TY - JOUR
T1 - Real-time assessment of learning curve for robot-assisted laparoscopic prostatectomy
AU - Tamhankar, Ashwin Sunil
AU - Spencer, Neil
AU - Hampson, Alex
AU - Noël, J. P.
AU - El-Taji, Omar
AU - Arianayagam, Ranjan
AU - McNicholas, Thomas
AU - Boustead, Gregory
AU - Lane, Tim M.
AU - Adshead, James
AU - Vasdev, Nikhil
PY - 2020/11
Y1 - 2020/11
N2 - Introduction: The learning curves analysed to date for robot-assisted laparoscopic prostatectomy are based on arbitrary cut-offs of the total cases.
Methods: We analysed a large dataset of robot-assisted laparoscopic prostatectomies from a single centre between 2008 and 2019 for assessment of the learning curve for perioperative outcomes with respect to time and individual cases.
Results: A total of 1,406 patients were evaluated, with mean operative time 198.08 minutes and mean console time 161.05 minutes. A plot of operative time and console time showed an initial decline followed by a near-constant phase. The inflection points were detected at 1,398 days (308th case) for operative time and 1,470 days (324th case) for console time, with a declining trend of 8.83 minutes and 7.07 minutes, respectively, per quarter-year (p<0.001). Mean estimated blood loss showed a 70.04% reduction between the start (214.76ml) and end (64.35ml) (p<0.001). The complication rate did not vary with respect to time (p=0.188) or the number of procedures (p=0.354). There was insufficient evidence to claim that the number of operations (p=0.326), D’Amico classification (p=0.114 for intermediate versus low; p=0.158 for high versus low) or time (p=0.114) was associated with the odds of positive surgical margins.
Conclusions: It takes about 300 cases and nearly 4 years to standardise operative and console times, with a requirement of around 80 cases per annum for a single surgical team in the initial years to optimise the outcomes of robot-assisted laparoscopic prostatectomy.
AB - Introduction: The learning curves analysed to date for robot-assisted laparoscopic prostatectomy are based on arbitrary cut-offs of the total cases.
Methods: We analysed a large dataset of robot-assisted laparoscopic prostatectomies from a single centre between 2008 and 2019 for assessment of the learning curve for perioperative outcomes with respect to time and individual cases.
Results: A total of 1,406 patients were evaluated, with mean operative time 198.08 minutes and mean console time 161.05 minutes. A plot of operative time and console time showed an initial decline followed by a near-constant phase. The inflection points were detected at 1,398 days (308th case) for operative time and 1,470 days (324th case) for console time, with a declining trend of 8.83 minutes and 7.07 minutes, respectively, per quarter-year (p<0.001). Mean estimated blood loss showed a 70.04% reduction between the start (214.76ml) and end (64.35ml) (p<0.001). The complication rate did not vary with respect to time (p=0.188) or the number of procedures (p=0.354). There was insufficient evidence to claim that the number of operations (p=0.326), D’Amico classification (p=0.114 for intermediate versus low; p=0.158 for high versus low) or time (p=0.114) was associated with the odds of positive surgical margins.
Conclusions: It takes about 300 cases and nearly 4 years to standardise operative and console times, with a requirement of around 80 cases per annum for a single surgical team in the initial years to optimise the outcomes of robot-assisted laparoscopic prostatectomy.
U2 - 10.1308/rcsann.2020.0139
DO - 10.1308/rcsann.2020.0139
M3 - Article
SN - 0035-8843
VL - 102
SP - 717
EP - 725
JO - Annals of the Royal College of Surgeons of England
JF - Annals of the Royal College of Surgeons of England
IS - 9
ER -