The measure of MCER that we propose in this chapter addresses both of the situations above: for middle-income families with a high cap on cost-sharing, family medical care out-of-pocket spending at the 90th percentile of the distribution of out-of-pocket expenditures could be enough to push them into poverty; and for families close to the SPM threshold, the 50th percentile of medical care out-of-pocket spending might be enough. From calculations based on suitable data on each family’s distance to the SPM threshold and the distribution of their expected out-of-pocket expenses for medical care, one can summarize in tables or graphs what fraction of families will be pushed into poverty by expenditures of a specific size or at each level of future income as a percentage of the SPM threshold.
Furthermore, one can ask whether a particular event or set of chronic and acute illnesses would move a family down to 150 percent of the poverty threshold or any other multiple of the threshold compared with the situation when its resources were not this low and its members were healthy. One can also distinguish the effect on available resources of out-of-pocket premiums from the effects of other medical care out-of-pocket spending beyond premiums.
THE IDEAL VERSUS THE FEASIBLE: DATA NEEDS, TIMELINESS, AND REFINING A MEASURE OF MCER
“Essentially, all models are wrong, but some are useful.”2
To understand the effects on available family income across the U.S. population of various kinds of financial exposure to medical care costs, one needs to calculate the probability for families with particular characteristics of having out-of-pocket premiums and spending on medical care services greater than their resources minus the SPM threshold (excluding the correction for out-of-pocket spending for medical care and adding a portion of liquid assets). Ideally, the calculation would reflect the actual terms of health insurance coverage; the age, gender, and health status of family members; and the composition of the family for a large number of families.
Practically speaking, the calculation must be constructed on the basis of information that is available from MEPS or the CPS ASEC (which is the basis for the SPM calculations). These surveys, however, do not include finely detailed information on plan coverage (which affects both out-of-pocket premiums and spending for medical care services). Moreover, the annual cross-sectional CPS ASEC does not document transitions in insurance status, which can occur for many reasons, including loss of a job and changes in health status, such as the acquisition of Medicaid by a low-income
2 Box and Draper (1987:424).