Much of the motivation driving health care reform is grounded in the belief that U.S. health care spending is too high and rising too quickly. Whether measured by individual insurance premiums, average spending per person, total national spending, or federal and state government health spending, U.S. health care expenditures are growing faster than inflation, faster than average wages, and faster than the gross domestic product (GDP). Thus, the President has declared that one key purpose of health care reform is to "bend the cost curve" downward.
However, this strong consensus that health care spending is too high and growing too fast has not led to agreement on the causes or the appropriate responses. The most commonly proposed explanations for increases in overall health care spending include:
Each of these possibilities leads to a different set of appropriate policy solutions and has different implications as to whether the current proposals could, in the President's words, "bend the cost curve" downward. We will examine each of these possibilities in turn, then discuss whether current reform proposals are likely to "bend the cost curve" and solve these problems, and if not, what other policies might do so.
Regrettably, neither the House nor the Senate health care reform bills that were passed in late 2009 would "bend the cost curve" downward. On the contrary, these bills would exacerbate the same inefficiencies and perverse incentives that have led to the current situation. Even taking into account only a few of these factors, independent assessments by the Office of the Actuary in the Centers for Medicare and Medicaid Services have concluded that total national spending would increase even faster if either the Senate bill (H.R. 3950) or the House bill (H.R. 3962) become law. The House and Senate bills appear to be based on a fundamental misunderstanding of the basic factors driving health care spending upward. As a result, instead of restraining these basic factors, the bills neglect some and reinforce others, driving spending upwards instead of downward.
Rapidly Increasing Health Care Spending
There is widespread agreement on both sides of the political divide that health care spending is increasing rapidly. President Barack Obama told Congress on February 24, 2009:
The cost of health care eats up more and more of our savings each year, yet we keep delaying reform....
[W]e must also address the crushing cost of health care.
...In the last eight years, [health insurance] premiums have grown four times faster than wages.... And it's one of the largest and fastest-growing parts of our [federal] budget.
During the 2008 presidential election, his campaign literature declared, "Health care costs are skyrocketing." Writing in the Journal of the American Medical Association, Republican candidate John McCain agreed:
Costs that continue to grow year after year have become unsustainable. Rising health care costs make it difficult for families and businesses to afford private coverage, and they consume an increasing share of middle-class wages. Rising costs put health insurance out of reach for tens of millions of uninsured Americans. And they put increasing pressure on taxpayers who pay the bill for public programs.
On this point, politicians on both sides are indisputably correct. On a per capita basis, health care spending increased by a factor of six between 1965 and 2005, after adjusting for inflation. In 2008, the latest year for which figures other than projections are available, total health care spending in the United States was $2.34 trillion (16.2 percent of GDP), up 4.4 percent from the $2.24 trillion spent the previous year. By contrast, in 1960, total health spending accounted for only 5.2 percent of GDP. Since then, health spending has more than tripled as a percentage of GDP. The Congressional Budget Office (CBO) forecasts that, if present trends continue, health care spending will account for 25 percent of GDP by 2025, 37 percent by 2050, and 49 percent by 2082.
Yet high or increasing levels of spending by themselves do not necessarily indicate that there is a problem. For example, in a relatively wealthy country such as the United States, where most people can meet their basic needs for food and shelter, people will reasonably place a high priority on health and longevity and willingly pay high prices for health care if it improves and lengthens their lives. To say that we are spending "too much" on health care is equivalent to saying we are spending "too little" on other goods and services, yet few goods and services are more important to one's well-being than those with the potential to improve one's health and longevity.
Over time, medical advances may also provide more opportunities for treatment, making spending more worthwhile. By way of analogy, improvements in computer technology have resulted in the average family spending much more on computers now than in 1950, when home computers were unavailable and spending on them was zero, but this is not regarded as a "computer cost crisis." It is well understood that increased spending on computers and other electronics is the result of both higher incomes and more and better spending options. Likewise, increasing health care spending that is the result of medical advances--whether for better but more expensive treatments, or new treatments for previously untreatable conditions--would not necessarily indicate a problem, much less a "crisis." As David Cutler points out, "Cost increases are justified if the things that they buy (increases in health) are worth the price paid."
However, several obvious sources of inefficiency in the health care system indicate that health spending has increased more than can be attributed to positive factors, such as increased wealth and improved opportunities for treatment due to medical advances. These negative factors increase spending more than necessary to achieve any given level of health outcomes. In other words, if these inefficiencies could be eliminated, we could achieve the same level of population health and longevity with less total spending, a higher level of health and longevity with the same level of spending, or some combination of the two.
In between these two extremes, there is also the possibility that some of the spending increase is due neither to positive factors, such as wealth or new treatment options, nor to inefficiencies, but to an increased prevalence of diseases and chronic conditions. Such a trend could increase the amount of health care--and thus spending--necessary to achieve a given level of population health and longevity.
We will proceed to examine each of these potential drivers of health care spending.
Is Disease Prevalence Driving Increased Spending?
One possible explanation for increased spending is increased prevalence of disease. Even if the cost of treating each disease is stable, increased prevalence of disease would increase total health care spending.
There are several reasons why disease prevalence could be increasing. First, the U.S. population is aging. As Americans live longer and have fewer children, the rate of age-related diseases could increase simply because more people--both in absolute numbers and as a percentage of the total population--are in the upper age ranges. If improved health and nutrition enable people to live longer and acquire the same expensive diseases, only later in life, the aging of the population might not substantially increase medical spending. However, if people acquire diseases at the same age as before, but survive longer--perhaps because of more, or more expensive, treatment--then aging would increase health care spending. This could occur through extended, costly treatments for chronic conditions or successful treatment of more diseases per person over the course of a lifetime.
Another reason for increased disease prevalence could be an increase in unhealthy lifestyles. For example, obesity is partly the result of lifestyle factors, such as exercise, diet, and increases in the proportion of sedentary jobs. Obesity is associated with many costly diseases and has been increasing over time. However, other lifestyle factors point in the other direction; for example, U.S. smoking rates have been declining.
One study found that the 15 most expensive diseases account for 43 percent to 61 percent of health care spending growth from 1987 to 2000. The five costliest conditions--heart disease, mental disorder, pulmonary disorders, cancer, and trauma-- account for most of the increase. This increase reflects both an increase in treated prevalence (the number of cases treated as a share of the population) and cost of treatment (spending per case). Eight of the 15 conditions showed a large increase in treated prevalence, and eight showed a significant rise in cost per case, with very little overlap. In general, disorders with a large increase in cost per treated case had a smaller increase in treated prevalence. A follow-up study examined the impact of obesity on increased medical spending and concluded that increased obesity prevalence and the relatively increased spending on obesity-related illnesses accounted for 27 percent of the real health care expenditure increase between 1987 and 2001, of which increased obesity prevalence accounted for 12 percent.
Subsequent research examined whether spending increases resulted more from increased treated prevalence or increased spending per case. The authors concluded that treated prevalence played a more significant role in spending growth between 1987 and 2002. For 16 of the 20 most expensive conditions examined, increased disease prevalence had a greater impact on spending growth than increases in the cost of treatment. More importantly, the authors concluded that these 20 expensive medical conditions comprised 67 percent of private health insurance spending growth in this period. They also found that 10 medical conditions accounted for two-thirds of Medicare's spending increase over the same period.
Does Coverage Increase Health Spending?
With private health insurance companies being accused of denying care to save money and with Medicare, Medicaid, and other government programs cutting payments to doctors and hospitals, how can health coverage be increasing spending?
The primary purpose of health insurance is to protect people from the financial risks of illness by enabling people to incur health care costs without worrying too much about the financial consequences. In other words, insurance allows patients to focus on solving the health problem rather than paying for it. When considered in this way, increasing health care spending is almost the purpose of health insurance. In microeconomic terms, a person will procure a product or service--medical or otherwise--if the perceived benefit exceeds the cost to the buyer (patient). While the "cost to the patient" of health care services includes many factors besides the money to be paid--such as time and inconvenience, discomfort, and risk of complications-- money is one factor. While the nonmonetary costs are enough to ensure that a patient will not use even free medical care without a good reason (from the patient's perspective), increasing the monetary price that patients pay out of pocket will clearly deter some patients from obtaining some fraction of health care services. Conversely, reducing the price paid will increase consumption.
Could insurance coverage therefore be at least partially responsible for the increase in health care spending? Over the past half-century, the role of health insurance has grown, covering both more people and a higher percentage of total health care spending. In 1960, insurance and government health care programs covered only 46 percent of total medical expenditures. By 2000, the figure had grown to nearly 78 percent. Not only did health insurance cover a higher percentage of health care spending, but the total amount of health care spending increased by 450 percentover that period, after adjusting for inflation.
Did the increase in coverage contribute to the increase in spending? Even if it did, this might not be an entirely bad thing. If people were forgoing important health care because of the financial cost, increased insurance may have improved people's health by inducing patients to obtain more health care. If that were the case, people with health insurance should have better health outcomes than those without it.
The RAND Health Insurance Experiment. Between 1974 and 1982, RAND Corporation undertook a study to determine how health insurance affected both the consumption of health care and actual health. The pathbreaking RAND Health Insurance Experiment randomly assigned individuals and families to different insurance plans with different cost-sharing policies. One group received all health care free of charge, other groups had various levels of coinsurance and various limits on total out-of-pocket spending. The different groups were comparable in age distribution, several measures of initial health status, and income distribution, with low-income families oversampled in all plans. Each family was enrolled for three or five years and health status statistics were checked before, during, and after the enrollment period.
The data obtained in the study showed no statistically significant differences among the groups in mortality risk or measures of overall health. Of 23 specific physiological measures of health status, the results of only three were statistically significant in favor of the free-care plan at the 5 percent level. Of the remaining 20 measures, 13 favored cost-sharing plans, and seven favored the free-care plan, but these results were not statistically significant either individually or as a group. On the other hand, the free-health-care group consumed 45 percent more health care (measured in dollars) per person than the highest-spending cost-sharing group. While spending decreased as the cost sharing increased, the biggest jump was from the free-care plan to the lowest cost-sharing plan. From these results, many analysts have concluded that free health care and insurance with lower cost sharing has little substantial effect on health, but contributes significantly to higher health care spending. Of course, free health care is never truly free. While the patients did not pay for the "free" health care, the insurance plan did.
To what extent could increasing insurance coverage explain the overall increase in health spending over time? Applying the spending differences in the RAND results to the increase in insurance coverage over time, increased prevalence of health insurance by itself would account for only 8 percent to 10 percent of the increase in national health spending between 1950 and 1984. However, the effect of a large increase in the proportion of the population covered by insurance could be greater than the proportional change in individual effects measured by the RAND study.
The Impact of Medicare. Amy Finkelstein examined this question by studying the single largest change in American health insurance, the introduction of Medicare.
In 1963, before Medicare was introduced, only 25 percent of Americans over age 65 were covered by Blue Cross, the dominant (and arguably the only comprehensive) private hospital insurance plan, and only 55 percent had any private hospital insurance. These figures varied substantially by region. In the least covered region, 12 percent of seniors over age 65 had Blue Cross coverage, and 43 percent had private hospital insurance. In the most covered region, these figures were 51 percent and 63 percent, respectively. In 1966, Medicare almost instantly increased elderly insurance rates to 100 percent. Because of the differences in prior coverage rates, the introduction of Medicare had different levels of impact across regions. If health insurance were an important determinant of either health status or health care spending, Medicare's introduction would likely have had a more dramatic impact in regions with lower prior insurance rates.
Applying the results of the RAND study to the increase in insurance coverage induced by Medicare predicts that total hospital spending would increase by 5.6 percent from 1965 to 1970. However, based on regional variations in prior coverage, Finkelstein estimates that Medicare accounted for a 37 percent increase in hospital spending over that same period--six times larger than the individual effects predicted by the RAND study. On the other hand, despite the additional spending, Medicare failed to reduce mortality rates among the elderly in its first 10 years (1965 to 1975).
Finkelstein notes that her results are not necessarily incompatible with the RAND study. The RAND study measured changes in health spending and behavior for a relatively small number of individuals acting in an environment in which the vast majority of patients were unaffected by the experiment. In contrast, Medicare was a vast, instantaneous, and permanent expansion of coverage to more than 14 million people (about 7.5 percent of the population) and a segment of the population that initially accounted for 20 percent of the spending.
Finkelstein suggests several reasons why a massive expansion in coverage can have effects much larger than simply the individual effects multiplied by the number of people covered. For example, a large increase in the number of people who can purchase health care products and services can lead companies to invest in new technologies and facilities in the expectation that large-scale health coverage will create a larger potential market. Indeed, Finkelstein found that regional variations in the percentage of newly covered seniors was associated with substantial increases in hospital spending on the non-elderly population (not covered by Medicare) and with variations in the opening of new hospitals, the deployment of open-heart surgery, and the establishment of cardiac intensive care units.
During this same period, private insurance coverage also expanded. Extrapolating "from the estimated impact of Medicare to the impact of the overall spread of health insurance more generally suggests that the spread of health insurance between 1950 and 1990 may be able to explain about half of the six-fold rise in real per capita health spending over this time period."
Does New Medical Technology Increase Spending?
One of the most commonly discussed puzzles in health care is that technological improvements seem to increase quality, but also to increase unit costs and total spending. This contrasts with other industries, such as computers and electronics, in which technological improvements are typically associated with both increases in quality and noticeable decreases in costs. To understand why technological improvements induce different economic effects in health care than in other industries, it is important to understand two different classes of technological improvements in health care as well as a particular characteristic of the health care pricing system that inhibits the market processes that cause technological improvements to reduce costs in other industries.
The first class of technological improvement enables a new treatment for a previously untreatable or less effectively treatable disease or condition. While introducing a treatment for a previously untreatable condition does not, strictly speaking, increase the unit cost, it will necessarily increase spending if it is implemented. A disease or condition for which there is no possible treatment obviously incurs zero spending. Thus, any technological improvement that enables treatment will increase spending. Of course, it will also increase patient well-being.
The second class is potentially cost-reducing. For example, improvements in computer technology could lead to lower-cost imaging systems, such as computerized tomography (CT) scanners, lower-cost pacemakers, and other medical devices. Alternatively, a completely different and lower-cost treatment might be discovered. For example, a new drug might be developed to treat a disease that was formerly treated with a more costly surgery. In such cases, it is important to consider the total cost of the treatment, not just one aspect of it or one treatment modality. For example, if a drug therapy replaces a surgical procedure, spending on drugs will increase, but that increase could be more than offset by the decrease in spending on surgery for that disease. Looking only at the change in drug spending-- which is often easier given the data that are available--will present a misleading picture of the effect of the new technology.
In the case of a new treatment for a disease that was previously treated in a different manner, the new technology could either increase or decrease total costs, depending on both the unit cost of the treatment and any change in the number of patients treated.
Some have attempted to measure the degree to which improving technology affects health care costs. For example, David Cutler and Mark McClellan examined Medicare data on the treatment of acute myocardial infarction (AMI or "heart attack"). From 1984 to 1991, Medicare's average spending per AMI increased at an annual rate of 4.1 percent. Much of the increase was due to the more frequent use of technologically intensive procedures. In 1984, 11 percent of Medicare AMI patients received catheterization, 5 percent underwent bypass surgery, and 1 percent received angioplasties. By 1991, the percentages had increased significantly to 41 percent for catheterization, 13 percent for bypass surgery, and 12 percent for angioplasty.
Cutler attributes the entire increased cost of heart attacks to new medical technologies, writing, "Both the aggregate decomposition of health spending, and the example of heart attacks, suggest that technological change is the source of most, if not all, increases in health costs." Most importantly, the effectiveness of the treatment increased, resulting in longer average survival after the heart attack. When measured on the basis of additional life years saved, rather than simply the number of AMIs treated, Cutler and McClellan concluded that the price of AMI treatment per life-year saved actually decreased during this period.
For overall health spending, Cutler traces 51 percent of the increase to quantifiable factors, such as demographics, income, insurance, relative price increase, administrative expenses, and increases in capital and labor costs. He attributes the remaining 49 percent to technology. Other prominent economists and health policy analysts, including Joseph Newhouse, Paul Ginsburg, and the Congressional Budget Office, have also attributed about half the increase to technological change.
However, a peculiar aspect of the pricing system for medical products and procedures often prevents technological improvements from reducing spending, as frequently happens in other industries. For example, in the case of personal computers, the people and companies that use computers both pay for them and benefit from their use. Vigorous competition among suppliers means that improvements that reduce the cost of manufacturing computers confer a competitive advantage on the manufacturer that achieves the cost reduction--but only if the producer uses at least a portion of the cost reduction to reduce prices. Frequent improvements by competing suppliers ensure that cost reductions are passed on to consumers in the form of lower prices, thus reducing spending (per unit of computing capability).
In most cases, as technology improves, prices go down. Prices of computers, flat screen televisions, and DVD players have fallen over time as their technologies have improved. Why has this not happened in the health care sector? Why is a CT scan or a pacemaker any different?
The answer is that the CT scan and the pacemaker are not fundamentally different in terms of their technological development, but that the pricing system for medical devices and services is radically different. While patients derive the primary benefits from treatments and products, insurance companies, government programs, and other third parties primarily pay for them. Once an insurance company or government program has approved payment for a particular procedure or product at a particular price, it is typically available to all similarly situated patients. As a result, the supplier obtains little or no competitive benefit from reducing prices. After the product or service (e.g., a particular type of pacemaker) is approved for use by the third-party payer at a particular price, the supplier has little prospect of increasing sales volume by reducing the price. As a result, technological improvements that reduce the cost of producing the pacemaker may not be passed along to patients or payers in the form of lower prices, but rather retained by the manufacturer in the form of higher profits. In addition, when an improved version of the product is introduced, the manufacturer might be able to obtain a higher administratively determined price on the basis of quality improvement, even if the manufacturing cost is similar or even lower.
This is not to say that cost-reducing technological improvements exert no downward pressure on prices, but the degree of downward pressure due to competition is substantially smaller in health care than in other sectors of the economy. For example, a subsequent product or service could be "sold" to a payer on the basis of lower total cost. This is sometimes the case for different drugs used to treat the same condition or for new surgical techniques that might not previously have been covered by the payer.
How Much of Health Care Spending is Wasteful?
Many observers believe that much health care spending is ultimately wasteful. Aside from the commonly cited problems of billing fraud, other cases in which health care spending never reaches patients, and defensive medicine, many claim that that much of the health care service delivered to patients does not ultimately benefit those patients by increasing their longevity or quality of life.
Regional Variation in Medicare. Based on their examination of regional variations in Medicare spending and Medicare spending growth, Elliott Fisher and his colleagues at the Dartmouth Atlas Project argue that waste plays a substantial role in rising health care costs. From 1992 through 2006, Medicare spending nationwide increased at a 3.5 percent annual rate in real terms. However, this average rate masks considerable regional variation. Real per capita expenditures increased at an annual rate of 5 percent in the Miami area, but at rates of only 2.3 percent in Salem, Oregon, and 2.4 percent in San Francisco. Spending growth also varied widely among hospitals, with 26 "referral regions" exhibiting greater spending growth than Miami and 18 regions experiencing slower growth than Salem.
To look at it another way, in 1992, the referral regions of San Francisco and eastern Long Island had similar per capita Medicare spending, but their subsequent average annual growth rates were 2.4 percent and 4 percent, respectively. Over time, these seemingly small differences add up. By 2006, Medicare spent almost $2,500 more per person in eastern Long Island than in San Francisco. This difference alone accounts for $1 billion in annual Medicare spending. Overall, if the national average annual growth rate (3.5 percent) could be reduced to the growth rate in the San Francisco referral region, cumulative Medicare spending would be reduced by more than $1.4 trillion over 15 years.
Fisher et al. claim that the extra spending in higher-spending regions is wasteful, not simply because it is higher, but because they found no evidence that differences in health status or health outcomes accounted for such wide variations in regional spending. The authors also point out that health technology cannot explain these variations because "residents of all U.S. regions have access to the same technology, and it is implausible that physicians in the regions with slower spending growth are consciously denying their patients needed care." Instead, they argue that a more plausible explanation is regional variation in doctors' practice patterns and patients' preferences, which involves more intensive treatment in certain regions, but no improvement in health outcomes in those regions.
For example, in 2002, John Wennberg and his colleagues found that per capita Medicare spending in Miami was about 2.5 times Medicare spending in Minneapolis. This additional spending in Miami purchased 6.55 times more appointments with medical specialists, 2.13 times more days in the hospital, and 2.16 times more ICU admissions, but "care strongly substantiated by the literature" was actually lower in Miami. According to Fisher and Wennberg, increased spending was not correlated with efficacious services known to reduce morbidity and mortality, but with supply-sensitive services, including more time in hospitals, more time in intensive care units, and more visits to specialists in the last six months of life. However, the results should be interpreted with some caution because the observed supply of such resources might indicate a response to demand caused by unobserved differences in initial health status rather than simply being evidence of waste.
These findings may help to explain why regions with lower spending show better outcomes and regions with huge growths in spending have failed to demonstrate survival gains from their increased expenditures.
Professor Katherine Baicker and Professor Amitabh Chandra at Harvard University actually found a negative correlation between per capita Medicare spending and quality at the state level. They studied 24 quality measures, such as how fast patients with pneumonia receive antibiotics or how frequently patients receive mammography, and found that increased spending had no statistically significant effect for nine of the quality measures and a statistically significant negative effect on the remaining 15 measures. For example, for every $1,000 increase in a state's per-beneficiary Medicare spending, the proportion of heart attack patients receiving aspirin decreased 3.6 percent and the share of diabetics having an HbA1c check decreased by 3.2 percent.
If these widespread variations in Medicare spending are truly associated with no benefits--or even with harm--they indicate a program fraught with systemic inefficiencies at best and vast amounts of waste at worst. Based on regional variation, Fisher and others estimated that wasteful health services could account for 30 percent of Medicare expenditures. Milstein estimated that including operational waste in the Medicare program would raise the level of waste to 40 percent. Regardless of the actual number, the possibility that a large percentage of spending in the nation's largest health plan is wasted certainly cannot be ignored.
Variation in Physician Practice Patterns. Several studies have directly examined physician practice patterns and their influence on cost. One study focused on primary care physicians in an effort to assess discretionary decision making, and compared responses to regional variations in health care spending. The authors assessed physician practice patterns by asking physicians about their routine follow-up intervals and their recommendations on cancer screening for mammography (a screening test supported by the medical literature), prostate-specific antigen (PSA, an ambiguous recommendation), and spiral CT (a screening test not supported by the literature). They also asked doctors what they would recommend in common clinical scenarios as described in clinical vignettes.
Doctors in both high-spending and low-spending regions recommended literature-backed mammograms at approximately equal rates. However, doctors in high-spending regions were more likely to recommend PSA screening for prostate cancer and regular spiral CT screening for lung cancer.
When given a clinical vignette of a 75-year-old woman with clear-cut gastroesophageal reflux disease, doctors in high-spending and low-spending regions recommended numerous interventions at a similar rate, including H. pylori testing and treatment with a proton pump inhibitor. However, primary care physicians in high-spending regions were more likely to recommend an upper gastrointestinal (GI) endoscopy and to refer the patient to a gastroenterologist.
Similarly, in the case of a hypothetical 75-year-old male presenting with new onset chest pain with exertion, approximately the same percentage of doctors in both high-spending and low-spending regions recommended a stress test, but doctors in high-spending regions were much more likely to order an echocardiogram, refer to a cardiologist, or admit the patient to a hospital. Presented with a case of an exacerbation of end-stage congestive heart failure, doctors in high-spending regions were more likely to admit the patient to an acute medicine floor or an intensive care unit (ICU).
For 100 patients of each clinical vignette, doctors in the highest-quintile spending region recommended an average of 80 more hypertension follow-up visits annually, 14 more spiral CTs, 25 more echocardiograms, 24 more coronary care unit admissions, and 29 more GI referrals than doctors in the lowest-quintile spending region recommended. The authors concluded that doctors in high-spending and low-spending regions were equally likely to recommend therapeutic and diagnostic interventions strongly supported by the literature, but doctors in higher-spending regions tended to recommend less-well-supported services at a much higher frequency.
Yet simply noting regional variation in the levels of services recommended by physicians does not necessarily mean that the practices in the low-spending regions are "right" and that practices in the high-spending regions are "wasteful." It is also possible that physicians in high-spending regions may practice at the "right" level, while the physicians in low-spending regions deliver insufficient levels of care. Alternatively, neither level may have been "right" as such, but the higher levels of care are associated with health benefits that are regarded as worth the extra cost for more people in some regions than in others. However, a number of studies suggest that these extra services fail to improve health outcomes and are not valued by patients.
Regional Variation in Non-Medicare Spending. The empirical case for regional variation as evidence for wasteful health care spending depends almost entirely on data from the Medicare program. This is most likely due to the fact that detailed patient-level data are publicly available for the Medicare program rather than any evidence that Medicare spending has the same pattern as other spending. In other words, it is a case of "looking where the light is better."
The picture given by the Medicare data breaks down when other data are considered, even though other data are not available at the same level of detail. For example, Rettenmaier and Saving find that the pattern of variation in Medicare spending is substantially different from aggregate health care spending at the state level. Louisiana has the highest per-enrollee Medicare spending among the 50 states, but ranks only 36th in per-capita health care spending when all sources of health care spending are considered. Likewise, South Dakota has the lowest per-enrollee Medicare spending, but ranks 25th in per-capita health care spending. Indeed, per-enrollee Medicare spending is negatively correlated with per-capita health care spending by the non-Medicare/ Medicaid population. Furthermore, state rankings according to per-enrollee Medicare spending are highly correlated over time, but rankings according to non-Medicare/Medicaid spending per person not enrolled in these programs change substantially over time.
In another analysis that directly challenges the claim that variation in spending is evidence of waste, Richard Cooper finds that the same two quality metrics that Baicker and Chandra found to be negatively correlated with per-enrollee Medicare spending are in fact positively associated with per-capita health care spending by all sources. "Thus, while more Medicare spending is associated with poorer health care quality at the state level, more non-Medicare spending and more total spending are associated with better quality."
Looking strictly at private health insurance spending, Rong Yi found "significant and consistent variation by region for well-defined chronic conditions such as diabetes and heart disease, as well as ill-defined symptoms, signs and other conditions." Not only does this variation in disease explain regional variation in spending, but there is "substantial consistency in the marginal contribution to costs of specific categories of disease" across regions. In other words, regional variation in private health care spending appears to reflect regional variation in disease prevalence, not variations in practice patterns, treatment intensity, or other sources that might be considered waste.
The Economic Roots of High Health Care Spending
It is entirely possible that all four proposed causes--increased prevalence of disease, the third-party payment system, technological improvements, and waste and fraud--are contributing to increased health care spending. Indeed, they may be interconnected. Today's health care system is fraught with perverse economic incentives that generate artificially high and rapidly increasing spending.
Thorpe is correct to argue that treating diseases is becoming more expensive. Cutler is right to contend that the spending per heart attack has increased, and Newhouse is correct to point out that patients now have more done during an average hospital visit. Frequently, as technology improves prices decrease, but this is often not the case in health care. These observations are important, but by themselves they do not answer the question of increased health care spending.
A major source of these spending increases is a third-party payment system that often leaves the physician and patient insulated from and even unaware of the costs of the various treatment options. Often, the patient faces the same co-payment regardless of which treatment is chosen, and the extra costs are passed along to the insurance company, Medicare, or Medicaid. These payers may appear to have an incentive to encourage efficient use of resources, but ultimately they do not pay the price for inefficiency. Insurance companies offer "generous" benefits and pass on the increased spending to patients (and often their co-workers) through increased insurance premiums, and government programs pass on the spending increases to taxpayers.
To a large extent, increased health care spending is a consequence of this third-party payment system. In recent decades, the percentage of health care spending paid "out of pocket" by patients has fallen substantially, from 52 percent in 1965 to only 15 percent in 2005, which means that third-party payments have increased from 48 percent to 85 percent. As third-party payer spending has risen as a percentage, total spending has grown even faster. Since 1965, real per capita health care expenditures have increased approximately sixfold.
In short, neither the patient, the doctor, the insurance company, nor any government program has much incentive to spend health care dollars efficiently. A system that determines prices through administrative procedures rather than market processes disconnects the prices paid for health care services and products from both the costs incurred to provide them and their value to patients. A tax code that rewards employees who purchase insurance through their jobs and punishes individuals who purchase health insurance in the outside market further distorts these incentives. A litigious tort system that encourages doctors to order unnecessary tests and procedures at no cost to themselves in order to forestall lawsuits exacerbates the problem. However, the main problem is a system that insulates both patients and producers from normal market incentives to reduce prices and spending.
Will Currently Proposed Reforms "Bend the Cost Curve?"
President Obama and the congressional leadership have proposed complex packages of reforms, which the President says will "bend the cost curve," slowing the rate of increase in total national health care spending and possibly even reducing insurance premiums by a promised average of $2,500 per family. Yet will the proposed reforms deliver the promised cost reductions?
The primary components of the House and Senate bills are:
Limits on Out-of-Pocket Spending. Limits on out-of-pocket spending will increase the role of third-party payment. In fact, this is their goal; insulating patients and physicians from the health care costs is seen as one of the benefits of reform. Such limits will strengthen the incentives for most patients to engage in excessive spending, especially those who receive premium and cost-sharing subsidies, which could amount to approximately 57 percent of the non-elderly population. The additional costs will be passed along to the nonsubsidized population in the form of increased premiums and onto the entire population through special taxes (as described below).
Coverage Mandates. Regulatory changes to increase covered services will extend the third-party payment phenomenon to a wider variety of services for most patients. To remain solvent, insurance plans will need to charge higher premiums--in addition to any increases required by the incentive effects of lower cost sharing. This will also eliminate the ability of cost-conscious patients to choose "no-frills" health plans with lower premiums and reduced incentives for excess health care utilization.
New Taxes on Health Insurance. The general tax on health insurance will be passed along to patients in the form of higher premiums. The Senate bill would also impose a special 40 percent excise tax on high-value health plans (plans with premiums over certain thresholds). The CBO estimates that almost 20 percent of households will be in plans above the thresholds in 2016. Some plans might attempt to move under the thresholds by reducing benefits, but the coverage mandates will limit their ability to do so. In addition, the thresholds are set to grow at a slower rate than the current growth rate of health care costs, which will force more plans above the thresholds every year. Furthermore, the tax will not be considered a business expense for the insurer, meaning that insurance companies will be charged a profits tax as if the excise tax paid were part of their profit. This will make the effective tax rate approximately 54 percent. To stay solvent, insurance companies will have to pass the tax along to patients in the form of increased premiums--resulting in a premium increase of $1.54 for every $1.00 increase in average health care spending above the tax threshold.
Increased Spending. The first three reform components will clearly increase total spending, not reduce it. In addition, the plan calls for about $850 billion in new government spending over 10 years according to the CBO and an estimated $4.9 trillion over 20 years, with annual spending increasing every year. It strains credulity to claim that increasing government spending by hundreds of billions or trillions of dollars while simultaneously mandating additional spending by the private sector will somehow reduce total spending. If the government is spending more and the private sector is spending more, who exactly is spending less?
The Public Option. The House bill includes a "public option," an additional government-run insurance plan that will allegedly "compete on a level playing field" with private insurance plans. However, if the public option really is required to meet the same requirements as private plans-- including providing the same benefits, meeting the same solvency requirements, paying the same state and federal taxes, and not taking taxpayer subsidies--then it is difficult to see how it will perform any differently than just another private plan, joining the approximately 1,300 health insurance companies currently in the market. Of course, if the plan fails to meet these requirements, it will not compete on a level playing field. As The Washington Post acknowledges, "It is difficult to imagine a truly level playing field that would simultaneously produce benefits from a government-run system."
Improved Record Keeping and Communications. The only significant reform that congressional proponents point to as an actual cost reducer is a hefty increase in electronic recordkeeping. The $787 billion American Recovery and Reinvestment Act of 2009 (the "stimulus" bill) included $20 billion in subsidies for health information technology (HIT), which is also known as electronic health records (EHRs). The stimulus bill also codified the role of the Office of the National Coordinator for Health Information Technology and purports to reward doctors and hospitals for "meaningful use" of a "certified EHR." After 2014, doctors and hospitals will be penalized for failing to use EHRs.
While the current system clearly fails to provide incentives for health care providers to communicate with each other efficiently, this does not mean that the greater efficiency in record keeping and communication will translate into cost savings significant enough to overcome the other forces that are driving costs up. Dr. David Blumenthal, President Obama's HIT czar, has previously written that "[a]ctual evidence of the efficacy and cost-saving potential of HIT is scarce." The Congressional Budget Office has concluded: "By itself, the adoption of more health IT is generally not sufficient to produce significant cost savings." Jerome Groopman and Pamela Hartzband wrote that they both voted for President Obama, but were "dumbfounded" by the President's claim that HIT could save $80 billion a year and tracked the estimate to a report that openly presented that estimate as speculation unsupported by actual data.
The Comparative Effectiveness Approach. The stimulus bill also included $1.1 billion for "comparative effectiveness research" to examine the efficacy of different therapeutic interventions for the same conditions. By itself, acquiring this knowledge may be helpful, but when coupled with a public plan and regulation of benefit packages, this research could easily become the framework for government to require that patients be arbitrarily denied care regardless of physician judgment, patient preferences, and even willingness to pay.
A one-size-fits-all approach to health care simply cannot serve any actual patient's best interests. One hypothetical patient may respond quickly and positively to bactrim, a cheap therapy for urinary tract infections, while his cousin might suffer a potentially fatal adverse drug reaction from the same dose of the same drug administered to treat the same illness. Different patients manifest the same illness differently and respond differently to the same treatment. The one-size-fits-all approach explicitly substitutes a set of rules predetermined by distant bureaucrats and regulators for the professional judgment of the physician who actually sees and talksto the patient. At best, this means that new information on "best practices" will be delayed until a bureaucracy gives its imprimatur. At worst, variation in patient needs will be ignored, and efforts to investigate new treatment protocols will be preempted.
Furthermore, different patients enter the doctor's office with different treatment preferences. For a common complaint like back pain, some patients prefer the most invasive and intensive procedures available despite the risk of significant side effects. Other patients prefer more conservative therapy. Is one patient wrong to prefer aspirin and physical therapy? Is another patient wrong to prefer a potentially better, but riskier laminectomy? Mandating the same treatment for every patient seems to violate the basic principles of individual rights and freedom of choice. Yet this is the express goal of the comparative effectiveness approach to cost control.
Two Extreme Scenarios: Reducing Spending by Denying Care. Indeed, this leads to the only two ways to reduce total spending under the proposed legislation. First, regulators could use their authority to define benefit packages to mandate not only minimum coverage, but also maximum coverage by requiring private insurance companies to comply with "best practices" guidelines, effectively denying care to patients except under specified conditions. This could force spending down to nearly any desired level simply by arbitrarily denying care to patients regardless of their decisions, their physicians' recommendations, and their or their insurance companies' willingness to pay. To make this system airtight, regulators or Congress would need to prohibit physicians from accepting payment directly from patients for services denied by their insurance. This is already the law for Medicare patients, but these restrictions would need to be extended to all patients.
The second approach would be to combine the regulatory power to define benefit packages with the authority to prohibit "excessive premiums" by requiring insurance companies to set premiums below the level needed to break even while providing the required benefit packages. This would force all private plans out of business, leaving a public option as the only surviving health plan. The public plan would then establish guidelines to deny care except under specified conditions, as described in the first option.
While these extreme scenarios are not specifically required by either the House or Senate bill, enacting either bill would make it possible for regulators to implement these extreme scenarios by regulation without any further action by Congress.
Furthermore, while such an approach might control rising spending, it cannot fairly be described as "bending the cost curve." The cost of providing any particular service would remain unchanged. This approach would merely flatten spending by arbitrarily reducing the quantity of health care by government fiat.
Real Reforms That Could Control Costs and Improve Care
Congress could pursue a different approach, with the potential to improve the health care system and control or even reduce health care spending. To accomplish these objectives, Congress should:
Reform the Medicare and Medicaid programs.
The Medicare payment systems for physicians and hospitals reward behavior that increases spending, and Medicare is both the "800-pound gorilla" that drives many private payment systems and the model for the proposed public option. "Hospitals lose money when they improve care in ways that reduce admissions, and they lose market share when they don't keep pace in the local medical arms race. In this race there are no financial rewards for collaboration, coordination, or conservative practice." As Dr. Julie Bynum observed, "Physicians operate under the rules of a system that is rigged to reward high-cost care." Medicaid, on the other hand, contains cost by paying doctors so little that patients have difficulty obtaining care outside the emergency room.
Medicare and Medicaid should reward, not punish, health care providers for delivering high-quality care at a low cost. The most effective way to do this would be to empower beneficiaries to control their health care dollars directly, allowing them use their benefits to enroll in the health plans that deliver the best value according to their own preferences and values.
Empower patients and expand choice.
Outside of Medicare and Medicaid, most people have little choice in their health care plans. Those who have a choice are often limited to a small number of health plans provided through their employer. Federal regulations make it difficult and expensive for companies to offer a large menu of health plans, and hefty tax penalties discourage employees from buying individual health plans.
With the exception of consumer-driven health savings account (HSA) plans, tax laws encourage employer-sponsored health plans to set higher premiums--that is, more third-party payment--rather than implement incentives for efficient use of health services. A 2005 McKinsey study discovered that patients in consumer-driven health plans were twice as likely to inquire about cost and three times more likely to select a cheaper treatment plan compared to patients in traditional plans.
The tax laws and rules are wrongheaded. Regulations should be changed to allow more choices of health plans without tax penalties and greater use of HSA plans. This would encourage patients to make rational choices about day-to-day health care, while protecting them from the financial impact of truly serious illnesses and injuries. At the same time, competitive pressure from cost-conscious patients would reduce prices and improve quality for insurance-paid care, making everybody better off and rewarding providers who deliver quality care at lower prices.
Create a real national market for health insurance.
Congress could further empower patients by creating a real national market for health insurance. Unlike the life insurance market in which a customer can buy any plan that he or she wants, patients can buy health insurance plans only in his or her state. States currently prohibit the purchase of health plans across state lines, and many states mandate costly benefit packages. These two restrictions combine to reduce consumer choice and increase costs and uninsurance rates in many states. Congress could pre-empt these limits using its constitutional power to regulate interstate commerce. Indeed, this power was written into the Constitution specifically to allow Congress to override restrictions on trade among states.
A real national market for health insurance would increase choices and reduce costs. People could buy policies tailored to their individual needs and preferences without states compelling them to purchase unnecessarily expensive coverage with mandated benefits they do not want. Patients would be free to choose between lower-cost catastrophic plans and higher-cost comprehensive plans, thus reducing the number of people who go without insurance due to high premiums.
Despite the rampant inefficiencies and extremely high costs of health care in the United States, it is still possible to make the American health care system even more inefficient and more costly. Regrettably, the health care bills passed by the House and Senate would do precisely that by saddling an already burdened system with more mandates, higher taxes, and less flexibility.
Instead, Congress should pass health care reform that increases patient choice and allows doctors and hospitals to be rewarded for providing high-quality, cost-efficient care. Any other reform will only deepen the current inefficiencies and introduce more problems.Jason D. Fodeman, M.D., is a former Health Policy Fellow in the Center for Health Policy Studies at The Heritage Foundation and is currently an Internal Medicine Resident at the University of Connecticut. Robert A. Book, Ph.D., is Senior Research Fellow in Health Economics in the Center for Data Analysis at The Heritage Foundation.
Richard S. Foster, "Estimated Financial Effects of the 'Patient Protection and Affordable Health Care Act of 2009' as proposed by the Senate Majority Leader on November 18, 2009," U.S. Department of Health and Human Services, Centers for Medicare and Medicaid Services, December 10, 2009, pp. 19-20, at http://src.senate.gov/files/OACTMemorandumonFinancial
ImpactofPPAA%28HR3590%29%2812-10-09%29.pdf (January 7, 2010).
Richard S. Foster, "Estimated Financial Effects of the 'America's Affordable Health Choices Act of 2009' (H.R. 3962), as Passed by the House on November 7, 2009," U.S. Department of Health and Human Services, Centers for Medicare and Medicaid Services, November 13, 2009, p. 12, at http://republicans.waysandmeans.house.gov/UploadedFiles/
OACT_Memorandum_on_Financial_Impact_of_H_R__3962__11-13-09_.pdf (January 7, 2010).
Obama, "Remarks of President Barack Obama."
Obama for America, "Barack Obama and Joe Biden's Plan to Lower Health Care Costs and Ensure Affordable, Accessible Health Coverage for All," 2008, at http://www.barackobama.com/pdf/issues/HealthCareFullPlan.pdf (April 23, 2009).
John S. McCain, "Making Access to Quality and Affordable Health Care a Reality for Every American," JAMA, Vol. 300, No. 16 (October 22/29, 2008), p 1925-1926, at http://jama.ama-assn.org/cgi/content/full/300/16/1925 (April 23, 2009).
Congressional Budget Office, "The Long-Term Outlook for Health Care Spending," November 2007, at http://www.cbo.gov/ftpdocs/87xx/doc8758
/11-13-LT-Health.pdf (February 3, 2010).
Centers for Medicare and Medicaid Services, Office of the Actuary, "National Health Expenditures Web Tables," at http://www.cms.hhs.gov/
NationalHealthExpendData/downloads/tables.pdf (February 3, 2010).
Congressional Budget Office, "The Long-Term Outlook for Health Care Spending."
David M. Cutler, "Technology, Health Costs, and the NIH," paper presented at the National Institutes of Health Economics Roundtable on Biomedical Research, Cambridge, Mass., September 1995, p. 2, at http://www.economics.harvard.edu/faculty/cutler/files/Technology,%20
Health%20Costs%20and%20the%20NIH.pdf (January 26, 2010).
It is useful to distinguish between "cost" and "spending." We adopt the convention of economists by using "cost" to refer to the cost of delivering a unit of a particular health care product or service and "spending" to refer to the total expenditure, which reflects both the cost of each delivered service or product and the quantity actually delivered. Thus, treating twice as many heart attacks for the same amount of money each will be referred to as an increase in spending on heart attack treatments, but not an increase in cost per heart attack.
Kenneth E. Thorpe, Curtis S. Florence, and Peter Joski, "Which Medical Conditions Account for the Rise in Health Care Spending?" Health Affairs Web Exclusive, August 25, 2004, pp. 437-445, at http://content.
healthaffairs.org/cgi/content/full/hlthaff.w4.437/DC1 (May 22, 2009).
Kenneth E. Thorpe, Curtis S. Florence, David H. Howard, and Peter Joski, "The Impact of Obesity on Rising Medical Spending," Health Affairs Web Exclusive, October 20, 2004, pp. 480-486, at http://content.
healthaffairs.org/cgi/content/full/hlthaff.w4.480/DC1 (May 22, 2009).
Kenneth E. Thorpe, Curtis S. Florence, David H. Howard, and Peter Joski, "The Rising Prevalence of Treated Disease: Effects on Private Health Insurance Spending," Health Affairs Web Exclusive, June 27, 2005, pp. 317-325, at http://content.healthaffairs.org/cgi/content/full/hlthaff.w5.317/DC1 (May 22, 2009).
Kenneth E. Thorpe and David H. Howard, "The Rise in Spending Among Medicare Beneficiaries: The Role of Chronic Disease Prevalence and Changes in Treatment Intensity," Health Affairs, Vol. 25, No. 5 (August 22, 2006), pp. w378-w388, at http://content.healthaffairs.org/cgi/content
/full/25/5/w378 (May 22, 2009).
Centers for Medicare and Medicaid Services, "National Health Expenditures Web Tables."
Joseph P. Newhouse and the Insurance Experiment Group, Free for All? Lessons from the RAND Health Insurance Experiment (Cambridge, Mass.: Harvard University Press, 1993).
Diastolic blood pressure, functional far vision, and functional near vision.
Willard G. Manning, Joseph P. Newhouse, Naihua Duan, Emmett B. Keeler, Arleen Leibowitz, and M. Susan Marquis, "Health Insurance and the Demand for Medical Care: Evidence from a Randomized Experiment," American Economic Review, Vol. 77, Issue 3 (June 1987), pp. 251-277.
Amy Finkelstein, "The Aggregate Effects of Health Insurance: Evidence from the Introduction of Medicare," The Quarterly Journal of Economics, Vol. 122, Issue 1 (February 2007), pp. 1-37.
Ibid., p. 33.
In the standard economic sense of the term. That is, the cost of each particular treatment remains the same, but a new treatment is introduced that was not previously available. Spending on this new treatment increases total health care spending, even if the cost of every previously available treatment remains unchanged. See also footnote 11.
The most famous example of this is the replacement of surgical treatment of peptic ulcers with drugs like Tagamet and its successors. See Terence Kealey, The Economic Laws of Scientific Research (New York: Palgrave Macmillan, 1997).
David M. Cutler and Mark McClellan, "The Determinants of Technological Change in Heart Attack Treatment," National Bureau of Economic Research Working Paper No. 5751, September 1996.
Cutler, "Technology, Health Costs, and the NIH," p. 13.
David M. Cutler, Mark McClellan, Joseph P. Newhouse, and Dahlia Remler, "Are Medical Prices Declining? Evidence from Heart Attack Treatments," The Quarterly Journal of Economics, Vol. 113, No. 4 (November 1998), pp. 991-1024.
Cutler, "Technology, Health Costs, and the NIH."
Joseph Newhouse, "An Iconoclastic View of Health Cost Containment," Health Affairs, Vol. 12, Supplement 1 (1993), pp. 152-171, at http://content.healthaffairs.org/cgi/reprint/12/suppl_1/152 (May 22, 2009).
Paul B. Ginsburg, "Controlling Health Care Costs," The New England Journal of Medicine, Vol. 351, No. 16, (October 14, 2004), p. 1591, at http://content.nejm.org/cgi/content/full/351/16/1591 (May 22, 2009).
Congressional Budget Office, "Technological Change and the Growth of Health Care Spending," January 2008, at http://www.cbo.gov/ftpdocs/
89xx/doc8947/01-31-TechHealth.pdf (May 22, 2009).
The analysis for products used to deliver services to numerous patients, such as CT and MRI scanners, is slightly more complicated, but the basic principle is the same. Hospitals and other providers make purchasing decisions based on the amount they will be paid for each service, and this amount is determined by a similar administrative mechanism. There may be some competition due to multiple manufacturers of some devices that provide the same services, but the level of downward pressure on prices will still be more limited than in the case of non-health-care products, which are not paid for by third parties.
"Defensive medicine" refers to the practice of physicians recommending tests and treatments to protect themselves from malpractice liability, which they might not otherwise recommend on the basis of patient benefit.
Elliott S. Fisher, Julie P. Bynum, and Jonathan S. Skinner, "Slowing the Growth of Health Care Costs--Lessons from Regional Variation," The New England Journal of Medicine, Vol. 360, No. 9 (February 26, 2009), pp. 849-852, at http://content.nejm.org/cgi/content/full/360/9/849 (May 21, 2009).
John E. Wennberg, Elliot S. Fisher, and Jonathan S. Skinner, "Geography and the Debate over Medicare Reform," Health Affairs Web Exclusive, February 13, 2002, at http://content.healthaffairs.org/cgi/
content/full/hlthaff.w2.96v1 (May 24, 2009).
Elliott S. Fisher and John E. Wennberg, "Health Care Quality, Geographic Variations, and the Challenge of Supply-Sensitive Care," Perspectives in Biology and Medicine, Vol. 46, No. 1 (Winter 2003), pp. 69-79.
Fisher et al., "Slowing the Growth of Health Care Costs."
Katherine Baicker and Amitabh Chandra, "Medicare Spending, the Physician Workforce, and Beneficiaries' Quality of Care," Health Affairs Web Exclusive, April 7, 2004, pp. 184-197, at http://content.healthaffairs.org/
cgi/content/full/hlthaff.w4.184v1/DC1 (January 8, 2010).
Elliott S. Fisher, David E. Wennberg, Thérèse A. Stukel, Daniel J. Gottlieb, F. L. Lucas, and Étoile L. Pinder, "The Implications of Regional Variations in Medicare Spending; Part 1: The Content, Quality, and Accessibility of Care," Annals of Internal Medicine, Vol. 138, No. 4 (February 18, 2003), pp. 273-287.
Arnold Milstein, testimony before Committee on Health, Education, Labor, and Pensions, U.S. Senate, January 28, 2004, at http://healthcaredisclosure.org/docs/files/Testimony012804.pdf (May 24, 2009).
This term in the medical literature refers to hypothetical patients with particular symptoms and characteristics.
"Proton pump inhibitors" are a class of drugs (not devices, commonly) used to treat this condition.
Brenda Sirovich, Patricia M. Gallagher, David E. Wennberg, and Elliott S. Fisher, "Discretionary Decision Making by Primary Care Physicians and the Cost of U.S. Health Care," Health Affairs, Vol. 27, No. 3 (May/June 2008), pp. 813-823, at http://content.healthaffairs.org/cgi/reprint/27/3/813 (May 24, 2009).
Andrew J. Rettenmaier and Thomas R. Saving, "Perspectives on the Geographic Variation in Health Care Spending," National Center for Policy Analysis, June 2009, at http://www.ncpa.org/pub/perspectives-on-the
-geographic-variation-in-health-care-spending (January 29, 2010).
Richard A. Cooper, "States With More Health Care Spending Have Better-Quality Health Care: Lessons About Medicare," Health Affairs, Vol. 28, No. 1 (2009), pp. w103-w115, at http://content.healthaffairs.org/cgi/
content/abstract/28/1/w103 (January 27, 2010).
Rong Yi, "Understanding Geographic Variations in Health Care Expenditure of the Privately Insured Population," paper presented at The Economics of Population Health: Inaugural Conference of the American Society of Health Economists, Madison, Wis., June 4, 2006.
Congressional Budget Office, "Technological Change and the Growth of Health Care Spending."
Barack Obama, "Transcript of Second McCain, Obama Debate," CNN, October 7, 2008, at http://www.cnn.com/2008/POLITICS/10/07/
presidential.debate.transcript (December 10, 2009).
Congressional Budget Office, letter to Majority Leader Harry Reid, November 18, 2009, at http://www.cbo.gov/ftpdocs/107xx/doc10731
/Reid_letter_11_18_09.pdf (February 3, 2010).
James C. Capretta, "A $4.9 Trillion Spending Increase," Critical Condition, November 19, 2009, at http://healthcare.nationalreview.com/
post/?q=OTc1MjEzYjI5NzM0M2Y1YjUwNzZhZmVhZGFhYTQxYjI (February 3, 2010). See also Congressional Budget Office, letter to Majority Leader Harry Reid, and James C. Capretta, "The Real Budgetary Impact of the House and Senate Health Bills," Heritage Foundation WebMemo No. 2756, January 14, 2010, at http://www.heritage.org/Research/HealthCare
/wm2756.cfm. Many experts consider the CBO estimate overly optimistic.
Editorial, "Reforming Health Care," The Washington Post, April 27, 2009, at http://www.washingtonpost.com/wp-dyn/content/article/2009/04/26/
AR2009042602072.html (May 27, 2009).
Melissa M. Goldstein and David Blumenthal, "Building an Information Technology Infrastructure," The Journal of Law, Medicine & Ethics, Vol. 36, No. 4 (Winter 2008), pp 709-710.
Congressional Budget Office, "Evidence on the Costs and Benefits of Health Information Technology," May 2008, p. 3, at http://www.cbo.gov/
ftpdocs/91xx/doc9168/05-20-HealthIT.pdf (March 26, 2009).
Jerome Groopman and Pamela Hartzband, "Obama's $80 Billion Exaggeration," The Wall Street Journal, March 12, 2009, at http://online.wsj.com/article/SB123681586452302125.html (January 27. 2010).
Social Security Act, 42 U.S. Code § 1395(b).
 Fisher et al., "Slowing the Growth of Health Care Costs."
 Press release, "Taming Wide Variations in Spending Key to Health Reform," Dartmouth Institute for Health Policy & Clinical Practice, February 26, 2009, at http://www.dartmouthatlas.org/press/NEJM_Release_RWJF
_022609.pdf (May 21, 2009).
 For example, see Stuart M. Butler and Robert Moffit, "The FEHBP as a Model for a New Medicare Program," Health Affairs, Vol. 14, No. 4. (Winter 1995), pp. 47-61, at http://content.healthaffairs.org/cgi/reprint/14/4/47 (January 8, 2010).