Generic Initiation and Antidepressant Therapy Adherence Under Medicare Part D
Published Online: December 20, 2013
Yuhua Bao, PhD; Andrew M. Ryan, PhD; Huibo Shao, MS; Harold Alan Pincus, MD; and Julie M. Donohue, PhD
Antidepressants are among the most prescribed drugs for US adults.1 Among people 65 years or older, 14% use antidepressants annually for depression, anxiety, or another indication.2 While adherence to antidepressants is critical to realizing the effectiveness of antidepressant treatment,3,4 around 40% of Medicare managed care patients discontinue their antidepressant treatment prematurely.5 High out-of-pocket costs due to lack of drug coverage or high cost sharing has been shown to decrease drug adherence in most populations,6 including Medicare beneficiaries using antidepressant medication.7
Generic antidepressants are now widely available.8 By 2007, most major brands of second-generation antidepressants had generic quivalents in the US market. Generic use has the potential to improve adherence to antidepressant therapy because patient out-of-pocket costs for generics are nearly always much lower than they are for brands.9 For example, for patients receiving Medicare prescription benefits in 2011, the median copayment was $7 for generics, $42 for preferred brands, and $78 for nonpreferred brands.10 Choice of generic or brand name is partly a function of provider preferences.11 When a branded drug is prescribed in absence of a “dispense as written” request by the prescriber or the patient, patients often receive a generic equivalent because of state mandates of generic substitution12 or pharmacist discretion. The generic (vs branded) status of the first prescription is likely highly influential in determining generic or branded drug use throughout the course of treatment and therefore may have important implications for patient adherence to chronic medication therapy.
The cost advantage of generics has greater implications under Medicare’s current prescription drug benefit (Part D) than under a traditional insurance plan because of the Part D coverage gap. For example, in 2007 (the study year), under most plans, patients whose total Part D–covered drug spending reached $2510 were responsible for 100% of drug costs until their total spending reached $5726, or until the start of 2008. An estimated 3.4 million beneficiaries (about 14% of all Part D enrollees) reached the coverage gap in 2007.13 While the Affordable Care Act will take steps to gradually close the coverage gap over the 10 years starting in 2011, in the near term, differences in out-of-pocket costs between branded and generic antidepressants will remain greater during the coverage gap than otherwise.
In this study, we assessed the effects of initiating antidepressant treatment with a generic versus a branded prescription (generic initiation) on adherence to antidepressant therapy for the treatment of depression. Our study contributes to the literature by examining both the effect of generic initiation by itself and how the effect might be moderated by the presence of the Medicare Part D coverage gap.
We used data from a 5% random sample of beneficiaries with depression in 2006 and 2007 from the Medicare Chronic Condition Data Warehouse.14 Files used in this study included carrier claims and the Part D Prescription Drug Event file. We also used the Beneficiary Summary File and Chronic Condition Summary File to derive demographic and comorbidity information for beneficiaries.
Our study population was Medicare fee-for-service patients who experienced a new episode of depression and subsequently initiated antidepressant therapy within 60 days of the new depression diagnosis. This is a population with a clear clinical indication for depression treatment. To be included in the analysis, all beneficiaries were required to be continuously enrolled in Medicare Parts A and B throughout 2006 and 2007. Because Part D had an enrollment deadline of May 11 in 2006, we further required beneficiaries to be continuously enrolled in Part D from July 1, 2006, to December 31, 2007.
To identify patients experiencing a new episode of depression, we first identified for each patient the first physician service claim between January 1 and June 30, 2007, that hadmajor depression, depressive disorder not elsewhere classified, or dysthymia as a primary or secondary diagnosis (International Classification of Diseases, Ninth Revision codes 296.2x, 296.3x, 311x, and 300.4x) (the index diagnosis). We further excludedpatients who had any physician claim with a depression diagnosis or antidepressant use during the 6 months prior to the index diagnosis. We then restricted the sample to patients who filled an antidepressant prescription within 60 days of the index date. The resulting study sample contained patients who initiated antidepressant therapy no later than July 4, 2007, to allow for follow-up data covering 180 days after initiation for every patient. We excluded 111 patients who had missing Part D benefit phase information. We also excluded a small number of beneficiaries who were entitled to Medicare because of end-stage renal disease.
More than half of patients in the study sample received the Part D low-income subsidy (LIS) and thus were not subject to the coverage gap. Among patients not receiving LIS, we excluded patients who were already in the coverage gap by the time they initiated antidepressant therapy (n = 434), since these patients faced very different cost sharing compared with patients who transitioned into the coverage gap after antidepressant initiation. Among non-LIS patients who transitioned into the coverage gap during the 180 days, about 20% spent through the coverage gap later in 2007 and transitioned to the catastrophic coverage phase in which they had almost complete coverage. A recent study of a depression cohort found that patients who eventually attained catastrophic coverage did not change their medication use while in the coverage gap.15 We thus excluded these patients (n = 431) in our main analysis. In a sensitivity analysis, we included both types of patients to examine the robustness of our findings. Our main analytic sample included 16,778 beneficiaries.
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