Jain Monica, Fry Brian T, Hess Luke W, Anger Jennifer T, Gewertz Bruce L, Catchpole Ken
Department of Surgery, Cedars Sinai Medical Center, Los Angeles, California.
University of Michigan Medical School, Ann Arbor, Michigan.
J Surg Res. 2016 Oct;205(2):296-304. doi: 10.1016/j.jss.2016.06.092. Epub 2016 Jul 4.
Robotic surgery offers advantages over conventional operative approaches but may also be associated with higher costs and additional risks. Analyzing surgical flow disruptions (FDs), defined as "deviations from the natural progression of an operation," can help target training techniques and identify opportunities for improvement.
Thirty-two robotic surgery operations were observed over a 6-wk period at one 900-bed surgical center. FDs were recorded in detail and classified into one of 11 different categories. Procedure type, robot model, and resident involvement were also recorded. Linear regression analyses were used to evaluate the effects of these parameters on FDs and operative duration.
Twenty-one prostatectomies, eight sacrocolpopexies, and three nephrectomies were observed. The mean number of FDs was 48.2 (95% confidence interval [CI] 38.6-54.8 FDs), and mean operative duration was 163 min (95% CI 148-179 min). Each FD added 2.4 min (P = 0.025) to a case's total operative duration. The number and rate of FDs were significantly affected by resident involvement (P = 0.008 and P = 0.006, respectively). Resident cases demonstrated mostly training, equipment, and robot switch FDs, whereas nonresident cases demonstrated mostly equipment, instrument changes, and external factor FDs.
Although the FDs encountered in resident training are more frequent, they may not significantly increase operative duration. Other FDs, such as equipment or external factors, may be more impactful. Limiting these specific FDs should be the focus of performance improvement efforts.
机器人手术比传统手术方法具有优势,但也可能伴随着更高的成本和额外风险。分析手术流程中断(FDs),即定义为“手术自然进程的偏差”,有助于确定培训技术的目标并识别改进机会。
在一家拥有900张床位的外科中心,在6周时间内观察了32例机器人手术操作。详细记录了FDs,并将其分为11种不同类别之一。还记录了手术类型、机器人型号和住院医师参与情况。使用线性回归分析来评估这些参数对FDs和手术持续时间的影响。
观察了21例前列腺切除术、8例骶骨阴道固定术和3例肾切除术。FDs的平均数量为48.2(95%置信区间[CI] 38.6 - 54.8次FDs),平均手术持续时间为163分钟(95% CI 148 - 179分钟)。每次FD使病例的总手术持续时间增加2.4分钟(P = 0.025)。FDs的数量和发生率受住院医师参与情况的显著影响(分别为P = 0.008和P = 0.006)。住院医师参与的病例主要表现为培训、设备和机器人切换方面的FDs,而非住院医师参与的病例主要表现为设备、器械更换和外部因素方面的FDs。
尽管住院医师培训中遇到的FDs更频繁,但它们可能不会显著增加手术持续时间。其他FDs,如设备或外部因素,可能影响更大。限制这些特定的FDs应成为性能改进工作的重点。