一个时间调整的控制图表,用于监测手术结果的变化
Quentin Cordier1,2, My-Anh Le Thien2, Stéphanie Polazzi1,2
1Research on Healthcare Performance RESHAPE, INSERM U1290, Université Claude Bernard Lyon 1, Lyon, France.
PloS one
|May 15, 2024
概括
将时间相关的趋势与患者因素相结合,可以更好地检测手术结果的显著变化. 这提高了用于手术质量监测的统计过程控制 (SPC) 图的可靠性.
科学领域:
- 改善医疗保健质量 改善医疗保健质量
- 手术结果研究研究.
- 统计过程控制 统计过程控制
背景情况:
- 统计过程控制 (SPC) 工具通过提供反来帮助手术团队,以提高患者的结果.
- 目前的医院数据质量限制了对患者病例组合对手术结果的影响的准确评估.
- 需要纳入与时间相关的变量,以便更精确地监测手术结果.
研究的目的:
- 为了评估包括与时间相关的变量 (世俗和季节性趋势) 除了患者病例组合之外,用于检测手术结果中的特殊原因变异的影响.
- 为了证明增强控制图表在手术绩效监测中的附加值.
主要方法:
- 来自法国全国医院数据库的151588名结直肠手术患者 (2014-2018) 的回顾性分析.
- GEE多层逻辑回归模型预测了仅针对病例组合 (经典图表) 和病例组合加时间趋势 (增强图表) 的调整后的手术结果 (死亡率,ICU停留,重新手术).
- 使用科恩卡帕,灵敏度和积极预测值的经典和增强控制图表之间的特殊原因变异检测的比较.
主要成果:
- 增强图表显示,与经典图表 (18.9%) 相比,特殊原因变异的检测率略高 (19.6%).
- 32.2%的检测到的变化显示两种图表类型之间的不一致,表明信号检测的差异.
- 观察到高一致性 (Kappa 0.67-0.89),但增强图表显示出更好的灵敏度和检测变化的积极预测值.
结论:
- 考虑到季节性和长期趋势作为潜在的混因素,可以显著改善对手术结果的有意义变异的检测.
- 结合时间趋势的增强控制图表为随着时间的推移监测外科手术质量提供了更强大的工具.
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