Using a simulation model developed from previous analyses (Feldman, Parente, Abraham, et al., 2005; Parente, Feldman and Abraham, 2007), we applied the Synthetic State MEPS (SS-MEPS) described above and in Appendix 1 to develop a set of national estimates. The simulation model is capable of generating estimates of national health plan take-up for both the individual and employer-sponsored insurance (ESI) markets.
One of the distinguishing attributes of the simulation model is the presence of consumer driven health plans (CDHPs). Specifically, there are two types of CDHPs utilized in the model: a low-option Health Reimbursement Arrangement (HRA) and a high-option HRA. The low-option HRA is very similar in deductible, coinsurance and premium structure to a Health Savings Account (HSA) plan. This enabled us to model both HRA and HSA choices in the simulation as well as high, moderate and low-option Preferred Provider Organizations (PPOs), and a Health Maintenance Organization (HMO).
In the simulation, consumers in the individual market have five choices: high, moderate and low-option PPO, HSA, and the choice to be uninsured. Consumers with employer-sponsored coverage are given up to eight choices including HMO, three PPO options, an HRA, an HSA where the employee opts out of employer sponsored coverage, an HSA where the employer picks up most of the cost of the HSA/high deductible insurance policy, and finally a choice to turn down coverage for any reason (e.g. already had coverage from spouse).
Chronic illness is modeled at the contract level in the simulations. That is, either the person choosing insurance, or someone covered by their insurance contract, has a chronic illness. This assumption was made because the data used to estimate the health plan choice model could only be attributed to contract holders, not the person receiving care under a contract. As a result, the chronic illness metric reflects a household’s illness burden, more than that of one individual, unless the person is buying a single-coverage contract.
The simulation model adjusts premiums for the tax treatment of health insurance offered by employers in the ESI market. Specifically, premiums are adjusted to take into consideration the federal marginal tax rate as well as the social security tax burden. The capability to adjust for state tax effects is also possible, but not considered in this model in order to identify the pure effects of differences in insurance regulations by state.
We use premium estimates for each of the plan choices based on our earlier work (Feldman, Parente, Abraham, et al., 2005). These premium estimates are derived from a combination of ehealthinsurance.com and Kaiser/Commonwealth estimates of premium prices. These premium estimates are adjusted to 2008 dollars.
We develop state-specific premium inflators/deflators from the AHIP individual market single and family coverage report. Individual market premiums were experience rated for age and gender (with the exception of community rated states). For this analysis, we define the small group market as one where an employer has less than 250 employees. At this level, employers generally do not self-insure. Premiums for employers with less than 250 employees were adjusted by state-specific regulatory effects. Finally, HSA premiums include a $1,000/$2,000 investment in accounts depending upon whether the person was choosing a single or family insurance product, respectively.
The simulation is based only on choices made by adults aged 19-64 who are not students, not covered by public insurance, and not eligible for coverage under someone else’s ESI policy. As a result, our baseline uninsured and turned down population represents 32.3 million people (excluding military, students, persons under age 18 or 65 and older, and those without an ESI offer who could be covered by a spouse). However, we present results for our selected sample as well as a national approximation that would yield 47 million people uninsured.