![INFORMATION VISUALIZATION
INFO. VIS.
“ Using visual representations and interaction techniques,
which take advantage of the human eye’s
broad bandwidth pathway into the mind,
to allow users to see, explore, and understand
large amounts of information at once.”
[Wikipedia]!](https://image.slidesharecdn.com/infovisforhealthcare22-111127221133-phpapp02/75/information-visualization-for-health-care-4-2048.jpg?cb=1669663716)
![Healthcare
Electronic medical records (EMRs)
“ To improve the quality of our health care while lowering its cost,
we will make the immediate investments necessary to ensure that,
within five years, all of America's medical records are computerized.
This will cut waste, eliminate red tape and reduce the need
to repeat expensive medical tests.
But it just won't save billions of dollars and thousands of jobs;
it will save lives by reducing the deadly but preventable medical errors
that pervade our health-care system.”
[President Barack Obama – Jan 2009]!](https://image.slidesharecdn.com/infovisforhealthcare22-111127221133-phpapp02/75/information-visualization-for-health-care-9-2048.jpg?cb=1669663716)
![Lifelines
One patient
x
[Plaisant et al. 1998]!
http://www.cs.umd.edu/hcil/lifelines!](https://image.slidesharecdn.com/infovisforhealthcare22-111127221133-phpapp02/75/information-visualization-for-health-care-13-2048.jpg?cb=1669663716)
![Lifelines
One patient
Demographic
- Gender
- Age
- …
x
[Plaisant et al. 1998]!
Medical Events*
- Emergency room on Jan 15
- Surgery on Oct 1
- …
http://www.cs.umd.edu/hcil/lifelines!](https://image.slidesharecdn.com/infovisforhealthcare22-111127221133-phpapp02/75/information-visualization-for-health-care-20-2048.jpg?cb=1669663716)
![Lifelines 2
Multiple patients
xxxxx
[Wang et al. 2008, 2009]!
http://www.cs.umd.edu/hcil/lifelines2!](https://image.slidesharecdn.com/infovisforhealthcare22-111127221133-phpapp02/75/information-visualization-for-health-care-21-2048.jpg?cb=1669663716)
![Lifelines 2
Multiple patients
xxxxx
[Wang et al. 2008, 2009]!
http://www.cs.umd.edu/hcil/lifelines2!](https://image.slidesharecdn.com/infovisforhealthcare22-111127221133-phpapp02/75/information-visualization-for-health-care-28-2048.jpg?cb=1669663716)
![Lifelines 2
search from medical events
xxxxx [Wang et al. 2008, 2009]!
http://www.cs.umd.edu/hcil/lifelines2!](https://image.slidesharecdn.com/infovisforhealthcare22-111127221133-phpapp02/75/information-visualization-for-health-care-29-2048.jpg?cb=1669663716)
![LifeFlow
overview
xx
x x
xx x
x x xx
[Wongsuphasawat et al. 2011]!
http://www.cs.umd.edu/hcil/lifeflow!](https://image.slidesharecdn.com/infovisforhealthcare22-111127221133-phpapp02/75/information-visualization-for-health-care-34-2048.jpg?cb=1669663716)
Information Visualization for Health Care
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Information Visualization for Health Care
- 1. INFORMATION VISUALIZATION for healthcare Krist wongsuphasawat @kristwongz Department of Computer Science & Human-Computer Interaction Lab University of Maryland
- 3. A picture is worth a thousand words.
- 4. INFORMATION VISUALIZATION INFO. VIS. “ Using visual representations and interaction techniques, which take advantage of the human eye’s broad bandwidth pathway into the mind, to allow users to see, explore, and understand large amounts of information at once.” [Wikipedia]!
- 5. Anscombe’s quartet #1 #2 #3 #4 X Y X Y X Y X Y 10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58 8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76 13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71 9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84 11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47 14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04 6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25 4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50 12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56 7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91 5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89
- 6. Anscombe’s quartet #1 #2 #3 #4 Property Value Mean of X 11.0 Variance of X 10.0 Mean of Y 7.5 Variance of Y 3.75 Correlation between X and Y 0.816 Linear regression y = 3.0 +0.5x Identical statistics
- 7. Anscombe’s quartet #1 #2 #3 #4 12! 10! 14! 14! 9! 10! 12! 12! 8! 7! 10! 10! 8! 6! 8! 8! 6! 5! 4! 6! 6! 4! 3! 4! 4! 2! 2! 2! 2! 1! 0! 0! 0! 0! 0! 5! 10! 15! 0! 5! 10! 15! 0! 5! 10! 15! 0! 10! 20! But very different
- 8. INFORMATION VISUALIZATION Visual representation + User interactions click, drag, zoom, select, etc.!
- 9. Healthcare Electronic medical records (EMRs) “ To improve the quality of our health care while lowering its cost, we will make the immediate investments necessary to ensure that, within five years, all of America's medical records are computerized. This will cut waste, eliminate red tape and reduce the need to repeat expensive medical tests. But it just won't save billions of dollars and thousands of jobs; it will save lives by reducing the deadly but preventable medical errors that pervade our health-care system.” [President Barack Obama – Jan 2009]!
- 10. EMRs + INFO. VIS. A lot of data! Help understand data!
- 11. One patient x
- 12. Example of EMRs System
- 13. Lifelines One patient x [Plaisant et al. 1998]! http://www.cs.umd.edu/hcil/lifelines!
- 14. LifeLines
- 15. LifeLines
- 16. LifeLines
- 17. LifeLines
- 18. LifeLines
- 19. Lifelines user study Faster decision Better recall
- 20. Lifelines One patient Demographic - Gender - Age - … x [Plaisant et al. 1998]! Medical Events* - Emergency room on Jan 15 - Surgery on Oct 1 - … http://www.cs.umd.edu/hcil/lifelines!
- 21. Lifelines 2 Multiple patients xxxxx [Wang et al. 2008, 2009]! http://www.cs.umd.edu/hcil/lifelines2!
- 22. Case study Contrast-induced nephropathy Radiographic Examination (Medical Imaging) e.g. X-ray using a contrast agent e.g. Iodine, Barium x Creatinine - Amino Acid Damage to the kidney - Levels in blood reflect kidney function
- 23. Data : contrast & creatinine CREAT- Normal level of Creatinine RADIOLOGY Radiographic exam (with contrast) CREAT-H High level of Creatinine (bad) x Time Jan Feb Mar Apr
- 24. LifeLines2
- 27. Video demo Data Analysis with Lifelines2
- 28. Lifelines 2 Multiple patients xxxxx [Wang et al. 2008, 2009]! http://www.cs.umd.edu/hcil/lifelines2!
- 29. Lifelines 2 search from medical events xxxxx [Wang et al. 2008, 2009]! http://www.cs.umd.edu/hcil/lifelines2!
- 30. Data : patients transfer ARRIVAL Arrive the hospital EMERGENCY Emergency room ICU Intensive Care Unit FLOOR Normal room EXIT-ALIVE Leave the hospital alive EXIT-DEAD Leave the hospital dead
- 31. Improve the Quality of Care Pa$ent ID: 45851733 Pa$ent ID: 45851732 12/02/2008 14:26 Arrival 12/02/2008 14:26I D: 45851731 Pa$ent Emergency Emergency Department 12/02/2008 14:26 Arrival 6,000+ 12/02/2008 22:44 ICU mergency 12/02/2008 14:26 E 12/05/2008 05:071Floor Arrival 12/02/2008 4:26 12/02/2008 22:44 ICU mergency 12/02/2008 14:26 E 12/08/2008 10:02 Floor 12/05/2008 05:07 Floor 12/02/2008 22:44 ICU 12/14/2008 06:19 Discharge 12/08/2008 10:02 Floor 12/05/2008 05:07 Floor 12/14/2008 06:19 Discharge 12/08/2008 10:02 Floor 12/14/2008 06:19 Discharge patients per month
- 32. task Find “Bounce backs” ICU Floor ICU within 2 days Limitations High-level questions Arrival ? ICU ? ?
- 33. patients x x x xx x x x xx x xx x x x x x x x x x x
- 34. LifeFlow overview xx x x xx x x x xx [Wongsuphasawat et al. 2011]! http://www.cs.umd.edu/hcil/lifeflow!
- 35. Video demo Creating LifeFlow
- 38. LifeFlow
- 39. Video demo Data Analysis with LifeFlow
- 40. collected visual representation large eye interactions rich EMRs + INFO. VIS. A lot of data! Help understand data! and more… Lifelines LifeFlow Save more lives Lifelines 2 Patientslikeme / i2b2 / BTRIS Many case studies / etc. Krist wongsuphasawat @kristwongz kristw@cs.umd.edu! http://www.cs.umd.edu/hcil/temporalviz!
- 41. Other examples Visualizations in the Medical Domain