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The American Journal of Managed Care December 2013
Implementing Effective Care Management in the Patient-Centered Medical Home
Catherine A. Taliani, BS; Patricia L. Bricker, MBA; Alan M. Adelman, MD, MS; Peter F. Cronholm, MD, MSCE, FAAFP; and Robert A. Gabbay, MD, PhD
Cost Utility of Hub-and-Spoke Telestroke Networks From Societal Perspective
Bart M. Demaerschalk, MD, MSc; Jeffrey A. Switzer, DO; Jipan Xie, MD, PhD; Liangyi Fan, BA; Kathleen F. Villa, MS; and Eric Q. Wu, PhD
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Generic Initiation and Antidepressant Therapy Adherence Under Medicare Part D
Yuhua Bao, PhD; Andrew M. Ryan, PhD; Huibo Shao, MS; Harold Alan Pincus, MD; and Julie M. Donohue, PhD
Impact of Electronic Prescribing on Medication Use in Ambulatory Care
Ashley R. Bergeron, MPH; Jennifer R. Webb, MA; Marina Serper, MD; Alex D. Federman, MD, MPH; William H. Shrank, MD, MSHS; Allison L. Russell, BA; and Michael S. Wolf, PhD, MPH
Medication Utilization and Adherence in a Health Savings Account-Eligible Plan
Paul Fronstin, PhD; Martin-J. Sepulveda, MD; and M. Christopher Roebuck, PhD, MBA
Characteristics of Low-Severity Emergency Department Use Among CHIP Enrollees
Justin Blackburn, PhD; David J. Becker, PhD; Bisakha Sen, PhD; Michael A. Morrisey, PhD; Cathy Caldwell, MPH; and Nir Menachemi, PhD, MPH
Collection of Data on Race/Ethnicity and Language Proficiency of Providers
David R. Nerenz, PhD; Rita Carreón, BS; and German Veselovskiy, MS
Dietary Diversity Predicts Type of Medical Expenditure in Elders
Yuan-Ting Lo, PhD; Mark L. Wahlqvist, MD; Yu-Hung Chang, PhD; Senyeong Kao, PhD; and Meei-Shyuan Lee, DPH

Generic Initiation and Antidepressant Therapy Adherence Under Medicare Part D

Yuhua Bao, PhD; Andrew M. Ryan, PhD; Huibo Shao, MS; Harold Alan Pincus, MD; and Julie M. Donohue, PhD
This study shows that generic initiation improves adherence to antidepressant therapy among Medicare patients and mitigates the negative effects of the Part D coverage gap.
Objectives: To assess the effect of initiating antidepressant therapy with a generic prescription on adherence to antidepressant therapy among Medicare patients. A second objective is to assess how the effect might be moderated by the Medicare Part D coverage gap.

Study Design and Methods: Adherence to antidepressant therapy was measured by (a lack of) disruption in medication use defined by a gap of 30 days or more in antidepressant possession and monthly days of possession, both measured over 180 days since antidepressant initiation. We used a 5% random sample of Medicare fee-for-service beneficiaries who received a new depression diagnosis in the first half of 2007 and initiated antidepressant therapy within 60 days (n = 16,778). We estimated a Cox proportional hazard model for antidepressant disruption and a mixedeffects linear model for monthly possession. All analyses were stratified by 4 cohorts defined by Part D low-income subsidy (LIS) status and Medicare entitlement (aged vs disabled).

Results: Generic initiation was associated with improved adherence among all 4 cohorts, with a stronger effect among the non-LIS patients. Hazard ratios for antidepressant disruption ranged from 0.71 (95% confidence interval [CI], 0.53-0.96) among non-LIS, disabled patients to 0.88 (95% CI, 0.79-0.98) among LIS, aged patients. Generic initiation was associated with increases in days of monthly possession in all 4 cohorts and an additional benefit during the coverage gap for non-LIS patients.

Conclusions: Generic initiation can be an important tool to improve adherence to antidepressant treatment among Medicare patients and to mitigate the negative effects of the Part D coverage gap.

Am J Manag Care. 2013;19(12):989-998
Encouraging prescribers to initiate antidepressant treatment with a generic drug has the potential to improve antidepressant adherence among Medicare patients.
  • Starting patients with generics had benefits for antidepressant adherence by lowering out-of-pocket costs for all patients and by mitigating the effect of the Part D coverage gap faced by patients not receiving low-income subsidies.

  • Managed care organizations may target prescriber drug choice behaviors to further improve antidepressant adherence and effectiveness of antidepressant treatment among its members.
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.

METHODS

Data


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.

Study Sample

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.

We identified 4 distinct patient cohorts defined by their Medicare entitlement status (aged vs disabled) and Part D LIS status. Disabled beneficiaries differ in both socioeconomic status  and complexity of healthcare needs from aged beneficiaries. Patients  receiving LIS are either Medicare-Medicaid dual enrollees or have limited income or resources16; as shown below, they also have  more comorbid conditions. We thus chose not to treat the LIS patients as a “control” cohort for the non- LIS patients (since their  baseline trends in medication may not be comparable), but instead stratified all of our analysis by the 4 patient populations. 

We used the Multum Lexicon drug classification system17 to identify antidepressants (and whether a given prescription was generic or branded) based on the National Drug Code. We used drug-dispensing date and days of supply to determine time intervals during which a patient was in possession of antidepressants. When 2 or more intervals overlapped, we counted the overlapping period only once.

Main Outcome Measures

We created 2 measures of antidepressant adherence. The first measure is disruption in antidepressant therapy during the 180 days after initiation, equal to 1 if there was a gap in antidepressant possession of 30 days or longer and 0 otherwise. Patients who switched medication during the 180 days were considered adherent (ie, no disruption) as long as they did not experience a gap of 30 days or more. A follow-up  period of 180 days was based on depression treatment guidelinesthat recommend minimum length of pharmacotherapy during acute and continuation phases of treatment.3,4,18 The 30-day gap was defined so that patients who retained antidepressants from previous fills or who had a washout period between medication changes would not be incorrectly classified as nonadherent.19

The second measure, monthly days of antidepressant possession, is defined as the number of days in each of the 6 months following antidepressant initiation that the patient was in possession of antidepressants. We chose a monthly measure of possession (rather than the typical medication possession ratio over 180 days) because the monthly measure allows us to examine the dynamics of antidepressant use in relationship to the onset of the coverage gap.

Independent Variables

Our primary independent variable was the generic/brand status of the first prescription. Of all the branded antidepressant initiations in our sample, 83% were 1 of 3 antidepressants that did not yet have a generic equivalent on the US market in 2007: Lexapro (escitalopram, a selective serotonin reuptake inhibitor [SSRI], accounting for 44% of all branded initiations), Cymbalta (duloxetine, a serotonin and norepinephrine reuptake inhibitor; 20%) and Effexor XR (venlafaxine XR, a serotonin and norepinephrine reuptake inhibitor; 19%). While our main analysis included all classes of antidepressants, we conducted a sensitivity analysis by including  only patients who initiated their treatment with a generic or branded SSRI. 

For non-LIS patients, whose Part D coverage includes a coverage gap, a second independent variable of interest was an indicator of  whether the patient was in the coverage gap at a given time. In analyses of both outcomes, this indicator is time varying because  patients may transition into the coverage gap during the follow-up.

Statistical Analysis

For disruption in antidepressant therapy, we estimated a Cox proportional hazard model of time to disruption. For non-LIS patients, in addition to generic initiation, independent variables included Part D benefit phase (coverage gap vs before the coverage gap) and an interaction between generic initiation and coverage gap. This allowed us to examine whether the effect of generic initiation was stronger as patients experienced the coverage gap. We conducted tests of the proportional hazard assumption based on Schoenfeld residuals.20

For monthly days with antidepressant possession, we estimated a mixed-effects linear model using data at the patient-month level, with a patient-level random intercept to account for correlations between multiple observations clustered within a given patient. Generic initiation was the primary independent variable. The models estimated among the non-LIS cohorts also included dichotomous indicators of number of complete months that a patient had been in the coverage gap, which ranged from 1 to 5. This was to allow the effect of coverage gap to differ with the length of time spent in the coverage gap. Interaction terms between generic  initiation and each of the coverage gap month indicators were also included. To control for time patterns in antidepressant use that  were independent from the effects of generic initiation and experience of the coverage gap, we included ordinal indicators of months  following antidepressant initiation.

 
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