Team-based learning curve and cost efficiency in robot-assisted hysterectomy: a four-phase CUSUM study of 915 cases

Team learning may influence both efficiency and hospital margins in robot-assisted hysterectomy (RAH), yet phase-specific economic data remain limited. We analyzed 915 consecutive RAHs (single-center, April 2019-August 2024). A CUSUM of operative time with segmented regression identified four phases (breakpoints at cases 155, 551, 800). Outcomes included operative metrics (operative, console, docking, patient-in-room times), blood loss, Clavien-Dindo complications, and itemized direct hospital costs under Japan's DPC system; the profit margin was calculated as the profit divided by the total surgical fees. As an institutional benchmark, outcomes from 164 laparoscopic hysterectomies (LH) performed during the same period were also analyzed. Operative time rose in Phase 2 and declined thereafter; major complications (CD ≥ III) remained 0-1.3%. Median total costs decreased from ¥401,116 (Phase 1) to ¥390,035 (Phase 4), a 2.76% reduction; profit margins improved in both benign (to ~ 37%) and malignant cases (to ~ 57%). In the Mastery Phase, RAH demonstrated a higher profit margin for both benign (37.4% vs 35.5%) and malignant (56.8% vs 53.0%) cases compared to the LH benchmark. Team proficiency-beyond individual surgeon skill-was associated with shorter operative time and improved hospital margins at maturity. Findings support institutional standardization and team training to accelerate the RAH learning curve.