Variation and Trends in Medigap Premiums. Appendix C: Methodology

12/16/2011

Data for this study was provided by the National Association of Insurance Commissioners (NAIC). The data are based on reporting by insurers to state departments of insurance, and exclude data for companies that are regulated by the California Department of Managed Health Care (DMHC).

For regression analysis of the predictors of Medigap monthly premiums in 2008, we specify a model in which the premium in 2008 is regressed on state‐level Medicare spending per beneficiary in 2008, percent of the Medigap market at the state level accounted for by the top two Medigap insurers in 2008, state‐level percentage of beneficiaries with Medicare Advantage in 2008, variables to reflect state rating requirements, an individual market vs. group policy variaible, Medigap plan type variables, and the number of covered lives in 2008.

For regression analysis of the predictors of the annual increase in Medigap monthly premiums we included all plans that had data for each of the four years, 2007 ‐2010. We used a fixed effects method to analyze within plan premium increases over that time period. We specify a model in which current year’s monthly premium is regressed on the previous year’s premium, the previous year’s medical loss ratio, the state‐level percent change in Medicare Advantage enrollment in the previous year, the state‐level percent of Medicare beneficiaries with Medicare Advantage in the previous year, number of covered lives in the previous year, state rating requirement variables, an individual market vs. group policy variable, Medigap plan type variables, and year variables.

We used a logisitic regression model to examine predictors of plans having very large premium increases over the 2007‐2010 time period (being “outlier” plans). The model estimated the likelihood of being an outlier is predicted by the number of covered lives, the state‐level Medicare spending per beneficiary, the State‐level percent of Medicare beneficiaries with Medicare Advantage in the previous year, change in medical loss ratio, state rating requirement variables, an individual vs. group policy variable, Medigap plan type variables, a newer vs. older policy variable and variables reflecting the annual change in enrollment.

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