Abstract
Purpose :
Administering retrobulbar blocks (RBB) is a challenging, yet commonly employed approach to provide infiltrative local anesthesia for ophthalmic surgeries. It requires the skillful delivery of anesthetic into the accurate orbital space with precise orientation to avoid damage to surrounding ocular structures. The purpose of this study is to evaluate the impact of a structured training session on self-reported knowledge, comfort, and skills needed for retrobulbar block injections.
Methods :
Thirteen trainees from New York Eye and Ear Infirmary completed a quality improvement survey questionnaire before and after participating in the training session. The session involved a 20-minute instructional video followed by a wet-lab training session using a bovine head and porcine eyes for simulation. A paired-samples t-test was conducted to compare self-reported scores for all outcome measures before and after the training session.
Results :
Of 13 participants, there were 4 (30.8%) postgraduate year two residents (PGY2), 1 (7.7%) PGY3, 6 (50%) PGY4, and 2 fellows (16.7%). Thirteen surveys were completed before and after training. One participant did not view the video. All measured outcomes improved significantly after the training session compared to baseline. The mean score on knowledge of anatomy and complications pre and post training was 7.38 (SD=2.63, CI=5.79-8.97) and 9.31 (SD=0.95, CI=8.74-9.88) respectively (p=0.0401). The mean score on perception of skills pre and post training was 3.46 (SD=1.39,CI=2.62-4.30), 4.46 (SD=0.66,CI-4.06-4.86) respectively (p=0.0475).
Conclusions :
Retrobulbar blocks are technically-challenging procedures that provide excellent anesthesia but come with considerable risks. We have demonstrated that incorporating a structured training session improves trainees’ self-reported knowledge, comfort, and skills. We suggest that integrating a fixed didactic and wet-lab session with animal models during residency, will improve level of skill transfer from surgeons to trainees.
This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.