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Overcoming the Arduous Transition for Robotic Hepatopancreatobiliary Cases: A Multi-Procedure Learning Curve Study Utilizing CUSUM Analysis

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Abstract

Background/objective

Quick optimization and mastery of a new technique is an important part of procedural medicine, especially in the field of minimally invasive surgery. Complex surgeries such as robotic pancreaticoduodenectomies (RPD) and robotic distal pancreatectomies (RDP) have a steep learning curve; therefore, findings that can help expedite the burdensome learning process are extremely beneficial. This single-surgeon study aims to report the learning curves of RDP, RPD, and robotic Heller myotomy (RHM) and to review the results’ implications for the current state of robotic hepatopancreaticobiliary (HPB) surgery.

Study design

This is a retrospective case series of a prospectively maintained database at a non-university tertiary care center. Total of 175 patients underwent either RDP, RPD, or RHM with the surgeon (DRJ) from January 2014 to January 2020.

Results

Statistical significance of operating room time (ORT) was noted after 47 cases for RDP (p < 0.05), 51 cases for RPD (p < 0.0001), and 18 cases for RHM (p < 0.05). Mean ORT after the statistical mastery of the procedure for RDP, RPD, and RHM was 124, 232, 93 min, respectively. No statistical significance was noted for estimated blood loss or length of stay.

Conclusions

Robotic HPB procedures have significantly higher learning curves compared to non-HPB procedures, even for an experienced HPB surgeon with extensive laparoscopic experience. Our RPD curve, however, is quicker than the literature average. We suggest that this is because of the simultaneous implementation of HPB (RDP and RPD) and non-HPB robotic surgeries with a shorter learning curve—especially foregut procedures such as RHM—into an experienced surgeon’s practice. This may accelerate the learning process without compromising patient safety and outcomes.

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Author notes

  1. Joseph S Lim and Terence Jackson are contributed equally for this work.

Authors and Affiliations

  1. Department of Surgery, Methodist Health System, 2805 E President George Bush Hwy, Dallas, Richardson, TX, 75082, USA

    Joseph S. Lim, Terence Jackson, James Kurtz, Edward E. Cho, Shyam Vedantam, Kei Nagatomo, Houssam Osman & Dhiresh Rohan Jeyarajah

  2. Department of Surgery, Medical City Arlington, Arlington, TX, USA

    Joseph S. Lim

  3. Department of Surgery, Tower Health, Reading, PA, USA

    James Kurtz

  4. Department of Surgery, Texas Christian University/University of North Texas Health Science Center, Fort Worth, TX, USA

    Edward E. Cho & Dhiresh Rohan Jeyarajah

Authors
  1. Joseph S. Lim
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  2. Terence Jackson
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  3. James Kurtz
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  4. Edward E. Cho
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  5. Shyam Vedantam
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  7. Houssam Osman
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  8. Dhiresh Rohan Jeyarajah
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Correspondence to Dhiresh Rohan Jeyarajah.

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Lim, J.S., Jackson, T., Kurtz, J. et al. Overcoming the Arduous Transition for Robotic Hepatopancreatobiliary Cases: A Multi-Procedure Learning Curve Study Utilizing CUSUM Analysis. World J Surg 45, 865–872 (2021). https://doi.org/10.1007/s00268-020-05861-z

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  • DOI: https://doi.org/10.1007/s00268-020-05861-z

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