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1
Engineering a Learning
Healthcare System
INTRODUCTION
As the roles and complexities of provider profiles, patient care pro-
cesses, and diagnostic and treatment options grow—often in an independent
and disintegrated fashion—gaps in efforts concerning patient safety, clinical
outcomes, reimbursement policy, medical education, and other aspects of
the functioning of the healthcare system continue to widen. Defining the
future state of American health care will require a clear vision on the part
of the healthcare community.
The Engineering a Learning Healthcare System: A Look at the Future
workshop drew together participants from healthcare and engineering dis-
ciplines to identify challenges in health care, including effectiveness, safety,
and efficiency, that might benefit from a systems engineering perspective.
With the baseline assumption that reform efforts must extend beyond
finance to remedy the growing complexities in health care. Participants
evaluated aspects of healthcare culture and practice through examples and
lessons from within and outside the healthcare sector. Workshop attendees
considered approaches to taking a new look at the organization, structure,
function, and delivery of services in health care while maintaining a patient-
centered focus.
Presentations and discussions touched on elements from prior work-
shops, including Clinical Data as a Public Good and the Learning Health-
care System, in an effort to synthesize topics and take advantages of various
synergies. The Engineering a Learning Healthcare System: A Look at the
2
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28 ENGINEERING A LEARNING HEALTHCARE SYSTEM
Future workshop addressed multiple components central to the work of the
Roundtable on Value & Science-Driven Health Care:
• Facilitate collaboratie healthcare choices of each patient and
provider.
• Ensure innoation, quality, safety, and value in health care.
• Foster the transformation of the American healthcare system
into a learning health system that generates and applies evidence
naturally.
• Emphasize preention and health promotion as means to increase
value.
• Instill principles of accountability, care coordination, expectation
setting, incentive alignment, and patient-centered focus.
This chapter contains a brief summary of the workshop’s three key-
note addresses followed by individually authored pieces based on those
presentations. The three keynote talks were a commentary by Brent C.
James on “Learning Opportunities for Health Care,” W. Dale Compton’s
discussion of “Teaching Opportunities from Engineering,” and Donald
M. Berwick’s presentation, “Observations on Initiating Systems Change in
Health Care.”
Engineering a Learning Healthcare System: A Look at the Future
The first two keynote addresses together outlined the landscape of is-
sues the workshop was designed to address and framed many of the most
important questions that workshop participants would explore. The third
keynote address, delivered near the end of the workshop, added further
depth to the intellectual framework of the workshop and contributed ad-
ditional specific suggestions for moving forward in engineering a learning
healthcare system.
Reflecting the fact that the workshop was sponsored by the Institute of
Medicine (IOM) Roundtable on Value & Science-Driven Health Care in co-
operation with the National Academy of Engineering (NAE), the program
opened with two talks that addressed, respectively, issues in health care and
opportunities for addressing those issues from the realm of engineering.
The first presentation, “Learning Opportunities for Health Care” was
by Brent C. James, executive director of the Institute for Health Care
Delivery Research and vice president of medical research and continuing
medical education at Intermountain Healthcare. Based in Salt Lake City,
Intermountain Healthcare is an integrated healthcare system of hospitals,
clinics, a large physician group, and a health maintenance organization/
preferred provider organization insurance plan covering more than 450,000
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29
ENGINEERING A LEARNING HEALTHCARE SYSTEM
people. James is known internationally for his work in clinical quality
improvement, patient safety, and the infrastructure that underlies success-
ful improvement efforts, such as culture change, data systems, payment
methods, and management roles.
James began by discussing the historical evolution of the modern struc-
ture of healthcare delivery. He outlined five areas where care delivery cur-
rently falls short of its theoretic potential, touched briefly on the reasons
for that failure, and then reflected on emerging solutions, emerging frame-
works, and challenges that create a context for work on improving health
care.
The five areas of health system failure noted by James were (1) the well-
documented, significant variation in practices; (2) high rates of inappropri-
ate care; (3) unacceptable rates of preventable patient injury and death; (4)
a striking inability to “do what we know works”; and (5) large amounts of
waste and spiraling prices, which limit access. James suggested that we may
be on the verge of a head-on collision of two factors: first, the guild nature
of medicine, in which physicians, nurses, and other health professionals act
as stand-alone experts, and second, what James characterized as “clinical
uncertainty.” The latter term refers to the era of unprecedented complexity
that characterizes health care today, an era marked by a lack of valid clini-
cal knowledge and evidence regarding the best treatments and exponentially
increasing new medical knowledge, in tandem with a continued reliance
on subjective judgment and the innate limitations of the expert mind when
making complex decisions.
James proposed four specific areas for attention in the effort to al-
leviate these shortfalls: (1) addressing clinical complexity, (2) developing a
more robust capacity of knowledge management in a learning system, (3)
improving systems for care delivery via a team approach instead of through
independent experts, and (4) designing health care as a coordinated system.
In particular, he called on engineering professionals to share their knowl-
edge and expertise with healthcare professionals in order to address these
issues collaboratively.
W. Dale Compton complemented James’ healthcare expertise by offer-
ing the engineering perspective. Compton, the Lillian M. Gilbreth Distin-
guished Professor (Emeritus) of Industrial Engineering at Purdue University,
brings extensive experience in engineering research from work in academia
and the private sector and has served since 2000 as Home Secretary for
the NAE. He offered a variety of suggestions on how engineering can help
health care transition from where it is today to the point where it might
realize its full potential as a learning healthcare system.
Compton explored some of the most pressing, overarching issues, in-
cluding creating change within large organizations, healthcare transforma-
tions, and integrating learning into systems change. Focusing on a case
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0 ENGINEERING A LEARNING HEALTHCARE SYSTEM
study of the Ford Motor Company, Compton outlined several principles
of continuous improvement that he believes could benefit health care. Or-
ganizing a comprehensive understanding of health care’s disparate parts
from a systems point of view will be a critically important step. It will also
be vital to have adequate data—and the capacity to mine that data for
knowledge—as well as to engage participation by staff at all levels of an
organization.
Communication is another key factor. Although communication has
many dimensions that vary among organizations, Compton asserted that
engineers and healthcare professionals have considerable work to do in
creating a common understanding of problems and opportunities. A cadre
consisting of both engineering and medical professionals is needed to tackle
some of health care’s more intractable problems, working in the near term
on problem solving and in the longer term on more fundamental systems
design.
Later in the workshop, a keynote address from Donald M. Berwick
explored in greater depth the issues that health care faces and the ways in
which solutions might be engineered. Then president and chief executive
officer (CEO) of the Institute for Healthcare Improvement, Berwick was
also a professor of pediatrics and healthcare policy at the Harvard Medi-
cal School and professor of health policy and management at the Harvard
School of Public Health. Berwick posited that there is enormous potential
benefit to health care in deepening system knowledge and basing action on
that knowledge. He warned, however, that real value in healthcare reform
will come only if people are willing to confront the status quo, whether
in technique, culture, training, or economics. The core challenge, he sug-
gested, is that health care needs to clarify its aims, and leadership is needed
to make that happen.
The heart of Berwick’s presentation discussed seven issues: (1) the need
to emphasize interdependence in the healthcare system; (2) the need to
make the redesign of processes more visible; (3) the need to recognize the
importance and value of dynamic learning and local adaptation as scien-
tific learning processes; (4) the question of waste, which health care must
confront with knowledge and action; (5) the need for a sufficient platform
for robust multidisciplinary research and development at the intersection
of health care and engineering; (6) the need to enrich professional educa-
tion and development in health care—for example, with more attention to
teamwork and systems thinking; and (7) the reform of health care in a way
that would result in a radically different, integrated systems design of the
fundamental healthcare infrastructure.
Following are the full presentations of the keynote addresses that set
the stage and tone for the discussions that took place throughout the re-
mainder of the workshop.
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1
ENGINEERING A LEARNING HEALTHCARE SYSTEM
LEARNING OPPORTUNITIES FOR HEALTH CARE
Brent C. James, M.D., M.Stat., Institute for Health Care
Deliery Research, Intermountain Healthcare, Inc.
The healing professions have always been central to human society.
Humanity’s earliest written records refer to clinical practice. For example,
the Code of Hammurabi, written almost 1,800 years BCE, addresses the
legal implications of medical treatment. Artifacts from Stone Age cultures
indicate the presence and importance of healers and the healing professions
in preliterate times.
Until relatively recently, the healing role was limited to two basic ele-
ments: when approached by a patient suffering a health problem, a healer
could give unique insight into what was happening—that is, he could ex-
plain the present; and, drawing on experience with similar cases from the
past, the healer could predict the patient’s potential health future. But for
most of human history, healers had little to offer in the way of effective
treatment. Any “healing” that occurred was mainly of a spiritual nature—a
shoulder to lean on, a listening ear, and (2) compassion and understanding
that could help a patient reach balance, acceptance, and closure. While no
one made careful measurements of the health outcomes of early medical
care at a population level, educated observers routinely opined that if one
were seriously ill and sought the attentions of a typical physician, chances
of survival actually declined. For many centuries, the most common ap-
proaches to treatment centered on a humoral theory of disease, which held
that the human body was made up of four basic humors: black bile, yellow
bile, white phlegm, and red blood. Disease was thought to arise from imbal-
ances in the humors. Health could be restored by bringing the humors back
into balance, usually by removing some of the red humor. As late as 1900,
the most common physician-prescribed treatment in the United States was
bloodletting. The second most common therapy was the administration of
purgatives, producing chemically induced vomiting and diarrhea. Hospitals
were where poor people went to die (Porter, 1997; Rosenberg, 1987; Starr,
1984).
Around the turn of the 19th century, medical practice underwent a
massive transformation. Between the 1860s, during the American Civil War,
and about 1910, clinical leaders introduced four important changes (Porter,
1997; Rosenberg, 1987; Starr, 1984).
First, they adopted the scientific method as the foundation for “how
we know what we know” within the allopathic healing professions. Driven
by the scientific method, a germ-based theory of disease rapidly replaced
competing frameworks and their related treatments, such as the humoral
theory. Over time, this approach greatly improved the professions’ under-
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2 ENGINEERING A LEARNING HEALTHCARE SYSTEM
standing of the human organism in health and disease. It also produced
literally thousands of effective treatments and fundamentally changed the
medical model: where before physicians could explain the present and pre-
dict the future, medical science gave them the ability to “change a patient’s
future.”1
Second, clinical leaders created the modern model of clinical educa-
tion. The transformation of medical education started with a report of the
American Medical Association published in 1902. That report led Andrew
Carnegie to commission Abner Flexner, a high school teacher, to conduct
a more detailed evaluation. Flexner found that the average course of study
to become a licensed physician took about 4 months. (Apparently, little ef-
fort was needed to understand the humoral theory of disease, bloodletting,
and purgatives.) That training usually took place exclusively in a classroom
setting, with no exposure to patients or patient care. Flexner’s report, pub-
lished in 1910, led to the closing of more than half of all so-called “medical
schools” in the United States. A new 2-year curriculum, centered in hospi-
tals at the patient bedside, emerged.
Third, the leaders tightened the process of professional licensing. Previ-
ously, laws regarding professional licensure had served primarily to protect
the guild of medicine from external competition. Those laws took on new
meaning when they rested on the foundation of medical science and effec-
tive clinical education. Clinical leaders refined the licensing laws, produced
a new definition of medical professionalism, and used the resulting tools
to hold the profession as a whole uniformly accountable to a much higher
level of demonstrated knowledge, skills, and ethical conduct.
Finally, clinical leaders created a new organizational structure for care
delivery. In 1895 physicians planning the new Johns Hopkins University
Hospital divided management of the facility from the practice of medicine.
A new class of health facility administrators managed staffing, supplies,
and the physical plant, freeing physicians to focus exclusively on patients’
clinical diagnoses and treatment.
Collectively, these changes led to dramatic gains in human health mea-
sured at a population level. A child born in the United States in 1900 had
a life expectancy of 49 years. A child born 100 years later, in 2000, could
expect almost 77 years of life (Cutler et al., 2006) (Figure 1-1). The years
from 1900 to 1960 might be called the Public Health Era. Essentially all
of the life expectancy gains achieved over those six decades came from
sanitation, safe food, clean water, vaccination, and immunization. For
example, the cholera epidemics that killed thousands at a time during the
1 The phrase comes from Dr. James Reinertsen through a personal communication. He
describes the role of the physician as (1) explain the present, (2) predict the future, and (3)
change a patient’s health future.
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
100 100
Life Expect ancy at Birth (year s)
76
75 75
75
.8
73
7
.3
7
.8
70
8
69
.7
68
.9
6
.1
63
.
6
59
.2
56
.4
50 50
51
49
.5
.2
25 25
0 0
19
19
19
19
19
19
19
19
19
19
20
00
10
20
30
40
50
60
70
80
90
00
From 1900–1960: 20.7 years gained over 6 decades = 3.45 years/decade.
From 1900-1960: :26.97 years gained overer decades = 1.74 years/decade.
Since 1960
0.7 years gained ov 4 6 decades = 3.45 years/decade.
FIGURE 1-16.97 years in life expectancy at birth1.74 years/decade.States, by de-
Since 1960: Increases gained over 4 decades = within the United
cade, 1900 through 2000.
latter half of the 19th century disappeared almost completely following the
introduction of easily accessible clean drinking water. Typhus fever, one of
the most common killers in human history, was virtually eliminated through
improvements in living conditions that reduced the infestations of fleas
that spread the disease. Deaths from smallpox, a true scourge, ceased with
the introduction of effective vaccination programs. In 1900, somewhere
between one-fifth and one-third of all children died before reaching the age
of 5 years, victims of common pediatric infectious diseases—diphtheria,
pertussis, measles, mumps, and polio (CDC, 1999). Widespread childhood
immunization makes such deaths very rare today. During the Public Health
Era, life expectancy at birth increased by an average of 3.45 years with
each passing decade (as calculated by the author from the data presented
in Figure 1-1).
Life expectancy gains due to advances in public health plateaued in the
decade following the end of World War II. As these public health−related
gains attenuated, however, a new source of health improvements emerged.
For the first time in human history, physicians and nurses began to have
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
treatment tools that could change a patient’s future. Starting midcentury,
disease treatment began to have a major impact on how long and how well
people lived as measured at the population level. For example, since 1960
age-adjusted mortality from ischemic cardiac disease (the number one killer
in modern first-world nations) has decreased by 56 percent (from 307.4 to
134.6 age-adjusted deaths/100,000 people), and since 1950 age-adjusted
mortality from stroke (the number three killer in industrialized nations) has
decreased by 70 percent (from 88.8 to 26.5 age-adjusted deaths/100,000
people) (CDC, 1999; Cutler et al., 2006; National Center for Health Sta-
tistics, 2000). This is remarkable progress, particularly when considered in
the context of the entirety of human history. The evidence is clear: modern
health professionals now routinely offer treatments that would have ap-
peared miraculous to any previous generation.
Aim Defines the System
Given these achievements, it is worth reflecting on what is known about
the factors most important in determining a person’s total health—that is,
how long and how well one lives. In an analysis of the actual causes of
death in the United States, roughly 40 percent of total health was found
to be determined by individual behavioral choices (McGinnis and Foege,
1993). The top three behavior-based challenges to health are tobacco use,
obesity, and consumption of alcohol and other recreational drugs. For
example, alcohol consumption is associated with about 65 percent of fa-
tal violent crimes, 70 percent of all domestic abuse, and 60 percent of all
fatal non−motor vehicle accidents (Doonon, 1998). Other behaviorally
related health issues include sexually transmitted diseases, including AIDS;
pregnancies among unwed teens; and suicide, accidents, and violence, par-
ticularly among young men (McGinnis et al., 2002). Healthy behaviors
are closely linked with educational level, which in turn is associated with
income level and health insurance coverage.2
One’s genetic inheritance determines another 30 percent of total health.
Some scientific progress has been made in understanding linkages between
genes and disease, but the field is still relatively new. Some estimate that we
are still 20 to 30 years away from being able to broadly offer treatments to
counter genetic determinants of health.
Another 20 percent of total health relates to environmental and public
health factors. These factors include clean air, safe water, and the control of
epidemic infectious disease through immunization and sanitation.
2 These four elements usually appear in combination and are very difficult to separate: (1)
low levels of education are directly associated with (2) unhealthy behaviors, (3) low income
levels, and (4) lack of health insurance.
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
Only 5 to 10 percent of total health—an estimated 3.5 to 7 years of
lifespan—derives from the health care delivery system.
In 1977 Aaron Wildavsky published a classic essay in which he defined
“the Great Equation” as the belief that “health equals health care” and
that “health care means access to care.” He cited statistics to show that
the Great Equation is fundamentally false (Wildavsky, 1977). Such findings
underscore the importance of understanding the returns achieved from our
current national investment in health care.
In 2006, the United States spent about $7,100 per person on health
care. For a typical family of four, healthcare expenditures far exceed the
costs of owning a home. (Total national health care expenditures for a
family of four totaled about $2,375 per month in 2005, while the median
family home cost only $1,040 [KFF, 2006].) U.S. expenditures are high
compared with those of other Organisation for Economic Co-operation and
Development (OECD) countries (Peterson and Burton, 2007; Reinhardt
et al., 2002). Sweden, for example, has the reputation of having the finest
socialized medicine system in the world. Despite that country’s spending
less than half of what the United States spends on health per capita, the
average Swede lives about 3 years longer than the average U.S. citizen.
Likewise, although infant mortality rates have decreased very significantly
worldwide over recent decades, the United States has rates roughly twice
as high as those reported in Sweden.3 Wildavsky’s argument raises serious
questions about whether differences in overall health at a national level
can be traced back to a country’s spending on health care. But even if U.S.
health outcomes were equivalent to those of other developed nations, the
United States still spends twice as much per person as most other mod-
ern nations. What do we get for all that extra money? Dr. W. Edwards
Deming, the father of modern quality theory, regularly noted that “[a]im
defines the system.” Relative to health spending, what are the aims of
healthcare delivery? The current national healthcare debate implicitly as-
sumes, without examination, that the primary aim of healthcare delivery is
“total health”—how long and how well we live. There are, however, two
additional possible aims.
When carefully asked, most U.S. citizens say they value their relation-
ship with a trusted medical counselor very highly. They appear to judge
their health outcomes according to their opinion of that relationship, sug-
gesting that to patients, the clinician−patient relationship may be even more
3 Although these figures are often thought to represent a direct reflection of the quality of
each nation’s healthcare delivery system, it is important to note that the Swedish advantage
disappears when risk adjustments are made for the infant mortality rate for gestational age.
Each country defines preterm birth differently at a functional level, with implications for
whether the infant is treated as a stillbirth or is placed in newborn ICU, with massive amounts
of money invested in his/her care.
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
important than health outcomes. “High touch” care denotes the idea of car-
ing, not just curing. Emeril Szilagyi captured the essence of high touch care
quite accurately in his 1965 essay “In Defense of the Art of Medicine”:
A man stricken with disease today is assaulted by the same fears and finds
himself searching for the same helping hand as his ancestors did five or
ten thousand years ago. He has been told about the clever tools of modern
medicine and somewhat vaguely, he expects that by-and-by he will profit
by them, but in his hour of trial his desperate want is for someone who
is personally committed to him, who has taken up his cause, and who is
willing to go to trouble for him. (Szilagyi, 1965)4
High touch care leads to patient satisfaction with the healthcare delivery
system. Effective primary care networks, in which people have easy access
to a clinical counselor, facilitate this kind of care. Compared with other
countries, the United States performs poorly in providing easy access to
high touch care (Schoen et al., 2007).
Another possible aim of health care delivery is rapid response, or “res-
cue care.” Jonsen defined the Rule of Rescue as “the imperative people feel
to rescue identifiable individuals facing suffering or death” (McKie and
Richardson, 2003). For the Rule of Rescue to apply, there needs to be an
emotional link. There must be a name and a face so that the sufferer be-
comes a human being rather than a statistic (McKie and Richardson, 2003).
Some commentators have pointed out that this view of care reflects a “Do
something! She’s dying!” reaction. They note that the interventions applied
do not have to be effective—that humans feel an overwhelming need to try
to help, regardless of the chance for a positive result. For example, about
a year ago, six miners were underground when a coal mine in central Utah
collapsed (the Crandall Mine disaster). Their plight gripped the state of
Utah and the nation, as the news media shared pictures of the six men,
their life stories, and interviews with their distraught friends and families.
Those six men probably died in the initial collapse, but tens of millions of
dollars was spent and three would-be rescuers died on the chance that the
six might be alive. Other examples of the Rule of Rescue are easy to find.
Indeed, the response is so powerful that in many cases, the “victim” need
not be human; we respond in similar fashion to heartrending stories of
animals in distress.
When examined through the lens of rapid-response rescue care, the
U.S. healthcare system is the best in the world. For example, mortality rates
following major trauma in the United States are about half those seen in
Europe. Mortality following a heart attack in the United States is roughly
4 Of particular interest, Szilagyi defined the “art of medicine” as the knowledge and skills
to optimize the clinician−patient relationship.
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
United States Germany Great Britain France
20 20
17.1
16.5
15 15
14.3
Mortality Rate (%)
10 10
9.4 9.2
8.2 8.1
6.5
5 5
0 0
Major Trauma Heart Attack
FIGURE 1-2 System performance by nation for two major examples of rescue
care.
SOURCE: Based on data from OECD (2006).
a third lower than the European rates (Figure 1-2). Mortality rates for
very small (less than 1,500-gram) preterm neonates in the United States
are about half those observed in other developed nations (OECD, 2006).
Renal dialysis rates are five times higher in the United States than in Sweden
and almost twice as high as in the closest European country (Germany).
Similar differences exist for other classes of high-technology, specialty-based
rescue care, such as cancer treatment (Coleman et al., 2008; Verdecchia et
al., 2007).
Many other countries’ healthcare systems outperform the U.S. system
from the perspective of total health and patient satisfaction. This advantage
appears to be attributable to healthier behaviors, better public health, and
easily accessible primary care. Conversely, the U.S. healthcare system per-
forms significantly better for patients suffering from severe illness or injury,
both of which require easy access to technology and subspecialists. Yet
despite the massive investment it requires, rescue care is not strongly asso-
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2 ENGINEERING A LEARNING HEALTHCARE SYSTEM
of the integration of the healthcare information enterprise in the United
States.” A second bill, the 10,000 People Trained by 2010 Act, would au-
thorize the National Science Foundation “to award grants to institutions of
higher education to develop and offer education and training programs.”
The former bill would allocate $3.5 million to $3.8 million per year over
4 years for health informatics and an additional $9 million to $9.6 million
per year over 4 years to establish multidisciplinary centers for informatics
research on healthcare information. Although the first bill was never voted
on, and the second passed in the House but was not voted on by the Senate,
they represent a promising start.
In the long term, it will be necessary to create a cadre of both engi-
neering and medical professionals who can work together. They must un-
derstand each other and be able to tackle collectively some of the difficult
problems facing the healthcare industry. In particular, the NAE/IOM report
Building a Better Deliery System recommends the creation of centers that
would bring together members of the medical and engineering professions
in a multidisciplinary environment where joint research would prosper,
where the development of new tools would be undertaken, where the
existing and new tools would be demonstrated to healthcare providers,
where new joint educational tools could be created, and where assistance
in implementing these tools could be provided to the healthcare community.
The report calls for the establishment of 30 to 50 of these centers at a cost
of about $3.5 million each (NAE/IOM, 2005). The total investment would
be $100 million to $150 million per year—a modest investment compared
with the approximately $500 billion currently being wasted.
A long-term refocusing of some of the educational aspects of both pro-
fessions will be necessary, as well as help with problem solving in the near
term. Multidisciplinary research does not mean that one discipline works
on a problem while another watches or simply consents to having the first
one around; there is some possibility of falling into this trap. Medical pro-
fessionals are becoming more open to letting engineers into their practices,
but they appear to be involved less frequent in joining the engineers in
actually conducting research.
All interested parties should become actively involved in encouraging
members of Congress and other officials to see the importance of investing
not only in the short-term but also in long-term activities that can improve
the system. Collaboration is needed to help people understand what health-
care professionals and engineers can accomplish together in the proper
environment.
For a large, diverse, diffuse system to learn and change requires the
involvement of all people at all levels, starting with a committed CEO. It
is also necessary to have a common understanding of where the system is
going, what is needed, and the tools that are available to assist in those
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
changes, along with a recognition of the importance of creating an environ-
ment that fosters continuous improvement. The tools that engineers possess
need to be brought to bear to help improve the care delivery process, and
more powerful tools need to be developed. Finally, the successes achieved
by individual teams need to be demonstrated to others.
It will not be easy for the healthcare delivery system to learn and
change. Change can be accomplished, individually and collectively, by ap-
plying knowledge learned in other industries. Clearly a crisis is imminent
in the form of safety failures, the knowledge–practice gap, waste and inef-
ficiency, and so forth. In the short term, the tools that can be used to imple-
ment immediate changes must be identified. For the long term, it will be
necessary to develop convincing arguments that research and development
must receive greater funding if a stable system is to be created.
Ford learned. It changed. It survived, and it prospered. Then it went on
to forget some of the important lessons it had learned. The latter must not
happen to health care. Leaders in the field have a responsibility to make
change occur, as well as the wherewithal to collectively make it happen; this
opportunity must not be allowed to stagnate or slip away.
OBSERVATIONS ON INITIATING SYSTEMS CHANGE
IN HEALTH CARE: CHALLENGES TO OVERCOME
Donald M. Berwick, M.D., M.P.P.,
Institute for Healthcare Improement, (former)
Centers for Medicare & Medicaid Serices
The potential benefit to the healthcare system of deepening system
knowledge and of action based on that knowledge is enormous. The result
would be equivalent to the sea change seen in health care with the entry
of statistical rigor and formal experimental design in the evaluation of
healthcare practices in the mid-20th century, led by pioneers such as Fred
Mosteller, Tom Chalmers, Archie Cochrane, Ian Chalmers, and David
Sacket. These courageous intellectual leaders changed the collective think-
ing about evidence, to the enormous benefit of patients. The wedding of
fields that is being explored at this meeting has the same potential, and it
may require equal courage. The potential for the IOM and the NAE to
work together as intellectual leaders is extraordinary. Few other agents of
change could carry us through the transitional barriers that this intellectual
expertise is encountering.
The major challenges to instituting systems thinking in health care lie
with the status quo—in technique, culture, training, and economics. It will
not be possible to realize the benefits of such thinking without confronting
some of those challenges, the same sort of challenges that intellectual transi-
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
tions in any field encounter. The core notion behind this change in perspec-
tive is, “Every system is perfectly designed to achieve the results it gets.”
Therefore, the key to better performance in most complex environments
is to redesign systems. Just as any car has a top speed, health care of any
particular design has a characteristic safety level. The car has a top speed
as a property of the car; in health care, similarly, elements such as error
rates, costs, and defects are properties of the system as currently designed.
That is a scientific premise: that system designs explain system perfor-
mance. Some commonly espoused views fail to acknowledge performance
as a characteristic of a system. These are “black box” views—unscientific
views—of how things get better. Even though some of these views are today
quite hegemonic in public discourse, especially the reliance on incentives to
produce change, there are reasons to be skeptical of them.
A reliance on incentives, on motivation, on encouraging effort, and
on markets is widespread in popular theories of healthcare change today.
However, the healthcare problem is mainly one of improper designs, not an
imperfect market. The great scholar of quality, W. Edwards Deming, used
to say that trying harder is the worst plan. Nonetheless, most of the current
dominant theories of public policy aimed at making health care perform
better are “try harder plans,” and consequently they are likely to fail.
Market mechanisms are particularly worrisome when applied at the
level of individuals. The majority of the healthcare workforce is trying
quite hard now—and mostly doing its best. The advice offered by Donald
Norman in his book on human factors The Design of Eeryday Things is,
“Honor thy user” (Norman, 1988). The worst thing to do when human
factors are at play is to blame the human for the factors. In pursuit of excel-
lence, someone who understands human factors works instead to construct
dikes around the frailties of human beings in order to have systems perform
better than human beings do and much closer to what those humans really
wish they could accomplish. There is little point in trying to mold individual
behavior to achieve excellence through effort. Rather, the ownership of im-
provement lies squarely on the shoulders of leaders of systems rather than
those of individuals within the workforce.
This paper examines seven challenges. One challenge that is not in-
cluded in this list because it is so basic is the challenge of setting aims.
Deming used to say that without an aim, there is no system. A variation on
this saying with a more positive tone is, “Aim creates a system.” One of
the serious barriers to wedding engineering, sciences, and health care lies
outside these fields; it is the absence of aim. A country that cannot make a
clear decision that its health care will be safe, or efficient, or effective, or
patient centered, or timely, or equitable will not achieve those aims. This is
not a technical problem. It is a political problem, a problem of leadership.
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
Without aim there is no system, and without it all of our explorations of
systems thinking will be fruitless.
Beyond the need to set aims, at least seven challenges to the wedding
of medicine and systems knowledge can be identified. The first is the dif-
ficulty of getting people to emphasize interdependence in their thinking.
Romantic views of professionalism emphasize personal responsibility, hier-
archy, specialization, independence, and professional autonomy. Such views
are evident everywhere in health care. Take, for example, architecture. In
hospitals there are “doctors’ conference rooms” and “nurses’ conference
rooms” and even “patient bathrooms” and “staff bathrooms.” There are
discipline-specific spaces. The fragmentation is also evident in training:
schools are separate, and the experiences offered to young people to de-
velop their self-images are separate. Separateness, not interdependence, is
emphasized in the preparation of professionals.
The separateness is further evident in the framings of professional eth-
ics. Each discipline has its own statement of its ethics, and this statement is
nowhere unified with another. There is no common, shared description of
the ethical center of health care that applies to everybody, from a physician
to a radiology technician to a manager. Physicians have the Hippocratic
oath, nurses take pledges, and therapists take pledges, but they do not take
the same pledges together.
Fragmentation is evident in the lack of financial compensation for co-
ordinating mechanisms. It is a habit of payment systems to pay for interac-
tions but not for coordination, as evidenced by the institutional boundaries
that exist. I am engaged in a great debate right now in one of the commit-
tees on which I serve concerning whether hospitals’ mortality rates should
include deaths that occur beyond the hospital walls. Is it fair to characterize
a hospital mortality rate within 30 days of discharge? Hospitals are saying,
“No, we are not responsible for what happens once a patient has left our
building.” That attitude represents fragmentation and a failure to under-
stand, let alone embrace, interdependence.
Failure is evident in chronic care hand-offs, and it is embedded in
the language used. The word “discharge,” for example, is a peculiar one.
It implies that there is an “admission” and then a “discharge,” as if the
patient were a type of effluent. The word suggests the patient is no longer
a responsibility, and it is a symptom of a lack of sensitivity to interdepen-
dence. Proper systems in health care will place interdependence and its
management at the top of the hierarchy of professional concerns. That is
not the current culture.
The second challenge is the need to increase the isibility of care pro-
cesses, from the iewpoint of patients. Paul Batalden once said that health
care lacks catwalks. It is extremely difficult to see processes of care. It is not
easy to “hover” above the work, to see the workflow, because of the way
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
space and time are divided. When processes are seen, they are not always
seen accurately because they are seen from the supply side, not the patient
side. The work is described as it is performed, not as patients and their
loved ones experience it. The immediate effect is very toxic—patients are
expected to adjust to processes instead of having processes molded to their
needs, even at the level of the individual. This is a vicious cycle: the more
that patients are forced into processes that do not fit them as individuals,
the more their expectations will be construed as unreasonable and their
capacities seen as constrained.
Possibilities derive only from the redesign of processes, not from the
reinforcement of current processes. The first step is to make the processes
visible from the viewpoint of the people served. I have recently been study-
ing, to my enormous benefit, with Amory Lovins, founder of the Rocky
Mountain Institute and one of the world’s leading scholars in the fields of
energy and the environment. In 1976 Lovins proposed a focus on what he
called end use efficiency as the hallmark of proper energy design and policy.
A concern with end use efficiency is exactly what is needed in health care,
as opposed to centralized efficiency, which is not going to meet the needs
of patients.
Currently, there are few mechanisms for the coordination and commit-
ment necessary to make processes visible. Taichi Ohno, the creative genius
behind the Toyota Production System, offered an important observation.
He wrote, “When waste is at a minimum, every customer can be seen as an
individual.” Not being focused on process, the healthcare system operates
with exactly the opposite premise, assuming that trying to meet the needs
of the individual drives costs up. It does not. Rather, when done properly,
it drives costs down.
The third challenge is the need to recognize the importance of nonlin-
earities and the alue of dynamic learning and of local adaptation as scien-
tific learning progresses. The nonlinear nature of system dynamics in health
care, as in any nonlinear system, weakens the learning power of many for-
mal and classical methods of evaluation and inquiry. Some formal methods
of inquiry tend to be insensitive to contacts, mechanisms, and recurring and
meaningful stratification. Those methods also weaken the contribution of
local knowledge because they are trying to protect against bias.
Health care today lacks habits and norms of inquiry that capitalize
on processes and knowledge growth in a nonlinear context. That is actu-
ally the side effect of a major intellectual achievement in health care: the
establishment of a hierarchy of scientific evidence as a basis for evaluating
clinical practices. That hierarchy places RCTs at the top—where they surely
belong when considered relative to other forms of inquiry. However, RCTs
usually do not belong at the top of the hierarchy of learning processes when
nonlinear complex systems are involved. Most sound learning in complex
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
systems occurs in local and individual settings. Currently, there are no
powerful ways to harvest the knowledge accumulating through innovation
in local settings in health care.
There is a chasm between, on the one hand, pragmatic engineering sci-
ences (which are very sensitive to nonlinearities) and local learning and sys-
tem improvement methods and, on the other hand, the current hegemonic
hierarchies of evaluation of clinical procedures. Journals have not opened
their review processes and pages to the former kind of knowledge. The
RCT continues to be placed at the pinnacle of methodologies even in those
settings where it simply cannot provide the information needed. I recently
received an extremely discouraging e-mail from a very discouraged leader
of improvement, a quite senior physician at a major medical center, who
forwarded to me the instruction that he had received from his chief of medi-
cine ordering that “no further Plan-Do-Study-Act cycles will be permitted in
this department.” The chasm between formal trials and local improvement
is enormous, and the cost to knowledge growth is very high.
The fourth challenge has to do with attention to waste—knowledge
of and action on waste in health care. One early benefit of proper system
views is knowledge concerning waste, including the degree of waste and
its different forms. Waste is often the manifestation of system failure and
illiteracy. In the nonsystemic view, being mired in that waste can even feel
productive. What might otherwise be seen as waste feels like necessary ac-
tivity. One who attacks waste, even if the attempt is to avoid suboptimiza-
tion, can appear to be ill-motivated and sinister. For example, the following
can feel extremely risky and assaultive in a fragmented system: (1) using
someone else’s laboratory findings instead of repeating them, (2) eliminating
inventories that buffer against poor flow, (3) automating processes, and (4)
using capital fully. It is wasteful when the neurosurgery operating room is
never touched by the orthopods and when the orthopods never allow the
neurosurgeons to use their room. From the viewpoint of waste, this is poor
management of capital, yet many would regard such “ring fencing” as ab-
solutely necessary to achieving excellence in the current system.
The forms of waste in health care are just as vast as they are in other
industries: rework, scrap, inventory, queues, motion, unused space and
equipment, idle capital, excess information, records of no value, loss of
ideas, and, most of all, demotivating of the workforce through insult and
indignity. The economics of health care today are in some sense founded on
waste. Waste means jobs; it means profit; it means income; it means familiar
habit and comfort. Surely, waste levels exceed 30 percent in the healthcare
industry; that is 30 percent of the $2.6 trillion spent. In fact, waste may
exceed 60 percent, but that would be more difficult to prove. Indeed, if
formal value chain analysis were used, the figure might prove to be even
higher. Despite the opportunity, it should be noted that there is no formal
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8 ENGINEERING A LEARNING HEALTHCARE SYSTEM
research agenda in health care in the nation that is intended to discover and
identify waste in its myriad forms.
The fifth challenge is the missing platform for multidisciplinary re-
search and deelopment in the intersection of systems sciences and health
care. My career benefited enormously from leaders at Harvard—Howard
Hiatt the first among them—who built a platform for the intersection of
quantitative analysis methods and healthcare delivery. That platform was
the foundation of my own career. With Hiatt and others, I studied a vari-
ety of sciences not usually associated with health care, and that study was
made easier because there was a platform that linked one part of my brain,
performing quantitative analysis, to the other part of my brain, learning to
be a doctor. The intersections for the collaborative efforts being explored at
this workshop are insufficient. That is, the most valuable potential forms of
collaborative research and development among engineering sciences, system
sciences, and health care are not yet dignified.
Of interest, the barrier is dyadic. It is symptomatic of the history of the
distance between the fields that engineers feel unwelcome, unfamiliar, and
intimidated in the healthcare setting. They become silent, as all people tend
to do when they are awed in the cathedral of health care. Healthcare leaders
tend not to be aware of the engineering disciplines or to be suspicious of
their applicability. Although this wall is being broken down slowly, much
remains to be done. Bridge building here will be expensive and it will take
time, but it will pay off. The recent examples of, say, Steven Spears’ work
in health care or Eugene Litvak’s work are already paying off handsomely
in settings where the participants are wise enough to seek these experts’
counsel.
As the IOM and others forge these intersections (I love the idea of
a master of sciences and engineering degree in health systems), the days
when industrial engineers were very common in healthcare settings should
be remembered. Somehow that situation never grew into the truly fertile
interaction it might have become. The question of what stalled it should
be addressed. The idea of more physician-engineers is intriguing. There are
physician-information technologists, physician-bioscientists, and molecular
biologists who are physicians; now there need to be more engineers who
are physicians, people like Kate Sylvester, who is a leader of such syntheses
in the United Kingdom.
The sixth challenge has to do with the implications of systems thinking
for professional deelopment. Today there are no requirements for physi-
cians and nurses for training in safety science and safety practices. Medical
schools are just starting to incorporate these subjects into their curricu-
lums. No physician is emerging from training today who has not heard of
Osler or Watson and Crick or the Krebs Cycle, yet thousands of physicians
graduate every year who have never heard of James Reason or W. Edwards
Deming or Karl Weick—or even Robert Brooke or Jack Wennberg, who are
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ENGINEERING A LEARNING HEALTHCARE SYSTEM
right here within the field. Nor have most of the teachers heard of these lu-
minaries, which is probably the reason the students do not hear about them.
The preparation of professionals today dismisses systems sciences through
its silence. Moreover, the siloing of professional preparation itself deempha-
sizes the role of interdependency. I trained for 9 years in medicine before I
was a fully qualified physician. In that training, I spent not a single day of
study self-consciously with students of nursing, even though we would then
spend our professional lives together locked in interdependency.
The seventh challenge is the greatest in some sense: institutional rede-
sign, or the institutional rearrangements, will be needed if systems sciences
are to be fully exploited. If process literacy, process knowledge, and invest-
ment in process redesign were increased, the institutions created to preserve
the current fragments would become visibly inadequate, and the spaces
between them would appear larger and larger. The waste incurred through
fragmentation would be obvious. Systems knowledge inevitably leads to the
desire for integrated design. It is not at all clear that upon emerging from
that exploration, there would be a need for hospitals or offices or insurers
or professions in anything close to their current forms.
Some caution against this kind of grandiose thinking about redesign,
but it may be that the science would lead there, that system redesign—not
political or financing rearrangement—would be the true manifestation of
what should be called healthcare reform. It would be care reform, not
financing reform or insurance reform or coverage reform, and yet little,
if any, of that kind of change is being discussed in the current political
debate.
It is doubtful that the political or social will to go there yet exists. If it
did, the issues being faced in health care, such as financing, coverage, and
costs, would melt away, or at least begin to do so. Furthermore, hospitals
would look profoundly different. Indeed, a measure of whether health
care had become truly system-minded would be whether hospitals, at last,
would seek to be empty, not full. Instead, virtually every hospital board of
trustees is holding virtually every executive in virtually every hospital in
America accountable for making sure that occupancy levels are trending
up, not down. This tells us that “success” has been defined incorrectly from
the viewpoint of the true social need for health and gives some idea of the
level of institutional rearrangement that would be needed if a truly rational
system design were chosen.
The discussion encouraged by this workshop, about a merging of
engineering, sciences, and health care, does make sense. It makes a great
deal more sense than the status quo. Systems thinking and knowledge are
manifest already in many areas of human endeavor other than health care,
and someday they will be seen as too promising to continue to be ignored
by the healthcare enterprise.
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