Assessing the accuracy of survey reports of health insurance coverage using enrollment data.

Health Serv Res

School of Public Health and the State Health Access Data Assistance Center, University of Minnesota, Minneapolis, Minnesota.

Published: October 2019

Objective: To measure the accuracy of survey-reported data on features and type of health insurance coverage.

Data Source: Enrollment records from a private insurer were used as sample for primary survey data collection in spring of 2015 using the Current Population Survey health insurance module.

Study Design: A reverse record check study where households with individuals enrolled in a range of public and private health insurance plans (including the marketplace) were administered a telephone survey that included questions about general source of coverage (eg, employer), program name (eg, Medicaid), portal, premium, and subsidies.

Data Collection/extraction Methods: Survey data were matched back to enrollment records, which indicated coverage status at the time of the survey. Concordance between the records and survey data was assessed.

Principal Findings: Correct reporting of general source of coverage ranged from 77.8 percent to 98.3 percent across coverage type, premium ranged from 91.6 percent to 96.4 percent, and subsidy ranged from 83.0 percent to 91.0 percent. Using a conceptual algorithm to categorize coverage type resulted in sensitivity of 98.3 percent for employer-sponsored enrollees, and 70.6 percent-77.6 percent for the other coverage types, while specificity ranged from 93.9 percent to 99.4 percent across coverage types.

Conclusions: Survey reports of features of coverage suggest they are viable items to include in an algorithm to categorize coverage type. Findings have implications beyond the CPS, particularly for marketplace enrollees.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736923PMC
http://dx.doi.org/10.1111/1475-6773.13191DOI Listing

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