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The American Journal of Managed Care October 2013
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Dispensing Channel and Medication Adherence: Evidence Across 3 Therapy Classes
Reethi Iyengar, PhD, MBA, MHM; Rochelle Henderson, PhD, MPA; Jay Visaria, PhD, MPH; and Sharon Glave Frazee, PhD, MPH
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Physician Capability to Electronically Exchange Clinical Information, 2011
Vaishali Patel, PhD, MPH; Matthew J. Swain, MPH; Jennifer King, PhD; and Michael F. Furukawa, PhD
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David T. Liss, PhD; Paul A. Fishman, PhD; Carolyn M. Rutter, PhD; David Grembowski, PhD; Tyler R. Ross, MA; Eric A. Johnson, MS; and Robert J. Reid, MD, PhD
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Dispensing Channel and Medication Adherence: Evidence Across 3 Therapy Classes

Reethi Iyengar, PhD, MBA, MHM; Rochelle Henderson, PhD, MPA; Jay Visaria, PhD, MPH; and Sharon Glave Frazee, PhD, MPH
Findings indicate that patients using mail order pharmacies had significantly better adherence to antidiabetics, antihypertensives, and antihyperlipidemics than patients who used the retail dispensing channel.
Objectives: To examine the association of mail order versus retail pharmacy dispensing channels with medication adherence for patients on diabetes, hypertension, or high blood cholesterol  medications, controlling for prior adherence behavior (PAB) and days of supply.

Study Design: Retrospective analysis using de-identified pharmacy claims data from a large national pharmacy benefits manager between April 2009 and December 2011.

Methods: Continuously eligible patients with an antidiabetic, antihypertensive, or antihyperlipidemic prescription claim between October and December 2009 were identified and followed over a 2-year period. Multivariate logistic regression was used to evaluate the impact of dispensing channel on medication adherence, controlling for differences in demographics, disease burden, and drug use pattern. Patients with a medication possession ratio of 80% or greater were considered adherent. The analysis controlled for PAB by using patients’ adherence status in 2010.

Results: Overall, patients using the mail order channel had higher adherence rates than their retail counterparts across all 3 therapeutic classes. In 2011, the likelihood of a mail order patient being adherent was approximately 1.15 times higher than that of a retail patient for antidiabetics, 1.11 times higher for antihypertensives, and 1.19 times higher for antihyperlipidemics. PAB was the strongest contributor to the odds of a patient being adherent across all 3 therapy classes: odds ratios ranged from 5.87 to 9.49.

Conclusions: After adjusting for PAB, differential days of supply, and differences in demographics and disease burden, patients who use mail order have a greater likelihood of being adherent than patients who use a retail pharmacy.

Am J Manag Care. 2013;19(10):798-804
The dispensing channel is an important contributor to improving maintenance medication adherence among patients. Given that patients’ prior adherence behavior might confound the relationship between channel and adherence, it is important to control for this effect in any channel-adherence analysis.
  • Our study demonstrated that adherence is better with mail order than with retail pharmacies and is not just an artifact of increased days of supply.
  • Prior adherence behavior is an important confounder in channel-adherence studies, and our study provides a reasonable proxy measure based on pharmacy claims data to lessen the impact of this confounder.
Medication adherence, defined as taking medications as prescribed, is a key component in controlling disease progression and managing chronic illnesses.1,2 The clinical benefits of medication adherence have been well established in the scientific literature. Previous studies have indicated that medication adherence is associated with reducing disease morbidity,3 reducing healthcare resource utilization,4 decreasing hospitalization,5 improving effectiveness of treatment,6 and increasing likelihood of survival.7

In addition to worse health outcomes, medication nonadherence is linked to increased healthcare costs. Nonadherence across just  chronic therapy classes (antidiabetics, antihypertensives, and antihyperlipidemics) resulted in an estimated $105.8 billion in direct costs in the United States during 2010 alone.8 Nevertheless, this cost burden can be reduced. Previous studies have found that adherence rates of 80% or greater were associated with significant decreases in total medical costs for diabetes, hypertension, and high blood cholesterol.4

Studies have indicated that obtaining medication through the mail is one option for improved medication adherence.9-11 Compared with retail pharmacies, mail order has been touted as more cost-effective12 and convenient.13 In contrast, retail pharmacies are perceived to add value in terms of pharmacist face-to-face interaction.14-16 Proponents of mail order contend that medication  adherence is greater among patients who secure medications via mail order, while proponents of retail attribute any improved adherence to the increased days of supply per prescription in mail order.14

Many patients who intend to take their medications as prescribed fail to get medications refilled due to various factors such as inability to visit a pharmacy, their schedule, forgetfulness, or procrastination. Mail order provides a convenient and effective alternative for continued access to medications. Inadequate access17 and financial concerns18 are 2 factors identified as impediments to adherence.19 The impact of access and cost is reduced for many patients by the use of mail order, because  prescriptions are delivered to one’s home and the total patient out-of-pocket (OPP) costs are frequently less. Hence, we hypothesized that use of the mail order channel is associatedwith higher adherence rates than use of the retail channel.

A common limitation in adherence studies is the failure to control for underlying factors that affect adherence and selection of delivery channel. For example, it is quite possible that health-conscious individuals are more likely to have other healthy behaviors such as exercise, good diet, and preventive screenings. Hence, they may be more likely to engage proactively in activities that improve their adherence—sometimes referred to as the “healthy adherer” effect.20,21 Mail order generally provides more days of supply, regular refill reminders, and convenient reordering for members, mitigating the potential to procrastinate on medication refills, which can adversely affect adherence. Healthconscious individuals may choose the mail order channel to ensure continuity in their medication regimens. Thus, better medication adherence with mail order may reflect healthier patients’ predisposition to self-select the mail order option. To accurately attribute the impact of dispensing channel on adherence, it is important to control for bias from a patient’s predisposition to be adherent.

To our knowledge, previously published channel-adherence studies have not controlled for this potential confounder.13-15 A part of this effect, prior adherence behavior (PAB), can be controlled for by using a proxy measure—prior adherence, calculated based on pharmacy claims data. Also, most channel-adherence studies either have not fully controlled for differences in the days of supply between the 2 channels or have not taken patients’ choice of channel into account. This study aims to address the aforementioned biases and limitations, and tease out the effect of dispensing channel on adherence to medications to treat diabetes, hypertension, and high blood cholesterol.


Study Population

This study used prescription claims data from a nationally representative sample of commercially insured members whose pharmacy benefits were managed by a large pharmacy benefit management company. Inclusion was limited to patients who were continuously enrolled for pharmacy benefits from April 1, 2009, until December 31, 2011, who were between the ages of 18 and 64 years, and who had any prescription claim for antidiabetics, antihypertensives, or antihyperlipidemics during the index period, which was from October 1, 2009, to December 31, 2009. Patients whose pharmacy benefit design required the use of mail order exclusively for maintenance medications or did not allow access to mail order (mandatory retail) at any time during the entire study period were excluded from analysis. That is, only those patients who were free to choose either channel at any time during the study to fill their maintenance prescriptions were selected. Under provisions of the Health Insurance Portability and Accountability Act of 1996, all data specific to individual patients were removed to maintain the privacy of protected health information from internal analytical data sets. All prescription claims were adjusted to 30-day equivalents.

Research Design

A retrospective claims analysis over a 3-year period divided into 4 distinct phases (Figure) was conducted. A 6-month look-back period from April to September 2009 was used to assess whether the patients were new or continuing users of the medications identified. Patients having a claim within  the same therapy class under study in the look-back period were categorized as continuing users and those without claims as new users. This indicator attempted to capture any differences in adherence that resulted from the longevity of treatment. The analysis period for this study was from January 1, 2011, to December 31, 2011. As previous adherence may be indicative of a health-conscious personality and a measure of  better health-seeking behavior,22 a patient’s prior adherence was used as a proxy control for self-selection bias due to the PAB effect in the multivariate model. Prior adherence was based on the patient’s medication possession ratio (MPR) in the year 2010, termed as the baseline period.

Study Variables

The primary outcome measure was patient adherence to diabetes, hypertension, or high blood cholesterol medications, defined as an MPR of 80% or greater23 in the analysis period. Patients’ MPR was calculated as the total days of supply divided by 365 days, capping it at 100%. At the drug group level, the combination of 8-digit Generic Product Identifier (GPI) codes and clinically appropriate drug groups was used to calculate the MPR, which then was averaged to the therapy class level for each patient (eAppendix A, available at Drug groups were based on clinically accepted drug subclasses within each therapy class. Only the numbers of medication units actually meant to be taken during the study periods were included in calculations. That is, the parts of any claim that  were in possession before the key periods (2010 for baseline and 2011 for analysis) and any excess in possession after the ends of the periods were excluded from the adherence calculations.

Based on a literature review, independent variables to be included in the model were identified. In addition to dispensing channel, other independent variables included prior adherence, age, sex, OOP costs for 30-day adjusted prescriptions, disease burden, severity of illness, location (urbanicity) of the patient, and average days of supply per claim. Channel was assigned to individuals based on where they obtained at least two-thirds (66.7%) of their 30-day adjusted prescriptions. Those who did not receive at least 66.7% of their 30-day adjusted prescriptions from either mail order or retail were assigned to a mixed channel group. Prior adherence was included in the model to control for the PAB effect, as past health behavior has been known to be a good marker for predicting future health behavior.24 A similar method was used in a 2011 study examining the association between statin use and outcomes that used prior adherence to control for the healthy-adherer effect.22 The MPR for 2010 was calculated for each patient to establish prior adherence, and patients with an MPR of 80% or greater were classified as adherent.13,23,25

Patient demographics have been known to be significant confounders in assessing the relationship between dispensing channel and medication adherence.26 Age as of December 31, 2009, was used in the analysis. The OOP costs for 30-day adjusted prescriptions were calculated by dividing total OOP pharmacy costs (for each therapeutic class) for the patient in 2011 by that patient’s total number of 30-day adjusted prescriptions. In addition, proxy covariates controlled for patient disease burden and severity of illness. A patient’s overall disease burden was defined as the number of unique 2-digit GPIs, which indicate drug therapy classes used by the patient. The number of unique drug groups for which the patient had a prescription claim in 2011 defined severity of illness for diabetes and hypertension. For high blood cholesterol, only adherence to statins was analyzed and hence involved only 1 drug group. The location variable (urbanicity) was based on the core-based statistical area used by the US Census Bureau to ascertain the urban core of metropolitan and micropolitan statistical areas.27 Average days of supply per claim were used to control for the differences in days of supply of prescriptions between retail and mail order channels. The adherence rate was defined as the percentage of patients in each cohort (mail order/retail/mixed) who had an MPR of 80% or greater over the study period.


From a random sample of 4 million members, 109,794 diabetes patients, 467,054 hypertension patients, and 296,594 high blood cholesterol patients were identified between October and December 2009. eAppendix B (available at presents the sample selection methodology for the study, which resulted in final analytical samples of data for 37,639 diabetes, 152,819 hypertension, and 103,333 high blood cholesterol patients.

Descriptive statistics were estimated and bivariate differences between groups were tested using analysis of variance for all continuous variables and x2 tests for categorical variables. Multivariate logistic regression analyses were performed to estimate the association of aforementioned covariates with the odds of being adherent. In order to address the suggestion that better adherence with mail order is an artifact of more days of supply,15 average days of supply per claim was used as a proxy measure.

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