Emily Hildebrand
CST 591
Review Paper 4
Feb. 28, 2012
A Visual Analytics Framework for Emergency Room Clinical Encounters
Z. Zhang, A. Mittal, S. Garg, A.E. Dimitriyadi, I.V. Ramakrishnan, R. Zhao, A. Viccellio, & K. Mueller
Published in: IEEE Workshop on Visual Analytics in Health Care, Salt Lake City (2010)
Paper citations: 0
The purpose of this paper is to discuss an emerging visual analytics system that is dedicated to clinical
encounters in emergency room (ER) situations. This system will unify all electronic medical records
(EMR) into a single interactive visual framework that can be controlled by either voice or touch. This
system will also allow physicians to conduct analytical reasoning tasks with the clinical data. Current
frameworks and paradigms incorporate visualizations such as timelines, body-centric data layouts, and
flowcharts. This framework will incorporate some of these elements but adds new functionality to them.
ER doctors have to deal with numerous pieces of information in a high stress and fast paced
environment. Often their tasks can consist of documentation, mental data analysis, recognizing patterns
or contradictions, observing changes in a patient’s status and reacting appropriately, and all this might
need to be accomplished simultaneously for multiple patients. Thus, the authors describe an vision for a
system that can reduce the amount of external work the doctor has to complete so they can give more
cognitive attention and focus to the task at hand. Their system will interact with the doctor throughout
the their interaction with the patient and provide inferential assistance. Information can be input via
touch screen on diagrams, checklists, drop down menus, or via a voice-text programs.
The framework for developing this cognitive aid system relies on the 5 W-principles:
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Who: the patient, doctor, nurse
What: the various information categories and items (symptoms, tests and results, etc)
Where: for example, locations of the “what” on the human body
When: time and duration of the “what” (timelines)
Why: cause and effect of the various “what constituents” (causal graphs)
How: outlines responsibilities in getting the treatment accomplished
The following figure (2) visualizes the who, what, where, and how by showing a sequence of frames
from the overall user interface of the system as it is updated with information and interacted with
during a standard patient/physician interview.
To visualize the “when” component of the framework a visualization similar to a timeline is used. Figure
3 shows an example of the temporal layout visualization. The authors suggest this visualization will help
physicians easily keep track of the different lengths of a patient’s treatment, symptoms, medication
usage, etc. Each entry regarding the patient’s medical information is calssified into of four tracks each
corresponding to a different color:
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symptoms: blue
tests: yellow/orange
diagnosis: green
treatments: pink/purple
Also, inferential analytics allow for causal relationships to be displayed via nodes in the panel.
Finally, to visualize the “why” component of the framework, the authors incorporate directed graphs. It
is suggested that these layouts will facilitate the physician in detecting errors in diagnoses and getting
up to date with a patient’s medical record history very quickly. Basically, the information represented in
the temporal layout above is translated into a causality graph and these are collected for every patient
visit so they can be viewed in isolation or in series to determine patterns and assess diagnoses.
Figure 4 shows the causal graph for the information depicted in the temporal layout above.
Finally, the authors discuss an example of a case study where multiple causal graphs could be used to
visualize multiple symptoms and provide knowledge regarding the patients medical history to facilitate
the physician in providing the correct diagnoses. Figure 5 shows an example of the reasoning process for
multiple sympotoms that a physician might encounter.
The authors feel that they are in the process of developing a visual analytics system that can have a
positive impact in the emergency room setting. They are currently implementing a “tighter integration
of the visual interface components in terms of look and feel.” And finally they hope to improve the
casual graph layout so that is it more geometrically structured than the present free form force directed
layout as well as incorporating a temporal element.
I chose this paper because I am interested in how visual analytic interfaces can improve knowledge
synthesis, decision making, and performance in the healthcare environment. This article supplied me
with good ideas about how to create a theoretical basis for visual interface design. I think they have
some really innovative ideas however I was hoping that they would have included more information
about the data collection (if available) process regarding user needs and usability testing.