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Summary
Health care in America presents a fundamental paradox. The past 50
years have seen an explosion in biomedical knowledge, dramatic innova-
tion in therapies and surgical procedures, and management of conditions
that previously were fatal, with ever more exciting clinical capabilities on
the horizon. Yet, American health care is falling short on basic dimensions
of quality, outcomes, costs, and equity. Available knowledge is too rarely
applied to improve the care experience, and information generated by the
care experience is too rarely gathered to improve the knowledge available.
The traditional systems for transmitting new knowledge—the ways clini-
cians are educated, deployed, rewarded, and updated—can no longer keep
pace with scientific advances. If unaddressed, the current shortfalls in the
performance of the nation’s health care system will deepen on both qual-
ity and cost dimensions, challenging the well-being of Americans now and
potentially far into the future.
Consider the impact on American services if other industries routinely
operated in the same manner as many aspects of health care:
• If banking were like health care, automated teller machine (ATM)
transactions would take not seconds but perhaps days or longer as
a result of unavailable or misplaced records.
• If home building were like health care, carpenters, electricians, and
plumbers each would work with different blueprints, with very
little coordination.
5
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6 BEST CARE AT LOWER COST
• If shopping were like health care, product prices would not be
posted, and the price charged would vary widely within the same
store, depending on the source of payment.
• If automobile manufacturing were like health care, warranties for
cars that require manufacturers to pay for defects would not ex-
ist. As a result, few factories would seek to monitor and improve
production line performance and product quality.
• If airline travel were like health care, each pilot would be free to
design his or her own preflight safety check, or not to perform one
at all.
The point is not that health care can or should function in precisely the
same way as all other sectors of people’s lives—each is very different from
the others, and every industry has room for improvement. Yet, if some of
the transferable best practices from banking, construction, retailing, auto-
mobile manufacturing, flight safety, public utilities, and personal services
were adopted as standard best practices in health care, the nation could see
patient care in which
• r
ecords would be immediately updated and available for use by
patients;
• care delivered would be proven reliable at the core and tailored at
the margins;
• patient and family needs and preferences would be a central part
of the decision process;
• all team members would be fully informed in real time about each
other’s activities;
• prices and total costs would be fully transparent to all participants;
• payment incentives were structured to reward outcomes and value,
not volume;
• errors would be promptly identified and corrected; and
• results would be routinely captured and used for continuous
improvement.
Unfortunately, these are not features that would describe much of
health care in America today. Health care can lag behind many other sectors
with respect to its ability to meet patients’ specific needs, to offer choice, to
adapt, to become more affordable, to improve—in short, to learn. Ameri-
cans should be served by a health care system that consistently delivers reli-
able performance and constantly improves, systematically and seamlessly,
with each care experience and transition.
In the face of these realities, the Institute of Medicine (IOM) convened
the Committee on the Learning Health Care System in America to explore
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SUMMARY 7
the most fundamental challenges to health care today and to propose ac-
tions that can be taken to achieve a health care system characterized by
continuous learning and improvement. This study builds on earlier IOM
studies on various aspects of the health care system, from To Err Is Human:
Building a Safer Health System (1999), on patient safety; to Crossing the
Quality Chasm: A New Health System for the 21st Century (2001a), on
health care quality; to Unequal Treatment: Confronting Racial and Ethnic
Disparities in Health Care (2003), on health care disparities. The study
process was also facilitated and informed by the published summaries of
workshops conducted under the auspices of the IOM Roundtable on Value
& Science-Driven Health Care. Over the past 6 years, 11 workshop sum-
maries have been produced, exploring various aspects of the challenges and
opportunities in health care today, with a particular focus on the founda-
tional elements of a learning health system.
Meeting the challenges discussed at those workshops has taken on great
urgency as a result of two overarching imperatives:
• to manage the health care system’s ever-increasing complexity, and
• to curb ever-escalating costs.
The convergence of these imperatives makes the status quo untenable.
At the same time, however, opportunities exist to address these problems—
opportunities that did not exist even a decade ago:
• vast computational power that is affordable and widely available;
• connectivity that allows information to be accessed in real time
virtually anywhere;
• human and organizational capabilities that improve the reliability
and efficiency of care processes; and
• the recognition that effective care must be delivered by collabora-
tions between teams of clinicians and patients, each playing a vital
role in the care process.
The committee undertook its work to consider how these opportuni-
ties for best care at lower cost can be leveraged to meet the challenges
outlined above. The committee, whose work was supported by the Blue
Shield of California Foundation, the Charina Endowment Fund, and the
Robert Wood Johnson Foundation, was charged with (1) identifying how
the effectiveness and efficiency of the current health care system can be
transformed through tools and incentives for continuous assessment and
improvement and (2) developing recommendations for actions that can be
taken to that end. This report explores the imperatives for change, describes
the emerging tools that make transformation possible, sets forth a vision
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8 BEST CARE AT LOWER COST
for a continuously learning health care system, and delineates a path for
achieving this vision. Detailed findings are presented throughout the report,
together with the conclusions and recommendations they support, which
are also highlighted in this summary.
The title of the report underscores that care that is based on the best
available evidence, takes appropriate account of individual preferences, and
is delivered reliably and efficiently—best care—is possible today. When such
care is routinely implemented, moreover, it is generally less expensive than
the less effective, less efficient care that is now too commonly provided.
Moreover, the transition to best care envisioned in this report is urgently
needed given the budgetary, economic, and health pressures facing the na-
tion’s health care system.
THE IMPERATIVES
Decades of rapid innovation and technological improvement have cre-
ated an extraordinarily complex health care system. Clinicians and health
care staff work tirelessly to care for their patients in an increasingly com-
plex, inefficient, and stressful environment. Certain breakthrough innova-
tions have benefited millions of patients, but the aggregate impact of the
flood of new interventions has introduced challenges for both clinicians and
patients in treating and managing health conditions. In addition to the chal-
lenge of complexity, and in part because of it, health care often falls short
of its potential in the quality of care delivered and the patient outcomes
achieved. These shortfalls are occurring even as costs are rising to unsus-
tainable levels. Additionally, new opportunities emerging from technology,
industry, and policy can be leveraged to help mold the system into one
characterized by continuous learning and improvement. In this context, the
committee identified three imperatives for achieving a continuously learning
health care system that provides the best care at lower cost: (1) managing
rapidly increasing complexity; (2) achieving greater value in health care;
and (3) capturing opportunities from technology, industry, and policy.
Managing Rapidly Increasing Complexity
The complexity of health care has increased in multiple dimensions—in
the ever-increasing treatment, diagnostic, and care management options
available; in the rapidly rising levels of biomedical and clinical evidence;
and in administrative complexities, from complicated workflows to frag-
mented financing. The complexity due to ever-increasing treatment options
can be illustrated by the evolution of care for two common conditions—
heart disease and cancer. During much of the twentieth century, heart
attacks commonly were treated with weeks of bed rest. Today, advanced
diagnostics allow for customized treatments for patients; interventions
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SUMMARY 9
such as percutaneous coronary interventions and coronary artery bypass
grafts can reopen blocked vessels and restore blood flow to the heart; and
pharmaceutical therapies, such as thrombolytics and beta-blockers, improve
survival and reduce the chances of subsequent heart attacks (Certo, 1985;
Nabel and Braunwald, 2012). Similarly, five decades ago, breast cancer
was detected from a physical exam, and mastectomy was the recommended
treatment. Today, multiple imaging technologies exist for the detection and
diagnosis of the disease, and once diagnosed, the cancer can be further clas-
sified and treated according to genetic characteristics and hormone receptor
status (Harrison, 1962; IOM, 2001b; Kasper and Harrison, 2005).
As a result of improved scientific understanding, new treatments and
interventions, and new diagnostic technologies, the U.S. health care system
now is characterized by more to do, more to know, and more to manage
than at any time in history. As one quantification of this increase, the vol-
ume of the biomedical and clinical knowledge base has rapidly expanded,
with research publications having risen from more than 200,000 per year
in 1970 to more than 750,000 in 2010 (see Figure S-1). The result is a
800,000
Medical Journal Articles
600,000
400,000
200,000
0
1970 1980 1990 2000 2010
Year
FIGURE S-1 Number of journal articles published on health care topics per year
from 1970 to 2010. Publications have increased steadily over 40 years, with the rate
of increase becoming more pronounced Figure approximately in 2000.
starting S-1 and 2-5
SOURCE: Data obtained from online searches at PubMed: http://www.ncbi.nlm.
nih.gov/pubmed/.
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10 BEST CARE AT LOWER COST
paradox: advances in science and technology have improved the ability of
the health care system to treat diseases, yet the sheer volume of new dis-
coveries stresses the capabilities of the system to effectively generate and
manage knowledge and apply it to regular care. These advances have oc-
curred at the same time as, and sometimes have contributed to, challenges
in health care quality and value.
Conclusion: Diagnostic and treatment options are expanding and
changing at an accelerating rate, placing new stresses on clinicians
and patients, as well as potentially impacting the effectiveness and
efficiency of care delivery.
Beyond the increasing stores of biomedical and clinical knowledge,
changes in disease prevalence and patient demographics have altered the
landscape for care delivery. The prevalence of chronic conditions, for ex-
ample, has increased over time. In 2000, 125 million people suffered from
such conditions; by 2020, that number is projected to grow to an estimated
157 million (Anderson, 2010). The role of chronic diseases has changed as
the demographics of the population have shifted. In general, the population
has gotten older; in the past decade, the portion of the population over age
65 has increased at 1.5 times the rate of the rest of the population (Howden
and Meyer, 2011). Almost half of those over 65 receive treatment for at least
one chronic disease, and more than 20 percent receive treatment for mul-
tiple chronic diseases (Schneider et al., 2009); fully 75 million people in the
United States have multiple chronic conditions (Parekh and Barton, 2010).
Managing these multiple conditions requires a holistic approach, be-
cause the use of various clinical practice guidelines developed for single
diseases may have adverse effects (Boyd et al., 2005a; Parekh and Barton,
2010; Tinetti et al., 2004). For example, existing clinical practice guidelines
would suggest that a hypothetical 79-year-old woman with osteo orosis, p
osteoarthritis, type 2 diabetes, hypertension, and chronic obstructive pul-
monary disease should take as many as 19 doses of medication per day. Such
guidelines might also make conflicting recommendations for the woman’s
care. If she had peripheral neuropathy, guidelines for osteoporosis would
recommend that she perform weight-bearing exercise, while guidelines
for diabetes would recommend that she avoid such exercise (Boyd et al.,
2005a). These situations create uncertainty for clinicians and patients as to
the best course of action to pursue as they attempt to manage the treatments
for multiple conditions.
Conclusion: Chronic diseases and comorbid conditions are increas-
ing, exacerbating the clinical, logistical, decision-making, and eco-
nomic challenges faced by patients and clinicians.
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SUMMARY 11
Care delivery also has become increasingly demanding. It would take
an estimated 21 hours per day for individual primary care physicians to
provide all of the care recommended to meet their patients’ acute, preven-
tive, and chronic disease management needs (Yarnall et al., 2009). Clini-
cians in intensive care units, who care for the sickest patients in a hospital,
must manage in the range of 180 activities per patient per day—from
replacing intravenous fluids, to administering drugs, to monitoring pa-
tients’ vital signs (Donchin et al., 2003). In addition, rising administrative
burdens and inefficient workflows mean that hospital nurses spend only
about 30 percent of their time in direct patient care (Hendrich et al., 2008;
Hendrickson et al., 1990; Tucker and Spear, 2006). These pressures are
not limited to clinicians; patients often find the health care system uncoor-
dinated, opaque, and stressful to navigate. One study found that for 1 of
every 14 tests, either the patient was not informed of a clinically significant
abnormal test result, or the clinician failed to record reporting the result to
the patient (Casalino et al., 2009).
With specialization, moreover, clinicians must coordinate with multiple
other providers; for their health care, Medicare patients now see an aver-
age of seven physicians, including five specialists, split among four differ-
ent practices (Pham et al., 2007). One study found that in a single year, a
typical primary care physician coordinated with an average of 229 other
physicians in 117 different practices just for Medicare patients (Pham et al.,
2009). The involvement of multiple providers tends to blur accountability.
One survey found that 75 percent of hospital patients were unable to iden-
tify the clinician in charge of their care (Arora et al., 2009).
Conclusion: Care delivery has become increasingly fragmented,
leading to coordination and communication challenges for patients
and clinicians.
Achieving Greater Value in Health Care
In addition to, and sometimes as a result of, the challenge of complex-
ity, health care quality and outcomes often fall short of their potential. A
decade after the IOM (1999) estimated that 44,000 to 98,000 patients died
each year from preventable medical errors, recent studies have reported
that as many as one-third of hospitalized patients may experience harm
or an adverse event, often from preventable errors (Classen et al., 2011;
Landrigan et al., 2010; Levinson, 2010). While infections and complica-
tions once were viewed as routine consequences of medical care, it is now
recognized that strategies and evidence-based interventions exist that can
significantly reduce the incidence and severity of such events.
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12 BEST CARE AT LOWER COST
Similarly, medical care often is guided insufficiently by evidence, with
Americans receiving only about half of the preventive, acute, and chronic
care recommended by current research and evidence-based guidelines
(McGlynn et al., 2003). Sometimes this occurs because available evidence
is not applied to clinical care, while in other cases evidence is not available.
As a result of all of these factors, the nature and quality of health care
vary considerably among states, with serious health and economic con-
sequences. If all states could provide care of the quality delivered by the
highest-performing state, an estimated 75,000 fewer deaths would have
occurred across the country in 2005 (McCarthy et al., 2009; Schoenbaum
et al., 2011).
Conclusion: Health care safety, quality, and outcomes for Ameri-
cans fall substantially short of their potential and vary significantly
for different populations of Americans.
These deficiencies in care quality have occurred even as expenses have
risen significantly. Health care costs1 have increased at a greater rate than
the economy as a whole for 31 of the past 40 years, and now constitute
18 percent of the nation’s gross domestic product (CMS, 2012; Keehan et
al., 2011). The growth in health care costs has contributed to stagnation in
real income for American families. Although income has increased by 30
percent over the past decade, these gains have effectively been eliminated by
a 76 percent increase in health care costs (Auerbach and Kellermann, 2011).
These high costs have strained families’ budgets and put health insurance
coverage out of reach for many, contributing to the 50 million Americans
without coverage (DeNavas-Walt et al., 2011).
In addition to unsustainable cost growth, there is evidence that a sub-
stantial proportion of health care expenditures is wasted, leading to little
improvement in health or in the quality of care. Estimates vary on waste and
excess health care costs, but they are large. The IOM workshop summary
The Healthcare Imperative: Lowering Costs and Improving Outcomes con-
tains estimates of excess costs in six domains: unnecessary services, services
inefficiently delivered, prices that are too high, excess administrative costs,
missed prevention opportunities, and medical fraud (IOM, 2010). These
estimates, presented by workshop speakers with respect to their areas of
expertise and based on assumptions from limited observations, suggest the
1 n this report, price refers to the amount charged for a given health care service or product.
I
It is important to note that there are frequently multiple prices for the same service or product,
depending on the patient’s insurance status and payer, as well as other factors. Cost is the total
sum of money spent at a given level (episodes, patients, organizations, state, national), or price
multiplied by the volume of services or products used.
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SUMMARY 13
substantial contribution of each domain to excessive health care costs (see
Table S-1).
Although these estimates have unknown overlap, the sum of the indi-
vidual estimates—$765 billion—suggests the significant scale of waste in
the system. Two other independent and differing analytic approaches—
considering regional variation in costs and comparing costs across coun-
tries—produce similar estimates, with total excess costs approaching $750
billion in 2009 (Farrell et al., 2008; IOM, 2010; Wennberg et al., 2002).
TABLE S-1 Estimated Sources of Excess Costs in Health Care (2009)
Estimate of
Category Sources Excess Costs
Unnecessary Services • Overuse—beyond evidence- $210 billion
established levels
• Discretionary use beyond benchmarks
• Unnecessary choice of higher-cost
services
Inefficiently Delivered • Mistakes—errors, preventable $130 billion
Services complications
• Care fragmentation
• Unnecessary use of higher-cost
providers
• Operational inefficiencies at care
delivery sites
Excess Administrative • Insurance paperwork costs beyond $190 billion
Costs benchmarks
• Insurers’ administrative inefficiencies
• Inefficiencies due to care
documentation requirements
Prices That Are Too High • Service prices beyond competitive $105 billion
benchmarks
• Product prices beyond competitive
benchmarks
Missed Prevention • Primary prevention $55 billion
Opportunities • Secondary prevention
• Tertiary prevention
Fraud • All sources—payers, clinicians, $75 billion
patients
SOURCE: Adapted with permission from IOM, 2010.
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14 BEST CARE AT LOWER COST
While there are methodological issues with each method for estimating
excess costs, the consistently large figures produced by each signal the po-
tential for reducing health care costs while improving quality and health
outcomes.
At this level, unnecessary health care costs and waste exceed the 2009
budget for the Department of Defense by more than $100 billion (OMB,
2010). Health care waste also amounts to more than 1.5 times the nation’s
total infrastructure investment in 2004, including roads, railroads, aviation,
drinking water, telecommunications, and other structures.2 To put these es-
timates in the context of health care expenditures, the estimated redirected
funds could provide health insurance coverage for more than 150 million
workers (including both employer and employee contributions), which
exceeds the 2009 civilian labor force.3 And the total projected amounts
could pay the salaries of all of the nation’s first response personnel, includ-
ing firefighters, police officers, and emergency medical technicians, for more
than 12 years.4
Conclusion: The growth rate of health care expenditures is unsus-
tainable, with waste that diverts major resources from necessary
care and other priorities at every level—individual, family, com-
munity, state, and national.
In sum, as illustrated in Figure S-2, each stage in the processes that
shape the health care received—knowledge development, translation into
medical evidence, application of evidence-based care—has prominent short-
comings and inefficiencies that contribute to a large reservoir of missed
opportunities, waste, and harm. The threats to the health and economic
security of Americans are clear, present, and compelling.
2
The Department of Defense budget was calculated from the fiscal year 2009 outlays listed
in the Fiscal Year 2011 U.S. Government Budget (OMB, 2010); the comparison of health care
waste with the national infrastructure investment was drawn from a Congressional Budget
Office analysis, with inflation adjusted according to the Consumer Price Index (CPI) (Congres-
sional Budget Office, 2008).
3
The average premiums for a single worker were calculated using the Kaiser Family Founda-
tion’s 2009 Employer Health Benefits survey, with the size of the civilian labor force drawn
from Bureau of Labor Statistics estimates for 2009 (Kaiser Family Foundation and Health
Research & Educational Trust, 2009; U.S. Bureau of Labor Statistics, 2012).
4 he comparison with expenditures on first responders was calculated from the annual
T
salary data for firefighters, police officers, and emergency medical technicians provided in the
2009 National Compensation Survey, while the total number of individuals in those occupa-
tions was drawn from the 2009 Occupational Employment Statistics (U.S. Bureau of Labor
Statistics, 2010a,b).
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SUMMARY 15
Communities
Patients Clinicians
Science Evidence Care Patient
Experience
Insights Evidence Experience
poorly poorly poorly
managed used captured
Missed Opportunities, Waste, and Harm
FIGURE S-2 Schematic of the health care system today.
Capturing Opportunities from Technology, Industry, and Policy
Care
As noted earlier, new opportunities exist to address the challenges
Inc
re
outlined above. Just as the information revolution has transformed many
en
ltu
other fields, growing stores of data and computational abilities hold the
tiv
Cu
same promise for improving clinical research, clinical practice, and clinical
es
decision making. In the past three decades, for example, computer process-
ing speed has grown by 60 percent per Cliniciansaverage, while the capacity
Patients
year on
to share information over telecommunications networks has risen by an
average of 30 percent per year (Hilbert and López, 2011). These advances
in computing and connectivity Communities
have the potential to improve health care by
expanding the reach of knowledge, increasing access to clinical information
when and where needed, and assisting patients and providers in managing
Science Evidence
chronic diseases. Studies also have found that using such electronic systems
can improve safety—one study reported a 41 percent reduction in potential
adverse drug events following the implementation of a computerized pa-
tient management system (computerized physician order entry, or CPOE),
while another estimated that overall medication error rates dropped by 81
Leadership
percent (Bates et al., 1998, 1999; Potts et al., 2004). Projections are for
90 percent of office-based physicians to have access to fully operational
electronic health records by 2019, up from 34 percent in 2011 (Congres-
sional Budget Office, 2009; Hsiao et al., 2011). Because these capacities are
relatively early in their development in the health care arena, there is sub-
stantial room for progress as they are implemented in the field. However,
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34 BEST CARE AT LOWER COST
Strategies for progress toward this goal:
• Health care delivery organizations should utilize systems engineer-
ing tools and process improvement methods to eliminate inefficien-
cies, remove unnecessary burdens on clinicians and staff, enhance
patient experience, and improve patient health outcomes.
• The Centers for Medicare & Medicaid Services, the Agency for
Healthcare Research and Quality, the Patient-Centered Outcomes
Research Institute, quality improvement organizations, and process
improvement leaders should develop a learning consortium aimed
at accelerating training, technical assistance, and the collection
and validation of lessons learned about ways to transform the ef-
fectiveness and efficiency of care through continuous improvement
programs and initiatives.
Supportive Policy Environment
Recommendation 8: Financial Incentives
tructure payment to reward continuous learning and improvement in
S
the provision of best care at lower cost. Payers should structure pay-
ment models, contracting policies, and benefit designs to reward care
that is effective and efficient and continuously learns and improves.
Strategies for progress toward this goal:
• Public and private payers should reward continuous learning
and improvement through outcome- and value-oriented payment
models, contracting policies, and benefit designs. Payment models
should adequately incentivize and support high-quality team-based
care focused on the needs and goals of patients and families.
• Health care delivery organizations should reward continuous
learning and improvement through the use of internal practice
incentives.
• Health economists, health service researchers, professional spe-
cialty societies, and measure development organizations should
partner with public and private payers to develop and evaluate
metrics, payment models, contracting policies, and benefit designs
that reward high-value care that improves health outcomes.
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SUMMARY 35
Recommendation 9: Performance Transparency
ncrease transparency on health care system performance. Health care
I
delivery organizations, clinicians, and payers should increase the avail-
ability of information on the quality, prices and cost, and outcomes
of care to help inform care decisions and guide improvement efforts.
Strategies for progress toward this goal:
• Health care delivery organizations should collect and expand the
availability of information on the safety, quality, prices and cost,
and health outcomes of care.
• Professional specialty societies should encourage transparency on
the quality, value, and outcomes of the care provided by their
members.
• Public and private payers should promote transparency in quality,
value, and outcomes to aid plan members in their care decision
making.
• Consumer and patient organizations should disseminate this infor-
mation to facilitate discussion, informed decision making, and care
improvement.
Recommendation 10: Broad Leadership
xpand commitment to the goals of a continuously learning health care
E
system. Continuous learning and improvement should be a core and
constant priority for all participants in health care—patients, families,
clinicians, care leaders, and those involved in supporting their work.
Strategies for progress toward this goal:
• Health care delivery organizations should develop organizational
cultures that support and encourage continuous improvement, the
use of best practices, transparency, open communication, staff em-
powerment, coordination, teamwork, and mutual respect and align
rewards accordingly.
• Leaders of these organizations should define, disseminate, support,
and commit to a vision of continuous improvement; focus atten-
tion, training, and resources on continuous learning; and build an
operational model that incentivizes continuous improvement and
ensures its sustainability.
• Governing boards of health care delivery organizations should sup-
port and actively participate in fostering a culture of continuous
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36 BEST CARE AT LOWER COST
improvement, request continuous feedback on the progress being
made toward the adoption of such a culture, and align leadership
incentive structures accordingly.
• Clinical professional specialty societies, health professional edu-
cation programs, health professions specialty boards, licensing
boards, and accreditation organizations should incorporate basic
concepts and specialized applications of continuous learning and
improvement into health professions education; continuing educa-
tion; and licensing, certification, and accreditation requirements.
Given the interconnected nature of the problems to be solved, it will
be important to take the actions identified above in concert. To elevate the
quantity of evidence available to inform clinical decisions, for example, it
is necessary to increase the supply of evidence by expanding the clinical re-
search base; make the evidence easily accessible by embedding it in clinical
technological tools, such as clinical decision support; encourage use of the
evidence through appropriate payment, contracting, and regulatory poli-
cies and cultural factors; and assess progress toward the goal using reliable
metrics and appropriate transparency. The absence of any one of these fac-
tors will substantially limit overall improvement. To guide success, progress
on the recommendations in this report should be monitored continuously.
ACHIEVING THE VISION
Implementing the actions detailed above and achieving the vision of
continuous learning and improvement will depend on the exercise of broad
leadership by the complex network of decentralized and loosely associated
individuals and organizations that make up the health care system. Given
the complexity of the system and the interconnectedness of its different
actors and sectors, no one actor or sector alone can bring about the scope
and scale of transformative change necessary to develop a system that con-
tinuously learns and improves. Each stakeholder brings different strengths,
skills, needs, and expertise to the task of improving the system, faces unique
challenges, and is accountable for different aspects of the system’s success.
There is a distinct need for collaboration between and among stakeholders
to produce effective and sustainable change.
As the end users of all health care services, patients are central to the
success of any improvement initiative. Any large-scale change will require
the participation of patients as partners, with the system building trust on
every dimension. Patients can promote learning and improvement by engag-
ing in their own care; setting high expectations for their care in terms of
quality, value, and the use of scientific evidence and selecting clinicians, or-
ganizations, and plans that meet those expectations; sharing decision making
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SUMMARY 37
with their clinicians; and, with the help of their caregivers, directly applying
evidence to their self-care and self-management on an ongoing basis.
Partnering with patients are the health care professionals who deliver
care. Physicians, nurses, pharmacists, and other health professionals rep-
resent the front lines of health care delivery and the primary interface for
patients and consumers. Expanding the supply of clinical information, pro-
moting the use of evidence, and better involving patients in their care are
all contingent upon the engagement and teaming of health professionals.
By convening their constituent professionals and providing a forum for
action, professional societies have important roles in achieving the vision of
a learning health care system. Through guidelines, performance measures,
quality improvement initiatives, and data infrastructures for assessing per-
formance with respect to specific procedures or conditions, these societies
can take a leadership role in improving quality, safety, and efficiency.
Health care delivery organizations, because of their size and care ca-
pacities, have several levers by which they can steward progress toward a
continuously improving system, such as using new practice methods, setting
standards, and sharing resources and information with other care delivery
organizations. Furthermore, through investments in health information
technology, these organizations can build their capacity to perform near-
real-time research, speeding the generation of practical evidence and its
translation to the bedside.
Those who finance care also have opportunities to leverage their unique
position to improve the quality and efficiency of care. As organizations
that interact directly with patients, public and private payers can support
patients as they seek to maintain healthy behaviors and access quality
health care services, while their payment and contracting policies have a
strong influence on how clinicians practice. Similarly, employers can sup-
port efforts to improve quality and value by using their purchasing power
to drive improvement efforts through contracts with providers and insurers,
the design of benefit plans, and the provision of incentives and information
for employees.
Digital technology developers, health product innovators, and regula-
tors are additional stakeholders that need to be engaged in achieving the
vision of a learning health care system. Digital technology developers create
the products and infrastructure necessary to meet the growing demand for
capturing, storing, retrieving, and sharing information in virtually every
aspect of health care. Continuous improvement in diagnostic and treat-
ment options is contingent on a safe and innovative product development
enterprise. Health product innovators, by conducting clinical research and
devising new treatments and interventions, can develop novel products for
diagnosis and treatment. Essential partners in this arena are regulators,
including the Food and Drug Administration, who can work to develop
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38 BEST CARE AT LOWER COST
streamlined methods for ensuring that safe, effective products are brought
to market without delay.
A learning health care system depends on evidence to promote im-
provements in care delivery processes and patient care and overall system
improvement. Consequently, health researchers are critical partners in gen-
erating knowledge on the effectiveness and value of interventions and care
protocols. A commitment to practical and efficient research methods across
the spectrum of the research enterprise—the design and operation of clini-
cal trials, the development of clinical registries and clinical databases, the
creation of standards and metrics, modeling and simulation studies, studies
of health services and care delivery processes, and the aggregation of study
results into systematic reviews and clinical guidelines—is foundational for a
learning system. Through their programmatic and funding activities, private
philanthropies, as well as agencies and organizations such as the Agency for
Healthcare Research and Quality, the National Institutes of Health, and the
Patient-Centered Outcomes Research Institute have a central role to play in
the stewardship and strategic direction of these activities.
Missed opportunities for better health care have real human and eco-
nomic impacts. If the care in every state was at the quality delivered by the
highest performing state, there would have been an estimated 75,000 fewer
deaths across the country in 2005 (McCarthy et al., 2009; Schoenbaum et al.,
2011). Current waste diverts resources from productive use—an estimated
$750 billion lost (IOM, 2010). It is only through shared commitments,
in alignment with a supportive policy environment, that the opportunities
o
ffered by science and information technology can be captured to address the
health care system’s growing challenges and to ensure that it reaches its full
potential to provide the best care for each patient. The nation’s health and
economic futures—best care at lower cost—depend on the ability to steward
the evolution of a continuously learning health care system.
REFERENCES
Anderson, G. F. 2010. Chronic care: Making the case for ongoing care. Princeton, NJ: Robert
Wood Johnson Foundation.
Antman, E. M., J. Lau, B. Kupelnick, F. Mosteller, and T. C. Chalmers. 1992. A comparison
of results of meta-analyses of randomized control trials and recommendations of clinical
experts. Treatments for myocardial infarction. Journal of the American Medical Associa-
tion 268(2):240-248.
Arora, V., S. Gangireddy, A. Mehrotra, R. Ginde, M. Tormey, and D. Meltzer. 2009. Abil-
ity of hospitalized patients to identify their in-hospital physicians. Archives of Internal
Medicine 169(2):199-201.
Auerbach, D. I., and A. L. Kellermann. 2011. A decade of health care cost growth has wiped
out real income gains for an average US family. Health Affairs 30(9):1630-1636.
OCR for page 39
SUMMARY 39
Bates, D. W., L. L. Leape, D. J. Cullen, N. Laird, L. A. Petersen, J. M. Teich, E. Burdick, M.
Hickey, S.��������������������������������������������������������������������������������
�������������������������������������������������������������������������������
Kleefield, B. Shea, M. Vander Vliet, and D. L. Seger. 1998. Effect of computer-
ized physician order entry and a team intervention on prevention of serious medication
errors. Journal of the American Medical Association 280(15):1311-1316.
Bates, D. W., J. M. Teich, J. Lee, D. Seger, G. J. Kuperman, N. Ma’Luf, D. Boyle, and L. Leape.
1999. The impact of computerized physician order entry on medication error prevention.
Journal of the American Medical Informatics Association 6(4):313-321.
Bechel, D. L., W. A. Myers, and D. G. Smith. 2000. Does patient-centered care pay off? Joint
Commission Journal on Quality Improvement 26(7):400-409.
Bertakis, K. D., and R. Azari. 2011a. Determinants and outcomes of patient-centered care.
Patient Education and Counseling 85(1):46-52.
Bertakis, K. D., and R. Azari. 2011b. Patient-centered care is associated with decreased health
care utilization. Journal of the American Board of Family Medicine 24(3):229-239.
Boyd, C. M., J. Darer, C. Boult, L. P. Fried, L. Boult, and A. W. Wu. 2005a. Clinical practice
guidelines and quality of care for older patients with multiple comorbid diseases. Journal
of the American Medical Association 294(6):716.
Boyd, C. M., J. Darer, C. Boult, L. P. Fried, L. Boult, and A. W. Wu. 2005b. Clinical prac-
tice guidelines and quality of care for older patients with multiple comorbid diseases:
Implications for pay for performance. Journal of the American Medical Association
294(6):716-724.
Brach, C., B. Dreyer, P. Schyve, L. M. Hernandez, C. Baur, A. J. Lemerise, and R. Parker.
2012. Attributes of a health literate organization. Discussion Paper, Institute of Medi-
cine, Washington, DC. http://www.iom.edu/Global/Perspectives/2012/Attributes.aspx
(accessed May 27, 2012).
Brownstein, J. S., S. N. Murphy, A. B. Goldfine, R. W. Grant, M. Sordo, V. Gainer, J. A.
Colecchi, A.�����������������������������������������������������������������������������
����������������������������������������������������������������������������
Dubey, D. M. Nathan, J. P. Glaser, and I. S. Kohane. 2010. Rapid identifica-
tion of myocardial infarction risk associated with diabetes medications using electronic
medical records. Diabetes Care 33(3):526-531.
Burdi, M. D., and L. C. Baker. 1999. Physicians’ perceptions of autonomy and satisfaction in
California. Health Affairs 18(4):134.
Bureau of Transportation Statistics. 2011. National transportation statistics. Washington, DC:
Research and Innovation Technology Administration, U.S. Department of Transportation.
Casalino, L. P., D. Dunham, M. H. Chin, R. Bielang, E. O. Kistner, T. G. Karrison, M. K. Ong,
U. Sarkar, M. A. McLaughlin, and D. O. Meltzer. 2009. Frequency of failure to inform
patients of clinically significant outpatient test results. Archives of Internal Medicine
169(12):1123-1129.
Cebul, R. D., T. E. Love, A. K. Jain, and C. J. Hebert. 2011. Electronic health records and
quality of diabetes care. New England Journal of Medicine 365(9):825-833.
Certo, C. M. 1985. History of cardiac rehabilitation. Physical Therapy 65(12):1793-1795.
Chauhan, S. P., V. Berghella, M. Sanderson, E. F. Magann, and J. C. Morrison. 2006. American
College of Obstetricians and Gynecologists practice bulletins: An overview. American
Journal of Obstetrics and Gynecology 194(6):1564-1572.
Chernew, M. E., R. E. Mechanic, B. E. Landon, and D. G. Safran. 2011. Private-payer inno-
vation in Massachusetts: The “alternative quality contract.” Health Affairs (Millwood)
30(1):51-61.
Classen, D. C., R. Resar, F. Griffin, F. Federico, T. Frankel, N. Kimmel, J. C. Whittington,
A. Frankel, A. Seger, and B. C. James. 2011. “Global trigger tool” shows that adverse
events in hospitals may be ten times greater than previously measured. Health Affairs
(Millwood) 30(4):581-589.
OCR for page 40
40 BEST CARE AT LOWER COST
CMS (Centers for Medicare & Medicaid Services). 2012. National health expenditures
summary and GDP: Calendar years 1960-2010. http://www.cms.gov/Research-
Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/
downloads/tables.pdf (accessed August 31, 2012).
Congressional Budget Office. 2008. Issues and options in infrastructure investment. Washing-
ton, DC: Congressional Budget Office.
Congressional Budget Office. 2009. Health Information Technology for Economic and Clini-
cal Health Act. Washington, DC: Congressional Budget Office.
Cosgrove, D., M. Fisher, P. Gabow, G. Gottlieb, G. C. Halvorson, B. James, G. Kaplan, J.
Perlin, R. Petzel, G. Steele, and J. Toussaint. 2012. A CEO checklist for high-value health
care. Discussion Paper, Institute of Medicine, Washington, DC. http://www.iom.edu/
CEOChecklist (accessed August 31, 2012).
Curry, L. A., E. Spatz, E. Cherlin, J. W. Thompson, D. Berg, H. H. Ting, C. Decker, H. M.
Krumholz, and E. H. Bradley. 2011. What distinguishes top-performing hospitals in acute
myocardial infarction mortality rates? A qualitative study. Annals of Internal Medicine
154(6):384-390.
Degner, L. F., L. J. Kristjanson, D. Bowman, J. A. Sloan, K. C. Carriere, J. O’Neil, B. Bilodeau,
P. Watson, and B. Mueller. 1997. Information needs and decisional preferences in women
with breast cancer. Journal of the American Medical Association 277(18):1485-1492.
DeNavas-Walt, C., B. D. Proctor, and J. C. Smith. 2011. Income, poverty, and health insurance
coverage in the United States: 2010. Washington, DC: U.S. Census Bureau.
Donchin, Y., D. Gopher, M. Olin, Y. Badihi, M. Biesky, C. L. Sprung, R. Pizov, and S. Cotev.
2003. A look into the nature and causes of human errors in the intensive care unit. Qual-
ity & Safety in Health Care 12(2):143-147.
Epstein, R. M., P. Franks, C. G. Shields, S. C. Meldrum, K. N. Miller, T. L. Campbell, and K.
Fiscella. 2005. Patient-centered communication and diagnostic testing. Annals of Family
Medicine 3(5):415-421.
Fagerlin, A., K. R. Sepucha, M. P. Couper, C. A. Levin, E. Singer, and B. J. Zikmund-Fisher.
2010. Patients’ knowledge about 9 common health conditions: The decisions survey.
Medical Decision Making 30(Suppl. 5):S35-S52.
Farrell, D., E. Jensen, B. Kocher, N. Lovegrove, F. Melhem, L. Mendonca, and B. Parish. 2008.
Accounting for the cost of US health care: A new look at why Americans spend more.
Washington, DC: McKinsey Global Institute.
Harrison, T. R. 1962. Principles of internal medicine. 4th ed. New York: Blakiston Division,
McGraw-Hill.
Helmchen, L. A., and A. T. Lo Sasso. 2010. How sensitive is physician performance to alter-
native compensation schedules? Evidence from a large network of primary care clinics.
Health Economics 19(11):1300-1317.
Hendrich, A., M. P. Chow, B. A. Skierczynski, and Z. Lu. 2008. A 36-hospital time and mo-
tion study: How do medical-surgical nurses spend their time? The Permanente Journal
12(3):25-34.
Hendrickson, G., T. M. Doddato, and C. T. Kovner. 1990. How do nurses use their time?
Journal of Nursing Administration 20(3):31-37.
Hilbert, M., and P. López. 2011. The world’s technological capacity to store, communicate,
and compute information. Science 332(6025):60-65.
Holve, E., and P. Pittman. 2009. A first look at the volume and cost of comparative effective-
ness research in the United States. Washington, DC: AcademyHealth.
Holve, E., and P. Pittman. 2011. The cost and volume of comparative effectiveness research.
In Learning what works: Infrastructure required for comparative effectiveness research:
Workshop summary. Institute of Medicine. Washington, DC: The National Academies
Press. Pp. 89-96.
OCR for page 41
SUMMARY 41
Howden, L. M., and J. A. Meyer. 2011. Age and sex composition: 2010. Washington, DC:
U.S. Census Bureau, U.S. Department of Commerce.
Hsiao, C.-J., E. Hing, T. C. Socey, and B. Cai. 2011. Electronic health record systems and
intent to apply for meaningful use incentives among office-based physician practices:
United States, 2001-2011. Hyattsville, MD: National Center for Health Statistics.
IOM (Institute of Medicine). 1999. To err is human: Building a safer health system. Washing-
ton, DC: National Academy Press.
IOM. 2001a. Crossing the quality chasm: A new health system for the 21st century. Washing-
ton, DC: National Academy Press.
IOM. 2001b. Mammography and beyond: Developing technologies for the early detection of
breast cancer. Washington, DC: National Academy Press.
IOM. 2003. Unequal treatment: Confronting racial and ethnic disparities in health care.
Washington, DC: The National Academies Press.
IOM. 2004. Health literacy: A prescription to end confusion. Washington, DC: The National
Academies Press.
IOM. 2008. Knowing what works in health care: A roadmap for the nation. Washington, DC:
The National Academies Press.
IOM. 2009. Beyond the HIPAA privacy rule: Enhancing privacy, improving health through
research. Washington, DC: The National Academies Press.
IOM. 2010. The healthcare imperative: Lowering costs and improving outcomes: Workshop
series summary, Learning health system series. Washington, DC: The National Academies
Press.
IOM. 2011a. Clinical practice guidelines we can trust. Washington, DC: The National Acad-
emies Press.
IOM. 2011b. Patients charting the course: Citizen engagement in the learning health system:
Workshop summary. Washington, DC: The National Academies Press.
Jencks, S. F., M. V. Williams, and E. A. Coleman. 2009. Rehospitalizations among pa-
tients in the Medicare fee-for-service program. New England Journal of Medicine
360(14):1418-1428.
Joint Commission. 2011. Improving America’s hospitals: The Joint Commission’s annual
report on quality and safety. http://www.jointcommission.org/assets/1/6/TJC_Annual_
Report_2011_9_13_11_.pdf (accessed September 25, 2011).
Kaiser Family Foundation and Health Research & Educational Trust. 2009. Employer health
benefits: 2009 annual survey. Menlo Park, CA: Kaiser Family Foundation and Health
Research & Educational Trust.
Kasper, D. L., and T. R. Harrison. 2005. Harrison’s principles of internal medicine. 16th ed.,
2 vols. New York: McGraw-Hill, Medical Publications Division.
Keehan, S. P., A. M. Sisko, C. J. Truffer, J. A. Poisal, G. A. Cuckler, A. J. Madison, J. M.
Lizonitz, and S. D. Smith. 2011. National health spending projections through 2020:
Economic recovery and reform drive faster spending growth. Health Affairs (Millwood)
30(8):1594-1605.
Landrigan, C. P., G. J. Parry, C. B. Bones, A. D. Hackbarth, D. A. Goldmann, and P. J. Sharek.
2010. Temporal trends in rates of patient harm resulting from medical care. New Eng-
land Journal of Medicine 363(22):2124-2134.
Larsson, S., P. Lawyer, G. Garellick, B. Lindahl, and M. Lundström. 2012. Use of 13 disease
registries in 5 countries demonstrates the potential to use outcome data to improve health
care’s value. Health Affairs (Millwood) 31(1):220-227.
Lee, C. N., R. Dominik, C. A. Levin, M. J. Barry, C. Cosenza, A. M. O’Connor, A. G. Mulley,
Jr., and K. R. Sepucha. 2010a. Development of instruments to measure the quality of
breast cancer treatment decisions. Health Expectations 13(3):258-272.
OCR for page 42
42 BEST CARE AT LOWER COST
Lee, C. N., C. S. Hultman, and K. Sepucha. 2010b. Do patients and providers agree about
the most important facts and goals for breast reconstruction decisions? Annals of Plastic
Surgery 64(5):563-566.
Lee, C. N., J. Belkora, Y. Chang, B. Moy, A. Partridge, and K. Sepucha. 2011. Are patients
making high-quality decisions about breast reconstruction after mastectomy? Plastic and
Reconstructive Surgery 127(1):18-26.
Lee, C. N., Y. Chang, N. Adimorah, J. K. Belkora, B. Moy, A. H. Partridge, D. W. Ollila,
and K. R. Sepucha. 2012. Decision making about surgery for early-stage breast cancer.
Journal of the American College of Surgeons 214(1):1-10.
Levinson, D. R. 2010. Adverse events in hospitals: National incidence among Medicare ben-
eficiaries. Washington, DC: U.S. Department of Health and Human Services, Office of
Inspector General.
Linzer, M., L. B. Manwell, E. S. Williams, J. A. Bobula, R. L. Brown, A. B. Varkey, B. Man,
J. E. McMurray, A. Maguire, B. Horner-Ibler, M. D. Schwartz, and MEMO (Minimiz-
ing Error, Maximizing Outcome) Investigators. 2009. Working conditions in primary
care: Physician reactions and care quality. Annals of Internal Medicine 151(1):28-36,
W26-W29.
Maurer, M., P. Dardess, K. L. Carman, K. Frazier, and L. Smeeding. 2012. Guide to patient
and family engagement: Environmental scan report. Rockville, MD: Agency for Health-
care Research and Quality.
McCarthy, D., S. How, C. Schoen, J. Cantor, and D. Belloff. 2009. Aiming higher: Results
from a state scorecard on health system performance. New York: Commonwealth Fund
Commission on a High Performance Health System.
McGinnis, J. M., P. Williams-Russo, and J. R. Knickman. 2002. The case for more active
policy attention to health promotion. Health Affairs (Millwood) 21(2):78-93.
McGlynn, E. A., S. M. Asch, J. Adams, J. Keesey, J. Hicks, A. DeCristofaro, and E. A. Kerr.
2003. The quality of health care delivered to adults in the United States. New England
Journal of Medicine 348(26):2635-2645.
Mechanic, R. E., P. Santos, B. E. Landon, and M. E. Chernew. 2011. Medical group responses
to global payment: Early lessons from the “alternative quality contract” in Massachu-
setts. Health Affairs (Millwood) 30(9):1734-1742.
Nabel, E. G., and E. Braunwald. 2012. A tale of coronary artery disease and myocardial
infarction. New England Journal of Medicine 366(1):54-63.
Neily, J., P. D. Mills, Y. Young-Xu, B. T. Carney, P. West, D. H. Berger, L. M. Mazzia, D. E.
Paull, and J. P. Bagian. 2010. Association between implementation of a medical team
training program and surgical mortality. Journal of the American Medical Association
304(15):1693-1700.
Neily, J., P. D. Mills, N. Eldridge, B. T. Carney, D. Pfeffer, J. R. Turner, Y. Young-Xu, W.
Gunnar, and J. P. Bagian. 2011. Incorrect surgical procedures within and outside of the
operating room: A follow-up report. Archives of Surgery 146(11):1235-1239.
Nelson, L. 2012. Lessons from Medicare’s demonstration projects on disease management and
care coordination. Washington, DC: Congressional Budget Office.
Ness, R. B. 2007. Influence of the HIPAA privacy rule on health research. Journal of the
American Medical Association 298(18):2164-2170.
O’Connor, A. M., C. L. Bennett, D. Stacey, M. Barry, N. F. Col, K. B. Eden, V. A. Entwistle,
V. Fiset, M. Holmes-Rovner, S. Khangura, H. Llewellyn-Thomas, and D. Rovner. 2009.
Decision aids for people facing health treatment or screening decisions. Cochrane Data-
base of Systematic Reviews (3):CD001431.
Office of the Attorney General of Massachusetts. 2011. Examination of health care cost
trends and cost drivers pursuant to G.L. c. 118g, § 6½(b). http://www.mass.gov/ago/
docs/healthcare/2011-hcctd-full.pdf (accessed August 30, 2012).
OCR for page 43
SUMMARY 43
OMB (Office of Management and Budget). 2010. Fiscal year 2011 budget of the U.S. govern-
ment. Washington, DC: OMB.
Parekh, A. K., and M. B. Barton. 2010. The challenge of multiple comorbidity for the US
health care system. Journal of the American Medical Association 303(13):1303-1304.
Peikes, D., A. Chen, J. Schore, and R. Brown. 2009. Effects of care coordination on hospital-
ization, quality of care, and health care expenditures among Medicare beneficiaries: 15
randomized trials. Journal of the American Medical Association 301(6):603-618.
Pham, H. H., D. Schrag, A. S. O’Malley, B. Wu, and P. B. Bach. 2007. Care patterns in Medi-
care and their implications for pay for performance. New England Journal of Medicine
356(11):1130-1139.
Pham, H. H., A. S. O’Malley, P. B. Bach, C. Saiontz-Martinez, and D. Schrag. 2009. Primary
care physicians’ links to other physicians through Medicare patients: The scope of care
coordination. Annals of Internal Medicine 150(4):236-242.
Potts, A. L., F. E. Barr, D. F. Gregory, L. Wright, and N. R. Patel. 2004. Computerized physi-
cian order entry and medication errors in a pediatric critical care unit. Pediatrics 113(1
Pt. 1):59-63.
Pronovost, P., D. Needham, S. Berenholtz, D. Sinopoli, H. T. Chu, S. Cosgrove, B. Sexton, R.
Hyzy, R. Welsh, G. Roth, J. Bander, J. Kepros, and C. Goeschel. 2006. An intervention
to decrease catheter-related bloodstream infections in the ICU. New England Journal of
Medicine 355(26):2725-2732.
Pronovost, P. J., C. A. Goeschel, K. L. Olsen, J. C. Pham, M. R. Miller, S. M. Berenholtz, J. B.
Sexton, J. A. Marsteller, L. L. Morlock, A. W. Wu, J. M. Loeb, and C. M. Clancy. 2009.
Reducing health care hazards: Lessons from the commercial aviation safety team. Health
Affairs (Millwood) 28(3):w479-w489.
Schneider, K. M., B. E. O’Donnell, and D. Dean. 2009. Prevalence of multiple chronic condi-
tions in the United States’ Medicare population. Health and Quality of Life Outcomes
7:82.
Schoenbaum, S. C., C. Schoen, J. L. Nicholson, and J. C. Cantor. 2011. Mortality amenable
to health care in the United States: The roles of demographics and health systems per-
formance. Journal of Public Health Policy 32(4):407-429.
Sepucha, K. R., A. Fagerlin, M. P. Couper, C. A. Levin, E. Singer, and B. J. Zikmund-Fisher.
2010. How does feeling informed relate to being informed? The decisions survey. Medical
Decision Making 30(Suppl. 5):S77-S84.
Song, Z., D. G. Safran, B. E. Landon, Y. He, R. P. Ellis, R. E. Mechanic, M. P. Day, and M. E.
Chernew. 2011. Health care spending and quality in year 1 of the alternative quality
contract. New England Journal of Medicine 65(10):909-918.
Spear, S. J. 2005. Fixing health care from the inside, today. Harvard Business Review 83(9):78.
Stacey, D., C. L. Bennett, M. J. Barry, N. F. Col, K. B. Eden, M. Holmes-Rovner, H. Llewellyn-
Thomas, A. Lyddiatt, F. Legare, and R. Thomson. 2011. Decision aids for people fac-
ing health treatment or screening decisions. Cochrane Database of Systematic Reviews
(10):CD001431.
Stewart, M., J. B. Brown, A. Donner, I. R. McWhinney, J. Oates, W. W. Weston, and J. Jordan.
2000. The impact of patient-centered care on outcomes. Journal of Family Practice
49(9):796-804.
Stremikis, K., C. Schoen, and A.-K. Fryer. 2011. A call for change: The 2011 Commonwealth
Fund survey of public views of the U.S. health system. New York: Commonwealth Fund.
Tinetti, M. E., S. T. Bogardus, and J. V. Agostini. 2004. Potential pitfalls of disease-specific
guidelines for patients with multiple conditions. New England Journal of Medicine
351(27):2870-2874.
OCR for page 44
44 BEST CARE AT LOWER COST
Tricoci, P., J. M. Allen, J. M. Kramer, R. M. Califf, and S. C. Smith, Jr. 2009. Scientific
evidence underlying the ACC/AHA clinical practice guidelines. Journal of the American
Medical Association 301(8):831-841.
Trude, S. 2003. So much to do, so little time: Physician capacity constraints, 1997-2001.
Tracking report/Center for Studying Health System Change (8):1.
Tucker, A. L., and S. J. Spear. 2006. Operational failures and interruptions in hospital nursing.
Health Services Research 41(3 Pt. 1):643-662.
U.S. Bureau of Labor Statistics. 2010a. May 2009 national occupational employment and
wage estimates. http://www.bls.gov/oes/2009/may/oes_nat.htm (accessed May 22, 2012).
U.S. Bureau of Labor Statistics. 2010b. National compensation survey: Occupational earn-
ings in the United States, 2009. http://www.bls.gov/ncs/ocs/sp/nctb1346.pdf (accessed
May 22, 2012).
U.S. Bureau of Labor Statistics. 2012. Labor force statistics from the current population sur-
vey. http://data.bls.gov/pdq/SurveyOutputServlet?request_action=wh&graph_name=LN_
cpsbref1 (accessed May 23, 2012).
Wennberg, J. E., E. S. Fisher, and J. S. Skinner. 2002. Geography and the debate over Medicare
reform. Health Affairs (Millwood) (Suppl. Web Exclusives):W96-W114.
Yarnall, K. S. H., K. Krause, K. Pollak, M. Gradison, and J. Michener. 2009. Family physicians
as team leaders: “Time” to share the care. Preventing Chronic Disease 6(2).