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使用行政数据调整先天性心脏手术风险

Natalie Jayaram1, Philip Allen2, Matthew Hall3

  • 1Children's Mercy Kansas City, Kansas City, Missouri, USA.

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|November 29, 2023
PubMed
概括
此摘要是机器生成的。

一种新的风险调整模型,RACHS-2 (ICD-10行政数据的先天性心脏手术风险分层),已被开发和验证用于先天性心脏手术 (CHS). 这种模型可以改善儿科心脏手术患者住院死亡率的预测.

关键词:
生产性心脏手术是一项手术.结果就是结果.进行风险调整.

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科学领域:

  • 儿科心脏手术 儿科心脏手术
  • 医疗保健服务研究 医疗服务研究
  • 生物统计学 生物统计学

背景情况:

  • 先天性心脏手术 (CHS) 涉及多种不同的患者和手术,需要对比性研究进行风险标准化.
  • 现有的模型可能无法完全捕捉到CHS患者群体和手术干预的复杂性.

研究的目的:

  • 开发和验证CHS的风险调整模型,使用ICD-10行政数据 (RACHS-2) 的先天性心脏手术风险分层方法.
  • 确定关键的患者和程序特征,与CHS的住院死亡率相关.

主要方法:

  • 利用2019年儿童住院患者数据库来识别具有RACHS-2分数的CHS病例.
  • 采用分层后勤回归来分析与住院死亡率相关的因素.
  • 利用2017年24个州住院患者数据库的数据验证了该模型.

主要成果:

  • 仅仅RACHS-2评分就实现了0.81的C统计,用于死亡率预测.
  • 包括年龄,付款人和复杂的慢性疾病在内,改善了模式歧视,达到0.87.
  • 该模型在验证队列中显示出强烈的歧视 (C-统计 = 0.83).

结论:

  • 已经开发了一种经过验证的CHS风险调整模型,包含RACHS-2和其他行政数据.
  • 这个模型准确地解释了影响医院死亡率的患者和程序因素.
  • 开发的风险模型对于推动医疗服务研究和CHS质量改善至关重要.