Although most researchers agree on the general trends of health insurance coverage -- that is, that the rate of private or employer-sponsored coverage is falling while public sponsored coverage is rising -- they often disagree on the actual number of uninsured, or even how the uninsured should be defined and measured. For example, although the most widely cited estimate of the number of uninsured children in America is about 9.8 million, which is based on the March 1996 Current Population Survey (CPS), there is debate over whether this estimate is closer to the number of uninsured at a point in time or the number uninsured throughout the year. Moreover, estimates of the uninsured using alternative data sources, or using CPS data that have been edited because of problems with the reporting of Medicaid, vary from the basic CPS estimate by as much as one-third.
This chapter reviews the literature on the recent estimates of the uninsured and why the estimates from various databases differ. We review the estimates of the uninsured based on the following databases: the March CPS, the SIPP, the National Health Interview Survey (NHIS), the National Medical Expenditure Panel Survey (MEPS), the Community Tracking Study (CTS), and the Kaiser/Commonwealth Survey of Americans.
A. MEASURING THE UNINSURED
Estimates of the number of uninsured may differ for a number of reasons, such as which data are used for the estimate, how the data are interpreted, and the time-period over which the uninsured are defined. Monheit (1994) reviewed how estimates of the uninsured population are obtained and reached four general conclusions. First, a consistent, long-term series of estimates is not available. For example, the CPS, the most commonly used source for health insurance coverage, changed the content of its health insurance questions at various times, which has resulted in artificial changes in the number who are uninsured from one year to the next. Second, analysts using the same data may obtain varying estimates for the same time periods because the data can be interpreted in different ways. For example, estimates of the uninsured done by The Urban Institute using CPS data are lower than estimates by other groups using the same data because The Urban Institute adjusts their estimates for the known underreporting of Medicaid in the CPS. Third, as mentioned above, estimates across alternative data vary. And fourth, estimates vary depending upon the time-frame around which the estimate is made. For example, the number of persons uninsured throughout a given year will be less than the number of uninsured at a point in time which, in turn, will be less than the number of uninsured at any time during a given year.
B. CPS ESTIMATES OF THE UNINSURED
The most commonly cited estimates of the number of uninsured children -- those produced by the Census Bureau, the Congressional Budget Office (CBO), the U.S. General Accounting Office (GAO), the Employee Benefit Research Institute (EBRI), and The Urban Institute -- use the March CPS as their source. The CPS, which is the source of the official Government statistics on employment and unemployment, is a nationally representative monthly survey of approximately 57,000 households in the United States. The sample is based on the civilian noninstitutionalized population of the United States, which includes persons living in households and group quarters (for example, college dormitories and rooming houses), but does not include residents of institutions (for example, homes for the aged) and persons living abroad. As well as being nationally representative, the sample is also representative of each of the 50 states and the District of Columbia, although for most states the samples are too small for precise state-level estimates.
The main purpose of the survey is to collect, by means of personal interviews, information on the employment status of the population during the survey month. In addition, supplemental questions are regularly added to the core questionnaire on topics such as health, education, income, and previous work experience. The March CPS contains supplemental questions on the health insurance status of each person in the household in the prior calendar year. Specifically, respondents are asked whether they had any of various types of private or public health insurance in the previous year. Respondents are permitted to report more than one type of health insurance coverage, although it is impossible to tell from the data whether persons with multiple types of coverage had the coverage concurrently or at different times during the previous year. The health insurance portion of the March 1995 CPS questionnaire is presented in Appendix A.
Respondents are never asked directly whether they were uninsured in the previous year. Instead, estimates of the uninsured are calculated as a residual -- that is, the uninsured are all those who do not report having some type of coverage in the previous year. As a result, the uninsured are those without any coverage throughout the previous year. However, some researchers believe that the CPS estimates of the uninsured are too high and, thus, that respondents may be reporting their health insurance status as of the interview date. This and other issues pertaining to estimates of the uninsured according to the CPS are discussed below.
The two principal classes of estimates of the uninsured using the CPS are (1) those done by the Census Bureau, CBO, GAO, and EBRI; and (2) those done by The Urban Institute. These estimates are summarized in Table II.1. The Urban Institute's estimates of the uninsured differ from the other estimates because they adjust for the underreporting of Medicaid in the CPS.
1. Census Bureau, CBO, GAO, and EBRI Estimates
Beginning with the March 1995 CPS, when the health insurance questions were revised to eliminate the possibility of respondent inconsistencies, the Census Bureau (Bennefield 1996a), CBO
(Bilheimer 1997), GAO (1997), and EBRI (Fronstin 1996) began publishing identical estimates of the number of uninsured.(1) Using the March 1996 CPS, they found the following:
None of these organizations adjusted their estimates for the underreporting of Medicaid in the CPS.
2. The Urban Institute's Estimates
The Urban Institute's estimates of the uninsured differed from others because the Institute adjusted for the underreporting of Medicaid in the CPS. The Institute used its Transfer Income Model (TRIM2), a microsimulation model, to test for Medicaid eligibility among non-reporters of Medicaid and then selected individuals to participate so that the size of the resulting Medicaid population in the model matched Health Care Financing Administration (HCFA(now known as CMS)) administrative data according to age and disability status of all persons ever enrolled in Medicaid in a given year. Using the TRIM2 model with March 1996 CPS data, the Institute found the following:
The estimate of 6.9 million uninsured children in 1995 is 30 percent lower than the CPS estimates that include no adjustment for the underreporting of Medicaid. In all, the Institute simulated 2.9 million children to participate in Medicaid who reported no health insurance coverage in the CPS.
Researchers debate whether the Institute's adjustment for the underreporting of Medicaid yields improved estimates of the uninsured. One potential problem is that the Institute's adjustment may overcompensate for the underreporting because the adjustment is based on administrative estimates of the number of persons ever enrolled in Medicaid during the year, while CPS estimates of the uninsured may reflect those uninsured at a point in time. Another potential problem is that although the Institute adjusts for Medicaid underreporting, it makes no adjustment to reported private employment coverage, which could be either over- or underreported. This is important because the uninsured are calculated as a residual and, therefore, accurate estimates of the uninsured require accurate estimates of coverage for all other types of insurance. Despite these potential problems, the fact remains that Medicaid is substantially underreported in the CPS and, therefore, will affect most estimates of the uninsured in one way or another. The issues of underreporting of Medicaid and whether the CPS estimates may reflect those enrolled at a point in time are described in more detail below.
3. CPS Health Insurance Measurement Issues
When interpreting estimates of the uninsured done by researchers using the CPS, it is important to understand that these estimates are affected by various measurement issues that specifically pertain to the CPS data. These issues include the following: the time-frame of the CPS measures of health insurance, Medicaid underreporting, and survey undercoverage of the population.
a. Time-Frame
If respondents answer the CPS health insurance questions as intended -- that is, as coverage at any time during the previous year -- then estimates of the uninsured should be interpreted as those without coverage throughout the previous year. However, some researchers believe that the CPS estimates of the uninsured are too high and, thus, that respondents may be reporting their health insurance status as of the interview date. Swartz (1986) compared CPS estimates of the uninsured with estimates from three other surveys that asked respondents about their health insurance coverage as of the interview date. The three other surveys were: the National Medical Care Expenditure Survey (1977), the Health Interview Survey (1978), and the National Medical Care Utilization and Expenditure Survey (1980). She found that the CPS estimates more closely resembled the point-in-time estimates of these surveys. CBO agreed with Swartz and considers its own CPS-based estimates of the uninsured to be closer to a point-in-time estimate rather than an estimate of those uninsured throughout the previous year (Bilheimer 1997).
Although the CPS estimates may resemble point-in-time estimates of the uninsured, there is evidence that some respondents interpret the questions correctly and report their status as of the previous year. For example, in 1995, 15 percent of children enrolled in Medicaid according to the CPS also reported coverage by private health insurance (Fronstin 1996). These children are probably not reporting their current status, since it is unlikely that this many children would be covered by Medicaid and private insurance at the same time. Instead, they are probably reporting their status as of the previous year when they were covered by private insurance for part of the year and Medicaid for part of the year. Other researchers provide additional evidence that many respondents interpret the questions correctly. For example, Kronick (1989)(3) found that private employer-sponsored health insurance coverage in the CPS is more consistent with employment status in the previous year than in the interview month. In addition, the first round of the Medical Expenditure Panel Survey (MEPS), which asked respondents whether they were uninsured continuously from January 1, 1996 to their interview date 3 to 6 months later (and links their responses to employment related data), provided estimates that were strikingly similar to the CPS (Beauregard et al. 1977).(4)
In a more recent analysis, Bennefield (1996c) compared longitudinal data from the SIPP with the standard health insurance data from the CPS and with data from experimental questions on the March 1995 CPS that asked about current health insurance status. Bennefield's results indicated that CPS respondents interpreted the standard health insurance questions correctly and provided their health insurance status as of the previous year. However, he found that respondents may have had recall problems and failed to report some coverage and, as a result, the CPS estimates of the uninsured looked more like point-in-time estimates. Some researchers, though, doubt the usefulness of the experimental health insurance questions on the CPS because they yielded extremely large numbers of uninsured.(5)
Long and Marquis (1996) compared the 1993 March CPS estimates of the uninsured in 10 states with the findings from the Robert Wood Johnson Foundation (RWJF) Family Health Insurance Survey. The RWJF survey was administered to approximately 2,000 families each in Colorado, Florida, Minnesota, New Mexico, New York, North Dakota, Oklahoma, Oregon, Vermont, and Washington during 1993. The uninsured and those covered by Medicaid were oversampled. The content includes considerable detail on insurance status -- both current and throughout the previous year. Across the 10 states included in the RWJF survey, the CPS estimate of the uninsured for all persons (14.7 percent) fell between the RWJF estimate of the currently uninsured (15.7 percent) and the uninsured throughout the previous year (12.2 percent). Long and Marquis also examined each state individually and found that for 9 of 10 states, the CPS measure fell between the RWJF current and throughout the previous year measures; in the remaining state, the CPS estimate was above the RWJF estimate of the currently uninsured by only 0.2 percentage points. Long and Marquis concluded that using the CPS as if it were a measure of the currently uninsured generally will understate estimates of the uninsured at a point in time. However, the CPS measure was considerably closer to the RWJF currently uninsured estimate than the uninsured throughout the previous year. The CPS estimate was only 6 percent below the RWJF currently uninsured estimate, but 20 percent above the RWJF estimate of the uninsured throughout the previous year.
Overall, though, most researchers tend to agree that the CPS probably contains a mixed bag of reporting -- that is, some respondents report health insurance status during the previous year, some report it as of the interview date, and some fail to report it altogether -- which, in the end, yields estimates that are probably best interpreted as health insurance status at a point in time.
b. Medicaid Underreporting
One weakness of the CPS is that the number of persons reporting Medicaid is lower than the number of persons enrolled in Medicaid in a given year according to administrative data from HCFA(now known as CMS) -- the agency that administers the Medicaid program. This problem is often referred to as "underreporting." Underreporting is thought to occur because survey respondents may not admit to being covered because of the stigma associated with public assistance programs, because they are not currently receiving health services, or because they may not realize they are covered by Medicaid.(6)
Most estimates of the number of uninsured use CPS data that are not first adjusted for Medicaid underreporting. This could lead to overestimates of the uninsured if many of those that appear uninsured are actually enrolled in Medicaid. It is important to recall, though, that CPS estimates of the uninsured are calculated as a residual and, therefore, accurate estimates rely on the accurate reporting of both Medicaid and private coverage. Unlike Medicaid, though, it is not known whether private insurance is reported accurately using the CPS.
The evidence for underreporting on the CPS is usually based on comparisons with HCFA(now known as CMS) administrative data, which show the number of persons ever enrolled in Medicaid during a given year. This comparison is valid if CPS health insurance questions are answered as intended -- that is, health insurance status during the previous year. However, if the CPS provides a point-in-time estimate, as many researchers believe it does, then comparing CPS Medicaid enrollment estimates with HCFA(now known as CMS) administrative data will tend to exaggerate the problem of Medicaid underreporting, since the number of Medicaid enrollees at a point in time will always be less than those ever enrolled during a year.(7) Comparisons with HCFA(now known as CMS) data will also be exaggerated because persons in institutions, who often receive Medicaid, are not within the sampling frame of the CPS. However, most institutionalized Medicaid enrollees are elderly (in nursing facilities), while the estimates of the uninsured in this paper focus on the nonelderly. Despite the definitional differences between HCFA(now known as CMS) and CPS data, the apparent underreporting of Medicaid on the CPS is probably too large to be explained by time-period and sample frame differences alone.
Holahan et al. (1995) estimated that, in 1990, 19.6 million nonelderly individuals were enrolled in Medicaid according to the CPS versus 24.7 million according to HCFA(now known as CMS) administrative data -- a 21 percent difference. To be comparable to the underreporting estimate of Holahan et al., underreporting should be calculated in relation to what HCFA(now known as CMS) refers to as "Medicaid eligibles," which is defined by HCFA(now known as CMS) as those ever enrolled during the year.(8) In 1993, 34.3 million nonelderly individuals were enrolled in Medicaid according to HCFA(now known as CMS), a 15.5 percent difference from the CPS estimate. As shown in the top panel of Table II.2, Medicaid underreporting then rose to 19.8 percent in 1994 and 21.0 percent in 1995 (Fronstin 1997b; HCFA(now known as CMS) 1996).
Medicaid underreporting for children age 0 to 17 follows the same general trend as that for all nonelderly individuals, although the underreporting rate is slightly higher. In 1995, for example, 16.5 million children were enrolled in Medicaid according to the CPS versus 21.4 million according to HCFA(now known as CMS) data -- 22.9 percent underreporting (bottom panel of Table II.2; Fronstin 1997a; HCFA(now known as CMS) 1996). Therefore, the underreporting of Medicaid among children could be as high as 4.9 million
children in 1995, suggesting that many of the 9.8 million children thought to be uninsured according to the CPS could actually be enrolled in Medicaid.(9) However, some of the Medicaid underreporting could be due to (1) children with both Medicaid and private coverage in the previous year reporting only private coverage, and (2) the CPS survey systematically failing to obtain interviews from population subgroups that may receive Medicaid disproportionately.
Underreporting of Medicaid on the CPS may actually be worse than is indicated by the rates in Table II.2 because HCFA(now known as CMS) data sometimes underreport the number of Medicaid enrollees. A few states submit to HCFA(now known as CMS) only their data on recipients, or persons who receive services in a given year, rather than enrollees, or all persons who were enrolled during the year. This is evidenced by the fact that the number of enrollees is either zero or almost the same as the number of recipients. For example, the difference between the number of enrollees and the number of recipients is 3 percent or less in 1995 in the following states: Connecticut, District of Columbia, Hawaii, Louisiana, New York, and Tennessee.(10)
Overall, little research has been done on the problem of Medicaid underreporting and its effect on the estimates of the uninsured, partly because, until recently, HCFA(now known as CMS) Medicaid enrollment data were not considered reliable. Recent improvements to the HCFA(now known as CMS) data, though, make this type of research more feasible. Such research is warranted since studies on the characteristics of the uninsured will be affected to the extent that those who appear to be uninsured may actually be enrolled in Medicaid.
c. Undercoverage of the Population
According to the Census Bureau (Bennefield 1995), all demographic surveys, including the CPS and the SIPP, suffer from undercoverage of the population. Undercoverage results from missed housing units in the sampling frame and missed persons within sampled households. The Census Bureau estimated that the overall CPS and SIPP undercoverage rate is about seven percent and that undercoverage varies with age, sex, and race. They reported that for some groups, such as 20 to 24 year old black males, the undercoverage rate is as high as 27 percent. The Census Bureau noted that even though their weighting procedures partially correct for the bias due to undercoverage, the final impact of undercoverage on estimates is unknown. This problem could bias estimates of the uninsured if the groups that are missed in the survey are either disproportionately insured or disproportionately uninsured.
C. SIPP ESTIMATES OF THE UNINSURED
The value the SIPP adds to analyses of the uninsured is that it allows researchers to examine the dynamic aspects of the uninsured that are not apparent in the oft-cited point-in-time estimates. For example, Swartz and McBride (1990) pointed out that data collected at a point in time from a population with dynamic movements are more likely to contain people who are in long spells without health insurance even though most people have fairly short spells (this phenomenon is described in more detail below).(11) In short, using point-in-time data to describe the characteristics of the uninsured presents a myopic picture of all individuals who lose health insurance. The SIPP's longitudinal data, though, can answer questions such as:
1. Overview of the SIPP
The SIPP is a multipanel longitudinal survey of adults in a sample of approximately 20,000 households selected to be representative of the noninstitutionalized resident population of the United States. The research reviewed below is based on data from either the 1990, 1991, or 1992 SIPP panels. These panels followed sampled adults for approximately two-and-a-half years, interviewing them either in person or by telephone every four months.(12) During each SIPP interview (called a wave), household-, family-, and person-level information is collected for each of the previous four months on income, labor force activity, program participation (such as AFDC, Food Stamps, and Medicaid), and health insurance status.
Over the life of a given SIPP panel, the Census Bureau produces a separate data file for each wave. At the conclusion of the panel, the Census Bureau produces a full panel file containing one record for each person who was ever a member of a SIPP household. This file differs in two important ways from what users would create were they to link each of the wave files for the panel. First, an entirely separate set of edit and imputation procedures is used by the Census Bureau when creating the full panel file, including the imputation of missing waves when a single missing wave is bounded on both sides by reported information for that person. Because these data processing procedures take advantage of the reported longitudinal information in the file, the full panel files are generally believed to have superior data to those contained in the wave files. Second, the full panel files contain weights that are not available on any of the wave files. The Census Bureau generally creates two types of weights for its longitudinal files: (1) calendar year weights for all persons present throughout a given calendar year of the panel, and (2) panel weights for persons present throughout the entire panel. All other persons do not receive weights and, thus, are not counted in longitudinal estimates.(13)
Like all longitudinal surveys, not all respondents remain in the survey for all the interviews. This is known as attrition and may bias estimates using the SIPP to the extent that those who attrite are systematically different from those that do not. Research on this topic has indicated that for many estimates, there is no detectable bias that can be attributed to attrition. Still, more research needs to be conducted before firm conclusions can be drawn on the effects of attrition in the SIPP.
2. Measuring Health Insurance Status Using the SIPP
The SIPP asks respondents whether they were covered by employer- or union-sponsored insurance, other private health insurance, Medicare, military health care, or Medicaid. Like the CPS, estimates of the uninsured using the SIPP are calculated as a residual -- that is, the uninsured are those who do not report receiving coverage of any type. Unlike the CPS, though, SIPP respondents are asked about health insurance coverage in each month of the 4-month reference period. The health insurance portion of the 1993 SIPP survey instrument is presented in Appendix B.
The SIPP also suffers from underreporting of Medicaid. For example, HCFA(now known as CMS) administrative data show that 35.7 million persons were ever enrolled in Medicaid in 1992. In comparison, Bennefield (1996c) calculated that 12.3 percent of all persons, or approximately 30.5 million persons, reported Medicaid for at least one month in 1992 based on the SIPP -- an underreporting of about 15 percent, or roughly the same magnitude of the underreporting on the CPS. Therefore, the number of uninsured based on the SIPP may be overestimated somewhat, assuming that private health insurance is reported accurately (or, at least, not overreported). Also like the CPS, the SIPP suffers from undercoverage of the population in general. According to the Census Bureau, though, the final impact of undercoverage on estimates is unknown.
Various SIPP estimates of the uninsured, even those for the same time period, may not be comparable because there are a number of different alternatives for analyzing a given time period based on the SIPP. Some examples of these alternatives are as follows:
This last point deserves further explanation. Researchers' estimates of the uninsured using the SIPP can vary substantially depending on whether they use duration estimates for all spells observed over a period of time or whether they simply examine spells in progress at a point in time. Swartz and McBride (1990) pointed out that studies of the dynamics of health insurance coverage that concentrate on uninsured spells already in progress are misleading because spells in progress at a point in time are disproportionately long spells, whereas most spells are actually fairly short. Using data from the 1984 panel of the SIPP, Swartz and McBride demonstrated this phenomenon by comparing the distribution of spell lengths for all persons for whom they could observe a spell beginning in the SIPP with the distribution of spell lengths among persons whose spells were in progress at a point in time. Using a survival analysis technique, they found that half of all observable spells ended within 5 months, and another 16.5 percent ended within 5 to 8 months. Only 15 percent of all spells lasted more than 2 years. In contrast, among spells in progress at a point in time, 58 percent lasted more than 2 years and only 13 percent ended within 5 months.
Although researchers have calculated estimates for a wide variety of time periods, this section discusses only a few estimates simply to give an overall picture of the uninsured according to the SIPP. In addition, we do not attempt to compare and contrast estimates because, as stated above, estimates can vary based on the SIPP files and methodology used and most researchers do not publish their precise methodology. A more detailed set of estimates that researchers have produced is presented in Tables II.3 (for children) and II.4 (for all persons).(14) First, though, we compare SIPP estimates of the uninsured with the corresponding CPS estimates.
3. SIPP Versus CPS Estimates of the Uninsured
Bennefield (1996c) compared the SIPP and CPS estimates of the uninsured and offered explanations as to why they seem to differ. Bennefield compared the CPS estimates of the uninsured for 1991, 1992, and 1993 with two types of estimates from the SIPP: (1) the SIPP first quarter average monthly estimates for 1992, 1993, and 1994, which can be considered point-in-time estimates; and (2) the SIPP estimates of those uninsured throughout the year for 1991, 1992, and 1993.
He chose the SIPP first quarter average monthly estimates for his SIPP point-in-time estimates because they correspond with March, the month in which the CPS collects data about the previous year. Bennefield found that the CPS estimates are more similar to the SIPP point-in-time estimates than the annual estimates, suggesting that CPS respondents were reporting their current health insurance status ( Table II.5). He found uninsurance rates of 14 to 15 percent for all persons for both the CPS estimate and the SIPP point-in-time estimate.(15) In contrast, he found uninsurance rates of 7 to 8 percent for the SIPP annual estimates.
Bennefield showed that the estimate of the uninsured throughout a given year using the SIPP is substantially lower than CPS estimates because the SIPP has substantially more persons reporting private health insurance coverage. For example, in 1993 the SIPP showed an 81 percent annual coverage rate for private health insurance versus 70 percent for CPS; in comparison, the SIPP point-in-time coverage rate was 72 percent. Unlike estimates of private insurance, estimates of government-sponsored health insurance were generally consistent across timeframes and surveys -- the CPS Medicaid coverage rates were 11 to 12 percent for the periods analyzed, and both the annual and point-in-time SIPP coverage rates were 9 to 11 percent for the periods analyzed. It is not clear what conclusions should be drawn from the fact that private health insurance coverage accounted for much of the difference between the CPS and SIPP annual estimates. On the one hand, if recall problems were to blame for higher CPS estimates of the uninsured compared with SIPP annual estimates, then respondents seemed to be more likely to fail to recall private insurance than public insurance. Such an explanation is plausible if those publicly insured are more likely than those privately insured to have coverage throughout the year. On the other hand, CPS respondents may simply be reporting their health insurance status as of the interview date.
Even though the CPS estimates of the uninsured are more widely cited, Census Bureau officials suggest that SIPP may be better suited to measure health insurance information for a number of reasons.(16) First, the SIPP may have less recall error than the CPS because it has a shorter recall period (4 months for the SIPP versus over 1 year for the CPS). Second, respondents may be more likely to answer the SIPP health insurance questions because the questions are more detailed and are better positioned at the beginning of the interview. Third, the SIPP attempts to interview each person in the household age 15 and over, whereas the CPS interviews only one person, who may not obtain accurate information on all household members. Finally, the SIPP is especially designed to measure program participation (such as Medicaid), whereas the CPS is primarily a labor force survey.
4. Other SIPP Estimates of the Uninsured
As one might expect, as the reference period for SIPP estimates of the uninsured lengthens, the percent uninsured throughout decreases while the percent uninsured in at least one month increases. Estimates of uninsured children in 1993 versus the 32-month period from early 1991 through mid-1993 illustrate this point:
Thus, for a given reference period, the percentage of children uninsured throughout is considerably less than the percentage uninsured in at least one month. This simply suggests there is substantial churning among uninsured children. From the examples above, 6.5 percent were uninsured throughout 1993 versus 15.5 percent uninsured at least one month.(19) The evidence of churning is even greater as the reference period increases: 3.2 percent were uninsured throughout the 32-month period versus 29.0 percent for at least one month. In short, although a substantial number of children are uninsured at a point in time (about 14 percent according to the CPS) the SIPP data tell us that the problem of uninsured children is even more widespread -- over a two-and-a-half year period almost one-third of all children will be uninsured at some point (Swartz 1994).(20)
D. OTHER ESTIMATES OF THE UNINSURED
The CPS and the SIPP are the most commonly used surveys to measure the health insurance status of individuals, primarily because of their large sample sizes, rich economic and demographic data, and repetition on a regular basis. Nevertheless, other surveys, which are generally smaller than the CPS and the SIPP, have been conducted that measure the health insurance status of individuals. One of the principal values of these other surveys is that they help to validate results from the CPS and the SIPP. Below, we present the estimates of the uninsured using four other data sources: (1) the National Health Interview Survey, (2) the Medical Expenditure Panel Survey, (3) the Community Tracking Study, and (4) the Kaiser/Commonwealth Survey of Americans. A summary of these estimates is presented in Table II.6.
1. National Health Interview Survey
The NHIS is the principal source of information on the health of the civilian noninstitutionalized population of the United States. The NHIS, conducted by the National Center for Health Statistics, is an annual cross-sectional survey of approximately 43,000 households and 106,000 persons. The survey is conducted on a rolling basis throughout the year so that one-twelfth of the annual sample is interviewed each month. The main objective of the NHIS is to monitor the health of the United States population through the collection and analysis of data on a broad range of health topics. The health insurance questions on the NHIS define uninsured as lacking health coverage in the previous month. The health insurance portion of the NHIS questionnaire is presented in Appendix C.
According to the NHIS, there was a monthly average of 11.5 million uninsured children age 0 to 17 in 1994 (NHIS 1996). This estimate is 17 percent higher than the CPS estimates, which is expected if we view the CPS as an annual estimate, or at least one covering a longer period of time than "last month."
2. Medical Expenditure Panel Survey
Beauregard et al. (1997) estimated the number of uninsured in the U.S. using the 1996 MEPS.(21) The MEPS is co-sponsored by the Agency for Health Care Policy and Research (AHCPR) and the National Center for Health Statistics. The sample of 9,400 households is a subsample of the households responding to the 1995 NHIS and is representative of the civilian noninstitutionalized population of the U.S. The survey was designed to yield comprehensive data that estimate the level and distribution of health care use and expenditures, monitor the dynamics of the health care delivery and insurance systems, and assess health care policy implications. MEPS is the third in a series of national probability surveys conducted by AHCPR on the financing and utilization of medical care in the United States. The National Medical Care Expenditure Survey (NMCES, also known as NMES-1) was conducted in 1977, and the National Medical Expenditure Survey (NMES-2) in 1987.
The MEPS collects data from a nationally representative sample of households through a rotating panel design. In this design, data are collected through a pre-contact interview followed by a series of five rounds of in-person interviews over a two year period of time. As a rotating panel survey, this series of data collection rounds is begun again each subsequent year on a new sample of households drawn from the NHIS sampling frame to provide overlapping panels of survey data, which when combined with other ongoing panels will provide continuous estimates of health care expenditures at both the person and household level.
Each MEPS interview collects information pertaining to a specific time period called the "reference period." The reference period for the first interview began January 1, 1996 and ended on the date of each responding unit's first round interview, conducted from March through June 1996. The health insurance section of the MEPS collects information about private and public health insurance programs. It identifies the household members covered by health insurance and various details about their plans. For employer sponsored coverage, a link is created to job characteristics collected in the employment section of the questionnaire. For individuals who are uninsured at the beginning of the year, information is collected on the length of time they have been uninsured. Additional questions clarify whether each person identified by each policy was covered throughout the reference period. Information for public insurance is collected on Medicare, Medicaid, Medicaid waiver programs, military sponsored plans, and other government programs. A questionnaire section on managed care determines whether household members that are either publicly or privately insured are covered under a managed care plan; additional questions ask about the characteristics of their managed care plans. The entire MEPS health insurance questionnaire is too large to include in this document. Instead, portions of the health insurance questions pertaining to Medicaid and the uninsured are presented in Appendix D.
Beauregard et al. used MEPS to develop a national estimate of the uninsured population based on sample persons who were uninsured continuously from January 1, 1996 to their first-round interview date 3 to 6 months later.(22) By this measure they found that 19 percent of nonelderly adults age 0 to 64 (44.5 million persons) and 15 percent of children age 0 to 17 (11 million children) were uninsured. Although these estimates appear higher than those of the CPS (9.8 million uninsured children) and other data sources, Beauregard et al. concluded that once time-period and definitional
issues are considered, their estimates are consistent with the findings of the CPS.(23) In reaching this conclusion, though, they assumed the CPS measured the uninsured throughout the previous year rather than at a point in time. If, instead, the CPS is viewed as a point-in-time estimate of the uninsured, then the MEPS and CPS findings are not consistent, since the MEPS estimate of those uninsured throughout a 3 to 6 month period should be considerably less than a point-in-time estimate. Additional research comparing MEPS and CPS estimates of the uninsured is warranted before firm conclusions can be drawn.
3. Community Tracking Study
Reschovsky et al. (1997) estimated the number of uninsured children age 0 to 18 using the CTS Household Survey. The CTS, sponsored by the Robert Wood Johnson foundation and conducted by the Center for Studying Health System Change, consisted of telephone interviews for 33,000 families, 11,600 of which had children. Information was gathered on all adults and one randomly chosen child in each household. Altogether, the survey has information on about 60,000 individuals. The data are weighted to be representative of the United States and are adjusted for nonresponse. Interviews took place, primarily via telephone, between July 1996 and July 1997. Like the MEPS, the CTS health insurance questionnaire is too large to include in this document; therefore, only the portions pertaining to Medicaid and the uninsured are presented in Appendix E.
Reschovsky et al. estimated that at any point in time from late 1996 to early 1997, there were approximately 8.8 million uninsured children, or about 12 percent of all children age 0 to 18. This is substantially lower than the estimate of 10.5 million uninsured children in 1995 produced by Fronstin and others using the March 1996 CPS. Reschovsky et al. pointed out that the difference between the two numbers most likely reflects methodological differences in how the two surveys asked about health insurance coverage. Reschovsky et al. asserted that the CTS estimate is lower in part because of methodological innovations in how insurance coverage is measured. With the CTS, persons who reported none of the various types of coverage when asked about each one individually, were then asked directly whether they were, in fact, uninsured. Some respondents at that point did report coverage. The CPS, in contrast, never directly asks respondents whether they are uninsured. Reschovsky et al. acknowledged, though, that the debate over whether the CPS is a point-in-time or period-of-time estimate confounds comparisons between the CTS and the CPS. If the CPS is a period-of-time estimate, then the CTS estimate, which is clearly a point-in-time estimate, would be expected to be higher rather than lower than the CPS estimate.
Reschovsky et al. did not adjust their estimate of uninsured children for possible underreporting of Medicaid in the CTS. Medicaid underreporting in the CTS appears to be even more substantial than in the CPS. Reschovsky et al. found that 9.8 million children age 0 to 17 were enrolled in Medicaid in the CTS versus 16.5 million in the CPS. Although the underreporting of Medicaid is quite high in the CTS, it is difficult to determine exactly the extent to which Medicaid may be underreported because the survey did not ask about Medicaid coverage in households where everyone reported private coverage. Therefore, the CTS missed Medicaid enrollees who were also covered by private insurance.(24) In any case, CTS estimates of the uninsured may be inaccurate because Medicaid enrollment appears to be underreported.
4. Kaiser/Commonwealth Survey of Americans
Davis et al. (1995) estimated the number of uninsured adults age 18 to 64 using the 1993 Kaiser/Commonwealth Survey of Americans. The survey consisted of telephone interviews with a nationally representative sample of 2,000 adults in August 1993. Davis et al. found that one-third of all adults, or 53 million adults, lacked health insurance at some point during the 2-year period from 1991 to 1993. They also found that at the time of the survey in August 1993, 18 percent of all adults were uninsured, which is very close to EBRI's estimate, based on the CPS, that 19 percent of adults age 18 to 64 in 1993 were uninsured (Fronstin 1995). The survey had a response rate of only 53 percent (compared with CPS and SIPP response rates in excess of 90 percent) raising concern about potential response bias. The possible effect of Medicaid underreporting on these findings is unknown because the percentage of respondents with Medicaid was not reported.
E. STATE-LEVEL ESTIMATES
Several researchers have combined CPS surveys to increase the sample sizes enough to produce state-level estimates of the uninsured. Below, we give an overview of two of these studies, one by The Urban Institute and one by Families USA.
1. The Urban Institute
Winterbottom et al. (1995) combined data from the 1991, 1992, and 1993 March CPS surveys to obtain state-level estimates of the health insurance status of individuals. Because CPS households are interviewed for two consecutive years and Winterbottom et al. only wanted to include each household once, they included all the observations from the 1993 CPS plus approximately half of the observations from the 1991 and 1992 surveys. Thus, combining three years of CPS data doubles the sample size, which reduces the sampling variance.(25) Winterbottom et al. then used The Urban Institute's TRIM2 model to adjust for underreporting of Medicaid.
Winterbottom et al. found that the rate of uninsured among children age 0 to 17 varied by state and region. For example, in the West South Central region -- the region with the highest rate of uninsurance -- 18.5 percent of children were uninsured.(26) In contrast, in the East North Central region -- the region with the lowest rate of uninsurance -- 6.8 percent of children were uninsured.(27) Winterbottom et al. pointed out that uninsurance rates vary by region and state for a number of reasons, including the rate of employer-sponsored insurance coverage and the rate of Medicaid coverage. Winterbottom et al. used the following example of the uninsurance rates of all persons age 0 to 64 to illustrate their point:
"The Middle Atlantic region has the lowest rate of employer coverage among its poverty population -- only 11.5 percent have employer-sponsored coverage -- significantly lower than the 15.8 percent coverage in the Mountain states. However, because the Middle Atlantic region has a high rate of Medicaid enrollment in the poverty population -- 53 percent of the poor get their primary coverage through the program -- its uninsured rate of 25.1 percent is not the highest. The Mountain States, with greater employer coverage among the poor, have a higher uninsured rate (32.6 percent) than the Middle Atlantic region because Medicaid covers fewer of the poor in the Mountain States region (40 percent)."
2. Families USA
Families USA (Families USA 1997) used 1995 and 1996 March CPS data in combination with imputation equations developed from the 1991 SIPP panel to estimate the number of children age 0 to 17 who were without health insurance in one or more months over the 2-year period from 1995 through 1996.(28) They estimated that 23.1 million children, or 33 percent of all children, were without health insurance in at least one month of the two-year period from 1995 to 1996. Families USA noted that the proportion of children with gaps in health insurance varied significantly from state to state due to differences in state economies and residents' income, the prevalence of jobs that offer employer-based coverage, the scope of public insurance programs (especially Medicaid), and the existence of other state health reforms. They found the highest proportions of uninsured children in southern and southwestern states. This supports the finding of Winterbottom et al. that the three regions with the highest proportion of uninsured children are (1) the West South Central, (2) the South Atlantic, and (3) the East South Central. According to Families USA, the following ten states had the highest percentage of children who experienced gaps in their health insurance during the period 1995 through 1996: Texas (46 percent); New Mexico (43 percent); Louisiana (43 percent); Arkansas (42 percent); Mississippi (41 percent); District of Columbia (39 percent); Alabama (38 percent); Arizona (38 percent); Nevada (37 percent); and California (37 percent). Families USA did not report confidence limits for these estimates, however, and readers are cautioned that the estimates for smaller states are not nearly as precise as those for larger states.
1. Because of these revisions and a change in the sample framework for the survey in 1995, it is difficult to compare estimates done before and after that year. Researchers believe that these revisions, coupled with the change in the sample framework for the survey in 1995, may have increased the number of persons reporting that they were insured (Swartz 1997). As a result, estimates before the 1995 CPS are not fully comparable to more recent estimates. However, at least one researcher has made adjustments to the CPS data in order to make more valid comparisons of health insurance coverage before and after the 1995 revisions (Fronstin, 1997b).
2. Including the elderly increases this estimate by only 300,000 individuals, since nearly all elderly are covered by Medicare. If the elderly are included, then 15.4 percent of the total population was without health insurance in 1995.
3. As cited in Monheit (1994).
4. Of course, the MEPS could have similar reporting problems to the CPS. However, the MEPS health insurance questions are much more detailed than the CPS questions, and interviewers are trained specifically on asking health related questions. The MEPS study is discussed in more detail later in this chapter.
5. Personal correspondence with Linda Bilheimer of CBO and Kathy Swartz of the Harvard School of Public Health, September 15, 1997.
6. One reason suggested by researchers for why people may not realize they are covered by Medicaid is that they are enrolled in a managed care program and, therefore, report that they are covered by the managed care company. If, indeed, this is occurring, then the problem of Medicaid underreporting could get worse as more states adopt Medicaid managed care programs.
7. For example, if most persons are enrolled for only 10 of 12 months, then the number of persons ever enrolled in the year should be adjusted downward by almost 17 percent to be comparable to a point-in-time estimate. With additional HCFA(now known as CMS) data, it is possible to calculate the average monthly number of persons enrolled in Medicaid.
8. HCFA(now known as CMS) also reports the number of Medicaid "recipients." Recipients, though, are defined by HCFA(now known as CMS) as the subset of enrollees, or eligibles, that utilized services during the year
9. Some researchers (for example, see Thorpe 1997a and 1997b) cite the number of children enrolled in Medicaid in 1995 according to the CPS as 13.8 million rather than 16.5 million. These researchers are reporting the number of children covered only by Medicaid during the previous year, thus excluding children that were covered by both Medicaid and private insurance during that period.
10. Nationally, enrollees exceeded recipients by 14 percent (HCFA(now known as CMS) 2082 tables for 1995).
11. They further add that analyses of people in poverty, people receiving welfare (AFDC), and people experiencing unemployment have been consistent in finding that most people who experience any of these situations, do so for short periods of time (see, for example, Bane and Ellwood 1986; O'Neill, Bassi, and Wolf 1987; Akerlof and Main 1980).
12. The 1992 panel was extended about one year, to 40 months.
13. One exception to this rule is that persons who die are given weights. Also, an important implication of this weighting design is that almost all infants born during a calendar year will have a zero-weight for that calendar because they are not part of the population on January 1. As a result, infants will be underrepresented in the SIPP data, which is of particular concern because infants have been a key target group for Medicaid expansions over the last decade.
14. Sometimes only a count or a percent is presented in the tables, but not both, because that is all a researcher reported. We do not attempt to calculate implied percents or counts because the denominator over which they are calculated is not always reported and not always obvious.
15. Bennefield did not cite the denominator for his calculation of the SIPP estimate of all persons who were uninsured. Based on other SIPP literature, the universe of all persons represents about 250 million persons. This would suggest that there were about 37 to 38 million uninsured at a point in time, an often cited figure.
16. Interview of Chuck Nelson and Bob Bennefield of the Census Bureau, conducted by Dave Baugh and Roger Buchanan of HCFA(now known as CMS) (July 23, 1997).
17. The comparable estimates for all persons were 7.7 percent (Bennefield, 1996c) and 4 percent (Bennefield 1995), respectively.
18. The comparable estimates for all persons were 21.2 percent (Bennefield, 1996b) and 26.5 percent (Bennefield 1995), respectively. That the differences between the 1-year and the 32-month estimates for adults was less than that for children suggests that there was less churning of the uninsured for adults.
19. Point-estimates of the uninsured using the SIPP fell somewhere between the uninsured throughout and the uninsured in at least one month estimates. In 1993, 13.5 percent of children were uninsured at any given time (Bilheimer 1997).
20. Swartz (1994) provides a useful overview of the dynamic of people without health insurance, along with references to earlier works on this topic.
21. A similar analysis of the MEPS with the same findings can be found in Vistnes and Monheit (1997).
22. Full-year 1996 MEPS estimates of the uninsured were not available as of the writing of this paper, but are planned once all interviews pertaining to 1996 are completed.
23. One of the definitional differences they cite is that the CPS assumes all AFDC recipients and most SSI recipients are enrolled in Medicaid, whereas MEPS usually does not. In addition, CPS counts children of adults covered by Medicaid as insured, whereas for these preliminary estimates, MEPS does not (unless their families reported them as covered). Finally, unlike MEPS, CPS counts as uninsured military veterans whose source of coverage is the Department of Veterans Affairs.
24. Missing Medicaid coverage for this group -- that is, those covered by private insurance and Medicaid -- would not affect the estimates of the uninsured because this group is reported as receiving private insurance.
25. The two samples are not independent, in that they tend to be pulled from the same neighborhoods; therefore, the doubled sample size yields something less than a proportionate reduction in variance.
26. The West South Central region includes the following states: Arkansas, Louisiana, Oklahoma, and Texas.
27. The East North Central region includes Illinois, Indiana, Michigan, Ohio, and Wisconsin.
28. The imputation equations predict which children will be uninsured in one or more months over the 2-year period on the basis of their demographic and economic characteristics. Researchers generally do not use the SIPP alone for state-level estimates because not all states in the SIPP are uniquely identified and because SIPP's relatively small sample sizes make resulting estimates imprecise. Even the CPS, with its larger sample sizes, does not support precise estimates in most of the smaller states.
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