs it administers, largely due to the self-assessment model on which the tax system is based. Implementation of an employer mandate would impose substantial new responsibilities on the IRS, both to administer the mandate in general and to address the enforcement issues noted above. Its budget would need to be increased in order to fulfill these responsibilities (Holtzblatt, 2008). Additional resources might also be needed to adapt IRS procedures to allow for continuous monitoring of employer compliance with the mandate. Current IRS operations are structured primarily around the annual accounting and filing period for tax returns. Although a defined filing period results in some reduction in compliance, it is acceptable for administering the tax system since, at least in principle, unpaid tax liability can be recovered, with interest, after the fact. Administration of the employer mandate, on the other hand, would involve a more continuous schedule of operation in order to ensure that employees covered by the mandate have insurance at all times. It is unclear how readily IRS procedures could be adapted for that purpose, and at what cost (Holtzblatt, 2008).

In summary, administration of an employer mandate would require reporting of information by employers that is not covered by existing tax laws. Verification of this information would dictate involvement of employees and insurance companies and coordination of this information flow among employers, employees, and insurance companies by the IRS. It may also involve adaptation of IRS procedures to accommodate continuous monitoring and enforcement of compliance with the mandate, in contrast to tax obligations, whose monitoring and enforcement are designed around an annual cycle. These features of implementation of an employer mandate would add some complexity and impose costs beyond those that arise under existing tax laws.

Previous experience with the operational feasibility of employer mandates is limited and cannot be readily extrapolated to assess the operational feasibility of the mandate we modeled.

There is little previous experience with employer mandates that can be used to assess the operational feasibility of a nationwide mandate such as the one we modeled. Some information is available concerning state mandates in Hawaii and Massachusetts, although the experience of these states to date provides only a limited basis for assessing the feasibility of a broader mandate.

Hawaii. Until recently, Hawaii was the only state that had enacted an employer health insurance mandate. Hawaii's law, which was adopted in 1974, requires employers to offer health insurance to all employees working 20 hours per week or more (Oliver, 2004). Hawaii's employer mandate is enforced through random and routine audits, employee reports, and data matches. According to Glied, Hartz and Giorgi (2007), data matching in Hawaii is facilitated by the fact that only a few large insurers operate there. Glied, Hartz and Giorgi (2007) conclude that the mandate appears to have reduced uninsurance by 5 to 8 percent but provide no information concerning the cost of administration. Dick (1994) argues further that Hawaii provides a limited basis on which to assess the administrative difficulty of a broader health insurance mandate because of categorical exemptions that it includes and because it does not require coverage of an employee's dependents.

Massachusetts. In 2006, Massachusetts passed a comprehensive statute aimed at providing universal coverage for residents of the state. The law combines many policies, including Medicaid expansions, the creation of a state-sponsored purchasing pool, and an individual mandate (McDonough et al., 2006). The policy change also includes employer provisions that may be considered a mandate. Under the original rule, employers with more than ten employees must either make a "fair and reasonable" contribution to their employees' insurance (defined as 25 percent of full-time employees taking coverage or payment of 33 percent of the premium cost) or pay a fee called a Fair Share Contribution ($295 per employee annually) (Gabel, Whitmore, Pickreign, 2008). As of January 1, 2009, a revised version of these rules went into effect that requires employers with more than 50 full-time equivalent employees to both cover at least 25 percent of their full-time employees and contribute at least 33 percent of the premium cost or to cover at least 75 percent of full-time employees. Massachusetts also has an individual mandate under its 2006 reform law, which provides an additional incentive for employees to take an employer offer of insurance (Steinbrook, 2008; Glied, Hartz, and Giorgi, 2007).

To date, there are limited empirical data on the costs or administrative burden imposed by implementation of the Massachusetts Fair Share Contribution requirement. Preliminary information suggests that the number of firms in Massachusetts that are offering health insurance to their employees has neither increased nor decreased, but offer rates in the state were relatively high prior to implementation of the new legislation (Weissman and Bigby, 2009).

References

Dick AW, "Will Employer Mandates Really Work? Another Look at Hawaii," Health Affairs, Vol. 13, No. 12, Spring (I), 1994, pp. 343-49.

Gabel JR, Whitmore H, Pickreign J, "Report from Massachusetts: Employers Largely Support Health Care Reform, and Few Signs of Crowd-Out Appear," Health Affairs, Web Exclusives [Epub November 14, 2007], Vol. 27, No. 1, January/February 2008, pp. w13-w23.

Glied SA, Hartz J, Giorgi G, "Consider It Done? The Likely Efficacy of Mandates for Health Insurance," Health Affairs, Vol. 26, No. 6, Spring (I), 1994, pp. 343-49.

Hall, MD, The Constitutionality of Mandates to Purchase Health Insurance, unpublished manuscript, 2009. As of December 9, 2009: http://ssrn.com/absract=1334955.

Hevener MBH, Kerby CK, "Administrative Issues: Challenges of the Current System," in Aaron HJ, Burman LE, Using Taxes to Reform Health Insurance: Promises and Pitfalls, Washington, D.C.: The Brookings Institution, 2008.

Hewitt, "Massachusetts Tightens Fair Share Contribution Rules for 2009," Web page, October 11, 2008. As of December 9, 2009: http://www.hewittassociates.com

Holtzblatt J, "The Challenges of Implementing Health Reform Through the Tax System," in Aaron HJ, Burman LE, Using Taxes to Reform Health Insurance: Promises and Pitfalls, Washington, D.C.: The Brookings Institution, 2008.

McDonough JE, Rosman B, Phelps F, Shannon M, "The Third Wave of Massachusetts Health Care Access Reform," Health Affairs, Vol. 25, No. 6, November-December 2006, pp. w420-w431. [Epub September 14, 2006].

Oliver T, State Employer Health Insurance Mandates: A Brief History, Oakland, Calif.: California HealthCare Foundation, March 2004. As of December 9, 2009: http://www.chcf.org/

Steinbrook, R, "Health Care Reform in Massachusetts – Expanding Coverage, Escalating Costs," New England Journal of Medicine, Vol. 358, No. 26, 2008, pp. 2757-2760.

Steuerle CE, "Implementing Employer and Individual Mandates," Health Affairs, Vol. 13, No. 2, Spring (II), 1994, pp. 54-68.

Weissman JS, Bigby J, "Massachusetts Health Care Reform – Near Universal Coverage at What Cost?" New England Journal of Medicine, Epub October 21, 2009. As of December 9, 2009: http://content.nejm.org/

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