Currently Viewing:
The American Journal of Managed Care June 2018
Prevalence and Predictors of Hypoglycemia in South Korea
Sun-Young Park, PhD; Eun Jin Jang, PhD; Ju-Young Shin, PhD; Min-Young Lee, PhD; Donguk Kim, PhD; and Eui-Kyung Lee, PhD
Initial Results of a Lung Cancer Screening Demonstration Project: A Local Program Evaluation
Angela E. Fabbrini, MPH; Sarah E. Lillie, PhD, MPH; Melissa R. Partin, PhD; Steven S. Fu, MD, MSCE; Barbara A. Clothier, MS, MA; Ann K. Bangerter, BS; David B. Nelson, PhD; Elizabeth A. Doro, BS; Brian J. Bell, MD; and Kathryn L. Rice, MD
A Longitudinal Examination of the Asthma Medication Ratio in Children
Annie Lintzenich Andrews, MD, MSCR; Daniel Brinton, MHA, MAR; Kit N. Simpson, DrPH; and Annie N. Simpson, PhD
Physician Practice Variation Under Orthopedic Bundled Payment
Joshua M. Liao, MD, MSc; Ezekiel J. Emanuel, MD, PhD; Gary L. Whittington, BSBA; Dylan S. Small, PhD; Andrea B. Troxel, ScD; Jingsan Zhu, MS, MBA; Wenjun Zhong, PhD; and Amol S. Navathe, MD, PhD
Simply Delivered Meals: A Tale of Collaboration
Sarah L. Martin, PhD; Nancy Connelly, MBA; Cassandra Parsons, PharmD; and Katlyn Blackstone, MS, LSW
Currently Reading
Placement of Selected New FDA-Approved Drugs in Medicare Part D Formularies, 2009-2013
Bruce C. Stuart, PhD; Sarah E. Tom, PhD; Michelle Choi, PharmD; Abree Johnson, MS; Kai Sun, MS; Danya Qato, PhD; Engels N. Obi, PhD; Christopher Zacker, PhD; Yujin Park, PharmD; and Steve Arcona, PhD
Assessing Markers From Ambulatory Laboratory Tests for Predicting High-Risk Patients
Klaus W. Lemke, PhD; Kimberly A. Gudzune, MD, MPH; Hadi Kharrazi, MD, PhD, MHI; and Jonathan P. Weiner, DrPH
Satisfaction With Care After Reducing Opioids for Chronic Pain
Adam L. Sharp, MD, MS; Ernest Shen, PhD; Yi-Lin Wu, MS; Adeline Wong, MPH; Michael Menchine, MD, MS; Michael H. Kanter, MD; and Michael K. Gould, MD, MS
Cost Sharing for Antiepileptic Drugs: Medication Utilization and Health Plan Costs
Nina R. Joyce, PhD; Jesse Fishman, PharmD; Sarah Green, BA; David M. Labiner, MD; Imane Wild, PhD, MBA; and David C. Grabowski, PhD

Placement of Selected New FDA-Approved Drugs in Medicare Part D Formularies, 2009-2013

Bruce C. Stuart, PhD; Sarah E. Tom, PhD; Michelle Choi, PharmD; Abree Johnson, MS; Kai Sun, MS; Danya Qato, PhD; Engels N. Obi, PhD; Christopher Zacker, PhD; Yujin Park, PharmD; and Steve Arcona, PhD
There is significant heterogeneity in formulary placement and restrictions on new drug approvals in the Part D marketplace.
RESULTS

Table 1 presents characteristics of the 863 Part D plans included in the study sample. The plans were divided almost evenly between PDPs (427) and MAPDs (436). Together they represented 241 contracts among 102 different sponsors. The PDPs were just about evenly split between basic plans (215) and enhanced plans (212), but among MAPDs, enhanced plans predominated (389 vs 47). Benchmark plans were offered exclusively by PDPs. Plan quality measured by star ratings was substantially higher among MAPDs (a mean ranking of 3.81 stars vs 2.91 stars among PDPs).

Table 2 [part A and part B] provides descriptive information on all drugs of interest. Most of the products were NCEs (26), with CPs (5) and LEs (2) limited to antihyperglycemic agents and drugs used in treating COPD. Among NCEs, there was a wide mix of agents that were first in class (12), second in class (5), or third or later in class (16).

NDC codes were assigned within a median of 6 days of FDA approval across all drugs reviewed. NDC assignments for every anticoagulant, antiplatelet, disease-modifying agent for MS and RA, and antihyperglycemic agent occurred within 9 days of FDA approval. However, for most COPD drugs, antiepileptics, and antipsychotics, NDC approval dates were delayed by several months (10 months in the case of ezogabine [Potiga], an antiepileptic medication). From the NDC assignment date onward, there were further delays of between 2 months (golimumab [Simponi], lacosamide [Vimpat], and asenapine [Saphris]) and 9 months (rivaroxaban [Xarelto], ticagrelor [Brilinta], indacaterol [Arcapta Neohaler], and fluticasone/vilanterol [Breo Ellipta]) before first observed formulary placement. Both the mean and median times between NDC assignment and first formulary placement was 4.6 months. Within 6 months of first placement, 56.7% of the 33 drugs had been placed on the formularies of the 863 plans under review (47.5% if drugs in protected classes are excluded). Uptake ranged from 17.7% for linagliptin (Tradjenta) to 100% placement for the antiepileptics and 2 of the 4 antipsychotics. The adoption rate at 12 months post NDC assignment was 64.1% (57.2% if drugs in protected classes are excluded). For 3 drugs, our observation period (January 2006-December 2014) was too short to observe formulary coverage 12 months post first formulary placement.

The final 2 columns in Table 2 present summary statistics regarding new formulary placements. The application of ST and PA restrictions differed widely by therapeutic class. Across all classes, 10.8% of plans required ST upon formulary placement versus 29.5% for PA. ST was rarely applied to anticoagulants (1.1%), antiplatelets (0.5%), MS drugs (0.2%), RA drugs (0.1%), COPD drugs (2.4%), and antiepileptics (5.1%), but was required for between 19% and 35% of all antihyperglycemic drugs and antipsychotics. PA was required by 89% or more of plans for all MS and RA drugs. Overall, antiplatelet drugs were the least restricted.

Table 3 provides a breakdown of differences in formulary adoption rates between PDP and MAPD plans. Overall, MAPDs had higher adoption rates for 28 of the 33 drugs at 6 months (59.0% vs 52.3%) and 25 drugs at 12 months (65.5% vs 60.0%). For 3 drugs, MAPDs formulary placement rates were more than double those of PDPs at 12 months. Teriflunomide (Aubagio) was placed by 66.3% of MAPDs but only 31.6% of PDPs, liraglutide (Victoza) was placed by 44.0% of MAPDs and 20.0% of PDPs, and prednisone DR (Rayos) was placed by 31.6% of MAPDs versus 13.2% of PDPs. MAPDs had higher rates of adoption for expensive biologic agents used to treat MS and RA. Drugs with significantly higher placement rates among PDPs included prasugrel (Effient) (91.4% of PDPs at 1 year versus 78.4% of MAPDs), saxagliptin/metformin (Kombiglyze XR) (88.6% vs 76.9%), and linagliptin/metformin (Jentadueto) (84.8% vs 61.1%).

Table 4 summarizes results from the regression analysis. As hypothesized, enhanced benefit plans were significantly more likely to place new drugs on formulary (model 1) compared with basic benefit plans by 4 percentage points (P <.01). At the same time, enhanced benefit plans were 2% more likely to impose ST (<.05) and 5% more likely to impose PA (P <.01) restrictions (models 3 and 4, respectively). Benchmark plans were less likely to add newly approved drugs (–4%; P <.01), and when they did, they delayed adoption (model 2) by nearly a month (0.89 months; P <.01) compared with nonbenchmark plans. Plans with higher star ratings were also significantly more likely to place new drug products per additional star (4%; P <.01). After controlling for other plan characteristics, MAPDs were more likely to impose PA (4%; <.01) compared with PDPs. However, the fact that MAPDs were much more likely to offer enhanced benefits and earn higher star ratings (Table 1) meant that, overall, MAPD plans had higher and earlier formulary placement rates across the 33 drugs under investigation.

Drug characteristics played a bigger role in formulary placement decisions than did plan characteristics. Compared with NCEs, LEs and CPs were much less likely to be placed on formulary (–36%; <.01; and –22%; P <.01, respectively). However, plans placing these products did so more quickly than with NCEs (–1.04 months; P <.01; and –0.93 months; P <.01, respectively). The timing of drug approval relative to other drugs in class had consistently significant effects on all outcome measures. Being second and third in class increased the likelihood of placement by 5% and 7%, respectively (P <.1), but delayed placement by 4.53 months (second in class) and 1.77 months (third or later in class) (P <.01). Later entrants were also significantly more likely to be subject to ST but less likely to require PA.


 
Copyright AJMC 2006-2019 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up