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Open access

Joanne Pascale

Abstract

Measurement error can be very difficult to assess and reduce. While great strides have been made in the field of survey methods research in recent years, many ongoing federal surveys were initiated decades ago, before testing methods were fully developed. However, the longer a survey is in use, the more established the time series becomes, and any change to a questionnaire risks a break in that time series. This article documents how a major federal survey – the health insurance module of the Current Population Survey (CPS) – was redesigned over the course of 15 years through a systematic series of small, iterative tests, both qualitative and quantitative. This overview summarizes those tests and results, and illustrates how particular questionnaire design features were identified as problematic, and how improvements were developed and evaluated. While the particular topic is health insurance, the general approach (a coordinated series of small tests), along with the specific tests and methods employed, are not uniquely applicable to health insurance. Furthermore, the particular questionnaire design features of the CPS health module that were found to be most problematic are used in many other major surveys on a range of topic areas.

Open access

Joanne Pascale, Angela Fertig and Kathleen Call

Abstract

This study randomized a sample of households covered by one large health plan to two different surveys on health insurance coverage and matched person-level survey reports to enrollment records. The goal was to compare accuracy of coverage type and uninsured estimates produced by the health insurance modules from two major federal surveys – the redesigned Current Population Survey Annual Social and Economic Supplement (CPS) and the American Community Survey (ACS) – after implementation of the Affordable Care Act. The sample was stratified by coverage type, including two types of public coverage (Medicaid and a state-sponsored program) and three types of private coverage (employer-sponsored, non-group, and marketplace plans). Consistent with previous studies, accurate reporting of private coverage is higher than public coverage. Generally, misreporting the wrong type of coverage is more likely than incorrectly reporting no coverage; the CPS module overestimated the uninsured by 1.9 and the ACS module by 3.5 percentage points. Other differences in accuracy metrics between the CPS and ACS are relatively small, suggesting that reporting accuracy should not be a factor in decisions about which source of survey data to use. Results consistently indicate that the Medicaid undercount has been substantially reduced with the redesigned CPS.