Estimating the Number of Individuals in the U.S. Without Health Insurance

Prepared for:

Office of the Assistant Secretary for Planning and Evaluation
Office of the Secretary
Department of Health and Human Services
Room 405F
Humphrey Building
200 Independence Avenue, S.W.
Washington, D.C. 20201

Submitted by:

Cathi M. Callahan
James W. Mays

Actuarial Research Corporation
6928 Little River Turnpike, Suite E
Annandale, VA 22003
(703) 941-7400
www.aresearch.com

With Assistance From:
George D. Greenberg, DHHS/ASPE
Robert Stewart, DHHS/ASPE

This report is made pursuant to DHHS Contract Number HHS-100-00-0016.  The analysis and conclusions contained herein are solely those of the contractor and do not represent an official opinion or endorsement by the Department.

The Census Bureau's Current Population Survey (CPS) has long served as the most widely-cited source of statistics on the nation's uninsured. But over time, the CPS has undergone several methodological changes that create some inconsistency in the time series of uninsured date. This report presents the Acturarial Research Corporation's (ARC) adjustments to the CPS to create a consistent time series.

Executive Summary

Although there are multiple sources of data on the uninsured, the Census Bureau’s Annual Social and Economics Supplement (ASEC) to the Current Population Survey (CPS) is often the main focus of analytic work. Some of the reasons for this are: it is the most widely cited source of data, it has the largest sample size of any major survey with data on the uninsured, it can be used for state-level analysis, and it contains detailed data allowing for analysis of the uninsured by income level. However, one factor that has complicated the analysis of the uninsured is that this supplement to the CPS has changed considerably over time, making longitudinal analysis less reliable.

Without adjusting for these changes, we are able to look only at the most recent survey years which use a consistent methodology. For CY 2003, the CPS estimates that 45.0 million individuals, or 15.6 percent of the U.S. civilian non-institutionalized population, were without health insurance for the entire year. This number is a full year uninsured estimate based on the structure of the CPS questionnaire – which asks respondents about their insurance coverage at any time during the prior calendar year. When compared, however, to other surveys that examine both full year and point in time uninsured, the CPS estimate appears to more closely resemble the point in time estimate from these other surveys.

While some analysts have suggested, as far back as 1986, that the CPS represents a measure of the uninsured at a point in time, ASPE believes that it is more likely that the CPS does represent the full year uninsured, but that the estimate is inflated due to poor reporting of Medicaid coverage and perhaps other coverage types as well.

In order to more fully examine this premise, it becomes necessary first to adjust for the survey changes that have occurred in the CPS over time. Focusing mainly on the period from CY 1994 (March 1995) forward but looking back as far as CY 1987 (March 1988), these changes (and our adjustments) include: a) updating the survey weights to reflect the new decennial Census, b) adjusting for consistency in the insurance questionnaire which was modified beginning in March of 1995, c) adjusting for consistency in employer sponsored insurance (age of policy-holder, coverage from outside of household), and d) adjusting for inclusion of questions to verify uninsurance and coverage under SCHIP.

Once these changes have been taken into account and adjusted for, the Medicaid undercount can then be considered. For CY 1995, the CPS showed just over 30 million persons covered by Medicaid. CMS data, however, suggests that approximately 39 million non-institutionalized persons were covered under Medicaid some time in that year. By CY 2002, this discrepancy has doubled, with the CPS finding fewer than 29 million ever covered by Medicaid, while CMS data suggests an “ever enrolled in Medicaid” count on the order of 46 million in the noninstitutionalized population¹. The CPS counts are lower by subpopulation both when compared to CMS estimates as well as when compared to data from other surveys.

For CY 2003, correcting for an undercount of 17 million persons lowers the full year uninsured estimate by just over 9 million persons. For CY 2003, with this adjustment, the almost 36 million uninsured (as compared to an unadjusted 45.0 million) is more consistent with the full year uninsured count reported by MEPS of 31.7 million (although for an earlier year).

¹Explained in more detail in the body of this paper, CMS presents Medicaid enrollment statistics both from MSIS data as well as summary historical counts and projections of the Medicaid population on their website. Our use of these estimates of the Medicaid population is explained in detail in the Technical Appendix to this document

Introduction

As policy makers continue to search for solutions to the problem of the uninsured, analysts have sought ways to better understand who comprise the uninsured population and how this population has changed over time. Although there are multiple sources of data on the uninsured, the Census Bureau’s Annual Social and Economics Supplement (ASEC)² to the Current Population Survey (CPS) is often the main focus of analytic work. Some of the reasons for this are: it is the most widely cited source of data, it has the largest sample size of any major survey with data on the uninsured, it can be used for state-level analysis, and it contains detailed data allowing for analysis of the uninsured by income level (a significant factor given how most proposed solutions to the uninsured problem are means-tested in some manner). However, one factor that has complicated the analysis of the uninsured is that this supplement to the CPS has changed considerably over time, making longitudinal analysis less reliable.

These survey changes create sources of discontinuity in the CPS data that need to be adjusted for over time in order to allow policymakers to understand the trends in both direction (increases or decreases in coverage) and level (how many people are insured or uninsured). As a result, the Office of the Assistant Secretary for Planning and Evaluation (ASPE) has been working with Actuarial Research Corporation (ARC) to refine the CPS time series and account for other CPS data issues.

This report discusses estimates of the number of uninsured from the unadjusted CPS, looks at the CPS in the context of other surveys that estimate the number of uninsured, and discusses revisions to the survey and how we have adjusted for them in order to have a consistent time series. Finally, we will look at how a particular limitation with the CPS estimates (the count of persons with Medicaid) can be adjusted for, and how this affects the estimate of the uninsured.

How Our Approach is Different: The focus of this report is covered lives, e.g. the counts of people who have or do not have health insurance coverage during different time intervals or at specific points in time. The number of uninsured reported will vary substantially depending on the approach selected. The report does not address changes in health insurance benefits, shares of premiums paid by employers and employees, or other changes in the health insurance market that occurred over the period studied. We concentrate on data from the last nine years, starting with the March 1995 CPS and ending with the most recent (March 2004) year available. We begin at March 1995 due to the many major changes in the survey that occurred that year and which affect the insurance estimates from that point forward. In addition, we have also applied our methodology back to CY 1989 (March 1990) in order to look at changes in insurance over a longer time period. Due to the many improvements that occurred with the March 1995 survey, we are more confident in our estimates from that point forward. Our methodology is explained below, and in more depth in the methodological appendix accompanying this paper.

²The Annual Social and Economics Supplement to the CPS was formerly known as the March Demographic Supplement and is also known as the “March CPS.” Data on the ASEC is collected in March and insurance information refers back to the prior calendar year (for example the 2003 ASEC is collected in March 2003, with insurance information from CY 2002).

CPS Portrait of the Uninsured Population

Before discussing changes to the survey over time, it is important to first be familiar with the characteristics of the uninsured based on the most recent CPS. This will establish a baseline against which the insights gained from creating a more consistent time series can be measured. Using data from the 2004 Annual Social and Economics (ASEC) Supplement to the Current Population Survey (formerly called the March Demographic Supplement), which contains information on insurance for calendar year 2003, ASPE examined the demographic characteristics of the uninsured population. The CPS estimates that 45.0 million individuals, or 15.6 percent of the U.S. civilian population, were without health insurance for the entire year in 2003. The main source of health insurance coverage was employer-sponsored insurance (60.4% of persons had such coverage), followed by Medicare (13.7%) and Medicaid (10.7%).

Table 1 contains a more detailed breakdown of the uninsured population. An important consideration to keep in mind when reviewing the demographics of the uninsured is that there are several ways to analyze the data. For example, one can determine the uninsured rate of a given demographic group, such as “what percentage of men are uninsured?” Alternatively, one can calculate the percentage of the uninsured that is comprised of given demographic group, such as “what percentage of the uninsured are male?” Table 1 shows, for some key demographic groups:

• the total number of individuals within those groups,
• their percentage of the population,
• the number of uninsured within those groups,
• the uninsured rate for the group, and finally,
• the percent of the total uninsured population the uninsured from that group represent.

Table 1. The Uninsured in 2003 According to the Unadjusted CPS

Source: The 2004 CPS