[Economic Report of the President (2013)]
[Administration of Barack H. Obama]
[Online through the Government Publishing Office, www.gpo.gov]



In March 2010, the President signed into law the Affordable Care Act.
Provisions of the Act have already helped millions of young adults
obtain health insurance coverage and have made preventive services
more afford�able for most Americans. When fully implemented, the law
will expand coverage to an estimated 27 million previously uninsured
Americans and ensure the availability of affordable comprehensive
coverage through tra�ditional employer-sponsored insurance and new
health insurance market�places or exchanges. There are signs that the
Affordable Care Act has started to slow the growth of costs and
improve the quality of care through pay-for�performance programs,
strengthened primary care and care coordination, and pioneering
Medicare payment reforms. These provisions, as well as others in the
Affordable Care Act, will help to bend the cost curve downward while
laying the foundation for moving the health care system toward
higher quality and more efficient care.

Health Care Spending

Health care spending has increased dramatically over the past half
century, both in absolute terms and as a share of gross domestic
product (GDP) (Figure 5-1). Spending in the U.S. health care sector
totaled $2.7 tril�lion in 2011, up by a factor of 3.9 from the
$698.3 billion (in 2011 dollars) spent in 1980. Health care spending
in 2011 accounted for 17.9 percent of GDP�almost twice its share in
Some of the increase in health care spending is attributable to
demo�graphic changes. Of the real increase in spending on
prescription drugs, office-based visits, hospitalizations, and all
other personal care from 1996 to 2010, for example, 11.5 percent can
be accounted for by the changing



age structure of the population and 22.8 percent can be accounted
for by increases in the size of the population (Figure 5-2).1 The
effects of popu�lation aging will become a more important driver
of higher spending in coming years; by 2030, one in five Americans
will be over age 65, com�pared with only one in eight today,
and per capita medical costs in a given year are approximately three
times greater for those 65 and over than for younger individuals.
The majority of the increase in health care spending, historically,
has come from increases in the amount spent per person over and
above any effects attributable purely to population aging and
population growth, reflecting increases in the use of medical
services driven at least in part by the development of new
technologies and increases in unit costs that exceed the overall rate
of inflation.

1 Total annual spending on prescription drugs, office-based visits,
hospitalizations and other personal care between 1996 and 2010 was
estimated using the Medical Expenditure Panel Survey (MEPS). To
estimate the effect of changes in the age distribution between 1996
and 2010 on spending, age-specific spending levels and total U.S.
population were held constant at 1996 levels, but the proportion of
the population within each age group was allowed to reflect the
2010 age distribution. To estimate the effect of population growth
between 1996 and 2010 on spending, total spending increases were
calculated holding age-specific spending levels constant at 1996
levels, but allowing both the age distribution and total population
to reflect their 2010 values. Then, the estimated spending increases
due to changes in the age distribution were subtracted from this

Chapter 5


Long-Term Spending Growth

Why has health care spending risen so much, even after taking into
account changes in the size and age mix of the population? A likely
piece of the story is that long-term growth in health care wages
has not been accom�panied by corresponding labor-saving
technological progress. The theory of �cost disease� as developed
by Baumol and Bowen (1966) notes that labor�saving technological
progress has led to significant increases in labor pro�ductivity
and hence wage growth in some important parts of the economy (such
as the manufacturing sector). To compete for workers, labor-intensive
sectors such as health care, education, and the performing
arts also must raise their wages. According to the theory,
productivity growth has been slower in these sectors. The result,
the argument concludes, is an increase in the relative cost of output
in these labor-intensive sectors, as higher costs are passed on to
consumers in the form of higher prices.
Consistent with this theory, Nordhaus (2006) found that labor-
intensive sectors generally experienced rising relative prices
between 1948 and 2001. Nordhaus also found that shifts in labor
from sectors that experienced labor-saving technological progress
to sectors that remained relatively labor-intensive lowered overall
productivity growth, as the share of labor-intensive sectors in
overall output rose over the second half of the 20th century.


The cost-disease diagnosis assumes that, in labor-intensive
sectors, it is difficult to reduce the amount of labor required to
produce a given set of outputs. The health care sector, however, has
experienced substantial technological progress, as new pharmaceutical
therapies, diagnostic and medical devices, and surgical procedures
have been introduced, allowing many conditions to be treated more
effectively than in the past.

While some of these innovations have been labor-saving (some
pharmaceuticals, for example), most others are complementary to
expensive specialist labor (such as imaging and advances in surgical
procedures). Consequently, technological change in medicine has
caused the cost per treatment to rise, even as improvements in
clinical effectiveness have led to increases in medical productivity.
Technological change in medicine has contributed to long-term
increases in spending. A recent study found that a quarter to a half
of the rise in health care spending since 1960 can be explained by
technological change in the health care system (Smith, Newhouse,
and Freeland 2009). And rather than satisfying a relatively fixed
demand for health care at lower cost, the development of many of
these new technologies has contributed to an increase in the demand
for health care services.
For some researchers, the importance of technological change
for health care spending points to increases in demand as an additional
explana�tion to the cost disease theory for why health care spending
has increased disproportionately with income. If health care is a
"super-normal good" good associated with an elasticity of consumption
with respect to income that is greater than one-then as incomes rise
by a certain percentage, con�sumption of health care rises by a
greater percentage. Hall and Jones (2007) argue that this can happen
if, after achieving a certain level of consumption, individuals prefer
to spend additional income on life-extending health care (which allows
for consumption in the extended years of life) rather than on extra
consumption now. Consequently, as incomes rise, people choose to spend
ever more on health care over other goods.
The disproportionate effect of income on the demand for health care
may also operate through larger institutional mechanisms. Consistent
with this idea, Smith, Newhouse, and Freeland (2009) find that income
growth affects health care spending growth primarily through the
actions of governments and employers on behalf of large insurance
pools, suggesting a key role for payment reform in affecting medical
spending growth.
These factors are not only a U.S. phenomenon. Indeed, while the
United States has higher levels of health care spending than other
members of the Organisation for Economic Co-operation and Development
(OECD), the annual real rate of growth in health care spending per
capita in the

164 | Chapter 5

United States between 1960 and 2010 was not too different
from elsewhere, averaging 4.13 percent compared with 3.62 percent in
the other OECD countries, adjusted for purchasing power parity.
In more recent years, health care spending has continued to grow at
similar annual real rates�3.10 percent in the United States and 3.30
percent in the other OECD countries between 2000 and 2010, somewhat
below the long-term rates of spending growth observed since 1960.

Medical Productivity

Productivity growth in health care largely has taken the form
of improvements in the quality of care, with developments in new
procedures and care practices contributing to increased survival,
decreased morbidity, reduction in pain, and less onerous treatment
administration in many cases.
A full accounting of medical productivity growth should reflect
changes not only in cost per service but also in health outcomes.
However, medical productivity is often hard to measure because
health outcomes are hard to measure. Recent studies comparing
increases in life expec�tancy to increases in treatment costs
over time suggest that productivity growth in the health care
sector has been enormous. For example, Cutler and McClellan (2001)
found that the value of increased survival rates and decreased
morbidity rates as a result of improved treatment of heart attacks,
low-birth-weight infants, and depression over the past few decades
has far exceeded the increased spending on these conditions over
the period. Using a similar methodology, Philipson et al. (2012)
found that survival gains across all cancer patients in the United
States between 1983 and 1999 cost on average only $8,670 per
life-year gained. Estimates of the value of a sta�tistical life-year,
based on compensating wage differentials that measure the implied
trade-off between wages and increased risk of fatality, are typically
multiples higher (Viscusi and Aldy 2003). Therefore, even if some
piece of the apparent gain in longevity results from earlier
diagnosis, the introduc�tion of these cancer therapies represents
an enormous improvement in productivity. Faster growth in spending
on cancer treatment in the United States than in Europe over this
period is sometimes mistakenly taken to indicate the inefficiency of
U.S. medical care, but it is also the case that the improvement in
life expectancy for cancer patients was greater in the United States
than in Europe. From 1983 to 1999, U.S. spending per cancer patient
rose by $16,700 (in 2010 dollars) more than European spending per
cancer patient (Figure 5-3), and U.S. cancer patient life expectancy
rose by 0.4 years more than European cancer patient life expectancy
(Figure 5-4), implying a cost per extra life year saved of
approximately $42,000. Given the consensus

| 165

in the literature that the value of additional life-years is much
higher, the additional U.S. spending has been a good value.

Murphy and Topel (2006) directly estimate the aggregate mon�etary
value of increases in longevity, finding that, if valued in the
national accounts, increases in life expectancy since 1970 would have
added $3.2 trillion a year to national wealth. While a different set
of assumptions about the statistical value of a life year, the
elasticity of intertemporal substitution, and the value individuals
place on non-working hours lowers the aggregate valuation of the
observed longevity increase, the order of magnitude of the estimated
valuation nonetheless suggests an enormous return to the increase in
health care spending over this period.
In general, estimating how much the productivity of health care
has grown is a difficult task. Changes in health outcomes, morbidity
rates, and patient convenience are hard to measure, hard to attribute
to the use of spe�cific technologies, and hard to value. Furthermore,
limitations in available data mean that spending often cannot be
disaggregated to the treatment of specific diseases or patients. Given
these difficulties, it is widely agreed that aggregate measures of the
output of the health care sector do a poor job of capturing the
effects of productivity growth. Developing better methods to measure
real output and productivity growth in health care is an important
area of ongoing research (Data Watch 5-1).

Sources of Inefficiency in Health Care Spending

Although growth in overall medical productivity has been large,
not all increases in medical spending are productive. Cutler and
McClellan (2001) showed that improved treatment of heart attacks
produced sig�nificant increases in patient longevity between 1984
and 1998. By contrast, Skinner, Staiger, and Fisher (2006) found
little improvement in survival rates among heart attack patients
between 1996 and 2002 despite significant growth in treatment
costs. The latter study also found that the regions with the
largest increases in spending also experienced the smallest gains
in sur�vival. Geographic variation in practice patterns and health
outcomes implies that more than 20 percent of Medicare spending on
heart attack treatment produces little health value (Skinner, Fisher,
and Wennberg 2005). The case of heart attack treatment points to more
general inefficiencies in the alloca�tion of spending within the
health care system.
Among the many possible sources of spending inefficiencies, several
stand out as key sources of waste. First, the fragmentation of the
delivery system contributes to a failure to provide patients with
necessary care. That in turn can lead to complications and readmissions,
particularly for the chronically ill for whom care coordination is most
essential for health.
Data Watch 5-1: Toward Disease-Based Health Care Accounting

Existing national data on health expenditures generally are
orga�nized by the type of medical care that individuals purchase
(such as doc�tor visits or drugs). For addressing questions related
to the productivity of health care, however, data on health care
spending by disease would be far more useful.
Switching to disease-based accounting poses a challenge because
patients often suffer from more than one disease at once, making it
difficult to allocate spending to specific diseases. Three conceptual
approaches to allocating spending across disease have been suggested:
tracking each encounter with the health care system; tracking disease
"episodes"; or identifying all conditions a person has and using
regres�sion analysis to allocate spending to diseases. All three
approaches have advantages and limitations, and a consensus has not
yet developed on which one is preferable. Whichever approach is
adopted, the universe of conditions will need to be categorized into
a set of disease groups, at an appropriate level of detail, to which
Medical costs then can be assigned for analysis.
The Medical Expenditure Panel Survey (MEPS) is a nationally
representative survey that provides information on most health
spend�ing, although it fails to capture spending on behalf of
institutionalized patients and active duty military. The MEPS sample
is too small, however, to represent rare conditions. Although not
comprehensive in their coverage, data on health care claims provide
another  valuable�and potentially much more detailed�source of
information on health care spending. In addition to data on spending,
data on health outcomes that can be linked to the disease-based
spending data also are needed.
Important progress has been made toward developing
disease-based health care data. The Bureau of Economic Analysis is
working on a health care satellite account that will provide
disease-based measures of household medical expenditures. These
estimates will be based on private insurance claims data, Federal
data on Medicare and Medicaid spending, and data from MEPS on the
uninsured. Simultaneously, the Bureau of Labor Statistics is
developing disease-based price indexes that account for shifts in
treatment patterns. These indexes will be useful to the Bureau of
Economic Analysis for decomposing spending into changes in prices
versus changes in quantities.
The Affordable Care Act has significantly increased funding for
research on patient-centered outcomes, and data will be available
to qualified entities to evaluate the performance of providers and
suppli�ers with respect to quality, efficiency, effectiveness, and
resource use. Under the President�s Open Data initiative, the
Department of Health and Human Services has launched a Health Data
Initiative to promote the availability of Medicare and Medicaid
data, where appropriate, to researchers and entrepreneurs.
Paralleling these initiatives, the Health Care Cost Institute, a
nonprofit organization, has developed a claims database to be made
available to researchers to foster a better under�standing of what
drives health care costs. These administrative data on claims hold
the potential for further progress on understanding the drivers of
health care spending increases and identifying high value medical

Second, lack of care coordination also contributes to duplicate
care and overtreatment, a source of waste exacerbated by payment
systems that compensate physicians based on the number of services
provided (see Economic Applications Box 5-1). Overuse of expensive
medical technologies is particularly costly, and some research
suggests that a significant portion of coronary artery bypass graft
surgery, angioplasty, hysterectomy, cataract surgery, and angiography
is of questionable or low medical value (Goldman and McGlynn 2005).
Third, the failure of providers to adopt widely recognized best
medical practices also contributes to waste. These failures include
lack of adherence to established preventive care practices and patient
safety systems, as well as widespread failure to adopt best treatment
practices. In cases where the best medical practice is both clinically
more effective and lower in cost�for example, the use of beta
blockers in the treatment of acute myocardial infarction (Skinner
and Staiger 2005, 2009)�failure to follow these practices results in
worse clinical outcomes and higher readmissions and contributes to
wasteful spending.
Finally, payment fraud also adds to system waste, not only
through inappropriate payments but also through the administrative
burden on hon�est providers who must adhere to the regulatory
requirements of unavoid�able but burdensome fraud detection systems.
Taken together, fragmentation of care, overtreatment, failures of
care delivery, and payment fraud have been estimated to account for
between 13 and 26 percent of national health expenditures in 2011
(Berwick and Hackbarth 2012). The magnitude of this waste offers
an equally large opportunity for spending reductions and improvement
in quality of care�an opportunity that underpins many of the
provisions of the Affordable Care Act.

Economics Application Box 5-1: Matching in Health Care

Traditional economic analysis focuses on markets in which prices
and quantities adjust so that in principle, supply equals demand.
In some markets, however, prices do not exist and cannot be used
to allocate resources. Gale and Shapley (1962) made early
theoretical contributions to our understanding of how markets can
be designed to allocate resources efficiently in the absence of
prices. Taking the �marriage market� as an example, Gale and
Shapley studied how, in the absence of prices, these markets can
produce stable matches�matches where no alternative pairing would
make both individuals in any match better off. These principles
were extended by Roth, who applied them to the practical design of
market institutions�for example, the market for medical students
in residency programs (Roth 1984), and the assignment of students
to public high schools in New York City and Boston (Abdulkadiroglu,
Pathak, and Roth 2005). For these pioneering contributions, Shapley
and Roth were awarded the 2012 Nobel Prize in Economic Sciences.
The market for live kidney transplants is yet another market where
prices do not determine allocation. Paying for organs is a felony
under the 1984 National Organ Transplant Act. Patients can receive
a kidney from a compatible donor or are placed on a waiting list
for a cadaveric kidney. Currently, nearly 95,000 patients in the
United States are waiting for a kidney transplant. Dialysis for
these patients costs approximately $60,000 a year, for a total of
$30 billion a year, or 6.7 percent of total Medicare spending, the
single most expensive component of Medicare. In 2011, there were
about 11,000 transplants of deceased donor kidneys and only 5,770
transplants from living donors; in the same year, more than 4,700
patients died while waiting for a kidney transplant.
Many patients have willing potential donors. However,
immuno�logical incompatibility greatly limits the number of
transplants using live kidneys, which are preferred to cadaverous
kidneys for their tissue quality and greater longevity. Patients
receiving a live kidney transplant are estimated to live 10-15 years
longer than they would on dialysis.
Increasing exchanges between incompatible patient-donor pairs
would greatly expand the opportunity for dialysis patients to receive
a living donor kidney, and increase the quality of matches. In paired
kidney exchanges, a donated kidney from one (immunologically
incompatible) patient-donor pair is transplanted in the patient of a
second patient-donor pair, and vice versa. The potential for
improving the number of live kidney transplants is greater with
"chains"--exchanges involving many donor-recipient pairs. The 2007
amendment to the National Organ Transplant Act clarified that kidney
paired donations

170| Chapter 5

(KPD) do not constitute "valuable consideration"
(that is, financial com�pensation), thereby paving the way for the
creation of KPD exchanges.
The economic principles of stable matches developed by Shapley
and Roth can be applied to KPD exchanges. Whereas the concept of
stability in the medical residency setting, for example, is based
on the mutual preferences of medical students and residency programs,
stability in a kidney exchange is primarily based on obtaining the
best matches along immunological criteria. Using these principles,
transplant centers have established KPD programs, as have nonprofit
organizations such as the New England Program for Kidney Exchange,
founded by Roth and colleagues. Congress also established a national
KPD pilot program, operated under the Organ Procurement and
Transplantation Network (OPTN) as a nonprofit under Federal contract.
In 2011, the separate pilot KPD programs, including OPTN,
resulted in 430 transplants�a promising start to paired kidney
exchanges, but nevertheless representing only a fraction of the
potential number of possible transplants.
Computer models suggest that many more transplants could be
achieved each year if there were a nationwide pool of all eligible
donors and recipients. A larger pool of eligible donor-recipient
pairs also could potentially increase the quality of matches. A
living kidney transplant (and all subsequent care) saves money over
dialysis after roughly two years. On average, Medicare would save
$60,000 a year for every patient who receives a living kidney
transplant rather than continuing to receive dialysis, all while
increasing the life expectancy of a kidney recipient by 10�15 years,
again relative to dialysis treatment.

EarIy Implementation of the Affordable Care Act

The Affordable Care Act includes a series of provisions that will
transform the Nation�s health care system. By expanding coverage, the
health reform law stabilizes insurance markets and makes health
insurance affordable. The Affordable Care Act also includes important
provisions that are aimed at reducing inefficient spending, promoting
competition, and improving the quality of medical care.

Economic Benefits of Insurance
Insurance provides important economic benefits to covered
households. It covers unforeseen medical expenditures, allowing
individuals to receive necessary medical treatment without suffering
potentially crippling financial consequences.

| 171

The 2008 Medicaid expansion in Oregon provided a unique setting
in which to study the effects of health insurance on health and
financial security. Because access to the Oregon Medicaid coverage
expansion was offered through a lottery, the benefits of insurance
could be estimated without the usual statistical concerns that
purchasers of insurance differ from non-pur�chasers in ways related
to health and financial outcomes. Finkelstein et al. (2011) found
that, after one year of Medicaid coverage, previously uninsured
adults in Oregon were 10 percent less likely to report having
depression and 25 percent more likely to report their health as good,
very good, or excellent. They also experienced lower financial
strain because of medical expenses, including lower out-of-pocket
expenditures, lower debt on medical bills, and lower rates of refused
medical treatment because of medical debt, than individuals who were not
randomly assigned to Medicaid coverage.

The benefits of having insurance coverage are large. A recent
study (CBO 2012a) estimated that the insurance value of Medicaid to
enrollees in the lowest quintile of income earners is equivalent
to 11 percent of their before-tax income, defined by the CBO as
market income plus cash trans�fers. As a comparison, real average
before-tax incomes in the lowest quintile rose 15 percent between
1995 and 2009, while real incomes in the highest quintile rose
24 percent. Hence, the value of Medicaid is roughly comparable to
the additional income that would have kept average income in the
lowest quintile growing at the same rate as average income in the
highest quintile.

Expanding Affordable Health Insurance Coverage
The Affordable Care Act is projected to increase the number of
insured individuals in the United States by 14 million in 2014 and by
27 million in 2022 (CBO 2012b). The requirement that health insurance
plans offer dependent coverage to children up to age 26 went into
effect in 2010. Sommers (2012) found that this provision resulted
in more than 3 million uninsured young adults gaining health insurance
between September of 2010 and December of 2011.
Looking ahead to 2022, the Congressional Budget Office
(CBO 2012b) projects that the Affordable Care Act will lead to an
additional 12 million people being insured through Medicaid and the
Children's Health Insurance Program (CHIP), with the remainder of the
estimated 27 mil�lion newly insured individuals covered through
employer-based insurance, the Affordable Insurance exchanges, or the
Small Business Health Options Program (SHOP) exchanges (Economics
Application Box 5-2). The law likely will cause some firms that
currently do not offer health benefits to begin doing so, and some
workers who are currently uninsured will take up employer coverage
that is already offered. At the same time, the new

172 | Chapter 5
Economics Applications Box 5-2: Economics of Adverse
Selection and the Benefits of Broad Enrollment

In health insurance markets, adverse selection occurs when
relatively unhealthy individuals are more likely than healthy
individuals to purchase health insurance coverage at a given price.
Insurers understand this tendency and attempt to set premiums to
reflect average expected expenditures in a plan. The selection of
relatively unhealthy enrollees into coverage raises average
expected expenditures, resulting in higher premiums and more adverse
selection into coverage.
Adverse selection explains why offered premiums in the individual
and small group health insurance markets often are too high for most
healthy people compared with the health costs they actuarially can be
expected to incur, meaning that they either pay too much for coverage
or choose to go uninsured rather than pay the high premiums. In some
cases, insurance markets subject to extreme adverse selection may
disappear completely (Cutler and Reber 1998).
Encouraging broad participation in health insurance coverage
helps tremendously to solve the market failure associated with adverse
selection. For example, adverse selection is virtually nonexistent
in the large group employer sponsored insurance (ESI) market.
Take-up rates in this market are very high, thanks both to the tax a
dvantages associated with ESI and to the fact that employers typically
pay a portion of premi�ums, which makes ESI a good deal for the vast
majority of employees. While employer contributions are offset by
lower wages in equilibrium (Gruber 1994; Baicker and Chandra 2005),
employees who decline coverage rarely recoup the employer
contribution on the margin. The large enrollment in many ESI plans
means that a small number of high expenditure enrollees does not
dramatically affect premiums for a large risk pool. This prevents
adverse selection from taking root and reinforces broad enrollment
through premium stabilization and affordability.
Similarly, the Affordable Care Act encourages broad enrollment
through the widespread accessibility of health insurance exchanges,
the individual responsibility requirement related to the purchase
of health insurance, and the financial assistance offered to
lower-income earners to purchase private plans on an insurance
exchange. Other provisions of the Affordable Care Act raise consumer
awareness and foster consumer choice through information campaigns,
standardization, and consumer search tools, similar to those
implemented in the successful rollouts of the Medicare Advantage and
Medicare Part D prescription drug programs. As in ESI, broad enrollment
in the exchanges is expected to foster premium stability and
affordability and to reduce the incidence of cost-shifting from
uncompensated care to the insured.

| 173

options created by the Affordable Care Act may make
employer-sponsored insurance (ESI) coverage less attractive for
some employers. The net effects on the prevalence of
employer-sponsored coverage, however, are likely to be small.
Based on microsimulations of firms� optimizing behavior, analysts
have estimated effects of the Affordable Care Act on the number of
individu�als with ESI coverage ranging from a 1.8 percent decline
(CBO 2012b) to a 2.9 percent increase (Eibner et al. 2011). Other
estimates fall with this nar�row range (Buettgens, Garrett, and
Holahan 2010; Lewin Group 2010; Foster 2010) and are consistent
with the small positive effects of health reform on ESI coverage
observed in Massachusetts, where similar statewide health insurance
reforms were legislated in 2006 (Long, Stockley, and Yemane 2009).

Consumer Protection
The Affordable Care Act also establishes numerous consumer
protections related to the purchase of private health insurance,
some of which are already in effect. Starting in 2014, individual
and group health plans will not be allowed to deny or limit coverage
on the basis of an individual�s health status. And within certain
limits, premiums will be allowed to vary by age, geography, family
size, and smoking status, but not by individual health status,
gender, or other factors.
The Affordable Care Act also requires that double-digit increases
in insurance premiums be reviewed by States or the Department of
Health and Human Services, with insurance companies needing to
provide justification for any such premium increases. Plans may be
excluded from an insurance exchange based on premium increases that
are not justified. Further, since the beginning of 2011, most
insurers have been allowed to retain no more than 20 percent of
consumers' premiums for profits, marketing, and other administrative
costs. Overhead and administrative costs in excess of this limit
are to be rebated to consumers (or in the case of
employer-sponsored insurance, to employers, who must pass a share of
these rebates to their employees as cash, improved benefits, or
lower premiums, with the share depending on the proportion of the
total health plan premium paid by the employees). As of August
2012, an estimated 12.8 million Americans had received rebates
totaling $1.1 billion from insurers as a result of this 80/20
medical loss ratio rule.

Health Care Spending and Quality of Care
The Affordable Care Act includes a series of provisions designed
to reduce spending while improving the quality of care in the
health .

174 | Chapter 5

care system. Reducing excessive payments to Medicare Advantage plans,
strengthening antifraud efforts, and initiating reforms to Medicare
provider payment systems, among other policies, are expected to extend
the life of the Medicare Trust Fund by an additional eight years.
These reforms comple�ment numerous other provisions that improve
health care quality while lowering costs.
The Hospital Value-Based Purchasing Program went into effect in
October 2012. The program rewards more than 3,500 hospitals for
providing high-quality care and reduces payments for hospitals
demonstrating poor performance. Similar pay-for-performance programs
in Medicare Advantage and the end-stage renal disease prospective
payment system encourage higher-quality care and more efficient care
delivery. Additionally, pay-for-reporting initiatives in which providers
are rewarded for reporting procedures and outcomes have been launched
in virtually every Medicare payment category, and mark the first step
toward value-based purchasing.
The Partnership for Patients program is a public-private
partnership that aims to reduce hospital complications and improve
care transitions in more than 3,700 hospitals and partnering
community-based clinical organizations. By stopping millions of
preventable injuries and complica�tions in patient care, this
nationwide initiative has set as its goal saving 60,000 lives and
up to $35 billion in spending, including up to $10 billion in
Medicare spending, over the three years following its launch. Data
provided by the Centers for Medicare and Medicaid Services (CMS)
show that since the Partnership for Patients program was introduced
in 2011, the hospital readmission rate within Medicare has fallen
to 17.8 percent, down from an average of about 19 percent that had
prevailed from 2007 through 2010 (CMS 2013) (Figure 5-5). The data
also show that the declines were larger in hospitals participating
in Partnership for Patients.
The Affordable Care Act builds on the investments made in the
Recovery Act to encourage the use of health information technology.
By making it easier for physicians, hospitals, and other providers
to assess patients� medical status and provide care, electronic
medical records may help eliminate redundant and costly procedures.
More than 186,000 health care professionals (about one-third of
eligible providers) and 3,500 hospitals (about two-thirds of
eligible hospitals) have already qualified for incentive payments
for the meaningful use of electronic health records authorized by
the Recovery Act.
The Affordable Care Act also launched extensive efforts to
prevent and detect fraudulent payments under Medicare, Medicaid,
and the Children�s Health Insurance Program. An important goal of
the Administration's efforts has been to prevent fraudulent payments
before they are made rather
| 175

than chasing them afterward, but there also are ongoing efforts to
recover fraudulent payments if they occur. Antifraud efforts have
recovered a record-high $14.9 billion over the last four years.

Medicare Payment Reform
Traditional fee-for-service Medicare reimburses physicians for
each service provided, creating incentives for overutilization.
Spending ineffi�ciencies are exacerbated by fragmentation across
providers, who historically have had few incentives to coordinate
care. Likewise, the prospective pay�ment system (PPS) for Part A
hospital services, which is designed to control costs by paying
hospitals a prospective amount per diagnostic-related group (DRG)
episode, is not immune to waste. While the DRG-based PPS encour�ages
more efficient care and reductions in length of stay compared with
cost-based reimbursement (Sloan et al. 1988; Seshamani, et al.
2006), it also can encourage a reduction in necessary care, leading
to negative short-term health effects and readmissions (Cutler 1995;
Encinosa and Bernard 2005; Seshamani, et al. 2006). Further, the
inpatient PPS also can be susceptible to �upcoding,� whereby
providers code patients as being sicker than they are to raise the
risk-adjusted prospective payments (Cutler 1995; Carter et al.
2002; Dafny 2005).

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To curb these inefficiencies, the Affordable Care Act has
established initiatives that lay a foundation for reforming care
delivery and physician payment. At their core, these initiatives
are designed to foster greater coor�dination of care across
providers, while simultaneously aligning financial incentives to
encourage provider organizations to deliver higher-quality, more
efficient medical care. Each initiative builds on a core of
clinical and patient engagement quality measures to ensure that
\cost savings are derived from more efficient delivery of care
and not reduced patient access or care quality.
One such initiative is the Medicare Shared Savings Program (MSSP).
Under this program, providers deliver care through accountable
care organizations (ACOs), contractual organizations of primary
care physi�cians, nurses, and specialists responsible for
providing care to at least 5,000 beneficiaries. The Federal
Government shares any savings generated for those beneficiaries,
relative to benchmarks, with ACOs that meet rigorous quality
standards, giving the ACOs incentives to invest in delivery
practices, infrastructure, and organizational changes that help
deliver higher-quality care for lower costs. Currently, more than 4
million beneficiaries receive care from more than 250 ACOs
participating in the MSSP and other CMS projects, with ACO
participation and covered beneficiaries continuing to increase as
the program expands.
The Affordable Care Act also created the Center for Medicare
and Medicaid Innovation, which is charged with identifying,
testing, and ultimately expanding new and effective systems of
delivering and paying for care. The CMS Innovation Center is
authorized to invest up to $10 billion in initiatives that have
the potential to reduce program expenditures while preserving or
enhancing quality of care furnished to individuals under Medicare,
Medicaid, and the Children's Health Insurance Program. Initiatives
within the CMS Innovation Center include shared savings mod�els,
as well as bundled payments to hospitals and post-acute-care providers.
The Innovation Center's Pioneer ACO program is a more aggressive
version of the MSSP and is open to organizations that have had
success with risk-based payment arrangements. Pioneer ACOs may
keep a greater share of Medicare savings than ACOs in the MSSP
but are also at greater risk for losses if spending benchmarks
are not met. Successful Pioneer ACOs are also eligible to move to
a population-based payment arrangement whereby they assume greater
financial risks and rewards for a predetermined set of patients.
This greater risk-reward profile further encourages investments
in care coordination and best practice delivery reforms. Pioneer
ACOs must also develop similar outcomes-based payment arrangements
with other

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payers, extending payment innovations to the commercial market and
maxi�mizing the impact of the program�s incentives.
Currently, roughly 860,000 beneficiaries are enrolled in 32
Pioneer ACOs. The Pioneer program is just entering its second year,
so it is too early for any comprehensive assessment, but Pioneer
ACOs do seem to be making substantial investments in infrastructure
and care processes. Infrastructure investments include health
information technology adoption and improved data analytic
capabilities, which enable providers to identify opportunities
for improvements in care processes and the quality of care.
For example, the potential savings associated with early
identification and treatment of patients with high propensity for
developing a chronic disease have led some Pioneer ACOs to make
organizational changes that place greater focus on primary care
and disease management. CMS is supporting Pioneer ACOs
by providing privacy-protected patient information to promote
care coordina�tion, hosting collaborative learning networks, and
offering other technical assistance.
Care coordination is also central to the Comprehensive Primary
Care (CPC) initiative. Primary care is critical to promoting
overall health and reducing medical spending. Yet because any one
insurer accounts for only a fraction of a provider�s business,
insurers underinvest in primary care systems that would improve
care coordination. Through the CPC initiative, Medicare partners
with State and commercial insurers to promote community-wide
investments in the delivery of coordinated primary care.
Simultaneously, through direct financial payments or shared
Medicare savings, the CPC initiative rewards high-quality
providers who reduce health care costs through investments
in care coordination. At the end of 2012, about 500 primary care
practices were participating in the CPC initiative,
representing 2,343 providers serving approximately 314,000
Medicare beneficiaries.
The CMS Innovation Center has introduced bundled payments as a
model for hospital payment and delivery reform. A bundled payment
is a fixed payment for a comprehensive set of hospital and/or
post-acute services, including services associated with
readmissions. Moving from individual payments for different
services to a bundled payment for a set of services across
providers and care settings encourages integration and coordination
of care that will raise care quality and reduce readmissions.
Variants on bundled payments are being demonstrated, differing in
the scope of services included in the bundle, and whether payment
is retrospec�tive (based on shared Medicare savings) or prospective,
which intensifies the financial risk and return to investing in
changes to the efficiency and quality

178 |

of care. Currently, 467 health care organizations across 46 states
are engaged in the bundled payment initiative.

Is the Cost Curve Bending?
The real rate of health expenditure growth has declined or
remained constant in every year between 2002 and 2011. For each of
the three years 2009, 2010 and 2011, National Health Expenditure
data show the real rate of annual growth in overall health spending
was between 3.0 and 3.1 percent, the lowest rates since reporting
began in 1960.
Additionally, the National Health Expenditure data show that
growth in Medicare spending fell from an average of 8.6 percent a
year between 2000 and 2005 to an average of 6.7 percent a year
between 2006 and 2010. Notably, over a third--2.5 percentage
points-of the 2006-2010 growth was attributable to increases in
Medicare enrollment. With the exception of a spike in 2006, the
year Medicare Part D was introduced, the growth rate of Medicare
spending per enrollee�a measure of health care spending intensity--
has been on a downward trend since 2001, with a particularly
significant slow�down over the past three years (see Figure 5-6).
Projections suggest the growth rate of Medicare spending per
beneficiary will decline even further. While Medicare enrollment
is expected to increase 3 percent a year over the next decade
(CMS 2012), the rate of growth in spending per enrollee is


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projected to be approximately the same as the rate of growth in GDP
per capita, according to the CBO and Office of the Actuary at CMS
(Kronick and Po 2013). Similarly, the rate of growth in spending per
Medicaid enrollee is projected to be near the rate of growth in
GDP per capita. In the commercial health insurance market, per
enrollee spending growth also has declined in recent years, the
proximate cause being a slowdown in the growth rate of per-enrollee
use of medical services (HCCI 2012).
There are several potential causes of the recent declines in
the growth rate of spending per enrollee. One factor is the recent
recession, in which job losses have caused the loss of insurance
coverage. However, the recession explains only a small fraction
of the declines in spending growth rates since the start of the
recession. The slowdown in the growth rate of per-capita health
expenditures began before the recession took hold, and has
continued through the economic recovery and into 2012.
As expected, changes in real per-capita total health care
spending at the state level are negatively correlated with changes
in unemployment in the state between 2007 and 2009 (Figure 5-7).
If the relationship in Figure 5-7 holds at the national level,
then the increase in the national unemploy�ment rate between 2007
and 2011 of 4.3 percentage points was associated with a $199
decline in spending per-capita (in 2007 dollars), or 2.6 percent
of per-capita health care spending in 2007. This accounts for
only 18 percent of the slowdown in spending growth since the start
of the recession in 2007 and an even smaller proportion of the
slowdown in spending growth since 2002, when the growth rate in real
per-capita total health care spending began to decline.2
Structural changes in the health care market offer another
explana�tion for the decline in per-enrollee spending growth. One
possibility is that hospitals and provider groups have increasingly
sought to improve efficiency�through adopting more high value
medical practices and per�forming fewer low value procedures�in
response to evidence showing their potential for cost savings and
quality improvements (Fisher and Skinner, 2010). At the same time,
formulary changes that encourage substitution away from branded to
generic drugs, and changes in insurance design that increase
patient cost sharing for both services and pharmaceuticals, also may
explain a portion of the declines in spending growth per enrollee
over the past decade. For example, the sharp slowdown in the
growth rate of medical
2 Between 2001 and 2006, real per-capital spending grew by 21.5
percent. Between 2006 and 2011, real per-capital spending grew
by 7.1 percent, where the 14.4 percentage point difference in
spending growth captures the slowdown in spending growth.
The 2.6 percent decline in total health care spending between
2007 and 2011 attributable to the recession accounts for
approximately (2.6/14.4)*100 = 18 percent of the slowdown in
spending growth since the start of the recession.

180  | Chapter 5


imaging since 2006 likely was due to a confluence of reforms including
prior authorization, increased cost sharing and reduced reimbursements
(Lee and Levy 2012). Notably, Lee and Levy found that a large fraction
of the declines involved imaging identified as having unproven
medical value. Similarly, payment reforms and regulations are thought
to have contributed to long-run declines in Medicare spending growth
rates (White 2008).
Early responses to the Affordable Care Act may have contributed
to the decline in per enrollee spending since 2010 (Kronick and Po
2013). Relevant provisions of the law include provisions intended to
foster coordi�nated care, improve primary care, reduce preventable
health complications during hospitalizations, and promote the
adoption of health information technology.
The decline in the hospital readmission rate, coinciding with
the introduction of the Partnership for Patients program in 2011,
also may point to early effects of the Affordable Care Act on
spending. The Act�s Medicare hospital readmissions reduction
program, introduced in October 2012, should reinforce these effects.
Likewise, infrastructure investments and care process changes, either
funded directly by the Affordable Care Act or stimu�lated through
the Affordable Care Act�s payment reform, are other possible sources
for the recent declines in spending growth.

| 181

In addition, spending declines may reflect early changes in medical
care delivery made in anticipation of impending Medicare payment
reform. The Affordable Care Act moves providers towards
savings-based pay�ment models in Medicare that encourage improved
coordination of care. Hospitals seeking new ways to reduce costs
and increase bargaining power with suppliers and insurers may
respond by consolidating their operations. Recent years have
seen a continued consolidation and integration of physi�cians
into provider networks.

The long-run growth rate of per-capita spending has significant
implications for the budget. Medicare spending represented 3.7
percent of GDP in 2011 (Medicare Trustees 2012). Under current law,
including cost control measures of the Affordable Care Act and
the Sustainable Growth Rate-mandated physician payment cut, CMS
projects that Medicare spend�ing will rise to represent 6.7 percent
of GDP in 75 years, with long-term nominal per-beneficiary spending
growing at a rate on average equal to 4.3 percent per year
(Medicare Trustees 2012). However, nominal growth rates of
per-beneficiary Medicare spending have been declining since 2001,
and over the past five years have averaged 3.6 percent. At least
some of the recent decline in Medicare spending growth appears to
be structural, implying that the low spending growth rates from
the past few years may persist.3 If the per-beneficiary growth rate
of Medicare spending were to remain 3.6 per�cent per year, then after
75 years Medicare spending would account for only 3.8 percent of
GDP, little changed from its share today, and substantially less
than what the Medicare Trustees estimate. (Figure 5-8). This should
not be interpreted as a forecast but rather an indication of how
sensitive long-term projections are to the assumed rate of growth of
Medicare spending per beneficiary. In this hypothetical scenario where
per-beneficiary Medicare spending grows at a rate equal to the one
observed over the past five years, Medicare spending as a share of
GDP would be much lower than what cur�rent long-term projections suggest.

The causes for the recent and projected declines in the growth
rate of medical spending and utilization, and their relationship to the
major quality-improving and cost-saving provisions of the Affordable Care
Act, remain an important area for future research. Enacted provisions of
the health reform law appear to be having positive effects on care
coordination, hospital outcomes and spending. And payment reforms that
better align payment with cost and provide incentives for efficiency such
as shared savings and bundled payment programs hold potential to improve
to care quality and reduce medical spending.

3 Regression analysis shows a flat and insignificant relationship between
state-level 2007-09 changes in per-beneficiary Medicare spending and
changes in unemployment, suggesting that little if any of the recent
declines in per-beneficiary Medicare spending growth is related to
regional cyclical factors.