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The American Journal of Managed Care June 2007 - Part 2
Formulary Tier Placement for Commonly Prescribed Branded Drugs: Benchmarking and Creation of a Preferred Placement Index
C. Daniel Mullins, PhD; Francis B. Palumbo, PhD; and Mojdeh Saba, BS
Effects of Benefit Design Change Across 5 Disease States
Diana I. Brixner, PhD, RPh; Vijay N. Joish, PhD; Gary M. Oderda, PharmD, MPH; Steven G. Avey, RPh; Douglas M. Hanson, MA; and H. Eric Cannon, PharmD
Consumer Response to Dual Incentives Under Multitiered Prescription Drug Formularies
Boyd H. Gilman, PhD; and John Kautter, PhD
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Incentive Formularies and Changes in Prescription Drug Spending
Bruce E. Landon, MD, MBA; Meredith B. Rosenthal, PhD; Sharon-Lise T. Normand, PhD; Claire Spettell, PhD; Adam Lessler, BA; Howard R. Underwood, MD, MBA; and Joseph P. Newhouse, PhD
Effect of a Medication Copayment Increase in Veterans With Schizophrenia
John E. Zeber, PhD; Kyle L. Grazier, PhD; Marcia Valenstein, MD; Frederic C. Blow, PhD; and Paula M. Lantz, PhD
Effect of Copayments on Drug Use in the Presence of Annual Payment Limits
George Kephart, PhD; Chris Skedgel, MDE; Ingrid Sketris, PharmD; Paul Grootendorst, PhD; and John Hoar, MPA
"Fiscally Responsible, Clinically Sensitive" Cost Sharing: Contain Costs While Preserving Quality
A. Mark Fendrick, MD; and Michael E. Chernew, PhD

Incentive Formularies and Changes in Prescription Drug Spending

Bruce E. Landon, MD, MBA; Meredith B. Rosenthal, PhD; Sharon-Lise T. Normand, PhD; Claire Spettell, PhD; Adam Lessler, BA; Howard R. Underwood, MD, MBA; and Joseph P. Newhouse, PhD

OBJECTIVES: To examine the impact of incentive formularies on prescription drug spending shifts in formulary compliance, use of generic medications, and mail-order Fulfillment in the year after introduction of a new pharmacy benefit strategy.

STUDY DESIGN: Pre-post comparison study with matched concurrent control group (difference-indifferences analysis).

METHODS: Study subjects were continuously enrolled patients from a single large health plan in the northeastern United States. Health plan administrative data were used to determine the total, health plan, and out-of-pocket spending in the year before and the year after the introduction of 12 different benefit changes, including 1 in which copayments decreased.

RESULTS: Overall, changing from a single-tier or 2-tier formulary to a 3-tier formulary was associated with a decrease in total drug spending of about 5% to 15%. Plan spending decreased more dramatically, about 20%, whereas out-of-pocket spending that resulted from higher copayments increased between 20% and >100%. Changing to an incentive formulary with higher copayments was accompanied by a small but inconsistent decrease in use of nonformulary selections and a concomitant increase in both generic and formulary preferred utilization. Mail-order fulfillment doubled, albeit from a low baseline level.

CONCLUSIONS: Switching to incentive formulary arrangements with higher levels of copayments generally led to overall lower drug costs and vice versa. These effects varied with the degree of change, level of baseline spending, and magnitude of the copayments. Whether these effects are beneficial overall depends on potential health effects and spillover effects on medical spending.

(Am J Manag Care. 2007;13(part 2):360-369)

The impact of incentive formularies on prescription drug spending was determined by examining a large and diverse number of benefit changes, including 1 that lowered copayments, in a single large health plan.

Changing from a single-tier or 2-tier formulary to a 3-tier formulary was associated with a decrease in total drug spending of about 5%-15%.

Changing to an incentive formulary with higher copayments was accompanied by a small but inconsistent decrease in the use of nonformulary selections and a concomitant increase in both generic and formulary preferred utilization.

These findings differ from some prior research in that smaller responses to changes in patient copayments were demonstrated across a wide variety of benefit designs.


Among the most common tools insurers use to reduce healthcare costs are incentive formularies, which promote the use of generic or preferred brand name medications through differential copayments. In recent years, incentive formularies have evolved through the addition of tiers and higher levels of copayments. As of 2005, almost 75% of commercially insured individuals had prescription drug coverage with an incentive formulary with 3 or more tiers, whereas a decade ago such coverage was rare.1 Nonetheless, drug spending grew substantially over this time period.

Pharmaceutical companies attempt to influence the placement of their products in a preferred tier through price, including rebates to pharmacy benefit managers based on utilization levels of specific drugs. By shifting market share to preferred products, benefit managers can obtain higher rebates and thereby reduce their drug costs. A growing number of studies have examined the impact of higher prescription drug copayments on consumer behavior and spending, but none has incorporated rebates into the analyses. Instead, previous studies used data from paid claims. By omitting information on rebates, these data overstate drug spending. In addition, most previous studies of cost sharing for pharmaceuticals have a variety of methodologic flaws or limitations.2-10 For instance, studies have been limited to a small number of benefit changes for a few companies, examined selected populations, been cross-sectional, or used nonequivalent comparison groups, including groups in different parts of the country or with different medical benefits.

In this study we used data on continuously enrolled patients from a single insurer that managed both medical and prescription drug benefits to estimate the impact of changes in drug benefit design on pharmaceutical use and spending. In all cases the changes in benefit structure were not under the control of the enrollee, but rather his or her employer. We examine 2 sets of outcomes: prescription drug spending, by both the health plan and member, and formulary compliance, including the use of generic medications and mail-order  fulfillment.


We assembled a dataset of complete pharmaceutical claims from January 1, 2000, through December 31, 2001, as well as demographic and benefit design information for 1.25 million continuously enrolled HMO/point-of-service (POS) members from the Northeast and mid-Atlantic regions of the health plan. Using these data we identified groups of enrollees whose pharmacy benefit structure changed on January 1, 2001, and matched these enrollees with others who maintained the identical benefit structure throughout the study period. We then compared prechange and postchange values for both groups using a  ifference-in-differences approach.

Study Population
Eligible enrollees were younger than age 64 years, had prescription drug coverage provided by the health plan (approximately 70% of HMO/POS enrollees), and were drawn from the 11 states in the Mid-Atlantic and Northeast areas where the health plan has its largest market penetration. We included states with a minimum of 10 000 enrollees to ensure adequate numbers of enrollees in each state. Because of potential selection bias in smaller firms, we eliminated enrollees associated with firms with fewer than 5 enrollees. Fifty-seven percent of the resulting study population were employed in firms with 100 or more employees.

Pharmaceutical Benefits and Claims
The health plan used a single national formulary for all enrollees, but individual employers could select from a menu of incentive-based formularies ranging from a single-tier formulary to a variety of 3-tier formularies that required higher copayments for medications in higher tiers.

We linked pharmaceutical claims data to an enrollment file that contained information on the employer group, benefit design, and standard demographic characteristics. From pharmaceutical claims we obtained medication name, dosage, days supplied, National Drug Code, place of purchase (retail vs mail order), and the amounts paid to the pharmacy by the health plan and the member through copayments. We categorized each drug prescribed over the 2-year period as generic, formulary preferred, or formulary nonpreferred based on observed copayments.

. To obtain plan and out-of-pocket pharmaceutical spending for each member month, we summed claims for each individual. For mail-order prescriptions, we determined the number of days supplied to the nearest month and the amount of the copayment. If a mail-order prescription spanned both years of the study, its expenditure was allocated to the year in which it was filled, and the spending and the copayment were apportioned equally to each month covered by the prescription. Combining retail and mail-order  spending, average monthly pharmaceutical spending was calculated for the 12 months before and the 12 months after the switch in benefits.

Formulary Compliance and Mail-Order Fulfillment. We calculated the portion of filled prescriptions (standardized by days supply for chronic medications) for generic, formulary preferred, and formulary nonpreferred drugs, and the proportion of total prescription months fulfilled through mail order. Mail-order fulfillment allowed the enrollee to receive a 3-month supply of a drug for 2 copayments instead of 3 copayments.

Creating Matched Cohorts
We identified 7 cohorts of enrollees that had the same pharmaceutical benefit structure in 2000, with some portion of each cohort being switched to a different benefit structure on January 1, 2001. Thus, we could examine a full 12 months of utilization before and after the benefit switch. Among the 7 cohorts, we chose “treatment groups†from the largest 12 groups with a benefit change in 2001. We then matched each of these 12 groups with a comparison group. To do so, we used individuals in the 7 cohorts and estimated propensity score models predicting a change in benefit structure. As explanatory variables, we used state, employer size, and baseline demographic and enrollee clinical characteristics, as well as information on formulary compliance in the first time period. To measure clinical characteristics we used DxCG software, which creates a summary score of the patients' comorbidities (DxCG, Boston, Mass).11 We matched each enrollee who switched benefits to an enrollee who did not switch based on the estimated propensity score. To ensure close matches, we required the estimated log-odds of a benefit change between an enrollee who switched and one who did not to be within 0.60 standard deviation. This value removes approximately 90% of the bias in estimates of effects due to differences in covariate distributions between “treatment†and comparison groups.12 Exact matching of enrollees was required for state and age (in 5-year increments).

Accounting for Rebates
Because of its confidential and proprietary nature, rebate information has not been available for previous research studies. Without this information, however, the estimated levels of spending on pharmaceuticals are likely to be biased. Assuming that incentive formularies shift market share to preferred drugs, rebates differentially affect estimates of spending on preferred drugs relative to nonpreferred drugs. To protect the proprietary nature of rebate information, we use the “average†value of rebates per prescription for formulary preferred products. Specifically, we apportioned the total dollar amount of rebates in aggregate equally to each filled prescription for a formulary product. The magnitude of the rebate was not related to the pharmacy benefit structure of the individual enrollee filling a prescription. This method assumes that the changes in utilization of brand formulary products within each cohort were consistently related to changes in rebates.

To test the null hypothesis of no difference between the treatment and comparison group, we used a 2-sample t test for continuous variables and a χ2 test for dichotomous variables. Our major interest, however, was in the differences between prechange and postchange use in our 2 groups. After matching on the basis of the propensity score, these differences were assessed using paired t tests for continuous variables and χ2 statistics from generalized estimating equations for grouped (paired) binomial data.


About 600 000 members, or half of all continuously enrolled members, had 1 of the 7 unique pharmacy benefit structures in 2000 that we included in our study. Just over half of these members were female, and the average age was generally in the low thirties. Across the 7 cohorts, the proportion of members from employers with more than 3000 covered employees ranged from 34% to 100%. After matching, there were no statistically significant  differences in any of the observed patient characteristics for any matched cohort (Table 1).

Changes in Spending
Prescription drug spending by the health plan (net of rebates) as well as total prescription drug spending for the matched cohorts is presented in Table 2. Columns 4-6 show plan spending for the baseline year (2000) and the intervention year (2001) as well as the difference in spending for the group that changed relative to its matched control group (labeled “difference-in-differences”). The subsequent columns present the same information for out-of-pocket spending (columns 7-9) and overall spending (columns 10- 12). Each specific benefit change has its own matched control group; within group 1, for example, 2 different comparison populations (cohorts 1a and 1c) were used because each of these comparison populations was exactly matched with individuals in the relevant group that changed benefits.

Overall, changing from a single- or 2-tier formulary to a 3-tier incentive formulary with concomitant higher copayments in the second and third tier was associated with a decrease in total drug spending of 5% to 15%. Plan spending decreased more, on the order of 20%, whereas out-of-pocket spending because of the higher copayments for the second and third tier increased between 20% and >100%. For example, group 1 started as a single-tier program with a $5 copayment for all medications. In 2001 cohort 1b switched to a 3-tier incentive formulary with copayments of $5, $10, and $25 for the respective tiers, and cohort 1d switched to a similar 3-tier program with higher copayments of $10, $15, and $30. When compared with the control group, average per member per month spending by the plan fell $7.20 for cohort 1b and $8.80 for cohort 1d (21% and 30%), whereas average per member per month out-of-pocket spending increased $3.80 and $5.10, respectively. Average total spending decreased $3.50 and $3.70, respectively (P < .001).

Group 6 began with a 3-tier incentive formulary. For group 6b, copayments increased for each tier, whereas for cohort 6d copayments fell for each tier. Compared with the control group, average per member per month spending by the health plan decreased $5.10 for cohort 6b and increased $7.20 for cohort 6d, the group with lower copayments. Similarly, average per member per month out-of-pocket spending increased $2.20 for cohort 6b and decreased $3.30 for cohort 6d. Symmetrically, total spending decreased $2.90 for cohort 6b and increased $3.90 for cohort 6d.

Copyright AJMC 2006-2018 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
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