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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.
The study estimates for the effects of formulary restrictions have high internal validity. By focusing on the randomized LIS recipients, we were able to minimize potential bias by isolating the effects of formulary restrictions from that of cost-sharing rules and removing confounding effects of virtually all beneficiary characteristics we could observe—and, by extension, other unobserved factors that represented critical threats to internal validity in conventional observational studies. 

Additionally, LIS recipients represent about 40% of Part D enrollees, yet account for over 55% of total drug spending.18 This is a socially and economically disadvantaged population that often lives with disabilities and multiple chronic conditions. They tend to have worse health outcomes, yet significantly higher healthcare expenditures.9 Such disparities suggest the need to improve both quality and efficiency of care for this vulnerable population.

In 2012, full LIS recipients paid at most $2.60 for generics and $6.50 for brand name medications.8 We found that neither the availability of free generics via mail order nor generous coverage of brand name medications seemed to meaningfully affect LIS recipients’ overall adherence to OHAs, statins, and RAS antagonists. Hence, LIS recipients’ suboptimal adherence may be due to behavioral or clinical causes rather than costs or access issues.9,19 Part D plan sponsors and other healthcare decision makers may consider behavioral interventions to improve LIS recipients’ perceived importance of medication adherence and disease management skills.


This study has a few limitations. First, the study subjects were randomized to plans rather than varying formulary restrictions. Hence, the observed effects of formulary restrictions may be confounded by other plan-level policies that also affect medication utilization patterns. We observed that several benchmark PDPs provided free mail order prescriptions for commonly used generics, which would incentivize beneficiaries to take generics instead of brand name drugs and use more medications overall. We also observed that Envision RxPlus Silver did not offer 90-days-supply prescriptions in 2012, whereas all the other benchmark PDPs did. Conceptually, shorter length of drug supply per prescription fill presents more opportunities for filling prescriptions late and may lead to gaps in medication usage. To eliminate these 2 plan-level policies as alternative explanations for the observed effects of formulary restrictions on the study outcomes, we excluded beneficiaries enrolled in the Envision RxPlus Silver plan from all analyses and included a covariate for count of generics available for free via mail order in the regression models. In addition, we estimated random intercept regression models to recognize variability in unobserved plan attributes.

Second, our randomized cohorts of LIS beneficiaries were not strictly comparable from plan to plan within PDP regions. Because Part D regional benchmark thresholds are determined annually through a competitive bidding process, plans can lose or gain benchmark status from year to year. When a plan loses benchmark status, its random assignees would be reassigned to other plans (however, there is an exception when the plan premium is just above the benchmark threshold). Additionally, the LIS recipients were randomized at different times. This dynamic randomization process resulted in small differences in beneficiary assignment year and age. To mitigate the potential confounding effects of beneficiaries’ tenure in the plan and age, we included both assignment year and age as covariates in the regression analysis.

Readers should use caution in generalizing the findings of this study to non-LIS beneficiaries. Compared with non-LIS beneficiaries, LIS recipients tend to be younger, more socioeconomically disadvantaged, and more likely to live with disabilities and multiple chronic conditions. Nevertheless, both LIS and non-LIS beneficiaries in each plan faced the same formulary policies and appeal process for requesting coverage exceptions. Although the impact of formulary restrictions on the study endpoints may differ in magnitude, we expected the nature of the relationships to hold in non-LIS populations. Last, our study focused on existing users of OHAs, statins, and RAS antagonists. Future research may consider evaluating the impact of formulary noncoverage and UM tools on treatment initiation among individuals who are candidates for those chronic medications.



Placing formulary restrictions on brand name drugs shifts drug utilization toward generics and lowers cost per prescription fill, but has minimal impact on overall adherence for OHAs, statins, and RAS antagonists among Medicare Part D enrollees receiving LIS. 

Author Affiliations: Department of Pharmaceutical Health Services Research (XS, BCS, SET, EMP), and The Peter Lamy Center on Drug Therapy and Aging (BCS), and Department of Epidemiology and Public Health (LSM), University of Maryland, Baltimore, MD; Information Products Group, Office of Information Products and Data Analytics, Center for Medicare and Medicaid Services (CAP), Baltimore, MD.

Source of Funding: This work was supported by a Young Investigator Adherence Award funded by the Pharmaceutical Research and Manufacturers of America (PhRMA) Foundation. The funder played no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article. The views expressed in this paper are those of the authors and no official endorsement by HHS or CMS is intended or should be inferred.

Authorship Information: Concept and design (XS, LSM, EMP); acquisition of data (XS, BCS); analysis and interpretation of data (XS, LSM, EMP); drafting of the manuscript (XS, LSM); critical revision of the manuscript for important intellectual content (XS, BCS, CAP, SET, LSM, EMP); statistical analysis (XS, LSM); obtaining funding (XS); administrative, technical, or logistic support (CAP); and supervision (BCS, CAP, SET).

Address Correspondence to: Xian Shen, PhD, University of Maryland, Baltimore, 220 Arch St, Rm 12-328, Baltimore, MD 21201. E-mail:

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