使用大型国家索赔数据库进行纵向和横截面分析的采样策略
Timothy L McMurry1, Jennifer M Lobo1, Soyoun Kim1,2
1Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States.
Frontiers in public health
|February 16, 2024
概括
一种新方法可以创建用于纵向研究的Medicare患者代表性样本. 这种方法确保人口和健康特征与整体医疗保险人口密切匹配,有助于研究医疗保健利用情况.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 生物统计学 生物统计学
- 流行病学 流行病学
背景情况:
- 医疗保险索赔档案对于国家医疗保健利用数据至关重要.
- 获取和分析用于纵向研究的大型医疗保险数据集存在重大挑战.
- 需要一种记录良好的方法来创建代表性样本.
研究的目的:
- 提出一种方法,用于从医疗保险索赔档案中构建纵向患者样本.
- 确保这些样本每年代表整个医疗保险人口.
- 为了促进具有多年后续的回顾性队列研究.
主要方法:
- 在10年的时间里使用了医疗保险主受益人总结文件.
- 目标每年约有90万名患者,按县和种族/种族分层,少数民族过量抽样.
- 根据持续招生和地理稳定性保留的患者,取代未保留的患者以保持样本代表性.
主要成果:
- 最终的样本平均每年有899,266名患者,与人口统计学 (年龄,种族,性别) 密切相关.
- 在样本中,慢性疾病的患病率与人口的患病率紧密相匹配 (在21种并发症中,在0.12%以内).
- 从样本中获得的纵向队列在5年和10年随访后准确地反映了人口队列.
结论:
- 描述的采样策略有效地产生了具有代表性的纵向医疗保险患者样本.
- 这种方法可以适应其他国家索赔数据库和特定子人口过量抽样.
- 该方法支持使用大规模医疗保健数据的强有力的回顾性队列研究.
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