scholarly journals Comparing Methods for Imputing Employer Health Insurance Contributions in the Current Population Survey

Author(s):  
Hubert P. Janicki ◽  
Brett OOHara ◽  
Alice M. Zawacki
2021 ◽  
pp. 107755872110008
Author(s):  
Edward R. Berchick ◽  
Heide Jackson

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.


2019 ◽  
Vol 35 (1) ◽  
pp. 189-202
Author(s):  
Brett O’Hara ◽  
Carla Medalia ◽  
Jerry J. Maples

Abstract Most research on health insurance in the United States uses the Current Population Survey Annual Social and Economic Supplement. However, a recent redesign of the health insurance questions disrupted the historical time trend in 2013. Using data from the American Community Survey, which has a parallel trend in the uninsured rate, we model a bridge estimate of the uninsured rate using the traditional questions. Also, we estimate the effect of changing the questionnaire. We show that the impact of redesigning the survey varies substantially by subgroup. This approach can be used to produce bridge estimates when other questionnaires are redesigned.


2016 ◽  
Vol 32 (2) ◽  
pp. 461-486 ◽  
Author(s):  
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.


2016 ◽  
Vol 74 (5) ◽  
pp. 595-612 ◽  
Author(s):  
Joelle Abramowitz ◽  
Brett O’Hara

This analysis uses new questions in the Current Population Survey Annual Social and Economic Supplement to examine rates of offer and take-up of employer-sponsored health insurance over early 2014 and early 2015, as well as reasons reported for why individuals did not enroll. We find increases in offer and eligible rates of 0.5 and 0.9 percentage points, respectively, and a decrease in the take-up rate of 1.5 percentage points, while the coverage rate remained stable. We further find an increase in the proportion of workers covered by another plan and decreases in the proportions eligible for coverage but having a preexisting condition, employed as contract or temporary employees not allowed in the plan, and who have not yet worked for an employer long enough.


2015 ◽  
Vol 51 (1) ◽  
pp. 240-261 ◽  
Author(s):  
Joanne Pascale ◽  
Michel Boudreaux ◽  
Ryan King

Author(s):  
Heide Jackson ◽  
Edward R. Berchick

In 2019, the Current Population Survey Annual Social and Economic Supplement introduced updates to data processing, including to the imputation of health insurance for cases with no reported health insurance information. This article examines the impact on health insurance estimates of modernized imputation procedures that were part of a redesign of the Current Population Survey Annual Social and Economic Supplement. We use descriptive analysis and multinomial logistic regression to examine whether imputation biases estimates of health insurance coverage using data from the 2017 Current Population Survey Annual Social and Economic Supplement, which used legacy methods, and the 2017 Current Population Survey Annual Social and Economic Supplement Research File, which debuted the processing redesign. We find that cases with all of their health insurance information imputed using legacy methods were more likely to be uninsured or to be covered by multiple insurance types after adjusting for factors associated with having missing data. With the processing updates, fully imputed cases do not differ from other cases in their likelihood of being uninsured, having private coverage, having public coverage, or in having private and public coverage. Processing updates in the Current Population Survey Annual Social and Economic Supplement improved data quality by increasing the percent of people with any health insurance coverage and decreasing the percent of people with multiple types of coverage, especially among fully imputed cases.


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