EventFlow Presentation

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madeyjay

Tecnología Noticias y política

EventFlow
Megan Monroe
KristWongsuphasawat
Catherine Plaisant
Ben Shneiderman
Jeff Millstein
Sigfried Gold

Research supported by NIH and Oracle

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

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

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

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

Point-Based Events
STROKE
ADMITTED
DIAGNOSED

Interval-Based Events
ASPIRIN
DIET
STEROIDS
Research supported by NIH and Oracle

Individual Patient Records
Time

Patient #1

Patient #2

Patient #3

Patient #4
….

….

Research supported by NIH and Oracle

EventFlowDisplay

Research supported by NIH and Oracle

Aggregated Patient Records

Research supported by NIH and Oracle

Interval Merging

Research supported by NIH and Oracle

Interval Querying

Research supported by NIH and Oracle

Query Scope: Presence Events
Point/Point Point/Interval Interval/Interval

Research supported by NIH and Oracle

Query Scope: Range Constraints

Point/Point Point/Interval Interval/Interval

Research supported by NIH and Oracle

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

Query Scope: Absence Events
Point/Point Point/Interval Interval/Interval

Research supported by NIH and Oracle

Basic Querying
Subsequence:

Overlap:

Research supported by NIH and Oracle

Advanced Querying

Research supported by NIH and Oracle

LABAsDemo

Research supported by NIH and Oracle

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

EventFlow

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

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My talk at the Data Visualization Summit in San Francisco April 11, 2013 http://theinnovationenterprise.com/summits/data-visualization-sf ---------------- Abstract ---------------- Many aspects of our lives can be captured and described as series of events, or event sequences. These event sequences can be keys to understanding many things: medical services, logistics, sports, user behavior, etc. In this presentation, I will talk about techniques for visualizing event sequences, from simple to advance, and also show examples that demonstrate the power of visualizations in exploring and understanding event sequences.

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EventFlow Presentation

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/

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