Artificial Intelligence: A New Tool in Operating Room Management. Role of Machine Learning Models in Operating Room Optimization
Artificial Intelligence: A New Tool in Operating Room Management. Role of Machine Learning Models in Operating Room Optimization
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DOI：
10.1007/s10916-019-1512-1
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发表时间：
2019-12-10
影响因子：
5.3
通讯作者：
Bignami, Elena
中科院分区：
文献类型：
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作者：
Bellini, Valentina;Guzzon, Marco;Bignami, Elena
我们对文献进行了系统回顾，以更好地了解新技术在围手术期的作用;特别是我们关注手术室（OR）的行政和管理角度。在2015年至2019年2月期间对成人（≥ 18岁）患者进行的研究被视为合格。共收录论文19篇。我们的评论表明，机器学习（ML）在OR组织领域的使用具有许多潜力。手术持续时间的预测获得了良好的性能;因此，它们的使用可以允许更精确的调度，限制资源浪费。ML能够支持更复杂的模型，可以同时协调多个空间，例如麻醉后监护室和手术室。人工智能的类型还可以用来限制另一个具有重要经济影响的组织问题：取消。随机森林已被证明可以有效地识别具有高取消风险的手术，从而可以计划预防措施，以相应地降低取消率。总之，尽管文献中的数据仍然有限，但我们相信ML在OR组织领域具有巨大的潜力;然而，需要进一步研究来评估这些新技术在围手术期医学中的有效作用。
We conducted a systematic review of literature to better understand the role of new technologies in the perioperative period; in particular we focus on the administrative and managerial Operating Room (OR) perspective. Studies conducted on adult (>= 18 years) patients between 2015 and February 2019 were deemed eligible. A total of 19 papers were included. Our review suggests that the use of Machine Learning (ML) in the field of OR organization has many potentials. Predictions of the surgical case duration were obtain with a good performance; their use could therefore allow a more precise scheduling, limiting waste of resources. ML is able to support even more complex models, which can coordinate multiple spaces simultaneously, as in the case of the post-anesthesia care unit and operating rooms. Types of Artificial Intelligence could also be used to limit another organizational problem, which has important economic repercussions: cancellation. Random Forest has proven effective in identifing surgeries with high risks of cancellation, allowing to plan preventive measures to reduce the cancellation rate accordingly. In conclusion, although data in literature are still limited, we believe that ML has great potential in the field of OR organization; however, further studies are needed to assess the effective role of these new technologies in the perioperative medicine.