• Understanding data on the numbers of uninsured (UPDATED)

    I am adding a note to this post for two reasons. The first is that people I have respect have pointed out to me that it is unlikely that Megan wrote the title for her piece, as editors usually choose the titles. That’s happened to me many times. The title, coupled with the sentence saying “we don’t have the uninsured problem we thought we had” made me, and many others, read this in a way it’s possible McArdle did not intend. Had I emailed her to ask (following my own advice at the end), I might have learned this before I posted. 

    I owe her an apology, both private and publicly for making those mistakes. I have edited this piece to reflect that i’m responding to an argument about interpreting the number of uninsured, not what she may have intended, and to make it less snarky, which was wrong to begin with.

    I’ve sometimes been hard on Megan McArdle in the past. I think she has, at times, ignored obvious answers because they were inconvenient to her argument. Other times, she has cherry picked evidence in order to make counter-intuitive claims, like that insurance doesn’t matter. Of course, if this was the case, then the rich (who should know how to make decent investments) would forego it. Does that happen?

    Yesterday, she wrote a piece at Bloomberg that could be interpreted as asking  if estimates for the uninsured are overblown. She uses data from the Medicaid Expenditure Panel Survey:

    A third possibility is that we don’t have the uninsured problem we thought we had. Most of the estimates we have for the uninsured population are really pretty crude. For one thing, we tend to treat the U.S.’s roughly 48 million uninsured as if they were part of a discrete group, like Mormons or people who know how to play the tuba. But in fact, people change insurance status all the time. If you look at data from the Medical Expenditure Panel Survey, you’ll see that a lot of people are uninsured for at least a month, but if you look at who is uninsured for as long as two years, that number falls by two-thirds. If you extend the reference period out to four years, just 7.6 percent of the population counts as “uninsured.” That is not a negligible number, but it is less than half of the 48 million we think of as uninsured. And it’s heavily skewed toward immigrants and the young:

    MEPS says the number of people who have been uninsured for four years or more is 7.6% of the population. That’s about 20.4 million people.  But why did she pick four years?

    The census (which is often quoted when talking about the numbers of uninsured) doesn’t ask if you’ve been uninsured for four contiguous years. It asks if you’ve been uninsured for the past year. It’s obvious that fewer people will have been uninsured for four contiguous years than for one year. If we were going to compare apples to apples, we’d want to look at the census one-year estimate and a MEPS one-year estimate. Two documents down from the one she picked, is this one. It reports that, most recently, the number of people who were uninsured for an entire year was 38.7 million people. In 2009, that number was higher, more than 41 million. The census that year had it at 46 million.

    Are there differences between those numbers? Sure. Are they monstrous? No.

    But which should policy makers use? If only someone had an analysis explaining the differences between the various ways to measure uninsurance, including CPS, MEPS, NHIS, and SIPP. Oh, wait, someone does. I highlighted it here. From that report (emphasis mine):

    It is clear that the estimates of the uninsured may vary depending upon the data source and data adjustments. The decision of which survey to use may depend on the purpose of the analysis. For credible state-level estimates, the CPS is the only source for all 50 states. Larger sample sizes enable CPS and NHIS to produce more reliable estimates for subgroups of the population (i.e. children, low-income workers, etc.). MEPS and SIPP are the best sources for examining changes in individuals’ insurance status over time and NHIS, MEPS, and SIPP can provide point-in-time estimates of the uninsured.

    By the way, that document was written in 2005, when George W. Bush was President.

    MEPS provides insurance status by month, for every month of the year. A researcher can use that to examine both short (one month) and long (one year) spells of uninsurance. By combining data across multiple years, he or she can examine longer spells. Therefore, you’re going to get different estimates in the literature because researchers are asking different questions and using the data differently.

    McArdle continues with this:

    Our projections are based on what we thought we knew about the uninsured. But what we thought we knew has turned out to be wrong before. In the three years between Obamacare’s passage and the time it went into full effect, the law created temporary high-risk pools for those with pre-existing conditions. The Congressional Budget Office projected they would cover 400,000 people, but they ultimately attracted only a quarter of that, even though they relaxed the criteria and undertook aggressive outreach programs. Where were the other 300,000 people who were willing and able to buy insurance but couldn’t get a company to sell it to them? It’s possible that they simply never existed.

    There are tons of reasons those high risk pools fell short of  expectations. Some of us even predicted the results. I entitled one post “Told you so“.

    Plus, let’s take a breather and actually look at CBO documents. Did they think that 50 million would take advantage of new insurance in the exchanges and Medicaid expansion? No. Even projected out in to the next decade, it looks like they believe that about 25 million will gain coverage. Does that sound reasonable based on all the data above, including McArdle’s?



    • I used to enjoy watching McArdle on Bloggingheads with either Jonathan Chait or Noam Scheiber, not so much for the debate between them, but for the entertainment of seeing Chait’s or Scheiber’s eyebrows merge with the hair on his head when McArdle said something especially insipid, the instant when I expected somebody to ring a gong. The poor woman subjects herself to ridicule in her search for affirmation that she is smarter than everybody else. Just give her a diploma and be done with it. Why she’s given such a large platform in her search is something that anthropologists will be studying for years.

    • “the rich (who should know how to make decent investments) would forego it. Does that happen?”

      Speaking of unsubstantiated claims, can you provide any evidence that the rich make better investment decisions?


      • In the current system the working “rich” have little reason to forgo insurance. For many of them it is efficient to let the insurer do the negotiating and payment – not worth their time or their spouses time to deal with.

        There is data – MEPS shows that about 14% of those above 400% of FPL are uninsured some of them are between jobs no doubt – by some percent GT 0 have opted to self-insure.

    • Seriously though – now that we know that there’s a “tax” involved and we know how loathe the Gov’t is to create or increase taxes, what are the long term implications of those uninsured individuals covering their own expenses through the “tax” if they aren’t going to be able to raise the rates should demand exceed supply of revenue?

    • Her misuse of uninsured statistics is bewildering. The issue isn’t “who is uninsured for [x period of time]?” but rather “at any given point, how many people are uninsured?” To add to your discussion of how rigorously people who do this for a living understand this, there’s a decent amount of data on this “churn.”

      Also, she relies on MEPS data. MEPS isn’t terrible, but their estimate for annual ED visits is generally <1/2 of everyone else's: around 55-60 million vs 120-35 million (depending on the year).

      • I think how long someone is uninsured matters. Since
        there’s been a huge tax advantage and no problems for pre-exisitng
        conditions, the vast majority of people who have individual
        insurance will ditch it as soon as a company plan become available.
        People between jobs might go bare for a few months, figuring they
        won’t get sick before they are again covered. That’s what all the
        people I knew who were uninsured for periods did: they were
        healthy, since 20-30 somethings who were betting they’d be covered
        by a company plan soon. These people make different choices from
        people who are looking for a longer tern insurance solution. If
        your insurance is running out and you have a bunch of promising
        interviews lined up, do you go though the cost and hassle of
        getting individual insurance when you expect better insurance will
        be available within a month or two?

        • I don’t think the length of time someone spends uninsured is inconsequential; but, when we are trying to accurately gauge the prevalence of being uninsured, the length of time doesn’t matter. The problem isn’t being uninsured: the problem is being uninsured and sick at the same time, and unfortunately, that’s not something anyone can do avoid.

          See this classic paper on churn: http://www.ncbi.nlm.nih.gov/pubmed/14649453

    • I would agree that MM does not make a very good case for the absolute size of the “uninsured” – but I do think her point on them being a pretty heterogeneous group is often lost [not on TIE – but elsewhere]. It contains those who would buy insurance if it were available at an affordable price AND those who do not think insurance is a good way to spend their money [for a wide variety of reasons – not all of them good] AND those so poor that they could not buy insurance at any price. The MEPS data for 2011 is interesting and should be big concern for those who think Obamacare is a good idea…

      34.3M of the uninsured describe their health as Good or better
      4.3M – a bit more than 10% of them said they were in fair or poor health

      47% of the first group had $0 in health care spending in that year
      of those with any spending…
      the mean-average was $1629 – about $135 a month…
      BUT the Median – half of those with ANY spend spent less than $45/mo

      so something like 25M of the uninsured are spending less than $50 a month on health care – this is over 60% of the group.

      The problem with the ACA is that they will now be asked to sign up for a plan that will cost them – or the taxpayers much more a month in premiums AND hit them with a pretty healthy deductible/OPC

      So she is right that the uninsured are not homogeneous – but IMO misses the big point – they are currently both pretty healthy and paying very little [yes perhaps they are holding off on care until they regain insurance as many of them likely will]

      [BTW for the 4.3 million who say they are in fair or poor health 24% of that group spent $0 on health care with mean annual spending for those with any expense of $5,124 and median of $1,126 – still less than $100 a month.]

    • I think this is the most frustrating thing about reporters and op-ed writers.

      They don’t know how to do basic research into the field they are writing on.

      “Hey, no one has considered what I just thought of!”

      1 minute on Google Scholar later and the derp becomes strong

    • If contributors to Bloomberg can engage in speculation,
      then I can offer this anecdote: many exchange customers are being
      incorrectly advised on qualification for subsidies. Why, I don’t
      know. But several people who asked for my advice after being told
      they didn’t qualify got a very different result after I referred
      them to the Kaiser Family Foundation web site that will calculate
      the subsidy (http://kff.org/interactive/subsidy-calculator/). Is it
      the fault of the exchange web site, the information from the IRS,
      or the customer? I don’t know. But some cases are so obvious
      (income barely above the poverty level) that I have to believe it
      is not the fault of the customer.

    • We tend to get caught up in the precision of metrics – but
      the scale of our healthcare problems is often more complex. The
      Commonwealth Fund reported this from their biennial health
      insurance survey in April: New Health Insurance Survey: 84 Million
      People Were Uninsured for a Time or Underinsured in in 2012.
      Biennial Health Insurance Survey Finds 75 Million People Struggled
      with Medical Debt and 80 Million Were Unable to Afford the Health
      Care They Need http://hc4.us/TCWFunderinsured Point being – this is
      a very large, fluid cohort – and another variable that’s about to
      kick in are people who have insurance today – but will lose it to
      part-time status, or simply altogether, in 2014. Employers not only
      have a stake in this – they have a really big vote. As we also
      know, more and more employers are favoring defined contribution
      over defined benefit – and Microsoft (for the first time in their
      storied history) started charging employees for their health
      benefit – just this year.

    • I don’t see any error in McArdle’s data analysis. She’s
      pointing out that the 48 million figure that has been bandied about
      so much doesn’t tell the whole story. Is that incorrect? She’s not
      saying that the 48 million is wrong, just that it tells you one
      specific thing–how many people at any given time do not have
      health insurance. The proponents of health reform used the number
      to indicate how many people couldn’t get health insurance which is
      much different. Some of those 48 million people are temporarily
      between jobs (which I believe Obamacare won’t have much effect on
      since they’ll presumably still be covered by employers). Another
      chunk, which she doesn’t discuss, are eligible for Medicaid.
      Another chunk comprises illegal immigrants (who also will be
      unaffected by Obamacare). During the debates on Health Care Reform,
      it would have been nice if the numbers used were more targeted to
      the problems being addressed.

    • Aaron, your 2009 article on high risk pools was terrific. I
      am sad that I missed so much good writing before I discovered your
      blog in 2012. Just as another viewpoint, I am a leftist but I have
      never been concerned about the gross number of uninsured. Instead I
      am concerned about the uninsured who are sick, and either do not
      get needed care, or get it at the last moment and then are harassed
      to pay the bill. My number is probably about 5-10% of the nominal
      uninsured, i.e. 2-4 million persons a year. My solution for the
      last 5 years has been this: a. let them stay uninsured b. make them
      pay about 3% of their income to help sustain our safety net c. If
      they are hospitalized or need extensive procedures, let Medicare
      Part A pay the bill. d. If they need to see a doctor, the majority
      can afford to see a doctor and pay in cash. At the same time, build
      up sliding scale public clinics. Thanks, Bob Hertz, The Health Care

    • Note to Lonely Libertarian

      thanks for raising some good points. I have been saying for the last four years that many of the uninsured would stay away from the ACA exchanges. Right now they are on the good end of a gamble on their health.

      Of course they would be more secure if they bought health insurance. But when the household budget is tight and no employer is helping out, then security is a little less important.

      This is why my proposal of a Medicare default plan makes so much sense.

      We do let people gamble by not buying fire insurance if they want to.
      But we do not let them avoid paying taxes for the fire department.