Medical Care Economic Risk Measuring Financial Vulnerability from Spending on Medical Care (2012) / Chapter Skim
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4 Measures of Medical Care Economic Risk and Recommended Approach
4 Measures of Medical Care Economic Risk and Recommended Approach
Pages 67-88
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From page 67... ...
As stated in Chapter 1, the sponsor's charge to the panel included conducting a public workshop to critically examine the state of the science in the development and implementation of a measure of medical care economic risk as a companion to the new Supplemental Poverty Measure (SPM)
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From page 68... ...
Through health insurance, families lower their financial risk and have a more predictable expense in the form of an insurance premium that, in theory, can be budgeted for as a share of income and resources. For the insured, MCER thus has two components -- premiums and out-of-pocket expenses for medical care not covered by insurance.
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From page 69... ...
What happens to people who become sick in those families? We propose to quantify the concept of risk for a family as the estimated probability that next year's medical spending is greater than the difference between the family's SPM poverty threshold and its resources as defined for the SPM, with two differences -- first, actual out-of-pocket medical care expenses would not be subtracted from resources (in contrast, the retrospective SPM poverty measure does subtract such expenses from resources)
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From page 70... ...
. 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.
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From page 71... ...
. The CPS ASEC has very limited information on health status and does not collect information on financial assets, a portion of which we recommend be included in resources for measuring MCER.
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From page 72... ...
The advantage of this method is that it needs only 1 year of data, which has two benefits -- timeliness and allowing the use of nonpanel data like the CPS ASEC.4 A disadvantage is that because nonpanel data sources systematically exclude recent deaths and those who have entered institutions in the immediate past time period -- two groups known to have high health e xpenditures -- it will be necessary to use other data sources and the relevant literature to provide an estimate of the missing information for those two transitions and their impact on out-of-pocket medical care spending. Although decedents and institutionalized people are not in poverty, the transitions to death and to institutions will often impose major drains on their families' resources and could push other members of the household into poverty.
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From page 73... ...
An Initial Retrospective Measure of MCER In the short term, with the data now being collected, the CPS ASEC could be used to report the burden of out-of-pocket medical care spending retrospectively, roughly 10 months after the end of the calendar year for which income and spending are reported. Furthermore, with additional assumptions, the retrospective measure of burden could serve as a proxy for the prospective MCER: for example, if x percent of families and individuals were moved into poverty this year, then the same x percent is the best estimate of those who will be in poverty next year, assuming no other major policy initiatives or differences in the business cycle.6 5 one develops risk adjusters for health conditions based on 1 year of health experience If and uses that experience to explain expenditures for that year, one would arrive at a biased assessment of the variance because the covariates are not independent of the out-of-pocket spending (see Manning, Newhouse, and Ware, 1982)
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From page 74... ...
has and that also has an adequate response rate and spans the age range necessary for this task. See the work of Goldman and colleagues on the Future Elderly Model, a demographic and economic simulation model designed to predict the future costs and health status of the elderly, at http://roybal.healthpolicy.usc.edu/projects/fem.html.
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From page 75... ...
What could be its added value? With its richer data on health conditions, distribution of medical care spending by service type, and 2-year panel, MEPS offers the opportunity to learn much more about the interplay of health status, health insurance, and out-of-pocket medical care spending with respect to family finances as well as to more accurately assess how risk varies with health.
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From page 76... ...
This situation dictates an analytic agenda before highly specific recommendations can be made on a prospective measure of MCER. Health services researchers and health policy analysts have substantial experience with mean expenditures adjusting for observable individual and family characteristics at the individual level.
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From page 77... ...
But for the distribution of out-of-pocket medical care spending or its variance, it is more complicated than keeping track of means, variance, and covariances among the family members. Because there is much to learn about the drivers of out-of-pocket medical care spending for families of varying size, composition in terms of ages, health status, insurance coverage, and resources, we recommend a series of analyses based on MEPS to test out various alternatives and to answer such questions as what factors (e.g., chronic conditions)
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From page 78... ...
The results of these analyses can be used to inform the move from a purely retrospective approach that uses medical care economic burden as a proxy for risk to an approach that estimates risk directly. These studies should include an analysis of both the cell-based approach to estimating the expected amount of spending and the use of regression methods to understand the expected risks; both are important to the development of appropriate alternatives to the short-term strategy that we have offered.
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From page 79... ...
. Recommendation 4-1: Given what limited work has been done in the field on issues in measuring medical care economic risk (MCER)
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From page 80... ...
SPECIFIC ISSUES IN ESTIMATING MCER We discuss below in more detail three specific issues in estimating medical care economic risk, which will need to be addressed in the analyses we recommend: family versus individual approaches to estimating MCER for a family unit, allowing for insurance plan choice and determining the predictors of choice, issues of selecting variables for cell determination or as covariates, and data and estimation issues. Family Versus Individual Approaches Our outcome of interest is the impact of MCER on family income, particularly for those families with relatively low incomes, who may be pushed below the SPM level by relatively high out-of-pocket medical care spending.
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From page 81... ...
Moreover, past research has typically shown that the major drivers of mean expenditures are individual characteristics -- age, gender, diagnoses, severity, and health status. Meier and Wolfe (in Part III of this volume)
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From page 82... ...
It can be formed on the basis of family composition, health status, completed education as a proxy for future income, and the likelihood of having coverage from the beginning of the year or baseline (using coverage information available at the end of the year may be a necessary stopgap approach in the short run)
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From page 83... ...
Thus, any risk classification system needs to be able to handle coarse risk cells for individuals and to find a method for combining data on individuals with varying risks internally within families. This may require the health equivalent of the family composition algorithm used in the calculations of the SPM thresholds.
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From page 84... ...
If it were possible to obtain the necessary data on insurance plan details, it would be desirable to model the effects of changes in those details -- for example, when premiums rise and to the extent that families have to pay for part or all of their premiums out-of-pocket, their medical care economic burden increases; if there is a move to a high deductible plan, the risk from out-of-pocket expenditures may increase. It would also be desirable to model the effects of changes in copays, coinsurance, and stop-losses (out-of-pocket maxima)
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From page 85... ...
. For private insurance, if one has details on the actual premiums and coverage provisions, one may standardize by adjusting total spending and out-of-pocket spending from actual to a standard, using the details of insurance to let the coinsurance rate at the time of spending affect the quantity of care obtained and thus out-of-pocket spending.
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From page 86... ...
Percentage in Figure 4-1 Poverty 100% 1.0 Income as Multiple of Poverty Threshold FIGURE 4-2 The probability of out-of-pocket medical care spending exceeding the difference between family income and the SPM threshold after a shift in out-ofpocket premiums due to incomplete subsidy for health insurance and reduced outof-pocket spending, as with the transition of the uninsured to coverage under ACA. SOURCE: Developed by the panel to illustrate the relationship between income and medical care economic risk described in the text.
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From page 87... ...
in households slightly above the poverty line have their incomes reduced to less than the SPM by premiums post-ACA, the dashed curved line is initially above the black solid curved line. However, the lines soon cross, as less healthy people who are newly insured experience out-of-pocket premiums plus spending for care that is less than their prior out-of-pocket spending, and thus their household incomes are not reduced below the SPM threshold.
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