Is robotic-assisted reverse shoulder arthroplasty economically justified? A break-even analysis

Robotic assistance in reverse total shoulder arthroplasty (rTSA) is likely to improve implant positioning and may reduce revision risk, but its cost-effectiveness is unknown. Break-even models can determine the economic viability of interventions in settings with low outcome event rates that would realistically preclude a randomized clinical trial. We applied this approach to determine the economic plausibility of robotic assistance for the prevention of revision after rTSA.

Incremental robotic assistance costs ($1,500), baseline early revision rates after rTSA (2.1%; within 1 year of surgery), and revision surgery-related costs ($22,920) were derived from institutional estimates and the literature. A break-even equation incorporating these variables was developed to determine the absolute risk reduction (ARR) in revision rate required for robotic assistance to be economically justified. The number needed to treat was calculated from the ARR. To provide a widely applicable model, multiple simulations were performed by varying the incremental cost of robotic assistance, baseline revision rate, and revision surgery cost.

Robotic assistance would be economically justified only if it prevented 1 revision for every 15 procedures (ARR = 6.55%). Because this required ARR exceeds the observed early revision rate (2.1%), the calculated break-even revision rate is negative (-4.45%), indicating that break-even cannot be achieved under typical clinical conditions. The required ARR remained unchanged when baseline revision rates were varied, but decreased substantially as the modeled cost of revision surgery increased.

Robotic assistance in rTSA is unlikely to be economically justified for routine use when evaluated solely on prevention of early postoperative revision. Selective application to higher-risk anatomy, costly failure pathways, or high-volume centers able to amortize robotic costs may improve economic viability, particularly when shoulder adoption leverages an existing robotic platform with lower incremental per-case costs rather than new capital investment. Because the value of positioning accuracy may accrue over time through delayed time-to-revision and better patient-centered outcomes, studies linking robotic assistance to longer-term implant survivorship and functional outcomes are needed to more fully define the technology's value proposition.