Ravivarapu Krishna T, Omidele Olamide, Pfail John, Tomer Nir, Small Alexander C, Palese Michael A
Department of Urology, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, Box 1272, New York, NY, 10029, USA.
J Robot Surg. 2021 Aug;15(4):627-633. doi: 10.1007/s11701-020-01152-w. Epub 2020 Oct 3.
The factors driving early adoption of robotic-assisted simple prostatectomy (RASP) for large gland BPH have not yet been identified. This study aims to determine the patient, provider, and facility level differences and predictors in undergoing RASP versus OSP. This population-based cohort study used data from the all-payer New York State Statewide Planning and Research Cooperative System (SPARCS) database. Patient, provider, and facility characteristics for each cohort were analyzed, and a multivariate analysis was conducted to identify predictive factors associated with undergoing RASP versus OSP. From 2009 to 2017, 1881 OSP and 216 RASP cases were identified. RASP utilization increased from 2.6% of all cases in 2009 to 16.8% in 2017. Patient demographics were similar between both cohorts. Median length of stay was shorter for RASP patients (3 vs. 4 days, p < 0.001), and OSP was associated with a long length of stay (> 7 days) (p < 0.001). There were no significant differences in 30- and 90-day readmission rates or 1-year mortality. More OSP patients were discharged to continued care facilities than RASP patients (p = 0.049), and more RASP patients were discharged to home compared to OSP patients (p = 0.035). Positive predictors for undergoing RASP included teaching hospital status, medium and high hospital bed volume, high hospital operative volume, high surgeon volume, and surgeons that graduated within 15 years of surgery. As RASP shows favorable perioperative outcomes, the diffusion of robotic technology and newer graduates entering the workforce may augment the upward trend of RASP utilization.
推动大腺体良性前列腺增生症患者早期采用机器人辅助单纯前列腺切除术(RASP)的因素尚未明确。本研究旨在确定接受RASP与开放性耻骨后前列腺切除术(OSP)的患者、医疗服务提供者和机构层面的差异及预测因素。这项基于人群的队列研究使用了来自纽约州全支付方全州规划与研究合作系统(SPARCS)数据库的数据。分析了每个队列的患者、医疗服务提供者和机构特征,并进行多变量分析以确定与接受RASP或OSP相关的预测因素。2009年至2017年,共识别出1881例OSP病例和216例RASP病例。RASP的使用率从2009年占所有病例的2.6%增至2017年的16.8%。两个队列的患者人口统计学特征相似。RASP患者的中位住院时间较短(3天对4天,p<0.001),而OSP与较长住院时间(>7天)相关(p<0.001)。30天和90天再入院率或1年死亡率无显著差异。与RASP患者相比,更多OSP患者出院后前往持续护理机构(p=0.049),与OSP患者相比,更多RASP患者出院后回家(p=0.035)。接受RASP的积极预测因素包括教学医院状态、中等和高医院床位数量、高医院手术量、高外科医生手术量以及在手术15年内毕业的外科医生。由于RASP显示出良好的围手术期结果,机器人技术传播以及新毕业生进入劳动力市场可能会增强RASP使用率的上升趋势。