To objectively assess suturing performance using an image analysis program and to provide validity evidence for this assessment method by comparing experts’ and novices’ performance.Method
In 2009, the authors used an image analysis program to extract objective variables from digital images of suturing end products obtained during a previous study involving third-year medical students (novices) and surgical faculty and residents (experts). Variables included number of stitches, stitch length, total bite size, travel, stitch orientation, total bite-size-to-travel ratio, and symmetry across the incision ratio. The authors compared all variables between groups to detect significant differences and two variables (total bite-size-to-travel ratio and symmetry across the incision ratio) to ideal values.Results
Five experts and 15 novices participated. Experts’ and novices’ performances differed significantly (P < .05) with large effect sizes attributable to experience (Cohen d > 0.8) for total bite size (P = .009, d = 1.5), travel (P = .045, d = 1.1), total bite-size-to-travel ratio (P < .0001, d = 2.6), stitch orientation (P = .014,d = 1.4), and symmetry across the incision ratio (P = .022, d = 1.3).Conclusions
The authors found that a simple computer algorithm can extract variables from digital images of a running suture and rapidly provide quantitative summative assessment feedback. The significant differences found between groups confirm that this system can discriminate between skill levels. This image analysis program represents a viable training tool for objectively assessing trainees’ suturing, a foundational skill for many medical specialties.