概率预测每小时到达急诊室的人数
Bahman Rostami-Tabar1, Jethro Browell2, Ivan Svetunkov3
1Cardiff Business School, Cardiff University, Cardiff, UK.
Health systems (Basingstoke, England)
|May 27, 2024
概括
准确的每小时预测急救部门 (ED) 的到来对于高效的医院运营至关重要. 基于通用添加模型和指数平滑的新模型显著改善了ED到来预测.
科学领域:
- 医疗保健 运营 研究 研究 研究
- 时间序列预测时间序列预测
- 预测分析是一种预测分析.
背景情况:
- 准确的急救部门 (ED) 抵达预测对于有效的资源配置和患者需求管理至关重要.
- 目前的预测方法可能无法充分捕捉ED患者流动的复杂动态.
- 优化ED人员和单位配置需要可靠的,每小时到达预测.
研究的目的:
- 开发和评估用于每小时概率预测ED到达的先进模型.
- 将新型预测模型的准确性与已建立的基准进行比较.
- 评估开发的模型对其他医疗保健服务的通用性.
主要方法:
- 使用通用添加模型 (GAM) 开发预测模型.
- 基于指数级光滑的先进动态模型的实现.
- 48小时预测窗口的每小时概率预测.
- 与基准进行比较:TBATS,Poisson回归,Prophet和经验分布.
- 使用根平均二次误差 (RMSE),量子偏差,PinBall分数和Pinball技能分数进行准确度评估.
主要成果:
- 拟议的通用添加模型和指数级平滑模型与基准模型相比,显示出更高的预测准确性.
- 这些模型可提供可靠的每小时概率预测,预测ED到达的时间可提前48小时.
- 量化指标证实了点和分布预测的准确性提高.
结论:
- 开发的预测模型在预测ED的到来方面提供了显著的改进.
- 这些模型可以有效地概括为预测对其他医疗保健服务的需求,包括医院,救护车和临床服务台.
- 改进ED到达预测支持医疗机构更好的运营规划和资源管理.
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