1. Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

2. http://www.nytimes.com/2002/06/18/health/oops-wrong-patient-journal-takes-on-medical-mistakes.html

3. Mrs. Morris, 67 Mrs. Morrison, 77 They were in same hospital floor. Mrs. Morris was taken to the operation room for the heart surgery

4. A drug administered to wrong patient Reading of wrong patients’ test results Patients miss needed treatment etc.

7. interruption fatigue urgency multitasking long work-hours

8.  Error Classification  what are the error-scenarios clinicians face  Task Analysis  which stage is more susceptible to a particular type of error  27 Specific Techniques  what to do, and then how to do it

9. Mistake Slips Failure to recognize

10. Mistake Slips Failure to recognize Recalling the wrong patient due to short term memory failure, name similarity, unfamiliarity with the patient, fatigue.

11. Mistake Slips Failure to recognize Mechanical errors such as wrong key press, mouse slip, or errors due to unreadable fonts and too small button size.

12. Mistake Slips Failure to recognize Failures to detect errors due to interruptions, multitasking, absence of relevant information.

18.  Facilitate recall: ▪Provide more context: room number, photo,…  Avoid confusion: ▪Emphasize the salient features: age, chief complaint,… ▪Use at least two sources of identification: name, medical record number,…

19. Poor recall strategy, more mistakes

21.  Allow sorting  Always show patient’s full name  Scan RFID to retrieve the patient  Use indoor location to retrieve the patients

22.  Improve target-selection  Improve text-readability  Highlight target under cursor

23. Poor selection mechanism, more slips

25.  Highlight row under cursor  Use an icon-based 2D grid instead of list

26.  Draw attention to patient information ▪Taieb-Maimon et al. : recognition increased from 7% to 43% with photo  Use decision support system

27. Poor verification, less error recognition Poor verification, less error recognition

30.  Use visual summary of patient history  Avoid visual distraction  Re-enter ID

33. ▪Human Error Classification ▪Attention Theory ▪Context Recovery Process ▪Cognitive Task Analysis ▪User Interface Design Principles ▪Expert Feedback ▪Medical Literature

34.  Categorization of the error-types, and sources  Suggestions of User Interface remedies  Prototype demonstrating the techniques

35.  Small changes in the UI can make big difference in patient safety  Include Clinicians and HCI researchers in the design process  To err is human, the systems should make up for it

36. www.cs.umd.edu/hcil/WPE www.youtube.com/watch?v=CrwOJIrnsg 8 Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman @awalinsopan awalin@cs.umd.edu We thank the Patient-Centered Cognitive Support under the Strategic Health IT Advanced Research Projects Program (SHARP) from the Office of the National Coordinator for Health Information Technology (Grant No. 10510592).