Objectives: The objective of this study was to assess the learning curve (LC) of robot-assisted lung segmentectomy and to evaluate hospital-related costs.
Methods: We conducted a retrospective study of Robot-assisted thoracic surgery (RATS) segmentectomies performed by 1 surgeon during 5 years. Perioperative and medical device data were collected. The LC, based on operating time, was assessed by Cumulative SUM analysis and an exponential model. Cost of care was estimated using the French National Cost Study method.
Results: One hundred and two RATS segmentectomies were included. The LC was completed at ∼30 procedures according to both models without significant difference in patients' characteristics before or after the LC. Mean operative time decreased from 136 min [95% confidence intervals (CI) 124-149] for the first 30 procedures to 97 min (95% CI 88-107) for the last 30 procedures. Mean length of stay decreased non-significantly (P = 0.10 for linear trend) from 8.1 days (95% CI 6.1-11.0) to 6.2 days (95% CI 4.9-7.9). The overall costs for the last 30 procedures as compared with the first 30 did not significantly decrease in the primary economic analysis but significantly decreased (P = 0.02) by €1271 (95% CI -2688 to +108, P = 0.02 for linear trend) after exclusion of 1 outlier (hospitalization-related costs > €10 000). After exclusion of this outlier, costs related to EndoWrist® instruments significantly decreased by €-135 (95% CI -220 to -35, P = 0.004), whereas costs related to clips decreased non-significantly (P = 0.28).
Conclusions: The LC was completed at ∼30 procedures. Inexperienced surgeons may have higher procedure costs, related to consumable medical devices and operating time.
Keywords: Cost-effectiveness; Learning curve; Robot; Segmentectomy; Thoracic surgery; Value.
© The Author(s) 2019. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.