在不同规模的临床质量登记册中进行场地基准测试的准确性
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Jessy Hansen1, Ahmad Reza Pourghaderi1, Susannah Ahern1
1School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
概括
准确的医疗保健提供者基准测试需要足够的患者数量和结果流行率. 风险调整模型可以提高临床注册表中异常结果检测的准确性,特别是在事件率较高的情况下.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
背景情况:
- 使用临床登记册对医疗服务提供者的表现进行公开报告正在增加.
- 识别表现不佳的网站 (异常值) 需要最佳的基准分析方法.
- 需要对理想条件进行研究,以准确检测异常值.
研究的目的:
- 评估基准测试和异常分类方法的准确性.
- 评估不同规模的临床注册表和最低病例数量的表现.
主要方法:
- 临床注册数据集的参数模拟.
- 各种参数:地点数量,临床医生,患者,结果事件,最小病例数量和结果流行率.
- 应用未经调整和风险调整 (逻辑回归) 的基准分析模型,用于异常值的分类,具有置信区间和控制极限.
- 在曲线下使用接收机操作员特征面积 (ROCAUC) 评估准确性.
主要成果:
- 与未经调整的方法相比,风险调整的基准分析提高了ROCAUC高达20%.
- 登记册的大小和临床医生人数对业绩的影响最小.
- 准确性随着每站点患者数量的增加和结果流行率的增加而增加.
- 对于>80%的ROCAUC,每个地点至少需要100150个结局事件.
结论:
- 使用低流行度结局的基准测试可能不适合在低体积的临床注册表中检测异常值.
- 卫生信息管理实践应考虑患者数量和结果流行率,以进行可靠的基准评估.
- 在异常值检测中实现可接受的准确性取决于这些注册表特征.
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