awalin sopan, catherine plaisant, seth powsner, ben shneiderman human-computer interaction lab &...

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User Interface Techniques to Reduce Wrong Patient Errors Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

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

User Interface Techniques to Reduce Wrong Patient Errors

Awalin Sopan, Catherine Plaisant,Seth Powsner, Ben Shneiderman

Human-Computer Interaction Lab & Department of Computer Science,

University of Maryland

Page 2: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

A Tale of Two Patients

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

Page 3: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

A Tale of Two Patients

Mrs. Morris, 67 Mrs. Morrison, 77

They were in same hospital floor.

Mrs. Morris was taken to the operation room for the heart

surgery

Page 4: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Problems

• A drug administered to wrong patient

• Reading of wrong patients’ test results

• Patients miss needed treatment

• etc.

Page 5: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Is Computerized Patient Order System a Panacea for

These Problems?

Page 6: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland
Page 7: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

interruption

fatigueurgenc

y

multitasking

long work-hours

Page 8: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Our ApproachError 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

Page 9: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Error Classification

Mistake

Slips

Failure to recogniz

e

Page 10: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Error Classification

Mistake

Slips

Failure to recogniz

e

Recalling the wrong patient due to short term memory failure, name similarity, unfamiliarity with the patient, fatigue.

Page 11: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Error Classification

Mistake

Slips

Failure to recogniz

e

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

Page 12: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Error Classification

Mistake

Slips

Failure to recogniz

e

Failures to detect errors due to interruptions, multitasking, absence of relevant information.

Page 13: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Task Analysis

Page 14: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Task Analysis

Page 15: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Task Analysis

Page 16: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Task Analysis

Page 17: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Task Analysis

Page 18: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

UI Techniques:Reduce Mistakes 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,…

Page 19: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Facilitate Recall

Poor recall strategy, more mistakes

Page 20: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland
Page 21: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Other Techniques

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

patients

Page 22: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

UI Techniques:Reduce Slips

Improve target-selection Improve text-readability Highlight target under cursor

Page 23: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Facilitate Selection

Poor selection mechanism, more slips

Page 24: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland
Page 25: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Highlight row under cursor Use an icon-based 2D grid instead of

list

Other Techniques

Page 26: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

UI Techniques:Increase Recognition

Draw attention to patient information▪ Taieb-Maimon et al. : recognition increased from 7% to 43% with photo

Use decision support system

Page 27: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Increase RecognitionPoor verification, less error recognition

Page 28: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

During Verification

Page 29: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland
Page 30: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Use visual summary of patient history

Avoid visual distraction Re-enter ID

Other Techniques

Page 31: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

During Confirmation

Page 32: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland
Page 33: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

What Guided Us

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

Page 34: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Contributions

Categorization of the error-types, and sources

Suggestions of User Interface remedies

Prototype demonstrating the techniques

Page 35: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

Take-away Messages

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

Page 36: Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman Human-Computer Interaction Lab & Department of Computer Science, University of Maryland

www.cs.umd.edu/hcil/WPE

www.youtube.com/watch?v=CrwOJIrnsg8

Awalin Sopan, Catherine Plaisant, Seth Powsner, Ben Shneiderman

@[email protected]

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).