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 source, and a variety of additional variables. SIPP is thus an excellent source with which to measure transitions in health insurance coverage and to identify potential trigger events.
The most recent SIPP panel was started in 1996 and ran through the end of 1999, but the first longitudinal data file from this panel, which will cover 1996 and 1997, is not scheduled for release until March 2001. The next most recent panels, which were started in 1992 and 1993, cover about three years each. 1 We selected the 1992 panel because we had worked with it previously and because comparisons with other data suggest that the 1993 panel overstates the number of families below poverty. We focus our analysis upon transitions occurring between July 1993 and June 1994 to give us a representative set of transitions occurring late in the life of the 1992 panel and to allow us to look forward several months past the last transitions (September 1994 is the final month for which all components of the health insurance measures are available for the full longitudinal sample). While these data are nearly six years old, they nevertheless provide a rich source of information on transitions in health insurance coverage and the events that may help to precipitate them. Undoubtedly, whatever these data can tell us about the events that trigger changes in health insurance coverage remains relevant as we enter the next decade.
A transition in health insurance coverage involves both an exit, from the first coverage or origin, and an entry, into the second coverage or destination. Each type of exit or entry may be associated with a different set of potential trigger events, which suggests that we examine different types of transitions separately. We elected to group the transitions by the coverage that precedes the transition--that is, the original coverage. We examined transitions among four distinct sources of coverage: employer-sponsored insurance (ESI), Medicaid, other insurance, and a lack of coverage. ESI includes all coverage obtained through a current or former employer, whether or not the employer pays any part of that coverage. 2 "Other insurance" may include both privately purchased insurance and public insurance other than Medicaid or Medicare, which respondents identify directly, but from the survey questions we know only that such coverage was obtained in some way other than through a current employer or union, former employer, or the CHAMPUS or CHAMPVA programs. 3 Children may also have coverage that is not described adequately enough to be assigned to one of the three general sources of coverage. This is particularly true of children whose coverage is provided by an adult who lives outside the household--a divorced parent in most cases. While most of this unknown coverage is ESI, we elected not to assign such coverage to ESI but to exclude it from our typology altogether. Thus, movements into or out of unknown coverage are not counted among the transitions that we examine. 4
While SIPP captures health insurance coverage on a monthly basis, the reporting of changes in health insurance coverage--as well as other types of transitions--is characterized by a substantial "seam bias." That is, reported transitions of many kinds fall disproportionately between rather than within the four-month reference periods for which the interviews collect data. If the timing of transitions were reported correctly, only one in four transitions would occur at the seams between reference periods. Instead, for the types of transitions in health insurance coverage that we examine in this report, between 66 and 99 percent were reported to have occurred at the seams (see Appendix Table A.1). 5 The seam bias for potential trigger events was weaker, with 34 to 76 percent of these changes being reported between rather than within reference periods. The seam bias affects the reported data in several ways that are relevant to our research. Both the temporal proximity and the sequencing of events may be misstated. Short spells are almost certainly underreported, and spell durations show a substantial heaping at multiples of four months. To use these data to investigate the impact of trigger events on transitions in health insurance coverage requires a number of accommodations, which we will discuss as we review our methodology and findings.