Economics and Management School, Panzhihua University, Panzhihua 617000, China.
Business School, University of Shanghai for Science and Technology, Shanghai 200093, China.
J Healthc Eng. 2022 Apr 14;2022:2921775. doi: 10.1155/2022/2921775. eCollection 2022.
Cost control is becoming increasingly important in hospital management. Hospital operating rooms have high resource consumption because they are a major part of a hospital. Thus, the optimal use of operating rooms can lead to high resource savings. However, because of the uncertainty of the operation procedures, it is difficult to arrange for the use of operating rooms in advance. In general, the durations of both surgery and anesthesia emergence determine the time requirements of operating rooms, and these durations are difficult to predict. In this study, we used an artificial neural network to construct a surgery and anesthesia emergence duration-prediction system. We propose an intelligent data preprocessing algorithm to balance and enhance the training dataset automatically. The experimental results indicate that the prediction accuracies of the proposed serial prediction systems are acceptable in comparison to separate systems.
成本控制在医院管理中变得越来越重要。医院手术室资源消耗量大，因为它是医院的主要部分。因此，手术室的最佳使用可以带来高资源节约。然而，由于手术程序的不确定性，很难提前安排手术室的使用。一般来说，手术和麻醉苏醒的持续时间决定了手术室的时间要求，而这些持续时间很难预测。在本研究中，我们使用人工神经网络构建了一个手术和麻醉苏醒持续时间预测系统。我们提出了一种智能数据预处理算法，能够自动平衡和增强训练数据集。实验结果表明，与单独的系统相比，所提出的串行预测系统的预测精度是可以接受的。
