Robotic technology has made joint replacement surgery more precise. The more difficult question is whether greater precision consistently translates into outcomes that patients can actually feel.
That question sits at the center of Episode 53 of The Joint Replacement Podcast, featuring Professor Fares Haddad, Professor of Orthopaedic and Sports Surgery at University College London and Editor-in-Chief of The Bone & Joint Journal. His career spans primary and revision arthroplasty, sports surgery, joint preservation, research, and the treatment of elite athletes. In our conversation, we discussed how those different perspectives have shaped his approach to modern hip and knee replacement.
From elite athletes to personalized joint replacement
One of the most interesting themes of our discussion was the influence of sports medicine on arthroplasty.
Professor Haddad described how treating elite athletes requires unusually detailed attention to planning, decision-making, surgery, rehabilitation, and individual expectations. He sees modern arthroplasty moving in a similar direction: away from applying the same operation to every patient and toward increasingly personalized treatment.
That shift has changed his own practice. Compared with 15 years ago, he now uses substantially more three-dimensional planning and CT imaging. In hip replacement, he pays greater attention to the relationship between the spine, pelvis, and component position. In knee replacement, his practice has evolved toward more partial knee replacement, greater preservation of the cruciate ligaments, and increasing use of cementless fixation.
His broader message was equally important: what surgeons learn during residency or fellowship should not become permanent dogma. Surgical practice has to evolve as better evidence emerges.
Questioning old surgical dogma
Professor Haddad used periprosthetic joint infection as an example of how dramatically thinking can change.
During his fellowship training in Vancouver, two-stage revision was a dominant strategy for infection. Over time, however, his perspective has shifted toward greater use of single-stage revision in appropriately selected patients, in part because of the morbidity associated with undergoing two major operations.
Perhaps the most important change is how success itself is defined. Historically, an infection outcome might have been determined primarily by the surgeon or microbiologist. Increasingly, Haddad argues, the patient should define whether the treatment was successful.
Mechanical alignment may no longer be the only target
Few topics in knee replacement generate as much discussion today as alignment.
Mechanical alignment remains widely used, but Haddad described his current philosophy as closer to individualized or functional alignment. His goal is generally to preserve anatomy where possible, maintain joint-line obliquity, respect medial collateral ligament isometry, and minimize unnecessary soft-tissue releases while remaining within defined boundaries.
He also emphasized that alignment should not be reduced to a single coronal-plane number. The knee is a three-dimensional structure, and component positioning, patellofemoral mechanics, ligament balance, and patient-specific anatomy all potentially matter.
This becomes especially important when evaluating robotics. A robot can execute a plan extremely precisely, but precision is only beneficial if the target itself is appropriate.
Why partial knee replacement may be an ideal application for robotics
The centerpiece of the episode was Professor Haddad’s recent randomized trial comparing conventional jig-based medial unicompartmental knee arthroplasty with robotic-arm-assisted UKA. The prospective double-blinded randomized trial was published in The Bone & Joint Journal in September 2026.
Haddad believes partial knee replacement may be particularly well suited to technological assistance because the operation is technically demanding.
When arthritis is isolated to a single compartment, a partial knee allows the surgeon to preserve substantially more of the patient’s native knee. But success depends on accurately resurfacing the diseased compartment while respecting the remaining anatomy, ligament balance, and alignment.
As Haddad put it during our conversation, there are many ways to get a partial knee wrong. Errors in component positioning or excessive correction can potentially contribute to failure or progression of arthritis elsewhere in the knee.
His randomized study found significant differences in implant positioning between the robotic and conventional groups, which was one of the central technical outcomes of the trial. Haddad also highlighted differences in patient-reported outcomes and the increasing preference of both patients and surgeons for the robotic pathway during the study.
An important limitation: robotics and implant design were both different
The trial also raises an important methodological issue.
The robotic and conventional groups did not use identical implant systems. The conventional arm used a well-established mobile-bearing partial knee, while the robotic system used a different implant with CT-based planning.
That makes it difficult to attribute every difference exclusively to robotic assistance.
Professor Haddad readily acknowledged this limitation. Ideally, a trial could compare robotic and manual implantation of exactly the same prosthesis. However, many robotic platforms remain tied to specific implant systems, making this type of comparison difficult.
It is an important reminder that studies evaluating surgical technology frequently test an entire treatment pathway rather than one isolated variable.
What about the negative randomized trials of robotic total knee replacement?
The discussion becomes more complicated when total knee replacement is considered.
The recently published RACER-Knee trial randomized 339 patients across ten hospitals in Great Britain to robotic-arm-assisted or conventional total knee replacement. At one year, mean Forgotten Joint Scores were 49.2 after robotic surgery and 50.2 after conventional surgery, with no clinically meaningful advantage for the robotic group. The robotic pathway was also more expensive in that pragmatic trial.
Another major trial, RASKAL, randomized 303 patients using a 2×2 design comparing robotic-assisted versus computer-assisted surgery and functional versus mechanical alignment. At two years, investigators found no significant improvement in KOOS-12 or several other patient-reported outcomes with robotics compared with computer navigation. Robotics did, however, shorten mean operating time by 11.5 minutes and was associated with less macroscopic PCL injury.
These studies create an important distinction: greater technical accuracy does not automatically guarantee better short-term patient-reported outcomes.
Was RACER testing the technology—or the target?
Professor Haddad offered an important interpretation of RACER during our discussion.
RACER was intentionally designed as a pragmatic study involving 33 surgeons and centers without established robotic programs at the beginning of the trial. The robotic procedures largely targeted mechanical alignment.
Haddad’s argument is that one potential advantage of robotics is the ability to accurately reproduce individualized alignment strategies. If robotics are primarily used to reproduce the same mechanical alignment target achievable with conventional instrumentation, the trial may be testing the execution technology without fully testing one of its potential advantages.
He also emphasized that RACER reported the primary outcome at one year. If improved component positioning affects implant longevity or later function, those differences might require longer follow-up to detect.
That interpretation does not invalidate the RACER results. Rather, it highlights the distinction between pragmatic trials that ask whether a technology improves outcomes across routine practice and tightly controlled mechanistic trials that investigate whether a specific surgical strategy produces a measurable biological or functional effect.
The real challenge may be determining where to put the implants
This may be the most important issue facing robotic joint replacement.
Modern robotic systems are already capable of extremely reproducible execution. But the surgeon still decides what the robot should execute.
Haddad argues that future progress will therefore require more sophisticated understanding of the patient’s three-dimensional anatomy, soft tissues, gait, and native knee phenotype rather than simply improving bone-cut accuracy.
He envisions predictive analytics eventually combining preoperative anatomy, CT imaging, intraoperative robotic data, component positioning, soft-tissue information, and patient-reported outcomes to help determine the optimal target for an individual patient.
That represents an important evolution in the robotics debate.
The question may eventually become less:
“Can the robot put the implant exactly where we planned?”
and more:
“Where should we have planned to put it for this particular patient?”
Are we measuring the right outcomes?
Another fascinating part of Haddad’s partial knee study involved differences between patient-reported outcome measures.
He believes the Forgotten Joint Score can be particularly useful in high-functioning patients because some traditional knee scores suffer from a ceiling effect. Once patients are functioning relatively well, those instruments may have difficulty distinguishing a good result from an exceptional one.
This becomes especially relevant when evaluating modern joint replacement technologies.
If both treatment groups achieve generally good outcomes, a traditional score may show little separation even if one group is more likely to reach the point where the patient rarely thinks about the artificial joint.
Determining which outcome measures best capture meaningful differences will therefore remain a major part of arthroplasty research.
How should surgeons evaluate new technology?
As Editor-in-Chief of The Bone & Joint Journal, Professor Haddad evaluates orthopedic research from a perspective few practicing surgeons have.
His starting point is methodological skepticism—whether a study reports positive or negative findings.
He looks closely at trial design, potential conflicts of interest, whether the investigators developing a technique may achieve results that are difficult for other surgeons to reproduce, and whether conclusions are truly supported by the methodology.
It is particularly relevant in an era when surgeons encounter information not only through peer-reviewed journals but also conferences, industry presentations, social media, podcasts, and online commentary.
The challenge is no longer simply finding information. It is deciding which information deserves to change clinical practice.
So, is robotic knee replacement actually better?
When I asked Professor Haddad the question patients increasingly bring to clinic—“Is robotic joint replacement better than regular joint replacement?”—his answer was appropriately nuanced.
He believes robotics improves his own planning and execution and that his center has seen benefits. But he also acknowledged that high-quality trials such as RACER and RASKAL have not demonstrated universal superiority in patient-reported outcomes.
That distinction matters.
The current evidence strongly supports the conclusion that robotic technology can improve surgical precision. A 2026 critical review of robotic TKA similarly found that improved technical or radiographic accuracy is among the most consistent findings across the literature.
Whether those gains produce better pain, function, satisfaction, implant longevity, or cost-effectiveness for every patient remains less certain.
And the answer may ultimately differ between partial knee replacement, routine total knee replacement, complex deformity, and revision surgery.
Robotics may eventually matter most in the hardest cases
Interestingly, Haddad believes orthopedic surgery may have initially approached robotics backward.
Rather than beginning with the most difficult operations, arthroplasty surgeons have largely introduced robotics into straightforward primary cases.
Other surgical specialties have sometimes taken the opposite approach, using robotic technology to accomplish procedures that are difficult or impossible through traditional techniques.
Haddad sees the greatest future value of orthopedic robotics potentially emerging in complex cases: severe hip dysplasia, conversion of fused joints, post-traumatic deformity, difficult primary arthroplasty, and revision surgery.
Routine cases may therefore serve another purpose: allowing surgeons and operating-room teams to master the technology before deploying it when precision and planning become even more important.
The bigger question
Episode 53 ultimately became less about whether surgeons should be “pro-robot” or “anti-robot” and more about what comes next.
Robotics can make surgery increasingly precise.
But precision alone is not the final destination.
The next generation of joint replacement may depend on combining precise execution with better targets, better understanding of soft-tissue behavior, better implant designs, predictive analytics, and more sophisticated patient-reported outcome measurement.
Professor Haddad’s perspective captures that evolution well: technology should not replace surgical thinking. It should give surgeons better tools to execute increasingly individualized decisions.
And perhaps the most important question for the next decade of joint replacement is not simply whether we can perform the operation more precisely.
It is whether we can determine what precision should be aiming at.
References
- Kayani B, Fontalis A, Tahmassebi J, et al. A prospective double-blinded randomized controlled trial comparing conventional jig-based versus robotic arm-assisted medial unicompartmental knee arthroplasty. Bone Joint J. 2026;108-B(9):1113-1120. doi:10.1302/0301-620X.108B9.BJJ-2025-1481.R1.
- Griffin J, Davis ET, Parsons H, et al. Robotic-arm-assisted versus conventional total knee replacement (RACER-Knee): a pragmatic, multicentre, participant-masked and assessor-masked, superiority, randomised controlled trial. 2026.
- MacDessi SJ, Wernecke GC, Ghadirinejad K, et al. Robotic-assisted surgery and functional alignment in total knee arthroplasty: the RASKAL registry-nested 2 × 2 factorial randomized trial. Bone Joint J. 2026;108-B:622-633. doi:10.1302/0301-620X.108B.BJJ-2025-1472.R2.
- Robotic-assisted total knee arthroplasty: accuracy, clinical outcomes, complications, learning curve and cost-effectiveness: a critical clinical review. 2026.