MA plans offer additional benefits over TM including vision coverage, hearing coverage, and some additional drug coverage; however, the primary additional benefits provided by MA over TM are lower expected OOPC for an equivalent benefit.
Not only can such policy make nonincident beneficiaries better off, if by transitioning into MA they are able to take advantage of a generous benefit at lower OOPC (such as that offered in Miami-Dade in 2007 and 2008), but it also has the potential to improve the value of federal spending on MA.
(5.) This diversity in plan benefits and expected out-of-pocket costs (OOPC) across plans and between MA and Traditional Medicare (TM) is similar in the latter part of the study period (2006-2008).
(12.) Average annual OOPC in any MA plan in one year is the average monthly expected OOPC in all MA plans across all ages that year, multiplied by twelve.
All MA plans HMO PPO Average monthly premium 88.05 88.01 102.56 Average monthly OOPC 182.49 181.27 329.55 No.
As policy makers and actuaries have defined insurance subsidies and cost-sharing limits without empirical evidence regarding what level of OOPC is burdensome for families, the development of a tool that can measure such burden will be important for assessing existing policies and guiding future policy decisions.
Financial burden was modeled as a joint function of family income and OOPC. Because some families (14.7 percent of the families in this sample) did not report their annual family income, the NHIS provides five imputed datasets with continuous measures of family income.
Because the NHIS provides only a categorical measure of OOPC (i.e., all out-of-pocket spending on all medical and dental care, not including health insurance premiums, over-the-counter drugs, or reimbursed costs) in the past 12 months, we used data from the MEPS to predict continuous OOPC for NHIS families within their endorsed cost category.
All income and OOPC values were adjusted for inflation to 2010 U.S.
Family income and OOPC from the first survey year were used to construct the novel categorical measures of financial burden (based on the results from the NHIS sample).
To develop and validate the novel measure, we conducted our analysis in three steps: (1) derived the marginal effect of financial burden using multivariable logistic regression predicting unmet need with bivariate splines for income and OOPC, adjusting for covariates; (2) performed recursive partitioning on the marginal effect of financial burden to identify cut-points in income and OOPC; and (3) assessed the performance of the novel measure for predicting unmet need, compared to the standard 10 percent cut-point.
Using a bivariate tensor product spline, which modeled a joint function of OOPC and income, allowed the relationship between OOPC, income, and unmet need to vary separately by the value of OOPC and income, similar to real-world conditions (e.g., spending 5 percent of family income has very different implications for a family making $40,000/year than for a family making $80,000/year).