Big Data
real-time decisions about how to best treat the
patient sitting in front of them.
In addition, big data can help tailor medical
therapy by selecting a smaller set of similar patients from a large pool of data and comparing
their responses to a particular treatment.
“For the clinical doctors, especially in
hematology and medical oncology, I think it
is incredibly challenging to predict whether or
not someone is going to respond to a therapeutic agent,” Dr. Meyer said, adding that she views
big data as “an immense opportunity” to collect
large volumes of data, create predictive algorithms, and, ultimately, improve patient care.
For instance, if a patient had a specific
genomic abnormality or mutated gene, clinicians may be able to use big data resources to
identify others with a similar mutation and determine if certain drug regimens outperformed
others in those individuals.
John Sweetenham, MD, executive medical
director for the Huntsman Cancer Institute at
the University of Utah, noted one area where
big data could be especially valuable: relapse
settings. The current process to discover which
drugs work best in a relapsed patient is essentially a trial-and-error process; big data could
give clinicians more real-world data when
making treatment decisions.
“The fact that we are going to be able to
do that in a data-driven way means that we’re
going to see higher response rates, longer survival, and fewer unnecessary treatments down
the line,” he said.
In an analysis published in Health Affairs,
David W. Bates, MD, MSc, and colleagues
identified six areas where they believed big
data would offer the greatest advantage: highcost patients, readmissions, triage, decompensation, adverse events, and treatment optimization for diseases that affect more than one
organ system.5
“Both predicting outcomes of patients –
such as who will be a high-cost patient, will be
readmitted, or will suffer an adverse event – and
tailoring the management of patients should
result in substantial savings for the health-care
system,” Dr. Bates wrote in the paper.
Clinicians could also potentially use big
data as a rationale for payment or prior authorization decisions from payers – in particular,
for drugs that are not approved for use in a particular indication but still have shown evidence
that the drug could be useful.
Isaac S. Kohane, MD, PhD, chair of the Department of Biomedical Informatics at Harvard
Medical School, added that big data can be used
to learn more about specific diseases. Dr. Kohane, for instance, has used entire health records
from multiple institutions to study children with
autism. “Access to the complete health record allows us to have a glance at the clinical landscape
of all the other diseases that they have – not just
the neurobehavioral diseases, but all of the other
clinical diseases that they have, and across tens
of thousands of patients.”
Dr. Kohane and colleagues discovered that
patients with autism also had a high incidence
of inflammatory bowel disease – a finding that
may not have been apparent without a wider
lens to study the population.
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ASH Clinical News
“Variety and veracity of data are the two
biggest issues. ... Our challenge is to
figure out how to produce good data,
and then to bring these data together
and use them with integrity.”
—ANNE-MARIE MEYER, PhD
“You could have 1,00