Assessing the Value of the NHISfor Studying Changes in State Health

Coverage Policies: The Case of New York

Sharon K. LongJohn 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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Time Period

Population Group

Target Population

Comparison Group

Pre-reform Period ß0 + ß1 ß0

Post-reform Period ß0 + ß1 + ß2 + ß3 ß0 + ß2

Difference in Outcome Between Time Periods

ß2 + ß3 ß2

Difference-in-Differences Estimate ß3

• Difference-in-differences (DD) models:

Yit = ß0 + ß1 TargetPopit + ß2 Postit+ ß3 TargetPopit*Postit + ß4 Xit + εit

Evaluation Framework

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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

*(**) (***) Statistically significant from zero at the 10% (5%) (1%) level

Public Coverage

Private Coverage Uninsured

Parents

CPS 0.045** -0.010 -0.036*

NHIS 0.085* -0.014 -0.071**

Childless Adults

CPS 0.020 -0.002 -0.024

NHIS 0.027 -0.041 0.014

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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 state-level 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