In a series of papers for the Mercatus Center at George Mason University, Christopher Conover and Jerry Ellig provide evidence to suggest that “the involvement of both White House and high-ranking agency staff” suggests that “the administration likely got the [ObamaCare] rules it wanted written.” To do this, it overrode the normal checks and balances used to ensure that federal regulations impose the smallest possible burden on the private sector. Rather than posting required regulatory impact analyses (RIAs) with interim rules and allowing time for analysis and comment, the White House and its agency heads dictated the rules that would be written, curbed the Office of Management and Budget (OMB) review function, and then simply declared that the interim rules were final.

In 2008, the average regulation received 56 days of OMB review. In 2009, the average regulation received 27 days of review. In 2010, the average ObamaCare regulation received 5 days of review. The RIAs accompanying the regulations were “seriously incomplete, and they fell far short of federal agencies’ normal practice.” The economic impact of the resulting regulations was so poorly understood that the authors suggest that Congress should consider establishing a review agency that is independent of politics and can “review agency regulatory analysis according to widely accepted standards.”

As the featured chart shows, poor analysis produced poor quality regulations.

Executive Order 12866 states that RIAs should “assess the systemic problem a regulation is supposed to solve, define the outcomes the regulation is supposed to produce for the public, examine a wide variety of alternative solutions, and assess the pros and cons (benefits and costs) of the alternatives.” An RIA is then supposed to be made available for public comment before a final rule is passed. The agency must consider public comment in formulating the final rule.

Rather than following the Executive Order, the “agencies decided on, wrote, and published the results without first publishing a proposal or RIA for public comment.” Specific analytical shortcomings include

▪ Benefits estimates that tended to be biased upwards

▪ Benefits estimates that were theoretically wrong, as when analysts confused transfers with efficiency benefits.

▪ Cost estimates that were biased downwards, usually due to a failure to consider entire categories of costs such as the efficiency losses associated with using higher taxes to finance a regulation.

▪ Net benefits estimates that were biased upwards, “in some cases with biases large enough to call into question whether the benefits of new rules exceed their costs.”

▪ Analyses that “ignored less-expensive alternatives that would be obvious to most health policy analysts.”

▪ Often cited benefits from increased “equity,” although the analytical effort was apparently so poor that the authors concluded that “When the word ‘equity’ appears at all, it is employed as a rhetorical embellishment rather than a serious category of analysis.”

In some cases, the regulations may impose costs that are higher than their benefits. Though the paper does not assess whether accurately calculated costs exceed accurately calculated benefits, it does find that The Early Retiree Reinsurance Program, the Pre-Existing Condition Insurance, and the Dependent Coverage for Children up to Age 26, “probably” generate more costs than benefits. Rules requiring guaranteed issue and eliminating lifetime benefit maximums “possibly” produce higher costs than benefits, as does the mandate to cover “preventive services” and the much ballyhooed, but undersubscribed, federal pre-existing condition pool. The relationship of net benefits to net costs in the rules for grandfathering health plans, the rules for claims appeals and external review processes, and the rules for calculating Medical Loss Ratios are considered “uncertain.”

The efficiency losses created by tax based finance are ignored both in the RIAs and in the public debate. They are generally understood to be large and significant costs. Since 1992, the Office of Management and Budget has required federal agencies to assign a shadow cost for the lost production of 25 cents to every $1 of expenditures. The authors note that other analyses suggest that the “deadweight loss” from taxation, the losses that occur because taxes distort the signals sent by the price system, for each dollar collected are as high as 44 cents. For the Early Retiree Reinsurance program, ignoring deadweight losses understates costs by roughly 44 percent of the program’s estimated costs of $2.2 billion.

The losses from the increased moral hazard generated by ObamaCare’s Medical Loss Ratio regulations were also systematically ignored. The amounts in question are substantial. As the authors point out, health insurance fraud alone accounts for an estimated 3 to 10 percent of annual US health care spending. Only 10 percent of the estimated fraud is actually discovered and only 10 percent of those funds are actually recovered. In view of this poor success rate, general opinion seems to hold that the biggest cost saving from anti-fraud measures comes from preventing fraud in the first place.

The authors note that the current health system “massively underinvests in fraud prevention/detection.” In view of this, the officials writing ObamaCare’s Medical Loss Ratio regulations could have decided to exempt all spending on anti-fraud activities from the Medical Loss Ratio calculation. Instead, they wrote rules that penalize insurers who spent more on deterring fraud. For example, a health plan spending $15 in administration for every $100 in premiums would be in violation of the Medical Loss Ratio regulations if it spent another $1 to prevent $5 in fraudulent claims. Spending the extra $1 would cause its Medical Loss Ratio would drop to 83 percent ($16/$100) because the $5 in fraudulent claims would never be paid, and would therefore never be entered into the denominator of the calculation.

Though insensitive to fraud prevention, the RIA analysis of Medical Loss Ratios was exquisitely sensitive to convenient definitions of equity. For example, readers are informed that the rebates required under the regulation would lead to “less disparate MLRs and value to consumers across issuers and States.”

This, as the authors point out, is nonsense. “Why equal percentages of expenditures are equitable is not explained. Indeed, if we assume the real goal is to equalize health outcomes across states, the equity claim is questionable, because differences in costs, insured populations, or market characteristics across states might require unequal MLRs to achieve the same outcomes for patients; equal MLRs could exacerbate inequality of outcomes.”

The inequity generated by the subsidized rates for people in the federal pre-existing conditions program, was ignored. Because people have to be uninsured for 6 months before enrolling, individuals in states with high-risk pools are required to either stay in those pools and pay higher premiums or go without insurance for six months to qualify for the federal program. This, as the authors point out, “arguably penalizes consumers who are currently in state high-risk pools, which appears to be a source of inequity worth commenting on.”

Parts of the rules simply seem irrational. The rules on Grandfathered Health Plans entirely prohibit changes in coinsurance while allowing copays to rise by inflation plus 15 percent. What, the authors ask, “is the rationale for limiting coinsurance changes to medical inflation plus 0 percent?” They conclude that there is no logical justification for tilting the playing field in “favor of plans that have adopted a copayment structure. Regulators apparently did not even consider an alternative that would have treated such plans similarly” even though they could have adopted a less restrictive actuarial equivalence standard.

Why didn’t the government adopt the actuarial equivalence standard? The RIA analysts said that using actuarial equivalence was just too complex and costly. This excuse does not hold water. As the authors point out, actuarial equivalence is used in Medicare Part D. It has been used to evaluate Massachusetts Connector Authority Plan benefit structure since 2006. Even more embarrassing, ObamaCare actually requires its use in structuring plans offered in the health insurance exchanges.

This article was originally published at National Center for Policy Analysis.

Linda Gorman, PhD, is director of the Health Policy Center at the Independence Institute, a free market think tank in Golden, Colorado. A former academic economist, she now focuses on state healthcare issues.


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