The first time I scrubbed to a robotic arthroplasty list, I made the same assumption most trainees make. I assumed the technology would do something recognisable — that I would watch it operate, and learn from watching. What I actually learned is that robotic surgery doesn’t work that way, and understanding why changes how useful you are on that list.
Three things I wish someone had told me first.
1. The robot executes the plan. It doesn’t make it.
This sounds obvious until you are standing at the operating table watching a robotic arm constrain the cutting guide to within one degree of the preoperative target, and realise you never asked whose target that was or how it was derived.
Robotic arthroplasty systems — Mako, ROSA, and their equivalents — work by enforcing a preoperatively defined plan based on CT imaging. The system constrains the surgeon’s movements to the planned resection zone. It does not deviate from that plan, which means it has no mechanism for correcting a plan that was wrong to begin with.
If the CT segmentation is inaccurate, the robot executes that inaccuracy with precision. If the alignment philosophy chosen in the planning software doesn’t suit the patient’s anatomy, the robot produces that mismatch reliably. One Edinburgh meta-analysis found no learning curve for component positioning accuracy on robotic TKA — the robot hits the plan from case one (Zhang et al., 2021). That is a statement about the system’s consistency, not about the quality of the plan it is executing.
Before your first robotic list: ask to review the preoperative plan. Understand the alignment targets. Know what decisions were made before the patient reached the table.
2. More accurate does not mean better — yet.
The evidence for robotic arthroplasty improving component positioning accuracy is consistent. The evidence for that accuracy translating into better patient outcomes is not.
A 2023 systematic review and meta-analysis of 14 randomised controlled trials found no overall superiority in clinical or radiological outcomes for robotic TKA compared to conventional TKA, with robotic cases taking a mean of 15.3 minutes longer (Bensa et al., 2023). An updated meta-analysis of 2,863 patients reached a similar conclusion: better alignment, no better functional scores — and at follow-up beyond six months, conventional TKA outcomes were marginally ahead (Fu et al., 2024).
The intuitive logic — precision leads to better results — is not wrong in principle. It may simply be that current follow-up periods are too short, or that mechanical alignment itself is the wrong target regardless of how accurately it is achieved. Either way, the claim that robotic surgery produces better knees is not yet supported by the evidence we have. Knowing that makes you a more useful person in the room when a patient or colleague asks.
3. The judgement moves — it doesn’t disappear.
Trainees on early robotic lists sometimes disengage. The cutting is constrained. The arm does what the plan says. There is less obvious manual skill on display than in conventional surgery, and it can feel like there is less to learn.
That misreads what robotic surgery actually demands. The judgement that previously happened at the saw — responding to unexpected anatomy, adjusting alignment feel intraoperatively, making decisions about soft tissue balance in real time — still has to happen. It happens earlier, in the planning phase, and it happens in the discussions that surround the plan. Which alignment philosophy? How to handle a patient with significant pre-existing deformity? What to do when the intraoperative anatomy doesn’t match the CT?
Those decisions are not robotic. They are surgical. The robot relocates where the judgement is required; it does not eliminate the requirement.
On a robotic list, the most instructive thing a trainee can do is not watch the arm. It is to understand every decision that was made before the patient arrived in theatre — and why.
For the evidence behind robotic systems in arthroplasty, see Mako, ROSA, and the rest: what the robotic revolution means for your training.
References
- Zhang J, Ndou WS, Ng N, et al. Robotic-arm assisted total knee arthroplasty is associated with improved accuracy and patient reported outcomes: a systematic review and meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2021;30(8):2677–2695. https://doi.org/10.1007/s00167-021-06464-4
- Bensa A, Sangiorgio A, Deabate L, et al. Robotic-assisted mechanically aligned total knee arthroplasty does not lead to better clinical and radiological outcomes when compared to conventional TKA: a systematic review and meta-analysis of randomized controlled trials. Knee Surg Sports Traumatol Arthrosc. 2023;31(11):4680–4691. https://doi.org/10.1007/s00167-023-07458-0
- Fu X, She Y, Jin G, et al. Comparison of robotic-assisted total knee arthroplasty: an updated systematic review and meta-analysis. J Robot Surg. 2024;18(1):292. https://doi.org/10.1007/s11701-024-02045-y