Lifelines2: Hypothesis Generation in Multiple EHRs Taowei David Wang Catherine Plaisant Ben...
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Lifelines2: Hypothesis Generation in Multiple EHRs
Taowei David WangCatherine Plaisant Ben ShneidermanShawn MurphyMark Smith
Human-Computer Interaction Lab, University of Maryland
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LifeLines: Overview of Patient Record
Plaisant et al.,CHI96 AMIA98 - www.cs.umd.edu/hcil/lifelines
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Single record Millions of records
• Large databases of Electronic Health Records (EHRs):
• Observational studies
• Recruitment for clinical trials
• Hospital metrics
• Alarm design and testing
• etc.
Often involves temporal comparison relative to an important event
(e.g. heart attack, start of a treatment, 1st diagnosis of cancer)
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multiple patients
Lifelines2Sets of patient records
Disclaimer: de-identified data
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Lifelines2
• Introduce powerful combination of simple operators Align, Rank, Filter, and Summarize
• Multiple records simultaneously visible• Align by sentinel events• Rank by frequency• Filter by events• Summaries
• Focus on Point Events• Diagnosis, lab tests, etc.
• Measure Benefits of Alignment
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• Sample of Related Work
• Demo
• (Quick) Report on Studies
• Ongoing & Future Work
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Static views
Powsner & Tufte, 1994
Lexis diagrams (Bertin)
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Lifelines and improvements Overview of categorical and/or numerical data (semantic zoom)
Plaisant, CHI 96, AMIA 98
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Lifelines and improvements Overview of categorical and/or numerical data (semantic zoom)
Plaisant, CHI 96, AMIA 98
i2b2 (Murphy, AMIA 07)
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Lifelines and improvements Overview of categorical and/or numerical data (semantic zoom)
Plaisant, CHI 96, AMIA 98
i2b2 (Murphy, AMIA 07) Bade, CHI 2004
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ExperiScope (Guimbretiere, CHI 07)
Spiral Graph: Weber, 01 (based on Carlis, UIST 89)
Periodic dataOne of many example of manual alignment
Alignment Inspirations
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Patients with increasing dosages of Remeron followed by a heart attack within 180 days
Ball and chain display of matchesFails, VAST 06
PatternFinderSpecification of complex temporal queries on categorical data
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• Sample of Related Work
• Demo LifeLines2
• Report on Studies
• Ongoing & Future Work
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Demo
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multiple patientsUser Studies
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Two user studies
•Controlled experiment on Alignment (some training, measure speed and error)
• Domain expert qualitative study (no training, think aloud, discussion)
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Two user studies
•Controlled experiment (some training, measure speed and error)
• Benefit of alignment: YES (Significant improvement on complex tasks)
• 20 participants: grad students• Data: synthetic student record data
Tasks checked as domain independent
• Domain expert qualitative study (no training, think aloud, discussion)
Details
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Two user studies
•Controlled experiment (some training, measure speed and error)
• Benefit of alignment: YES (Significant improvement on complex tasks)
• 20 participants: grad studentsData: synthetic student record dataTasks checked as domain independent
• Domain expert qualitative study (no training, think aloud, discussion)
• Learnability: GOOD• General feedback and suggestions Suggestions
• 4 participants: nurse, physician, 2 prof. of nursing • All experienced with EHR and medical research
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Context
Search millions of records
Interactive visualization of results
LifeLines2
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Combine Alignment with PatternFinder
Washington Hospital Center
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Integrate Align-Rank-Filter in i2b2
Harvard Medical School, Partners HealthCare
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In summary…
• Align Rank, Filter, and Summarize Powerful combination of simple operations to explore temporal categorical data (events)
• Performance benefit of alignment: significant
• Impact: Deployment in 2 large operational EHR systems
• Many applicable domains:• Highway incident log• Student records• Web logs• Vehicle fleet records
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www.cs.umd.edu/hcil/lifelines2
Thank you!
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Quant. Evaluation Sample Data
Back to Evaluations
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Quantitative Evaluation Tasks
Task 1: How many students submitted a paper within 1 month after proposal? (5 records)
Task 2: How many students submitted a paper within 1 month after proposal? (20 records)
Task 3: How many students submitted at least 3 papers between proposal and defense?
Task 4: What occurred most often within a month of a student’s 1st paper submission?
Back to Evaluations
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(Alignment vs. No Alignment)Task Completion Time
0
20
40
60
80
100
120
1 2 3 4
Tasks
Tim
e (s
eco
nd
s)
With Alignment
Without Alignment
Task Error Rate
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1 2 3 4
Tasks
Rat
e
With Alignment
Without Alignment
Task Error Size
0
0.10.2
0.30.4
0.5
0.60.7
0.80.9
1
1 2 3
Tasks
Ave
rag
e E
rro
r S
ize
With Alignment
Without Alignment
back
• RM 1-way ANOVA
• Counter-balanced
• Very helpful (8.3)
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TimeSearcherDynamic queries on numerical temporal data
www.cs.umd.edu/hcil/timesearcher
Hochheiser Infovis04
Buono VDA05
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Specification of temporal abstractions To reason/query with them
Shahar 1999
Post 2007
No focus on interaction