PLoS ONE (Jan 2022)

A time motion study of manual versus artificial intelligence methods for wound assessment.

  • Heba Tallah Mohammed,
  • Robert L Bartlett,
  • Deborah Babb,
  • Robert D J Fraser,
  • David Mannion

DOI
https://doi.org/10.1371/journal.pone.0271742
Journal volume & issue
Vol. 17, no. 7
p. e0271742

Abstract

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ObjectivesThis time-motion study explored the amount of time clinicians spent on wound assessments in a real-world environment using wound assessment digital application utilizing Artificial Intelligence (AI) vs. manual methods. The study also aimed at comparing the proportion of captured quality wound images on the first attempt by the assessment method.MethodsClinicians practicing at Valley Wound Center who agreed to join the study were asked to record the time needed to complete wound assessment activities for patients with active wounds referred for a routine evaluation on the follow-up days at the clinic. Assessment activities included: labelling wounds, capturing images, measuring wounds, calculating surface areas, and transferring data into the patient's record.ResultsA total of 91 patients with 115 wounds were assessed. The average time to capture and access wound image with the AI digital tool was significantly faster than a standard digital camera with an average of 62 seconds (PConclusionsUsing the digital assessment tool saved significant time for clinicians in assessing wounds. It also successfully captured quality wound images at the first attempt.