Response error and the Medicaid undercount in the current population survey

Noon, James; Fernández, Leticia; Porter, Sonya R.

doi:10.1111/1475-6773.13058

Cited by 15 publications

(29 citation statements)

References 12 publications

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“…We offer these results-on CPS-specific questions (general source of coverage and program name), the more widely used post-ACA PPS items, and algorithm-based coverage type reporting accuracy ratesas baseline findings for several reasons. First, while there is a wellestablished literature on reporting accuracy for Medicaid, 2,18,[21][22][23][24][25][26] for other coverage types the literature is far more scant. 19 2,18,19,[21][22][23][24][25][26][27] We also note that the algorithm is simplistic and does not leverage all the data points available in the CPS, nor does it utilize observed reporting patterns across data points among actual enrollees.…”

Section: Discussionmentioning

confidence: 99%

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

Pascale

Fertig

Call

2019

Health Services Research

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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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Section: Discussionmentioning

confidence: 99%

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

Pascale

Fertig

Call

2019

Health Services Research

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“…However, administrative counts are used as the official tally of program enrollment and used by the federal statistical system and academic researchers to benchmark survey estimates. [15][16][17][18][19]…”

Section: Data Limitationsmentioning

confidence: 99%

“…More recent work on the CPS, prior to the redesign of the health insurance module in 2014, found that the undercount declined from 32 percent in 2001 to 22 percent in 2010. 17 Chattopadhya and Bindman 24 found that the undercount increased in the California sample of the CPS from 1995 to 1999. They attributed the increase to the proliferation of Medicaid managed care which they argued was easily confused with private coverage.…”

Section: Introductionmentioning

confidence: 99%

“…The most important of these errors is thought to stem from the response rather than data processing, although less is known about the potential impact of sample coverage error. [15][16][17][18][19] A description of the design features and respondent factors that shape health insurance responses is reviewed elsewhere. [20][21][22] Few studies have examined whether discordance varies by state and year.…”

Section: Introductionmentioning

confidence: 99%

“…14 The magnitude of the undercount ranges from 20 to 30 percent across major federal surveys. [15][16][17] A notable exception to the undercounting of Medicaid/CHIP is the ACS. Boudreaux et al 18 found that the 2009 ACS overcounted administrative records by 8 percent.…”

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confidence: 99%

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Medicaid expansion and the Medicaid undercount in the American Community Survey

Boudreaux

Noon

Fried

et al. 2019

Health Services Research

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Objective To measure discordance between aggregate estimates of means‐tested coverage from the American Community Survey (ACS) and administrative counts and examine the association of discordance with ACA Medicaid expansion. Data Sources 2010‐2016 ACS and counts of Medicaid and Children's Health Insurance Program enrollment from the Centers for Medicare & Medicaid Services. Study Design State‐by‐year counts of means‐tested coverage from the ACS were compared to administrative counts using percentage differences. Discordance was compared for states that did and did not adopt expansion using difference‐in‐differences. We then contrasted the effect of expansion on means‐tested coverage estimated from the ACS with results from administrative data. Data Collection/Extraction Survey and administrative data. Principal Findings One year before expansion there was a 0.8 and 4 percent overcount in expansion and nonexpansion states, respectively. By 2016, there was a 10.64 percent undercount in expansion states vs a 0.02 percent undercount in nonexpansion states. The ACS suggests that expansion increased means‐tested coverage in the full population by three percentage points, relative to five percentage points suggested by administrative records. Conclusions Discordance between the ACS and administrative records has increased over time. The ACS underestimates the impact of Medicaid expansion, relative to administrative counts.

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Changes in Postpartum Insurance Coverage in the US During the COVID-19 Pandemic

2022

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This study's limitations include that the CPS-ASEC has historically undercounted people with Medicaid. 5 Also, for early postpartum respondents, coverage during the past year may not necessarily reflect coverage during pregnancy or the 60 days postpartum because the past year covered preconception, pregnancy, and early postpartum. Currently, the Families First Coronavirus Response Act is set to expire in April 2022. Passage of legislation, which is under consideration in many states, to extend pregnancy-related Medicaid through 1 year postpartum is necessary to maintain pandemic-era gains in postpartum insurance continuity. 6

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Response error and the Medicaid undercount in the current population survey

Cited by 15 publications

References 12 publications

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

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

Medicaid expansion and the Medicaid undercount in the American Community Survey

Changes in Postpartum Insurance Coverage in the US During the COVID-19 Pandemic

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