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LIFE event
event event
event event
event event event
event
event
event
event
event
event event
event
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( 7:00 am, Wake up )
LIFE event
event event
event event
event event event
event
event
event
event
event
event event
event
Time Event type
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LIFE event
event event
event event
event event event
event
event
event
event
event
event event
event
“Event Sequence”
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Human Activities
( 7:00 am, Wake up ) ( 7:10 am, Shower ) ( 7:30 am, Breakfast )
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Traffic Incidents Logs
( 9:30 am, Notification ) ( 9:55 am, Units arrived) ( 10:30 am, Scene cleared )
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Event Sequences
Human Activities
Electronic Health Records
Traffic Incident Logs
Usability Study Logs
Web logs
and more…
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Physicians at Washington Hospital Center
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Electronic Health Records • E.g. patient transfers in the hospital
• Event types:
ARRIVAL Arrive the hospital
EMERGENCY Emergency room
ICU Intensive Care Unit
FLOOR Normal room
DISCHARGE-ALIVE Leave the hospital alive
DIE Leave the hospital dead
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Improve the Quality of Care
Emergency Department Patient ID: 45851733
12/02/2008 14:26 Arrival 12/02/2008 14:26 Emergency 12/02/2008 22:44 ICU 12/05/2008 05:07 Floor 12/08/2008 10:02 Floor 12/14/2008 06:19 Discharge
Patient ID: 45851732
12/02/2008 14:26 Arrival 12/02/2008 14:26 Emergency 12/02/2008 22:44 ICU 12/05/2008 05:07 Floor 12/08/2008 10:02 Floor 12/14/2008 06:19 Discharge
Patient ID: 45851731
12/02/2008 14:26 Arrival 12/02/2008 14:26 Emergency 12/02/2008 22:44 ICU 12/05/2008 05:07 Floor 12/08/2008 10:02 Floor 12/14/2008 06:19 Discharge
6,000+ patients per month
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Visualizing event sequences
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• Single record
From one event sequence...
Patient ID: 45851737
12/02/2008 14:26 Arrival 12/02/2008 14:26 Emergency 12/02/2008 22:44 ICU 12/05/2008 05:07 Floor 12/08/2008 10:02 Floor 12/14/2008 06:19 Discharge Time
Patient #45851737 Arrival Emergency Room
ICU Floor
Discharge
compact
[Cousins91], [Harrison94], [Plaisant98], …
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To multiple event sequences... • Search
[Fails06], [Wang08], [Vrotsou09], …
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To multiple event sequences... • Search
[Fails06], [Wang08], [Vrotsou09], …
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To multiple event sequences... • Search
• Group
{ {
1
2
[Fails06], [Wang08], [Vrotsou09], …
[Phan07], [Burch08], [Wang09], …
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To multiple event sequences... • Search
• Group
• Summarize?
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Summarize
e.g. 1) What happened to the patients after they arrived?
Arrival
ICU
?
? ? ? ?
?
2) What happened to the patients before & after ICU?
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Overview / Summary
Millions of records
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Challenges • Display millions of records on one screen
– Limited space (typical monitors)
– Scalability (millions of records?)
– Aggregation
• While preserve important information – What are all the possible sequences?
– How long is the gap between each pair of events?
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LIFEFLOW
Picture > 1000 words LifeFlow > 1000 event sequences
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LIFEFLOW … is novel … is scalable
… provides the missing overview … summarizes all possible sequences
and time gap between events
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VIDEO LifeFlow Design
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DEMO LifeFlow Demonstration
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Improve the Quality of Care
Case Study#1: Medical
Feedback • Big picture + anomalies
• Less worry about query formulation, more time thinking about new questions
• Long-term monitoring
6,000+ patients per month
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Compare traffic agencies
Case Study#2: Transportation
200,000+ traffic incidents
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100 years!
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Clean the data.
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Video
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Agency
Time Notification Return to normal
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Compare traffic agencies
Case Study#2: Transportation
Feedback • Reveal unexpected sequences
• Identify data errors
• Can ask more questions, faster, and richer
200,000+ traffic incidents
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User Study • 10 participants
• Goals: – Learnability
– Strategies / Problems
• Procedure: – 12-minute training
– 15 tasks
• Results: – Participants can perform given tasks.
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Quotes
“The tool is easy to understand and easy to use.”
“Very easy to find common and uncommon sequences”
“LifeFlow provides a great summary of the big picture.”
“Oh! This is very cool!”
“Can I use it with my dataset?”
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Conclusions • LifeFlow
– Overview
– All sequences + gap between events
• 2 case studies + 1 user study – Show big picture + reveal anomalies
– New questions from the data
– Easy to learn
• Applicable to many domains
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Acknowledgement • Washington Hospital Center
Phuong Ho, Mark Smith, David Roseman http://www.whcenter.org
• National Institutes of Health (NIH) Grant RC1CA147489-02
http://www.nih.gov
• CATT Lab Michael Pack, Michael VanDaniker, Nikola Ivanov http://www.cattlab.umd.edu
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Conclusions • LifeFlow
– Overview of event sequences
– All sequences + gap between events
• 2 case studies + 1 user study – See big picture + reveal anomalies
– New questions from the data
– Easy to learn
• Applicable to many domains
HCIL’s 28th Annual Symposium May 25-26, 2011 University of Maryland #HCIL
Contact me [email protected] www.cs.umd.edu/hcil/lifeflow
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Q&A Any question?
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THANK YOU Your comments are welcome.
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