在熟练护理机构的干预分析与减少再接收相关.
Derek A Kaknes, Tanner B Barbour, Wenyan Ji
1Virginia Polytechnic Institute and State University, 4 Riverside Circle, Roanoke, VA 24016.
The American journal of managed care
|May 31, 2024
概括
使用干预分析 (IA) 平台的熟练护理设施 (SNF) 与没有IA的护理设施相比,显示了明显较低的30天再录取率. 这种IA的实施导致了全国和全州的患者结果和质量指标的改善.
科学领域:
- 医疗分析 医疗分析
- 提高熟练护理设施的质量.
- 减少患者再入院的策略
背景情况:
- 熟练的护理设施 (SNFs) 在急性后护理中发挥着至关重要的作用.
- 减少30天的再入院是SNF的一个关键绩效指标.
- 再接收率在设施和地理区域之间存在差异.
研究的目的:
- 为了比较与兰开斯特总医院 (LGH) 相关的SNF的纵向30天风险调整后再录取率.
- 评估干预分析 (IA) 平台对再接收率的影响.
- 评估实施IA的SNF,非IA的LGH设施,宾夕法尼亚SNF和国家SNF队列之间的差异.
主要方法:
- 对美国医疗保险和医疗补助服务中心 (CMS) 再接收数据 (2017-2022) 的回顾性纵向分析.
- 对CMS质量指标数据的横截面分析.
- 多变量混合效应建模,以在定义的SNF队列中比较再接收率.
主要成果:
- 与没有IA,宾夕法尼亚州和国家队列相比,具有IA的LGH SNF显示出明显较低的再接收率.
- 在截至2022年第四季度的12个月中,装有IA的SNF的再接收率下降了12.30-15.24个百分点 (P < .0001).
- 实施IA的SNF也显示出优异的CMS质量指标结果.
结论:
- 研究的IA平台的实施与风险调整后再接收率的统计和临床显著改善有关.
- 配备IA的SNF的表现优于国家,州和网络的同行.
- 建议进一步研究IA在SNF中的应用.
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