Census Bureau, Data Integration Division, Small Area Estimates Branch, 6H122A, Washington, DC 20233-8500, USA.
Health Serv Res. 2008 Oct;43(5 Pt 1):1693-707. doi: 10.1111/j.1475-6773.2008.00851.x. Epub 2008 May 5.
To assess the quality of new modeled estimates of health insurance based on a federal survey.
DATA SOURCES/STUDY SETTING: The study uses data from the Annual Social and Economic Supplements to the Current Population Survey (CPS ASEC), calendar years 2001-2003. Health insurance estimates for low-income populations are analyzed.
To assess a method for making estimates for uninsured low-income persons, survey estimates of low-income children are compared with modeled estimates. Inferences can be drawn from this comparison and the method is extended to account for demographic groups.
Data for 2001-2002 CPS ASEC were self-tabulated for low-income children aged 0-17. A special tabulation of the CPS ASEC was used to categorize the numbers of uninsured by age, race, sex, and Hispanic origin by low income at the state level. This special tabulation was the underlying data for the model. Principal Findings. The modeled estimates reduce the variance and margin of error substantially compared with the survey estimates.
These health insurance estimates are credible and increase the precision for the low-income uninsured population. They have broad uses for policy makers and program administrators who focus on the uninsured in special populations.
评估基于联邦调查的新医疗保险模型估计的质量。
数据来源/研究环境：本研究使用了 2001-2003 年“当前人口调查（CPS）年度社会经济补充调查”的数据。分析了针对低收入人群的医疗保险估计数。
为了评估一种针对低收入无保险人群的估计方法，将对低收入儿童的调查估计数与模型估计数进行比较。可以从这种比较中得出结论，并将该方法扩展到考虑人口统计学群体。
2001-2002 年 CPS ASEC 的数据为 0-17 岁的低收入儿童进行了自我制表。使用 CPS ASEC 的特别制表来按年龄、种族、性别和西班牙裔原籍对各州的低收入人群中的未参保人数进行分类。这一特别制表是模型的基础数据。主要发现：与调查估计数相比，模型估计数大大降低了方差和误差幅度。
这些医疗保险估计数是可信的，提高了对低收入无保险人群的精确性。对于关注特殊人群中未参保人群的政策制定者和项目管理者来说，它们具有广泛的用途。
