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Dedicated robotics team reduces pre-surgical preparation time

Gyan Pareek, MichaelS Lasser, ChintanK Patel, SammyE Elsamra, JosephF Renzulli, GeorgeE Haleblian

发表年份
2012
引用次数
29

摘要

CONTEXT: Robot-Assisted Laparoscopic Radical Prostatectomy (RALRP) requires significant preoperative setup time for the room, staff, and surgical platform. The utilization of a dedicated robotics operating room (OR) staff may facilitate efficiency and decrease costs. AIMS: We sought to determine the degree to which preoperative time decreased as experience was gained. MATERIALS AND METHODS: A total of 476 patients with a mean age of 60.2 years were evaluated (11/2006 to 1/2010). Data was assimilated through an institutional review board approved blinded, prospective database. Utilizing time from patient arrival in the OR to robot docking as preoperative preparation, our experience was evaluated. Age, body mass index (BMI), and American Society of Anesthesiologists risk scores (ASA) were compared. STATISTICAL ANALYSIS USED: Analysis of variance; Two-sample t-test for unequal variances. RESULTS: The first and last 100 cases were found to have similar age (P=0.27), BMI (P=0.11), and ASA (P=0.09). The average preoperative times were 66. 4 and 53.4 min, respectively (P<0.05). The second 100 patients treated were found to have a significantly shorter preoperative time when compared to the first 100 patients (P<0.05). When the first 100 cases were divided into cohorts of 10 cases the mean preoperative time for the first through fourth cohorts were 80.5, 69.3, 78.8, and 64.7 min, respectively. After treatment of our first 30 patients we found a significant drop in preoperative time. This persisted throughout the remainder of our experience. CONCLUSIONS: From the time of patient arrival a number of tasks are accomplished by the non-physician operating room staff during RALRP. The use of a consistent staff can decrease preoperative setup times and, therefore, the overall length of surgery.

关键词

MedicineBody mass indexAmerican society of anesthesiologistsRoboticsProspective cohort studySurgeryPhysical therapyInternal medicineRobotArtificial intelligence

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