Interactive training with a novel simulation model for upper gastrointestinal endoscopic hemostasis improves trainee technique and confidence Journal Articles uri icon

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abstract

  • Abstract Background and study aims Endoscopic hemostasis is a life-saving procedure for gastrointestinal bleeding; however, training for it is often performed on real patients and during urgent situations that put patients at risk. Reports of simulation-based training models for endoscopic hemostasis are scarce. Herein, we developed a novel simulator called “Medical Rising STAR-Ulcer type” to practice endoscopic hemostasis with hemoclips and coagulation graspers. This study aimed to evaluate the reproducibility of the clinical difficulty of this model and the effectiveness of simulation-based training for clipping hemostasis. Patients and methods This was a prospective educational study. Fifty gastroenterology residents from Japan and Canada were recruited to participate in a simulation-based training program. The primary outcome was the success rate for clipping hemostasis. We measured differences in trainee subjective assessment scores and evaluated the co-occurrence network based on comments after training. Results The hemostasis success rate of the trainees significantly increased after instruction (64% vs. 86%, P < 0.05). The success rate for ulcers in the upper body of the stomach (59%), a high-difficulty site, was significantly lower than that for ulcers in the antrum, even after feedback and instruction. Trainee self-perceived proficiency and confidence significantly improved after simulation-based training (P < 0.05). Co-occurrence network analysis showed that trainees valued a structured learning approach, acknowledged simulator limitations, and recognized the need for continuous skill refinement. Conclusions Our study demonstrates the potential of our simulation-based training model as a valuable tool for improving technical skills and confidence in trainees learning to perform endoscopic hemostasis.

authors

  • Kanno, Takeshi
  • Arata, Yutaro
  • Greenwald, Eric
  • Moayyedi, Paul
  • Suzuki, Suguo
  • Hatayama, Yutaka
  • Saito, Masahiro
  • Jin, Xiaoyi
  • Hatta, Waku
  • Uno, Kaname
  • Asano, Naoki
  • Imatani, Akira
  • Kagaya, Yutaka
  • Koike, Tomoyuki
  • Masamune, Atsushi

publication date

  • February 2024