Characteristics of Prescription Drug Fills Using Pharmacy-Pharmacy Benefit Manager Discount Programs: The “GoodRx” Model

Abstract

Objectives

This study aimed to characterize products using pharmacy-pharmacy benefit manager (PBM) discounts and to estimate the association among such discounts, prescription utilization, and out-of-pocket costs.

Methods

This is a retrospective cohort study using IQVIA’s Formulary Impact Analyzer, which contains anonymized, individual-level pharmacy claims representing US retail pharmacy transactions. We focused on 20 products with the greatest number of transactions using a pharmacy-PBM discount. Our unit of analysis was a treatment episode, defined as the length of time from an incident fill to no continuous use for 60 consecutive days after allowing for indefinite stockpiling. Outcome measures included products with greatest pharmacy-PBM discount use, characteristics of treatment episodes, and out-of-pocket costs with and without pharmacy-PBM discount.

Results

Across all products, 3.82% of transactions and 7.69% of treatment episodes were accompanied by a pharmacy-PBM discount. Commonly discounted products included generic treatments for chronic disease (lisinopril, levothyroxine, metformin) and neuropsychiatric conditions (alprazolam, amphetamine, buprenorphine, hydrocodone). The median postdiscount out-of-pocket cost was >2.5-fold higher during treatment episodes with a discount than those without ($15.15, interquartile range [IQR] $8.53-32.00, vs $5.88, IQR $1.40-15.00). Median treatment episode duration was 249 days (IQR 132-418) with discount use compared with 236 days (IQR 121-396) without discount use, although treatment episodes that began with a discount had fewer transactions per treatment episode and were shorter (median 212 days, IQR 114-360) than those that did not (313 days, IQR 178-500).

Conclusions

Pharmacy-PBM discounts may foster market competition and improve access for under- and uninsured individuals; however, these programs may not generate savings for many insured individuals.

Authors

Jill Curran Yuchen Wang So-Yeon Kang Andrew Xuan Gerard Anderson Ge Bai G. Caleb Alexander

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