开发和优化退伍军人事务局全国心力衰竭仪表板,用于人口健康管理
Nicholas Brownell1, Chad Kay2, David Parra3
1Division of Cardiology, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA.
Journal of cardiac failure
|September 27, 2023
概括
美国VA国家心力衰竭 (HF) 仪表板使用自然语言处理和成像模型优化了准确性. 这改进了对HF亚型的识别,提高了患者的护理.
科学领域:
- 心血管医学 心血管医学
- 医疗信息学 医疗信息学
- 在医疗保健中的数据科学.
背景情况:
- 退伍军人事务部 (VA) 在2020年部署了全国心力衰竭 (HF) 仪表板.
- 最初的仪表板在识别高频子类型方面缺乏精确性.
- 本研究详细介绍了VA国家HF仪表板的优化过程.
研究的目的:
- 描述VA国家HF仪表板的开发和优化.
- 提高VA系统内HF亚型识别的准确性和可靠性.
- 提高仪表板对人口健康管理的实用性.
主要方法:
- 逐步改进VA国家HF仪表板.
- 通过自然语言处理 (NLP) 改进病例定义和患者识别.
- 整合成像质量层次,评估成像方式和ICD-code要求.
主要成果:
- 降低弹射率 (HFrEF) 的HF仪表板准确度从54.1%提高到89.2%.
- 用保存的喷射分数 (HFpEF) 检测HF的精度从53.9%提高到88.0%.
- 轻微减少喷射分数 (HFmrEF) 的HF被添加,准确率为88.0%.
结论:
- 图像质量层次模型和NLP算法显著提高了VA HF仪表板的准确性.
- 修订后的仪表板显示了改善的可靠性和人口健康管理的更高的利用率.
- 优化的信息算法支持心力衰竭患者更好的健康管理.
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