Misdiagnosis-related harm quantification through mixture models and harm measures.
Misdiagnosis-related harm quantification through mixture models and harm measures.
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通过混合模型和危害措施对误诊相关危害进行量化。
DOI：
10.1111/biom.13759
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发表时间：
2023
期刊：
影响因子：
1.9
通讯作者：
Newman-Toker,David
中科院分区：
文献类型：
--
作者：
Zhu,Yuxin;Wang,Zheyu;Newman-Toker,David
调查和监测与误诊相关的危害对于改善卫生保健至关重要。然而，这项工作传统上侧重于图表审查过程，这是一个劳动密集型的过程，可能不稳定，而且伸缩性不好。为了监测医疗机构的诊断表现，并及时确定需要改进的领域，研究人员建议基于电子健康记录或索赔数据来利用症状和疾病之间的关系。具体地说，假阴性诊断后疾病风险的增加可以用来发出潜在危害的信号。然而，现成的统计方法不能完全适应假设良好的风险模式的数据结构，因此不能充分应对独特的挑战。为了填补这些空白，我们提出了一个混合回归模型及其相关的拟合优度检验。我们进一步提出了损害措施和概况分析程序，以量化、评估和比较具有潜在不同患者群体构成的研究所之间与误诊相关的损害。通过仿真研究了所提方法的性能。然后，我们通过对台湾纵向健康保险数据库中中风发生数据的数据分析来说明这些方法。通过分析，我们定量评估了误诊伤害的危险因素，为医疗质量研究提供了一些启示。我们还比较了台湾的普通护理医院和特殊护理医院，并使用各种新的评估和衡量标准观察到特殊护理医院的诊断表现更好。
Investigating and monitoring misdiagnosis‐related harm is crucial for improving health care. However, this effort has traditionally focused on the chart review process, which is labor intensive, potentially unstable, and does not scale well. To monitor medical institutes' diagnostic performance and identify areas for improvement in a timely fashion, researchers proposed to leverage the relationship between symptoms and diseases based on electronic health records or claim data. Specifically, the elevated disease risk following a false‐negative diagnosis can be used to signal potential harm. However, off‐the‐shelf statistical methods do not fully accommodate the data structure of a well‐hypothesized risk pattern and thus fail to address the unique challenges adequately. To fill these gaps, we proposed a mixture regression model and its associated goodness‐of‐fit testing. We further proposed harm measures and profiling analysis procedures to quantify, evaluate, and compare misdiagnosis‐related harm across institutes with potentially different patient population compositions. We studied the performance of the proposed methods through simulation studies. We then illustrated the methods through data analyses on stroke occurrence data from the Taiwan Longitudinal Health Insurance Database. From the analyses, we quantitatively evaluated risk factors for being harmed due to misdiagnosis, which unveiled some insights for health care quality research. We also compared general and special care hospitals in Taiwan and observed better diagnostic performance in special care hospitals using various new evaluation measures.