In this exercise, actuarial values are computed by taking health insurance plan parameters and applying them to the expenses and utilization of a standard population. The weighted average covered expenses and benefits paid by a specific plan for the entire population are then used to determine the richness of the plan. That is, actuarial value is equivalent to the “benefit rate”, which is defined as the ratio of benefits paid to underlying average covered expenses. In our model, multiple plans can be valued at the same time on the same underlying population. In addition, a behavioral response (also known as induction) can be computed for each plan relative to a starting plan that is designated as “average” coverage. Plans with coverage richer than average may cause increases in spending (an increase in demand, and in the underlying covered expenses) while plans with poorer than average coverage may result in a decrease in spending.
In our model, the starting population is taken from the AHRQ MEPS-HC and controlled to a starting per capita covered expense that is consistent with the National Health Accounts. As the plans we are looking at are employer sponsored health insurance plans, the population used here is those persons under age 65 with employer sponsored insurance (for other applications, other subpopulations can be used). In general, spending and utilization for four main services (hospital, physician, prescription drugs, and other health professionals) provides the basis for the covered expenses. For persons with private insurance, total spending here is the sum of private insurance plus out of pocket spending. Spending by other (government) channels is ignored. As noted above, the spending for this population has been controlled to be consistent with the CMS Office of the Actuary’s National Health Accounts, although the underlying spending can be controlled to any value as needed.5
5 The MEPS distribution of claims might produce somewhat different results than the claims distribution from insurers, in part because respondents with very high levels of expenditure are underrepresented in the MEPS data, although the differences are not likely to be large.