Data Limitations

The claims data present some limitations in the ability to measure the effect of specialty tier placement on utilization, switching, and expenditures. The primary limitation is the fact that the data only contain utilization, and do not have the full formulary information behind each plan. This, as described above, required a

reconstruction of the plan-level formularies using the observed utilization data, in order to estimate each plan’s out-of-pocket costs for beneficiaries enrolled in the plan. By being restricted solely to observed utilization, any effects of plan tier placement decisions on deterring beneficiary utilization will be reflected in the data itself. This means that, if the conceptual model holds and beneficiaries respond to higher cost sharing by reducing utilization, for some plans there may be no observed utilization. This means that potential users in plans with no utilization may not be included in the

regression analyses described in Chapters 6 and 7, due to a lack of ability to calculate the plan’s imposed cost sharing as a result of no utilization.

Given the complex nature of Part D, it is possible that other aspects of the benefit, other than the cost sharing, play a role in the utilization decision by beneficiaries as seen in the data. One such aspect of the benefit is the provision by Part D plans of coverage in the gap. The effect of such coverage, which can take the form of just generic, or generic and brand, or all formulary drugs, is to further reduce the beneficiary’s observed costs for his/her drugs. This in turn might induce additional utilization. However, a review of the association between gap coverage and out-of- pocket costs shows that more plans that do offer gap coverage are missing observed utilization. More specifically, 19.08% of plans in 2007 (19.28% in 2008) offered gap coverage and were not missing out-of-pocket costs, while 34.83% of plans in 2007 (26.95% in 2008) offered gap coverage and were missing costs. This suggests little association between offering gap coverage and additional utilization of specialty tier- eligible drugs.

Table 5.8 describes the extent to which lack of observed utilization is a problem in reconstructing plan-imposed out-of-pocket cost sharing. The table separates

beneficiaries with utilization and those without utilization, and details those with missing out-of-pocket costs. For beneficiaries who did not use a specialty tier-eligible drug in the MS/RA grouping, 11.4% in 2007 and 33.3% in 2008 had missing out-of-pocket costs. For those with cancer, 10.5% in 2007 and 37.0% in 2008 had missing out-of-pocket costs. If beneficiaries in plans with missing out-of-pocket costs are in fact responding to higher cost sharing by reducing (eliminating) utilization of these drugs, then the analyses presented in Chapters 6 and 7 would underestimate the effects of tier placement by not

including observations of beneficiaries with no utilization, who are enrolled in plans that have imposed higher cost sharing on their medications.

There are two main implications of this limitation: first, as stated above, that estimates of utilization, number of fills, switching, and expenditures, are underestimates due to a lack of observed out-of-pocket costs for a large proportion of those with no utilization; and second, that it is not possible to calculate an accurate estimate of the elasticity of demand for beneficiaries for specialty drugs in Part D, because of the extent to which the data are missing. However, these estimates do provide some initial

conclusions as to the effects of specialty tier placement on utilization, switching, and expenditures. Chapter 8, which concludes the dissertation, discusses some future extensions for this work that may be able to address the problem of missing data in the claims data.

Table 5.8: Beneficiaries with Missing Out-of-Pocket Costs at the Plan Level.24

Beneficiaries with Utilization Beneficiaries without Utilization Total Number With Missing

OOP Costs Number

With Missing OOP Costs 2007 MS / RA 14614 1160 80 13454 1531 Cancers 44718 1985 124 42733 4489 2008 MS / RA 15651 1014 290 14637 4881 Cancers 46883 654 182 46229 17117 24

Beneficiaries with utilization may have missing plan-level out-of-pocket costs due to the fact that only those costs in the initial phase of the Part D benefit were counted in averaging the out-of-pocket costs. Some drugs are so expensive that beneficiaries would cross from the deductible into the initial coverage phase with one prescription; or from the deductible to the coverage gap. These costs are not included in the estimate.

5.6 Conclusions

The empirical analyses examining the effect of tier placement on beneficiary demand for specialty drugs use claims data that required significant backwards engineering in order to generate the variables of interest. This chapter explained the rationale behind certain decisions made in order to calculate these variables, given the limitations inherent in the data. The primary limitation, that the data only provide

utilization and do not give a broader understanding of the benefit design at the plan level, required the calculation of alternative variables in order to proxy for specialty tier placement for drugs used to treat the six conditions of interest. The following chapters describe the empirical analyses and results associated with the different measures of beneficiary response to plan tier placement for specialty drugs.