基于时间到事件模型和当代澳大利亚行政数据的标准化住院时间的有希望的解决方案
Graeme J Duke1,2,3, Steven Hirth4,3, John D Santamaria5,6
1Intensive Care Service, Eastern Health, Box Hill, Victoria, Australia graeme.duke@easternhealth.org.au.
BMJ open
|December 3, 2025
概括
一种新的时间到事件方法创建了一个医院标准化停留时间比率 (HSLR). 这一改进的指标显示,大部分住院时间变化与患者有关,而不是与医院相关,提高了医院的效率和质量基准.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
背景情况:
- 住院时间 (LOS) 对于评估医院效率和护理质量至关重要.
- 目前用于对比LOS的方法存在问题,缺乏可靠性.
- 为了准确的医院比较,需要标准化和风险调整的指标.
研究的目的:
- 引入和评估一种新的时间到事件方法,用于生成医院住院标准化长度比率 (HSLR).
- 为了比较HSLR指标与传统的平均逗留时间 (aLOS),用于基准测试.
- 确定住院时间变化的主要驱动因素.
主要方法:
- 大规模司法行政数据集的回顾性观察分析 (澳大利亚维多利亚州).
- 应用时间到事件 (排放危险) 分析方法来计算风险调整后的LOS (预测的LOS - pLOS).
- 使用公式计算HSLR: (观察到的LOS总和) / (pLOS总和).
主要成果:
- 事件发生时间模型成功生成了风险调整的预测LOS (pLOS) 和HSLR指标.
- 在基准分析时,HSLR值显示出明显更好的初始率 (99.5%) 与传统的aLOS (61%的异常值) 相比.
- 分析表明,与患者相关的因素,而不是医院特定的因素,占LOS变化的大部分.
结论:
- 传统的平均LOS (aLOS) 是用于医院比较的不充分衡量标准.
- 时间到事件的方法提供了一个强大而可靠的HSLR,用于准确的风险调整基准分析.
- HSLR指标突出了患者特征对住院时间的主要影响.
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