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The American Journal of Managed Care August 2017
Health Insurance and Racial Disparities in Pulmonary Hypertension Outcomes
Kishan S. Parikh, MD; Kathryn A. Stackhouse, MD; Stephen A. Hart, MD; Thomas M. Bashore, MD; and Richard A. Krasuski, MD
Evaluation of a Hospital-in-Home Program Implemented Among Veterans
Shubing Cai, PhD; Patricia A. Laurel, MD; Rajesh Makineni, MS; Mary Lou Marks, RN; Bruce Kinosian, MD; Ciaran S. Phibbs, PhD; and Orna Intrator, PhD
The Effect of Implementing a Care Coordination Program on Team Dynamics and the Patient Experience
Paul Di Capua, MD, MBA, MSHPM; Robin Clarke, MD, MSHS; Chi-Hong Tseng, PhD; Holly Wilhalme, MS; Renee Sednew, MPH; Kathryn M. McDonald, MM, PhD; Samuel A. Skootsky, MD; and Neil Wenger, MD, MPH
What Do Pharmaceuticals Really Cost in the Long Run?
Darius Lakdawalla, PhD; Joanna P. MacEwan, PhD; Robert Dubois, MD, PhD; Kimberly Westrich, MA; Mikel Berdud, PhD; and Adrian Towse, MA, MPhil
The Hospital Tech Laboratory: Quality Innovation in a New Era of Value-Conscious Care
Courtland K. Keteyian, MD, MBA, MPH; Brahmajee K. Nallamothu, MD, MPH; and Andrew M. Ryan, PhD
Association Between Length of Stay and Readmission for COPD
Seppo T. Rinne, MD, PhD; Meredith C. Graves, PhD; Lori A. Bastian, MD; Peter K. Lindenauer, MD; Edwin S. Wong, PhD; Paul L. Hebert, PhD; and Chuan-Fen Liu, PhD
Risk Stratification for Return Emergency Department Visits Among High-Risk Patients
Katherine E.M. Miller, MSPH; Wei Duan-Porter, MD, PhD; Karen M. Stechuchak, MS; Elizabeth Mahanna, MPH; Cynthia J. Coffman, PhD; Morris Weinberger, PhD; Courtney Harold Van Houtven, PhD; Eugene Z. Odd
Cost-Effectiveness Analysis of Vagal Nerve Blocking for Morbid Obesity
Jeffrey C. Yu, AB; Bruce Wolfe, MD; Robert I. Griffiths, ScD, MS; Raul Rosenthal, MD; Daniel Cohen, MA; and Iris Lin, PhD
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Impact of Formulary Restrictions on Medication Use and Costs
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

Impact of Formulary Restrictions on Medication Use and Costs

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
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.
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.

RESULTS

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.

The estimated effects of formulary restrictions on overall adherence were minimal. Restricting access to brand name pioglitazone and single-source brand name DPP-4 inhibitors was linked to a PDC that was 0.4 percentage points higher (P = .3508), but the association was not statistically significant. Beneficiaries facing formulary restrictions of brand name atorvastatin and single-source brand name statins, on average, had a PDC that was 0.9 percentage points lower (P = .1197) compared with those that were not subject to such restrictions. Restricting the use of single-source brand name ARBs was related to a PDC that was 1.3 percentage points lower (P = .0211).

Stringent state laws for generic substitution (mandating generic substitution and only allowing brand name drugs by provider request) were associated with a GDR that was 3.3 percentage points higher for OHAs (P = .0120) and 3.0 percentage points higher for RAS antagonists (P = .0091). Providing free mail order prescriptions for 1 additional generic statin was associated with a GDR that was 1.5 percentage points higher (P = .0360).

DISCUSSION

We found that placing formulary restrictions on brand name drugs generally shifted utilization away from brand name agents toward inexpensive generics. The effects were consistent across the 3 drug classes, but the magnitude of impact was smaller for OHAs than for statins or RAS antagonists. LIS recipients who faced restrictions in accessing brand name drugs had 34.9% (38.80 vs 25.25 days) fewer annual days of supply for sitagliptin than their counterparts who could freely access these drugs, 74.3% (34.41 vs 9.10 days, respectively) fewer days of supply for rosuvastatin, and 95.7% (28.06 vs 1.22 days, respectively) fewer days of supply for valsartan (Tables 2-5). Correspondingly, the difference in GDR between the restricted and unrestricted groups was smaller for OHAs (0.88 vs 0.83, respectively) than for statins (0.95 vs 0.77) and RAS antagonists (0.95 vs 0.80). 

This varying magnitude of impact might be due to differences in the availability of therapeutically equivalent agents. There were multiple generic statins and generic ARBs available in 2012, whereas all DPP-4 inhibitors were single-source brand name drugs. Clinical guidelines on diabetes management recommend adding a DPP-4 inhibitor, sulfonylurea, or thiazolidinedione (TZD) as a second oral agent for patients who cannot achieve their glycemic target with metformin monotherapy.15 We observed that beneficiaries who either did or did not face restrictions on DPP-4 inhibitors had comparable utilization of sulfonylureas and TZDs, indicating lack of substitution. Although the findings from the regression analysis suggested that restricting access to DPP-4 inhibitors has minimal impact on overall OHA adherence, further study is needed to investigate concurrent adherence among patients treated with multiple OHAs and the clinical impact of formulary restrictions.

This study addressed the intended and unintended consequences of formulary restrictions, an understudied but important research topic given the near-ubiquity of these tools in modern formulary management.2 The lack of literature is partially due to complexity in deciphering formulary designs, especially if a large number of drug products are involved. Most prior studies are limited to providing descriptive statistics regarding shares of restricted drugs or evaluating formulary policy changes for particular drugs.2,16,17 Our analysis of the benchmark for PDPs formularies contributed valuable insight in identifying meaningful formulary restrictions and understanding how they may influence medication utilization patterns. To the best of our knowledge, this is the first study that has systematically evaluated formulary restrictions and their impact on medication utilization and costs in the context of an entire drug class. It is a methodological advancement because utilization of a drug is not only influenced by its own ease of access, but also formulary availability of other agents in the same therapeutic class.

 
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