开发和验证基于索赔的算法,以识别在美国接受治疗的喘患者中中度恶化
Melissa H Roberts1, Mei Sheng Duh2, Kieran J Rothnie3
1University of New Mexico, Albuquerque, NM, USA.
Respiratory medicine
|April 9, 2024
概括
开发一种算法来识别来自保险索赔的中度喘恶化对于评估经济影响至关重要. 这项研究改进了一种算法,实现了42%的积极预测值,突出了其潜力,但也突出了准确捕捉所有中度事件的局限性.
科学领域:
- 卫生经济学 卫生经济学
- 呼吸系统医学 呼吸系统医学
- 数据科学数据科学数据科学
背景情况:
- 对中度喘恶化的不一致定义阻碍了准确的经济负担评估.
- 需要一个经过验证的算法来识别使用医疗保健索赔数据的中度喘恶化.
研究的目的:
- 改进现有的算法,以在索赔数据中识别中度喘恶化.
- 使用正负预测值 (PPV和NPV) 评估精细算法的性能.
- 为了比较算法识别和图表确认的恶化之间的医疗保健资源利用率 (HRU).
主要方法:
- 用处方和医疗声明对患有喘的成年患者进行回顾性队列研究.
- 开发和完善一个算法,以识别基于诊断代码和药房声明的中度恶化.
- 通过对150个恶化事件和50个非恶化事件的图表审查来评估算法性能 (PPV,NPV).
主要成果:
- 精细的算法发现了中度恶化,PPV为42%和NPV为78%.
- 在算法识别和图表确认的中度恶化组之间,医疗保健资源利用率是可比的.
- 算法发现了一些严重的恶化,为其性能指标做出了贡献.
结论:
- 开发的算法可以从索赔数据中识别潜在的中度喘恶化.
- 温和的PPV表明在准确识别所有中度恶化时存在局限性,部分原因是包括严重病例.
- 基于索赔的未来研究可以利用这个算法,与严重恶化的算法一起,以更好地量化喘恶化的经济负担.
关键词:
喘的诊断 喘的诊断 喘的诊断医疗保健经济学 医疗保健经济学医疗保健资源的利用率 (最大) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 6) 没有人知道,没有人知道,没有人知道.中等程度的恶化.更多相关视频
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