Assessing the Value of the NHIS
for Studying Changes in State Health
Coverage Policies: The Case of New York
Sharon K. Long
John A. Graves
Stephen Zuckerman
AcademyHealth Annual Research Meeting
June 2007
Funded by the Robert Wood Johnson Foundation under the Urban Institute’s
Assessing the New Federalism Project
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Motivation for Study
• Lack of health insurance is a persistent problem
in the US
• Little consensus as to how to increase coverage
• States continue to be the primary source of
innovation in coverage strategies
• Key challenge to evaluating state initiatives is
lack of data
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Focus of the Study
• Explore feasibility of National Health Interview
Survey (NHIS) for state evaluations
– Compare estimates to Current Population Survey
(CPS)
• Use New York as test case: Estimate effects of
New York’s expansion efforts on insurance
coverage for parents and childless adults
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Current Population Survey
• Nation’s primary source of information on labor
force participation, employment and income
• Survey fielded every year with a sample of
approximately 50,000 U.S. households
• Health insurance coverage asked in March
supplement
• Asks about health insurance in prior calendar
year
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National Health Interview Survey
• Nation’s primary source of general health
information for the civilian non-institutional
population
• Survey fielded continuously every year with a
sample of approximately 43,000 U.S. households
• Asks about health insurance coverage in the
month prior to survey
• Also includes data on health indicators, access
and use, and health-related behaviors
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State-Level Estimates in NHIS and CPS
• Both are stratified multistage sample designs,
with sample drawn from every state
• Neither is designed to provide reliable state-level
estimates for all states
• However they do allow state-level estimates for
the largest states
• Sample sizes are larger in CPS than NHIS
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New York’s Reform Initiative
• Health Care Reform Act of 2000
– Family Health Plus (FHP)—public coverage
– Healthy New York (HNY)—subsidized private coverage
• Disaster Relief Medicaid (DRM)
– Temporary Medicaid expansion in New York City
following September 11th
• Timetable:
– HNY started Jan 2001
– DRM started Sept 2001
– FHP implemented in upstate NY Oct 2001 and NYC
Nov 2002
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Data
• 1999 - 2004 NHIS
• 2000 - 2005 CPS (data for 1999 to 2004)
• Samples of parents and childless adults ages 19
to 64
• NY samples sizes:
– N= 19,036 in CPS
– N= 10,189 in NHIS
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Evaluation Framework
• Difference-in-differences (DD) models:
Yit = ß0 + ß1 TargetPopit + ß2 Postit+ ß3 TargetPopit*Postit + ß4 Xit + εit
Population Group
Time Period
Target
Population
Comparison
Group
Pre-reform Period
ß 0 + ß1
ß0
Post-reform Period
ß 0 + ß1 + ß2 + ß3
ß 0 + ß2
ß2 + ß3
ß2
Difference in Outcome Between Time
Periods
Difference-in-Differences Estimate
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ß3
9
Regression Model
• Estimate linear probability models controlling for
age, race, gender, marital status, education, health
and disability status
• All analyses weighted and adjust standard errors
to account for complex survey designs
• Insurance categories: public and non-group (to
capture HNY), private coverage, uninsured
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DD Estimates of Impact of New York’s
Expansion Efforts in the Post-DRM Period
Public
Coverage
Private
Coverage
Uninsured
CPS
0.045**
-0.010
-0.036*
NHIS
0.085*
-0.014
-0.071**
CPS
0.020
-0.002
-0.024
NHIS
0.027
-0.041
0.014
Parents
Childless Adults
*(**) (***) Statistically significant from zero at the 10% (5%) (1%) level
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Conclusions I: The Impacts of
New York’s Expansion Efforts
• New York has been quite successful at reducing
uninsurance for parents.
• Among childless adults, for whom the New York’s
expansion efforts were more limited, we find no
evidence of a significant decline in uninsurance.
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Conclusions II: Using the NHIS
for State Evaluations
• NHIS is viable data source for analyses of statelevel initiatives
– Current insurance status
– More probes for state programs
– Access and use measures
• Limitations
– Smaller sample sizes
– Access to state identifiers requires analyses be done at
the National Center for Health Statistics’ Research Data
Center
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