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在美国验证算法以检测急性和传播的莱姆病. 行政索赔数据管理索赔数据

Sheryl A Kluberg¹, Noelle M Cocoros¹, June O'Neill²

¹Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.

Open forum infectious diseases

|March 31, 2025

概括

使用保险索赔的新算法可以有效地识别莱姆病 (LD) 病例. 这些经过验证的方法通过捕获早期和传播的LD来改善疾病监测,即使没有特定的诊断代码.

科学领域:

流行病学流行病学
传染性疾病传染性疾病
公共卫生监督公共卫生监督

背景情况:

莱姆病 (Lyme disease,简称LD) 是美国流行的一种媒介性疾病.
传统的监测方法往往低估了LD负担.
准确的病例鉴定对于了解疾病传播至关重要.

研究的目的:

通过使用行政保险索赔数据,验证用于识别早期本地化和传播LD病例的算法.
评估高发病率和邻近低发病率州的算法性能.
通过考虑当前方法中低估的情况来改善LD监测.

主要方法:

使用保险索赔数据开发和测试了三种算法 (2015年10月至2023年10月).
算法包括LD特定的诊断代码,抗生素处方和LD诊断测试.
使用修改后的监视病例定义对医疗记录进行验证的算法,计算正预测值 (PPV).

主要成果:

从索赔数据中确定了9483个潜在的LD病例;审查了841份医疗记录.
主要算法PPV为所有病例类型的90.7% (高发病率) 和81.3% (邻近州).
对于传播的LD的二次算法PPV较低,特别是在发病率较低的州.

结论:

基于索赔的算法,包括诊断代码和其他标准,可以可靠地识别LD病例.
调整后的算法为估计美国LD发病率提供了一种可行的方法.
这些经过验证的算法增强了对莱姆病的公共卫生监测.

关键词:

流行病学流行病学保险赔偿金保险赔偿金保险赔偿金的保险赔偿金是什么莱姆病是莱姆病的一种疾病.监控监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督监督传播疾病传播疾病

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