鱼类模型预测急性电脑中风患者的呼叫量
Joe Van Duren1, H Adrian Puttgen1, Julie Martinez1
1Department of Neurology, Intermountain Healthcare, Murray, Utah, USA.
概括
波桑模型准确地预测了电脑中风呼叫量,帮助人员处理时间敏感的中风护理. 这种方法可以优化医生分配在任何健康系统的已知呼叫量.
科学领域:
- 神经学 神经学
- 医疗保健服务研究 医疗服务研究
- 生物统计学 生物统计学
背景情况:
- 有效的人员配置对于管理时间敏感的中风至关重要.
- 预测远程中风和远程神经神经病咨询频率对于资源分配至关重要.
研究的目的:
- 评估Poisson分布适用于模拟每小时的电脑电击呼叫量.
- 开发一个24小时内对远程冲击呼叫频率的预测模型.
主要方法:
- 8,499次远程中风激活的回顾性队列审查 (2019年1月至2022年12月).
- 使用波桑概率质量函数 (PMF) 和累积分布函数 (CDF) 分析呼叫频率.
- 应用一个变量Poisson回归来预测未来的呼叫量.
主要成果:
- 波桑分布表现出与观察到的远程电话呼叫数据密切匹配.
- 平均每天的电话范围从0.07 (上午5-6点) 到0.45 (下午7-8点).
- 每天两次或更少的电话预测概率在98.9%至99.9%之间;未来的电话预计将增加.
结论:
- 波桑建模是一种可靠的方法,用于预测电脑电话电话量.
- 这种预测能力可以实时为人员决策和医生分配提供信息.
- 该模型可适应任何医疗保健系统,并具有已确定的平均呼叫量数据.
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