Impact of Formulary Restrictions on Medication Use and Costs | Page 2

Placing formulary restrictions on brand name drugs shifts use toward generics, lowers the cost per prescription fill, and has minimal impact on overall adherence for antidiabetes, antihyperlipidemia, and antihypertension medications among low-income subsidy recipients in Medicare Part D plans.
Published Online: August 26, 2017
Xian Shen, PhD; Bruce C. Stuart, PhD; Christopher A. Powers, PharmD; Sarah E. Tom, PhD, MPH; Laurence S. Magder, PhD; and Eleanor M. Perfetto, PhD, MS
Notably, we observed perfect correlations in the degree of restriction among drugs in each of the 3 classes. Specifically, every plan that partially restricted generic simvastatin also partially restricted ezetimibe-simvastatin. Plans either fully restricted brand name pioglitazone, sitagliptin, and sitagliptin-metformin across the board or did not restrict any of the 3 drugs. Plans that fully restricted valsartan also fully restricted valsartan-hydrochlorothiazide. We constructed composite measures that grouped commonly occurring formulary restrictions and estimated the effects of each group on the study outcomes. Table 1 provides a list of drugs selected for analysis, the degrees of restriction observed, and groups of formulary restrictions formed (eAppendix Table 1 displays formulary restrictions on individual drugs [eAppendices available at]). As indicated in the table, 3 OHAs (sitagliptin, sitagliptin-metformin, saxagliptin), 2 statins (ezetimibe-simvastatin, rosuvastatin), and 3 RAS antagonists (olmesartan, valsartan all, valsartan-hydrochlorothiazide) were single-source drugs for which generics were unavailable in 2012.

Key covariates included a variable for count of generics available without charge via mail order, indicators for PDP regions, and a categorical variable representing state laws for generic substitution. Plan cost-sharing rules are generally not applicable to full LIS recipients as they pay flat co-pays for prescription drugs (at most $2.60 for generics and $6.50 for brand name drugs in 2012).8 However, in 2012, several plans provided free mail order prescriptions for commonly used generics in the 3 drug classes of interest. The covariate—the count of generics available for free via mail order—was developed to account for the effect of this practice at the plan level. Last, several PDP regions covered multiple states, some of which could have had more forceful state laws for generic substitution than others. To represent the strictness of the state laws, we constructed a categorical variable consisting of 3 values: 1) state law allows generic substitution, 2) state law mandates generic substitution but allows brand by patient request, and 3) state law mandates generic substitution but allows brand by provider request.

We also evaluated the impact of CMS assignment methods by comparing enrollee characteristics across the benchmark PDPs within each of the 3 largest PDP regions: New York, Texas, and California. We expected comparable enrollee characteristics between plans, except for assignment year and age because some plans had operated as benchmark plans for more years and, thus, would have received more random assignees compared with plans that achieved benchmark status in recent years. These older benchmark plans would also have retained an older pool of enrollees. Beneficiary age and assignment year were also included as covariates in the analysis.


Statistical Analysis

In univariate analysis, we performed type 3 tests to examine the overall effect of the composite groups of formulary restrictions on each study outcome. We estimated 3 sets of random intercept regression models in which dependent variables were GDR, mean cost per prescription fill, and PDC. In each regression model, we included a random effect to account for unexplained variability between plans. Formulary restrictions were modeled as fixed effects. Count of generics available without charge via mail order, state law for generic substitution, PDP region, assignment year, and beneficiary age were included as covariates in the models and treated as fixed effects. We used SAS Version 9.3 (SAS Institute; Cary, North Carolina) for all statistical analyses.


A total of 28,082 beneficiaries were eligible for the OHA cohort; 53,864 for the statin cohort; and 57,289 for the RAS antagonist cohort (see eAppendix Figure for details about cohort selection). Approximately 30% of all study subjects resided in New York, Texas, and California in 2012 (eAppendix Table 2). As expected, enrollee characteristics were largely comparable across benchmark PDPs within each of these 3 regions except for assignment year and age (eAppendix Tables 3-11).   

From our assessment of the benchmark PDP formulary designs in 2012, we found consistent patterns in formulary restrictions for OHAs, statins, and RAS antagonists. For most of the drugs analyzed, plans either fully restricted their use (all strengths restricted) or applied no restrictions at all (all strengths available). Formulary restrictions were mostly placed on brand name drugs, whereas almost all generic drugs were readily available on formulary. In addition, the benchmark PDPs appeared to have 3 formulary approaches for handling brand name drugs (Tables 2-4). From most restrictive to most generous, these directives were: 1) placing restrictions on all brand name drugs, 2) selectively covering brand name drugs without restrictions, and 3) covering all single-source brand name drugs and commonly used multi-source brand name drugs without restrictions.

The top panels in Tables 2-4 present descriptive statistics for annual days of supply for every drug that accounted for at least 1% of overall utilization in the LIS population, beginning with OHAs (Table 2), statins (Table 3), and RAS antagonists (Table 4). These statistics are displayed by the groups of formulary restrictions described in Table 1. Placing formulary restrictions on a drug was associated with lower utilization of that medication, and the impact was more pronounced among statins and RAS antagonists than among OHAs. 

Utilization of generic drugs was much higher among beneficiaries enrolled in plans that restricted access to brand name drugs. Compared with those enrolled in plans that placed no formulary restrictions on the 4 statins under study (Table 3), beneficiaries who faced restrictions in obtaining rosuvastatin (single-source brand name), atorvastatin (multi-source brand name), and ezetimibe-simvastatin (single-source brand name) not only had considerable fewer annual days of supply for the 3 drugs—rosuvastatin (9.10 for enrollees in plans with restrictions vs 35.41 for patients in plans with no restrictions), brand name atorvastatin (1.61 vs 20.52, respectively), and ezetimibe-simvastatin (1.13 vs 7.99)—but they also had higher use of generic atorvastatin (58.99 vs 45.86), generic lovastatin (21.27 vs 16.66), generic pravastatin (48.72 vs 39.21), and generic simvastatin (136.30 vs 120.77). Similarly, beneficiaries who were subject to restrictions in accessing single-source brand name angiotensin II receptor blockers (ARBs), including olmesartan, valsartan, and valsartan-hydrochlorothiazide, had more days of supply for generic ARBs versus patients in plans not requiring plan approval (losartan: 50.18 vs 27.91, respectively; losartan-hydrochlorothiazide: 14.89 vs 8.57, respectively) (Table 4).

The bottom panels of Tables 2-4 present mean values for each of the study outcomes. The mean GDRs for the 3 OHA restriction groups varied from 0.83 for plans with no restrictions to 0.84 for plans restricting only saxagliptin (single-source brand name) and 0.88 for plans restricting brand name pioglitazone and single-source brand name dipeptidyl peptidase-4 (DPP-4) inhibitors (ie, saxagliptin, sitagliptin, and sitagliptin-metformin). The mean GDR for statins was also lowest for plans with no formulary restrictions (0.77), climbing to 0.95 for plans placing restrictions on brand name atorvastatin and single-source brand name statins (ie, rosuvastatin and ezetimibe-simvastatin). For RAS antagonists, plans with no restrictions again exhibited the lowest mean GDR (0.80), with the highest mean GDR (0.95) observed among plans restricting single-source brand name ARBs (eg, olmesartan, valsartan, and valsartan-hydrochlorothiazide). Mean costs per prescription fill were inversely related to GDR. The range for OHAs was $54.54 in plans with the most restrictions to $71.70 in plans with no formulary restrictions for the 4 OHAs under study. The range for statins was $40.49 to $73.04, respectively, and for RAS antagonists, $20.78 to $45.74, respectively. The differences in PDCs across plans by formulary restriction were small; in no instance was the difference greater than 0.04.  

These relationships persisted after covariate adjustment for assignment year, beneficiary age, count of generics available for free via mail order, PDP region, and state law for generic substitution (Table 5). Regarding OHAs, restricting the use of brand name pioglitazone and single-source brand name DPP-4 inhibitors was associated with a GDR that was 3.0 percentage points higher (P <.0001) and a cost per prescription fill that was $10.80 lower (P = .0001) for OHAs. Restricting access to brand name atorvastatin and single-source brand name statins was linked to a GDR that was 14.9 percentage points higher (P <.0001) and a cost per prescription fill that was $29.60 lower (P <.0001) for statins. Restricting single-source brand name statins was associated with a cost per prescription fill that was $25.60 lower (P = .0158), and restricting brand name atorvastatin and single-source brand name ezetimibe-simvastatin was related to a reduction of $12.40 (P = .0399). Placing restrictions on single-source brand name ARBs was related to a GDR that was 15.0 percentage points higher (P <.0001) and a cost per prescription fill that was $27.20 lower (P <.0001) for RAS antagonists. Restricting only olmesartan was linked to a GDR that was 3.8 percentage points higher (P = .0434) for RAS antagonists.

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