Health Insurance Dynamics: Coverage, Gaps, and Financial Impacts

ANNA PAULSON: Good morning. I'm Anna Paulson, Executive Vice President and Director of Research here at the Chicago Fed. Thank you so much for joining us for Health Insurance Dynamics, Coverage Gaps, and Financial Impacts. Obtaining health insurance in the United States can be a complicated process. It can involve transitions between public and private coverage, and in some cases, loss of insurance coverage when someone loses their job.

Because most Americans access health insurance through an employer-sponsored plan, coverage is tied to labor market fluctuations. So what happens when insurance coverage is interrupted by job loss? During this event, you will hear from two economists who will present research on the impact of insurance transitions on individuals who become unemployed and how expanded Medicaid access impacts coverage after involuntary loss of private employer health insurance.

In the first presentation, Bhash Mazumder will explain the connection between health insurance and financial health. Then you'll hear from Shanthi Ramnath, who will discuss the effect of ACA's Medicaid expansion on insurance coverage dynamics following the sudden loss of coverage from an employer-sponsored plan and how the expansion of Medicaid impacts the duration of uninsurance following a separation from an employer plan.

The research presentations will be followed by a panel discussion, during which experts in the fields of medicine and public health will discuss the policy implications of insurance transitions and Medicaid access for workers and for their families. We are very pleased that you have joined us this morning, and now I'll hand it over to Bhash Mazumder.

BHASH MAZUMDER: Thanks so much, Anna. I'm very happy to be here as part of today's webinar on health dynamics. In this presentation, I'm going to focus on one aspect of health insurance, which is how it impacts financial health. So after giving you some background information on the topic, I'm going to go through some research over the last 10 to 15 years that's highlighted the importance of health insurance as a way of protecting financial health. And I'll be talking about some of my own papers on the issue, as well.

So when we talk about health insurance, we often focus on why we need it to make sure we can take care of our health. But one of the preeminent goals of insurance is actually about improving our financial security. First, it's because, without insurance, a sudden illness could lead to catastrophic medical expenses.

But even more generally, insurance can improve the overall welfare of the population by allowing people to insure against shocks that can impact their standard of living. So these points highlight the fact that coverage may be desirable even in the absence of any health-promoting effects of insurance.

The last point I'd say is that, while I'm going to focus on the financial benefits of insurance, obviously there are large costs to the public to providing insurance. But the point of this presentation is to highlight that there are some important financial benefits that may not be fully recognized.

So before discussing the impact of health insurance on financial security, I thought I would motivate the issue by talking about medical debt and how it continues to affect many Americans. So medical debt arises through so-called out-of-pocket expenses that individuals face for a number of reasons, including lack of health insurance, but also due to rising health costs and increased cost-sharing that consumers face through things like copays and deductibles.

When these bills go unpaid, they're sent to debt collectors and are referred to as medical debt. And in one recent study in the Journal of the American Medical Association, where the researchers used credit bureau data, they were able to highlight how pervasive medical debt actually is. They found that about 18% of Americans had medical debt and that the average amount was well over $400.

And some surveys over the years have shown that this is quite impactful. For example, one survey showed that nearly half of uninsured individuals with medical bills exhaust all of their savings, and about 40% forgo basic necessities.

So while medical debt is quite high, it's interesting to note that the average amounts have actually declined quite a bit from the early 2010s, when the average amounts were more like $800. This is what you can see in the bluish line on this figure. And you can also see that the turning point appears to be after 2014, when the Affordable Care Act kicked in with the expansion of Medicaid to cover more of the population. I'm going to return to this idea few more times in the presentation.

It's also worth noting that there's quite a lot of variation in medical debt depending on where you live. As you can see, there are broad swaths of the South of the US where medical debt is $1,000 or more in many places.

And if you look at this map, interestingly, it kind of foreshadows the effects of the Affordable Care Act, or ACA, that I'm going to talk about because you can make out whole states by the color of their counties. So for example, you can see here Wyoming that didn't expand Medicaid is almost entirely in red, whereas an example of a Southern state that did expand Medicaid, Arkansas, has virtually no red counties.

This figure shows that medical debt also depends quite a lot on the income level of the ZIP code you live in. Here, what I'm showing you is the average medical debt for each decile of the income distribution. So these are 10 percentile groupings of the income distribution. And what you could see is that medical debt is quite a bit lower at the very top of the income distribution. And this shows that medical debt is primarily an issue facing low and middle-income communities.

OK, so now what I'm going to do is I'm going to turn to the research on-- I'm going to review a set of studies that have tried to estimate what we call the causal effect of health insurance on financial measures. So these are studies that try to more carefully tease out these various effects.

So I'm going to do this first by quickly talking about some studies that took place before the Affordable Care Act was enacted. So one of the seminal research papers was studying the Oregon Medicaid Experiment, which took place in 2008. Here, a group of low-income adults were selected by a lottery for a chance to be enrolled in Medicaid. This is because Medicaid was oversubscribed there.

And so the researchers could actually compare those that won the lottery and were able to enroll in Medicaid versus those that didn't. And this research approach is kind of what's referred to as a randomized controlled trial, which is the gold standard for medical research because it avoids the problem of people who select to go into a program might have certain characteristics that would have caused them to have better or worse outcomes, even if they were never in the program.

And these researchers, using this approach, found that individuals were much less likely to have bills sent to collection agencies and less likely to report severe strains from medical bills if they were enrolled in Medicaid. However, the study was a bit small in scope, as they only were able to examine a more limited number of people who were eligible. And of course, the study only covered one state.

So I'm going to talk about one other early paper, and this is a paper I wrote with Sarah Miller, where we looked at the effects of the Massachusetts Health Reform. We thought this was a particularly useful examination because the Massachusetts Reform was, in many ways, a blueprint for the ACA that came afterwards.

The reform led to near-universal coverage in the state and had policies like the ACA had in terms of having subsidies for private insurance and expanded coverage of dependents, in addition to also expanding the state's Medicaid program. We found pretty striking effects of the program.

So here in this figure, I'm showing you what we call an event study plot showing how credit scores, in particular, evolved both before and after the reform. And here, the two vertical lines are showing the implementation period of the reform. And you could see, before the reform, credit scores were pretty flat. And then during the implementation period and afterwards, you see that credit scores rise quite markedly.

In this figure, I'm showing you an additional five outcomes, in addition to the credit score. And we found significant effects of the Massachusetts policy on lowering total debt levels, lowering total debt past due, decreasing bankruptcy rates, and reducing the amounts of medical debt sent to collection agencies. And when we wrote the paper, we were hoping that this would presage some of what could occur with the rollout of the Affordable Care Act.

So this brings us to the next era of studies, which were the studies that actually started to evaluate the effects of the ACA, shortly after it was implemented. And what's really interesting about the ACA from a research point of view was that we could now see what the effects of access to insurance for lower-income people were for a much larger set of states.

In addition, there was a Supreme Court ruling in 2012 that allowed states to choose whether or not they wanted to expand Medicaid, and so this provided additional variation for a research study. However, it's still not quite like a randomized controlled trial because, obviously, some states could differ in whether or not they wanted to expand Medicaid. So researchers had to make additional modifications to more closely try to attempt to identify causal effects.

So in one paper I wrote with my colleague, Luojia Hu, as well as several other coauthors, we tried to do exactly this kind of an analysis. And specifically, we used a statistical technique called a synthetic control, which basically combined various states that did not expand Medicaid and combined them in such a way that they look very similar to the actual states that expanded Medicaid in terms of financial outcomes before the Affordable Care Act was enacted.

And the bottom line of our study was that the typical Medicaid enrollee would have experienced a very large decline of over $1,000 in medical collections, with most of the action coming from individuals who would have otherwise had very high medical bills-- say, over $2,000. And there was a parallel study to ours that used data from a different credit bureau than what we did. And they also found that the ACA led to improvements in credit scores and reduced delinquencies, as well.

So these papers I mentioned looked at the states that expanded or didn't expand right away in 2014. In this more recent paper in Journal of the American Medical Association, the authors were able to look at states that subsequently expanded Medicaid, even after 2014, and then look at the longer-run effects in all the sets of states out to 2020.

And you could see, prior to 2014, all states were trending up in their medical debt levels. But after 2014, you could see in the blue line the states that never expanded Medicaid. You could see medical debt remained pretty high, and even in 2020, were around 90% of their 2013 levels. All of these lines are referenced relative to their 2013 levels.

You could see that the states that immediately expanded Medicaid-- this is the green line-- saw a pretty sharp reduction that continued through 2020. And medical debt levels, by then, were only about 50% of their levels in 2013. And finally, the states that expanded a bit later are shown in the orange line. And you can see that they fall somewhere in between the other two groups of states. And by 2020, their debt levels were about 30% reduced relative to their 2013 levels.

So, so far, everything I showed you is about expanding Medicaid. But there are some other studies that show similar effects of having other types of insurance-- for example, either looking at older people who get Medicaid when they reach the age of 65 or younger people that were allowed to stay on their parents' health insurance for longer.

And finally, in one of my papers with Sarah Miller, we had some really neat data where we were directly able to link individuals on Medicaid in Michigan with their credit bureau data. And one advantage of this is that we could see their actual medical history. And we were able to show, in this study, that the improvement in financial outcomes was really most striking for those who had chronic diseases who were most susceptible and needed insurance.

So that wraps up my discussion. I hope you've gotten a better sense of the very profound effects of medical debt on people's welfare and how access to health insurance has been demonstrated to reduce financial distress. Now I'll turn it over to my colleague Shanthi Ramnath.

SHANTHI RAMNATH: Thank you, Bosch. Let me share my screen here. OK. Well, great. Thank you so much. I will be presenting some coauthored work with Brad Heim, Ithai Lurie, and Elena Patel called Medicating Uninsurance-- Evidence from the Affordable Care Act.

And before I begin, just due to different coauthor affiliations, I just want to say that the views in this presentation are those of the authors and not necessarily those of the Council of Economic Advisors, the US Department of the Treasury, and I'll throw in Federal Reserve Bank of Chicago or the Federal Reserve System.

So just to give you a little motivation for our project, as Anna mentioned earlier, the US doesn't have single-payer insurance. And so because of that, transitions across different plans are going to be inevitable, including transitions into uninsurance. And most people in the US, around 60%, receive their health insurance from employer-sponsored plans.

And so that means that uninsurance and these transitions can be driven by just standard labor market dynamics. And of course, that's going to be even more of a risk during periods of macroeconomic turmoil.

So work by Blackburn, et al found that the Great Recession was associated with massive job loss, but also, as a result, a huge loss in health insurance coverage. And as we just heard from Bhash, the reason why we would care about uninsurance is that it's costly. It's associated with reduced utilization of health care, increased likelihood of adverse health outcomes, and of course, increased financial distress.

So prior to the Affordable Care Act, there were limited options in terms of purchasing coverage outside of employer plans. So there were private, small-group market plans, but those were often expensive and didn't cover things like maternity care. So they had little coverage.

In addition, there was public insurance, or Medicaid, which had been limited to very low-income parents and largely excluded childless adults. So what the ACA did is that it really broadened the access to health insurance generally, but in particular, to Medicaid. And because of that, it had-- because the income levels for accessing Medicaid had increased, it had a potential to provide stop-gap coverage to the general population.

And so in the past, empirical evidence had been mostly focused on the persistently low-income population and how Medicaid impacted them. But our paper is looking at, how did the ACA's expansion of Medicaid benefit the broader population, and particularly those who are transitorily low-income, maybe due to job loss? And in order to answer this question, we're going to use a novel administrative data set that's at-- to learn about these higher-frequency dynamics for people who are temporarily low-income.

So just to give you a bit more context about the Affordable Care Act generally, it was passed in 2010, and it was fully effective by 2014. Some of the major changes included that there was an employer mandate for larger employers to offer employees affordable health care. There was an individual mandate to purchase insurance, although some of these-- that, in particular, has been rolled back.

There was the Medicaid expansion, and then there were state-specific health insurance marketplaces where people could purchase nongroup insurance. And that was typically subsidized either through the premium tax credit or through cost-sharing reductions for people falling within a certain income range. So we're mostly focused on this Medicaid expansion part.

And just to give you some background there, the original intent of the Medicaid expansion was to cover people who had modified adjusted gross incomes below 138% of the federal poverty line. But in 2012, the Supreme Court ruled that states didn't have to do this expansion. And so it created a situation where some states expanded Medicaid, and others didn't.

So by 2016, which is the year I'm going to be focused on for our empirical work, 30 states had chosen to expand. And to date, 40 states have chosen to expand Medicaid, and 10 have still not. So just to give you a map of what this looks like, the darker green are the expansion states, and the lighter green are the nonexpansion states. And for much of our analysis, we're going to be focused on looking at differences between those two sets of states.

So in order to do our analysis, we're going to be using a novel set of data that comes from the IRS. So as part of the enforcing of compliance for, particularly, the individual mandate, the ACA required new reporting on an individual's health insurance coverage. So all of this information was reported on the forms 1095-A, B, and C. The people who purchased plans through the exchange would be reported on 1095-A, whereas employer plans and government plans were on 1095-B. And the large employer plans were on 1095-C.

So what this data includes is plan-level information that tells you all of the people who are covered on that plan and what months they're covered. And so this allows us to track, at high frequencies, different changes in coverage across types and into uninsurance. So the data for the exchange coverage started in 2014, and for the rest of the, plan started in 2015. And so that's what determined our year of analysis.

So in terms of our analysis sample, so we're going to be identifying the full population of policyholders in 2016 who had been well-attached to their plan. So that means they had 12 months of coverage prior. They were covered by an employer policy-- so they either had a small-employer or a large-employer plan. And then within that year, they had the plan in one month and then were no longer covered by that plan in the following month.

So that's going to identify our total sample. And that's around 11 million people or 1.4 million people each month who are losing coverage. And then we follow those people for two years after that coverage loss.

So with the tax data, we can then merge on information about their demographics-- so that includes age, gender, and marital status-- their geography-- so that's going to allow us to determine whether or not they live in an expansion state or a nonexpansion state. We're going to know their wage earnings and whether or not they received unemployment benefits.

And the reason we are interested in unemployment benefits is because it allows us to identify people who lost their job. So we're interested in people who lost their coverage due to involuntary job losses. And the tax data-- we are able to look at people who changed jobs due to having a different employer pay their wages, but we don't know why they would have changed their job.

And so what the unemployment benefits allows us to do is to focus on people who were terminated due to layoff, changes in business conditions, or business closure because those are the reasons that qualify you to claim unemployment benefits. And so we think of this sample as people who likely didn't choose to lose to leave their job.

And once we do that, we can characterize policyholders as unemployed if they received those benefits in the year of or the year after they separated from their plan. And that allows us to give people some leeway in terms of when they claim those benefits. So that's going to reduce our sample to around 1.6 million observations. But that's going to be the focal point of our analysis.

OK, so just to give you a sense of what the sample looks like, the first column shows you all of the people who separated from a policy in 2016. And the second column is that 15% of the first column who claimed unemployment benefits. And what we can see is that, relative to all policy holders, the unemployed group is less likely to be female and married.

They're also older. They earned lower wages. And importantly, they had longer durations of uninsurance. So that's what the spell length there is implying. So that gets at this idea that they're not choosing to change jobs and just picking up new coverage at their new job.

One thing I wanted to highlight is the fact that their wages in 2015-- so the year before they lost coverage-- was, for all policy holders, around $62,000 and for the unemployed was around $55,600. So just to give you a sense of what the federal poverty line was that year, for a family of four, it was around $24,300.

So the idea here is just to show you that this group that we're focusing on is not your typical Medicaid population that we think of when we think of who's eligible for Medicaid. And so for the rest of the analysis, we're going to focus on that second column of people.

OK, so this first graph is really just highlighting the different dynamics of health insurance coverage. So focusing on that unemployed sample, what we're graphing here is the share of people who have either an employer plan-- that's the dark green-- Medicaid exchange, or have no coverage-- and those go through the different colors-- from the first month after they lost their plan all the way to two years later.

And think what this really highlights is that this is a very dynamic process. So if you pick a point in time, it's going to have a very different answer depending on if you're one month after the coverage loss or 24 months after. And what we see is that the uninsurance declines from around 50% to 20% two years later. But there are still people who are uncovered. And remember, this is a group of people who had stable coverage prior to losing their job.

So the previous graph is looking at a point in time, and so it's not capturing the different flows into and out of the different sources of coverage. So what we have here is a six-month transition matrix. So the rows indicate where you started in a given month-- so you can either be uncovered, have employer coverage, marketplace coverage, or Medicaid-- and the columns indicate what type of coverage you have six months later.

And so what we see here is that there's high persistence within coverage types. So we're not seeing-- among the different types of coverage, the most likely type of coverage you'll have six months later is the one you started with, with employer coverage and Medicaid having the strongest persistence.

But another thing to note is that, among the different sources of coverage, the second most common transition is to an employer plan. And so this highlights the idea that maybe Medicaid is offering a safety net for people who lose their employer coverage.

OK, so in our paper, we also do a regression analysis where we can control for different factors. And the culmination of that analysis is just-- what we find is that living in a Medicaid expansion state is a strong factor for exiting that uninsurance. And we see that 31% are more likely to find coverage within one month of losing coverage if they live in an expansion state.

37% are more likely to find coverage over that full two-year period. And uninsurance spells are almost 2 and 1/2 months shorter, or 50% shorter, in expansion states relative to nonexpansion states. So Medicaid appears to be really driving that uninsurance dynamic.

We also look to see, what is the first source of coverage after losing your coverage? And we find that Medicaid is more likely to be the first source of coverage in an expansion state. So individuals are 13.2 percentage points more likely to use Medicaid as their new coverage. So this confirms that Medicaid is a real driving force in getting people out of uninsurance in expansion states.

So just to illustrate these different dynamics, we have, on the left, what the point in time coverage looks like in expansion states. And on the right, we have what that looks like in nonexpansion states.

And I think this picture is pretty striking in terms of what you see is that the share of uninsured is about 50% greater in nonexpansion states, even two years after losing coverage. And the gap is really made up for by Medicaid. So in every month, Medicaid coverage is about three times more likely in expansion states compared to nonexpansion states.

And finally, when we look at these six-month transitions by expansion state or nonexpansion state, we see that people remain in the state of uninsurance for longer in nonexpansion states. So 51% of people who start out as uncovered are remaining uncovered six months later compared to people living in expansion states.

OK, so I will stop there. But just to conclude, uninsurance is a long-standing problem in the US. And as we heard from Bhash, spells of uninsurance are costly because they can expose people to health and financial risks. What this paper does is it looks to say whether or not Medicaid can help with the broader population who are also at risk of losing their insurance due to just standard labor market dynamics.

And I think we do find that there is, in fact, an effect. And Medicaid increases the probability of finding coverage among this group of people who lose coverage simply due to standard labor market dynamics. And I think our results have implications for some of the ongoing debates about requiring work for eligibility of Medicaid.

But in general, we find that Medicaid provides a stop-gap coverage for people losing their jobs. And that could, in turn, help ease different sources of friction in the labor market and allow for people to find better job matches, as that's one concern that they don't have to worry about. So with that, I'll conclude, and I will pass it over to Kristen Broady, who is the Director of the Economic Mobility Project here at the Chicago Fed.

KRISTEN BROADY: Thank you, Bhash and Shanthi. I now have the pleasure of introducing our esteemed panel of experts. James Capretta is Senior Fellow and holds the Milton Friedman Chair at the American Enterprise Institute, where he studies health care, entitlement programs, and fiscal trends, and advanced economies. Angela Harper Mahome is an adult and child psychiatrist at Montrose Behavioral Health Hospital.

Anthony LoSasso is Professor and Chair of the Economics Department at DePaul University. And Robin Rudowitz is Vice President at the Kaiser Family Foundation and Director of the Program on Medicaid and the Uninsured. She oversees all work on Medicaid, SHIP, and low-income populations. And now I'm happy to introduce Lydia DePillis, economy reporter for The New York Times, who will serve as the moderator for the discussion. Lydia, I'll turn it over to you.

LYDIA DEPILLIS: Hi, everyone. Thank you so much for those paper presentations. We have an awesome panel to discuss them. And what we were hoping to do with this panel is put this in context and help you all understand a little bit more about what we've learned about the impact of the ACA, what, 14 years later now with these cool natural experiments in states that expanded and states that didn't. So let's get this rolling.

Just a broad question to you all who've studied these issues, and especially happy to have Angela as a practitioner who sees people who are affected by these changes, what did these papers add to the landscape of what we already knew? Do they change your thinking at all, or does it fit in with what we knew-- any initial thoughts?

ROBIN RUDOWITZ: I could jump in.

LYDIA DEPILLIS: Yeah, can I pick on you, Robin? That would be great.

ROBIN RUDOWITZ: Sure. Again, thank you for the presentations and glad to be here to participate. But I think the papers really bolster a lot of research that we have and continue to show the effects of expansion, both on uninsurance and coverage status, as well as financial security.

We have looked at well over 600 studies looking at expansion and compiled literature review over the years of what has-- the effects of Medicaid expansion that consistently show increases in coverage, reductions in uninsurance, increases in measures like access, utilization, as well as improvements in financial security and another whole metric looking at other economic effects for both providers and for states. And I think these two studies really bolster some of the findings that we've seen before in those two regards.

JAMES CAPRETTA: I'll jump in here. Thank you for inviting me to participate in this. It's a very-- I thought the presentations were excellent. I think the findings of both papers point to confirmation of a general view of the value of health insurance-- that is, it's very strong on-- has been very strong on additional financial protection.

People want health insurance because it does provide a level of financial protection. They know they're going to end up needing services or using services. And that's why they end up with uncollected bills sometimes because they need the services, or they go to get care, and without insurance, of course, those then pile up.

So I'm not surprised by the evidence showing that when public law comes through and offers, through, Medicaid-- it's essentially free insurance for the enrollees. It does improve their financial situation quite substantially.

I do think that the other part of the question is, what happens to their physical and mental health? I think it's clear from previous studies that were cited that mental health has always been clear-- that people's sense of well-being and stability is clearly associated with insurance and being protected against that requirement. Physical health has been all over the map, I must say, with studies showing all kinds of different conclusions over the years.

But having said that, I think it's starting to move more clearly in the direction with more studies showing over time, when more time is allowed to pass, that, of course, one would predict that enrollment in health insurance would have positive health effects, as well. And so I think, all in all, it's confirmation of the reasons that motivated passage of the law.

LYDIA DEPILLIS: Anthony, did you want to add anything to that?

ANTHONY LOSASSO: Yeah, I would just jump in. Thanks, also, for the invitation to be part of this-- two excellent papers, and panelists are outstanding. So I really feel privileged to be part of this group here.

I guess I'd say that these issues that are raised in the two papers are very complicated and nuanced because there are always a lot of moving parts. I always like to-- I always like to tell my students or anybody else that listens to me that health, health care, and health insurance are three different things. That's usually my day 1 lecture in health economics.

And there are linkages between them, but they must be looked at and explored very carefully. So I mean, I would just say that, to some degree, some of what-- at least for Bhash's presentation, some of that has kind of been overtaken by some recent findings that have just dropped in the-- less than a month ago where, actually, Ray Kluender, who he cites several times in his talk, and his colleagues conducted a randomized controlled trial of what happens when you alleviate people's medical debt.

And I think surprising many, including the authors themselves, what they found was that it had no effect on debt balances, on past-due debts, on future debts, on bankruptcy, no effects on credit score or access to credit. Actually, it increased the probability of having other medical bills sent to collections in the future. They followed these people over three years.

And then even surprising because one thing, as Jim mentioned, there's always-- there has been this notion that mental health is one of the things that is improved when insurance and the peace of mind that you get knowing that you're not on the hook for a potentially catastrophic health care spending event-- when that is removed, you have improvements in mental-- they didn't find that either.

So I mean, I do think that it raises a lot of questions. I mean, again, it was well done. They checked all the boxes, prespecified the endpoints prior to doing the randomization. They did everything that you're supposed to do in these types of studies. And so it does make me wonder, is medical debt the thing that we should be focused on?

And this is in no way to diminish, I think, the hardship that families are facing out there, the financial hardships that families are facing. But at the same time, I mean, I think you want to be able to diagnose the problem if we are collectively going to engage in solving it.

LYDIA DEPILLIS: Yeah, that was a really interesting study. But I wanted to ask, Angela, how do you see this in your patients, especially the transitions, like when someone loses a job, and they need to scramble to find some other way to get care. What does that look like?

ANGELA HARPER MAHOME: Yes, it's been huge. When people have been in between jobs, and they've been able to continue their insurance with Medicaid, they've been able to pay for medications. So people who had had insurance, when they're looking for a new job, they really need to continue the medications that they have been taking, whether for anxiety, depression, bipolar, or anything more serious. So it's been very helpful in their being able to continue treatments that they've had.

Also, when patients are unfunded for psychiatry, if they need psychiatric hospitalization, if they don't [AUDIO OUT] Medicaid or some sort of insurance, they have to go to a state hospital. And sometimes those hospitals don't have beds, and there's a long waiting list. So it affects their ability to be hospitalized. It affects their ability to find outpatient care.

But the main thing I've noticed is to continue medications because, oftentimes, if they're stable, a doctor will give them enough medication to last through a year if they had to. But they have to be able to afford that medication. So that's the biggest thing I've noticed.

LYDIA DEPILLIS: Yeah. Yeah, well, that would really explain a little bit why the mental health effects of having insurance seem to be real, and a continuation of insurance, even if-- yeah, as we're not sure what releasing medical debt results from noninsurance-- what effect that has.

So the effects on jobs are an interesting element of this because I think part of the theory for why the ACA would help is that, by somewhat detaching health insurance from employers, providing an option outside of employers, you could free people to take different jobs or take time away from a job if they needed to, and then perhaps allow them to find a better job if they have more time to do that.

And Shanthi said something at the end of her presentation, too, about implications for the idea of work requirements for Medicaid. If you require work to get this insurance that is now actually a safety net in between jobs when you get displaced for no fault of your own, then what is-- so what do you think this new research tells us about the implications of Medicaid expansion for work versus what we already know about that?

ROBIN RUDOWITZ: I'm happy to jump in and--

LYDIA DEPILLIS: Great.

ROBIN RUDOWITZ: --start that one. I think it's a really complex question. And there's a lot of intersection, obviously, between Medicaid and employment. I just want to start by saying, the large majority of people, Medicaid enrollees, adults, are working. So six in 10 are working. And among those who are not working, many face barriers to work, either for caregiving responsibilities, they're in school, or they say they have a disability, even though they don't qualify on the basis of disability.

So there's a group of people that are working, but working in low-wage jobs so that they are eligible-- continue to be eligible for Medicaid coverage because they meet the income requirements, particularly in expansion states. And I just want to reemphasize some of the points that were made in the presentation that, prior to the ACA, many workers in these low-wage jobs were uninsured because they just didn't have an option for affordable coverage.

And if they did have an option, that coverage was typically too expensive. So the options created by the ACA, both through Medicaid expansion and through the marketplaces, really created new options for coverage for many people who did not have coverage.

We also know that typically during economic downturns, when people lose income and their jobs, more people become eligible and qualify. And I think we have seen this recent experiment during the pandemic. It was really the first major economic downturn since the Affordable Care Act was in place. And things functioned, and Medicaid functioned as it was intended in that many individuals who lost their job and lost income then became eligible for the program and enrolled.

And as a result, the uninsurance rate in the country hit a record low from some policy changes and the fact that these programs were in place. So I do think that there's this economic effect. And now we're seeing this, as the unwinding happens, what happens to individuals who might lose their Medicaid coverage as they face these renewals?

And we are seeing that there's large disenrollment rates. We are still waiting to figure out what that means. We just did a survey, and many people are being disenrolled from coverage. About 23% of the people who are disenrolled are uninsured, but there's also a set of people who have other coverage. So maybe they got a job in that period of protected coverage and now may go back to or have employer-sponsored coverage.

LYDIA DEPILLIS: Interesting. Other thoughts on the labor market implications here?

ANTHONY LOSASSO: I would just add-- it's excellent points there. I mean, one of the things that has been a long-running concern in the area of public health insurance expansions is the idea that, when a public insurance option is available, it might crowd out, to use the terminology, the privately available option.

And depending on one's perspective on that, I mean, that might-- as you said, Lydia, that might, afford one greater ability to perhaps not be job-locked, which was kind of the implication of what you were talking about, in a particular job because you may be able to more easily slide into a new job. And so we can disagree, I suppose, on the relative merits of that.

But I think the crowd-out issue had been studied quite extensively by economists 20-plus years ago. I contributed to that literature myself. And generally, the finding was that roughly half of the individuals who gained public coverage actually had the option and were effectively crowded out of a private health insurance option.

And so it's, again, not clear whether this is good or bad. But it just speaks to the potential efficiencies of the program design. If there's already a private option that's meeting the needs for half or more of the people who gain public coverage, well, I mean, is the program, A, moving the needle against uninsured, and then, B, is it necessarily as well-targeted as it could or should be?

LYDIA DEPILLIS: And then there's a question of private cost to people for those different types of coverage.

ANTHONY LOSASSO: Well, things cost money. I mean, we don't necessarily look to the government to necessarily provide everything that we might need or want. So I mean, yes, but that probably gets into a bigger question about what the optimal role is of government vis-a-vis the private sector.

JAMES CAPRETTA: Remember, of course-- just to add one more comment to that, which is that if you substitute public insurance for private insurance, somebody's paying, or they're borrowing it. So it's the federal government is paying a matching rate to the states. The states then also have their own costs, and that comes from tax-funded support.

So the question is, how much-- public money will be going in and then the benefits to society generally from building the safety net a certain way versus another way. And those are the things that get weighed by our policymakers when they're deciding these questions, which is what we want them to do. And they have to balance competing objectives.

One other item that they would consider, probably-- it's been coming up recently-- is incentives for work, that, depending on the design of these various programs, you want to provide strong support for people. At the same time, you're also encouraging them to work, if you can, and if they can. So like I said, and as Anthony started out with at the top, all of these things are connected and complicated. And you have to decide how to weigh them and prioritize them.

LYDIA DEPILLIS: Yeah. Angela, did you have thoughts on the interaction between work, insurance, health care, et cetera?

ANGELA HARPER MAHOME: Yes, definitely, because I totally-- especially, again, with mental health care, having insurance is crucial for those who need treatment so that they can be able to work or to look for a job. And also with respect to the cost, if a person needs mental health care, and it gets delayed, or deferred, or they don't receive it, they're more likely to need hospitalization or things that are a bigger financial burden to the system.

So it's all related. And again, it's hard for us to determine if they would be eligible to work if they're not receiving the treatment that they need. So it's totally related.

LYDIA DEPILLIS: Yeah. And have you seen that happen, like people fall out of insurance and lose their connection to health care and connection to their medications? And how does that-- I mean, is there a really direct connection between their ability to work?

ANGELA HARPER MAHOME: Yes. I've seen it happen, but it's been happening less, which is a good thing. And even in the transition for those who graduate from college and graduate school, but they're in between jobs, or they're studying for the bar, and things of the sort, it's been huge in their ability to stay on their medications so that they can prepare for the next step in their career.

But being in between jobs-- it's been huge for people to stay on their medication so they can stay stable and look for the job, have a motivation to look for a job. So yeah, it's been a positive change that people have been better able to stay on their medication.

LYDIA DEPILLIS: Yeah. Yeah, and I wonder what it would look like in a nonexpansion state. You're sitting in Illinois, right? And are there particular demographics that we think that having this connective tissue is useful for? Clearly, people who are experiencing mental health difficulties, but do we know anything more about the distribution of-- both of these phenomena that our researchers identified-- for whom that is most important?

ROBIN RUDOWITZ: I mean, I could jump in again. Certainly, health insurance coverage allow-- we know from lots of research that individuals that have coverage are much more likely to get care when they need it, have lower out-of-pocket costs, have a usual source of care, relative to individuals who are uninsured. But of course, individuals with chronic conditions, particularly physical and mental health conditions, are much more at risk with gaps in coverage.

Again, we're seeing this all play out now with this Medicaid unwinding as individuals come up for their renewal. And we're talking to people and talking to try to understand what is happening-- so if they're no longer eligible for Medicaid, if they're able to transition to other coverage, or if they wind up uninsured. And the process is quite stressful for individuals at the prospect of losing their coverage.

And for individuals who have been disenrolled, when we've spoken to people, they are at risk of major disruptions to care, and as was mentioned, particularly disruptions in course of treatment and medications, if they're not able to afford those out of pocket.

LYDIA DEPILLIS: Yeah. Well, Anthony, I mean, do you-- you were talking before about crowd-out. And I'm wondering if you think that the last 14 years of the ACA have left the private insurance system in a less robust state so that, when people are in the situation of getting disenrolled, for example, there isn't as good a set of options? Or was there not a good set of options before for that?

ANTHONY LOSASSO: No, I think there clearly-- I mean, one thing-- and this has been pointed out-- that the Affordable Care Act certainly opened up the options available to individuals in the form of the Medicaid expansions that we've talked a lot about and the exchanges, which, again, have heavy subsidies that we, taxpayers, do pay for.

And so where It probably fell short-- and I don't know that I'd get a lot of push-back from anybody on this-- is that the Affordable Care Act did not necessarily make health care more affordable in any broader sense. So in terms of-- we used to talk-- 14 years ago, the expression was "bending the cost curve." It hasn't been bent. It's been bent probably upward, in fact, and not downward, which was the hope. And we have pretty strong support on that.

The other thing I just wanted to add, just on the issue of the Medicaid expansions and the consequences of either enrollment or disenrollment, is that Bhash did bring up the excellent Oregon Health Insurance Experiment from, admittedly, pre-ACA time, so late 2000s. And it is important to note that they looked pretty hard, and they had the benefit of randomization through a lottery system, and there were really no-- the only health effects that they did find were improvements in mental health.

So that's a point. However, those mental health improvements actually manifested before anybody had any contact with care. So again, that's not nothing. Getting that psychic relief of not having to face the potential risk of a potentially catastrophic health spending event-- that's what insurance is generally good at doing.

So I just want to point out that the connection to health care in that, I guess, is just a little more tenuous. And I think we have to have a little more humility here about just what we can actually hope to accomplish, given that health insurance, health care, and health are three very different things with only limited linkages between them.

JAMES CAPRETTA: I'll just say one more thing before we get out of time here. I wanted to make sure I got this in, which is that I think the other aspect of the Affordable Care Act that maybe the next stage of change down the road can try to address is that-- and maybe they wanted to, but it was not possible at the time-- is that there's still a lot of disconnects between these three pipelines into coverage. So a lot of our trouble here is churn-- people's life situations changing and then not having some stable insurance for at least some period of time.

So if your income is low during a calendar year, maybe that should allow you to get on Medicaid instead of a month-to-month kind of possibility of review, which is pretty frequent and a little bit absurd, frankly. Medicaid is never going to be able to check on everybody month-to-month.

So there probably needs to be some more clearer system of when you become eligible based on what income look-back puts you into a coverage option, and then allow you to stay there for maybe at least a year. And then you can be re-evaluated to go into the other pipelines-- either employer plan or ACA coverage. I think that might add to some of the stability and comfort that people know they're going to be in some kind of coverage, at least for some period of time.

One other thing I'd say is we're going to have a Medicaid unwinding one way or another because, essentially, the numbers grew in part because there was no income checks going on for a long period. And so it had to get revisited. And I know it's difficult, but the public system was going to have to reset the system after the pandemic.

LYDIA DEPILLIS: Yeah.

ANGELA HARPER MAHOME: I just wanted to jump in and say, having worked at a safety net hospital-- not a psych hospital, but just a general-- patients having Medicaid made the difference. They could follow up for their health appointments instead of coming to the emergency room to get routine care, which is a very big burden on the system, as well. So I do feel like it may not be a perfectly link, but there's a definite benefit to the expanded care.

LYDIA DEPILLIS: Any last words from Robin before we hand this back to Kristen?

ROBIN RUDOWITZ: We didn't really talk about work requirements. We just alluded to them. But I will say that there is a lot of research that shows that work requirements don't increase employment for Medicaid, but they do result in declines in enrollment. So while there's an intersection, work requirements have not been proven to increase employment.

LYDIA DEPILLIS: Got it. All right. Kristen, we are done. Thank you all, and thanks to the audience.

KRISTEN BROADY: Thank you so much to our presenters, Bhash Mazumder and Shanthi Ramnath, for sharing their research. I'd also like to thank our panelists and moderator for a very informative policy discussion about health insurance, how it impacts our finances, who pays for it, the different types of insurance. I certainly learned a lot. I hope you did, as well.

We'll be sending a post-event survey, so please be on the lookout for it. We value your feedback, and the findings will help us shape future programs. A recording of the event and a summary will be available on chicagofed.org/mobility in the next few days.

We'd also like for you to check out the papers and the policy briefs for the papers that were presented. They'll be on our website. And we hope that you'll join us for future Economic Mobility Project events. Thank you so much, and have a great rest of your day.