Measurement Error in Public Health Insurance Reporting in the American Community Survey: Evidence from Record Linkage

Abstract

Objective: Examine measurement error to public health insurance in the American Community Survey (ACS).

Data sources/study setting: The ACS and the Medicaid Statistical Information System (MSIS).

Study design: We tabulated the two data sources separately and then merged the data and examined health insurance reports among ACS cases known to be enrolled in Medicaid or expansion Children's Health Insurance Program (CHIP) benefits.

Data collection/extraction methods: The two data sources were merged using protected identification keys. ACS respondents were considered enrolled if they had full benefit Medicaid or expansion CHIP coverage on the date of interview.

Principal findings: On an aggregated basis, the ACS overcounts the MSIS. After merging the data, we estimate a false-negative rate in the 2009 ACS of 21.6 percent. The false-negative rate varies across states, demographic groups, and year. Of known Medicaid and expansion CHIP enrollees, 12.5 percent were coded to some other coverage and 9.1 percent were coded as uninsured.

Conclusions: The false-negative rate in the ACS is on par with other federal surveys. However, unlike other surveys, the ACS overcounts the MSIS on an aggregated basis. Future work is needed to disentangle the causes of the ACS overcount.

Keywords: American Community Survey; CHIP; Medicaid; survey methods.

Figure 1

Unadjusted and Adjusted False‐Negative Rates for Children. (A) Unadjusted Rate for Children Age 0–18. (B) Adjusted Rate for Children Age 0–18 Source: Reweighted estimates from the 2009 American Community Survey linked to MSIS, civilian noninstitutional population. The regression adjusted rates are based on a logistic regression model and are calculated using average marginal effects. They control for race, gender, poverty status, citizenship, household education, and household employment. Tables of values and regression coefficients are included in the appendix.

Figure 2

Unadjusted and Adjusted False‐Negative Rates for Adults. (A) Unadjusted Rate for Adults Age 19 and over. (B) Adjusted Rate for Adults Age 19 and over Source: Reweighted estimates from the 2009 American Community Survey linked to MSIS, civilian noninstitutional population. The regression adjusted rates are based on a logistic regression model and are calculated using average marginal effects. They control for race, gender, poverty status, citizenship, household education, and household employment. Tables of values and regression coefficients are included in the Appendix.