评估商业医疗保健索赔数据的概括性
Alex Dahlen1,2, Yaowei Deng2,3, Vivek Charu2,4
1Department of Biostatistics, School of Global Public Health, New York University, New York, NY.
American journal of epidemiology
|July 3, 2025
概括
商业医疗保健索赔数据低估了所有美国人的住院出院率的23.1%. 偏见与社会经济因素有关,但只关注商业保险人员时会减少.
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
- 卫生经济学 卫生经济学
背景情况:
- 商业医疗保健索赔数据集被广泛使用,但代表了美国人口的非随机样本,引发了对概括性的担忧.
- 之前的研究缺乏严格的与基准真相数据的比较,以量化索赔数据固有的外部有效性偏差.
研究的目的:
- 量化商业医疗保健索赔数据的外部有效性偏差.
- 评估社会经济/人口因素与这种偏见之间的关系.
主要方法:
- 在2019年1月1日至2019年31月12日期间,分析了来自五个州 (CA,IA,MD,MA,NJ) 的住院患者出院记录.
- 在MerativeTM MarketScan®商业数据库和参考数据 (州住院患者数据库和美国人口普查) 之间比较住院手术率 (每人/年).
- 对不同目标人群的250种最常见的住院手术中偏差大小的评估.
主要成果:
- 商业索赔数据低估了美国普通人口的整体住院出院率的23.1%.
- 大约25%的程序显示有偏差,其中率被低估了2倍.
- 社会经济因素显著解释了69.4%的偏差差异 (p < 0.001).
- 当目标人群仅限于商业保险的美国人时,偏见大幅减少,只有1.4%的程序显示出显著的偏见.
结论:
- 商业医疗保健索赔数据在对整个美国人口进行概括时表现出显著的外部有效性偏差,特别是关于住院手术率.
- 社会经济和人口因素与这种偏差的大小密切相关.
- 虽然仅分析商业保险人群时,偏见会减少,但程序变化仍然存在,需要仔细考虑概括性.
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