Dr. Nagy
is an Associate Professor, Director of Quality and Informatics
Research, Department of Radiology, University of Maryland School of
Medicine, Baltimore, MD.
One of the roles of an informatics architect is to provide an
infrastructure that enables radiologists to read images immediately
wherever they are. Such rapid access to digital imaging reduces
delays in interpretation, speeds report turnaround time, and
hastens clinical decision-making, all of which clearly improve
efficiency.
Over the years, however, it has become equally clear that an
accelerated work pace, a focus on productivity, and the use of
distance medicine can sterilize work relationships. When a
technologist no longer comes into the reading room to hang
films, something gets lost in the relationship between
radiologist and technologist. When referring physicians no longer
engage the radiologist in consultations, something gets lost in
that relationship too. These changes threaten to compromise
quality.
In our desire to leverage information technology (IT) to be as
productive as possible, we have threatened our work relationships.
This doesn’t need to be so. Essentially, IT was born to
communicate, whether by voicemail, e-mail, text messaging, instant
messaging, or paging. We can do a better job of using some of these
communication vehicles to create a culture of quality within
radiology-to make it easier to do the right thing while being as
productive as possible. This article will discuss 3 tools we have
developed at the University of Maryland to enhance quality through
informatics.
Quality-control reporting
The first challenge many radiology practices face when
they “go digital” is incorporating the quality-control practices
that were used in the film environment. In the past,
radiologists could note on the film if the images were
poorly collimated or were substandard in some other way. In an
electronic environment, there is little feedback between
radiologists and technologists.
The result can be a downward spiral in quality. Often,
radiologists submit quality-control reports using the same
paper-based forms they were using years ago. The reports go to
modality supervisors, who discuss them with the technologists. But
the radiologists typically don't receive any feedback on actions
taken and don't observe any improvement. As a result, it is
difficult for radiologists to see the value in submitting
future quality-control reports.
Once radiologists become apathetic about reporting quality
issues, many things can go awry. If technologists don’t get
feedback on the quality of their work, they are likely to either
think they’re doing a great job or that radiologists in their
institution don’t care about image quality. Radiology supervisors
may know that radiologists are unhappy, but they have no data to
use in taking action. The result is a disappointing stalemate.
Information technology systems must be able to handle
communications feedback to ensure quality processes. The key
ingredients for change at the University of Maryland were a picture
archiving and communications system (PACS) and a simple Web-based
issue tracking tool that enables radiologists to submit
quality-control issues, assigns issues to owners, and
notifies users when the issue has been resolved. We also
supplied our technologists and modality supervisors with digital
pagers. When a radiologist reports a quality issue, the system
pages the technologist and modality supervisor immediately.
To encourage radiologists to report quality issues, it is
important to remove as many barriers as possible and to make
reporting simple. With this in mind, we synchronized quality
control with our clinical workflow by adding a button to
our PACS that launches a Web-based quality-control tool called
Radtracker
1
(Figure 1).
The issue-submission Web page provides the user name, the study
session number, the patient medical record number, and the
modality. Within a single pull-down menu, the radiologist can
select what is wrong with the images-poor patient positioning, for
example-and can add comments. When the radiologist clicks on
“submit,” the modality supervisor and technologist receive a text
message about the issue and how to correct it. The technologist
then resolves the issue, and the radiologist receives an e-mail
about actions taken.
Using this system, we have gone from approximately 5 to 10
paper-based quality-control reports per month in 2006 to 300 per
month today. This does not reflect deterioration in
quality; in fact, only roughly 1% of our annual volume of studies
has a quality-control issue. Instead, better quality-control
reporting has enabled us to focus on the root cause of
quality-control issues and to track how quickly we respond to these
issues. In approximately 40% of cases, we resolve the issue within
an hour.
We have also uncovered new types of quality issues, beyond those
related to image acquisition. Data quality issues can affect the
radiologist’s workflow. For example, if the technologist
doesn’t sign off and complete a study in time, the radiologist
might not be able to finalize it. Using this process,
we’re better able to understand problem areas in the
department.
We have used the quality-control data to create knowledge bases
that we can click through and explore. When we do in-service
training, we use the knowledge bases to find various types
of cases. Using URL-based integration, we can even launch the PACS
system simply by clicking on a case file.
Every few months, a radiologist, technologist, modality
supervisor, and physicist meet for an hour to work through all of
the quality-control issues in a given imaging section. This offers
radiologists an ideal opportunity to lead a discussion on how
quality-control issues arise. In the past, our modality supervisors
were very good at fixing problems on a day-to-day basis
but didn’t necessarily understand the magnitude of the issue. Now,
when they see that a problem is occurring many times a year, they
realize it’s worth the effort to determine why the problem is
happening and how to remove the root causes.
We also use this system for generating report cards (Figure 2).
These report cards enable our technologists to see how well they’re
doing, how many quality reports they’re getting from radiologists
over a period of time, and how they compare with other
technologists. We have found that most technologists are very
responsive. Once they see the data, they try to understand how they
can do a better job. This is a very powerful tool for creating a
culture of quality.
For radiologists, this system provides a mechanism to report
quality issues and removes any reason for being apathetic. We now
have data-driven discussions with the radiologists to try to
understand the root causes of quality issues. The radiologists feel
that the technologists are working with them, that we are a team,
and that we have a good feedback mechanism and good
communication.
Technologist peer review
The second quality-control tool that we have implemented,
technologist peer review, also harkens back to the days of
film. Acquiring images has always been an art that
requires training and feedback to perfect. In the past, as senior
film technologists processed films, they would
review images and take junior technologists to task for quality
problems. Through peer pressure, junior technologists would be
motivated to improve their performance.
Peer pressure is an enormous motivator that we don’t use well
enough in healthcare to improve performance. At our institution, we
use informatics as a tool for applying peer pressure. We no longer
have the luxury of doing in-line quality control while processing
film. Radiologists need to read images right away and
report them immediately. However, we can do retrospective quality
control.
To achieve this goal, we have built a fully automated Web-based
Tech Quality Assurance (QA) tool that captures all the studies done
by a section, then randomly assigns approximately 5% of them to a
volunteer to review (Figure 3). Reviewing technologists are given a
worklist with the procedure names and dates. Because of
synchronization between information systems, they can launch the
study in the PACS system simply by clicking on the integrated
URL.
Once the study has been launched, the technologist reviewer
rates it on a scale of 1 to 5, with 1 being poor and 5 being
excellent. The ratings cover patient positioning, image
clarity/artifacts, contrast, annotations, markers, and radiation
safety. The reviews are then approved or disapproved by a modality
supervisor. This step enables us to train our volunteers to become
better reviewers.
We have used this technique to review >5000 studies so far.
We have found that we're doing well on contrast, data quality, and
annotations, but have room for improvement in markers, positioning,
and radiation safety (mostly collimation).
We can also use the Tech QA tool in preparing individual
technologist report cards. This is a way of giving very tailored
feedback on how to improve their processes. We can also use this
tool as a knowledge base to identify the best and worst studies in
each section, so that technologists can learn by both doing and
seeing.
Communication
Communication between radiologists and referring physicians
plays another important role in quality. Take the case of a
critical finding that warrants rapid communication. The
Joint Commission on the Accreditation of Healthcare Organizations
(JCAHO) requires that radiologists document not only that a
critical finding has been delivered but also how long it
took to deliver the finding.
Delivery of critical findings can be especially
challenging in a large in-patient medical center. At the University
of Maryland, we have roughly 1100 attending physicians and another
900 residents. Often the physician who orders a study is not the
right person to take delivery of the critical finding.
This is a source of frustration for radiologists.
To help in identifying the right person to receive information
to critical situations, we have developed data mining tools that
identify who is involved in patient care (Figure 4). This tool can
perform a real-time query of the electronic medical record to
determine where the patient is located and which service team is
caring for the patient. Often, it is more important to identify the
appropriate service team than to identify the individual
physician.
We can also use the critical alert tool to determine who has
been in contact with the patient in the last 24 hours. Knowing
which physicians and nurses are giving care to the patient offers
an important clue in determining to whom to deliver critical
information. We can also look at the PACS to see who has been
looking at the images and the computer-based order entry system to
see who has been placing physician orders for the patient.
When the radiologists launch the critical alert tool from our
PACS, they are presented with all of the patient information and
names of clinicians who have been involved in patient care, along
with information on how old the contact data are. Once we have all
this information, we mine a centralized physician contact database
with phone numbers and an integrated online paging system. The
radiologist simply clicks on the “contact” button next to each
name.
In addition, we have built a blogging tool that can be launched
from the PACS and documents all the radiologist’s efforts to
communicate critical findings, as well as to document
that it was successfully delivered, to whom, and when.
Healthcare IT systems are a gold mine of information. If we can
provide some of that information in a relevant format to
radiologists, it can help them to make decisions and to communicate
information quickly in a critical environment.
Conclusion
Communication plays a vital role in how we deliver radiology
services and in the quality of those services. Information
technology is immensely qualified to deliver tools that
improve quality and communications. The time has come for
radiologists to insist that vendors provide these tools. PACS
stands for picture archiving and communication system. It’s time to
put the communication back in PACS.