Our principal findings with respect to the importance of individual trigger events in predicting changes in coverage are obtained from a logistic regression analysis that we present in the next section. The regression results are particularly useful in describing the relative strengths of individual events as predictors of changes in coverage, but
We do not regard a parent's change in coverage as a trigger event for the child's change in coverage. Rather, we think of changes in the coverage of parent and child as often having a common set of trigger events. When examined in light of changes in children's coverage, changes--or the lack thereof--in the parents' health insurance coverage can b
We also considered the possibility that the frequent reversals of transitions between one SIPP interview and the next could reflect error in the reporting of health insurance coverage. Specifically, if coverage during a reference period were misreported and then corrected in the next, this would give the appearance of an initial transition followe
Table 3 reports how often each of the 23 million transitions was followed by a second transition within the next four months--that is, by the next SIPP interview--and the frequency with which the initial transitions were reversed by these second transitions. Altogether, 40 percent of the 23 million transitions were followed by a second transition
Sample counts and population estimates of the transitions that are the focus of this study are reported in Table 2A along with the percentage distribution of the total transitions. The transitions are grouped by the status of origin. In Table 2B the transitions are grouped by the destination status. For the 12-month period from July 1993 through J
Table 1 reports the average number of children who reported each major source of coverage between July 1993 and June 1994, including the number who were uninsured and the number who were reported as insured but with missing information on the actual source of coverage. The number of transitions out of each category of coverage (except the one indi
To perform the analyses reported herein, we constructed a dataset consisting of 11-month snapshots providing measures of health insurance coverage and a variety of parental and family characteristics. Each snapshot consisted of data from a focal month, m , plus the next four months and the preceding six months. 6 Month m was any of the 12 mon
The data source for this analysis is the 1992 panel of the Survey of Income and Program Participation (SIPP), which interviewed a nationally representative sample of household residents every four months over a span of three years and collected monthly data on health insurance coverage, family composition, family and personal income by detailed so
Data from repeated cross-section surveys such as the Current Population Survey (CPS) or the National Health Interview Survey (NHIS) show little year-to-year change in the proportion of children who are without health insurance or the proportion who are covered by specific types of insurance, even when there are clear upward or downward trends. The
While we did not address this macro level question explicitly, trigger events provide a mechanism that is capable of accounting for the volume of transitions--and for changes that may develop over time. The events that we examined occurred with varying frequency in the different coverage groups, and when particular events occurred the children who
Regression analysis of the effects of particular events on the likelihood that children who have a given type of insurance coverage (or none at all) will experience a transition to a specific other type of coverage indicates the following.
Events representing changes in the parents' employment status, jobs, or hours worked; family income; family headship or size; and participation in AFDC were shown to have occurred with greater frequency among children who experienced transitions in health insurance coverage than among children who did not. Depending on the type of transition, betw
Parents mirrored their children's changes in coverage more than half the time. When they did not, the children split about equally between those whose parents kept the coverage that the children exited and those whose parents did not share the same coverage that their children exited. For the most part these patterns are explained by the way in wh
The nearly equal numbers of transitions into and out of each coverage status raise questions about the source of this near-equilibrium. Do children return to their original source of coverage? Indeed, many do. Children who changed their health insurance coverage often changed it again in the next four months--the interval between SIPP interviews.
We examined changes among three sources of coverage--employer-sponsored insurance (ESI), Medicaid, and other, primarily private insurance--plus a fourth status: uninsured. Table 1 summarizes our findings. It shows how children were distributed by major source of coverage and how many changes in coverage, or transitions, were recorded among these m
Changes in children's health insurance coverage occur with far greater frequency than the modest year-to-year changes in the proportion uninsured or the proportion with different types of coverage would suggest. We present evidence that in the one-year period from July 1993 through June 1994 there were more than 23 million instances of children ch