Tag Archives: Maryland

New data on ACA enrollment shows problems in many states

The Department of Health and Human Services released updated data today on enrollment on the Exchanges including, for the first time, greater breakdowns on enrollment by several key categories: age, gender, and the metal level of purchase. The result of this long awaited and much requested data is, at first glance, very much a mixed picture. Some of the overall statistics do not look as problematic as some — including me — had feared they might be. But it looks as if there is a very serious potential for large adverse selection problems brewing in a number of states,  most notably West Virginia, Mississippi, Maryland and Washington State.

 

The good news for the ACA from the data

There are three major pieces of good news for those who support the goals of the ACA.

1. The overall gender distribution of enrollees, 54% female, 46% male does not appear on preliminary inspection to be sounding “red alert.” To be sure, the problem may be a little greater than would otherwise be suggested by the aggregated numbers if the middle age group is more heavily female and the oldest group of enrollees more heavily male that the aggregated numbers suggest.  And Mississippi is troubling with 61% female enrollment (and for other reasons, see below). But, overall, and if they hold up, these do not appear to be the the kind of numbers that would be way beyond what insurers likely expected or that, standing by themselves, would be devastating to an insurer on an Exchange.

2. Several states have total enrollments and the age distributions that should reduce the possibility of a serious death spiral getting started. New York and California are the two big states doing better than most.  Connecticut is doing very well also.

3. The metal tier distribution is 80% for Bronze and Silver policies and only 20% in Gold and Platinum.  That’s comforting for adverse selection. A higher proportion of enrollment in the more generous plans would have been a warning sign that enrollment was coming disproportionately from the sick.  There’s a footnote on this point later on — we are not out of the woods — but this is definitely better news for the ACA than a distribution of, say, only 50% Bronze and Silver purchases.

The bad news

Just because the ACA is doing better than some had forecast on an overall basis does not mean there will not be very serious problems in some states.  Given that the statute is presently unamendable as a practical matter, problems in just a few states can hurt a lot of people.  The data released by HHS today shows that there are a number of states in serious trouble.

The table below shows current enrollment in states that appear at first glance to be in significant trouble. (There may be states that are as bad as those shown in the table below; I kind of eyeballed the data, which was not provided in a nice electronic format, to select what appeared to be a problem).  I also show the projected number of purchasers, the percentage of current enrollees as a fraction of purchasers, the percentage of “young invincibles” as a fraction of the enrolled population and the percentage of the expensive 45-64 year old age group.

Maelstrom_Index

I also construct a “back-of-the-envelope”/quick and dirty “Maelstrom Index” that roughly measures the problems confronting the individual Exchanges in the state.  The maelstrom index is calibrated to run from 0 to 1 with a 0 score meaning the state is in excellent shape and a 1 meaning there is an extremely high risk of an adverse selection death spiral materializing.  It is not a probability measure.  The formula for the maelstrom index is shown at the end of this post.

Maelstrom_Index

As one can see, there are a number of states that have serious potential problems. West Virginia is problematic with 66% of its enrollees ages 45 to 64 and only 17% ages 18-34. Almost all experts would concede that this poses serious risk of adverse selection. And the overall fraction of enrollment relative to projections, just 20%, suggests that West Virginia’s insurance pool may be disproportionately populated by the sick. Mississippi is likewise a problem with enrollment only 14% of that projected, 58% in the age 45-64 bracket and, as mentioned above, 61% female enrollment. I have to believe that insurers writing in Mississippi are deeply concerned about these numbers.

Also  troubling are the numbers in Texas, Washington State, and Ohio simply because, as an absolute number, there is such a large absolute difference between the number of people projected to purchase and actual enrollment. I’ll speak more about all of these numbers and try to update the chart in the days ahead.

The unknown

There’s one key piece of data not found in the HHS release today. The number of “enrollees” who have actually purchased policies.  If this conversion rate is, as I fear, hardly 100%, the numbers presented today overstate the extent of purchases in the Exchanges and understate the dangers of adverse selection breaking out in many states.

The Maelstrom Index Formula

Max[0, (5*(1.4 – enrollmentPercentage – youngInvinciblePercentage))/7]

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The new Exchange enrollment numbers are bad

The federal government announced today that 137,204 people have selected a healthcare plan through the federal Exchange as of November 30, 2013. The number is an increase over the 29,794 who had done so by the end of October, a month during which the website portal for enrollment, healthcare.gov, was in disarray. The government reports that 258,497 have now selected a plan through one of the state Exchanges, making a total of 364,682 enrolled. Asked by reporters whether the Obama administration stands by its estimate that 7 million will enroll in individual plans sold on the various Exchanges by March 31, 2013, the day necessary to do so in order to avoid a tax penalty,  Michael Hash, director of the office of health reform in the federal Health and Human Services Department, said that they were “on track, and we will reach the total that we thought.”

The pace of enrollment announced by the federal government today is inconsistent with the claim that its 7 million goal will be achieved. The claim rests on hopes of two surges, one taking place over the next 12 days before the December 23, 2013, deadline for coverage starting January 1, 2014 and a second surge taking place as we approach the end of March at which point, if coverage has not been obtained, many Americans will be hit with a tax penalty.

The magnitude of the surge required strains credulity.  A scenario in which most of  those who wanted coverage have already applied and in which the pace of enrollment stays the same or even sags for lengthy periods as we go forward would appear almost as likely. Plus, it seems unlikely that there will be major enrollment between December 23, 2013, the first deadline, and March 23, 2014, the second deadline. If someone wanted coverage, they would try to get it earlier. What does applying in the middle of February accomplish? Moreover, if, given the unpredictability of human behavior, the surge actually materialized, it might well strain the government’s computer systems.

Analysis

There are many disturbing aspects to today’s release of numbers. First, forget for the moment about the March 2014 projection date and the March deadline.  There are only 12 shopping days left before the pool will be closed for those who will have coverage as of January 1, 2014.  Even if the pace of enrollment surges by a factor of 10 over what it was for the last two weeks on which we have data and healthcare.gov enrolls people at 45,000 per day, that would still put only about 668,000 persons enrolled through the federal Exchange as of that deadline.  Even this rather cheery estimate would result in only 14% of the 4.8 million the Obama administration has projected will be enrolling in the federal Exchanges in 2014.  The original projections for enrollment on opening day, January 1, 2014, were considerably higher, 3.3 million.

The number enrolled as of December 23, 2014, matters greatly. While of  course there could be a second surge, in the mean time insurers are having to pay claims for three months on those first 14% to enroll. The initial enrollees are very likely to be comprised disproportionately of people with above average health care expenses. The result will be that, until that prayed-for second surge occurs, insurers will likely be losing large sums of money in the Exchanges and, ultimately, seeking reimbursement pursuant to the Risk Corridors program from the federal government and, derivatively, taxpayers.

Moreover, the aggregate numbers mask the fact that there are 50 different sets of Exchanges. While numbers are better in some, there are many jurisdictions in which there are huge problems.  It is not “OK” if the Exchanges succeed in California, New York and a few other states if insurers and insureds in many other states suffer severe adverse selection problems that result in rapidly rising prices or reductions in availability.

Let’s look at a few states. I start with Texas. There, out of 780,959 projected to be enrolled, there are 14,038 as of the end of November.  This is fewer than 2% of the ultimate projected amount.  Even if one assumes that enrollments in Texas surge to go 20 times faster in December than they did in November, which is a pretty heroic assumption, this would still result in only 183,425 being enrolled as of the December 23 deadline. This would be  only 23% of what needs to occur. It would be as if a football team were down 35-3 in the 3rd quarter and hoping to make a comeback. It could, I suppose, happen, and you shouldn’t turn off the TV set, but the probabilities are remote.

One might argue that Texas is an exceptional case due to the degree of hostility prevailing among many here about “Obamacare.” Take another fairly large state using the federal Exchange, Pennsylvania. There, we see 11,788 enrolled out of 268,858 ultimately projected, just 4.4%.  To get to even 1/3 of the ultimate projected number being enrolled by December 23, the pace for December would have to be 6 times greater than it was in the last two weeks of November. Not impossible given procrastination, but again, a major challenge.

The figures when one looks to the various state Exchanges are a mixed bag. The poster child for the Obama administration would appear to be California. It has 107,087 of the 691,016 it ultimately hopes to enroll, over 15%.  With a decent last minute kick, it is not unimaginable that California could make 1/3 of its total by the December 23, 2013 deadline and get closer to its ultimate goal by the end of March.  But even with these better-than-average numbers, there is the risk of at least some adverse selection in a pool substantially smaller than projected. Also doing better than many is New York. There, we see 45,513 enrolled. But even this is but 11% of the 411,304 projected. It will again take a major surge over the next 12 days if New York were to get to even 1/4 of the ultimate projected enrollment by the December 23 first deadline.

But for every California or New York running its own show, there is an Oregon or a Maryland. These are large states in which enrollment is lagging. In Oregon, owing substantially to the collapse of its computer system, only 44 people have enrolled in plans on their Exchange. It will take an unimaginable surge there to make the system functional. Officials there and in Washington, D.C. will soon need to start contemplating what to do about a failed system; will, for example, tax penalties be imposed for those in Oregon who do not have health care coverage? In Maryland, where the director of the program recently quit, just 3,758 have enrolled out of 91,528 projected, just 4.1%. It goes beyond hope and into the realm of fantasy to believe that Maryland is not going to have a serious adverse selection problem starting January 1, 2014, when those 3,758 who penetrated the state’s application system start filing claims.

Finally, nowhere in the release do I see an age distribution of those enrolling. Unquestionably, the administration has this information. It is required in the enrollment process. And, perhaps this is a bit cynical, but I have to think that if those numbers looked good, if the hoped-for proportion of younger persons were enrolling, the Obama administration would release the information.  I believe we are entitled to draw a negative inference from the fact that the information was not released that the pool is disproportionately elderly. If this is correct, what we are seeing is a small pool composed disproportionately of the elderly. That does not augur well for those who want to see the promises of the Affordable Care Act fulfilled.

An Experiment

HHS was kind enough to include a graphic in their report. Here it is.

Cumulative enrollment in the federal Exchange for various states
Cumulative enrollment in the federal Exchange for various states

The graphic plots time on the x-axis and cumulative enrollment on the y-axis. Recognizing all the enormous problems with doing so, I thought it would still be interesting to try to fit a curve to the data and extrapolate it out to see where we might end up.

The short version is that if we extrapolate the curve using quadratic and cubic models, we end up at between 278,000 to 383,000 enrolled in the federal system by the December 23, 2013 first deadline. This would represent fewer than 10% of the ultimate projected enrollment and will create substantial adverse selection problems for at least the first three months of the program, particularly in the less enthusiastic states. This all assumes, of course, that all people who have selected a plan actually pay the premiums. The numbers could be worse. Regardless, insurers are going to be very concerned if these are the sort of numbers that materialize; the federal government better get out its Risk Corridors checkbook to help relieve the pain.

By March 23, 2013, however, the same models show we could be at 1.35 million to 3.94 million, depending on the model chosen.   This would represent 28% to 82% of that originally projected and would cause serious adverse selection problems at 28% or mild adverse selection problems at 82%.  I appreciate fully that these are large error bars but we just don’t have the data or an a priori model that permits me to extrapolate with any confidence this far into the future.

Here’s a graphic showing these results.  The Mathematica notebook that generated them has been placed here on Dropbox.

Extrapolation of enrollment data
Extrapolation of enrollment data

 

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