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机器人辅助手术的医院学习曲线:基于人群的分析。

Hospital learning curves for robot-assisted surgeries: a population-based analysis.

机构信息

Division of General Surgery, Department of Surgery, University of Toronto, Toronto, Canada.

Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.

出版信息

Surg Endosc. 2024 Mar;38(3):1367-1378. doi: 10.1007/s00464-023-10625-6. Epub 2023 Dec 20.

Abstract

BACKGROUND

Robot-assisted surgery has been rapidly adopted. It is important to define the learning curve to inform credentialling requirements, training programs, identify fast and slow learners, and protect patients. This study aimed to characterize the hospital learning curve for common robot-assisted procedures.

STUDY DESIGN

This cohort study, using administrative health data for Ontario, Canada, included adult patients who underwent a robot-assisted radical prostatectomy (RARP), total robotic hysterectomy (TRH), robot-assisted partial nephrectomy (RAPN), or robotic portal lobectomy using four arms (RPL-4) between 2010 and 2021. The association between cumulative hospital volume of a robot-assisted procedure and major complications was evaluated using multivariable logistic models adjusted for patient characteristics and clustering at the hospital level.

RESULTS

A total of 6814 patients were included, with 5230, 543, 465, and 576 patients in the RARP, TRH, RAPN, and RPL-4 cohorts, respectively. There was no association between cumulative hospital volume and major complications. Visual inspection of learning curves demonstrated a transient worsening of outcomes followed by subsequent improvements with experience. Operative time decreased for all procedures with increasing volume and reached plateaus after approximately 300 RARPs, 75 TRHs, and 150 RPL-4s. The odds of a prolonged length of stay decreased with increasing volume for patients undergoing a RARP (OR 0.87; 95% CI 0.82-0.92) or RPL-4 (OR 0.77; 95% CI 0.68-0.87).

CONCLUSION

Hospitals may adopt robot-assisted surgery without significantly increasing the risk of major complications for patients early in the learning curve and with an expectation of increasing efficiency.

摘要

背景

机器人辅助手术已迅速普及。定义学习曲线对于告知认证要求、培训计划、确定快速和慢速学习者以及保护患者非常重要。本研究旨在描述常见机器人辅助手术的医院学习曲线。

研究设计

本队列研究使用加拿大安大略省的行政健康数据,纳入 2010 年至 2021 年间接受机器人辅助根治性前列腺切除术(RARP)、全机器人子宫切除术(TRH)、机器人辅助部分肾切除术(RAPN)或使用四个机械臂的机器人门腔静脉切开术(RPL-4)的成年患者。使用多变量逻辑模型评估机器人辅助手术的累计医院量与主要并发症之间的关联,调整患者特征和医院水平的聚类。

结果

共纳入 6814 例患者,其中 RARP、TRH、RAPN 和 RPL-4 队列分别有 5230、543、465 和 576 例患者。累计医院量与主要并发症之间无关联。学习曲线的直观检查显示,结果在初期出现短暂恶化,随后随着经验的增加而有所改善。随着手术量的增加,所有手术的手术时间都有所减少,并且在大约 300 例 RARP、75 例 TRH 和 150 例 RPL-4 之后达到平台期。接受 RARP(OR 0.87;95%CI 0.82-0.92)或 RPL-4(OR 0.77;95%CI 0.68-0.87)的患者,住院时间延长的几率随手术量的增加而降低。

结论

医院在学习曲线的早期采用机器人辅助手术可能不会显著增加患者发生主要并发症的风险,并期望提高效率。

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