在高需求,高成本人群中使用电子健康记录数据描述住院治疗轨迹
Scott S Lee1, Benjamin French2, Francis Balucan1
1Section of Hospital Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, United States.
Health affairs scholar
|May 17, 2024
概括
一小群患者通过频繁住院导致高医疗费用. 识别不同的住院模式可以帮助预测和管理高需要,高成本的个人.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 临床流行病学临床流行病学
- 卫生经济学 卫生经济学
背景情况:
- 少数患者的高医疗保健利用率显著影响总体成本.
- 了解患者住院模式的动态对于控制成本至关重要.
- 对住院病例的纵向分析可以揭示不同的患者轨迹.
研究的目的:
- 描述成人患者住院治疗的纵向轨迹.
- 通过时间来识别患者住院模式的不同集群.
- 确定与不同住院轨迹相关的基线因素.
主要方法:
- 在学术医疗中心对3404名成年患者进行了回顾性队列研究 (2017-2023年).
- 增长混合模型被用来确定在最初的"风险上升"期间后住院轨迹的集群.
- 分析与已确定轨迹相关的基线临床和人口因素.
主要成果:
- 确定了四个不同的住院治疗轨迹集群:没有进一步的利用,慢性利用率低,缓慢增长的持续高,快速增长的持续高.
- 与更高的利用轨迹相关的因素包括非手术服务录取,完整的代码状态,ICU护理和阿片类药物管理.
- 诸如心血管疾病,末期脏或肝脏疾病和癌症等并发症与更高的住院率有关.
结论:
- 患者住院治疗遵循可识别的纵向轨迹.
- 早期识别具有特定风险因素的患者可以预测高需求,高成本的利用.
- 描述这些轨迹为有针对性的干预和资源分配提供了基础.
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