The economic impact of robotic arthroplasty systems is a hurdle to adoption, despite the technology’s promise

Robotic-assisted total hip and knee arthroplasty (THA/TKA) has gained global traction, promising enhanced surgical precision and improved outcomes, despite initial hesitancy due to capital costs, longer setup times, and learning curves. However, these platforms require substantial initial investment before they can be implemented.

Walgrave et al determined that robotic systems typically cost $500,000 to $1 million per platform, with additional costs for annual maintenance and disposable instruments. A cost-modeling study from Hua and Salcedo found robotic-assisted TKA to be cost-effective only in centers performing ≥50 cases per year. High-volume hospitals can distribute costs more effectively, whereas lower-volume centers may struggle to recoup expenses unless the technology can help reduce rates of complications or revision surgeries.

Cost-value equation
Despite the high purchase price, robotic arthroplasty can be cost-competitive over an episode of care. Pierce et al conducted a 90-day Medicare analysis of >5,600 THAs and found that robotic cases had $785 less in total 90-day costs due to reduced post-acute care needs.

A five-year Markov model used by Maldonado et al projected robotic THA could save $945 (Medicare) to $1,810 (private payer) per patient. For TKA, the study found no significant difference in total hospital costs between robotic and manual approaches. Higher intraoperative costs for robotics (~$500 to $1,000 per case) were offset by shorter hospital stays and fewer complications.

In the largest study to date, published in 2021 in The Bone and Joint Journal, Emara et al reviewed the outcomes of more than 4 million cases in the U.S. healthcare system and reported a statistically significant reduction in length of stay with robotic THA, albeit without clinical significance. They also reported a reduction in early in-hospital dislocation rates following revision THA.

In a recent systematic review and meta-analysis of randomized, controlled trials by Alrajeb et al, robotic TKA showed superior postoperative anatomical and mechanical alignment compared to conventional methods. Despite this, clinical and functional outcomes, as well as complication rates, were similar between robotic and conventional TKA.

No consensus on the benefit of these systems has yet been reached, possibly because current evidence regarding each robotic system is diverse in quantity and quality. Each system has its own specificities and must be assessed for its own value, necessitating further long-term evaluations such as the U.K. RACER trials.

Efficiency
Robotic procedures initially take longer due to preoperative planning and intraoperative setup. Hoeffel et al found that robotic TKA was nine to 18 minutes longer than manual TKA. However, these time differences diminish with experience. A study by Kayani et al found a learning curve of about seven cases for robotic TKA, after which operative times approached conventional TKA. A systematic review on robotic THA by Hecht et al found that by 12 to 17 cases, operative times were equivalent to manual THA.

Robotic arthroplasty may also be associated with shorter hospital stays and faster recovery. Hoeffel et al reported a 14 percent reduction in length of stay and 74 percent greater likelihood to achieve same-day or next-day discharge to home with robotic TKA, with other studies reporting similar findings for robotic THA. According to Fontalis et al, the improved early recovery associated with robotic arthroplasty may stem from more precise implant positioning and soft-tissue handling, leading to less iatrogenic trauma and faster rehabilitation.

Workflow integration
Implementing a robotic system requires adjustments at multiple levels. Surgeons must undergo dedicated training, including manufacturer-led courses, simulation practice, and proctoring. OR teams must also adapt, with initial stress levels decreasing as familiarity increases.

Robotic arthroplasty may require advanced imaging (CT or radiographs). Although this improves preoperative planning, it adds cost and time. In the OR, robotic setup involves positioning the system, draping, and placing tracking arrays, requiring adjustments in workflow. Additionally, OR roles may change, sometimes requiring a dedicated technician to manage the system. However, after the initial learning curve, robotic cases can be performed with no additional staffing or time compared to manual arthroplasty, as reported by Londhe et al and Grau et al.

High-volume centers may employ checklists and preoperative coordination to maintain efficiency. Hospitals must adjust scheduling to accommodate robotic cases, potentially increasing turnover times initially. Some institutions cluster robotic cases on designated days to optimize efficiency. Although robotic procedures involve added costs from disposable instruments and imaging, careful budget planning can mitigate these expenses.

Additional efficiencies may be gained by reducing the number of trays and instruments opened, minimizing sterile-field clutter and inventory burden, as implant size and configuration are often predetermined with high precision.

Long-term viability
Robotic THA/TKA is transitioning from early adoption to mainstream practice, supported by improving economic and clinical evidence. Cost-effectiveness is achievable in high-volume centers that capitalize on shorter hospital stays and reduced complications. Initial costs remain high, but as competition increases and technology matures, prices may moderate as new options enter the market. Efficiency concerns have largely been addressed as robotic surgeries now approach conventional times, and challenges associated with workflow integration can be managed with proper training and system optimizations.

Although not every hospital or surgeon will adopt robotics immediately, the technology is proving to be a powerful ally in achieving high-quality outcomes in arthroplasty. As global experience with use of these tools accumulates, further research will refine best practices, ensuring that robotic-assisted surgery delivers on its promise of higher-value, precision-driven orthopaedic care.

Shujaa T. Khan, MD, is a clinical research fellow for adult reconstruction in the Department of Orthopaedic Surgery at Cleveland Clinic.

Ahmed K. Emara, MD, is an orthopaedic surgery resident at Cleveland Clinic. Dr. Emara is the Education Committee chair of the AAOS Resident Delegate Executive Committee and a member of the AAOS Now Editorial Board.

Ignacio Pasqualini, MD, is an orthopaedic surgery resident at Cleveland Clinic.

Matthew Deren, MD, is an orthopaedic surgeon and director of the Adult Reconstruction Fellowship at Cleveland Clinic.

Nicolas S. Piuzzi, MD, is vice chair of research and associate professor in the Department of Orthopaedic Surgery at Cleveland Clinic. Dr. Piuzzi is also codirector of the Musculoskeletal Research Center, director of the Cleveland Clinic Adult Reconstruction Research Program, and executive editor of The Journal of Bone & Joint Surgery.

References

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