数据处理改进对当前人口调查年度社会经济补充健康保险覆盖范围估计的影响。
Data Processing Improvements for Estimates of Health Insurance Coverage in the Current Population Survey Annual Social and Economic Supplement.
机构信息
U.S. Census Bureau, Suitland, MD, USA.
University of Maryland, College Park, MD, USA.
出版信息
Med Care Res Rev. 2022 Apr;79(2):308-316. doi: 10.1177/10775587211000812. Epub 2021 Mar 23.
Estimates of health insurance coverage in the United States rely on household-based surveys, and these surveys seek to improve data quality amid a changing health insurance landscape. We examine postcollection processing improvements to health insurance data in the Current Population Survey Annual Social and Economic Supplement (CPS ASEC), one of the leading sources of coverage estimates. The implementation of updated data extraction and imputation procedures in the CPS ASEC marks the second stage of a two-stage improvement and the beginning of a new time series for health insurance estimates. To evaluate these changes, we compared estimates from two files that introduce the updated processing system with two files that use the legacy system. We find that updates resulted in higher rates of health insurance coverage and lower rates of dual coverage, among other differences. These results indicate that the updated data processing improves coverage estimates and addresses previously noted limitations of the CPS ASEC.
美国健康保险覆盖范围的估计依赖于基于家庭的调查，而这些调查旨在改善不断变化的健康保险环境下的数据质量。我们研究了当前人口调查年度社会经济补充调查（CPS ASEC）中健康保险数据的后期处理改进，这是覆盖范围估计的主要来源之一。在 CPS ASEC 中实施更新的数据提取和估算程序标志着两阶段改进的第二阶段，也是健康保险估计新时间序列的开始。为了评估这些变化，我们比较了引入更新处理系统的两个文件与使用传统系统的两个文件的估计值。我们发现，更新后的保险覆盖范围更高，双重覆盖范围更低，以及其他差异。这些结果表明，更新的数据处理改进了覆盖范围的估计，并解决了 CPS ASEC 之前指出的局限性。
Zotero 插件