Monitoring Health Access using
the American Community Survey
Kathleen Thiede Call
Workshop on the Benefits (and Burdens) of the
American Community Survey
June 14, 2012
Washington, DC
Funded by the Robert Wood Johnson Foundation and Federal and State Agencies
About SHADAC
• We help states collect and analyze data to
inform state health policy decisions relating to
health insurance coverage and access to care.
• Our goal: To help states bridge the gap
between health data and the policy-making
process.
• Based at the University of Minnesota
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States’ needs for monitoring coverage
• Consistent estimates
• Trends over time
– Monitor impacts of health reform
• Comparisons across states
• Subpopulation analysis
– Race/ethnicity, poverty, age
– Counties/sub-state areas
• Access to microdata
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Key federal survey data sources
• General household survey
– ACS: American Community Survey
• Employment/Income survey
– CPS: Current Population Survey (ASEC)
• Health surveys
– NHIS: National Health Interview Survey
– MEPS-HC: Medical Expenditure Panel Survey-Household
Component
– BRFSS: Behavioral Risk Factor Surveillance System
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CPS: the good, the bad and the ugly
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Good • Historic trends
• State-level estimates
• Several control
variables available
• State-specific public
health insurance
program names
• Timely data release
Bad • Low sample in
smaller states
• 10% of respondents
have entire
supplement imputed Ugly • Concerns about the
coverage questions
ACS to the rescue
• SAMPLE SIZE!!!!!!!!!!!!!!
• Sub-state estimates
• Robust subpopulation analysis
• Representativeness
• Current coverage measured
• WISH LIST:
– Data updates during the year, like NHIS
– Self reported health status
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Questions we help states answer
• How many uninsured are in my state and
where do they live? What is their
demographic profile?
• How many people in my state will be eligible
for Medicaid under ACA.
• How many kids in each county are eligible for
CHIP or Medicaid but not enrolled?
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Where should we allocate funds for
community clinics?
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West Virginia Sub-State Uninsurance Estimates, Age 0-64
Source: 2009 American Community Survey
All income levels ≤200% of poverty
How many Minnesotans will be NOT be
eligible for Medicaid under ACA?
Eligible, 89% Eligible, 92%
Not Eligible, 11% Not Eligible, 8%
0%
20%
40%
60%
80%
100%
United States Minnesota
462,000
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38,000 4.0 Million
32.7 Million
How many uninsured kids in Colorado are
eligible for CHIP but not enrolled?
10 Source: Colorado Health Institute Analysis of 2008-2010 American Community Surveys
What percent of poor kids are uninsured?
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Uninsurance Rates, Age 0-18, ≤200% FPG
Source: 2010 American Community Survey
Unmet needs with American FactFinder
• Does not provide all policy-relevant measures
– Health insurance unit rather than Census family
– Federal poverty guidelines (HHS) rather than
thresholds
– FPG cuts at ACA policy levels (138%, 200%)
• Not user-friendly
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SHADAC’s technical assistance for states
• SHADAC’s Data Center
– Online table and chart generator of policy-relevant tables
of health insurance coverage estimates from the ACS and
CPS.
• 12 years of rigorous investigation
• Technical assistance to help states use data
• Education and capacity building
• FPG at 138% and 200%
• Health Insurance Unit
– Family relationships assigned according to health plan
eligibility
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SHADAC’s Data Center
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SHADAC’s Health Insurance Unit (HIU)
Married couple
with two children
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Married
Kids
Grandparents
Child Spouse
Grandchild
• Census family has 1 unit
• HIU family has 1 unit
• Census family has 1 unit
• HIU family has 2 units
Grandparents, married
child, and grandchild
Conclusions
• The ACS fills a gap in state-level data to inform
policy decisions
– Statewide and locally
– Subpopulations; small minority, age or income groups
• The ACS is widely accessible
– Don’t need to be a data programmer to access this
information
• The ACS is a great tool for modeling/linking with
other data to develop state-level estimates
• Benchmarking and sub-population analysis will be
compromised if ACS becomes voluntary
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