The Uninsured: Policy and Data Issues Michael J. O’Grady, Ph.D. Assistant Secretary for Planning and Evaluation US Department of Health and Human Services June 10, 2005

 Who are the Uninsured?  Steps Taken to Increase Insurance  New Initiatives to Expand Access  Data Issues Related to the Uninsured  The Medicaid Undercount  Future Policy Work The Uninsured

The Uninsured: What the Data Shows  The uninsured are not one population.  There is considerable diversity among the uninsured population in terms of employment status, income, race/ethnicity and age.  There is also wide variation in the length of time the uninsured go without coverage.  While some are uninsured for years, many are uninsured for just a few months.

Distribution of Uninsured by Attachment to Labor Force, 2003

Distribution of Uninsured by Percent of FPL, 2003

Uninsurance and Poverty Trends, SOURCE: U.S. Census Bureau Current Population Survey.

Changes in wages and salaries and in benefit costs, private industry, Source: BLS, National Compensation Survey Employment Cost Index, December 2004,

SOURCE: Bureau of Labor Statistics, Office of Compensation Levels and Trends, April Employment Cost Index, Private Industry, 12-month Percent Change, Total Benefits and Health Benefits 12-month percent change

Steps Taken to Reduce Uninsurance  Health Savings Accounts  Expansion of Community Health Centers  Trade Adjustment Assistance  Continued Success of SCHIP

 Health Insurance Tax Credits to Individuals  Tax Rebates to Small Businesses to set up HSAs  Further Expansion of Community Health Centers  Increased Outreach to Children New Initiatives to Expand Access to Health Insurance and Health Care

Data Issues Related to the Uninsured  Since the Administration supports incremental approaches, good data is essential for identifying populations in need.  There are four major Federal surveys that measure the uninsured– two HHS, two Census.  These surveys report a wide range of estimates, leading to some confusion and difficulty targeting policy solutions.

Uninsured Estimates from National Surveys SurveyMost Recent Year Method of Estimate Uninsured For Full Year At The Time Of The Survey Uninsured At Any Time During The Year Current Population Survey (CPS), Census million 15.6% N/A Medical Expenditure Panel Survey (MEPS), HHS* million 11.5% 47.3 million 16.6%** (2003) 62.6 million 22.3% Survey of Income and Program Participation (SIPP), Census million 6.8% 38.7 million** 14.0% 66.5 million 24.0% National Health Interview Survey (NHIS), HHS million 10.0% 42.0 million 14.6% 51.4 million 17.9% Notes: - “N/A“ = Survey does not capture this dimension; and - Point in time refers to the period from Jan. 1 through the interview date, which is 5 months on average. *non-elderly **Estimate for March 2001.

Medicaid Undercount  As states improved Medicaid data systems, it became apparent that the CPS increasingly undercounts Medicaid enrollment and overcounts the uninsured.  ACF and ASPE funded a project by RAND to examine the undercount in California by matching Medicaid administrative data with the CPS data.  ASPE has funded two models that analyze the Medicaid undercount – The Actuarial Research Corporation The Urban Institute’s TRIM model

ARC TRIM Eligible for MA/SCHIP Childless Adults Remaining Uninsured Key Subpopulations of the Uninsured

SOURCE: Actuarial Research Corporation, Working Paper: Estimating the Number of Individuals in the United States Without Health Insurance, Marcy Uninsured as Percent of Population

Medicaid Undercount  Our goal is to work with the best data available to develop the best possible solutions.  ASPE is continuing the effort to understand the size of the Medicaid undercount by partnering with the Census Bureau to sponsor further research: SHADAC will examine Medicaid coverage differences among CPS and CMS. SHADAC will match state Medicaid enrollment data to existing Census data. The scope of the project is nationally, state and locally focused.

Future Policy Work  The Administration continues to develop a range of policy tools to increase access and reduce the number of uninsured  Fixing this requires every tool in the toolbox  We continue to work with the data on the uninsured to better target the key subpopulations of the uninsured  So we can match the right policy to the right subpopulation