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Validity of discharge diagnoses in the surveillance of stroke

机译:出院诊断在中风监测中的有效性

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Background: Hospital administrative data have been suggested as a valuable cost-effective tool for providing information about the stroke burden. Nevertheless, the choice of the diagnosis codes has been a critical issue in the development of case ascertainment algorithms. Methods: In this study, the Minimum Basic Data Set administrative database was used to analyze the accuracy of different ICD-9-CM algorithms based on the neurologist's clinical judgement as the 'gold standard'. Results: The most accurate algorithm observed in our study involved the selection of ICD-9-CM codes 430-438 in the primary diagnosis. It yielded a sensitivity of 96.1%, a specificity of 87.5% and a positive predictive value of 82.5%. Conclusions: The Minimum Basic Data Set is a valuable source to evaluate stroke frequency when using an accurate algorithm to select events.
机译:背景:医院管理数据被认为是提供有关中风负担信息的有价值的具有成本效益的工具。尽管如此,诊断代码的选择一直是案例确定算法发展中的关键问题。方法:在这项研究中,使用最小基础数据集管理数据库,以神经科医生的临床判断为“黄金标准”,分析了不同ICD-9-CM算法的准确性。结果:在我们的研究中观察到的最准确的算法涉及在初步诊断中选择ICD-9-CM代码430-438。它产生了96.1%的灵敏度,87.5%的特异性和82.5%的阳性预测值。结论:最小基本数据集是使用精确算法选择事件时评估笔画频率的宝贵资源。

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