使用缩小尺寸方法预测熟练护理设施的再住院和死亡风险
Juan Camilo David Gomez1, Amy Cochran2, Maureen Smith2
1Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, USA.
BMC geriatrics
|June 28, 2023
概括
熟练的护理设施 (SNFs) 对患者再住院和死亡风险产生影响. 将患者状况与SNF容量相匹配,就像现场治疗一样,可以改善结果,减少再入院.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 老年学是指老年学的学科.
- 医疗保健管理的管理
背景情况:
- 医院的目标是尽量减少再住院率,增加对退院后熟练护理设施 (SNF) 的依赖.
- 了解患者和SNF特征如何影响再入院至关重要,但由于数据的复杂性而具有挑战性.
- 本研究解决了根据详细的患者和SNF属性估计再住院和死亡风险的需要.
研究的目的:
- 根据熟练护理机构 (SNF) 组和患者特征估计再住院和死亡风险.
- 确定高维患者和SNF因素如何影响出院后的结果.
- 为改善医疗保健结果,在SNF中提供最佳患者安置信息.
主要方法:
- 使用因子分析将616个患者和SNF特征减少到12个患者因子和4个SNF组.
- 应用K-means集群,根据其特征对SNF进行分类.
- 估计60天再住院和死亡风险使用医疗保险出院数据超过100万患者在13,708SNFs.
主要成果:
- 将复杂的数据减少到12个患者因子和4个不同的SNF组.
- 在容量 (床位,工作人员,治疗) 和相关的再住院/死亡率方面,SNF组存在差异.
- 患有心脏病,骨科和神经精神疾病的患者从现场容量更高的SNF中受益,而癌症/功能衰竭患者在容量较低的SNF中表现更好.
结论:
- 根据患者与SNF的相互作用,再住院和死亡风险显著不同.
- 某些SNF更适合特定的患者状况,强调了量身定制安置的重要性.
- 根据患者需求和设施资源优化SNF选择可能会减少不良结果.
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