进入长期护理机构后不久死亡率的预测因素
Robert N Jorissen1,2, Steve L Wesselingh3, Craig Whitehead4,5
1Registry of Senior Australians, South Australian Health and Medical Research Institute, Adelaide, SA, Australia.
Age and ageing
|May 22, 2024
概括
在进入长期护理机构 (LTCF) 后,识别高死亡风险的个体对于护理规划至关重要. 一个新的预测模型,使用51个因素,适度识别那些高风险的90天死亡率.
科学领域:
- 老年学是指老年学的学科.
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
背景情况:
- 进入长期护理机构 (LTCF) 需要大量的投资和风险.
- 识别高风险的个人进入后短期死亡对于有针对性的护理规划和资源分配至关重要.
研究的目的:
- 为了确定进入LTCF后90天死亡率的预测因素.
- 为进入LTCF的个人制定风险概况.
主要方法:
- 使用澳大利亚老年人登记册数据进行的回顾性队列研究.
- 考克斯回归模型是使用有目的变量选择开发的.
- 分析包括个人,药物,系统和LTCF入境时的医疗保健因素.
主要成果:
- 研究了一组116,192个进入1967个设施的个人;9.4%在90天内死亡.
- 确定了51种死亡率预测因素,日常生活活动,复杂的健康状况,药物类别和男性性别的联系最强.
- 该预测模型实现了0.773.3的样本外哈雷尔C指数.
结论:
- 一个经过验证的死亡率预测模型可以在进入LTCF后不久中适度识别高死亡风险的个体.
- 该模型结合了多个密切相关的因素,有助于积极的风险管理和护理策略.
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