1. EventFlow
Megan Monroe
KristWongsuphasawat
Catherine Plaisant
Ben Shneiderman
Jeff Millstein
Sigfried Gold
Research supported by NIH and Oracle

2. Temporal Event Sequences
Data of the following format:
Item Identifier Type of Event Time (Start/End)
Patient #1 Stroke 11/3/2011
Patient #2 Heart Attack 7/1/2011
Patient #1 Diagnosed 11/5/2011
Examples:
•Electronic Health Records
• Process Flow
• Web Logs
Research supported by NIH and Oracle

3. Big Data Data Mining
Post-marketing surveillance has become a viable alternative
to clinical trials (example: medical insurance databases).
Advantages: Cost effective
No direct effect on patients
Disadvantages: Data is messy and imprecise
Must use very large datasets
Research supported by NIH and Oracle

4. US Army PharmacovigilanceCenter, OTSG
14 million EHR’s
(8 billion observations)
+
Standard Statistical Software
(PVDAS, SAS, Systat, etc.)
Difficult to: Develop new questions
Find unusual event patterns
Understand dataset holistically
Communicate findings
Research supported by NIH and Oracle

5. EventFlowMotivation
• Allow researchers to evaluate their data holistically
- Have immediate visual access to data
- Develop new questions/hypotheses
- Make rapid adjustments to view and dataset
• Facilitate communication about the data and
findings
• Integrate easily into existing systems (open source
Java coding)
Research supported by NIH and Oracle

6. Point-Based Events
STROKE
ADMITTED
DIAGNOSED
Interval-Based Events
ASPIRIN
DIET
STEROIDS
Research supported by NIH and Oracle

7. Individual Patient Records
Time
Patient #1
Patient #2
Patient #3
Patient #4
….
….
Research supported by NIH and Oracle

8. EventFlowDisplay
Research supported by NIH and Oracle

9. Aggregated Patient Records
Research supported by NIH and Oracle

10. Aggregated Patient Records
Research supported by NIH and Oracle

11. Interval Merging
Research supported by NIH and Oracle

12. Interval Querying
Research supported by NIH and Oracle

13. Query Scope: Presence Events
Point/Point Point/Interval Interval/Interval
Research supported by NIH and Oracle

14. Query Scope: Range Constraints
Point/Point Point/Interval Interval/Interval
Research supported by NIH and Oracle

15. Query Scope: Absence Events
Point Absences
The absence of a point event necessarily implies that the absence spans the period of
time between the previous presence event (or the beginning of the record) and the
subsequent presence event (or the end of the record).
Interval Absences
The absence of an interval event can occur for both a span of time, or at a point in time.
Research supported by NIH and Oracle

16. Query Scope: Absence Events
Point/Point Point/Interval Interval/Interval
Research supported by NIH and Oracle

17. Basic Querying
Subsequence:
Overlap:
Research supported by NIH and Oracle

18. Advanced Querying
Research supported by NIH and Oracle

19. LABAsDemo
Research supported by NIH and Oracle

20. Next Steps
• Complete advanced query implementation
• User tests for advanced query interface
• Begin analysis of new datasets
(Children’s Hospital)
Research supported by NIH and Oracle

21. EventFlow
Contact: madeyjay@umd.edu http://www.cs.umd.edu/hcil/eventflow/