Electronic Health Records
Meaningful Use
Success Stories
Roadmaps, clinical decision support,
big data analysis – these are some
areas where EHRs shine brightest.
Here is just a sampling of some EHR
success stories in hematology:
• Researchers at the Children’s Hos-
pital of Wisconsin developed a
computable phenotype algorithm
to identify patients with sickle cell
disease through EHR data. The
algorithm was validated in adults
from a neighboring health system
and was deemed to have reliably
high sensitivity and positive pre-
dictive value for its intended use.
The authors eventually hope to use
their method to conduct research
at the national level. 1
• Providers were able to reduce un-
necessary blood transfusions (a
well-recognized source of medical
overuse) by embedding decision
support within an EHR-based
transfusion order set. 2
• At Washington University in St.
Louis, Missouri, a team in the medi-
cal school’s Pediatric Computing
Facility is developing the electronic
Oncology Roadmap Application.
This program will allow for seam-
less sharing of comprehensive
“treatment roadmaps” built in to
EHRs and based on the Children’s
Oncology Group protocols. The
same technology can be applied to
adults. 3
• Recognizing that the data collected
by randomized clinical trials (RCTs)
are often similar to those found in
EHRs, a group in the Netherlands
merged a population-based registry
with an advanced EHR system to
generate high-quality data for ob-
servational studies in hematology/
oncology. The approach may bridge
the gap between the RCT world and
the real world. 4
REFERENCES
1. Michalik DE, Taylor BW, Panepinto JA. Identification and
validation of a sickle cell disease cohort within electronic
health records. Acad Pediatr. 2017;17:283-7.
2. Sadana D, Pratzer A, Scher LJ, et al. Promoting high-value
practice by reducing unnecessary transfusions with a
patient blood management program. JAMA Intern Med.
2018;178:116-22.
3. Washington University in St. Louis School of Medicine,
“Pediatric Hematology-Oncology Roadmap Builder.”
Accessed March 8, 2018, from http://pediatrics.wustl.
edu/pcf/Projects/eroadmap.
4. Kibbelaar RE, Oortgiesen BE, van der Wal-Oost AM, et al.
Bridging the gap between the randomized clinical trial
world and the real world by combination of population-
based registry and electronic health record data: a case
study in haemato-oncology. Eur J Cancer. 2017;86:178-85.
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ASH Clinical News
clear mandate and ease-of-use were crucial
factors in obtaining buy-in and compliance
from the clinical staff.” They also noted that
implementation of an EHR system is never
done, and, even after established, the system
required constant monitoring. 11
“The heart and soul of oncology is
clinical trials, so systems that help us
track studies and reduce costs and time
involved in patient care are valuable,” said
Dr. Zelenetz. His group is working on an
easy way to record drug-related adverse
events for use in clinical investigations.
The Interoperability Problem
Clearly, collecting EHR data has great
implications for patient care and medical
research, but EHR systems need to be able
to “talk to each other” if any of those goals
are going to be realized. “We have been
behind in medicine in creating a standard
for exchanging medical information,” said
Dr. Zelenetz. He suggested this is as much
a result of vendor competition as it is a
technical issue.
Health-care IT has borrowed the
term “interoperability” from the systems
engineering world to describe the ability
of EHR technology and software applica-
tions “to work together within and across
organizational boundaries in order to
advance the effective delivery of health care
for individuals and communities.” 12