The CBO and Obamacare replacements: using the wrong metric

The CBO and Obamacare replacements: using the wrong metric July 31, 2017; By Unknown photographer [Public domain], via Wikimedia Commons

Here’s what I’m noticing about Congress’s ongoing attempts to create a credible Obamacare-replacement bill:  with each version of an Obamacare-repeal bill, from the House version to the initial Senate proposal to the “skinny repeal” bill of last week, the CBO has weighed in, and the media has repeated its pronouncements, on the Key Question, how many additional uninsured people will there be upon implementation of the bill?

A repeal without replacement would increase the uninsured by 32 million.  The “skinny repeal,” 16 million.  The House plan from May, 23 million.  The original Senate bill, 22 million.   Avik Roy, in a Forbes article, criticizes all of these calculations, observing that, in the CBO’s eyes, the key driver of insurance levels is the existence, or lack thereof, of a mandate; that is, observing that the CBO calculations seem to be similar for several plans with different approaches towards subsidies, he writes

The principal way to explain these three results from the CBO model—nearly identical coverage numbers despite substantially divergent resources directed to low-income individuals to afford coverage—is to remember that the CBO’s model is heavily tied to the idea that the individual mandate is forcing all sorts of people to buy coverage that otherwise would not.

In the latest report, the CBO estimates that 15 million people would voluntarily drop out of the market in 2018 due to the repeal of the mandate. That’s nearly three-quarters of the total coverage loss, in one year.

And, of course, opponents of the repeal efforts point to all of these projections of loss-of-coverage and, based on a calculus of “health insurance saves lives,” proclaim that what Congress and the GOP is doing is nothing sort of killing people.

But we’re measuring the wrong thing.

To back up for a moment, consider the status quo ante:  low and moderate-income Americans who did not have insurance provided through their employers, or through various anti-poverty programs (e.g., poor single mothers and children), had two choices when it came to healthcare.  They could purchase individual insurance, at rates which consume very high proportions of their income, or they could attempt to navigate the maze of government-funded clinics, charity care, financial assistance programs, installment payments, and, when all else fails, file for bankruptcy.  And individuals who didn’t manage this maze would make do without health care.  (Yes, one expects that, as a result, the insured population would have been dying in droves, and the implementation of Obamacare would have dramatically reduced mortality rates, yet studies have indicated that this hasn’t happened; what seems to have happened instead is simply that financial stress has been modestly alleviated.) To a certain degree, individuals still face these two choices, though Obamacare attempts to limit the cost of health insurance as a percent of income, for those with income below 400% of poverty level, and the maze-navigation is at least limited to the cost below the out-of-pocket maximum, with the concomitant search for in-network providers.

And in our new status quo, Americans who purchase on the exchanges, or read about them, are upset by the rising cost of premiums, and the declining number of participating insurers, and the challenges of narrow networks.  But there is nonetheless a broad consensus that the government has a legitimate role to play in enabling low/moderate-income Americans to purchase health insurance at rates that are affordable to them, to spare them the need to seek out charity or use bankruptcy court or do without entirely.

Which fundamentally means that the appropriate method of measuring whether any replacement proposal is the right path forward, is this:  to what degree will Americans be able to purchase health insurance at premiums that are affordable for them as a percentage of their income/assets?

In my prior analysis of the original Ryan plan, with a tax credit ranging from $2,000 to $4,000, I estimated that an individual policy with a deductible of $7,000 would cost about $2,000 in annual premiums for a 49 year old, about $5,000 for a 64 year old, using some rudimentary online sources.  Maybe that’s fine for a middle-income earner, but I think there’s a general consensus that this isn’t affordable for someone earning considerably less, especially considering the high deductible.  And, readers, your facebook friends likely shared, as mine did, worst-case scenarios of near-retirees paying massive amounts for health insurance under various GOP proposals, such as the analysis from the AARP.

What’s a fair percentage of pay?   There is no single answer.  Someone with a higher income can afford to pay a higher amount towards health insurance; a low-income individual could pay very little before their ability to pay the rent is at risk.  But the CBO consists of a number of intelligent, numerate individuals, who could surely, among themselves, derive an affordability index that would be broadly acceptable to both parties.

Such an index would be a far better way of measuring the reasonableness of health insurance proposals.  Multiple factors would drive this index for any given proposal:  not just the level of subsidy, but any proposals which impact the cost of insurance (or the cost of healthcare, in the absence of health insurance or up to the deductible/out-of-pocket limit) in the first place.  An affordability index wouldn’t be contingent, as the “number of uninsured” metric is, on estimating individual choices to elect or decline health insurance.  It would, admittedly, not be as simple a number as the uninsured metric is, but should be explainable to the general public, at any rate, and various proposals can be compared to each other on the basis of this metric in combination with the amount of federal spending proposed.

How would the various replacement plans fare on this metric?  Not as well as they should, I’m afraid, because we haven’t yet begun to measure this.


Image:; By Unknown photographer [Public domain], via Wikimedia Commons

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