Minimum caseload for cost-effective robotic-assisted surgery: a systematic review

Robotic-assisted surgery (RAS) has been increasingly adopted across surgical specialties due to its potential clinical benefits. However, the high fixed and variable costs associated with robotic platforms raise concerns regarding economic sustainability. Procedural volume is frequently cited as a key determinant of cost-effectiveness; however, reported minimum caseload thresholds vary widely across surgical specialties, robotic platforms, and healthcare settings. This systematic review aims to synthesise the available evidence on cost-effectiveness thresholds and annual surgical volumes associated with the economic viability of the da Vinci and Mako robotic systems. Searches were conducted in MEDLINE (via PubMed), Embase, and the Cochrane Library. Two independent reviewers performed study selection and data extraction. Studies reporting minimum procedural volume thresholds and/or cost-effectiveness outcomes for da Vinci or Mako robotic systems were included. Results were synthesised descriptively and stratified by surgical specialty and robotic platform. Ten studies met the inclusion criteria, encompassing orthopaedic, urologic, colorectal, and head and neck surgery. Reported minimum procedural volume thresholds varied substantially, ranging from approximately 40 to 300 cases per year. This heterogeneity reflected differences in surgical specialty, robotic platform, study design, economic perspective, and underlying modelling assumptions. Across studies, high-volume centres were more consistently associated with favourable cost-effectiveness profiles, whereas findings in low- and intermediate-volume settings were highly variable and context dependent. The cost-effectiveness of robotic-assisted surgery is strongly influenced by procedural volume but remains highly context dependent. No single minimum caseload threshold can be generalised across surgical specialties or robotic platforms. Reported volume thresholds should therefore be interpreted within specific clinical, organisational, and economic contexts when informing decisions regarding investment in robotic surgical systems.