By Salam Abdus and Steven C. Hill
Health Affairs, May 2017

Abstract

Recent expansions in health insurance coverage have raised concerns about health care providers’ capacity to supply additional services and how that may have affected access to care for people who were already insured. When we examined data for the period 2008–14 from the Medical Expenditure Panel Survey, we found no consistent evidence that increases in the proportions of adults with insurance at the local-area level affected access to care for adults residing in the same areas who already had, and continued to have, insurance. This lack of an apparent relationship held true across eight measures of access, which included receipt of preventive care. It also held true among two adult subpopulations that may have been at greater risk for compromised access: people residing in health care professional shortage areas and Medicaid beneficiaries.

From the Introduction

The ways in which population-level increases in insurance coverage affected people who were already insured during the recent insurance expansions depend on three key factors. The first is providers’ capacity and willingness to offer more visits and supply additional services. If providers had excess capacity, then increased demand could easily be met, but many observers have expressed concern that providers could not supply enough additional services—especially primary care services. Concern about reduced access may be most relevant in medically underserved areas—that is, areas already facing shortages of primary care providers.

The second factor is the extent to which the provider market is segmented by the types of insurance patients carry, if any. Some providers, such as federally qualified health centers, primarily serve patients with public insurance and the uninsured. More generally, providers are less likely to accept Medicaid patients than Medicare and privately insured patients. Thus, people who had Medicaid before the ACA-related Medicaid expansions might have been at greater risk of reduced access, especially because Medicaid enrollment increased 25 percent from 2013 to 2014 in states that expanded eligibility for Medicaid.

The third factor is the effects of ACA provisions intended to increase health care capacity. In particular, the act provided funding for expanding the capacity of federally qualified health centers; training more physicians, mid-level practitioners, and nurses; and encouraging more providers to work in primary care and in underserved areas. It also temporarily increased Medicaid payments for some services supplied by primary care providers. The ACA set its capacity-building activities in motion before the biggest eligibility expansions occurred, whereas Massachusetts did not begin to address provider capacity problems until after its insurance expansion. Thus, the efforts to increase supply built into the ACA had the potential to mitigate negative spillovers such as those seen in Massachusetts. Moreover, many of the ACA provisions were designed to mitigate negative spillovers among the groups most likely to be negatively affected: people in medically underserved areas and Medicaid beneficiaries.

From the Discussion

We found no consistent evidence that increased local-area insurance coverage rates reduced access to care among the continuously insured. This remained true even when we restricted our sample to adults residing in geographic Health Professional Shortage Areas or to adults continuously insured by Medicaid.

Our results are consistent with the possibility that funding in the ACA to increase provider capacity mitigated potential negative spillovers, as intended. While we know of no rigorous evaluations of these provisions, data suggest that capacity did expand. ACA funding was used to add sites of care and other expansions of community health center capacity, which was associated with serving more patients. ACA funding for training might have contributed to growth in the number of midlevel practitioners, who can help meet increased demand for primary care. From 2009 to 2014 the number of employed physician assistants rose 19 percent, and from 2012 to 2014 the number of employed nurse practitioners rose 15 percent. ACA funding to expand capacity began to be disbursed shortly after the act passed, before the major insurance eligibility expansions in 2014.

From the Conclusion

Despite concerns, increasing rates of insurance coverage did not appear to reduce access to care among the continuously insured.

http://content.healthaffairs.org…

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Comment:

By Don McCanne, M.D.

One concern about the increases in the numbers of people insured as a result of implementation of the Affordable Care Act was that people already insured might find that their access to care became impaired because the increased demand for care might overload the delivery system. However, measures to increase capacity in the system, such as expansion of community health centers and increased training of health care professionals helped to alleviate that concern. Thus, “increasing rates of insurance coverage did not appear to reduce access to care among the continuously insured.”

Well designed health care reform includes giving attention to system capacity. Central planning along with separate budgeting of capital improvements is designed to ensure that capacity is adequate and equitably distributed. People who are satisfied with their current insurance need not be concerned that expanding coverage to include everyone – as in an improved Medicare for all – would result in impaired access. Not only would access be assured, they would have better coverage than the best of current plans in the private sector.

NBER Working Paper No. 23353; Cost of Service Regulation in U.S. Health Care: Minimum Medical Loss Ratios

By Steve Cicala, Ethan M.J. Lieber, and Victoria Marone
National Bureau of Economic Research, April 2017

Abstract

In health insurance markets, an insurer’s Medical Loss Ratio (MLR) is the share of premiums spent on medical claims. As part of the goal of reducing the cost of health care coverage, the Affordable Care Act introduced minimum MLR provisions for all health insurance sold in fully- insured commercial markets as of 2011, thereby explicitly capping insurer profit margins, but not levels. This cap was binding for many insurers, with over $1 billion of rebates paid in the first year of implementation. We model this constraint imposed upon a monopolistic insurer, and derive distortions analogous to those created under cost of service regulation. We test the implications of the model empirically using administrative data from 2005–2013, with insurers persistently above the minimum MLR threshold serving as the control group in a difference-in- difference design. We find that rather than resulting in reduced premiums, claims costs increased nearly one-for-one with distance below the regulatory threshold, 7% in the individual market, and 2% in the group market.

From the Introduction

At its simplest level, this paper observes that our hypothetical insurer with $100 in premium revenue and $79 in claims finds it must bear the full administrative cost of keeping expenditures below $80, but reaps none of the rewards. That is, minimum MLR requirements encourage higher costs, not lower. We draw the direct parallel between MLR regulation and cost of service regulation, and show empirically that the 80/20 rule has, indeed, substantially increased insurers’ medical expenditures. While perhaps obvious ex post, this connection has not been established (nor estimated) to date.

From the Conclusion

This paper connects regulations of actuarial fairness to cost of service regulation, and uses the recently-implemented ‘80/20’ rule in the ACA to estimate the role these forces play in the determination of claims costs and premiums in the market for health insurance. The 80/20 rule requires health insurers in the commercial, fully-insured market to keep the share of their premium revenue spent on medical claims, known as the Medical Loss Ratio (MLR), above a minimum threshold, and to rebate the difference to customers if they fall short of this minimum. We find robust evidence that insurers increased their MLRs to comply with the regulation, and that this increase came largely by increases in claims costs.

We find that insurers in the individual market were most strongly impacted by the 80/20 rule, with affected insurers increasing their claims costs 7% on average and as much as 11% after two years of adjustment. We find that the rule also resulted in higher MLRs and claims costs in the group market, though the regulation was less binding in this segment. We generally find that the magnitude of the increase in claims costs scales with the initial distance from the minimum threshold. These results stand in stark contrast to the original intention of the rule: lower premiums. We do not find that insurers lowered premiums as a means to increase their MLR.

Instead, it is more likely that insurers raised their claims costs from a combination of more comprehensive coverage and reduced cost-containment effort, such as negotiations with providers or claims utilization management practices.

http://www.nber.org…

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Quote of the Day: AHIP on medical loss ratios

By Don McCanne, M.D.
Physicians for a National Health Program, July 26, 2010

Excerpt from Comment:

An extremely important unintended consequence of fixed medical loss ratios has been mentioned here before, but seems to have escaped the mainstream media, so it is being repeated: Once the MLR rules are established, the primary method by which insurers can increase the services they sell us, while increasing their profits, is by increasing gross revenues, since they are guaranteed a fixed percentage of those revenues. The most effective way to increase gross revenues is to increase the amount of health care services authorized and paid for.

If the insurers change provider incentives to double the amount of health care that is being delivered, they can double their own total revenues, keeping even more as profit because of the smaller marginal administrative costs of paying for more care. This incentive of the insurers to increase total health care spending is the exact opposite of the reform goal of slowing future health care cost increases.

All of this is good business. But that’s the problem. Our elected representatives chose a business model to finance health care when what we desperately need is a service model.

“Medical loss ratio” is a term that needs to be moved into the history books of failed policy concepts. Instead, we need our own public service model – an improved Medicare for everyone.

https://www.pnhp.org…

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Comment:

By Don McCanne, M.D.

Paying for health care is a loss for insurers. They get to keep for their administrative costs and profits whatever they do not spend on health care. In crafting the Affordable Care Act our legislators surmised that they could limit the administrative waste and excess profits by requiring that at least 80 percent of premiums be used for health care for individual plans and 85 percent for small group plans – the medical loss ratio. If you were an insurer, think of the opportunity this offers.

In previous messages it was pointed out that the more the insurers pay out in health benefits, the more they can expand their administrative expenses and especially their profits. They get to keep 15 to 20 percent of the premiums.

How do you pay out more in health benefits? Simple. Negotiate higher prices with physicians and hospitals. Maximize benefits covered. Authorize more care; be very conservative with rejecting prior authorization requests. Avoid adjusting claims and avoid claim denials. Do not investigate over-utilization or frank health care fraud. Then have your actuaries calculate the premiums to include 15 to 20 percent over the inflated health care spending. Make that a little bit over 15 to 20 percent which will then have to be refunded but will ensure that the full padded margin is received.

As with so many policy flaws of the Affordable Care Act that we have reported here, there is some disbelief that the insurers would do that. But isn’t that the way markets work? Maximize revenues and profits? There is nothing illegal here.

Today’s report indicates that, guess what, “insurers raised their claims costs from a combination of more comprehensive coverage and reduced cost-containment effort, such as negotiations with providers or claims utilization management practices.” Thus the insurers defeated the MLR rule that was intended to reduce premiums.

From a 2010 Quote of the Day:

“If the insurers change provider incentives to double the amount of health care that is being delivered, they can double their own total revenues, keeping even more as profit because of the smaller marginal administrative costs of paying for more care. This incentive of the insurers to increase total health care spending is the exact opposite of the reform goal of slowing future health care cost increases.

“All of this is good business. But that’s the problem. Our elected representatives chose a business model to finance health care when what we desperately need is a service model.

“‘Medical loss ratio’ is a term that needs to be moved into the history books of failed policy concepts. Instead, we need our own public service model – an improved Medicare for everyone.”

NBER Working Paper 23329; How the Growing Gap in Life Expectancy May Affect Retirement Benefits and Reforms

By Alan J. Auerbach, Kerwin K. Charles, Courtney C. Coile, William Gale, Dana Goldman, Ronald Lee, Charles M. Lucas, Peter R. Orszag, Louise M. Sheiner, Bryan Tysinger, David N. Weil, Justin Wolfers, and Rebeca Wong
National Bureau of Economic Research, April 2017

(Note: These excerpts from this paper are quite wonkish so you may want to skim down to the Comment, and then return to read this only if you are still interested in the specifics.)

ABSTRACT

Older Americans have experienced dramatic gains in life expectancy in recent decades, but an emerging literature reveals that these gains are accumulating mostly to those at the top of the income distribution. We explore how growing inequality in life expectancy affects lifetime benefits from Social Security, Medicare, and other programs and how this phenomenon interacts with possible program reforms. We first project that life expectancy at age 50 for males in the two highest income quintiles will rise by 7 to 8 years between the 1930 and 1960 birth cohorts, but that the two lowest income quintiles will experience little to no increase over that time period. This divergence in life expectancy will cause the gap between average lifetime program benefits received by men in the highest and lowest quintiles to widen by $130,000 (in $2009) over this period. Finally we simulate the effect of Social Security reforms such as raising the normal retirement age and changing the benefit formula to see whether they mitigate or enhance the reduced progressivity resulting from the widening gap in life expectancy.

From the Introduction

We have several major findings. First, consistent with other recent studies, we confirm that life expectancy at older ages has been rising fastest for the highest socioeconomic groups. For those born in 1930, the gap in life expectancy at age 50 between males in the bottom 20 percent and top 20 percent of lifetime income is 5 years, according to our estimates. For males born 30 years later (in 1960), the projected gap at age 50 between the highest and lowest quintiles widens to almost 13 years, an increase of nearly 8 years. Second, we find that there is a growing gap by lifetime income in projected lifetime benefits from programs such as Social Security and Medicare. For the 1930 cohort, the present value of lifetime benefits at age 50 is roughly equal for those in the highest and lowest quintile of lifetime income, as those at the top receive more from Social Security while those at the bottom receive more from Disability Insurance, Supplemental Security Income, and Medicaid. For the 1960 cohort, by contrast, there is a $130,000 gap in benefits between the highest and lowest quintiles, as those in the top quintile are increasingly likely to receive benefits over longer periods of time, relative to those at the bottom. Finally, we show that a number of commonly-discussed Social Security reforms would make the program more progressive, although their impact on progressivity tends to be small compared to the changes arising due to differential changes in life expectancy.

Policy Reform Simulations

Our final goal is to analyze policy reforms to determine how they would affect the progressivity of government programs and interact with projected changes in life expectancy. The reforms we simulate – five that affect Social Security and one that affects Medicare – were chosen because they are either frequently mentioned in policy discussions or meet objectives with which many stakeholders would agree. Unfortunately, the structure of the FEM (Future Elderly Model) made it impossible to simulate certain reforms, such as raising the Social Security maximum taxable earnings amount. The policy simulations we study include: raising the Social Security EEA (Early Eligibility Age) by 2 years (to age 64), raising the Social Security NRA (Normal Retirement Age) by 3 years (to age 70); reducing the cost-of- living adjustment applied to benefits by 0.2 percent per year; reducing the top PIA factor by one- third (from a 15% to 10% rate); reducing the top PIA factor (Primary Insurance Amount) to 0 above median AIME (Average Indexed Monthly Earnings); and raising the Medicare eligibility age by 2 years (to age 67).

There are two mechanisms by which a policy change may translate into change in
benefits. The first, which can be characterized as the “mechanical effect,” results directly from the policy change, holding behavior constant. For example, if the NRA were raised by 3 years, a worker claiming benefits at age 67 would see the monthly benefit amount fall from 100 percent of the PIA to 80 percent, experiencing a 20 percent reduction in benefits. The second channel, which can be characterized as the “behavioral effect,” results from changes in individual behavior in response to the policy. For example, the individual may claim Social Security later, work longer, or be more likely to claim DI. These responses can be captured by the FEM.

We show results for all reforms on Table 4, reporting only the change in net benefits as a fraction of inclusive wealth for brevity. We begin with the increase in the EEA. At first glance, it might seem that this policy would have little effect on the present value of benefits given the common belief that the actuarial adjustment is roughly actuarially fair. We find that this reform raises net benefits as a share of wealth by 0.1 for males in the lowest quintile under the 1960 mortality regime and by 0.4 for males in the highest quintile. Under our assumptions, the actuarial adjustment for delayed claiming is slightly more than fair, so when individuals are forced to claim later by this policy change, lifetime benefits increase, particularly for high- income individuals who have longer life expectancies. The policy change is thus mildly regressive, although its effects are fairly small.

Raising the NRA has a much bigger effect – we estimate that lifetime Social Security benefits fall by $30,000 (or 25% of the pre-reform value) for the lowest quintile of males in the 1960 mortality regime and by $59,000 (20%) for the highest quintile. The percentage drop need not be the same in the two quintiles because the behavioral response of the two groups to the policy change (captured by the FEM) could differ; also, the same response – say, postponing retirement and claiming by one year – could have a different effect on lifetime benefits because of differences in life expectancy. As low income males experience the larger percentage drop in benefits, this policy might be considered regressive. Yet the policy change reduces benefits as a share of wealth by 4.8 percent for males in the lowest quintile and by 5.2 percent for males in the highest quintile, as the larger dollar loss for high income males ends up being a slightly larger share of their lifetime wealth (as captured by our inclusive wealth measure). Viewed by this metric, the policy change is progressive. Thus, the progressivity of this policy change is somewhat sensitive to the particular measure used.

Reducing the cost-of-living adjustment (COLA) has a modest effect on benefits, reducing them by 0.4 percent of wealth for males in the lowest quintile under the 1960 mortality regime and by 0.6 percent for males in the highest quintile. The larger effect for high income men is due to their longer life expectancy, since the effect of a lower COLA is cumulative over time. Reducing the top PIA factor by one-third has a fairly modest impact of 0.1 percent of wealth for low-income males and 0.3 percent for high-income males; the larger effect on high-income males is expected, since the top PIA factor applies only to earnings past the second bend point of AIME (e.g., at higher earning levels). A related policy with a much bigger impact is reducing the top factor to zero and moving the second bendpoint to the median of AIME. This policy, which would reduce benefits for the top half of earners, is chosen an as example of a substantial benefit cut designed to have a smaller impact on low earners. We find that this policy would reduce benefits as a share of wealth by 1.1 percent for males in the lowest quintile and by 3.4 percent for men in the highest quintile. Finally, we simulate raising the Medicare eligibility age. This policy has a fairly similar effect across quintiles in dollar terms, reducing lifetime Medicare benefits by $8,000 for low-income males in the 1960 mortality regime and by $7,000 for high- income males. Measured as a share of inclusive wealth, there is a loss of 1.4 percent for low- income males and 0.5 percent for high-income males, indicating a regressive policy.

Overall, most of these policy changes would make overall net benefits more progressive. The exceptions are raising the EEA or the Medicare eligibility age, which make benefits less progressive. When compared to the changes in progressivity occurring due to mortality trends, however, the effect of these policies on progressivity is generally fairly small. For example, consider the policy reducing the top PIA factor to zero above median AIME, which is the most progressive of the policies we simulated. Absent any policy change, the gap in lifetime Social Security benefits between males in the highest and lowest income quintiles grows from $103,000 in the 1930 mortality regime to $173,000 in the 1960 mortality regime. Implementing this policy would eliminate 60 percent of the increase, so that the gap under the 1960 regime would be $131,000. This illustrates the scale of the policy reform that would be needed to counteract the changes in progressivity of government benefit programs that we project are occurring due to the widening gap in life expectancy.

From the Discussion

Life expectancy at older ages has been growing steadily in the U.S. over the past several decades. Yet there is growing awareness that these gains are not being shared equally. Our study confirms a substantial increase in the life expectancy gap between those with higher and lower income. For men, we project that the gap in life expectancy at age 50 between males in the highest and lowest quintiles of lifetime income will grow from 5 years for the 1930 cohort to nearly 13 years for the 1960 cohort. Estimates for women (from Committee, 2015) are somewhat less reliable, but show a similar if not larger change over time.

We also assess the effects of the growing gap in life expectancies among older adults on the major entitlement programs. The larger life expectancy gap means that higher-income people will increasingly collect Social Security, Medicare, and other benefits over more years than will lower-income people. We estimate the value of net lifetime benefits for different income groups from Social Security, Disability Insurance, Supplemental Security Income, Medicare, and Medicaid. Our estimates suggest that these net lifetime benefits are becoming significantly less progressive over time because of the disproportionate life expectancy gains among higher-income adults. The changes in life expectancy between the 1930 and 1960 mortality regimes generate an increase in benefits equivalent to an increase of 6.9 percent of wealth (measured at age 50) for men in the highest income quintile, while benefits for men in the lowest income quintile are essentially unchanged. While we caution that one cannot rely too heavily on the specific numbers we estimate, since these are projections that necessarily rely on assumptions and our analysis does not allow us to construct confidence intervals around these projections, our results clearly indicate that lifetime benefits are increasingly accruing to those in the top of the income distribution due to the widening gap in life expectancy.

We then consider how the differential changes in mortality would affect analyses of some possible reforms to major entitlement programs in the face of population aging. For example, many proposals to increase the normal retirement age under Social Security are motivated by the rise in mean life expectancy. The mean, however, masks substantial differences in mortality changes across income groups. We show the impact of that proposal and other possible Social Security and Medicare reforms on lifetime benefits across income groups and in a manner that reflects their different life expectancy trajectories. We find that while there are policy reforms that tend to raise the progressivity of government programs, the effect of these reforms are fairly small when viewed next to the reduction in progressivity that is occurring due to the growing gap in life expectancy. This suggests that policy changes that (alone or in combination) are more progressive than those we simulate here would be needed to undo the effect of the widening longevity gap on the progressivity of government programs.

Social Security, Medicare, and the other programs included in our study face rising expenditures over time, straining the ability of existing revenue sources to fully fund benefit promises at current tax rate. The US is far from unique in this regard – rising longevity, falling birth rates, and slowing economic growth threaten the long-term solvency of entitlement programs in many countries, particularly where financed via a pay-as-you-go mechanism or out of general revenues. Many countries have already implemented reforms to public pension, disability insurance, and other social insurance programs, for example by raising retirement ages or altering benefit formulas in a way that reduces program generosity, and many countries continue to contemplate implementing (further) reforms. As policy makers continue to debate the future of social programs in the United States, they would do well to consider the welfare implications not only of improved longevity, but also the increasing gap in life expectancy by socioeconomic status.

http://www.nber.org…

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Comment:

By Don McCanne, M.D.

This paper was authored by a team of prominent economists (some names you may recognize) who are members of the National Academies of Sciences’ Committee on the Long-Run Macroeconomic Effects of the Aging U.S. Population. It is an important paper because it demonstrates the disproportionate distribution of Social Security, Medicare, and other public benefits to wealthier individuals by virtue of the fact that they live longer and thus collect benefits for a longer period of time. Since the life expectancy differential is increasing, the inequity of distribution of benefits is also increasing.

This team begins with the basic assumption that entitlement programs, especially Social Security and Medicare, are growing too rapidly and will create an excess burden for the federal budget. In their concluding remarks they note that other nations have raised retirement ages and reduced generosity of benefits. So this analysis seems to aim for that same goal of controlling spending. Thus they direct their consideration to various proposals designed to reduce federal spending for these programs while not giving consideration to increasing revenues to cover the anticipated growth in spending. We’ll get back to this in a moment.

It is widely acknowledged that, over the past several decades, there has been an unacceptable transfer of income and wealth upwards such that the wealthier are becoming much wealthier while the incomes and wealth accumulation of America’s working families have largely stagnated. Public policies, especially tax policies, are now required to correct these inequities.

The authors of this report do understand the inequities and thus describe how the various proposals to reduce spending on entitlements are either regressive or progressive. They conclude, “most of these policy changes would make overall net benefits more progressive. The exceptions are raising the EEA (Early Eligibility Age for Social Security) or the Medicare eligibility age, which make benefits less progressive.”

An interesting observation is that they did not evaluate one of the more important proposals – raising the Social Security maximum taxable earnings amount – simply because the economic model they selected (Future Elderly Model or FEM) made it impossible to do such a simulation. Since this is one of the more important proposals that would improve progressivity, you would think that they might look for or create a model that would take this into consideration, but then this would be counter to their goal of decreasing spending rather than increasing revenues.

In decreasing spending they are concerned about the progressivity of the various proposals since currently the wealthier are favored because of their increased longevity resulting in greater accumulated benefits, thus reductions in spending should apply more to the wealthier individuals. But their concern is about relative progressivity; they still anticipate that reductions would also occur amongst those with lower incomes and wealth, except at a lesser percentage.

The difficulty is that they are addressing the dubious problem as to whether we can afford the increases in entitlement spending, which would require greater revenues, when the problem that they should be addressing is whether or not the benefits are adequate for America’s workforce. Clearly, reducing retirement and health benefits for the workforce is the wrong direction, especially considering the background of wealth moving to the top.

So instead of policies designed to reduce spending, we should be looking at policies designed to ensure adequate retirement and health security. That means protecting and expanding benefits for those with lower incomes (e.g., improving Medicare). Wealthier individuals do not need expanded benefits, but in an egalitarian system it is far easier to provide the same benefits to everyone. To make the system more equitable, revenues from the wealthier individuals with higher incomes should be increased. For those who say that the “economy cannot afford it,” that’s nonsense. Social Security checks are spent, moving that money into the economy, and health care is one of the largest, most robust sectors of the economy, which is supported by the Medicare program. The economy thrives on Social Security and Medicare.

Unfortunately, right now the Trump administration is recommending the opposite. The tax policy recommendations released this week would greatly reduce revenues from those with higher incomes and totally eliminate estate taxes which tax wealth.

The groupthink of this committee is on target to be concerned about the progressivity of entitlement reform, but they have totally missed the boat by suggesting that harmful reductions in benefits for the majority are acceptable merely because the wealthy have a greater percentage reduction. Though that percentage reduction may be greater, the accumulated benefits for the wealthy still remain much greater, and they certainly are not harmed by these reductions, as those with little wealth are. But instead of increasing administrative complexity by selectively reducing benefits for the wealthy, we can offset that inequity by increasing revenues from the wealthy.

We can afford to ensure that absolutely everyone has a decent retirement, including freedom from fear of medical debt though a well financed Medicare program (make that a Medicare program for everyone). Normative economics needs to have a prominent place in groupthink deliberations.

Where Does the Health Insurance Premium Dollar Go?

By Uwe Reinhardt, Ph.D.
The JAMA Forum, April 25, 2017

In early March, America’s Health Insurance Plans (AHIP), the national association of private US health insurers, released an interesting report that presents, for insured patients younger than 65 years, financial statistics for 2014 of commercial and nonprofit health insurance companies.

According to the report, “Where Does Your Premium Dollar Go?,” an average of 79.7 cents per premium dollar is spent by insurers on health care proper and 17.8 cents on the insurers’ “operating costs,” leaving only 2.7 cents per premium dollar as profits.

The nearly 80 cents per premium dollar that insurers report to spend on medical expenses are known in insurance jargon as the “medical loss ratio (MLR),” because it is the portion of premiums collected health insurers “lose” to physicians, hospitals, and other entities who offer health care.

The Affordable Care Act (ACA) mandated an MLR of at least 85% for large insurance companies and of at least 80% for smaller carriers. By their own admission, insurers selling policies for individually purchased health insurance before the ACA went into effect tended to have MLRs in the 55% to 65% range. Should a repeal of the ACA entail elimination of the mandated minimum MLRs, the market might well revert again to these extraordinarily low payouts of premiums for health care.

As already noted, the AHIP reports that insurers had an average profit margin (net profits divided by premium revenue) of only 2.7%. The number seems low, perhaps because it is a simple average. Profit margins for the larger US health insurers, for example, actually were much higher  than just 3% in recent years, with 4.7% for Aetna, 7.0% for Cigna, and 4.6% for United Health Group in 2015 and 3.5% for Anthem in 2014. (These numbers, however, also include the Medicare Advantage program for older people.)

But even a profit margin of 5% belies the frequent assertion that private health insurers divert huge fractions of their premiums to their own profits. Much more troublesome is the 18 cents per premium dollar reported to cover the insurers’ “operating costs.” These include the cost of marketing, determining eligibility, utilization controls (eg, prior authorization of particular procedures), claims processing, and negotiating fees with each and every physician, hospital, and other health care workers and facilities.

These operating costs are about twice as high as are the overhead costs of insurers in simpler health insurance systems in other countries. A 2010 study comparing per capita health spending in Canada and the United States, for example, found that administrative costs in 2002 accounted for 39% of the total per capita spending difference between the 2 countries.

Also worthy of note is that the 18 cents per premium dollar that insurers report as their “production costs” exclude 2 additional forms of administrative overhead. First, the number excludes the value of the time US patients must spend dealing with insurers, mainly over enrollment and over claims. It can be very time-consuming. Second, the insurers’ cost naturally excludes also the sizeable outlays that physicians, hospitals, and other health care workers and facilities make to negotiate prices for health care and to argue over medical bills.

A Costly “Coding War”

A “must read” in this regard is a recent article by Elizabeth Rosenthal, MD, “Indecipherable Medical Bills? They’re One Reason Health Care Costs So Much.” Rosenthal describes a costly “coding war” in which physicians, hospitals, and others who treat patients seek to maximize their profits by hiring legions of consultants who know how to “upcode” procedures in their medical bills. For their part, insurers hire legions of coding consultants who know how to protect insurers from such upcoding. Rosenthal vividly describes how individual patients can get mauled in the process.

We can think of the extraordinarily high overhead imposed on insured individuals and patients in the United States as the price they seem to be willing to pay for the privilege of choice among health insurers and, for each insurer, among multiple different insurance products. US consumers seem so fanatic about this choice that to keep it, they have been willing to give up their erstwhile freedom of choice among physicians, hospitals, and other clinicians and health care facilities. Citizens of most other countries have made that trade-off in exactly the opposite direction.

https://newsatjama.jama.com…

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Comment:

By Don McCanne, M.D.

The last paragraph sums up today’s message: “We can think of the extraordinarily high overhead imposed on insured individuals and patients in the United States as the price they seem to be willing to pay for the privilege of choice among health insurers and, for each insurer, among multiple different insurance products. US consumers seem so fanatic about this choice that to keep it, they have been willing to give up their erstwhile freedom of choice among physicians, hospitals, and other clinicians and health care facilities. Citizens of most other countries have made that trade-off in exactly the opposite direction.”