In 2008, during his radiology residency at Massachusetts General
Hospital (MGH) in Boston, Dr. Choy parlayed a $30,000 RSNA Research
& Education Grant (see sidebar) into a search-engine based
informatics platform that has since been integrated into the hospital's
"This clinical decision support tool acts as a safety net and assists
physicians by automatically mining the data in the medical record in
real-time, seeking to identify risk factors and preventing the
performance of a contrast-enhanced scan when there is the potential for
harm to a patient," Dr. Choy said.
CIN is the leading cause of hospital-acquired renal
failure—accounting for up to 12 percent of all cases—and leads to longer
hospital stays, higher mortality rates, and increased medical costs.
Most troubling of all: there is no available treatment to reverse or
even mediate the condition, Dr. Choy said. Identifying at-risk patients
is critical for physicians to determine the best course of action,
whether to administer contrast at all, reduce the dose and/or implement
prophylactic strategies, he said.
Data points currently used in the qualitative screening for patients
at risk of CIN include serum creatinine, estimated glomerular filtration
rate and conditions such as pre-existing renal insufficiency, diabetes,
congestive heart failure, dehydration, advanced age, multiple myeloma
and malignancy affecting the kidneys, ureters or bladder.
Drawing on his background in operations management and engineering,
Dr. Choy created a program capable of searching the MGH electronic
medical record (EMR) for keywords and targeted concepts relevant to
identifying factors and data within the EMR to determine if a particular
patient is at risk for CIN.
Dr. Choy, along with Michael Zalis, M.D., and Mitch Harris, Ph.D.,
developed the project with scientific advisor G. Scott Gazelle, M.D.,
Ph.D., M.P.H., a professor of radiology at MGH and Harvard Medical
School and a professor in the Department of Health Policy and Management
at the Harvard School of Public Health.
The team also retrospectively analyzed the records of more than
13,000 patients who had undergone CT scanning at MGH between 2005 and
2007 in an attempt to correlate the development of CIN with certain risk
factors. "We performed statistical analysis to quantify the effect of
various risk factors on the development of contrast nephropathy," Dr.
Choy said. "The analysis was used to develop a risk prediction score—a
number—that indicated the potential CIN risk."
The first version of their Queried Patient Inference Dossier (QPID)
module was tested in a group of 100 patients—22 of whom developed
contrast nephropathy—during a pulmonary embolism CT scan. The QPID
module performed at a sensitivity of 81 percent—18 of the 22 patients
were correctly identified—and a specificity of 43 percent.
Currently, Dr. Choy and colleagues are analyzing a larger cohort of
patients for further validation of their risk prediction model. They are
also modifying their radiology order entry system so that orders for
contrast-enhanced CT scans will be flagged when patients are at risk for
"Dr. Choy's research is highly innovative and of great potential
significance," Dr. Gazelle said. "Contrast-induced nephropathy continues
to be an important problem in radiology and a better means of
identifying and stratifying patients at risk for this condition is
Dr. Choy and colleagues plan to publish their RSNA-funded research
and hope to secure further funding to continue to work on
decision-support tools to improve quality and safety in other areas of
radiology, as well as other areas in clinical medicine.
"The RSNA research grant has given me the opportunity to pursue my
passion for informatics in the development of decision-support tools
that will aid the clinician," Dr. Choy said. "I hope to continue a
career focused on innovation in radiology and medical informatics."
Name: Garry Choy, M.D.Grant Received: $30,000 RSNA Resident Research Grant, 2008Study: "Development of a Multi-variable Risk Prediction
Score for Contrast Media-Induced Nephropathy: A Tool for Prevention,
Prognostication, and Decision Making."
Career Impact: As a result of the RSNA Resident
Research Grant, Dr. Choy has confirmed his aspirations to pursue
academic radiology, actively working in research focused on improving
quality and patient safety in radiology. "I received excellent
mentorship and support from my residency program in order to have
dedicated research time," Dr. Choy said.Clinical Implications: Developing and validating a
clinical prediction rule to stratify the risk of contrast media-induced
nephropathy (CIN) based on known risk factors in order to aid in
decision making to prevent the condition. The research also provides the
framework for developing risk stratification tools for other patient
safety issues in radiology including the prevention of nephrogenic
For information on RSNA Research & Education (R&E) Foundation grants, go to http://www.rsna.org/Foundation/grants.cfm.
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