一个ICD-10编码算法的有效性急性热病在急诊室:一个追溯的队列研究
Hasan Baassiri1, Timothy Varghese1, Kristin K Clemens2,3,4
1Division of Emergency Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5A5, Canada.
International journal of environmental research and public health
|September 28, 2024
概括
在加拿大急诊室,针对急性热病 (AHI) 的ICD-10编码算法显示出高特异性但低灵敏性. 该工具可以识别AHI病例,但可能低估其真实发生率.
科学领域:
- 公共卫生和流行病学
- 环境健康 环境健康
- 医疗信息学 医疗信息学
背景情况:
- 暴露于极端环境热量会带来严重的健康风险,包括急性热病 (AHI),导致急诊室 (ED) 访问,住院和死亡.
- 虽然国际疾病分类,第九修订 (ICD-9) AHI的代码在美国得到验证,但国际疾病分类,第十修订 (ICD-10) AHI代码在加拿大的有效性仍未研究.
- 准确的编码对于 AHI 的流行病监测和研究至关重要.
研究的目的:
- 评估ICD-10编码算法的有效性,用于识别加拿大急诊室 (ED) 与急性热病 (AHI) 相关的遭遇.
- 确定针对AHI开发的ICD-10算法的正预测值 (PPV),负预测值 (NPV),灵敏度 (Sn) 和特异性 (Sp).
主要方法:
- 使用来自加拿大伦敦两家大型学术,高等医院的ED数据进行了一项回顾性队列研究 (2014年5月至2018年9月).
- 基于文献审查和临床专业知识,开发了针对AHI的ICD-10编码算法.
- 对AHI的"黄金标准"定义包括患者报告的热暴露和至少一个与热有关的投诉. 从62个算法阳性记录中计算PPV. 从964个随机选择的ED记录中计算了NPV,Sn和Sp.
主要成果:
- 对于AHI,ICD-10算法的积极预测值 (PPV) 为61.3%±12.1%.
- 负预测值 (NPV) 在99.7%±0.4%高.
- 该算法表现出高特异性 (100.0%±0.0%),但敏感性有限 (25.0%±42.4%).
结论:
- 在加拿大急诊室开发的急性热病 (AHI) 的ICD-10编码算法具有高特异性但低灵敏性.
- 虽然该算法对于组装用于AHI研究的队列很有用,但它可能低估了急诊室AHI病例的真实发生率.
- 需要进一步完善编码算法,以提高全面AHI监测的灵敏度.
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