LifeLines for Visualizing Patient Records
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The Lifelines project started in 1994 with research grant from the
Maryland Department of Juvenile Services . We developed a new technique
called Life-Lines to visualize personal history records. In 1995 we started working
with IBM Watson Research Center and Kaiser Permanente Colorado to extend the technique to medical records.
At the time IBM's Kaiser system was one of very rare computerized system combining data from diverse sources (e.g. notes, pharmacy data, test results, etc.).
LifeLines provided a novel general visualization environment for personal histories.
A one screen overview of the record using timelines provides direct access
to the data. For a patient record, medical problems, hospitalization and
medications can be represented as horizontal lines, while icons represent
discrete events such as physician consultations, progress notes or tests.
Line color and thickness can illustrate relationships or significance.
Semantic zooming and filters allow users to focus on part of the information,
revealing more details.
LifeLines are easy to understand with no or limited training and can facilitate
the spotting of anomalies and trends, streamline the access to details
(as LifeLines act as large menus) and reduce the chances of missing information.
We believe that LifeLines have applicability to a number of the health
care projects. Computerized medical records pose tremendous problems to system developers.
Infrastructure and privacy issues need to be resolved before physicians
can even start using the records. Non-intrusive hardware is required for
physicians to do their work (e.g. interview patients) away from their desk.
But all the efforts to solve these problems will only succeed if appropriate
attention is also given to the user interface design. Long lists to scroll,
clumsy searches, endless menus and lengthy dialogs will lead to user frustration.
Techniques are being developed to summarize, filter and present large
amounts of information, leading us to believe that rapid access to needed
data is possible with careful design.
Influence: Examples of commercial or operational systems using some of the principles demonstrated in the Lifelines prototypes:
1) Harvard I2B2 (screenshot ~1997)
2) PatientLikeMe, e.g. Fig.2 from Frost and Massagli, 2008
3) Southampton EPR, from " Rew, D.A. Indian J Surg Oncol (2011)
4) Wand Timeline view of a patient record in Allscripts ambulatory EHR iPad application
Used with permission of Allscripts. (screenshot 11/2012)
5) HealthTronics UroChartEHR (Screenshot accessed 07/2014)
6) iSALUS EHR (Screenshot accessed 02/2015)
See also the nice Vitals screen)
7) UHR Rennes PEP platform. Screens from 2017 presentation.
8) VIP from Baudel and Brochard paper at Visu 2018 (IBM Fance Lab)
Plaisant, Assistant Research Scientist
Professor Computer Science
Anne Rose, Faculty Research Assistant
Jia Li, Graduate Student Computer Science
Diane Lindwarm (Alonzo), Graduate Student Psychology
Dan Heller, Undergraduate Student
Partha Ghosh, Graduate
Richard Mushlin, IBM Watson Research Center
Aaron Snyder, Kaiser Permanente Colorado
and we thank John Karat (IBM) for his leadership and support
The work on LifeLines was originally supported by the State of
Maryland Department of Juvenile Justice (94-96). In 97 and 98 HCIL received
some support from the University of Maryland (CMPS) to work on medical records in collaboration with IBM as part of the
IBM SUR program which provided equipment to the University. Ben Shneiderman also received an IBM faculty award, allowing us to explore how LifeLines could also be used in ebusiness and other applications.
Other HCIL projects on visualization of temporal data, e.g. Eventflow for exploring temporal patterns
The original Juvenile Justice project where LifeLines was "born".
Related HCIL workshops:
Personal Histories: a Workshop (July 21-22, 1997)
See also: HealthInfoDesign Resources on design and medical informatics.
Medical Devices Workshop: Increasing Patient Healthcare Participation (June
Visual Exploration of Electronic Health Records (May 30, 2008);
and many more, e.g.
(2014) Workshop on Exploring Temporal Patterns in Electronic Health Record Data
(Thursday, May 29, 2014)