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在临床决策支持系统中使用归算:在临床医生中进行一项心血管风险管理试点图片研究

Saskia Haitjema¹, Steven W J Nijman², Inge Verkouter³

¹Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.

European heart journal. Digital health

|September 25, 2024

概括

临床医生发现,临床决策支持系统 (CDSS) 中缺少患者数据的实时归算在临床上是合理的,但缺乏日常使用的舒适性. 为了改善临床决策,需要对CDSS进行更准确的归算.

科学领域:

医疗信息学医疗信息学
临床决策支持系统临床决策支持系统
在医疗保健中的数据科学.

背景情况:

缺少数据是临床预测模型的一个重大挑战.
实时归算提供了一个潜在的解决方案,以解决缺少的患者信息.
临床决策支持系统 (CDSS) 中实时归算的临床接受程度在很大程度上是未知的.

研究的目的:

评估临床医生对CDSS中缺少的患者数据实时归算的接受度.
评估归算对风险预测所感知的临床现实性,舒适性和临床附加值的影响.
确定联合建模归算 (JMI) 对10年心血管绝对风险估计的有用性.

主要方法:

通过使用现有的CDSS增强联合建模归算 (JMI) 进行了维尼特研究.
17名临床医生通过模拟不同数据场景 (缺失,归咎,完整) 的三个小组评估了CDSS.
通过评估临床现实主义,舒适性和临床附加价值来衡量接受度.

主要成果:

导入的预测值通常被认为是临床上合理的,并且符合预期.
临床医生对假定风险预测表示不太满意,并引用广泛的置信区间作为可靠决策的障碍.
对二进制变量不确定性的概率尺度的使用被认为是不方便的.
承认JMI的附加值是为了教育,研究和信息目的.

结论:

在CDSS中处理缺失数据的联合建模归算 (JMI) 是有用的,但需要改进以进行常规的临床采用.
提高归算准确度对于建立临床医生的信心和促进CDSS用于改进决策至关重要.
实时归算为CDSS提供了创造显著临床价值的潜力,但需要进一步开发.

关键词:

这是一个CDSSCDSSCDSS.心血管疾病的风险.计入计算是指计入计算的方法.预测模型的预测模型.这就是U-Prevent.

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