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Analyzing the Effect of Data Quality on the Accuracy of Clinical Decision Support Systems: A Computer Simulation Approach

机译:分析数据质量对临床决策支持系统准确性的影响:一种计算机仿真方法

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摘要

Clinical decision support systems (CDSS) use data from a variety sources to provide guidance to physicians at the point of care. However, several studies have shown that data from these registries often cannot be trusted to be accurate or complete. For instance, one study shows that accuracy and completeness in medical registries may be as low as 67% and 30.7%, respectively. Consequently, since CDSS rely on this data for generating guidance, the possibility that the medical decisions facilitated by the system may result in negative patient outcomes still exists. To analyze the extent of this problem, we present a two-pronged approach using simulation, followed by regression in order to quantify the relative impact of poor data quality on overall CDSS accuracy. The results from this analysis can be beneficial to developers and hospitals that can use the results to inform the development of procedures for minimizing incorrect medical decisions facilitated by these systems.
机译:临床决策支持系统(CDSS)使用来自各种来源的数据为护理点的医生提供指导。但是,一些研究表明,通常无法信任来自这些注册表的数据的准确性或完整性。例如,一项研究表明,医疗注册的准确性和完整性可能分别低至67%和30.7%。因此,由于CDSS依赖于此数据来生成指导,因此仍然存在由系统促进的医疗决策可能导致负面患者结果的可能性。为了分析此问题的严重程度,我们提出了一种使用仿真的两管齐下的方法,然后进行回归分析,以量化不良数据质量对总体CDSS准确性的相对影响。此分析的结果可能对开发人员和医院有益,他们可以使用该结果来告知程序开发,以最大程度地减少这些系统所促成的错误医疗决策。

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