Department of Engineering Science, The University of Auckland, 70 Symonds Street,Auckland, New Zealand.
Department of Engineering Science, The University of Auckland, 70 Symonds Street,Auckland, New Zealand.
Comput Methods Programs Biomed. 2023 Jun;235:107541. doi: 10.1016/j.cmpb.2023.107541. Epub 2023 Apr 11.
Predicting the duration of surgical procedures is an important step in scheduling operating rooms. Many factors have been shown to influence the duration of a procedure, in this research we aim to use medical ontological information to improve the predictions.
This paper presents two methods for incorporating the medical information about a surgical procedure into the prediction of the duration of the procedure. The first method uses the Systematised Nomenclature of Medicine Clinical Terms to relate different procedures to each other. The second uses simple text fragments. The relationships between types of procedures are included in a regression model for the procedure duration. These methods are applied to data from New Zealand healthcare facilities and the accuracy of the estimations of the durations is compared. In addition a simulation of scheduling the procedures in an operating room is performed.
It is shown that both of the methods provide an improvement in the prediction of procedure durations. When compared to a traditional categorical encoding, the ontological information provides an improvement in the continuous ranked probability scores of the prediction of procedure durations from 18.4 min to 17.1 min, and from 25.3 to 21.3 min for types of procedures that are not performed very often.
Different methods for encoding medical ontological information in surgery procedure duration predictions are presented, and show an improvement over traditional models. The improvement in duration prediction is shown to improve the efficiency of scheduling in a simple simulation.
预测手术过程的持续时间是安排手术室的重要步骤。许多因素已被证明会影响手术过程的持续时间，本研究旨在利用医学本体论信息来改进预测。
本文提出了两种将手术过程的医学信息纳入过程持续时间预测的方法。第一种方法使用系统命名法医学临床术语将不同的过程相互关联。第二种方法使用简单的文本片段。过程类型之间的关系包含在过程持续时间的回归模型中。这些方法应用于新西兰医疗设施的数据，并比较了持续时间估计的准确性。此外，还对手术室中的手术进行了调度模拟。
结果表明，这两种方法都可以提高手术持续时间的预测精度。与传统的分类编码相比，本体论信息将手术持续时间预测的连续等级概率得分从 18.4 分钟提高到 17.1 分钟，对于不太常见的手术类型，从 25.3 分钟提高到 21.3 分钟。
本文提出了不同的方法来对手术过程持续时间预测中的医学本体论信息进行编码，并证明了其优于传统模型。持续时间预测的改进表明，在简单的调度模拟中可以提高调度效率。
