The overall MCAHPS response rate for 2007 was 49 percent, with 30 percent of all responses by mail and 3 percent in Spanish.1
Among respondents with nonmissing gender, 58 percent were female (). Race/ethnicity was reported as non-Hispanic white, black, and Hispanic by 74.5, 7.0, and 6.3 percent of respondents, respectively, with MA respondents (12 percent) more often Hispanic than FFS respondents (6 percent), p
<.0001. About 9 percent of respondents were 85 and older, 20 percent did not graduate high school, 17 percent were eligible for LIS (14 percent in MA versus 18 percent in FFS, p
<.0001), and 32 percent were in poor or fair self-rated health (27 percent in MA versus 33 percent in FFS, p
<.0001). More than three in four beneficiaries (78 percent) belonged to at least one designated subgroup, with 37 percent belonging to only one subgroup, 22 percent belonging to exactly two, and 7 percent belonging to four or more (data not shown). About half of beneficiaries (54 percent) had one or more characteristics traditionally associated with vulnerability (the six characteristics other than female), with 30 percent belonging to only one, 15 percent to exactly two, and 9 percent to three or more (data not shown). No correlations among subgroup characteristics exceeded 0.26 (data not shown).
Characteristics of Medicare Advantage (MA) and FFS Beneficiaries
Overall unadjusted mean scores of the 11 CAHPS measures we analyzed () fell between 80 and 90 on a 0–100 scale, with the exception of getting information about prescription drug coverage (78.2) and paperwork (71.1). Means near the upper end of the response scale are typical of Medicare CAHPS and other surveys of patient experience (see, e.g., Landon et al. 2004
). Unadjusted scores were significantly higher for MA than FFS for seven measures and significantly lower for one measure (getting needed care). MA scores were highest compared with FFS on the paperwork item (difference of 9.4 points on a 0–100 scale), followed by rate prescription drug plan (2.8-point advantage) and getting information from one's prescription drug plan (2.6-point advantage). Because ratings of MA plan and of Medicare are not exactly parallel, one must use caution in interpreting overall differences between these variables. When we look at case-mix adjusted2
CAHPS score coefficients for MA versus FFS (last column of ), we find a more mixed pattern where MA scores are significantly higher than FFS on five measures (all three PDP measures, paperwork, and the problematic MA plan versus Medicare measure) and significantly lower than FFS on three measures, two physician measures, and getting needed care.
Unadjusted Mean CAHPS Scores and Case-Mix Adjusted Differences, Medicare Advantage (MA), and Fee-For-Service (FFS) Beneficiaries
For each of the 11 CAHPS measures, displays disparities within MA associated with each characteristic (adjusted mean differences between the subgroup and its counterpart, with a negative value indicating fewer positive experiences for the vulnerable subgroup), disparities within FFS, and the (MA–FFS) differences in disparities (an adjusted difference of differences corresponding to the interaction term of MA and the characteristic in question). Disparities within MA are calculated as the sum of the coefficient for the vulnerable characteristic and the coefficient for its interaction with MA. Disparities within FFS are simply the model coefficient for the vulnerable characteristic.
Adjusted Disparities in Medicare Advantage (MA) and Fee-For-Service (FFS), by Vulnerability Characteristic†
We briefly report the absolute differences in measures between beneficiaries with or without each of the seven characteristics within insurance type (MA or FFS), with the caveat that they may in part reflect differences in response tendency as noted above. Whereas Hispanic and black race/ethnicity were associated with less positive absolute evaluations than white race/ethnicity, and fair/poor health with less positive absolute evaluations than good to excellent health in more than half of the comparisons, other subgroups of interest tended to report more positive absolute experiences than their counterparts. Less educated, lower income, older, and female beneficiaries tended to report more positive absolute experiences than their counterparts.
The interactions of these subgroup identifiers with MA when significant were predominantly negative. There were significant (p<.05) negative interactions with MA in 27 of 77 instances. Significant negative interactions with MA were found for 8 of 11 measures for poor/fair health, with LIS eligibility, age 85 or older, and black race for 4 of 11 measures, and for female and no high school diploma for 3 of 11 measures. Among these six characteristics, there were only two instances of significant positive interactions. The exceptions to this pattern were Hispanic beneficiaries, where two positive and one negative interaction were observed; the two positive interactions involved Part D measures.
With respect to the eight Part C measures, significant (p<.05) negative interactions with MA were found in 18 of 56 instances (with one positive). Interactions with MA were negative for six of eight Part C measures for poor/fair health and for three of eight Part C measures for black and female. Physician-related items (doctor rating, specialist rating, and doctor communication) showed the fewest significant interactions (differences in disparities). Specifically, in only 2 of 21 instances did physician-related measures show statistically significant negative interactions, as opposed to 16 of 35 instances for other Part C measures measuring characteristics of care, plans, and paperwork.
With respect to the three Part D measures, there were nine negative and three positive interactions with MA (two of the latter involving Hispanic ethnicity). For the subgroup characteristics of older age, poorer health, lower education, and lower income, 8 of 12 interactions with MA were negative for Part D measures, with no positive interactions.
These interactions were estimated simultaneously, so that for Getting Care Quickly, for example, the disparity between a black beneficiary in fair or poor health and a non-Hispanic white beneficiary in good, very good, or excellent health is estimated to be 1.73+1.25=2.98 points less favorable to the former beneficiary in MA than in FFS, where the two beneficiaries would have more similar experiences with Getting Care Quickly.
The same models shown in also allowed us to estimate the absolute difference between MA and FFS within each subgroup of interest (results not shown). We compared MA and FFS within these seven subgroups for each of 10 measures, omitting Rate MA Plan/Medicare for these comparisons. The absolute scores for beneficiaries with each of the seven subgroup characteristics of interest were generally higher in MA than in FFS for Part D measures (p<.05 for 7 of 21 instances, no significant examples of FFS>MA) and paperwork (p<.05 for seven of seven instances), and lower in MA than FFS for most other measures (p<.05 for 17 instances where FFS>MA and five instances where MA>FFS of 42 total instances).
The propensity score weights used for the sensitivity analysis were successful in balancing all covariates at well below the commonly used 0.20 standard deviations threshold (Cochran 1968
). The sensitivity analysis replicated the analysis shown in using population average treatment effect propensity score weights, as shown in Appendix SA3
. The results are largely similar to those shown in , if somewhat smaller in magnitude on average. In particular, the tendency for larger disparities in MA for African Americans is no longer significant, while the tendency for larger disparities in MA for LIS deemed strengthens.