2012. Vol.3, Special Issue, 807-810
Published Online October 2012 in SciRes (http://www.SciRP.org/journal/ce) http://dx.doi.org/10.4236/ce.2012.326120
Copyright © 2012 SciRes. 807
Computer Science: The Third Pillar of Medical Education
Frank Lau1, Lindsay Katona2, Joseph M. Rosen3, Charles Everett Koop4
1Department of Surgery, Brig ham & Women’s Hospital, Boston, USA
2Thayer School of Engineering, Dartmouth College, Hanover, USA
3Department of Surgery, Dartmouth-Hi tch coc k Medical Center, Lebanon, USA
4Geisel School of Medicine, Dartmouth College, Hanover, USA
Received August 31st, 2012; revi s ed S e p t e mber 28th, 2012; accepted October 12th, 2012
In 2001, the Institute of Medicine (IOM) and the National Academy of Sciences (NAS) attributed sub-
stantial problems in the quality of American medicine to four domains: growing complexity of science
and technology; the increase in chronic conditions; a poorly organized delivery system; and constraints on
exploiting the revolution in information technology (IT). Although all of these domains have been im-
proved by IT systems within the last decade, the U.S. health care systems has been slow to adopt these
developments. We propose one way to combat such quality problems by incorporating a medicine-spe-
cific computer science (CS) curriculum as the third of Abraham Flexner’s pillars of medical education.
Keywords: Information Technology; Computer Science; Medical Education
Meanwhile the requirements of medical education
have enormously increased. The fundamental sciences
upon which medicine depends have been greatly ex-
tended… The education of the medical practitioner
under these changed conditions makes entirely dif-
ferent demands in respect to both preliminary and
—Abraham Flexner (1910)
Flexner’s first pillar of medical education was clinical ex-
perience. His report catalyzed rapid, systemic change, allowing
experimental science to become the second pillar. The subse-
quent fusion of research and teaching—the academic medical
school—remains intact today.
Today, medicine is slow to incorporate two forces that have
altered nearly every aspect of our lives: computer science (CS)
and information technologies (IT). The result is an inability to
properly address many of the mounting challenges and expecta-
tions of modern medicine. For example, electronic medical
records (EMRs) are the modern standard, but Jha and col-
leagues (2011) found only 15% of hospitals used them as of
Many factors contribute to these delays. But fundamentally,
very few physicians have formal CS training. We are therefore
hamstrung in implementing IT solutions. We are unqualified to
participate in designing and developing transformative applica-
tions. We are poorly equipped to apply the intellectual rigor of
CS in research and clinical problem solving.
To overcome this problem, one solution is to incorporate a
formal, medicine-specific CS curriculum as the third pillar of
On the surface, our proposal may seem heavy-handed. After
all, an entire industry of IT professionals exists. And, the act of
programming might seem unrelated to patient care. But CS and
medicine revolve around the same core processes: the gathering,
storage, and interpretation of data. Moreover, clinical and re-
search data are increasingly digitized. By giving physicians the
intellectual tools to deeply shape and understand healthcare IT,
medicine-specific CS education will be a boon to our profes-
sion. A parallel shift has started in journalism, with Columbia
University announcing a dual-degree program in journalism
and computer science (2010).
History makes a powerful case for incorporating CS into
medical education. Four paradigms have governed the progress
of science (Bell, Hey, & Szalay, 2009). The first paradigm of
empirical science relied on observations and empirical data.
Next, we developed the second paradigm of theoretical science
(e.g. Newton’s laws). Flexner’s report led American medical
education to adopt these two paradigms, ultimately yielding our
present-day models of physiology and disease.
With the advent of computing, the third paradigm of simula-
tion (e.g. weather modeling) became possible. Today, in re-
sponse to the data explosion of the past decade, a fourth para-
digm of technologies for data-intensive science is rapidly
emerging. These two paradigms fulfill clear needs within medi-
cine. For example, physiology simulations offer the promise of
intervention or drug testing without costly, time-intensive, and
potentially dangerous clinical trials (E ddy & Schle ssinger, 2003).
Similarly, the mountains of digitized, clinical data coming out
of patient care settings make fourth paradigm tools a necessity.
By building the third pillar of medical education around these
third and fourth paradigms of science, we will generate benefits
in the key realms of Patient Care, Education, Service, Research,
Patient Care Benefits
A CS-proficient physician workforce would drive the adop-
tion of healthcare IT. Patient care would directly benefit. In
2001’s “Crossing the Quality Chasm: A New Health System for
the 21st Century,” the Institute of Medicine (IOM) and the
National Academy of Science s (NAS) found “a bundant evidence
that serious and extensive quality problems exist throughout
F. LAU ET AL.
American medicine resulting in harm to many Americans.”
This report highlighted 4 contributory domains: “growing com-
plexity of science and technology, the increase in chronic con-
ditions, a poorly organized delivery system, and constraints on
exploiting the revolution in information technology.”
All of these domains have been improved by information
technology (IT) systems (Dexter, Perkins, Maharry, Jones, &
McDonald, 2004; Kucher et al., 2005; Litzelman, Dittus, Miller,
& Tierney, 1993). These systems have been available for years.
Examples include EMRs, computerized order entry systems,
and electronic prescription systems. But adoption remains slow.
Barriers to adoption include initial cost, physician time re-
quirements, difficulties with technology, and inadequate sup-
port (Miller & Sim, 2004; Pizzi, Suh, Barone, & Nash, 2005).
Tellingly, several of these barriers stem from a lack of CS/IT
literacy. Physicians well-versed in computers would require
less training, experience less initial difficulty, and would re-
quire less IT support.
Eleven years have passed since the IOM/NAS’s report with-
out significant progress in applying IT to improve patient care.
The federal government is preparing to force the implementa-
tion of basic healthcare IT systems. Rather than be pushed
along, we should lead these efforts.
As a pillar of medical education, CS benefits medical stu-
dents and physicians in two discrete domains: critical thinking
and lifelong learning. The optimal time for this training is dur-
ing the preclinical years of medical school. This way ensures
that the CS courses are relevant to physician careers. This
would also set the stage for applying CS to lifelong learning, a
crucial task for phy sicians.
With regards to critical thinking, the learning process behind
programming is uniquely well-suited to medicine: good pro-
gramming has many parallels to good surgery. For example,
programs must be carefully designed in advance. Contingencies
must be planned for, vulnerabilities identified, and checks im-
plemented. When things go wrong and the program needs de-
bugging, the programmer must proceed step-wise through the
program, considering all possible conflicts, until the problem is
identified. Good surgeons use similar processes to plan, execute,
and problem-solve their surgeries. Unlike surgery, in CS these
processes are easily reproducible and do not require a patient.
In this sense, CS offers the opportunity to sharpen critical
thinking at an accelerated rate and in a safe setting.
By learning how to program, medical students will enhance
their lifelong learning because they can develop applications
specifically for physician learning needs. This should be part of
their CS training. For example, a medical student could write an
application to summarize key findings from the 80,000 clinical
trials that are conducted annually (ACRO, 2010). Such a pro-
gram would yield lifelong returns by keeping our knowledge
Alternatively, a student could create a program to address the
problem of knowledge attrition. We know that physicians for-
get a tremendous amount of knowledge, even when that
knowledge is clinically relevant. For example, Ali and col-
leagues (1996) found in a study involving practicing trauma
physicians that, 6 months after successfully completing an Ad-
vanced Trauma Life Support course, 50% failed a repeat test. A
knowledge management program could track our rate of knowl-
edge attrition and prompt us to review critical material before
we forget it.
Medical students could drive the development of digital
simulators. In the past 7 years, non-medical simulation has
advanced tremendously. Powerful graphics cards allow for
highly realistic situational gaming and mobile gaming is eve-
rywhere. Despite these gains, digital simulation plays a small
role in medical education.
We propose that medical schools develop simulator plat-
forms specifically for medical education. These platforms should
focus on effective learning (Issenberg, McGaghie, Petrusa, Lee
Gordon, & Scalese, 2005). They should allow clinical scenarios
to be presented with high-fidelity. Students should be required
to program their own simulations using these platforms.
Analogous to tradition of student presentations, the authoring of
simulations will help students delve into clinical entities. How-
ever, these simulations could be shared with other students,
yielding a comprehensive educational library.
Service, or the contract between the patient and the physician,
is the very heart of medicine. But a service gap now exists
(Grumbach, 1999; Moore & Showstack, 2003). IT solutions
have been shown to improve this gap, but most physicians re-
main reluctant to implement them. Because computing profi-
ciency correlates positively with healthcare IT adoption, CS-
trained physicians are better able to close the service gap
(Kaushal, Bates, & Jenter, 2009).
For example, the American Medical Association published
guidelines for clinical emails in 2001. As of 2006, Brooks and
Menachemi found only 16.6% of Florida physicians used email
to communicate with their patients. Security and legal concerns
are oft-cited barriers to the adoption of email communications.
Security concerns are no greater than those faced by the bank-
ing industry, which has safely launched online and mobile
banking platforms. Similarly, no lawsuits have ever been
brought for medical advice given via email.
Newer technologies such as text messaging have been shown
to improve patient compliance in the management of type 1
diabetes and liver transplants (Franklin, Waller, Pagliari, &
Greene, 2006; Miloh et al., 2009). Videoconferencing and tele-
medicine also promise to restore the doctor-patient relationship
while lowering overall costs. But until physicians attain a high
level of comfort with information technologies, we expect a
significant lag in using these tools to renew the patient-doctor
Research & Innovation Benefits
A CS-proficient physician workforce will reap benefits in
research and innovation. The recent explosion of data from
every sector of medicine is currently an untapped gold mine. As
clinical records become digitized, this volume of data will only
grow. From bioinformatics to clinical research, physicians who
possess the intellectual framework for manipulating and under-
standing this data will generate novel insights. For example,
when routine text-mining methods were applied to published
abstracts, three novel rheumatoid arthritis risk loci were identi-
fied (Raychaudhuri et al., 2009).
Physicians who understand CS will drive healthcare IT in-
novation. For example, we currently lack national standards for
Copyright © 2012 SciRes.
F. LAU ET AL.
EMR interoperability. Physicians should lead the development
of these standards, but we cannot do so without CS fluency.
Medical students should drive the development of learning
platforms. Motivated and trained physicians will finally push
medicine into the third and fourth paradigms of computer sci-
enc e , perhaps perfecting applicati ons like the Arc himede s model,
a full-scale simulation model of human physiology, diseases,
behaviors, interventions, and healthcare systems (Eddy & Schl-
In 2009, healthcare spending comprised 17.3% of the gross
domestic product (Truffer et al., 2010). This is projected to
grow to one third of national income by mid-century (Hagist &
Kotlikoff, 2006). A cornerstone of current governmental efforts
to combat the rising cost is EMRs. Girosi (2005) projects $80
billion per year of cost savings if effective EMRs are imple-
mented nationally. Given the current shortage of specialists
capable of supporting healthcare IT, the best strategy for driv-
ing this implementation is to broadly increase the number of
This physician workforce would also allow for the imple-
mentation of additional, technologically sophisticated health-
care IT solutions. Examples include Cybercare, a proposed
distributed network-based healthcare system that shifts the
focus back to preventive care (Koop et al., 2008). Other tech-
nologies such as telemedicine, remote monitoring, and robotics
for telesurgery/telemedicine can increase patient healthfulness,
access to care, and systemic efficiency.
Building the Third Pillar
Integrating CS into the medical school curriculum is a mas-
sive undertaking. But it is no larger than the integration of ex-
perimental science that took place a century ago and the bene-
fits make it equally worthwhile. The proper development of this
curriculum should be undertaken by a national committee. Each
medical school should be evaluated to identify what is working,
and more importantly, what is missing. Schools that do not
uphold minimum standards need to implement a plan for get-
ting up to speed. We believe medical students should, at a
minimum, learn one scripting language, develop one database-
driven application, and create an extension for another program.
To maximize the medical relevance, this training must take
place in medical school.
The proposed process would capitalize on two theories of
education, namely social learning theory and constructivism.
Social learning theory would be most valuable during the stu-
dents’ introduction to a scripting language. Instructors, perhaps
in a virtual form, could model programming techniques while
demonstrating their applications to medicine (Ormrod, 1999).
In accordance with constructivism, the students will build con-
fidence through mastery of a scripting language. When chal-
lenged to develop a database-driven application, they would
cement their role as active participants at the intersection of CS
and medicine. By creating an extension for another program,
they would be responsible for refining their skills in a way that
they deem relevant. This merger of theories would ideally be
accomplished within learning and digital simulation platforms
(Sharma, Xiem Hsieh, Hsieh, & Yoo, 2008). Considering the
potential to blend learning theories with emerging technology,
the construction of this third pillar of medicine presents a wor-
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