In:
Obstetrics & Gynecology, Ovid Technologies (Wolters Kluwer Health), Vol. 132, No. 1 ( 2018-10), p. 53S-53S
Abstract:
John Fischer, MD PURPOSE: To develop a low fidelity model for retroperitoneal dissection and identification of the ureter to improve resident's confidence and competency in the operating room. BACKGROUND: Work hour restrictions and few open laparotomies have created barriers to confident resident performance of retroperitoneal dissections. While simulation training models have been developed for laparoscopy, few have been created and validated for open laparotomies. METHODS: OB/GYN residents were divided into case (PGY3) and control (PGY4). A pretest questionnaire assessed operative experience. Both groups performed a videotaped low fidelity simulated retroperitoneal dissection that included identifying the course of the ureter. An instructional video was introduced and repeat simulation was performed by PGY3 trainees only. Three expert gynecologists independently scored performances using a checklist and global rating scale of operative performance (OSAT). PGY3 pretest/posttest scores were compared to PGY4 scores using the Wilcoxon rank sum test. Paired t -test was used for comparison of cases. P 〈 .05. RESULTS: Median pretest checklist score for PGY4 was significantly increased compared to PGY3 (7.3 vs. 6.3, P =.0314) however the median pretest OSAT score was not. A statistically significant increase in average PGY3 scores between pre vs. post final checklist scores and final OSAT scores was noted. A statistically significant increase in the median scores between PGY4 pretest (control) vs. PGY3 posttest (case) final checklist scores and final global scores (7.3 vs. 9.2, P =.0052) and (24.2 vs. 28.2, P =.0042) was noted. DISCUSSION: The development of a low fidelity model for retroperitoneal dissection and use of an instructional video may complement traditional learning for this core competency.
Type of Medium:
Online Resource
ISSN:
0029-7844
DOI:
10.1097/01.AOG.0000546658.10648.a5
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2018
detail.hit.zdb_id:
2012791-1
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