Effects of improvements in the CPS on the estimated prevalence of medical financial burdens

Health Serv Res. 2019 Aug;54(4):920-929. doi: 10.1111/1475-6773.13158. Epub 2019 Apr 29.

Abstract

Objective: To measure the effects of questionnaire and imputation improvements in the Current Population Survey (CPS) on the estimated prevalence of high medical financial burden, that is, families spending more than 10 percent of income on medical care.

Data source: Matched longitudinal sample of CPS data for 2013 and 2014 calendar years.

Study design: The CPS used a split-sample design to field traditional and redesigned questions about 2013 income, and old and new out-of-pocket premium imputation procedures, respectively. For both samples, CPS data for 2014 were from the redesigned income questions and the new imputation procedures. We quantify the effects of the combined survey improvements using differences-in-differences methods.

Principal findings: The improvements were not associated with changes in the estimate of burden in the full sample. Estimated prevalence increased by 2.6 percentage points among nonelderly adults with private insurance, decreased by 6.6 percentage points among nonelderly adults with public coverage, and decreased by 5.8 percentage points among elderly adults with Medicare and no private coverage.

Conclusions: Improvements in the CPS changed the estimated prevalence of high medical financial burden among key subgroups. Researchers should use caution when tracking burden across the time-period in which these improvements were implemented.

Keywords: affordability; data quality; financial burden; imputation; medical care.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Cost Sharing / statistics & numerical data
  • Female
  • Health Expenditures / statistics & numerical data
  • Humans
  • Income / statistics & numerical data
  • Insurance Coverage / economics
  • Insurance Coverage / statistics & numerical data*
  • Insurance, Health / economics
  • Insurance, Health / statistics & numerical data*
  • Longitudinal Studies
  • Male
  • Surveys and Questionnaires / standards*
  • Surveys and Questionnaires / statistics & numerical data*
  • United States