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Medicaid Reporting in the ACS: Findings from Linked Administrative and Survey Data
1. MEDICAID REPORTING IN THE
ACS:FINDINGS FROM LINKED
ADMINISTRATIVE AND SURVEY DATA
Kathleen Thiede Call
ARM meeting
San Diego CA
June 9, 2014
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Acknowledgments
• Funding for this work is supported by the U.S.
Census Bureau
• Collaboration between Census Bureau and SHADAC
to extend previous Medicaid undercount research to
the American Community Survey (ACS)
• Collaborators:
• Brett O’Hara (Census Bureau)
• Michel Boudreaux, Joanna Turner, Brett Fried (SHADAC)
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Background
• Administrative data on public assistance programs are not
sufficient for policy making
• Not timely
• No population denominator
• Incomplete or lower quality covariates
• Population surveys fill these gaps
• Yet they universally undercount public program enrollment
described in administrative data
• Food stamps, public housing, TANF (Lewis, Elwood, and Czajka 1998;
Meyer, 2003)
• Medicaid (Call et al 2008, 2012)
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Research focus
• Describe the concordance of Medicaid reporting in
the ACS and enrollment data in administrative
records
• Compare undercount across characteristics of:
• Individuals: age, income, state
• Medicaid enrollment: scope of benefit, tenure
• Bias to uninsurance estimates
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Data source: American Community
Survey (ACS)
• Large, continuous, multi-mode survey of the US
population residing in housing units and group
quarters
• Added health insurance question in 2008
• One simple multi-part question on health insurance
type
• Unique data source due to its size
• Subgroup analysis (small demographic groups and low
levels of geography)
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ACS health insurance question part “d”
“Is this person CURRENTLY covered by any of the
following types of health insurance or health
coverage plans?
d. Medicaid, Medical Assistance, or any kind of government-
assistance plan for those with low incomes or a
disability?”
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Data source: Medicaid Statistical
Information System (MSIS)
• Medicaid enrollment records
• Longitudinal database of enrollment
• Records originate in the states and are reported to the
federal government
• Includes regular Medicaid and Expansion CHIP
• Tracks all levels of enrollment (e.g., emergency & family
planning)
• Not a perfect gold standard
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Definition differences
• MSIS includes comprehensive and partial coverage
• ACS comprehensive coverage is a subset
• ACS includes Medicaid, CHIP, and state-specific
public programs (will refer to coverage as “Medicaid
Plus”)
• MSIS Medicaid and Expansion CHIP coverage is a
subset
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Investigating survey response errors
• Discordance between MSIS and ACS can come from
definitional differences and survey response error
• Our focus here is on survey response errors which
we investigate by merging the ACS and the MSIS
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Investigating survey response errors (2)
• Use linking methodology developed by the Census
Bureau’s Center for Administrative Records
Research and Applications
• Personal Identification Key (PIK)
• Research conducted at the MN Census Research
Data Center located at the University of Minnesota
• http://mnrdc.umn.edu/
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Investigating survey response errors (3)
• Consider a case to have Medicaid enrollment if they
are covered on the day of ACS interview by full
benefit coverage from Medicaid or Expansion CHIP
• Adjust ACS person weights to account for unlinkable
records
• Although all persons were linked estimates reported
here are for the civilian non-institutionalized
population
• Explicit reports of coverage (not edited)
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Linked file: enrolled in Medicaid on
ACS interview date: Explicit reports
only
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ACS
Yes No
MSIS
Yes
No
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Coverage by age
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Source: 2009 MSIS and ACS civilian non-institutionalized population as analyzed by SHADAC.
Explicit reports (not edited)
* Indicates that estimate is statistically significantly different (at p<.01) from the estimate
for the 0-18 age group.
77% 81%
72%* 71%*
13%
12%
13%*
27%*
10% 8%
14.9%*
1%*
Total 0-18 19-64 65+
Uninsured
Other coverage
Any Medicaid Plus
Implied
undercount
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83%
71%*
64%* 61%*
8%
18%*
26%* 30%*
9% 11%* 11%* 9%*
0-138 139-249 250-399 400+
Uninsured
Other coverage
Any Medicaid Plus
Coverage by FPL
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Source: 2009 MSIS and ACS civilian non-institutionalized population as analyzed by SHADAC.
Explicit reports (not edited)
* Indicates that estimate is statistically significantly different (at p<.01) from the estimate
for the 0-138 FPL group.
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Percent of linked cases reporting Medicaid
Plus enrollment on the ACS interview date
Source: 2008 MSIS and ACS civilian non-institutionalized
population as analyzed by SHADAC; Explicit reports only
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Fifth level77% 75%*
46%
77%*
13% 16%*
35%
13%*
10% 9%*
19%
10%*
Medicaid Expansion CHIP Partial Full
Uninsured
Other coverage
Any Medicaid Plus
Coverage by benefit type and scope
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Source: 2009 MSIS and ACS civilian non-institutionalized population as analyzed by SHADAC.
Explicit reports (not edited)
* Indicates that estimate is statistically significantly different (at p<.01) from the estimate
for those with Medicaid, and for those with partial benefits, respectively.
Benefit Type Benefit Scope
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Fifth level82%
73%*
59%*
41%*
12%
14%*
18%*
24%*
6%
13%*
23%*
34%*
Continuously
Enrolled from
Oct 2008-Mar 2010
(18 months)
Enrolled For 50-99%
of Months
Enrolled For 25-49% Enrolled for 0-24%
Uninsured
Other coverage
Any Medicaid Plus
Coverage by enrollment tenure
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Source: 2009 MSIS and ACS civilian non-institutionalized population as analyzed by SHADAC.
Explicit reports (not edited)
* Indicates that estimate is statistically significantly different (at p<.01) from the estimate
for those who were continuously enrolled.
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Bias to estimates of uninsurance
• A key policy metric is the share of the population that
lacks any type of coverage
• Uninsurance is a residual category, so undercounting
Medicaid partially contributes to bias in uninsurance
• We cannot estimate bias from other sources of coverage
• We cannot estimate bias from those that report Medicaid,
but are in fact uninsured
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Upper bound of bias to uninsurance
attributable to Medicaid misreporting:
Explicit reports only
Count in
millions
Percent
(SE)
Original uninsured estimate 40.9 15.4
(0.05)
Share of the uninsured that
are linked
3.2 7.9
(0.07)
Partially adjusted uninsured
estimate
37.7 14.2
(0.04)
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Source: 2008 MSIS and ACS civilian non-institutionalized
population as analyzed by SHADAC.
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Summary of results
• Although not perfectly comparable, the undercount in the
ACS appears in line with other surveys
• Large (23%), but slightly better than some other surveys
(keep in mind ACS includes Medicaid and other means-
tested public coverage)
• As with other surveys the undercount increases with age
and family income and appears to vary by state
• The undercount translates into an overestimate of
uninsurance of 1.2 percentage points or 3.2 million but it
is likely that there are other offsetting influences
• ACS represents a valuable source of policy analysis
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www.shadac.org
@shadac
Contact Information
Kathleen Thiede Call
callx001@umn.edu
612.624.4802
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Previous research
• SNACC Phases I-VI (2007-2010)
• CPS (CY 2005) implied undercount of about 41%
• NHIS (CY 2002) implied undercount of about 33%
• MEPS (CY 2002) implied undercount of about 18%
• Known enrollees coded as uninsured was 18%, 9%, and 8%
respectively for CPS, NHIS and MEPS
• O’Hara (2009)
• ACS Content Test (CY 2006) implied undercount of 34.4% for the
non-elderly
• Turner & Boudreaux (2010)
• 2008 ACS produces coverage estimates similar to other population
surveys (e.g. 2008 NHIS)
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Coverage by type for linked cases enrolled
in Medicaid on ACS interview date:
Explicit reports only
Any Medicaid Plus
NOT Any Medicaid Plus
77.1 (0.12)
22.9 (0.12)
Employer sponsored insurance 8.3 (0.08)
Direct purchase 2.2 (0.05)
Medicare 3.3 (0.04)
TRICARE 0.3 (0.01)
VA 0.1 (0.01)
Uninsured 9.9 (0.08)
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Source: 2008 MSIS and ACS civilian non-institutionalized
population as analyzed by SHADAC.
Percent (Standard error)
Notas del editor
Put mode in household with household characteristics because mode is not randomly assigned. Instead it is an indicator of late participation given sequential administration of mode in ACS: mail, phone, in-person (now web).