Published Online: April 22, 2013
Feng Zeng, PhD; Bimal V. Patel, PharmD, MS; and Louis Brunetti, MD
Objectives: To investigate the impact of Part D coverage gap reform on diabetes medication adherence.
Study Design: Retrospective data analysis based on pharmacy claims data from a national pharmacy benefit manager.
Methods: We used a difference-in-difference-indifference method to evaluate the impact of coverage gap reform on adherence to diabetes medications. Two cohorts (2010 and 2011) were constructed to represent the last year before Affordable Care Act (ACA) reform and the first year after reform, respectively. Each patient had 2 observations: 1 before and 1 after entering the coverage gap. Patients in each cohort were divided into groups based on type of gap coverage: no coverage, partial coverage (generics only), and full coverage.
Results: Following ACA reform, patients with no gap coverage and patients with partial gap coverage experienced substantial drops in copayments in the coverage gap in 2011. Their adherence to diabetes medications in the gap, measured by percentage of days covered, improved correspondingly (2.99 percentage points, 95% confidence interval [CI] 0.49-5.48, P = .019 for patients with no coverage; 6.46 percentage points, 95% CI 3.34-9.58, P <.0001 for patients with partial coverage). Patients with full coverage also had lower copayments in the gap in 2011. However, their adherence did not increase (–0.13 percentage point, P = .8011).
Conclusions: In the first year of ACA coverage gap reform, copayments in the gap decreased substantially for all patients. Patients with no coverage and patients with partial coverage in the gap had better adherence in the gap in 2011.
Am J Manag Care. 2013;19(4):308-316
The Affordable Care Act mandated that Part D coverage gap be shrunk starting from 2011. The reform had an important impact on adherence to diabetes medications in the gap.
The coverage gap reform decreased copayments for diabetes medications substantially in the coverage gap for all patients.
Patients with no coverage and patients with partial coverage in the gap had significant improvements in adherence.
Patients with full coverage in the gap had unchanged adherence to diabetes medications in the coverage gap in 2011.
Medicare Part D was implemented in 2006 to provide prescription drug benefits for Medicare beneficiaries. The implementation of Part D has led to many positive changes: reduced out-of-pocket expenses, increased medication fills, improved adherence, decreased medical spending, and fewer avoidable hospitalizations.1-10 One controversial aspect of the Part D benefit design is the coverage gap, commonly referred to as the “donut hole.” Patients with a Part D plan that has a standard defined benefit have a copayment of 25% on prescription drugs after they pay the initial deductible. After their total pharmacy spending reaches the coverage gap limit ($2830 in 2010), patients have a 100% copayment for their drugs until they reach the catastrophic limit ($6440 in 2010). In the catastrophic stage patients pay 5% or $2.60 per prescription.
The lack of coverage in the donut hole raises concern that the increase in copayment may have an adverse effect on drug utilization. Research has shown that reaching the coverage gap decreases medication fills11-14 and lowers adherence to essential medications.15,16 In response to these concerns, the Affordable Care Act (ACA), passed in March 2010, includes a provision to shrink the coverage gap. Starting in 2011, the copayment for brand drugs in the coverage gap was reduced 50%, and the copayment for generic drugs was reduced 7%. The copayments for brand drugs and generic drugs in the gap will be further reduced after 2012. In the year of 2020, the donut hole will be completely closed with a 25% copayment for both brand and generic drugs.17,18
The closure of the donut hole represents another significant change for Medicare Part D. A solid understanding of the latest reform is critical for the design of Part D benefits. This research contributes by investigating the impacts of the 2011 coverage gap reform on adherence to diabetes medications. We focused on diabetes because it is a highly prevalent disease among Medicare beneficiaries. It is estimated that in 2010, the prevalence rates for people aged 65 to 74 years and >75 years were 20.7% and 18.9%, respectively. The diabetes prevalence rates for the 2 groups are expected to become 30.1% and 32.7% in 2050.19 Effective management of diabetes is vital to the success of Medicare.
There are 4 types of Part D plans: standard defined benefit, actuarially equivalent, basic alternative, and enhanced alternative. Of the 4 types of plans, the actuarially equivalent and basic alternative plans are similar to the standard defined benefit plan in coverage. Patients with an enhanced alternative plan can pay a higher premium for better coverage, such as having coverage in the gap and/or covering more drugs than standard defined benefit plans.
The year 2011 is the first year of coverage gap reform mandated by the ACA. In 2011, patients reaching the gap received a 50% copayment reduction for brand drugs and a 7% copayment reduction for generic drugs. For patients whose Part D plans provided coverage in the gap, discounts were applied to their copayments directly. For example, suppose a patient who had coverage while in the gap in 2010 paid a 25% copayment for both brand and generic drugs in the coverage gap. In 2011, this same patient would pay a 12.5% copayment for brand drugs and a 23.25% copayment for generic drugs in the coverage gap.
Data for this research came from pharmacy claim data from MedImpact HealthCare Systems Inc’s book of business. Med- Impact is a national pharmacy benefit manager. The research data included a 2010 cohort and a 2011 cohort. The 2010 cohort represents the last year before ACA reform and the 2011 cohort represents the first year after ACA reform.
Patients in both cohorts were required to be continuously enrolled in the same health plan for 2 years: 1 year before the cohort year and the cohort year. Patients with diabetes were identified as having at least 2 diabetes drug claims in both the cohort year and the year before the cohort year. It was important to require patients to have used diabetes drugs before the cohort year so that we had a full year to measure adherence in the cohort year. The inclusion of 1 year of data before the cohort year also was important to construct a comorbidity index. All patients had to be at least 65 years old in their cohort year. Patients eligible for a low-income subsidy were removed because their copayment structures are different.
Each data cohort included patients with no coverage, partial coverage (ie, generic coverage only), and full coverage in the gap. In this research, patients with partial and full coverage all came from enhanced alternative plans. Patients with no coverage came from standard defined benefit, actuarially equivalent, basic alternative, and enhanced alternative plans. Theoretically, patients in actuarially equivalent, basic alternative, and enhanced alternative plans could have coverage gap limits different from those of standard defined benefit plans. However, that was not the case in this research. We checked and confirmed that all patients in the data set had the same coverage gap limits.
These identification steps generated 20,709 patients in the 2010 cohort and 20,212 patients in the 2011 cohort. We selected only patients who entered the coverage gap but did not enter the catastrophic level to make it easier to compare adherence before the gap with adherence in the gap.12,13,16 This exclusion led to 6828 patients in the 2010 cohort and 6124 patients in the 2011 cohort.
The outcome variable was adherence to diabetes medications. Diabetes is a long-term and progressive disease. Adherence to diabetes medication is critical for maintaining glycemic control and slowing down disease progression. Poor adherence can lead to inadequate glycemic control, higher probabilities of hospitalization, higher medical cost, and higher mortality.20-27
Adherence is measured by proportion of days covered (PDC), defined as the number of days covered by at least 1 diabetes medication divided by the length of the study period based on medication fill date and days of supply. The PDC methodology has been used in many studies.16,20,25,26,28 The value of PDC is bounded between 0.0 and 1.0.
This research used a difference-in-difference-in-difference method to identify the impact of coverage gap reform on adherence to diabetes medications. In this model, year 2010 data and year 2011 data were used to represent the periods before and after coverage gap reform, respectively. Each patient in a cohort year had 2 observations: one before the coverage gap and the other in the coverage gap. Patients with no coverage or partial coverage were the treatment group; patients with full coverage were the control group. In a straightforward difference- in-difference-in-difference model, the effect of coverage gap reform was captured by the interaction of coverage gap, year 2011, and the type of coverage in the coverage gap.
One problem of a straightforward difference-in-difference-in-difference model is that the outcome variable, PDC, was bounded between 0 and 1. In this research, the mean PDC value was around 80% and the distribution was highly skewed. This can be problematic in an ordinary least squares regression. One way to address this issue is to transform the outcome variable as the change of PDC after reaching the coverage gap, defined as PDC in the coverage gap minus PDC before the gap. After the transformation, the model can be written as:
Y = b0 + NoCov*b1 + GenCov*b2 + Y2011*b3 + NoCov*Y2011*b4 + GenCov*Y2011*b5 + e,
where Y equals PDC in the coverage gap minus PDC before the coverage gap for each patient, NoCov is the dummy variable indicating no coverage in the gap, GenCov is the dummy variable indicating partial coverage in the gap, and Y2011 is the dummy variable indicating the 2011 cohort.
In this model b4 and b5 are the coefficients of interest. They represent the change in adherence in the coverage gap in response to coverage gap reform for patients with no coverage and partial coverage, respectively.
Through the transformation, each patient’s idiosyncratic propensity to be adherent was removed. Patients’ unchanged characteristics such as age, sex, and geographical location were also removed. As a consequence, the inclusion of covariates such as age and sex was not necessary. The main model was run without covariates. We included covariates in the model as part of the robustness analysis. Control variables included age, sex, geographical location, whether insulin was used in the last year, and comorbidities. Information on patient demographics was obtained from patients’ eligibility files. Information on the use of insulin was available from the previous year’s pharmacy claim file. Comorbidities were measured by RxRisk, a comorbidity measure based on pharmacy claims in the prior year.29 Each RxRisk category indicates whether a patient took certain classes of medications (eg, those for hypertension and hyperlipidemia) in the previous year. Only RxRisk categories with prevalence rates higher than 5% were included in the study.
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