This report uses data from the Survey of Income Program Participation (SIPP) to investigate dynamic aspects of the lack of health insurance, eligibility for Medicaid, and Medicaid participation among children in 1993 and 1994. After describing our data source we present findings on the duration of spells of uninsurance based on an analysis of new spells as well as spells active at a point in time. We explain why these alternative approaches to measuring the duration of uninsurance yield such different distributions of spell length. We also present estimates of the amount of time that uninsured children are eligible for Medicaid. From there we turn to an examination of the patterns of health insurance coverage preceding and following completed spells of uninsurance, and we compare spells of different lengths. We do this for spells of Medicaid-eligible uninsurance as well. Next we examine the frequency of transitions in coverage, beginning with changes in coverage between one year and the next and then turning our attention to monthly transitions in uninsurance and Medicaid enrollment, culminating in the presentation of estimates of cumulative monthly exit rates from uninsurance, Medicaid-eligible uninsurance, non-Medicaid-eligible uninsurance, and Medicaid enrollment. In the closing sections we discuss churning versus turnover as phenomena in the dynamics of uninsurance and Medicaid enrollment and then summarize our principal findings.
The findings presented herein are based on an analysis of longitudinal data from the 1992 panel of the SIPP. Starting with an initial sample of about 20,000 households representing the resident, noninstitutionalized population of the United States, except for those living in military barracks, the Census Bureau reinterviewed respondents every four months over a period of three calendar years. Respondents were asked a lengthy set of questions about their labor force participation, sources and amounts of income, family and household composition, and participation in government programs in each of the preceding four months. The interviews were staggered, with one quarter of the sample, constituting a “rotation group,” being interviewed each month. The purpose of this design was, in part, to minimize the impact of recall error and other reporting problems on the quality of the data compiled for calendar months. The estimates for a given calendar month are based on roughly equal proportions of the respondents describing circumstances one month ago, two months ago, three months ago, and four months ago.
Several features of the SIPP make these data especially appealing for the analysis of dynamic behavior in children’s health insurance coverage. The SIPP provides a detailed measure of health insurance coverage for every month of the two to three year duration of a panel. Measures of the duration of new spells of particular types of coverage or lack of coverage can be constructed by aggregating the reports from successive interviews, so that no matter how long the measured duration of a particular spell, no part of a reported spell relies on respondent recall beyond four months. In addition to providing measures of health insurance coverage, SIPP also provides very detailed measures of demographic and economic characteristics--again on a monthly basis. This affords us the opportunity to construct contemporaneous measures of circumstances that may affect eligibility for and enrollment in particular types of coverage. For example, we can construct a reasonably good simulation of Medicaid eligibility on a monthly basis and compare these monthly estimates to reports of Medicaid participation and insurance coverage--or the lack thereof--on a monthly basis as well. Arguably, there are no better data for investigating the dynamics of children’s health insurance coverage in the context of changing circumstances, including Medicaid eligibility.
Despite these strengths, however, the SIPP does possess some notable limitations that will become evident as we proceed through our findings. These include some well-documented but not well understood problems with the quality of retrospective monthly reports of program participation and health insurance coverage.
B. Duration of Uninsurance
The length of time that children spend without health insurance coverage is exceedingly important to policymakers. Brief spells of uninsurance carry very different policy implications than long spells. While transitional spells of even one month in duration carry risks to the temporarily uninsured, the policy responses that they invite are clearly different than those demanded to address chronic lack of insurance. The advent of the Children’s Health Insurance Program (CHIP) gives heightened importance to the duration of uninsurance as a policy variable. Federal law allows states considerable freedom in determining how much of the uninsured population to cover and how to define eligibility. A number of states are specifying minimum periods of uninsurance before a child can qualify for the new coverage.
How long do spells of uninsurance last? Here we present findings with respect to the duration of spells without insurance. We contrast two different ways of identifying spells: new spells that began within a particular 12-month period and active spells that were in progress at the end of that period. In addition to looking at spells of uninsurance, we examine spells in which the uninsured were eligible for Medicaid and, theoretically, could have availed themselves of such coverage.
C. Coverage Before and After Spells of Uninsurance
Other than children who are uninsured at birth, children who begin spells of uninsurance do so by losing previous coverage. What is the source of this coverage? Does it mirror the coverage of all insured children, or do the uninsured come disproportionately from former Medicaid enrollees? Similarly, when children regain coverage do they resemble the rest of the insured population with respect to the sources of this coverage or do they rely on a different mix of sources? And do children tend to return to the same type of coverage that they had prior to their spell of insurance, or do they often end up with another source of coverage? We address these questions by comparing the source of coverage before and after completed spells of uninsurance. We also examine how these answers differ by the duration of spells of uninsurance. After addressing these question with respect to spells of uninsurance, we examine spells of Medicaid-eligible uninsurance to determine what precedes and follows these spells. Here, however, a spell need not be preceded by coverage; instead a child may enter a spell of Medicaid-eligible uninsurance from the state of having been uninsured but not eligible for Medicaid, and may leave a spell of Medicaid-eligible uninsurance by losing Medicaid eligibility without regaining any form of coverage.
In the previous section we examined transitions into and out of uninsurance but restricted our attention to completed spells of uninsurance and, even more narrowly, completed spells of Medicaid- eligible uninsurance.. In this section we address the issue of transitions more broadly, looking first at changes in health insurance coverage at roughly one- and two-year intervals, then month-to-month transitions and, finally, cumulative monthly exits from uninsurance and Medicaid enrollment.
E. Churning Versus Turnover
The results presented in the preceding section indicate that about 600,000 children, on average, enrolled in Medicaid each month of FY93 and FY94 while nearly 800,000 became uninsured. Comparable numbers of children left Medicaid or became insured, so that the net change in the Medicaid child caseload or the population of uninsured children was small. Movements of children out of and into Medicaid or uninsurance include both “churning”--that is, exits entries by the same children over a relatively brief interval--and “turnover,” or exits and entries by different children.
Whether we classify a particular transition into Medicaid or uninsurance as an example of churning or not may depend on how we define the reference period for determining prior Medicaid enrollment or uninsurance. There’s no question that a child’s becoming uninsured after being covered for only six months should be included within the concept of churning.11 But what about a child who becomes uninsured after 13 months of coverage--or 24 months? Whatever we take churning to mean conceptually, moreover, measuring churning with available data may be quite another matter.
With data from the SIPP one could evaluate each transition into Medicaid or uninsurance within a period and determine whether and how long a child may have last been enrolled in Medicaid or uninsured. For transitions occurring in calendar year 1993, for example, one could look back as far as 12 months for children making transitions into Medicaid or uninsurance in January 1993 and as far back as 23 months for children making transitions in December 1993. For transitions occurring in calendar year 1994, one could look back 24 months for children making transitions in January 1994 and up to 35 months for children making transitions later in the year. Maintaining a consistent operational definition of churning would require that we look back no farther for children making transitions late in the period than we are able to do for children making transitions early in the period. This would imply that for transitions occurring in 1993 we look back at most 12 months and for transitions occurring in 1994 we look back at most 24 months.
Here we take a somewhat different approach to measuring the relative amount of churning and turnover in the transitions that we observe into Medicaid enrollment and uninsurance. We do so in order to pull together the findings that we presented earlier and in Technical Appendix A. From the data presented in Tables 9 and 11, we can count the number of transitions of children into Medicaid and uninsurance over a 23 month period, from November 1992 through September 1994. We also know the number of children enrolled in Medicaid or uninsured at the beginning of the period, October 1992 (or any month along the way). Finally, from data presented elsewhere, we know how many children under 19 were ever enrolled in Medicaid and how many were every uninsured in each of FY93 and FY94 and over the full two-year period. Subtracting enrollment or uninsurance at the beginning of a period from the number of children who were ever enrolled or ever uninsured during the period gives us a measure of aggregate turnover. Specifically, it tells us how many additional children entered Medicaid or uninsurance over the period, which we can express as a percentage of the initial enrollment. Subtracting the aggregate turnover from the total number of transitions into Medicaid or uninsurance over the period gives us a measure of excess transitions, which represent churning. In effect, then, we are counting each transition as an instance of either turnover or churning on the basis of whether the individual making the transition was in that state at the beginning of the period. This is not a time-based definition as we discussed above, but it provides a measure that is not only very intuitive but indicative of how much change occurred in the Medicaid or uninsured population over the period.
To obtain the population uninsured at the beginning of a period requires a small calculation.12 Children uninsured in the first month of a period include children who were uninsured before the period began and children for whom this is their first full month of uninsurance.13 Children ever uninsured in the period include those with one or more months of uninsurance. To count how many children became uninsured during the year we must compare the number ever uninsured during the year to those uninsured at the beginning of the year. If we equate all children who were uninsured in the first month--that is, the point-in-time estimate for that month--with the number uninsured at the beginning of the year, then our estimate of children who became uninsured during the year does not include those who became uninsured in the first month. To count children who became uninsured in the first month as well as the remaining 12, we need to redefine the population at the beginning of the year as children uninsured in the first month minus those who began spells of uninsurance in that month.14
Our estimates of the components of change in the population of uninsured children are presented in Table 16. For FY93 we start with about 9.5 million uninsured children in October 1992. From this we subtract the estimated 551,000 children who became uninsured in that month to obtain the number of children who were uninsured at the beginning of the year: 8.9 million.15 Altogether 16.1 million children were ever uninsured during FY93. Subtracting the initial population from this number yields our estimate of the number of children who became uninsured in FY93: approximately 7.2 million. This estimate of the turnover in the uninsured population represents 80 percent of the number who were uninsured at the start of the period and 44 percent of the number who were ever uninsured during the period. We obtain somewhat higher estimates of turnover in FY94, with the children who were added to the uninsured population in that year representing 90 percent of the number uninsured at the beginning of the year and 47 percent of those who were ever uninsured during the year. For the two-year period FY93 and FY94 we find that 12.1 million children became uninsured over this time or 136 percent of the number who were uninsured at the beginning of FY93 and 58 percent of the number who were ever uninsured during the two years. That the 12.1 million new uninsured is not 15 million (the sum of the FY93 and FY94 additions) implies that about 3 million of the 7.6 million children who were added to the uninsured after the beginning of FY94 were uninsured at some point during FY93. These children will figure into our estimate of churning over the two-year period.
Nearly 9.3 million new spells of uninsurance were started in FY93 and nearly 9.5 million in FY94, for a two-year total of 18.7 million. In FY93 the number of new spells exceed by 2.1 million the number of children who were added to the uninsured in that year. These excess spells were started by children with one or more other spells during the year--that is, spells that were already in progress at the beginning of the year or spells that began during the year. These excess spells represent 23 percent of all the new spells that started during the year. Similarly, for FY94 we estimate that 1.9 million of the 9.5 million spells of uninsurance that started during the year were associated with children who had one or more other spells of uninsurance during the year. For the two-year period, the number of excess spells is more than just the sum of the numbers of such spells in FY93 and FY94. The total of 6.6 million includes spells started by children with no other spells in FY94 but with spells in FY93 that ended before the start of FY94. Measured in this way, churning accounts for 35 percent of all the new spells that were started in FY93 and FY94. By implication, if we were to define churning in FY94 in terms of spells started by children who had other spells of uninsurance in either FY94 or FY93, rather than just FY94, the number of such spells would equal the difference between the 6.6 million two-year total and the 2.1 million spells started in FY93 by children who had one or more other spells of uninsurance during FY93. This difference of about 4.5 million represents 47 percent of the new spells started in FY94. In other words, 47 percent of the new spells of uninsurance started in FY94 represented second, third, or even higher order spells by children who had been uninsured once previously in either FY93 or FY94. If we were to look for earlier spells as far back as two years for all children who started new spells in FY94, rather than just those who started new spells at the end of FY94, we would obtain an even higher estimate of churning. On the other hand, if we were to limit our definition of churning to include only those new spells started within a year of the last spell, then the estimate of churning in FY94 would lie somewhere between 20 percent and 47 percent.16
Table 17 presents analogous estimates of the components of change in the population of children enrolled in Medicaid in FY93 and FY94. While the number of children enrolled in Medicaid at a point in time is about one-third higher than the number of children who are uninsured, both the number of new spells started during a year and the number of new enrollees that these spells represent are smaller than the corresponding numbers for the uninsured. In FY93, new enrollees represented 48 percent of the number enrolled at the beginning of the year and 32 percent of the number of children ever enrolled during the year. For FY94 these figures were 40 percent and 29 percent, respectively, while the new enrollees over the two-year period were 75 percent of the initial enrollees and 43 percent of the children ever enrolled during the period. Clearly, then, Medicaid enrollees are a more stable population than uninsured children, with fewer new children joining and those who do enroll staying longer. Except for FY93, however, the rate of churning appears comparable for Medicaid and uninsurance. While the new spells started by children with earlier spells of Medicaid enrollment during the year were only 14 percent of all new spells in FY93, they were 23 percent of all new spells in FY94--higher than the corresponding figure for the uninsured. Likewise, new spells started over the two-year period FY93 and FY94 by children with earlier spells of enrollment during that same period represented 33 percent of all new spells compared to 35 percent for uninsurance. As with uninsurance, if we were to define churning in FY94 in terms of spells started by children who had other spells of Medicaid enrollment in either FY93 or FY94, the number of such spells would equal the difference between the 4.4 million two-year total and the 980,000 spells started in FY93 by children who had one or more other spells of Medicaid enrollment during FY93. This difference of about 3.4 million represents 51 percent of the new spells started in FY94. That is, 51 percent of the new spells of Medicaid enrollment started in FY94 represented second, third, or even higher order spells by children who had been enrolled in Medicaid once previously in either FY93 or FY94.