Sam
Hawgood, MBBS, dean of the UCSF School of Medicine, right; with Clay
Johnston, MD, PhD, director of the UCSF Clinical and Translational
Science Institute, center; and Joseph DeRisi, PhD, co-chair of the UCSF
Department of Biochemistry and Biophysics, at the UCSF School of
Medicine leadership retreat on Jan. 20.
In the world of bioinformatics, the rush is on to extract gold from a data mine.
The
amount of data that health care providers and scientists collect from
patients and research participants is growing explosively. This
information ranges from the genetic to laboratory tests and imaging
exams, to medical histories and information about treatment and outcomes
— and in some cases to survey data on large populations.
This
deluge of data and the bioinformatics capabilities necessary to take
advantage of it were the focus of this year’s daylong UCSF School of
Medicine leadership retreat on January 20. In his welcome address, Dean Sam Hawgood,
MBBS, outlined his goal for the day — to engage campus leaders in the
question of how to optimally develop, organize and integrate
clinical-outcome data, research data, business intelligence, and
population data so that information is accessible and usable to empower
research and improve medical practice.
Making Greater Use of Available Data to Improve Care
Some
have compared efforts to take advantage of the data to trying to drink
from a fire hose. Consider DNA as an example. Our genetic variations
contain clues to disease risk, disease prognosis and treatment response.
The identification of such clues by scientists and their translation
into medical practice is a major enterprise. Soon, expense will no
longer be a major limitation to obtaining a readout of an individual’s
entire genetic makeup. “A complete human genome assay will be an assay
like any other, at least in terms of cost and time,” Hawgood said.
However,
as vivid as the water hose analogy may be, it might be more apt to say
that in many organizations data of many types dwells in various
unconnected dammed reservoirs, with little of it flowing to potential
users.
Much of the day’s discussions centered not only on
identifying data to collect and on ways to use this data, but also on
how best to “unlock the data” that already exists.
In introducing
the day’s theme, Hawgood said that in his view, UCSF, despite the depth
and range of clinical and research data being collected, must develop
ways to make much greater use of available data in the day-to-day
workflow to improve research and patient care.
UCSF’s leaders in
informatics can learn from what others have already done. “We want to
take enough time to make sure that we’re not repeating other people’s
mistakes,” Hawgood said.
Already this year UCSF is completing
implementation of a new electronic medical records system, called APeX,
tailored to UCSF by EPIC Systems Corporation of Madison, Wisconsin. The
system features a single, comprehensive record for each patient.
Apart
from being a boon to physicians and other care providers, information
within the new clinical record can be “de-identified” to protect privacy
and then made available to researchers.
The experience gained
from the implementation and the system itself may be a good jumping off
point for using data to advance research and education. But the true
potential of APeX as a platform to support collaborative research is
still being investigated. Taking full advantage of UCSF medical records
for research — and enabling ways for new research findings to be used to
better guide patient care — will require new innovations.
UCSF
already has convened a task force, soliciting input from an external
team of international leaders in the field, to explore strategies to
bolster bioinformatics on campus, including the establishment of new
academic programs and infrastructure through which computer sciences
faculty and other bioinformatics experts could be recruited, new experts
trained, and novel research collaborations launched. In addition,
Hawgood noted, thanks to UCSF’s proximity to Silicon Valley, “We are in a
spectacular region for partnerships.”
UCSF is exploring how to
accomplish its bioinformatics goals within UCSF and its affiliates, as
well as ways in which to access and use data in research networks that
span institutions. In addition, there is a need to share information
with other providers to provide the best care to patients who also
obtain health care outside of UCSF, a theme discussed at last year’s
School of Medicine retreat as well.
Using Hospital Systems as Living Laboratories
In
his keynote address at this year’s retreat, “Aligning the Academic
Health Care Enterprise for Acceleration of Precision Medicine,” Isaac
Kohane, MD, PhD, a renowned bioinformatics expert and a professor of
pediatrics and health sciences and technology at Harvard Medical School,
said that the expense of working with data from clinical records has
historically been much more expensive than working with genetic and
molecular laboratory data.
Isaac
Kohane, MD, PhD, a leading innovator in bioinformatics and computer
systems from Harvard Medical School, gave the keynote address at the
School of Medicine retreat on Jan. 20.
Kohane, who
co-directs the Harvard Medical School Center for Biomedical Informatics,
has led efforts to develop computer systems to allow cheaper use of
clinical records data from multiple hospital data systems in the study
of genes and disease, while maintaining privacy.
Kohane talked
about the potential for “apps” to capture useful information related to
health outside of the hospital or clinic — for instance a tool that
tallies nutritional information on purchases from the cash register.
In
his own research Kohane now combines clinical and genomic data to learn
more about cancer and autism, but he also presented research showing
that such systems — had they been in place earlier — could have called
attention to serious side effects of Vioxx and other drugs much sooner.
Kohane’s
described workflows and systems that can better “unlock” clinical data
to speed research discovery and its application in medical practice,
while lowering the costs of using clinical data.
Imagining UCSF’s Future in the Digital Age
Speakers
at a morning panel titled “Imagining UCSF’s Future in the Age of
Information Technology,” included Opinder Bawa, chief technology officer
for the School of Medicine; Michael Blum, MD, medical director of information technology for the UCSF Medical Center; Catherine Lucey, MD, vice dean for education; Joe DeRisi, PhD, co-chair of the Department of Biochemistry and Biophysics; and moderator Clay Johnston, MD, PhD, director of the Clinical and Translational Science Institute at UCSF and vice chancellor for research.
Not
all bioinformatics applications are orchestrated institution-wide from
the top down. Panelists and commenters from the audience highlighted a
role for applications developed by smaller groups. For instance, as an
educational tool, UCSF faculty from the Department of Emergency Medicine
have spearheaded implementation of software used by
physicians-in-training to respond to simulated clinical scenarios
unfolding in real time.
The data collected during these exercises
can be used to better understand how long it is likely to take for
emergency room physicians to take critical actions — in the management
of chest pain or in the ordering of pain medication, for example. In
essence, the data can be used to learn more about how we learn,
knowledge that can be incorporated into successive generations of
teaching tools.
In the coming years, physicians will be trained to
become increasingly comfortable using improved, data-driven,
decision-making software tools, according to Lucey. “We will be able to
teach students how to learn for themselves for 30 to 40 years, and we
will free faculty up to teach in person what needs to be taught in
person.”
DeRisi described how information on UCSF graduate school
applicants is being used to identify factors associated with future
success. In addition, he described how extensive data collection is
being used to log graduate students’ progress and decision-making
throughout their careers — another way of identifying early career
paths that bode well for future success. DeRisi also talked about an
information-technology partnership that allows lab notebook entries made
on pad devices to be immediately incorporated into a computerized
database.
Developing More Innovative Research, Clinical Protocols
An afternoon panel — “The Future Is Now” — moderated by Robert Hiatt,
MD, PhD, co-chair of the Department of Epidemiology and Biostatistics
and deputy director of the UCSF Helen Diller Family Comprehensive Cancer
Center, focused on two large-scale collaborative research programs
co-led by UCSF researchers in which molecular, clinical and demographic
data already are being put to work to develop more innovative research
and clinical protocols.
Vice
Chancellor for Research Keith Yamamoto, PhD, executive vice dean for
the UCSF School of Medicine, comments on the future of bioinformatics at
UCSF.
Laura van’t Veer, PhD, leader, and Laura Esserman,
MD, co-leader of the cancer center’s breast oncology program, described
the ATHENA Breast Health Project, which unites UC academic medical
centers in a state-wide collaboration. The project will initially
involve 150,000 women throughout California who will be screened for
breast cancer and followed for decades.
ATHENA project leaders aim
to create common systems to integrate clinical research and care across
the UC campuses to advance the science of prevention, screening,
diagnosis, and treatment of breast cancer. The collaborators are
creating a biospecimen repository that has broad racial and ethnic
representation. A major goal is to marshal molecular and clinical data
to better personalize breast care, tailoring treatment to the patient
and avoiding overtreatment, and to use the information gained to drive
innovation in prevention, diagnosis and treatment.
Neil Risch,
PhD, co-chair of the Department of Epidemiology and Biostatistics at
UCSF and director of the UCSF Institute for Human Genetics, along with
Catherine Schaefer, PhD, director of the Kaiser Permanente Research
Program on Genes Environment and Health, described progress to date in
building the largest data base of its kind to focus on genetic variation
and environmental exposures in an older population.
The average
age of the hundreds of thousands of individuals whose genetic
information will be genotyped for the project is 65. The project’s
foundation is Kaiser’s electronic health record, which for many Kaiser
Permanente members has information spanning decades — including
information on clinical diagnosis and treatment as well as lab-test
results and prescription information. UCSF expertise has allowed
extraordinarily fast genotyping, as well as uniquely large-scale
analysis of telomeres to quickly grow the molecular component of the
data resource.
The afternoon panel provided a useful point of
reference for break-out groups that met afterward, charged with
identifying institutional priorities, problems and potential solutions
in advancing the use of bioinformatics in research, clinical care and
education.
For instance, the ATHENA collaborators have
standardized protocols used at the different medical centers, including
protocols for mammography screening. To make clinical data more useful
for research, some breakout session panelists advocated more extensive
standardization of clinical imaging and clinical lab protocols and
reporting throughout UCSF clinical practices.
The Kaiser-UCSF
collaboration highlights ways to combine strengths across organizations.
While Kaiser is famous as a health maintenance organization, UCSF is
perhaps best known as a tertiary care center. Some breakout session
panelists raised the question — also raised at last year’s retreat — of
whether or not the focus of UCSF research should more closely reflect
the patient population seen at UCSF and its affiliated medical centers.
UCSF specialists routinely gather extensive information on large numbers
of patients with serious acute and chronic conditions, including many
of the most difficult–to-treat cases. This extensive data is a potential
gold mine for research aimed at identifying factors related to disease
risk, prognosis and treatment outcomes.
Moving Toward A New Taxonomy of Disease
The retreat followed on the heels of a similarly themed report by the National Academy of Sciences (NAS), “Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease” [PDF] by a committee co-led by UCSF Chancellor Susan Desmond-Hellmann,
MD, MPH. The NAS committee advocated the creation of a “knowledge
network” that could link researchers in collaborations that span the
nation and globe.
The NAS panel envisioned a future in which there
is much greater use of genomic and other molecular data to improve and
refine the classification of diseases, but also recognized an
opportunity to improve research by more extensively taking into account
information about how patients fare in the clinic or hospital.
Instead
of the current state of affairs, through which biological, pre-clinical
and clinical research eventually lead to advances in medical practice,
the new paradigm will be a virtuous cycle through which — with
appropriate privacy protections — patient data also will feed back into
research. In patient care increasing amounts of laboratory information
will become available and interpretable more quickly to help teams of
caregivers make more accurate and effective decisions and choices in
diagnosis, prognosis and treatment for each individual patient.
Post a Comment
Thanks for reading my blog.
Note: only a member of this blog may post a comment.