From the Department of Mathematics, University of Waterloo, Waterloo, Ont. (N. Rozario); and the Oakville Trafalgar Memorial Hospital, Oakville, Ont. (D. Rozario)
From the Department of Mathematics, University of Waterloo, Waterloo, Ont. (N. Rozario); and the Oakville Trafalgar Memorial Hospital, Oakville, Ont. (D. Rozario).
Can J Surg. 2020 Nov-Dec;63(6):E527-E529. doi: 10.1503/cjs.016520.
The cancellation of large numbers of surgical procedures because of the coronavirus disease 2019 (COVID-19) pandemic has drastically extended wait lists and negatively affected patient care and experience. As many facilities resume clinical work owing to the currently low burden of disease in our community, we are faced with operative booking protocols and procedures that are not mathematically designed to optimize efficiency. Using a subset of artificial intelligence called "machine learning," we have shown how the use of operating time can be optimized with a custom Python (a high-level programming language) script and an open source machine-learning algorithm, the ORTools software suite from the Google AI division of Alphabet Inc. This allowed the creation of customized models to optimize the efficiency of operating room booking times, which resulted in a reduction in nursing overtime of 21% - a theoretical cost savings of $469 000 over 3 years.
由于 2019 年冠状病毒病(COVID-19)大流行,大量外科手术被取消,这大大延长了等候名单,并对患者护理和体验产生了负面影响。由于目前我们社区疾病负担较低,许多医疗机构恢复了临床工作,因此我们面临的手术预约协议和程序在数学上并不是为了优化效率而设计的。我们使用一种称为“机器学习”的人工智能子集,展示了如何使用定制的 Python(一种高级编程语言)脚本和一个开源机器学习算法(来自谷歌 AI 部门的 Alphabet Inc 的 ORTools 软件套件)来优化手术时间的使用。这使得创建定制模型以优化手术室预订时间的效率成为可能,从而减少了 21%的护理加班时间——理论上在 3 年内节省了 46.9 万美元的成本。