Table 2.
The Effect of the Coverage Gap on Medication Use Among All Aged Beneficiaries Who Reached the Coverage-gap Threshold But Did Not Reach the Catastrophic-coverage Threshold in 2007
| Type of Medications |
Study & Comparison Groups |
Unadjusted Data* |
Diff-in-Diff Coverage Gap Effects† |
% Change, Diff-in- Diff Effects/Pre-Gap Values‡ |
|||
|---|---|---|---|---|---|---|---|
| Pre- Gap |
Within- Gap |
Estimate | 95% CI | % | 95% CI | ||
|
Probability of Using a Medication | |||||||
| All medications |
No-coverage | 1.00 | 0.88 | −0.03 | (−0.04, −0.03) | −3.3 | (−3.6, −3.0) |
| Generic-only | 1.00 | 0.94 | −0.02 | (−0.02, −0.01) | −1.6 | (−1.9, −1.3) | |
| LIS | 1.00 | 0.94 | Ref | ||||
| Brand-name | No-coverage | 1.00 | 0.79 | −0.07 | (−0.07, −0.06) | −6.7 | (−7.0, −6.3) |
| Generic-only | 1.00 | 0.84 | −0.08 | (−0.09, −0.08) | −8.2 | (−8.6, −7.8) | |
| LIS | 1.00 | 0.90 | Ref | ||||
| Generics | No-coverage | 0.98 | 0.81 | −0.05 | (−0.05, −0.05) | −5.2 | (−5.5, −4.8) |
| Generic-only | 0.98 | 0.90 | −0.02 | (−0.03, −0.02) | −2.4 | (−2.8, −2.0) | |
| LIS | 0.99 | 0.91 | Ref | ||||
|
Mean Number of Monthly Prescriptions | |||||||
| All medications |
No-coverage | 5.30 | 3.61 | −0.85 | (−0.88, −0.82) | −16.0 | (−16.5, −15.5) |
| Generic-only | 6.14 | 4.65 | −0.66 | (−0.70, −0.63) | −10.8 | (−11.4, −10.3) | |
| LIS | 5.84 | 5.02 | Ref | ||||
| Brand-name | No-coverage | 2.71 | 1.51 | −0.64 | (−0.65, −0.62) | −23.5 | (−23.9, −23.0) |
| Generic-only | 2.87 | 1.66 | −0.61 | (−0.62, −0.59) | −21.1 | (−21.7, −20.5) | |
| LIS | 2.59 | 1.99 | Ref | ||||
| Generics | No-coverage | 2.57 | 2.09 | −0.21 | (−0.23, −0.19) | −8.2 | (−9.0, −7.4) |
| Generic-only | 3.23 | 2.96 | −0.06 | (−0.08, −0.03) | −1.8 | (−2.6, −1.0) | |
| LIS | 3.22 | 2.99 | Ref | ||||
|
Mean Monthly Pharmacy Spending | |||||||
| All medications |
No-coverage | 309 | 184 | −73.15 | (−74.65, −71.66) | −23.7 | (−24.2, −23.2) |
| Generic-only | 351 | 224 | −66.59 | (−68.48, −64.69) | −19.0 | (−19.5, −18.5) | |
| LIS | 331 | 274 | Ref | ||||
| Brand-name | No-coverage | 256 | 143 | −66.65 | (−68.01, −65.30) | −26.1 | (−26.6, −25.5) |
| Generic-only | 277 | 157 | −65.16 | (−66.88, −63.45) | −23.5 | (−24.1, −22.9) | |
| LIS | 262 | 209 | Ref | ||||
| Generics | No-coverage | 52 | 40 | −6.40 | (−6.92, −5.88) | −12.2 | (−13.2, −11.2) |
| Generic-only | 73 | 66 | −1.39 | (−2.11, −0.66) | −1.9 | (−2.9, −0.9) | |
| LIS | 68 | 64 | Ref | ||||
This is the overall population, a national sample of aged beneficiaries regardless which medical conditions they had. The sample sizes for no-coverage, generic-only, and LIS groups are 61040, 21219, and 57699, respectively.
These are average numbers in the pre-gap and within-gap periods, but they are unadjusted and unweighted raw data.
“ Diff-in-Diff Coverage Gap Effects” are adjusted estimates from the difference-in-difference model with the inverse of propensity score as a weight. The estimates measure changes in outcomes between within-gap and pre-gap periods in each study group, relative to the changes in outcomes in the comparison group (“Ref”).
“% Change” is calculated using “Diff-in-Diff Coverage Gap Effects” divided by pre-gap values.
Abbreviations: LIS = low-income-subsidies; this is the comparison group. Ref = reference group.