Require Individuals to Obtain Coverage

Analysis of Individual Mandate

An individual mandate is a requirement that individuals have health insurance, either through an employer, an individual plan, a purchasing pool, or by enrolling in a public insurance program (such as Medicaid).

These are the nine performance dimensions against which we measured the individual mandate:

• Spending
• Consumer Financial Risk
• Waste
• Reliability
• Patient Experience
• Health
• Coverage
• Capacity
• Operational Feasibility

Spending

An individual mandate will have a negligible effect on aggregate national health spending but will increase government spending on Medicaid and premium subsidies:

• Aggregate national health spending will increase by $7 billion to $26 billion, depending on the design of the mandate; this represents an increase of 0.3–1.2 percent of total spending and is indistinguishable from zero.
• Under an individual mandate, Medicaid expenditures would increase by up to $25 billion (about 7.6 percent), and overall government spending in health care would increase $12 billion to $62 billion (1.2–6 percent), depending on the design of the mandate
• Government cost per newly insured person is similar at all nonzero subsidy levels and declines as the size of the penalty increases.
• In general, other researchers who have used microsimulation methods to estimate the effect of an individual mandate on spending have estimated substantially larger increases than we did.

We modeled an individual mandate with the following design:

• All individuals without exception are required to obtain health insurance coverage.
• A national purchasing pool is created, with private insurers offering coverage that complies with federal rating regulations.
• Plans participating in the national purchasing pool agree to sell policies to all who apply (i.e., guaranteed issue required for participation).
• Premiums in the purchasing pool can vary only with age, and four rate bands were created (0–17, 18–29, 30–49, 50–64 years).
• We modeled an average plan for the purchasing pool using an actuarial value of 0.70, which corresponds to a plan that is slightly more generous than a typical non-group plan and less generous than a typical employer plan.
• We estimated premiums for plans in the purchasing pool in our model using the experience of enrollees; they range from approximately $1,000–$1,400 (for enrollees under age 17) to $4,400–$6,200 (for enrollees ages 50 to 64).*
• The administrative cost of the purchasing pool in the results presented is 15 percent, but we also tested administrative costs of 25 percent.
• Subsidies for the purchase of insurance are available only for policies from the purchasing pool. We tested a variety of subsidy structures related to income. Full subsidies are available for people whose income falls below a minimum threshold (we use 100 percent of the federal poverty level [FPL] in the results presented, but we also tested 150 percent of FPL). Partial subsidies are available on a linear decreasing sliding scale, up to a maximum income threshold (we tested 150 percent, 200 percent, 250 percent, 300 percent, and 400 percent of the FPL).
• Individuals who are Medicaid eligible and individuals with access to employer sponsored insurance (either their own employer or that of a spouse) cannot buy into the purchasing pool. This follows the structure of the individual mandate in the Massachusetts Health Reform Law of 2006.
• Penalties for failure to purchase insurance are calculated as a percentage of the premium an individual would have paid in the purchasing pool. We tested four penalty levels: 0 percent, 30 percent, 50 percent, and 80 percent.

We made the following assumptions in modeling an individual mandate:

• The penalty is perfectly enforced. This assumption can be relaxed in future iterations of the model.
• Households in which all members are fully insured through employer sponsored insurance make no change in response to the mandate.**
• Households with at least one uninsured member make decisions about how to respond to the individual mandate, to the penalty for noncompliance, and to the availability of subsidies, if applicable, by choosing the option that provides the greatest value for the money (i.e., utility maximization). The methods are described in greater detail in the overview of the microsimulation model.
• We include in the model a parameter that accounts for the apparent disutility of insurance held by those who are currently eligible for Medicaid or employer sponsored insurance and who have elected not to participate.

Consumer Financial Risk

An individual mandate will have a negligible effect on consumer financial risk for the non-elderly, but it will increase the median spending on health care by the newly insured:

• Based on our model, an individual mandate results in no discernible change in consumer financial risk for the non-elderly overall.
• Based on our model, the median proportion of income spent on health care increases substantially among those who become newly insured under an individual mandate.
• Based on our model, the proportion of households that spend more than 10 percent of income on health care increases at all subsidy levels among those who become newly insured under an individual mandate.
• Subsidies are a prominent consideration among other researchers who have modeled individual mandates.

Waste

We do not know whether increases in coverage will lead to decreases in waste, because there is little direct evidence and because the theoretical relationships may have offsetting effects:

• No studies directly examine the effect of increasing coverage on waste.
• Clinical waste could decrease if the newly insured shift their patterns of utilization from less efficient to more efficient providers, particularly if they shift from using emergency departments for primary care to visiting physicians' offices.
• Administrative waste could increase if a significantly greater number of eligible persons are subjected to complex requirements needed to qualify for subsidies or to avoid penalties, and it could decrease to reflect reductions in uncompensated care.
• Operational waste is unlikely to be affected, because the policy change does not have a direct effect on the way the delivery system is organized.

Reliability

An individual mandate will have no noticeable effect on the reliability of health care delivery at the system level:

• At the system level, there is no clear empirical evidence of a relationship between coverage and reliability.
• For newly insured individuals, the reliability with which they receive certain services may increase, but they may also receive services they do not need.

Patient Experience

No studies directly examine the link between an employer mandate and changes in patient experience:

• No empirical studies directly analyze the relationship between an individual mandate and changes in patient experience.
• Generalizations from cross-sectional studies suggest that the patient experience of formerly uninsured individuals will improve if those individuals acquire insurance.

Health

An individual mandate will result in an increase in life expectancy among those who are newly insured and will result in an additional 1 to 4 million life years:

• We estimate from our model an increase of about 1 to 4 million life years, depending on the design of the individual mandate.
• Theory and published studies suggest that, if an individual mandate increases rates of coverage, the health of some groups should improve.
• 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.

Coverage

An individual mandate will increase the number of people with coverage by 9 to 34 million, depending on the design of the policy:

• From our modeling results, we estimate that an individual mandate combined with a subsidy and a 50 percent noncompliance penalty will result in about 15 to 26 million more people having insurance, depending on the generosity of the subsidy.
• Using our model, we find that both the subsidy schedule and the size of the penalty are important in determining the likely effect of an individual mandate on coverage.
• From our model, we find that the administrative cost in the purchasing pool has little effect on coverage.
• The Massachusetts reform although not identical to the scenarios we modeled, resulted in a larger reduction in “uninsurance” than our model would predict.
• Our model predicts considerably smaller effects of an individual mandate than do those of other researchers, although the design of the scenarios we modeled is not directly comparable to the scenarios modeled by others.

Capacity

An individual 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.
• No empirical studies directly evaluate the effect of coverage changes on capacity.

Operational Feasibility

Implementing an individual mandate would be difficult, because of challenges in determining compliance with the mandate and enforcing penalties for noncompliance.

• Implementation of an individual health insurance mandate presents challenges beyond those posed by other government mandates as a result of the scope of the population covered, the economic characteristics of health insurance, and the extent to which noncompliance with the mandate presents a public policy problem.
• Both substantive features of a mandate, such as the amount of subsidies provided, and administrative elements, such as enforcement mechanisms, are relevant to compliance with and the effectiveness of the mandate. Both should be taken into account in the mandate's implementation.
• Implementation of an individual mandate could make use of existing administrative mechanisms of the federal tax system, but significant expansion and improvements of these mechanisms would be necessary.

Notes

* Because premiums are determined endogenously, the specific value varies in each modeled scenario. For example, realized premiums are higher in scenarios in which the penalty for noncompliance with the mandate is low, since some healthy people will opt to pay the penalty rather than obtaining insurance in the purchasing pool.

** By households, we technically mean health insurance eligibility units (HIEUs); that is, the group of people who, together, are eligible for private and/or public coverage.