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Interprofessional veno-veno bypass simulation improved team confidence.

Julie A Hartman1, Dyan M Anderson1, Johnson Ding1

  • 1Center for Procedural Skills and Simulation, University of Iowa Health Care, Iowa City, IA.

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Simulation training improved surgical team confidence and communication for rare liver transplant procedures requiring veno-veno bypass, enhancing patient safety.

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Area of Science:

  • Medical Simulation
  • Surgical Team Training
  • Liver Transplantation

Background:

  • Rarely performed procedures, such as veno-veno bypass for liver transplants, present significant stress and communication challenges.
  • Effective team performance and procedural workflow are critical in emergency situations.

Purpose of the Study:

  • To develop and implement a simulation to practice and improve team performance and procedural workflow for liver transplant patients requiring veno-veno bypass.
  • To enhance communication and standardize the approach to this complex procedure.

Main Methods:

  • A simulation scenario was created for a predetermined liver transplant patient needing veno-veno bypass.
  • A checklist guided participants through procedural steps and communication requirements.
  • A multidisciplinary team (surgeons, anesthesiologists, nurses, perfusionists) participated.
  • Debriefing and a post-simulation survey assessed participant confidence.

Main Results:

  • Participants successfully performed steps outlined in the checklist during the simulation.
  • Post-simulation surveys indicated high confidence levels in communication (4.2), teamwork (4.6), and knowledge of supplies (4.4).
  • Discussions during debriefing led to improvements in equipment, supply management, and procedural standardization.

Conclusions:

  • The simulation was a positive experience, highlighting the need for standardized procedures for veno-veno bypass.
  • The checklist will be adopted as a resource for future operating room procedures.
  • The training enhanced team preparedness and identified areas for equipment and procedural optimization.