International expert consensus-driven surgical process model for robot-assisted hysterectomy: Delphi study results.

Area of Science:

• Robotic Surgery
• Surgical Education
• Artificial Intelligence in Medicine

Background:

• Robot-assisted total laparoscopic hysterectomy (rTLH) exhibits significant procedural variability, impacting surgical outcomes and training.
• Current curricula lack formal models for procedural logic and variability in rTLH.
• Standardized Surgical Process Models (SPMs) are crucial for reproducibility, education, and AI integration.

Purpose of the Study:

• To develop the first consensus-based Surgical Process Model (SPM) for standard robot-assisted total laparoscopic hysterectomy (rTLH).
• To establish a formal, expert-validated representation of rTLH procedures.

Main Methods:

• A five-round Delphi study involving 35 international expert robotic gynecologic surgeons (November 2023 - October 2024).
• Iterative refinement and consensus-building on rTLH phases, steps, and procedural paths.
• Consensus defined as ≥75% agreement.

Main Results:

• A final SPM comprising 7 phases and 34 detailed surgical steps was established through expert consensus.
• Seven validated SPM paths were identified, capturing procedural variability while standardizing uterine pedicle dissection.
• The model provides a formal, adaptable representation of standard rTLH.

Conclusions:

• This study presents the first internationally validated SPM for rTLH.
• The model facilitates improved surgical training and objective performance assessment.
• It serves as a foundational tool for surgical data science and AI applications in robotic gynecologic surgery.