在美国比较两种方法来识别患有严重喘的个体 声称数据数据
Julie Barberio1, Xinyu Li2, Sarah-Jo Sinnott1
1Sanofi, Cambridge, Massachusetts, USA.
Pharmacoepidemiology and drug safety
|September 10, 2025
概括
识别严重喘患者群体对于有效管理至关重要. 基于代码和基于计算的两种方法,使用高剂量吸入性皮质类固醇 (ICS) 和长效β-激动剂 (LABA) 的处方声明,在分层患者中显示出希望.
科学领域:
- 药理学和药理学流行病学
- 呼吸系统医学 呼吸系统医学
- 医疗信息学 医疗信息学
背景情况:
- 严重的喘管理是复杂的,通常涉及并发症和增加医疗保健利用率.
- 对喘严重程度的准确分层是必不可少的,但在药理流行病学研究中缺乏标准化的方法.
- 使用管理医疗保健数据库进行喘严重程度分类的现有方法不一致.
研究的目的:
- 通过使用管理医疗保健数据,评估两种不同的算法来识别严重喘患者.
- 将基于代码的方法与基于计算的方法进行比较,以根据处方要求推断严重的喘.
- 评估这些方法与全球喘倡议 (GINA) 准则的一致性.
主要方法:
- 确定的患有喘的人 (≥2 ICD-10-CM J45代码),年龄在2017-2023年之间≥6岁.
- 通过使用高剂量吸入性皮质类固醇 (ICS) 和长效β-激动剂 (LABA) 的处方声明来定义严重喘 (GINA第5步).
- 采用基于代码的方法 (吸入器属性) 和基于计算的方法 (方案属性) 来估计剂量.
主要成果:
- 鉴定了1,221,732名患有喘的人;3.1%严重的基于代码的方法,4.2%基于计算的方法.
- 这两种方法都与GINA基准 (3.7%) 一致,没有显著的队列特征差异.
- 值得注意的是,基于计算的方法确定的27%的严重喘患者被基于代码的方法遗漏了.
结论:
- 通过使用基于代码或基于计算的算法,通过处方声明估计患者水平的平均每日ICS剂量是识别严重喘的可行方法.
- 方法之间的差异凸显了医生指示和推剂量之间的潜在差异.
- 未来的研究将专注于验证这些算法与电子医疗记录进行验证,以提高准确性.
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