Biomedical Informatics
Synergies and Distinctions Between
Computational Disciplines in Biomedical
Research: Perspective From the Clinical and
Translational Science Award Programs
Elmer V. Bernstam, MD, MSE, William R. Hersh, MD, Stephen B. Johnson, PhD,
Christopher G. Chute, MD, DrPh, Hien Nguyen, MD, MAS, Ida Sim, MD, PhD,
Meredith Nahm, MS, Mark G. Weiner, MD, Perry Miller, MD, PhD,
Robert P. DiLaura, DBA, MBA, Marc Overcash, Harold P. Lehmann, MD, PhD,
David Eichmann, PhD, Brian D. Athey, PhD, Richard H. Scheuermann, PhD,
Nick Anderson, PhD, Justin Starren, MD, PhD, Paul A. Harris, PhD,
Jack W. Smith, MD, PhD, Ed Barbour, MS, Jonathan C. Silverstein, MD, MS,
David A. Krusch, MD, Rakesh Nagarajan, MD, PhD, and Michael J. Becich, MD, PhD,
on behalf of the CTSA Biomedical Informatics Key Function Committee
Abstract
Clinical and translational research
increasingly requires computation.
Projects may involve multiple
computationally oriented groups
including information technology (IT)
professionals, computer scientists, and
biomedical informaticians. However,
many biomedical researchers are not
aware of the distinctions among these
complementary groups, leading to
confusion, delays, and suboptimal
results. Although written from the
perspective of Clinical and Translational
Science Award (CTSA) programs within
academic medical centers, this article
addresses issues that extend beyond
clinical and translational research. The
authors describe the complementary but
distinct roles of operational IT, research
IT, computer science, and biomedical
informatics using a clinical data
warehouse as a running example. In
general, IT professionals focus on
technology. The authors distinguish
between two types of IT groups within
academic medical centers: central or
administrative IT (supporting the
administrative computing needs of
large organizations) and research IT
(supporting the computing needs of
researchers). Computer scientists focus
on general issues of computation such as
designing faster computers or more
efficient algorithms, rather than specific
applications. In contrast, informaticians are
concerned with data, information, and
knowledge. Biomedical informaticians
draw on a variety of tools, including but
not limited to computers, to solve
information problems in health care and
biomedicine. The paper concludes with
recommendations regarding administrative
structures that can help to maximize the
benefit of computation to biomedical
research within academic health centers.
Editor’s Note: A commentary on this article appears
on page 818.
(IT).1– 4 Managing, communicating, and
analyzing large quantities of data are
critical research functions. Thus, many
laboratories now host more computers
than human beings. However, working in
today’s biomedical research environment
requires more than simply placing a
computer on the researcher’s desktop or
even digitizing all of the data.
field of biomedical informatics that
combines quantitative disciplines, such as
computer science and statistics, with
social sciences, such as communications
and psychology, and application domains
like biology and clinical medicine.5
Increasingly, researchers spend less time in
their “wet labs” gathering data and more
time on computation. As a consequence,
more researchers find themselves working
in teams to harness the new technologies. . . .
Digital methodologies—not just digital
technology—are the hallmark of tomorrow’s
biomedicine.
—The Biomedical Information Science
and Technology Initiative (NIH, 1999)
B
iomedical research increasingly
depends on information technology
Please see the end of this article for information
about the authors.
Correspondence should be addressed to Dr.
Bernstam, School of Health Information Sciences,
The University of Texas Health Science Center at
Houston, 7000 Fannin Street, Suite 600, Houston,
TX 77030; e-mail: (Elmer.V.Bernstam@uth.tmc.edu).
964
Broadly speaking, biomedical research
faces two related but distinct sets of
computational challenges. The first
relates to IT, including its selection,
procurement, implementation,
maintenance, and user support. The
second concerns data, information, and
knowledge rather than technology.
Specifically, there is a growing
recognition of the challenges that arise
when biomedical information is digitized
and manipulated by computers. This has
led to the inherently interdisciplinary
Acad Med. 2009; 84:964–970.
Recognizing that biomedical informatics
is critical to its overall goals, the National
Institutes of Health (NIH) required
an informatics component within
each Clinical and Translational Science
Award (CTSA).6 Still, “in many circles
[biomedical] ‘informatics’ is coming
to mean ‘anything one does with a
computer.’”7 Both IT and informatics are
critical to modern biomedical research.
However, failure to appreciate the
differences between them can create
frustration for biomedical researchers
as well as for IT and informatics
professionals.8 More important,
confusion regarding the proper roles of
Academic Medicine, Vol. 84, No. 7 / July 2009
Biomedical Informatics
computationally oriented groups in
biomedical research can lead to delays in
productivity and even failure of projects
that rely on the inappropriate group for
critical tasks.
To address such confusion, we examine
the distinction between biomedical
informaticians, computer scientists, and
IT professionals as well as the synergies
that must be developed among these
computationally oriented groups within
academic health centers (AHCs). The
issues we address have implications for
students planning their careers (What
constitutes a career in informatics?),
researchers seeking collaborators and
applying for grants (Who should be my
collaborators?), principal investigators
managing research programs (Who do I
ask to do what?), and administrators and
funding agencies (Where do I allocate
scarce resources? What programs should I
build/enhance?). Although we intend this
article to be generally applicable, we write
from the viewpoint of the CTSA program
to clarify the role of biomedical
informatics cores and to inform the
transformation of clinical and
translational research expected from
the CTSA program.9
Process
This consensus statement represents the
combined effort of 24 CTSA grantee
institutions (2006 and 2007 grantees) as
well as the NIH. The writing committee
(E.V.B., J.W.S., and M.J.B.) drafted a
statement on behalf of the biomedical
informatics steering committee. A single
representative from each institution and
the NIH collected and synthesized
feedback on behalf of his or her
organization. Although all coauthors
agreed on the importance of the topic
and the need for clarification, we
recognize that no statement can address
all relevant issues, represent all points of
view, or satisfy all critics.
Background
Three distinct and complementary
computing groups collaborate with
biomedical researchers10: IT, computer
science, and biomedical informatics. We
further distinguish operational IT from
research IT support groups. Operational
IT groups focus on supporting generic
capabilities, such as desktop computers,
networks, and office software. On the
Academic Medicine, Vol. 84, No. 7 / July 2009
other hand, research IT supports the IT
needs of biomedical researchers. These
needs may include support of researchspecific hardware (e.g., computer that
controls a DNA sequencing machine)
and software (e.g., for microarray
data analysis). Thus, in contrast to
operational IT professionals, research IT
professionals may need to understand
specific biomedical research issues.
Although there is overlap among them,
we separately describe each of the
three groups’ roles and each group’s
relationship to the other groups. We use
the example of a clinical data warehouse
(CDW) to illustrate the contributions of
each group. A CDW is a shared database
that collects and integrates patient data
from a variety of sources. Unlike
electronic medical records, CDWs allow
queries about groups (e.g., average age of
patients with diabetes) rather than
individuals (e.g., John Smith’s age) and
are thus important clinical and
translational research resources.11
Operational IT support
Operational IT groups implement and
maintain e-mail and database servers,
networks, online storage, and backup
systems; support personal computers;
and ensure IT security and compliance
with institutional policies. IT support
professionals may have vocational (“on
the job”) training, certification in specific
technologies (e.g., Microsoft Certified
Professional12), or a formal degree in
computer science, management
information systems, or another field.
Some may consider IT and computer
science to be part of the same continuum.
Thus, IT represents applied computer
science. However, it is important to note
that in contrast to academic (PhD-level)
computer scientists, IT professionals are
not required to have training in the
conduct of science. Further, there is a
fundamental distinction between IT
(application of IT) and computer science
(research focused on computing).
In contrast to informaticians, IT
professionals are not required to have
training in core informatics areas, such
as decision support, knowledge
representation, or human– computer
interaction.
We cannot overemphasize the
importance of effective and efficient IT
operations. E-mail is one important
example. Investigators use e-mail to share
ideas, working documents, and data
sets. Similarly, identity management,
networking, server management, and
backup operations are fundamental to
any modern complex industry and are
essential to biomedical research.
A CDW generally resides on a centralized
server, but users access the CDW with
personal computers, perhaps via a Web
interface. IT support professionals are
responsible for selecting, purchasing,
maintaining, and supporting these
personal computers and the
infrastructure on which a CDW is built.
This infrastructure includes the server(s)
on which the CDW runs, security,
backup, and disaster recovery systems,
and the networks connecting the CDW
to its data sources, such as clinical,
laboratory, and radiology systems.
Research IT
Research IT and operational IT face
different demands from different user
communities. Some institutions have a
central research IT group for common
research needs (e.g., high-capacity storage
with backup). However, compared with
operational IT teams, research IT groups
are typically “local” to departments or
laboratories and support users who
collect data via specialized equipment or
analyze complex data sets via a variety of
special-purpose software packages that
change frequently depending on specific
researcher needs or preferences.1 For
example, researchers may write custom
software to analyze microarray data or
modify existing software to meet their
needs. Thus, each workstation may be
unique, and their configurations may
change frequently.
If a problem arises, the IT professional
cannot simply reinstall the system from
generic backup images. As a result,
research IT must be able to tolerate
changes and disruptions that would cause
havoc in a large operational IT group
responsible for mission-critical
applications. Further, increasing
regulation of biomedical research has
numerous implications for information
management (e.g., requirements for
HIPAA-compliant storage of protected
health information). Thus, research IT
professionals must be familiar with
research-specific processes and
regulations.13,14 In contrast, operational
IT is often centralized within institutions
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Biomedical Informatics
and is accustomed to handling large-scale
projects that serve many individuals.3
Researchers may be computationally and/
or scientifically sophisticated but still
require help with advanced functions or
with unusual tasks. Compared with
administrative computing, the hardware
and software needs for research,
especially when it involves very large data
sets or computations, are also far greater.
As a result, research IT groups must allow
users greater autonomy and must
manage a more heterogeneous hardware/
software environment. Different skills
may be required for research IT, and
therefore a division of a given AHC’s
overall IT organization into “research IT”
and “operational IT” may be warranted.
Research IT budgets should reflect the
greater resource requirements per
client compared with operational IT.
Increasingly, researchers recognize that
IT should be included on grant budgets
because research IT is rarely fully
supported by the AHC. There are
multiple options for funding research IT
including charging “user fees” of funded
projects or “taxing” laboratories a flat fee.
The most appropriate option depends
on the institution, but it is important
to recognize that research IT requires
dedicated and highly skilled resources.
IT support is becoming even more
important as research data migrate from
personal computers to institutional
servers. Operational IT groups are well
equipped to provide user support for
general-purpose office automation tools
and to ensure smooth operation of data
centers that house servers. In contrast,
research IT groups can support
specialized laboratory software, highperformance computing (e.g., Linux
clusters), and workstations increasingly
used by clinical and translational scientists.
As biomedical research becomes more
data-intensive, traditional data storage
and analysis approaches fail.1 For
example, large-scale efforts within
CTSA programs such as CDWs must
accommodate terabytes to petabytes
of data on thousands of subjects (1
petabyte ⫽ 1,000 terabytes ⫽ 1015 bytes).
General-purpose office automation tools,
such as Microsoft Excel, were not
designed to handle such large data sets.
Instead, centralized computing resources
ranging from servers, to networked
“Grid” clusters, to shared-access
966
supercomputers running specialized
software, are needed to extract useful
knowledge from such huge data sets.
informatics perspective, however, one
should choose the optimal tool for the
information task— often, but not always,
this tool is computer based.
Computer science
As computers become increasingly
important in biomedicine, biomedical
researchers are starting to collaborate
with computer scientists. Like IT
professionals, computer scientists
concentrate on technology, including
computing systems composed of
hardware and software as well as the
algorithms implemented in such systems.
In contrast to both operational and
research IT, academic (PhD-level)
computer scientists are trained as
researchers. They may work in academia
or industry, but they are expected to
generate new computer science
knowledge. Some, but not all, computer
science activities advance IT. For example,
computer scientists develop algorithms to
search or sort data more efficiently and
design faster memory or storage architectures
and more reliable computer software that is
less prone to “crash.”
Though often motivated by specific
applications, computer scientists typically
develop general-purpose approaches to
classes of problems (a characteristic
shared with academic biomedical
informaticians, as discussed below). For
example, a computer scientist may design
a memory architecture that works well
for storage and retrieval of large data sets
in a CDW. The computer science
contribution is the development of a
better memory architecture for large data
sets; although the memory architecture is
not a direct improvement of the CDW
per se, it is nonetheless critical to its
advancement.
Biomedical informatics research and
service
Biomedical informaticians focus on the
storage, retrieval, and optimum use of
data, information, and knowledge for
problem solving and decision making in
biomedicine.15 To an informatician,
computers are tools for manipulating
information. Indeed, there are many
other useful information tools, such
as pen, paper, and reminder cards.
There are significant advantages to
manipulating digitized data, including
the ability to display the same data in a
variety of ways and to communicate
with remote collaborators. From an
Similar to the distinction between
computer science (an academic discipline
that generates new knowledge) and IT
(an applied or engineering discipline that
uses computer science to solve real-world
problems), there is a continuum from
academic to applied informatics (Table
1). Like other researchers, academic
informaticians and students pursuing
PhD degrees in informatics are expected
to ask scientific questions, obtain
research funding, assess and identify the
generalizability of results, and publish in
the scientific literature. In contrast,
applied informaticians employ or adapt
existing tools. Applied informaticians
may work in industry or in academia.
They are especially indispensable to
organizations wishing to implement large
enterprise-wide applications, such as
electronic health records.16
Academic and applied informaticians
come from a wide variety of
backgrounds, including computer
science, biology, and/or clinical
disciplines. Because biomedical
informatics requires interdisciplinary
expertise, most informaticians have
graduate or postdoctoral training,
increasingly in biomedical informatics
itself. Informaticians should be computer
savvy, but, unlike IT professionals,
informaticians are not explicitly trained
in specific hardware or software and,
therefore, are not well suited to provide
researchers with operational IT support.
In contrast to computer scientists,
informaticians are concerned with
application domains, such as biology
(bioinformatics), clinical care (clinical
informatics), research processes (research
informatics), or public health (public
health informatics), although the new
methods motivated by those domains
may have applicability much more
broadly— even outside biomedicine.
There are currently 20 biomedical
informatics training programs funded by
the National Library of Medicine (NLM,
the NIH component traditionally
involved in fundamental informatics
research).17 In addition, there are nonNLM-funded programs and competent
informaticians without formal training.
The American Medical Informatics
Academic Medicine, Vol. 84, No. 7 / July 2009
Biomedical Informatics
Table 1
Examples of Topics and Tasks Addressed by Operational Information Technology
(IT), Research IT, Computer Science, and Biomedical Informatics as Identified by
the Clinical and Translational Science Awards Biomedical Informatics Writing
Group
Discipline
Operations/application (production or support)
Research (generating new knowledge)
IT (focused on
computation and
technology)
IT support
Supporting non-research-specific software and
infrastructure
• Setting up and maintaining e-mail servers
• Helping users with MS Office software
• Maintaining networks including developing and
implementing a security plan
Research IT
Supporting research-specific software and infrastructure
• Setting up research databases
• Installing and supporting existing research-specific
software (e.g., BLAST server)
• Maintaining high-performance computers (e.g.,
supercomputers)
Computer science
• Designing new high-performance computing architectures
and algorithms (parallel computing, supercomputing)
• Designing software and hardware systems to support
very large databases (⬎⬎⬎terabyte datasets)
• Designing new high-performance network
architectures
Information and knowledge management using known
tools/techniques to support research and clinical care
• Understanding the needs of users (e.g., clinicians and/
or researchers)
• Working with researchers to design data warehouses
according to known principles
• Designing interoperable systems using known
standards (e.g., SNOMED); includes participating in
standards development
Developing new ways of managing information and
knowledge
• Developing new ways of managing ontologies
• Developing new ways of integrating information
technology into the clinical (or biomedical research)
workflow
• Designing new algorithms to analyze biological data
(e.g., new algorithms to align DNA sequence)
...................................................................................................................................................................................................................................................................................................................
Informatics (focused on
information and
knowledge management)
Association (AMIA) currently has more
than 3,800 members.18 Recognizing the
need to develop an informatics workforce
rapidly, AMIA launched the “10 ⫻ 10”
program that aims to train 10,000 people
in applied informatics by 2010.19
The necessary and sufficient competencies
for a trained biomedical informatician
remain controversial.5 For example, should
informaticians be able to write computer
programs? Some argue that informaticians
must have programming experience to
effectively supervise software development.
Others counter that the task of supervising
programmers does not necessarily require
programming experience and that precious
training time should be spent on other
topics. Similarly, the depth to which
individual topics are covered differs
between programs. Some emphasize
cognitive or human factors; others
emphasize technology or other quantitative
disciplines. Most informatics training
programs require some exposure to both
quantitative sciences (e.g., computer
science, decision science, and statistics)
and application domains. In addition,
informaticians are trained in core
informatics methods, including concept
and knowledge representation.
Returning to our example of a CDW,
informaticians can help determine how to
Academic Medicine, Vol. 84, No. 7 / July 2009
represent the information to be stored. For
example, selecting and properly applying
a standard terminology such as the
Systematized Nomenclature of Medicine
(SNOMED)20 can facilitate interoperability
with other systems. If we represent data in
two different systems using SNOMED
codes, such as “D2-0007F (Pneumonia),”
then we can issue a query for all patients
with pneumonia the same way for both
systems and meaningfully aggregate results.
However, there are multiple alternatives,
and choosing the best terminology is not
always straightforward. Whereas an applied
informatician can make the best choice
among existing terminology systems, the
research informatician has the skills to
design new and better terminology systems.
For example, research informaticians
developed the structure and maintenance
procedures for SNOMED. Applied
informaticians know how to apply
SNOMED to clinical data. In contrast,
neither IT professionals nor computer
scientists are trained to develop or apply
terminologies to clinical and research data.
Increasing use of informatics in
biomedical research
We are now able to more robustly
represent complex biomedical concepts,
such as eligibility requirements for
clinical trials and clinical syndromes
(e.g., congestive heart failure).21 Thus,
informatics is beginning to deliver on
its potential, and informaticians are
increasingly useful to biomedical
researchers. Examples of informatics
successes important to biomedical
researchers include the MEDLINE
database of biomedical literature created
and maintained by the NLM but available
via multiple interfaces (e.g., Ovid,
PubMed), large biological databases such
as Genbank, which contains an annotated
collection of all publicly available genetic
sequences,22 as well as tools to access
biological databases (e.g., BLAST),23 and
contributions to the Human Genome
Project.4 Similarly, clinicians have
benefited from MEDLINE and from a
variety of informatics innovations such as
electronic health records and order-entry
systems.
Biomedical researchers may look to an
applied (bio)informatician, but probably
not an IT professional, to help them
access genetic databases using existing
tools, such as BLAST. However, much
research remains to be done to realize the
full potential of informatics in clinical
and translational research. Therefore, in
addition to supporting biomedical
researchers, academic informaticians
should collaborate with traditional
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Biomedical Informatics
biomedical researchers and conduct
independent research focused
on informatics. Research challenges in
informatics include formulating models
for acquisition, representation,
processing, display, and transmission of
biomedical information (e.g., into a
CDW), developing innovative systems
based on these models that deliver
information to users, implementing such
systems within established organizations,
and studying their effects on research and
health care.24
Discussion
Relationships among IT, computer
science, and biomedical informatics
As the CDW example illustrates, multiple
complementary computational
disciplines are necessary for clinical and
translational research.
Table 1 contrasts the focus and scope of
IT, computer science, and biomedical
informatics. Meaningful but relatively
distinct scientific research can be
conducted in computer science and in
biomedical informatics, and both can be
useful to biomedical researchers. For
example, management of very large
databases (⬎⬎petabyte size) is currently
very challenging. Database methods
and high-performance computing
(“supercomputing”) research are wellestablished areas of computer science.
Therefore, “IT research” (i.e., research to
advance IT, not support for biomedical
research) often falls within the domains
of computer science, management
information systems, and operations
research, not informatics. Research into
knowledge representation for biomedical
concepts, however, is clearly within the
scope of biomedical informatics.
Implications for AHCs
Because both IT support and informatics
are required to conduct biomedical
research, both should be reflected in the
administrative or academic structure of
AHCs. Specifically, a chief information
officer (CIO) should lead the IT
organization with appropriate emphasis on
research and operational IT, preferably as
separate subunits.
CIOs at non-AHCs have the ability to
focus solely on the operational and
clinical mission of the organization.
Success in this setting can be measured in
server and network up-time and in the
968
responsiveness of the IT infrastructure.
The additional priority of AHCs to
advance the science of medicine and
support education25 requires leadership
that is knowledgeable of the special IT
requirements of the biomedical research
community and that is appropriately
incentivized to be responsive to research
needs. The CIO should have an
independently negotiated budget with
dedicated staff and should advise senior
administration on the strategic use of
information systems.
Close cooperation between operational
IT, research IT, and biomedical informatics
is critical. Neither IT nor informatics alone
can support the increasingly complex
computing needs of biomedical research.
Without IT, there is no infrastructure.
Without informaticians, poorly specified
or even harmful computer systems can
be installed.26 These groups must
collaborate closely to avoid expensive
investments in redundant or
incompatible systems. Although recent
surveys did not differentiate between
informatics and IT, they showed that
AHCs were not investing sufficient
resources into IT, especially IT
support for research activities.1,3,8,27
Consequently, requests for IT support
(e.g., server setup and configuration in an
IT-controlled data center) are often
directed to informaticians who are
neither funded nor (necessarily) qualified
to satisfy these requests. Such requests
rarely go to computer science faculty
in general university settings,
perhaps because, unlike biomedical
informaticians, they reside outside
hospitals or medical schools. For
example, computer science departments
rarely operate university computing
centers or network infrastructures.
Informatics units with a designated
leader are required to provide a
professional and/or academic home for
informaticians, just as distinct units are
required for other investigators and
practitioners within AHCs (e.g.,
statisticians, oncologists, pathologists).
Multiple models have been successful,
ranging from sections within a clinical
department (e.g., Stanford University), to
departments within a medical school
(e.g., University of Pittsburgh, Columbia
University, Vanderbilt, Oregon Health
& Science University), to institutes
or schools (e.g., University of Texas
Health Science Center at Houston).
Regardless of the informatics unit type,
the leader should be a credible role model
who understands technology well enough
to provide strategic leadership and vision
for the institution. The leader should be
empowered and held accountable by the
institution to represent the unique needs
and abilities of informatics within the
larger organization.
Faculty informaticians must be supported
with respect to promotion and tenure.
They should be encouraged to lead
independent research programs and to
support traditional biomedical research.
Informatics has its own culture that
reflects connections to multiple fields
including biomedicine as well as
computer and information sciences.
Grants and publications are recognized
metrics of scientific success, but the
specifics vary across disciplines. For
example, conference proceedings are
relatively undervalued in biomedicine,
but they may be very competitive in
computer science or informatics (e.g.,
⬍10% acceptance rate, comparable with
competitive clinical journals). The
informatician with publications in
competitive conference proceedings
should not be penalized when it comes
time to review his or her scholarly record
for promotion and tenure.
Successful informatics research programs
interact with other academic disciplines,
such as computer and/or information
sciences. Indeed, it is difficult to find an
NLM-funded informatics program
without access to other appropriate
academic units. A distinct informatics
unit with a strong leader can facilitate
such collaborative interactions, even
across schools within a university, and
occasionally among multiple universities.
For example, the CTSA program is
an example of such collaboration.
Informatics component leaders interact
with computer scientists, biostatisticians,
biomedical researchers, and others as
they strive to transform clinical and
translational research within their
institutions and across the nation.
Informaticians who are not in academic
faculty positions, either because they
play an operational role or work in a
nonacademic institution, must also
be supported. As in any profession,
there should be commonly accepted
competencies, a society that supports
both academics and professionals (such
Academic Medicine, Vol. 84, No. 7 / July 2009
Biomedical Informatics
as AMIA), and a means for professional
growth and advancement.28
In addition, informatics units educate the
next generation of informaticians and
teach informatics skills to biomedical
researchers and clinicians. The CTSA
informatics national steering committee
formed a project group on education to
address the informatics training needs of
researchers. Similarly, some professional
schools and societies encourage or even
require their students or members
to demonstrate informatics
competencies.29 –32 For example, the
Association of American Medical
Colleges Medical Student Objectives
Project lists “the ability to retrieve (from
electronic databases and other resources),
manage, and utilize biomedical
information for solving problems and
making decisions that are relevant to the
care of individuals and populations” as
a core competency.33 Similarly, the
American Association of Colleges
of Nursing requires informatics
competencies such as knowledge of
standards relevant to health information
systems of doctor of nursing practice
graduates.34
We emphasize that IT and informatics
are distinct, but both are necessary for a
robust clinical and translational research
effort, and they must coexist within
AHCs.8 Biomedical researchers have
domain-specific computational needs
(e.g., create and maintain a cardiology
outcomes database). Thus, it may be
practical for a large research unit to have
a formal or informal subunit with
domain-specific informatics expertise
(e.g., experience managing cardiology
data). This unit would interact with
domain-independent biomedical
informaticians that would focus on core
informatics methods, such as decision
analysis or machine learning. Regardless
of the model adopted, a single point of
contact for computing needs can help
ensure that biomedical researchers are
aware of available computational
resources.8
Conclusions
Biomedical informatics is increasingly
visible within the larger research
community. AHCs should develop and
maintain IT units, headed by a CIO
reporting to central administration, as
well as distinct biomedical informatics
Academic Medicine, Vol. 84, No. 7 / July 2009
units with capable leaders. In addition to
collaborative support for traditional
biomedical research efforts, informatics
units should develop faculty with
independent research agendas that
address the informatics challenges of
modern biomedical research. Within
CTSAs, informatics components
complement, but do not replace, IT
organizations.
Dr. Smith is professor and dean, School of Health
Information Sciences, University of Texas Health
Science Center at Houston, Houston, Texas.
Dr. Bernstam is associate professor of health
information sciences and internal medicine,
University of Texas Health Science Center at
Houston, Houston, Texas.
Dr. Nagarajan is assistant professor of clinical
pathology, Washington University School of
Medicine, St. Louis, Missouri.
Dr. Hersh is professor and chair, Department of
Medical Informatics & Clinical Epidemiology, Oregon
Health & Science University, Portland, Oregon.
Dr. Johnson is associate professor of biomedical
informatics, Columbia University, New York, New
York.
Dr. Chute is chair, Division of Biomedical
Informatics, Department of Health Sciences
Research, Mayo Clinic, Rochester, Minnesota.
Dr. Nguyen is assistant professor of infectious
diseases, Department of Internal Medicine, University
of California, Davis, Davis, California.
Mr. Barbour is a manager, Hospital Informatics
Core, Rockefeller University, New York, New York.
Dr. Silverstein is associate professor of surgery
and radiology, Computation Institute, University of
Chicago, Chicago, Illinois.
Dr. Krusch is associate professor of medical
informatics, University of Rochester School of
Medicine and Dentistry, Rochester, New York.
Dr. Becich is professor and chair, Department of
Biomedical Informatics, University of Pittsburgh
Medical School, Pittsburgh, Pennsylvania.
Acknowledgments
The authors are indebted to Drs. Curtis Cole
(Weill Medical College of Cornell University)
and Milton Corn (National Library of Medicine)
for their support and guidance.
Mr. Overcash is chief information officer and
director of health sciences and research, Emory
University, Atlanta, Georgia.
Supported by the CTSA consortium including
National Center for Research Resources grants
1UL1RR024148 (UT Houston), 1UL1RR024146
(UC Davis), 1UL1RR024975 (Vanderbilt),
1UL1RR024128 (Duke), 1UL1RR024986
(University of Michigan), 1UL1RR024143
(Rockefeller), 1UL1RR024989 (Case Western
Reserve University/Cleveland Clinic),
1UL1RR025014 (University of Washington),
1UL1RR025011 (University of Wisconsin–
Madison), 1UL1RR024134 (University of
Pennsylvania), 1UL1RR025005 (Johns Hopkins),
1UL1RR024156 (Columbia), 1UL1RR024160
(University of Rochester), 1UL1RR024979 (University
of Iowa), 1UL1RR024996 (Cornell), 1UL1RR024131
(UC–San Francisco), 1UL1RR024140 (Oregon Health
& Science University), 1UL1RR024982
(UT–Southwestern), 1UL1RR024992 (Washington
University), 1UL1RR024153 (University of
Pittsburgh), 1UL1RR024150 (Mayo), 1UL1RR024139
(Yale), 1UL1RR024999 (University of Chicago), and
1UL1RR025008 (Emory).
Dr. Lehmann is associate professor of health
sciences informatics, Johns Hopkins University,
Baltimore, Maryland.
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Dr. Sim is associate professor of general internal
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Ms. Nahm is associate director, Biomedical Clinical
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Dr. Weiner is associate professor of medicine,
University of Pennsylvania, Philadelphia,
Pennsylvania.
Dr. Miller is professor, Center for Medical
Informatics, Yale University School of Medicine, New
Haven, Connecticut.
Dr. DiLaura is head, Section of Research
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Dr. Eichmann is associate professor of library and
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Dr. Athey is professor of psychiatry, University of
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Dr. Starren is director, Biomedical Informatics
Research Center, Marshfield Clinic, Marshfield,
Wisconsin.
Dr. Harris is research associate professor of
biomedical informatics and biomedical engineering,
Vanderbilt University, Nashville, Tennessee.
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Academic Medicine, Vol. 84, No. 7 / July 2009