In the pending health care bills, low-income individuals and families who buy health insurance outside employment will get large government subsidies. Those subsidies vary by locale. This represents a significant implicit policy decision with enormous distributional and political consequences. I don’t think most Members or their constituents have focused on this. I think they should.
Let’s start with the Knights, a family of four with adults age 40. The family has $44,000 of income, putting them at twice the poverty line for a family of that size. The Knights do not get health insurance through their employer. The Knight family lives in Las Vegas.
Their friends the Ford family are identical in every way, except they live in Portland, Maine. They, too, make $44,000 of income, but it doesn’t go quite as far as the Knights’ $44K, because it costs almost 6% more to live in Portland than in Las Vegas, according to CNN.com’s cost-of-living calculator. Utility costs are much higher in Portland, and food prices are 2% higher in Portland.
Suppose we are designing a new national program to subsidize food for modest-income families. We have a range of choices.
- At one extreme, both families get the same subsidy amount.
- At the other extreme, both families pay the same net amount for groceries, meaning the Ford family gets a bigger subsidy, since groceries cost more in Portland.
Which is fair? In a system of locally-elected representatives, your answer probably depends on where you live. I can construct legitimate arguments for either extreme, or for a midpoint policy such as the Ford family getting a 2% bigger subsidy than the Knights.
Now what if people in Portland eat 5% more than people in Las Vegas? If we go with approach (2), should the Ford family get a subsidy that accounts for the higher prices in Maine and their greater food consumption? Should the two families pay the same amount for groceries if they’re eating different amounts? Again, there’s no objectively right answer. My personal preference is to favor approach (1).
Different federal spending programs take each extreme approach and many variants in between. Some adjust for regional variations; others do not.
Now let’s look at what the Baucus bill does for the new low-income subsidies to purchase health insurance outside of employment. Here is the key sentence from the conceptual description of the Senate Finance Committee-reported bill (labeled as page 27, it’s page 30 of the PDF).
The premium credit amount would be tied to the second lowest-cost silver plan in the area where the individual resides.
This is approach (2) (and it becomes clear it’s the extreme when you study the details). If you live in an area with relatively inexpensive health plans, low- and moderate-income people in your area will receive smaller government subsidies than their similarly-situated identical twins who live in relatively high-cost areas.
A “health plan” is not a commodity like “a gallon of milk.” A health plan in Las Vegas is quite different from one in Portland. While the overall cost-of-living in Portland is higher, health care spending is much higher in Las Vegas. This higher health spending is a function of different prices and different usage of medical care.
Atul Gawande wrote a much-discussed article on this topic in The New Yorker, “The Cost Conundrum:” What a Texas town can teach us about health care. There are wide geographic dispersions in medical care spending, and it cannot all be explained by different prices. While I disagree with Gawande’s policy conclusions, I recommend the article.
Since insurance premiums ultimately reflect the cost of medical care used, insurance premiums too will vary widely from one area to the next. This brings us to the effects of the policy decision in the new health care bills.
We are fortunate have a calculator created by the (liberal) Kaiser Family Foundation to do most of the hard work for us.
The Kaiser calculator makes a simplifying assumption that premiums in high-cost areas will be 20% higher than in average areas, and premiums in low-cost area will be 20% lower than in average areas. That seems like a reasonable assumption to illustrate the conceptual point.
I have chosen Las Vegas and Portland because they represent high-cost and low-cost areas respectively. Using Kaiser’s assumption, I will assume that a typical health insurance premium costs one-third less in low-cost Portland than in high-cost Las Vegas (1 – (80%/120%)) = 1/3. Note that while the overall cost-of-living in Portland is higher than in Las Vegas, per-person health spending is much lower in Portland in part because of differences in medical care usage.
Under the Baucus/Senate Finance Committee bill, both the Ford family and the Knight family will pay only $3,070 for family health insurance after netting out their new government subsidy. That’s an incredible deal for either family.
It also represents approach (2) described above. Both families pay the same amount, post-subsidy, for health insurance. Since (using Kaiser’s assumption) health insurance costs 1/3 less in Portland than in Las Vegas, under the Baucus bill the Knights in Vegas will get a $6,365 subsidy, while the Fords in Portland will get a $3,220 subsidy, 49% less than the Knights. (The Kaiser calculator gives me these subsidy amounts.)
Is this fair? One family, living in a higher-cost area, gets a subsidy twice as large as the other because of differences in medical care usage in their local markets?
The President has made a big deal about regional differences in health spending as an opportunity for making American health care more efficient while retaining high health outcomes. That’s one of the points of the Gawande article, that greater usage of medical care does not result in similar improvements in health. Minnesota is the usual example, where per person medical spending is low, while health outcomes are quite high.
Academics have done a lot of research on this. If the New Yorker article excites you, go learn about the famous RAND Health Insurance Experiment and the Dartmouth Atlas of Health Care.
The President’s push to address this source of inefficiency would lead one to design a new subsidy program favoring approach (1), equal subsidy amounts that are independent of regional differences in health spending. Approach (2) has the downside of directing greater subsidies toward areas of greater usage. When you subsidize something you get more of it, so if you subsidize areas with greater usage, you should expect even more usage. Whatever your view on the equity question, the Baucus/SFC choice of approach (2) will likely increase disparities in health spending and exacerbate the problem the President has correctly identified. This is inefficient and counterproductive.
Efficiency is not, of course, the only goal of subsidy design. If my experience is any guide, most Members of Congress (and many citizens, and all local press) will care first about whether their modest-income families are being treated fairly relative to other similarly-situated families in other areas. Again this is a matter of perspective, but I think the approach chosen in both the Baucus bill and the House Energy & Commerce bill looks terribly unfair by creating such enormous disparities in subsidy amounts. To me it looks like if you’re a modest-income family in a low-health-spending area, you’re getting shafted relative to those in higher-spending areas.
Let’s look at a few more examples, using the same example family (4 people with adults age 40, $44K income, no health insurance through their job). The Baucus bill gives this family the same after-subsidy cost for health insurance. This means:
- If the family lives in the high-cost Bronx, Chicago, Baton Rouge, Detroit, or Las Vegas, they will get a government subsidy of $6,365 to buy health insurance.
- A family with the same income living in average-cost St. Louis, Reno, or Delaware will get a government subsidy of $4,792. That’s 25% less than the Bronx or Chicago family.
- A family with the same income living in low-cost Little Rock, Indianapolis, Portland, or Nebraska, will get a government subsidy of $3,220. That’s 49% less than the Baton Rouge or Detroit family.
I ran similar numbers for the House Energy & Commerce Committee bill, the one most-discussed before the August summer recess, and got similar results. I wanted to see both the relative subsidy levels in both bills, and which parts of the country might qualify for different subsidy amounts.
I needed a way to divide the country up into low, average, and high-cost areas. The nice people at Dartmouth have done the Dartmouth Atlas of Health Care, which extensively examines regional differences in medical care usage and prices. The Dartmouth folks break down per-capita Medicare spending by geographic area. It’s certainly not a perfect proxy for private health plan premiums, but we’re only trying to divide places up into high-average-low, so I think it works fairly well for a back-of-the-envelope exercise like this one. Fee-for-service Medicare spending tends to be highly correlated with non-Medicare spending in the same area. I end up with 134 “low cost” areas, 114 “average cost” areas, and 58 “high cost” areas.
I’m sure a team of researchers could do a slightly better job, but I would bet their final list would look a lot like mine. To be careful, though, I think of this as an illustrative list of regional differences for this thought experiment. I do not claim these are the actual subsidy amounts for each region, because I have had to make and use some simplifying assumptions. The actual different amounts and regions could be determined only after a drawn-out and incomprehensible regulatory process months after enacting a new law. So while the following tables are necessarily educated guesses, I hope they illustrate the rough impacts that will result from this critical policy choice that no one is discussing.
Here are the subsidy amounts for our example family for the two different bills:
Comparison of government subsidies by geographic area
Compared to high cost
Compared to high cost
The above methodology produces the following areas:
Illustrative geographic areas for varying low-income health insurance subsidies
gets high cost minus $3,773
gets high cost minus $1,886
San Luis Obispo
East Long Island
Do Members of Congress understand the massive distributional policy choice they are making by supporting these bills?
I’ll bet most of them don’t.
(photo credit: Christopher Chan)