Department of Science and Technology, Linköping University, Linköping, Sweden.
Anaesthesia. 2013 Nov;68(11):1148-55. doi: 10.1111/anae.12408. Epub 2013 Sep 13.
Intensive care capacity planning based on factual or forecasted mean admission numbers and mean length of stay without taking non-linearity and variability into account is fraught with error. Simulation modelling may allow for a more accurate assessment of capacity needs. We developed a generic intensive care simulation model using data generated from anonymised patient records of all admissions to four different hospital intensive care units. The model was modified and calibrated stepwise to identify important parameters and their values to obtain a match between model predictions and actual data. The most important characteristic of the final model was the dependency of admission rate on actual occupancy. Occupancy, coverage and transfers of the final model were found to be within 2% of the actual data for all four simulated intensive care units. We have shown that this model could provide accurate decision support for planning critical care resource requirements.
不考虑非线性和可变性而基于实际或预测的平均入院人数和平均住院时间进行重症监护能力规划充满了错误。模拟建模可能允许更准确地评估能力需求。我们使用从四个不同医院重症监护病房所有入院患者的匿名患者记录生成的数据开发了一个通用的重症监护模拟模型。该模型经过逐步修改和校准，以确定重要参数及其值，以实现模型预测与实际数据之间的匹配。最终模型的最重要特征是入院率对实际入住率的依赖性。最终模型的入住率、覆盖率和转院率在四个模拟重症监护病房中均与实际数据相差在 2%以内。我们已经表明，该模型可以为规划重症监护资源需求提供准确的决策支持。
