UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Development of a patient and institutional-based model for estimation of operative times for robot-assisted radical cystectomy: results from the International Robotic Cystectomy Consortium

Hussein, AA; May, PR; Ahmed, YE; Saar, M; Wijburg, CJ; Richstone, L; Wagner, A; ... Guru, KA; + view all (2017) Development of a patient and institutional-based model for estimation of operative times for robot-assisted radical cystectomy: results from the International Robotic Cystectomy Consortium. BJU International , 120 (5) pp. 695-701. 10.1111/bju.13934. Green open access

[thumbnail of Kelly_OR times-FINAL.pdf]
Preview
Text
Kelly_OR times-FINAL.pdf - Accepted version

Download (411kB) | Preview

Abstract

OBJECTIVES: To design a methodology to predict operative times for robot-assisted radical cystectomy (RARC) based on variation in institutional, patient, and disease characteristics to help in operating room scheduling and quality control. PATIENTS AND METHODS: The model included preoperative variables and therefore can be used for prediction of surgical times: institutional volume, age, gender, body mass index, American Society of Anesthesiologists score, history of prior surgery and radiation, clinical stage, neoadjuvant chemotherapy, type, technique of diversion, and the extent of lymph node dissection. A conditional inference tree method was used to fit a binary decision tree predicting operative time. Permutation tests were performed to determine the variables having the strongest association with surgical time. The data were split at the value of this variable resulting in the largest difference in means for the surgical time across the split. This process was repeated recursively on the resultant data sets until the permutation tests showed no significant association with operative time. RESULTS: In all, 2 134 procedures were included. The variable most strongly associated with surgical time was type of diversion, with ileal conduits being 70 min shorter (P < 0.001). Amongst patients who received neobladders, the type of lymph node dissection was also strongly associated with surgical time. Amongst ileal conduit patients, institutional surgeon volume (>66 RARCs) was important, with those with a higher volume being 55 min shorter (P < 0.001). The regression tree output was in the form of box plots that show the median and ranges of surgical times according to the patient, disease, and institutional characteristics. CONCLUSION: We developed a method to estimate operative times for RARC based on patient, disease, and institutional metrics that can help operating room scheduling for RARC.

Type: Article
Title: Development of a patient and institutional-based model for estimation of operative times for robot-assisted radical cystectomy: results from the International Robotic Cystectomy Consortium
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/bju.13934
Publisher version: http://dx.doi.org/10.1111/bju.13934
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & Technology, Life Sciences & Biomedicine, Urology & Nephrology, robot-assisted, cystectomy, operative time, quality control, scheduling, LEARNING-CURVE, OUTCOMES, SURGEON, VALIDATION, PREDICTION, DURATION, IMPACT
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Targeted Intervention
URI: https://discovery.ucl.ac.uk/id/eprint/1560861
Downloads since deposit
87Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item