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Appendix A
Learning What Works Best: The Nation’s
Need for Evidence on Comparative
Effectiveness in Health Care
AN ISSUE OVERVIEW
IOM ROUNDTABLE ON EVIDENCE-BASED MEDICINE
September 2007 version. This Issue Overview was prepared at the request
of the IOM Roundtable Working Group on Sustainable Capacity by J.
Michael McGinnis, LeighAnne Olsen, Katharine Bothner, Daniel O’Neill,
and Dara Aisner.
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LEARNING WHAT WORKS
MARCH 2009 UPDATE
The American Recovery and Reinvestment Act of 2009
In the time since the preparation of this white paper, $1.1 billion of fed-
eral funds have been provided by Congress, through the American Recovery
and Reinvestment Act of 2009 (ARRA), to increase national capacity for
clinical effectiveness research. AHRQ (Agency for Healthcare Research and
Quality) has received $700 million of these funds, of which $400 million
will be transferred to the Office of the Director of NIH (National Institutes
of Health) to conduct or support comparative effectiveness research (CER)
activities.
An additional $400 million will be allocated at the discretion of the
Secretary of HHS (Department of Health and Human Services) to:
“…accelerate the development and dissemination of research assessing
the comparative effectiveness of health care treatments and strategies,
through efforts that: (1) conduct, support, or synthesize research
that compares the clinical outcomes, effectiveness, and appropri-
ateness of items, services, and procedures that are used to prevent,
diagnose, or treat diseases, disorders, and other health conditions;
and (2) encourage the development and use of clinical registries,
clinical data networks, and other forms of electronic health data
that can be used to generate or obtain outcomes data.”
The recommendations from an Institute of Medicine consensus com-
mittee report and from a newly established Federal Coordinating Council
on CER within HHS will be considered by the secretary’s office in desig-
nating activities to receive funds. Members of the 15-member council will
be federal employees or officers appointed by the President, at least half of
which will have clinical expertise.
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APPENDIX A
LEARNING WHAT WORKS BEST
THE NATION’S NEED FOR
EVIDENCE ON COMPARATIVE
EFFECTIVENESS IN HEALTH CARE
Contents
Introduction
Implications for Stakeholders
Current Activities in Clinical Effectiveness Research
Activities and Needs Related to Comparative Effectiveness Research
Models for a Stronger Approach to Comparative Effectiveness Research
Decision and Implementation Considerations
Concluding Observations
APPENDICES
1. Current National Capacity for Clinical Effectiveness Research
2. International Activities in Clinical Effectiveness Research
3. Potential Model: Federally Funded Research and Development Centers
4. Potential Model: NIH Public-Private Partnership Program
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LEARNING WHAT WORKS
5. Potential Model: National Academies’ Transportation Research Board
6. Potential Model: Federal Reserve
7. The Business Case for Comparative Effectiveness Research:
A Commissioned Analysis
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APPENDIX A
Acknowledgments
This Issue Overview on current and needed capacity for comparative
effectiveness research was developed by staff of the IOM Roundtable on
Evidence-Based Medicine, initially as background material for the activities
of the Roundtable’s Sustainable Capacity Working Group, and to inform
discussion at the March 19, 2007 Roundtable meeting.
Guidance on structure and content were provided by members of
an advisory group including: Carmella Bocchino (AHIP), Queta Bond
(Burroughs Wellcome Fund), Kathy Buto (Johnson & Johnson), Steve
Galson (FDA), Mark McClellan (AEI-Brookings Joint Center for Regula-
tory Studies), Lisa Payne-Simon (Blue Shield of California Foundation),
Diana Petitti (University of Southern California), Jean Slutsky (AHRQ),
Sean Tunis (Center for Medical Technology Policy), and Gail Wilensky
(Project Hope).
We also extend special thanks to those who took the time to review and
comment on various sections or draft versions of this paper, including: Wade
Aubry (HealthTech), Tanisha Carino (Avalere Health), Nancy Featherstone
(AstraZeneca), Mark Gibson (OHSU), Carmen Hooker Odom (North Car-
olina HHS), Michael Johns (Emory), Peter Juhn (Johnson & Johnson),
Doug Owens (Stanford), Steve Pearson (AHIP), Steve Phurrough (CMS),
Eugene Rich (House Committee on Ways and Means, Health Subcommit-
tee), Wayne Rosenkrans, Jr. (AstraZeneca), and Jeff Shuren (FDA).
IOM staff who contributed include: Dara Aisner, Katharine Bothner,
Michael McGinnis, LeighAnne Olsen, and Daniel O’Neill.
Roundtable sponsors: The work of the Roundtable is supported by the
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LEARNING WHAT WORKS
Agency for Healthcare Research and Quality, AHIP (America’s Health
Insurance Plans), AstraZeneca, Blue Shield of California Foundation, Bur-
roughs Wellcome Fund, California Healthcare Foundation, Centers for
Medicare and Medicaid Services, Department of Veterans Affairs, Food and
Drug Administration, the HWG Fund, Johnson & Johnson, sanofi-aventis,
and Stryker.
Suggested citation Institute of Medicine. 2007. Learning what works best:
The nation’s need for evidence on comparative effectiveness in health care.
http://www.iom.edu/ebm-effectiveness.
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9
APPENDIX A
IOM ROUNDTABLE ON EVIDENCE-BASED MEDICINE
Working Group on Sustainable Capacity∗
LEARNING WHAT WORKS BEST
The Nation’s Need for Evidence on
Comparative Effectiveness in Health Care
INTRODUCTION
A core objective for the nation is achieving the best health outcome
for every patient. This objective simply cannot be accomplished until we
have better evidence on which to base healthcare decisions, as well as more
effective application of the knowledge we have. Each is vitally important.
We know, for example, that failure to deliver proven interventions is a
substantial challenge to the quality of health care for Americans—and is
a key concern of the IOM Roundtable on Evidence-Based Medicine. Yet,
with the current pace of change, the most rapidly growing problem is our
inability to produce the needed evidence in a timely fashion. This paper
provides background for discussion about the evidence gap—the fact that
the nation’s capacity has fallen far short of the need to produce reliable and
practical information about the care that works best. Medical care decision-
making is now strained, at both the level of the individual patient and the
level of the population as a whole, by the growing number of diagnostic
and therapeutic options for which evidence is insufficient to make a clear
∗ Jack Rowe, Columbia University (Chair); Adam Bosworth, Google; Helen Darling, Na-
tional Business Group on Health; Michael Johns, Emory University; Steve MacMillan, Stryker
Corporation; Mark McClellan, AEI-Brookings; Richard Platt, Harvard University; Steve Ud-
varhelyi, Independence Blue Cross; Bill Weldon, Johnson & Johnson; Janet Woodcock, FDA.
The material here is a staff paper prepared at the request of the working group. Information on
the IOM Roundtable on Evidence-Based Medicine may be obtained at www.iom.edu/ebm.
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0 LEARNING WHAT WORKS
choice. Biomedical insights and medical innovation continue to advance
opportunities to increase the health and life-span of the American public,
yet to capitalize fully on this potential requires enhanced capacity to ensure
that decisions, in the face of increasing complexity, can be supported and
guided by the best available scientific information.
Health care in the United States underperforms on many dimensions.
At the macro level, with per capita expenditures more than 20 percent
higher than any other country in the world and more than twice the average
expenditure for European countries[1], the nation ranks well below others
on key health indices—28th in overall life expectancy at birth and 23rd in
infant survival [2, 3]. In part this is because people often do not receive the
care they need. One study found that, where evidence exists, only about 55
percent of recommended services were actually delivered [4]. In part it is
also because the services people receive are not always necessary or the right
ones for them. The intensity of services for similar conditions with similar
results—in particular, for procedures such as lumbar surgery, hysterectomy,
and bypass surgery, where discretion plays a stronger role—can vary by
as much as a factor of 20 depending simply on where one lives. In Idaho
Falls, Idaho, 4.6 lumbar fusions were reported per 1,000 Medicare enrollees
annually, as compared with 0.2 in Bangor, Maine, with no difference in the
outcomes [5]. Similarly, wide geographic variations have been reported for
conditions such as hip fracture, colorectal cancer, and acute myocardial
infarction as well as end-of-life care [6], with a nearly fourfold difference
in cardiac bypass surgery rates, a phenomenon primarily related to the
region’s number of cardiac catheterization labs per capita rather than ill-
ness rates [7]. One estimate suggested that only 27 percent of the weighted
discrepancy in Medicare spending across regions could be explained by
population illness levels [7], and if all regional spending levels matched
those of the lowest decile, Medicare could see savings of up to $40 billion
(1996 dollars) without compromising health status [8]. Clearly, more does
not by itself equate to better—and the variation is greater for conditions in
which the evidence is more limited.
Ultimately, the central challenge is not primarily a matter of overuse or
underuse of services but instead is related to the lack of available evidence
to achieve the right care for any given patient. Information on which to
compare the results from drugs with the same purpose is often not avail-
able. For example, both Lucentis and Avastin are promising new drugs for
treatment of macular degeneration, but head-to-head information on the
relative outcomes is not available—and one costs about 20 times as much
as the other. Similarly, different approaches to radiation therapy—intensity-
modulated radiotherapy and conformal radiotherapy—have very different
costs but currently inadequate information on which to base clinical judg-
ments. And the pace of introduction of new genetic prognostic tests is on
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APPENDIX A
an exponential course without the necessary evidence about the results of
clinical decisions and outcomes.
Estimates range widely concerning the proportion of medical care in the
United States that is based on, or supported by, adequate evidence [9-14].
However, given concerns about the extent to which this information may
be generalized and the quality of the evidence that is used, some place this
figure at well below half. Regardless of the precise level, there is no question
about the need for improvement. Part of the challenge is the appropriate
delivery of what has already been proven effective. Medical care is becom-
ing more complex with the increase in multifaceted chronic diseases, the
development of new interventions, and the pressures to reduce the time of
patient-provider interaction in the face of greater administrative burdens.
New care management approaches, decision support systems, and incen-
tives will be required to help providers and patients work together to ensure
that the care delivered is the care that is known to be most effective.
The most rapidly growing problem may soon relate not so much to
shortfalls in applying what is known—a clearly significant problem—as
to the inability for evidence of comparative clinical advantage to keep
pace with innovation. It is both a capacity investment and a resource
allocation problem. Of the nation’s more than $2 trillion annual health
expenditure—nearly half of it borne by government—currently less than
0.1 percent [15, 16] is invested in assessing the comparative effectiveness of
available interventions. Although about 5 percent of overall health expen-
ditures is devoted to research, most is devoted either to basic research or
to product development [17], as opposed to assessing how well medical
treatment options perform. If trend data were kept, it would likely reveal
that the proportion of expenditures devoted to this assessment “budget”
was actually shrinking every year, yet the complexity of clinical decisions
continues to compound.
A testament to the power of innovation is the fact that new pharmaceu-
ticals, medical devices, biologics, and procedures are introduced constantly,
and the pace is quickening. From 1991 to 2003 the number of medical
device patents per year doubled, from 4,500 to nearly 9,100 [18]. From
1992 to 2001 the total biotechnology patents granted per year tripled, from
more than 2,500 to nearly 7,800, and the number of biopharmaceutical
patents granted in the United States increased nearly four-fold, from about
1400 to nearly 5,200 [19, 20]. In the same period, annual sales of biolog-
ics and pharmaceuticals more than doubled [21]. Between 1993 and 2004
there was a more than 80 percent increase in the number of prescriptions
received by Americans [22]. Data for the growth in procedures are more
difficult to obtain; however, as one example, between 1989 and 1995 spe-
cialized procedures in major teaching hospitals nearly tripled [23]. A recent
review by the Kaiser Family Foundation suggests that half or more of the
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2 LEARNING WHAT WORKS
growth in medical spending in recent years is attributable to technological
change [24].
Much, but certainly not all, of this change has resulted in better care.
Diagnostic imaging services, for example, grew more rapidly than any other
type of physician service under Medicare. Between 2000 and 2005 spending
on radionuclide imaging (RNI) doubled from $6.6 billion to $13.7 billion
[25]. Yet an American College of Cardiology Foundation technical panel
convened in 2005 to assess the appropriateness of cardiovascular RNI
imaging for 52 indications [26] found that the lack of clear evidence on the
best and most effective uses yielded strong disagreement on the appropriate
circumstances.
In addition to the growth in use of drugs, devices, biologics, and proce-
dures, the world of health care is about to experience dramatic new insights
concerning the variation in individual response to different diagnostic and
treatment interventions. The 3 billion base pairs of the human genome have
now been sequenced, revealing the 99.9 percent of the genetic code that
is common to all humans. Additional differences, such as the gain or loss
of regions of the genetic code, increase the variation between two random
individuals by five- to ten-fold. Cataloging and characterizing these differ-
ences by haplotype mapping and other initiatives is currently in progress
and will begin to reveal how people vary in their susceptibilities to diseases
and their responses to diagnosis and treatment.
The age of personalized medicine will soon be a reality, if the capacity
can be developed to contend with its insights. Today the average clinical
encounter already requires a health provider to manage more variables than
would be considered reasonable given what is known about the capabili-
ties of the human mind, and over the next decade that same encounter will
require contending with perhaps an order of magnitude more [27]. The
traditions of developing evidence through one-at-a-time studies and relying
for quality assurance on the recall capacity of an individual provider are
no longer practical.
Over the long term, substantial changes will emerge in the way the
nation goes about generating and applying evidence for clinical decision
making. A learning healthcare system is one in which the clinical research
paradigm depends more judiciously on the serial conduct of randomized
controlled trials—important, but often too expensive, untimely, and of
limited applicability—and draws more heavily on electronic health records
(EHRs) to generate evidence as a natural by-product of the clinical experi-
ence. But while these longer-term capacities emerge, substantial near-term
improvement will be necessary in our capacity to assess the relative effec-
tiveness of different interventions—to understand what works best for
whom under what circumstances. We need better understanding, agree-
ment, and focus on the value we get from our health care—including what
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APPENDIX A
constitutes value and how to measure it. Without this capability, it is likely
that the inefficiencies that currently characterize the U.S. healthcare system
will be compounded, perhaps considerably. Conversely, a more systematic
and sustained effort to develop evidence on comparative and “real-world”
effectiveness should stimulate more investment in research on innovation
that will deliver better outcomes and greater value.
Engaging the immediate need for a much stronger and sustained capac-
ity to meet the need for guidance on the clinical effectiveness of medical
interventions is the subject of this paper. Discussion follows on the perspec-
tives of the various stakeholders, the current capacity and activities on clini-
cal effectiveness research, the key functional needs to be met, and, finally,
some possible approaches to addressing the issues, including consideration
of decision principles, governance, funding, and public support.
IMPLICATIONS FOR STAKEHOLDERS
Better evidence is essential to securing trust in our healthcare system.
In the face of uncertainty borne of insufficient evidence, patients, provid-
ers, insurers, and health product companies frequently find themselves at
odds and distrustful of each others’ motives. Concern about the shortfall
in the national capacity to determine what medical care is actually best for
whom is shared among many stakeholders. Most important, of course, are
the patients who receive medical care and the health providers who deliver
it, but large stakes are also held by healthcare delivery organizations, insur-
ers, manufacturers, and others engaged in various aspects of health care,
with the shared goals of improving patient health and delivering the best
value. Increasing the level of investment in clinical effectiveness research,
and doing so in a comparative fashion, is key to facilitating significant
gains toward these shared goals. Roundtable teams are currently reviewing
the perspectives and action prospects as the various sectoral stakeholders
work to improve the prospects for the development of a learning healthcare
system. Following are some of the more important implications of accruing
substantially better information on clinical effectiveness.
Consumers-Patients
Each patient should be able to feel confident that there is solid evidence
that the care received is the appropriate care for his or her circumstances.
Yet, increasingly, this notion is strained. The American public has tradition-
ally expressed strong support for medical care, research, and technology
development, while also expressing a strong interest in both individual
patient prerogative and better information to aid decision making. But
with the increasing complexity of care and an increasing awareness of its
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2 LEARNING WHAT WORKS
In another study, mortality rates and quality-of-life measures were
compared for patients undergoing coronary angiography in Texas, where
the utilization of the procedure is high (45 percent), and for similar patients
in New York, where utilization is low (30 percent). After adjusting for case
mix differences, the researchers found no health advantages associated
with greater utilization, suggesting that savings associated with reduced
utilization of the procedure in Texas could be achieved with no deleterious
clinical consequences [7].
One estimate suggests that, in aggregate, only 27 percent of the weighted
variation in Medicare spending across regions can be explained by popula-
tion illness levels [6]. If spending levels in all regions were made to match
those in the lowest decile (age-, sex-, and race-adjusted), then Medicare
could see savings of up to $40 billion in 1996 dollars [8].
ii. Inappropriate use The second body of research that addresses waste
in the system attempts to directly measure how frequently certain medi-
cal services are delivered for medically inappropriate indications. Results
from this literature often demonstrate high levels of inappropriate use. For
example, a 1993 study of members of seven managed care organizations
found that about 16 percent of hysterectomies performed were judged to
have been clinically inappropriate, and 25 percent of the patients under-
went hysterectomy for uncertain indications [9]. A more recent study (in
2000) on hysterectomies found more dramatic results. Among hysterec-
tomies performed in a capitated medical group in Southern California,
70 percent of cases were judged to have been inappropriate, according to
RAND appropriateness criteria. Of the 497 women studied, 71 had hys-
terectomies for conditions covered by three recent ACOG criteria sets. The
recommendation for hysterectomy was judged inappropriate for 53 percent
of that subset by the RAND criteria and for 76 percent according to the
ACOG criteria [10].
In other cases, the rates of inappropriate use are relatively low, but
there is a wide range of situations in which appropriateness is uncertain,
which demonstrates the need for a stronger evidence base. For example, in
one study, 4 percent of coronary angiographies performed at 15 hospitals
in New York State were rated inappropriate; another 20 percent were rated
uncertain. The rate of inappropriate use varied from 0 percent to 9 percent
among hospitals, but the difference was not significant [11]. In another
study, 4 percent of percutaneous transluminal coronary angioplasty (PTCA)
performed at 15 hospitals in New York State were rated inappropriate;
another 38 percent were rated uncertain. The inappropriate rate varied
from 1 percent to 9 percent by hospital, the uncertain rate from 26 percent
to 50 percent [12].
Trends toward inappropriate and uncertain use appear in other clini-
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29
APPENDIX A
cal areas as well. Reviewing cases of new-onset chest pain not due to
myocardial infarction at one of five Los Angeles-area hospital emergency
departments revealed that 7 percent of those who received some form of
diagnostic cardiac testing had tests that were judged to be inappropriate. A
literature review on cases of metastatic renal cell cancer (MRCC) rated 46.9
percent of treatments as inappropriate and 25.8 percent as uncertain [13]. A
review of Medicare patients in three geographic areas revealed that 32 per-
cent of the sample had carotid endarterectomy for inappropriate reasons,
and 32 percent for uncertain reasons [14]. Seventeen percent of diagnostic
upper gastrointestinal endoscopy procedures for Medicare patients were
performed for inappropriate indications, and 11 percent were performed
for uncertain indications [15]. In cases of hospital use, 23 percent of admis-
sions were judged to be inappropriate and an additional 17 percent could
have been avoided by the use of ambulatory surgery [16].
These studies often examine a specific intervention (e.g., upper gastro-
intestinal endoscopy or percutaneous coronary angioplasty) and evaluate
the usefulness in a number of clinical indications. Most of the appropriate-
ness research focuses on high unit cost services. However, significant expen-
ditures associated with overuse may accrue from inappropriate utilization
of low unit cost services if they are used in sufficient volume (e.g., routine
blood testing, imaging procedures). Moreover, many of the studies cited
above are based on data from the 1980s. The more recent small area varia-
tions literature suggests that substantial inappropriateness likely still exists,
but much more work is needed in the area if we are to better understand,
and address, the inefficiencies in the system.
These findings of substantial variation in practice patterns and often
large rates of inappropriate use highlight the fact that the merit of a specific
medical intervention depends on the precise reason for use. Thus, in most
situations, detailed patient-specific information is required before reporting
whether the use of a drug, test, or device is worthwhile.
It is important to recognize that one cannot say that a particular
medical service is always appropriate or always inappropriate. Consider
an example in the area of diagnostic imaging: radionuclide cardiovascular
imaging (RNI). This is but one type of diagnostic imaging, but understand-
ing the appropriateness of imaging as a whole is crucially important. Diag-
nostic imaging services reimbursed under Medicare’s physician fee schedule
have grown more rapidly than any other type of physician service. Between
2000 and 2005, spending doubled from $6.6 billion to $13.7 billion [17].
In 2005 the American College of Cardiology Foundation convened a tech-
nical panel to assess the appropriateness of RNI for 52 indications [18].
Of the 52 indications, 13 were deemed inappropriate, 27 appropriate, and
for 12 the appropriateness was uncertain. Moreover, there was not even
consensus on all of the indications for which RNI was deemed appropriate.
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0 LEARNING WHAT WORKS
For example, for 6 of the 27 indications deemed appropriate, there was
strong disagreement among the panelists about that designation. Much
more research is needed to reduce the level of clinical uncertainty and move
the system toward efficient practice patterns.
However, CER will not be sufficient to eliminate overuse. Even when
identified, system factors and the complexities of care limit the ability of
the system to eliminate the waste. Research on these system factors, includ-
ing patient- and system-oriented interventions such as benefit design and
clinician/hospital reimbursement, will be needed to complement CER and
to allow development of the systems needed to realize the potential offered
by CER.
b. Underuse Paradoxically, while overuse in the healthcare system is com-
mon, underuse of medical services rigorously determined to provide sub-
stantial clinical benefit is also widespread. While the small area variation
discussion commonly focuses on overuse, similar aggregate-level outcomes
in high-expenditure areas and low-expenditure areas imply that some of the
small area variation may be due to underuse. For example, among patients
with heart attacks who were considered “ideal candidates” for beta-block-
ers, those who actually received the needed drug ranged from 5 percent to
92 percent of patients among the 306 Dartmouth Atlas Hospital Referral
Regions (HRRs) [6].
A substantial portion of underuse reflects the failure of individuals
or their physicians to use preventive services or to manage their chronic
illnesses as the scientific evidence would recommend. CER is needed to
improve our ability to identify when variation represents underuse and
when it represents overuse so that the system can respond appropriately.
However, as with overuse, CER will not be sufficient to eliminate underuse.
While the clinician-patient relationship plays a critical role in this shortcom-
ing, systemic effects such as access to care, benefit design, and ability to pay
are also likely contributors, and more research examining these factors will
be needed to improve the ability of the system to integrate CER findings
into practice.
2. Effects of Inefficiency on Key Stakeholders
Inefficiency in the healthcare system, particularly that which leads to
unnecessary expenditures, affects all stakeholders. Both overuse and unde-
ruse reduce the value of the resources devoted to the healthcare system.
The enormous incremental costs associated with this inefficiency are borne
throughout the system.
a. Individuals Individuals, whether they use the system or not, pay for these
inefficiencies in several ways and are unmistakably worse off. First, in some
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APPENDIX A
cases, individuals pay out of pocket for services (e.g., total body imaging
scans) that provide little value in terms of clinical outcomes. Second, the
financial costs associated with waste are reflected in higher healthcare
premiums. These are paid by workers either directly or, because higher
healthcare costs lead employers to pay lower wages, indirectly [19]. Third,
higher costs for public programs are financed by taxpayers. The costs of
the largest public program, Medicare, rose 8.9 percent to $342.0 billion
between 2004 and 2005 [20]. Furthermore, projections suggest that Medi-
care will grow at an annual rate of over 9 percent between 2005 and 2015
[21]. The growth of Medicare spending will represent a serious burden for
taxpayers and a significant challenge for policy makers. It is well established
that the tradeoff between access to medical care and how to pay for it is a
complex and extremely political issue.
Fourth, high healthcare costs are also associated with declining rates
of health insurance coverage [22]. To the extent that greater waste leads to
fewer covered individuals, those that are un- and under-insured must bear
greater financial risk and suffer the consequences of diminished access to
valuable care in the event that such care is needed.
Finally, inefficiency generates additional adverse consequences for
patients already engaged in the system. Specifically, the over-consumption
of care often entails clinical risk as well as financial costs. Over the past
decade, the “patient safety” movement has brought to light the extent of
the clinical and economic ramifications of avoidable medical errors. For
example, hospital-acquired infections are estimated to be responsible for
between $3.5 billion and $5.7 billion in excess healthcare costs each year
[23, 24]. Under-utilization also generates suboptimal clinical outcomes as
patients forego utilization of important services.
b. Employers The clinical and financial effects of inefficient care delivery
on other stakeholders are more complex. To the extent that employers bear
a large fraction of the costs associated with inefficiency, they are adversely
affected. As mentioned above, standard economic models supported by
empirical evidence suggest that, over time, employers shift the costs of
higher healthcare spending to workers in the form of lower wages. How-
ever, in the short run, employers (or the shareholders) may bear some of the
costs of inefficiency. Moreover, the ability to shift cost to workers is limited
for retiree expenses, suggesting that shareholders will bear the costs of inef-
ficiency for this population of workers. Employers may also bear some of
the administrative costs associated with managing healthcare benefits in an
environment of rising costs and considerable inefficiency.
c. Health insurers The fiscal implications of inefficiency for insurers are also
complicated. To the extent that cost increases can be anticipated, they may
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2 LEARNING WHAT WORKS
be included in premiums. However, as premiums escalate, the demand for
coverage may be dampened, suggesting that, on balance, insurers will find it
challenging to remain profitable in a rising cost environment over the long
run. Yet with the challenge comes opportunity. If insurers can develop ways
to address the problems of inefficiency in the healthcare system, substantial
profit opportunities may arise.
d. Providers of healthcare services Providers of healthcare services—espe-
cially those whose income is related to productivity, not quality of care—may
be one stakeholder group that benefits from inefficiency. Since one group’s
expense is another’s revenue, the payments for unnecessary interventions
are income for the providers of those services. Thus, while no physician or
hospital may intentionally, or even knowingly, provide unnecessary services,
they likely reap some financial gain from the services delivered, necessary
or not. The magnitude of this effect for particular providers depends on
the extent to which they deliver unnecessary care. Providers of necessary
care would not be adversely affected by reductions in the use of unneces-
sary services.
Reductions in the use of unnecessary care may offer indirect benefit to
providers in the long term. Specifically, higher costs lead to fewer people
with coverage. This may place a burden on providers who are increasingly
called on to provide uncompensated care. Providers may also benefit from
any reductions in inefficient care because they may find this type of cost
containment preferable to other approaches (such as fee reductions).
e. Manufacturers The impact of inefficiency (and efforts to reduce inef-
ficiency) on manufacturers is much the same as on the providers of those
services. Any reduction in utilization may be a reduction in revenue, but
the effects will target low-value or unnecessary services. Manufacturers that
have the potential to make important clinical advances can thrive in a low-
waste environment. Moreover, relative to other cost containment efforts
that may impact manufacturers, efforts to reduce unnecessary use of certain
medical products may be preferable.
. Uses of CER
Discussions about CER frequently focus on the use of these evalua-
tions to assist in development of practice guidelines or in coverage and
payment decisions. While CER could be used in these specific endeavors,
CER is needed for more far-reaching efforts to improve the efficiency of
the healthcare system. The critical nature of a comprehensive CER agenda
arises because of the lack of controlled assessments of available therapeutic
options and the substantial amount of patient heterogeneity that exists.
Waste generally arises when services that are valuable in some clinical situ-
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APPENDIX A
ations are applied to other indications. CER is an essential tool to determine
which intervention should be delivered to which person and in what clinical
circumstance.
By facilitating improved targeting of both the clinical intervention
and the specific patient population, the information provided by CER can
benefit key stakeholders, particularly patients and payers. Specifically, by
reducing the uncertainty about which treatment course is most appropri-
ate, CER can decrease the frequency that patients receive inappropriate
care, reducing costs and the potential for harmful medical errors. Similarly,
CER can facilitate efforts to develop coverage policy and design value-
based insurance packages, which should enhance the return on healthcare
expenditures made by payers—private or public [25]. Taking the perspec-
tive of the provider, the effects of CER on utilization will depend on both
the nature of the product and the incentives in place to use the service. If
coverage and reimbursement levels reflect the findings of CER (i.e., payment
based on clinical effects, not exclusively on production costs), providers
and manufactures of high-value services should find that the CER increases
their market share. However, the demand for low-value services will likely
(appropriately) decline. Given that the burden of proof necessary to demon-
strate value in the marketplace may intensify, so might the costs to perform
the requisite CER studies.
A particular concern for providers is that cost containment efforts
designed to eliminate the use of unnecessary services often inadvertently
lead to restrictions on the provision of needed care. In almost all of the
studies that report the appropriate indications for the use of a specified
intervention, the appropriateness is “uncertain” in a significant portion of
situations. Recall that there are few instances where the use of a specific
drug, diagnostic test, or procedure is always appropriate or inappropriate.
This underscores the need for a CER agenda that is able to measure health
and economic impact on a granular level that will ultimately target those
specific circumstances when certain interventions should and should not
be used.
While the evidence examines both under- and overuse of selected medi-
cal services, one cannot accurately predict the net effect of a more efficient
system on expenditures. This is related to the tradeoffs of how a better
evidence base drives the increased use of more valuable services (and likely
increases expenditures) and slows the utilization of low-value interventions
(and decreases spending).
Individual CER studies may not always suggest that the least expensive
course of action is the appropriate course of action—recall that “the most
expensive therapy is the one that doesn’t work.” However, medical culture
tends to be driven toward the adoption of new, expensive services, and cost
growth has widely been attributed to the development and diffusion of new
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LEARNING WHAT WORKS
medical services [25-27]. Therefore, on balance, we would expect that CER
would tend to dampen spending to a level below that which would other-
wise occur, because the ”adopt everything for everyone” mentality would
be replaced with an “adopt when appropriate” paradigm. For example, a
2006 study examined whether some stable, high-risk patients with persis-
tent total occlusion of the infarct-related coronary artery should undergo
percutaneous coronary intervention (PCI) in addition to receiving optimal
medical therapy [28]. Although use of this procedure in such cases was not
universal, the authors reported an inclination among physicians toward its
use. In this case, a randomized trial demonstrated that PCI did not improve
clinical outcomes, suggesting that resources could be saved by foregoing the
procedure. The trend would likely have been toward greater use, and the
CER-suggested lower use was medically appropriate.
Since the literature on diffusion of medical technology clearly shows a
preference among U.S. clinicians to use new interventions before definitive
clinical data are available, one can safely assume that the clinical data pro-
vided by a CER agenda will improve the quality of care. However, it should
not be assumed that the completion and implementation of a CER agenda
will save money in the short term. The short-term financial consequences
will depend on how CER is used and on whether the savings incurred to
lower rates of use of low-value interventions will offset the added expenses
of the increased use of higher-value services.
While enhancing the health of Americans is a noble goal, we acknowl-
edge that cost containment is an integral and inevitable part of the future
healthcare policy. Without a strong investment in CER, patients and provid-
ers are more likely to face unintended “across the board” restrictions on
the provision of valuable care because of the fiscal pressures that are being
imposed on public and private health care payers. Whether these are mani-
fested by fewer insured individuals or by the underinsurance of those with
some type of benefits, CER provides the knowledge base by which providers
of high-value services can advocate their continued use, using accepted sci-
entific approaches to make their case. The findings of research that directly
compares the pros and cons of available treatment options from numerous
perspectives will be important for clinical practice, regardless of the cost
containment/benefit reform approaches being considered. Cost containment
efforts that rely on an improved evidence base are likely preferable to cur-
rent efforts to drive all practice toward those of the lowest cost. Findings
from CER should be used to better target, not to limit, care.
The exact mechanisms by which CER will lead to enhanced efficiency
will vary based on the level of detail of the data generated by the studies
and the ability of the system to implement the findings in everyday practice.
On the quality improvement side, similar challenges have been identified
in studies examining the suboptimal uptake of evidence-based practice
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APPENDIX A
guidelines. From the financial perspective, cost-sharing approaches aim
to control spending by making patients pay more at the point of service.
Most efforts to raise patient out-of-pocket costs have resulted in higher
costs across all services (with the possible exception of some preventive
health services). It has been demonstrated that financial disincentives are
often placed at the patient level, making adherence with evidence-based
care difficult. Yet when faced with higher costs, patients often make poor
clinical decisions, which in fact could, in some cases, lead to greater overall
costs. Thus, the alignment of clinical and financial incentives is a necessary
component to ensure the attainment of an efficient delivery system. The
status quo has been unable to align quality improvement and cost contain-
ment initiatives. In fact, in some instances they actually compete with one
another, contributing directly to ineffiency [29].
Such an alignment of incentives is possible in the setting of improved
clinical evidence—driven by CER—and health benefit reform. Value-based
insurance design (VBID) represents a “clinically sensitive, fiscally respon-
sible” approach that advocates keeping patient out-of-pocket payments
low on high-value services and raising them on services of no or marginal
clinical value. Similar processes can be developed for clinician payment
(e.g., payment based on quality of care delivered, not productivity). Imple-
mentation of such a scheme, in any form, would require greater CER since
the relative value of services would be based directly on the findings. The
advantages of such an alignment of clinical and economic incentives are
obvious when compared to the current approach of untargeted “across the
board” cost-sharing schemes, where the rates of both non-essential and
essential services are negatively affected by higher out-of-pocket rates. By
using incentives to encourage the use of high-value services and discourag-
ing low-value ones, VBID has the potential to achieve marked increases in
the efficiency of the healthcare system.
Supply-side-oriented healthcare reform approaches could also benefit
from added investment in and coordination of CER. Certainly, coverage
policy and clinical guidelines require such knowledge. But other initiatives,
such as provider education, disease management, or pay-for-performance
programs, all require an understanding of which services provide value in
which settings and how quality and cost metrics can be designed in a clini-
cally meaningful way.
4. Conclusions
Healthcare cost growth has placed a growing strain on our healthcare
financing system. Although there is no consensus about how we can address
the healthcare cost issue, most stakeholders would probably agree that the
resources devoted to health care must be allocated more efficiently. This will
entail being able to identify situations when more resources are necessary to
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LEARNING WHAT WORKS
overcome the problem of underuse of highly valued services that improve
health, as well as when money is being wasted on interventions that do not
improve health, or worse, actually produce adverse consequences.
Regardless of the reform approach considered—market-based health
savings accounts or a system administered through a single source—
enhanced efficiency will require more detailed knowledge about the relative
effectiveness of different interventions in specific clinical indications. All
vested stakeholders should encourage investment in an infrastructure that
prioritizes and undertakes investigations that yield practical information
on which services to provide to which patients and when. Our healthcare
system is too complex and too large to be guided without an appropriate
knowledge base. Moreover, because innovation in the healthcare sector is
substantial, investment in an infrastructure that would allow the assessment
of the clinical and economic impact of new and existing diagnostic and
treatment modalities is essential.
Creating this infrastructure will require a substantial investment. For
those who consider the upfront investment necessary to create such an
infrastructure to be unaffordable, it is imperative to contemplate the costs
of the status quo that propagate tremendous inefficiency.
REFERENCES
1. Schoen, C., et al. 2006. US health system performance: A national scorecard. Health
Affairs Web Exclusive, W457-475.
2. Kaufman, J. S., et al. 1998, Subcutaneous compared with intravenous epoetin in pa-
tients receiving hemodialysis. Department of Veterans Affairs Cooperative Study
Group on Erythropoietin in Hemodialysis Patients. New England Journal of Medicine
339(9):578-583.
3. Fisher, E. S., and J. E. Wennberg. 2003. Health care quality, geographic variations, and the
challenge of supply-sensitive care. Perspectives in Biology and Medicine 46(1):69-79.
4. Fisher, E. S., et al. 2003. The implications of regional variations in Medicare spend-
4. spend-
ing. Part 1: The content, quality, and accessibility of care. Annals of Internal Medicine
138(4):273-287.
5. Fisher, E. S., et al. 2003. The implications of regional variations in Medicare spend-
5. spend-
ing. Part 2: health outcomes and satisfaction with care. Annals of Internal Medicine
138(4):288-298.
6. Wennberg, J. E., E. S. Fisher, and J. S. Skinner. 2002. Geography and the debate over
6.
Medicare reform. Health Affairs Suppl Web Exclusives:W96-114.
7. Guadagnoli, E., et al. 1995 Variation in the use of cardiac procedures after acute myo-
cardial infarction. New England Journal of Medicine 333(9):573-578.
8. Wennberg, J. E., and M. M. Cooper, eds. 1999. The Dartmouth Atlas of Health Care.
Chicago: American Hospital Association.
9. Bernstein, S. J., et al. 1993. The appropriateness of hysterectomy. A comparison of care
in seven health plans. Health Maintenance Organization Quality of Care Consortium.
JAMA 269(18):2398-2402.
10. Broder, M. S., et al. 2000. The appropriateness of recommendations for hysterectomy.
Obstetrics and Gynecology 95(2):199-205.
OCR for page 437
APPENDIX A
11. Bernstein, S. J., et al. 1993. The appropriateness of use of coronary angiography in New
York State. JAMA 269(6):766-769.
12. Hilborne, L. H., et al. 1993. The appropriateness of use of percutaneous transluminal
coronary angioplasty in New York State. JAMA 269(6):761-765.
13. Halbert, R. J., et al. 2006. Treatment of patients with metastatic renal cell cancer: A
RAND Appropriateness Panel. Cancer 107(10):2375-2383.
14. Winslow, C. M., et al. 1988. The appropriateness of carotid endarterectomy. New Eng-
land Journal of Medicine 318(12):721-727.
15. Kahn, K. L., et al. 1988. The use and misuse of upper gastrointestinal endoscopy. Annals
of Internal Medicine 109(8):664-670.
16. Siu, A. L., et al. 1986. Inappropriate use of hospitals in a randomized trial of health
insurance plans. New England Journal of Medicine 315(20):1259-1266.
17. Kuhn, H. 2006. Testimony on Payment for Imaging Services under the Medicare Physi-
cian Fee Schedule. July 18. Online. Available at http://www.hhs.gov/asl/testify/t060718.
html. Accessed January 22, 2007.
18. Brindis, R. G., et al. 2005. ACCF/ASNC appropriateness criteria for single-photon emis-
emis-
sion computed tomography myocardial perfusion imaging (SPECT MPI): A report of the
American College of Cardiology Foundation Quality Strategic Directions Committee
Appropriateness Criteria Working Group and the American Society of Nuclear Cardiol-
ogy endorsed by the American Heart Association. Journal of the American College of
Cardiology 46(8):1587-1605.
19. Gruber, J. 1994. The incidence of mandated maternity benefits. American Economic
Review 84(3):622-641.
20. CMS Office of Public Affairs. 2007. Press Release: CMS Releases U.S. Health Spending
Estimates Through 200. January 9. Online. Available at http://www.cms.hhs.gov/apps/
media/press/release.asp?Counter=2069&intNumPerPage=10&checkDate=&checkKey=
&srchType=&numDays=3500&srchOpt=0&srchData=&keywordType=All&chkNews
Type=1%2C+2%2C+3%2C+4%2C+5&intPage=&showAll=&pYear=&year=&desc=&
cboOrder=date. Accessed January 22, 2007.
21. Borger, C., et al. 2006. Health spending projections through 2015: Changes on the ho-
rizon. Health Affairs 25(2):w61-73.
22. Chernew, M., D. M. Cutler, and P. S. Keenan. 2005. Increasing health insurance costs
and the decline in insurance coverage. Health Services Research 40(4):1021-1039.
23. Burke, J. P. 2003. Infection control—A problem for patient safety. New England Journal
of Medicine 348(7):651-656.
24. Hollenbeak, C. S. 006. Factors associated with risk of surgical wound infections. Ameri-
can Journal of Medical Quality 21(6):29S-34S.
25. Chernew, M. E., et al. 1998. Managed care, medical technology, and health care cost
growth: A review of the evidence. Medical Care Research and Review 55(3):259-288;
discussion 89-97.
26. Cutler, D. M. 1995. Technology, Health Costs, and the NIH. Cambridge, MA: Harvard
University and the National Bureau of Economic Research.
27. Newhouse, J. P. 1992. Medical care costs: How much welfare loss? Journal of Economic
Perspectives 6(3):3-21.
28. Hochman, J. S., et al. 2006. Coronary intervention for persistent occlusion after myocar-
myocar-
dial infarction. New England Journal of Medicine 355(23):2395-2407.
29. Chernew, M. E., A. B. Rosen, and A. M. Fendrick. 2006. Rising out-of-pocket costs in
disease management programs. American Journal of Managed Care 12(3):150-154.
OCR for page 438