基于行政索赔数据的机器学习算法的开发,用于识别ED过敏反应患者的访问
Ronna L Campbell1, Mollie L Alpern2, James T Li2
1Department of Emergency Medicine, Mayo Clinic, Rochester.
The journal of allergy and clinical immunology. Global
|October 2, 2023
概括
仅凭国际疾病分类 (ICD) 代码就无法识别过敏反应病例. 使用行政数据的机器学习算法为分类急诊室过敏反应访问提供了更高的准确性.
科学领域:
- 过敏反应研究的研究.
- 医疗信息学医学信息学
- 流行病学 流行病学
背景情况:
- 过敏反应的流行病学研究经常使用国际疾病分类 (ICD) 代码.
- 依赖ICD代码可能导致不准确的病例识别和低于最佳的流行病学分类.
研究的目的:
- 开发和评估用于识别急诊室 (ED) 过敏反应访问的机器学习算法.
- 为了比较这个算法的准确性与传统的ICD代码-only方法.
主要方法:
- 从2013年1月到2017年9月的ED访问的回顾性审查.
- 使用三种基于ICD代码的方法和利用行政数据的机器学习算法来识别过敏症病例.
- 方法之间的测试特征 (灵敏度,特异性) 的比较.
主要成果:
- 机器学习算法实现了87.3%的灵敏度和79.1%的特异性.
- 仅使用ICD代码的方法显示出不同的性能,其中一种组合产生了98.4%的灵敏度,但只有15.1%的特异性.
- 仅ICD编码就错过了96%的与毒素相关的过敏反应病例.
结论:
- 传统的ICD编码本身就表明识别过敏症病例的灵敏度很差.
- 开发的机器学习算法提供了灵敏度和特异性的卓越平衡.
- 这种算法代表了对识别ED过敏症访问的现有策略的改进.
相关概念视频
Steps in Outbreak Investigation
152
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
152
Pharmacovigilance
876
Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
876


