Early ACA Data Shows No Wave of Sick Patients

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Since launching ACAView, our joint initiative between the Robert Wood Johnson Foundation (RWJF) and athenahealth, in early April, open enrollment under the Affordable Care Act (ACA) has closed for 2014 and The White House has issued final numbers: eight million people enrolled through the marketplace and five million outside the marketplace. Add another three million enrolled in Medicaid or the Children’s Health Insurance Program (CHIP) and the total number of people enrolled under the ACA’s individual mandate is close to 16 million.

Since some of these enrollees had previous forms of insurance coverage, it is important to estimate overall reductions in the number of uninsured. RAND estimates that 9.3 million more Americans have insurance in Q1 of 2014, compared to Q3 of 2013, but these figures exclude the surge of enrollments in the last half of March. The Congressional Budget Office (CBO) estimates 12 million net newly insured people through either the marketplace or Medicaid (including 1 million who lost insurance), but these estimates exclude enrollments outside the marketplace.

In short, “newly insured” and “enrollment numbers” are counted in different ways and can be confusing. But let’s conservatively assume that the number of net new insured individuals is roughly nine million, or 2.8% of the population.  Are these new beneficiaries having a measurable impact on medical practices?

In our previous report, we saw that, at least for the first quarter, a national sample of 12,700 physicians across the athenahealth network did not see an increase in new patients[1] due to the ACA. While not all new patients are newly insured, an increase in this population would suggest that coverage expansion is having an impact on medical practices. Instead, the percentage of total provider visits with new patients actually dropped slightly in the first three months of 2014 compared to 2013. Several factors may help explain why the ACA’s coverage expansion has not led to an immediate and measurable impact:

  1. The number of newly insured patients in the first quarter of 2014 may have been too small to have a measurable impact.
  2. Not all newly insured patients required care.
  3. It may require weeks or months for patients to schedule appointments and be seen.

Our data suggests the influence of new patients on provider activity may take considerable time to unfold. Figure 1 shows the percentage of visits by new patients to Primary Care Providers (PCPs) at practice locations active before 2011. New patients account for 15% to 20% of office visits in the beginning of the year, growing as a proportion throughout the year. Note that a patient defined as new at any point during 2014 remains classified as new throughout the entire calendar year. In other words, these new patients are tracked as a cohort as the year progresses. We chose this definition to measure the level of effort physicians place in treating patients that are new to the practice across the year.

The proportion of visits by new patients in the first quarter actually dropped slightly between 2013 and 2014. As the newly insured seek out care, we will monitor the proportion of total provider visits for new patients compared to last year.

In addition to tracking the percentage of new patient visits, it is also important to consider whether those new patients have a higher rate of chronic conditions compared to previous years, and therefore, increase the proportion of care they receive from providers. That is, will the ACA result in the release of pent-up demand, with previously uninsured patients seeking care for a host of chronic and/or complex conditions that were previously left untreated?

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So far, this does not appear to be the case. Figure 2 shows the proportion of visits, for Q1 of 2013, in which a chronic condition (diabetes, hypertension, hyperlipidemia) was diagnosed.  New patients are compared to established patients, by insurance type (commercial, Medicaid, Medicare). Results for commercial and Medicaid beneficiaries are shown only for adults under 65 and results for Medicare beneficiaries are shown only for adults 65+.

Not surprisingly, Medicare beneficiaries have higher rates of chronic disease than those with private insurance or Medicaid. It is also unsurprising that Medicaid beneficiaries have high rates of chronic conditions. But the most relevant comparison is that established patients have a higher rate of chronic diseases compared with new patients. In other words, new patients have a lower burden of chronic disease compared with established patients. This is true regardless of which age group (0-17, 18-49, 50-64, 65+) was examined.

This comparison shows numbers only for 2013. Have we seen any changes in the prevalence of chronic disease for new patients, so far in 2014? For the most part, no. 

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Figure 3 compares chronic condition diagnosis rates for first quarter of 2013 to first quarter of 2014, for commercially insured patients between 18 and 64 years of age. On a national basis, neither new nor established patients saw an increase in diagnosis rates of chronic conditions.

We also examined chronic disease rates for different census regions (West, Midwest, Northeast, South); insurance types (commercial, Medicaid, Medicare), and practice size (1-5 providers, 6-20 providers, 21+ providers). In most of these clusters, the rate of chronic conditions for new patients did not increase between 2013 and 2014, any more so than the rate for established patients.

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A potential exception is in the South. Figure 4 shows that for commercially insured patients of small practices in the South, ages 18-64, the rate of diabetes and high blood pressure diagnosis increased between 2013 and 2014 for new patients but remained fairly flat for established patients. We should caution that further observation and analysis is needed to evaluate whether this pattern holds up throughout the year.

It appears then, that during the first quarter of 2014, the ACA did not result in a shift of the composition of new patients towards those with more chronic diseases. A possible exception is with small practices in the South.

As part of our ACAView initiative, we will continue to provide updates on the impact the ACA has on physician practices. In coming months, we will update this look at new patient visits and disease profiles, and explore such topics as the amount that new patients owe for their care and whether they honor their financial obligations. As always, we welcome your comments.

[1] We define new patients as one who has not visited a particular physician in two years or more.

Josh Gray (@JoshGray_hit) is vice president of athenaResearch.  Iyue Sung (@IyueSung) is the director of athenaResearch. 

29 replies »

  1. I’m curious if you have planned an update of this report. If so, when do you anticipate releasing updated findings?

  2. You see overuse of ED visits everywhere in the world, including Canada and Great Britain. This would suggest that you will not see an upswing in new patient visits from newly insured among the lower income tier population. They will continue to use the ED instead of an office visit in no small part because taking time off from work to visit a regular hour provider, even one that sees patients into the evening, is beyond the financial resources of families on the edge. Let alone the deductible, copay and other costs. These families know and count on the EDs inability to refuse treatment without upfront payment. When you do not have sick hours to use the lose of even 2-3 hours of work to get into the physician can mean the difference between covering your daily expenses and going into debt. In addition the higher copay, deductible and out of pocket of the lower tier insurance policies should serve as a deterrent to the already underserved patient using any more medical resources than they already consume. Any purely insurance scheme to make healthcare ‘more affordable’ is doomed to failure because all it does is shift the burden of the payment not actually reduce it. Sadly adding another layer to the profit picture is a sure way to continue to make healthcare more costly year over year.

  3. Ever heard of claims lag? Still do not know how many enrolled. Still do not know how many made initial payment. Still do not know how many paid second payment. This is after at least six months and could be nine months. On top of this, exchange folks have 90 day grace period. I suggest many to most exchange patient’s office visits not close to be reported. Seems a little premature to draw any conclusions, particularly positive ones.

  4. We will be looking at patient insurance coverage, which is an (imperfect) indicator of income. Beyond that we do not have patient income data. In theory we could use patient zip code as another surrogate but we currently do not have concrete plans to do so.

  5. Peter1- that’s entirely possible. There’s a significant front end cost exposure for a lot of services.

  6. Not sure Peter. The next wave of metrics will look at patient obligations for newly insured individuals. It will be interesting to see if average patient obligations for commercially insured new patients have changed from last year. It will also be interesting to compare patient obligations for new vs. established patients and for specialty vs. primary care.

    The trend that we have noticed in general over the last few years is an increase in patient obligations for specialty care and a bifurcation of patient obligation levels. Relative to a few years ago, a higher proportion of visits are free to the patient and a higher proportion are significant – say > = $40 out of pocket for the patient. That is especially true of specialty care.

  7. That would be implying that everyone signed up due to need…if that were the case we’d see major spikes today. I think the impact is rather long-term, not on a month-by-month basis. More people will indeed see providers, just not all at once.

  8. Great input Dr. Mike, thank you. We will take a closer look at new patient visits to specialists. In particular we will look at how many new Medicaid patients specialists are seeing and compare those numbers for Medicaid expansion states and non-expansion states.

  9. The lack of a surge is interesting because when previously uninsured people join Medicare, there is, in fact, a surge, and their costs remain higher for seven years because of the accumulated effect of untreated chronic diseases.

    The fact that this is a younger population might account for some of this.
    There HAS been an apparent drop in bad debts/free care, and a “surge” in Medicaid patients among the investor owned HOSPITALS. And, one would expect, as seen in Massachusetts, a sharp rise in ER use. That’s where I’d look first for evidence of a coverage expansion.

    The logical explanation might be the one several commenters have alluded to: not all that many of the 9 million enrolled were previously uninsured, and that while the administration has pushed the sign-up figures as evidence of success of their program, a lot of these folks were transitioning over from other forms of coverage.

  10. I agree with Dr. Mike on this. Lots of middle class people who lack health insurance but don’t qualify for Medicaid or Medicare will see primary care doctors and pay on a sliding scale basis. If they have a minor ailment that can be treated with regular (as opposed to specialty) drugs, they will be given free samples. It’s the expensive specialist care that gets deferred especially if it also involves treatment in a hospital setting such as elective surgery.

    There could be some pent-up demand for specialist care among this population. The good news, though, is that Medicare spending is coming been below expectations and has been for at least four years now. This population was not affected by job losses caused by the 2008-2009 recession. For the first seven months of fiscal 2014, Medicare spending was up only 0.7% despite a 2%-3% growth in enrollment so per capita spending is on track to decline again.

    To quote the late 1960’s band, Buffalo Springfield, “There’s something happening here; what it is ain’t exactly clear.” I think it could be several things all of which are positive for healthcare spending, care quality and cost-effectiveness not to mention federal finances.

  11. I do some work at an FQHC – large numbers of uninsured. The FQHC had several navigators on staff – big push to get people signed up. I can tell you from first hand experience that most of those signed up were already patients and will have each and every visit in 2014 coded with an established visit cpt.
    I can also say with certainty that what the uninsured were waiting for was not primary care – that they got at the FQHC at sliding scale rates – they were waiting for specialty care – to see a rheumatologist for their RA, an orthopedist to have their knees done, a pain specialist to have lumbar injections, etc.
    I realize that the FQHC represents a small subset of the uninsured and these patients experience and expectations may not mirror those of the general population.

  12. Thanks for your comment Dr. Mike.

    You’re right that not all new patients are newly insured. Unfortunately, for technical reasons, we cannot identify directly whether a patient is newly insured. But if patients who are newly insured (as a result of ACA’s individual mandate) visit providers in large numbers, we would expect to see an increase in the proportion total physician visits accounted for by new patients, since most of these newly insured patients are probably new to the provider. It is an indirect way to measure the impact of coverage expansion, but overall, we think, a reasonable one.

    We’re intrigued by your hypothesis that tracking new patient visits to specialists would allow us to “pick up signals” more easily. In future reports, we will look more closely at various specialties.

    Thanks again.

  13. Right!

    And you have to be careful about saying anything to the contrary of what those in the main stream media and/or those on the left think and say about the ACA – otherwise you’ll be labeled a ‘hater’ or a racist; even if you are correct.

  14. The problem here is that you take the White House numbers at face value. Who really knows how many have signed up? The Obama administration has become notorious for fudging many things, including numbers and statistics.

  15. Please forgive me if I did not read closely enough but it doesn’t seem clear from reading the article here that the research is even relevant to the ACA. New patient to a practice has not much at all to do with newly insured. And newly insured has not much to do with chronic illness. It is very highly unlikely that a patient with a chronic illness will be seen in 2014 with a 99201-5 code (i.e. new patient cpt code). They may have been seen infrequently, but it is very highly probably that after becoming newly insured that their first visit in 2014 will be billed with a 99211-5 code (i.e. established patient cpt code). It seems like tracking new patient visits to specialists would be a more sensitive indicator of the ACA’s impact.

  16. Exactly. And — how do you determine from the outside what is cost-effective behavior. For instance, what we may see from primary providers in risk situations is more visits, more contact, use of home monitoring devices, even home nurse visits — to drive down ER visits, surgery, hospitalizations and such. Very cost-effective across the system, but if you are looking solely at the primary provider, added cost.

    Tracking those kinds of cost effects is orders of magnitude more complex than we can probably do at this point, because it requires tracking the costs per patient in matched populations. This has only been done effectively as far as I know in small pilot programs.

    Al is all about how the data on preventing high-cost interventions is mostly a crock. I divine that he takes that to mean that prevention is a crock. I think it means our data mining has not gotten sophisticated enough to capture anything that we are not looking for.

  17. Joe –

    Thanks for your comment; you raise good questions.

    I think it will be a while before we are able to analyze the impact of risk assumption of the physicians in our network. The coverage expansion work (which I personally consider to be very important) will keep us occupied for some time. I agree that the questions you raise are critical. I would be especially interested in determining a tipping point for physician practice patterns. In other words, what percentage of a physician’s practice needs to be at risk before he or she practices more cost effectively? I would also be interested in understanding the evolution of cost-effectiveness. Do physicians become cost-effective across the board in relatively short order or do they focus on particular cost components (hospital, specialist consults, diagnostics) first and expand their cost effective behaviors gradually and incrementally over time?

  18. In the Medicare Advantage market, insurers generally tell us that they tend to see higher claims in the first year of eligibility than in the following few years possibly because of a prior lack of insurance, underinsurance or high deductible plans. If people know they will be eligible for Medicare in the near term, there is a lot of care that can be deferred until more generous coverage is available. Moreover, in any given year, the healthiest 50% of seniors account for only 4% of the program’s costs.

    For the rest of the population, as Joe Flower notes, many of the previously uninsured were probably healthy enough to conclude that purchasing insurance was not a good enough value relative to other claims on their limited resources, both necessary and discretionary. There probably aren’t that many people who were previously uninsured that need some expensive surgical procedure right after getting coverage and Medicaid already pays for about 40% of all births in the U.S.

    The issue of changes in payment models away from fee for service and the potential effect on how medical care is practiced and delivered is a separate matter. Personally, I’m optimistic that most of the changes that come from these new payment approaches will result in more cost-effective care and less redundant and unnecessary care.

  19. It is too early to tell. Combine the difficulties of the roll-out, the late surge of sign-ups, and the fact that most people in any population are not sick (and so don’t ned to run out an find a doctor the moment they get insurance, it’s not surprising that the first months of 2014 show no surge of new patients.

    Nor is it surprising if so far we are not seeing a higher percentage of chronically ill people. While the concern has been, how do we get better care for the millions of people with poorly treated chronic conditions, the effort has been to spread the risk by enrolling everybody. Nor is it surprising that the new folks skew a little healthier. If they were not insured before because “it cost too much,” you have to ask “too much for what?” If they were basically healthy, that greatly skews the cost/benefit analysis. Healthy people are far more likely to say, “Why would I pay all that money? I don’t need this.” So it is not news that the new folk skew somewhat healthier. That, in fact, is a sign of the ACA doing what it was meant to do, by spreading the risk pool wider.

    These numbers are great, I am glad you guys pulled them together. But they don’t begin to tell what will be the big story of this shifting moment in the history of healthcare, which is: The actual practice of medicine will change radically in response to not only the new people, but to the new ways of paying for their healthcare. Any of the myriad shifts we are beginning to see away from straight comprehensive fee-for-service will deeply undermine the business model of healthcare, leading to major changes in practice.

    How we track that change is an interesting question. Perhaps Josh and Iyue have some ideas.

  20. Hi Bubba,

    Thanks for the question.

    Unfortunately, we don’t have information on how long a patient has been insured by a particular payer.

    We think that if the individual mandate has a practical impact on providers, then we should be able to pick that up when we measure what’s happening with “new” patients.

  21. Agree with Al that a thoughtful analyses is welcomed and good. But to me the headline of this post pretty much makes a determination to an extreme. It could just have well as read: “Too Early to Tell if ACA Data Shows No Wave of Sick Patients” – yes, it’s too early to tell.

  22. And the ‘Obamacare haters’ would not be wrong. But to me, your inability to consider important variables that would surely impact the “analysis” presented in this post speaks volumes about the ignorance of Obamacare Kool Aid drinkers. (Goes both ways, eh?)

  23. Thanks Al. Our goal is to provide a stream of objective data to measure the effects of this complex legislation over an extended period of time. It is going to require some iteration/experimentation to figure out what is most useful.

  24. Agree or disagree with Obamacare, it is very refreshing to read thoughtful analyses that seem to be based on actual arithmetic. Thank you very much for showing that not everyone is as stupid as people in the wellness industry.

    I know you didn’t do a qualitative analysis but your speculations are thought-provoking. I look forward to the followup.

  25. Thanks for the question John.

    We have our hands full with the quantitative analysis so no plans right now to do qualitative work. One related analysis we would like to find time for is to determine what percentage of doctors see what percentage of new patients. Are a small number of docs taking on the lion’s share of new patients – or do many physicians take on a few? Would also be interesting to know how many docs take on very small numbers of new patients, i.e., are effectively closed.

  26. The Obamacare haters are going to argue that the reason there is no sign of new patients is that a).they’re still on hold waiting to get appointments and b). they’re still figuring out how to use their new insurance policies ..

    Are you looking at qualitative measures at all? I.E. individual physician reports of problems?

  27. Curious about your definition of “new patients” – as you plainly acknowledge, there’s going to be some confusion around “newly insured” and “new patients”

    Did you attempt to dig down to the newly insured at all? Is that data not available in your payer information on the athena payer side? I get that it gets very complicated very, very quickly when you start dealing with multiple payers and multiple pratices