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Standard Setting of Competency in Mastoidectomy for the Cross-Institutional Mastoidectomy Assessment Tool

Posted on 2019-11-17 - 13:07
Objective:

Competency-based surgical training involves progressive autonomy given to the trainee. This requires systematic and evidence-based assessment with well-defined standards of proficiency. The objective of this study is to develop standards for the cross-institutional mastoidectomy assessment tool to inform decisions regarding whether a resident demonstrates sufficient skill to perform a mastoidectomy with or without supervision.

Methods:

A panel of fellowship-trained content experts in mastoidectomy was surveyed in relation to the 16 items of the assessment tool to determine the skills needed for supervised and unsupervised surgery. We examined the consensus score to investigate the degree of agreement among respondents for each survey item as well as additional analyses to determine whether the reported skill level required for each survey item was significantly different for the supervised versus unsupervised level.

Results:

Ten panelists representing different US training programs responded. There was considerable consensus on cut-off scores for each item and trainee level between panelists, with moderate (0.62) to very high (0.95) consensus scores depending on assessment item. Further analyses demonstrated that the difference between supervised and unsupervised skill levels was significantly meaningful for all items. Finally, minimum-passing scores for each item was established.

Conclusion:

We defined performance standards for the cross-institutional mastoidectomy assessment tool using the Angoff method. These cut-off scores that can be used to determine when trainees can progress from performance under supervision to performance without supervision. This can be used to guide training in a competency-based training curriculum.

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Annals of Otology, Rhinology & Laryngology

AUTHORS (7)

Thomas Kerwin
Gregory Wiet
Brad Hittle
Don Stredney
Paul De Boeck
Aaron Moberly
Steven Arild Wuyts Andersen
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