Drug Trends
Adherence Trends for 3 Chronic Disease
Medication Classes Among
Differently Insured Populations
Sara C. Erickson, PharmD; R. Scott Leslie, MPH; Wenyi Qiu, MS; and Bimal V. Patel, PharmD, MS
C
ardiovascular disease is the leading cause of
death in the United States.1 By 2030, the prevalence of cardiovascular diseases, including hypertension, is projected to reach more than 40% of US
adults and cost the United States $1.1 trillion annually
(unadjusted 2008 dollars).2 Hypertension, dyslipidemia,
and diabetes mellitus are key risk factors for cardiovascular disease and cardiovascular events. Several observational studies have demonstrated that adherence to
medications indicated for the treatment of hypertension,
diabetes mellitus, or dyslipidemia is associated with better cardiovascular outcomes, decreased cardiovascularrelated and all-cause hospitalizations and emergency
department visits, and lower total healthcare costs.3-8 Although the validity of these results has been called into
question by demonstration of the “healthy user bias,”9,10
it stands to reason that for a drug to be effective, it needs
to be taken regularly. Furthermore, adherence to oral
antidiabetic drugs (OADs), antihypertensives, and HMGCoA reductase inhibitors (statins) has been shown to be
associated with the cardiovascular intermediate outcomes
of lower glycosylated hemoglobin, blood pressure, and
low-density lipoprotein cholesterol levels.11,12
Medication adherence is defined as “the extent to
which a patient acts in accordance with the prescribed
interval and dose of a dosing regimen.”13 Payers with
large claims databases measure patient adherence with
“medication possession” methodologies that use prescription fill dates and days’ supply. These methodologies
are based on the number of days a patient has possession
of medication rather than if the patient has actually taken
the medication. The most commonly used measure in the
literature is the Medication Possession Ratio (MPR).14,15
There are many variations of MPR used in the literature;
however, MPR is generally calculated as the sum of the
days’ supply of medication available in a given period
of time divided by the sum of the number of days in
the period or the time between the first and last fill of
medication.14,15 The latter denominator may inflate adherence measurements as it does not consider potential
32 The American Journal of Pharmacy Benefits • January/February 2014
discontinuation of chronic therapy.15,16 Also, when shorter
observation periods are used, the likelihood of adherence is increased.15
The Pharmacy Quality Alliance (PQA) developed
and tested a medication possession adherence measure
known as the Proportion of Days Covered (PDC) in several chronic medication classes and concluded that it is
to be preferred over MPR methodologies.17 PDC is calculated as the number of days within the calendar year
with medication supply divided by the number of days
the patient is eligible for benefits. If fills overlap, the start
date of the next fill is adjusted to be the day after the
previous fill ended. Also, if patients have supply for more
than 1 medication within the measured class on the given
day, the day is only counted once as being “covered.”
Thus, the PDC provides a more conservative estimate of
adherence when there may be switching and concomitant therapy.17,18 Unfortunately, there are variations in
PDC methodology in the literature and PDC sometimes is
used as a misnomer for calculations consistent with MPR
methodology.15,19 The definition of 80% PDC or MPR as
a threshold for adherence is common in the literature.15
The PQA PDC methodology includes reporting the number of patients reaching 0.80 or greater PDC. While somewhat arbitrary, the 80% threshold for OAD, direct renin
inhibitors (DRIs), and statin adherence has been shown
to be predictive of clinical outcomes.20,21
Since the PQA endorsed a specific PDC methodology, there has been movement toward using it as the
“gold standard.” The National Quality Forum (NQF)
endorsed the PDC measure for 5 medication types in
2009.22 The Centers for Medicare & Medicaid Services
(CMS) adopted this methodology in 2010 for measurement of adherence to OADs, DRIs, and statins as part
of the Five-Star Ratings Quality Rating System.23 The
National Committee for Quality Assurance (NCQA) has
adopted PDC for adherence measures in the Healthcare
Effectiveness Data and Information Set (HEDIS),24 and
URAC—a healthcare accreditation agency—has adopted
the methodology as part of the mandatory performance
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Medication Adherence Trends
measures for pharmacy benefit management (PBM) and
health plan accreditations.25,26 Also, PDC will be included
in the battery of clinical quality measures for Qualified
Health Plans (QHPs) accreditation necessary for participation on the Health Insurance Exchanges initiated by
the Affordable Care Act.27,28
The inconsistency and variations in the use of MPR
and PDC in the literature encumbers the comparison of
adherence measurements in different medication classes
and in different patient populations when not conducted in the same study. Several studies have shown differences in the adherence to various chronic therapies
within the same population.5,7,11 Insurance type has been
shown to be a significant predictor of adherence,29 likely
because of the differences in demographic and clinical
characteristics of the patients eligible for each type of
benefit. It is of interest to compare adherence rates in
these disparate populations. To the authors’ knowledge,
such a comparative analysis does not exist. The objective
of this analysis is to compare adherence rates for 3 key
chronic medication categories in populations enrolled in
different insurance types using the PQA-endorsed PDC
methodology and to understand whether adherence may
be trending over time.
METHODS
A retrospective, cross-sectional analysis was performed
using de-identified data from a sample of participating
clients of MedImpact Healthcare Systems, Inc, a national
pharmacy benefits manager, during 2012 and 2013. Four
distinct cohorts were defined by type of insurance: commercial, Medicaid (a mix of Medicaid beneficiaries and
enrollees in programs for the indigent and other statefunded public programs), Medicare Part D beneficiaries
(a mix of Medicare Advantage Prescription Drug [MA-PD]
plans and Prescription Drug Plans [PDPs]), and selfinsured commercial health plans.
Within each insurance type, adherence was calculated
as the Proportion of Days Covered (PDC) for each target
medication class using specifications from the CMS Medicare 2014 Part C & D Star Rating Technical Notes (released
September 27, 2013) and Pharmacy Quality Alliance Technical Specifications.30,31 Specifically, for patients 18 years
and older with at least 2 claims for the target medication
class, PDC was measured from first claim in the measurement period (index date) to end of the measurement period or member disenrollment. Days of medication coverage
was calculated using fill dates and days of supply elements
of prescription claims within each patient’s measurement
period.32 Adherence was calculated for each cohort by
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using patients’ adherence rates while adjusting for length
of member enrollment, or member years. Member years
were calculated as number of months enrolled divided
by months eligible in each measurement period. Target
medication classes included OADs, DRIs, and statins—the
3 classes used in the CMS Part D Patient Safety measures.
Patients utilizing insulin during the measurement period
were excluded from the OAD measurement.
PDC and percent of patients meeting the definition
of adherence of PDC greater than or equal to 0.80 were
measured over the 2012 and 2013 calendar years as specified by PQA and CMS. We calculated these metrics for
rolling 1-year periods at the conclusion of each quarter to
observe possible temporal trends or seasonality. Analyses
were performed using SAS (Cary, North Carolina) version
9.3.
RESULTS
Patients enrolled in Medicare Part D demonstrated
greater adherence compared with the other insurance
types in all 3 measured medication classes (Figure 1). The
insurance types listed in order of decreasing observed adherence were Medicare Part D, commercial, self-insured
health plans, and lastly, Medicaid. This was consistent
across all medication classes. The percentage of Medicare
Part D patients meeting the threshold of PDC greater than
or equal to 0.80 ranged from 81.2% to 82.3% for OADs;
80.9% to 82.4% for DRIs; and 77.1% to 79.1% for statins.
Of patients enrolled in commercial plans, 77.5% to 78.7%
of patients were adherent to DRIs; 74.2% to 75.1% of
patients were adherent to OADs; and 72.1% to 73.8% of
patients were adherent to statins. The proportions of patients in self-insured plans who were adherent to therapy
were 70.5% to 72.5% for DRIs; 67.0% to 68.2% for OADs;
and 64.4% to 67.1% for statins. The Medicaid cohorts consistently had the smallest proportion of adherent patients
compared with other insurance types. The proportion of
adherent Medicaid patients ranged from 66.3% to 66.7%
for OADs; 60.6% to 62.1% for DRIs; and 57.2% to 58.6%
for statins. The proportion of adherent patients in the
commercial and Medicare Part D populations increased
from calendar year 2012 to calendar year 2013 for all 3
categories (Figure 2). The proportion of adherent patients
decreased between the 2012 and 2013 calendar years
for Medicaid beneficiaries. The self-insured commercial
population exhibited an increase in the proportion of
patients who were adherent to OADs, a decrease in the
proportion of patients who were adherent to DRIs, and
no change in the proportion of patients who were adherent to statins between the 2012 and 2013 calendar years.
Vol. 6, No. 1 • The American Journal of Pharmacy Benefits 33
■ Erickson • Leslie • Qiu • Patel
Figure 1. Percentage of Patients Meeting Threshold for Adherence (Proportion of Days Covered ≥80%)
A. Direct Renin Inhibitors
Commercial
Medicaid
Medicare Part D
Self-Insured
Percentage
100
90
80
70
60
50
Jan 2012-Dec 2012
Apr 2012-Mar 2013
Jul 2012-Jun 2013
Oct 2012-Sep 2013
Jan 2013-Dec 2013
B. Oral Antidiabetic Drugs
Commercial
Medicaid
Medicare Part D
Self-Insured
Percentage
100
90
80
70
60
50
Jan 2012-Dec 2012
Apr 2012-Mar 2013
Jul 2012-Jun 2013
Oct 2012-Sep 2013
Jan 2013-Dec 2013
C. Statins
Commercial
Medicaid
Medicare Part D
Self-Insured
100
Percentage
90
80
70
60
50
Jan 2012-Dec 2012
Apr 2012-Mar 2013
Jul 2012-Jun 2013
DISCUSSION
This analysis observed the greatest adherence in a
Medicare Part D population, followed by commercial,
self-insured health plans, and then Medicaid populations. Although copays are typically lowest for Medicaid
patients, the lower prevalence of adherent patients is
not unexpected, given the characteristics of the eligible
beneficiaries. The Medicaid population has a greater
34 The American Journal of Pharmacy Benefits • January/February 2014
Oct 2012-Sep 2013
Jan 2013-Dec 2013
prevalence of chronic diseases, mental disorders, and
higher utilization of acute care services compared with
commercial populations.33 In addition to greater disease
burden, Medicaid patients are recipients of lower quality
of care, similar to the uninsured.34,35
Higher rates observed among Part D beneficiaries
are likely impacted by the Five-Star Quality Rating System that rewards health plans for increases in quality
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Medication Adherence Trends
Figure 2. Change in Percentage of Patients Meeting Threshold of Adherence CY2012 to CY2013
DRIs
Statins
OADs
1.4
1.3%
1.2%
1.2
1.0%
1.0
0.9%
0.9%
Percentage
0.8
0.6%
0.6
0.3%
0.4
0.2
0.0%
0.0
–0.2
–0.1%
–0.1%
–0.4
–0.6
–0.4%
–0.5%
–0.8
Commercial
Medicaid
Medicare Part D
Self-Insured
CY2012 indicates calendar year 2012; CY2013, calendar year 2013; DRI, direct renin inhibitor; OAD, oral antidiabetic agent.
Table. Patient Counts, Proportion Female, and Proportion of Days Covered for Each Cohort During January 1, 2013,
Through December 31, 2013, Measurement Period
DRI
Patient count (n)
Female (%)
PDC
Statins
Patient count (n)
Female (%)
PDC
OAD
Patient count (n)
Female (%)
PDC
Commercial
Medicaid
Medicare Part D
Self-Insured
Health Plans
507,549
145,356
190,719
173,168
55.1
56.0
48.2
44.2
0.78
503,167
43.8
0.61
47.7
0.71
123,592
195,443
146,451
57.0
54.9
46.3
0.73
180,288
0.82
0.57
0.79
0.65
85,581
78,777
67,612
59.4
52.6
51.8
0.75
0.67
0.82
0.67
DRI indicates direct renin inhibitor; OAD, oral antidiabetic agent; and PDC, Proportion of Days Covered.
performance. The observed high adherence in Medicare
Part D is also consistent with our understanding that adherence improves with age. Increasing age is a significant
predictor of the increased likelihood of being adherent to
statins, antihypertensives, and antidiabetics.36-41 However,
adherence to these medication classes has been shown
to increase with age only up to a certain point, with the
“younger old” being more adherent.42-46 Older age is associated with more comprehension errors, inconsistent
preferences, and decreases in working memory that
are associated with decreased adherence.47,48 Therefore,
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a younger Medicare Part D population would be more
likely to have a higher proportion of adherent patients
compared with an older one. Our observations may not
be representative of the nation’s Medicare Part D population, as MedImpact’s Medicare population contains 21%
low-income subsidized eligible patients compared with
34% of Part D beneficiaries nationwide.49
We observed the least adherence and the smallest
proportion of adherent patients with the statin medication class (Table, Figure 1). This is consistent with other
observational studies examining diabetes, hypertension,
Vol. 6, No. 1 • The American Journal of Pharmacy Benefits 35
■ Erickson • Leslie • Qiu • Patel
and dyslipidemia medication adherence.29,50,51 A limitation of the PDC methodology is the possibility of inflation when combination therapy is used. For example, a
patient prescribed dual OAD therapy who is adherent
to 1 OAD (eg, glipizide) and not adherent to the other
(eg, metformin) will be classified as adherent. Since PDC
methodology requires supply of only 1 medication on
each given day, multi-drug regimens, as is common with
OAD, provide more opportunities to be adherent compared with monotherapy, as is the case with statins. The
decreased prevalence of adherence to statins compared
with DRIs may reflect a greater prevalence of intolerance
or negative patient beliefs, such as concerns regarding
possible side effects. Patient beliefs of lower perceived
risk of myocardial infarction, expected short treatment
duration, and concern about potential harm from statins
have been shown to be negative predictors of statin
adherence.38
The generalizability of these observations to other
populations may be limited due to the complex nature
of adherence. Adherence is impacted by many factors
not previously mentioned or described here, such as
gender,36,42 ethnicity,36-38,41,52 comorbities,37,39,41 pharmacy
type,37 and level of cost sharing.42,53-56 However, this
study selected data from a large geographically diverse
population.
CONCLUSIONS
Using the CMS-adopted PDC adherence methodology,
adherence rates differ by insurance type. Medicare Part
D and commercial plans have a greater proportion of patients who are adherent to the major chronic therapies for
diabetes, hypertension, and dyslipidemia compared with
Medicaid and self-insured health plans. OAD and DRI
adherence measurements were greater than adherence to
statins for all insurance types. Measurements were stable
over time, with commercial and Medicare Part D populations showing improvements from 2012 to 2013. The
measurements indicate that many patients are nonadherent to these medication categories. Health plan sponsors
should start or continue to increase promotion of intervention efforts aimed at improving medication adherence
and health outcomes.
Author Affiliations: Health Outcomes Research (SCE, RSL, WQ,
BVP), MedImpact Healthcare Systems, Inc, San Diego, CA.
Funding source: None reported.
Author Disclosures: The authors (SCE, RSL, WQ, BVP) report no
relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article. The content is solely
the responsibility of the authors and does not necessarily represent the
official views of MedImpact Healthcare Systems, Inc.
36 The American Journal of Pharmacy Benefits • January/February 2014
Authorship Information: Concept and design (SCE, WQ, BVP);
acquisition of data (WQ, RSL); analysis and interpretation of data (SCE,
WQ, RSL, BVP); drafting of the manuscript (SCE, RSL); critical revision of
the manuscript for important intellectual content (SCE, RSL, BVP); statistical analysis (WQ); administrative, technical, or logistic support (BVP);
supervision (BVP).
Address correspondence to: Sara C. Erickson, PharmD, Health
Outcomes Researcher, 10181 Scripps Gateway Ct, San Diego, CA 92131.
E-mail: sara.erickson@medimpact.com.
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