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Related Experiment Video

Updated: May 31, 2026

Reverse Total Shoulder Arthroplasty
10:10

Reverse Total Shoulder Arthroplasty

Published on: July 5, 2011

Early adopter surgeon experience with Mako robotic-assisted reverse shoulder arthroplasty: perceived utility,

Mariano E Menendez1, Vahid Entezari2, John G Costouros3

  • 1Department of Orthopaedic Surgery, University of California Davis, Sacramento, CA, USA.

Journal of Shoulder and Elbow Surgery
|May 28, 2026
PubMed
Summary

Early adopters found robotic-assisted reverse total shoulder arthroplasty (rTSA) accurate and reliable, with improved plan fidelity. While initial time pressure exists, it decreases with experience, suggesting feasibility for wider rTSA implementation.

Keywords:
MakoRobotic shoulderShoulder arthroplastyShoulder replacementUtilityWorkload

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Area of Science:

  • Orthopedic Surgery
  • Robotics in Medicine
  • Surgical Technology

Background:

  • Robotic-assisted reverse total shoulder arthroplasty (rTSA) is emerging, with its adoption influenced by usability and reliability.
  • This study evaluates early surgeon experiences with the Mako robotic rTSA system during its limited release phase.

Purpose of the Study:

  • To characterize the early adopter experience of surgeons using the Mako robotic rTSA system.
  • To assess perceived utility, workload, and workflow efficiency of robotic-assisted rTSA.

Main Methods:

  • A cross-sectional survey was administered to 15 surgeons using the Mako rTSA system.
  • Surveys assessed perceived utility (Likert scale) and workload (NASA-TLX), comparing robotic to non-robotic procedures.
  • Workflow conversions and reasons were also recorded.

Main Results:

  • Surgeons reported high satisfaction with accuracy, plan fidelity, and reduced outlier placement.
  • NASA-TLX scores indicated low mental demand but moderate physical demand and time pressure.
  • Temporal demand decreased with increased robotic experience; 43% reported workflow conversions due to registration or fixation issues.

Conclusions:

  • Robotic-assisted rTSA with the Mako system is perceived by early adopters as accurate and reliable, without increasing cognitive load.
  • Initial implementation challenges include time pressure and rare workflow conversions, which improve with experience.
  • Workflow efficiency and reliability are key factors for the scalability of robotic-assisted rTSA.