1. Effects of a Resident's Reputation on Laparoscopic Skills Assessment
- Author
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Michele Farrugia, Evan Tannenbaum, Ella Huszti, Mara Sobel, Melissa Walker, and Heather Sullivan
- Subjects
medicine.medical_specialty ,business.industry ,media_common.quotation_subject ,Psychological intervention ,Internship and Residency ,Obstetrics and Gynecology ,Assessment scale ,Gynecology ,Family medicine ,Surgical skills ,Humans ,Medicine ,Laparoscopy ,Educational Measurement ,Technical skills ,business ,Prejudice ,Reputation ,media_common - Abstract
OBJECTIVE To quantify the effect of a resident's reputation on the assessment of their laparoscopic skills. METHODS Faculty gynecologists were randomized to receive one of three hypothetical resident scenarios: a resident with high, average, or low surgical skills. All participants were then asked to view the same video of a resident performing a laparoscopic salpingo-oophorectomy that differed only by the resident description and provide an assessment using a modified OSATS (Objective Structured Assessment of Technical Skills) and a global assessment scale. RESULTS From September 6, 2020, to October 20, 2020, a total of 43 faculty gynecologic surgeons were recruited to complete the study. Assessment scores on the modified OSATS (out of 20) and global assessment (out of 5) differed significantly according to resident description, where the high-performing resident scored highest (median scores of 15 and 4, respectively), followed by the average-performing resident (13 and 3), and finally, the low-performing resident (11 and 3) (P=.008 and .043, respectively). CONCLUSION Faculty assessment of residents in gynecologic surgery is influenced by the assessor's knowledge of the resident's past performance. This knowledge introduces bias that artificially increases scores given to those residents with favorable reputations and decreases scores given to those with reputed surgical skill deficits. These data quantify the effect of such bias in the assessment of residents in the workplace and serve as an impetus to explore systems-level interventions to mitigate bias.
- Published
- 2021