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A time motion study of manual versus artificial intelligence methods for wound assessment
Heba Tallah Mohammed1, Robert L Bartlett1, Deborah Babb2
1Swift Medical Inc., Toronto, ON, Canada.
Plos One
|July 28, 2022
Summary
A new Artificial Intelligence (AI) wound assessment tool significantly reduces clinician time and improves image quality. This AI application streamlines wound evaluation, saving valuable time and enhancing data accuracy for better patient care.
Area of Science:
- Medical Technology
- Clinical Informatics
- Wound Care Management
Background:
- Wound assessment is a critical component of patient care, often time-consuming for clinicians.
- Manual wound evaluation methods can lead to inefficiencies and variable image quality.
Purpose of the Study:
- To compare the time efficiency of an Artificial Intelligence (AI) digital wound assessment application versus manual methods.
- To evaluate the proportion of high-quality wound images captured on the first attempt using AI versus manual techniques.
Main Methods:
- A time-motion study was conducted with clinicians at Valley Wound Center.
- Clinicians recorded time spent on wound assessment activities (labeling, imaging, measuring, data transfer) using AI tool vs. manual methods.
- 91 patients with 115 wounds were included in the analysis.
Main Results:
- AI tool significantly reduced image capture and access time by 62 seconds (P<0.001).
- AI application was 77% faster in wound measurement and surface area calculation (45.05 seconds, P<0.001).
- Overall wound assessment time was reduced by 79% with the AI tool, capturing quality images on the first attempt (92.2% vs. 75.7%, P<0.004).
Conclusions:
- AI-powered digital wound assessment tools offer significant time savings for clinicians.
- The AI application enhances the quality of wound imaging, improving first-attempt capture rates.
