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Visualizing surgical quality data with treemaps.

Akilah L Hugine1, Stephanie A Guerlain1, Florence E Turrentine2

  • 1Department of Systems & Information Engineering, University of Virginia, Charlottesville, Virginia.

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|April 29, 2014
PubMed
Summary
This summary is machine-generated.

Treemaps aid surgeons in quickly assessing surgical quality data. While effective for visual judgment, layout design impacts accuracy, necessitating further research for dashboard integration.

Keywords:
ACS NSQIPData visualizationQuality improvementSurgical quality dataTreemaps

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Area of Science:

  • Data Visualization
  • Surgical Quality Improvement
  • Human-Computer Interaction

Background:

  • Treemaps are space-constrained visualizations for hierarchical data.
  • They enable examination of large datasets in a single display.
  • The National Surgical Quality Improvement Program database contains valuable surgical quality data.

Purpose of the Study:

  • To evaluate treemap visualizations for assessing surgical quality data.
  • To determine if treemaps facilitate quick and timely judgments by surgeons.
  • To explore the impact of treemaps on surgical quality data assessment.

Main Methods:

  • A controlled human subjects experiment was conducted.
  • Participants completed 20 task questions using treemap visualizations.
  • Data were hierarchically displayed by surgeon group, surgeon, and patient.
  • Outcomes measured included error rates and task completion times.

Main Results:

  • 120 participants completed 2400 task questions.
  • Layout and node size significantly affected absolute error (P < 0.0505 and P < 0.0185).
  • Average task completion time was 24 seconds with 68% accuracy.

Conclusions:

  • Treemaps show potential for retrospective surgical data assessment.
  • Layout design is a critical factor influencing judgment performance.
  • Future research should investigate treemap integration into dashboard systems for improved accuracy.