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Project 3.5: Multi-specialty Robots

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Project 3.5: Multi-specialty Robots

  • Project Start Date: 9th December 2023
  • Project End Date: 31st December 2024

This research aimed to explore multi-specialty applications and optimise workflows to drive wider adoption of robotics in hospitals.  

Addressing the Challenges of Robotic Surgery  

While orthopaedic surgical robots have been shown to enable more accurate placement of implants and improved patient outcomes, they are currently utilised for only a small number of procedure types. Furthermore, these systems generally have high initial costs and in many cases are subject to a range of operational inefficiencies. 

By understanding and addressing current challenges, the project aimed to maximise efficiency, improve hospital utilisation, and highlight the financial and operational benefits of robotic surgery. Ultimately, the goal was to drive growth in Mako’s applications and increase the accessibility of robotic surgery.  

Research Approach: Understanding Surgical Workflows  

To tackle these challenges, QUT researchers employed a mixed-methods approach, predominantly using qualitative research techniques. The study involved:  

  • Tracking the timing of each phase of the surgical procedure to identify workflows and constraints.  
  • Observing surgical teams in action, including the interactions between Mako and medical staff.  
  • Interviewing Mako technicians to gain expert insights into the system’s strengths and limitations.  
  • Reviewing literature on robot-assisted surgery practices.  

Key Findings and Outcomes  

The research led to several crucial insights and the development of practical tools to improve surgical workflows. Among the key findings:  

  • Effective teamwork is critical: Strong collaboration between medical professionals, particularly the medical practitioner specialist (MPS), scrub nurses, and surgeons, leads to smoother operations.  
  • Operational challenges persist: While Mako offers advanced capabilities, optimizing its integration into surgical teams remains a priority.  
  • Training enhances efficiency: Improved training programs for scrub nurses on Mako’s operation resulted in fewer disruptions and a more seamless workflow.  
  • Experience matters: Familiarity and consistency in working with the Mako system, especially between the surgeon and the MPS, optimise procedure flow.  
  • Operational improvements yield major gains: the most significant efficiency gains come from enhanced team coordination, trust-building, and workflow refinements rather than the technology itself.  

Looking Ahead: Next Steps in Research  

While this project has concluded, the research continues. ACC PhD researcher Jasper Vermeulen is now leading further studies to gain deeper insights into teamwork dynamics and workflow disruptions in robotic surgery. His work will build on these findings, further refining best practices for integrating robotic systems into hospital environments.  

The first findings of Jasper’s research have been presented at the Human-Robot Interaction 2025 (HRI 2025). The details can be found here: 

https://dl.acm.org/doi/10.5555/3721488.3721750 

With ongoing research, the potential for robotic-assisted surgery continues to expand, promising a more efficient and effective future for healthcare.  

Project Team:  

  • Dr Alan Burden, QUT  
  • Jasper Vermeulen, QUT 
  • Dr Stine Johansen, QUT 

Industry Representative: 

  • Dr Tom Williamson, Stryker 

Project Team

Jasper Vermeulen

PhD Researcher
QUT
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Stine S. Johansen

Alumni (Previously Postdoctoral Research Fellow (Human-Robot-Interaction Program))
Queensland University of Technology
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Tom Williamson

Industry Partner
Stryker
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