Costs of Medication Nonadherence in Patients with
Diabetes Mellitus:A Systematic Review and Critical
Analysis of the Literaturevhe_539915..922
Maribel Salas, MD, DSc, MSc,1Dyfrig Hughes, MSc, PhD, MRPharmS,2Alvaro Zuluaga, MD,3
Kawitha Vardeva, MSc,4Maximilian Lebmeier, MSc5
1Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham,AL, USA;2Centre for Economics and Policy in Health,
Bangor University, Bangor, UK;3University of Alabama at Birmingham, Birmingham,AL, USA;4Amgen, Cambridge, UK;5Wyeth in Taplow,
Objectives: Information on the health care costs associated with nonad-
herence to treatments for diabetes is both limited and inconsistent. We
reviewed and critically appraised the literature to identify the main meth-
odological issues that might explain differences among reports in the
relationship of nonadherence and costs in patients with diabetes.
Methods: Two investigators reviewed Medline, EMBASE, Cochrane
library and CINAHL and studies with information on costs by level of
adherence in patients with diabetes published between January 1, 1997
and September 30th 2007 were included.
Results: A total of 209 studies were identified and ten fulfilled the inclu-
sion criteria. All included studies analyzed claims data and 70% were
based on non-Medicaid and non-Medicare databases. Low medication
possession ratios were associated with higher costs. Important differences
were found in the ICD-9/ICD-9 CM codes used to identify patients and
their diagnoses, data sources, analytic window period, definitions of
adherence measures, skewness in cost data and associated statistical issues,
adjustment of costs for inflation, adjustment for confounders, clinical
outcomes and costs.
Conclusions: Important variation among cost estimates was evident, even
within studies of the same population. Readers should be cautious when
comparing estimated coefficients from various studies because method-
ological issues might explain differences in the results of costs of nonad-
herence in diabetes. This is particularly important when estimates are used
as inputs to pharmacoeconomic models.
Keywords: costs, diabetes, economics, medication adherence, medication
Nonadherence has a significant impact on the cost-effectiveness
of pharmaceuticals , and has been estimated to cost the US
economy up to $100 billion per year . In diabetes, nonadher-
ence to oral hypoglycemic medications [3,4] may partly explain
why only 43% of patients with diabetes mellitus have glycosy-
lated hemoglobin (HbA1c) below the 7% level [5,6] recom-
mended by the American Diabetes Association .
Studies of adherence in diabetes have focused on its eco-
nomic burden [8–10], its complications [11,12] and the cost-
effectiveness of antidiabetic drugs [13–18]. Many have reported
wide variation in the percent of patients being “nonadherent,”
ranging from 13% to 64% for oral agents and from 19% to 46%
for users of insulin [19–21]. Additionally, important variations in
the coefficient estimations for costs have been reported [21,22],
which might be related to differences in the design, population,
variables included in the analysis and statistical analyses. There-
fore, we reviewed and critically appraised the literature to iden-
tify the main methodological issues that might explain differences
among reports in the relationship of nonadherence and costs in
patients with diabetes.
We conducted a systematic literature review using Medline,
EMBASE, Cochrane Library, and the Cumulative Index to
Nursing and Allied Health Literature (CINAHL) from January 1,
1997 to September, 30 2007.
The key terms used included: (compliance, adherence, persis-
tence, nonadherence, concordance) AND (economics, costs,
value, expenditures, resource utilization) AND (diabetes, hyper-
glycemia, diabetes-related complications, antidiabetic medica-
tions, insulin, oral hypoglycemic agents). We also hand-searched
medical journals and reviewed the reference lists of other
Studies that reported costs by different levels of medication
adherence or persistence were included. Adherence and persis-
tence definitions were according to previous studies . We also
included studies that used HbA1c as a proxy of medication
adherence because HbA1c is a well-established measure of gly-
cemic control [22,24,25] and a proxy for adherence . Non-
English studies, articles with insufficient data, and those without
costs or adherence information were excluded.
Abstracts and full publications were reviewed by two researchers
and disagreements were resolved by consensus. The extracted
information included the study design, data source(s), methods
of adherence measurement, statistical analysis, and results. Study
designs were classified as trials, cohort, case-control, or cross-
sectional studies. Data sources for patient demographics, adher-
ence, resource utilization, and costs, as well as observation and
follow-up periods, were recorded (Table 1). For statistical analy-
sis, we included information on any statistical method used
to assess the relationship or association between medication
Address correspondence to: Maribel Salas, University of Alabama at Bir-
mingham, 1530 3rd Avenue South MT 644, Birmingham, AL 35294-
4410, USA. E-mail: email@example.com
Volume 12 • Number 6 • 2009
V A L U E I NH E A LT H
© 2009, International Society for Pharmacoeconomics and Outcomes Research (ISPOR)1098-3015/09/915915–922
Studies identified with costs reported by adherence level in diabetic patients
Source of data
Medicare HMO inNorth Carolina
ICD-9 codes 250.xx
Reimbursement by the
Patients aged ?65 years, enrolled in a Medicare HMO
in North Carolina who received ?1 antidiabetic
prescription dispensed every 6 months
Up to 5 years
Cobden D, 2007
ICD-9 CM code
type 1 subcodes
Payments made by
third-party payers to
health care providers
?18 years, type 2 diabetes who converted to BIAsp
70/30 pen device and previously treated with human
or analog insulin
January 1, 2001 to
April 30, 2005
At least 2 years
North Carolina Medicaid program
Type 2 diabetes who were newly started on
thiazolidinedione therapy or other oral antidiabetic
July 2001 to June
Blue Cross Blue
Shield of Michigan
ICD-9 250, 352.2,
362, 366.41, 648
Non-Medicare eligible Michigan residents enrolled
continuously in 1999, at least 1 inpatient or
Emergency room claim, ?2 professional or outpatient
facility claims with diabetes diagnosis and a filled
prescription for antidiabetic drug.
Lee WC, 2006
pre and post
and pharmacy claims
ICD-9 code 250.xx
excluding type 1
Payments to the health
?18 years of age, type 2 diabetes who initiated
treatment with insulin analogue pen device between
July 1, 2001 and Dec 31, 2002, and whose treatment
was converted from conventional human or analogue
insulin injection (vial/syringe) to a prefilled insulin
Up to 4 years
North CarolinaMedicaid database
ICD-9 CM code
Total health care costs:
medical and dental care,
regular checkups, office
visits, home health care,
inpatient and outpatient
care, long term care
facility care and
At least one ICD9 code for diabetes, and one for
antidiabetic medication and Medicaid eligibility for
36-month follow-up period.African Americans were
analyzed vs. other
July 1, 2000 to June
Sokol MC, 2005
maintained by a
ICD-9 codes 250.xx,
357.2, 362.0x,366.41, 648.0
All-cause costs and
Patients aged 65 and older with diagnosis of diabetes
June 1997 to May
registry from the
Puget Sound, Seattle
diabetes and HbA1c
Decision support system
that is automated,
accounting for health
care provided to
Diabetics older than 18 years, with at least one
HBA1c, and continuously enrolled from 1992–1996
January 1, 1992 to
March 31, 1996
ICD-9 for type 2
Patients receiving an oral antidiabetic medication and
have a diagnosis of CVD, continuously enrolled in thehealth plan, and ?30 years of age
April 1, 1998 to
March 31, 2000
Shetty S, 2005
US Managed care
ICD-9 CM codes
250.x0 or 250.x2
Had ?2 claims for type 2 diabetes in either the
primary or secondary position, had at leas oneprescription for an oral hypoglycemic agent and/or
insulin, had at least one available HbA1c, were
commercially insured with a drug benefit, and had at
least 6 months of continuous enrollment.
CVD, cardiovascular disease; HMO, Health Maintenance Organization; ICD-9, International Classification of Diseases, 9th Revision; ICD-9 CM, International Classification of Diseases Clinical Modification. HbA1c, glycosylated hemoglobin.
Salas et al.
nonadherence and costs, sample size, adjustment for inflation
and/or discounting, adjustment for confounders or for the days
when patients were in institutionalized care settings such as
hospital, and nursing home (Table 2).
A checklist for economic evaluation  was modified to assess
the quality of studies. The original checklist contained 35 items,
but 5 of them were related to health economic models (12, 14 15,
20, and 21), and were not considered applicable to the studies
included in the review. We assigned a score of 1 if an article
included the required item, and zero if it was not included.
Therefore, the maximum score for an article that included all
information related to study design, data collection, analysis and
interpretation of results was 30.
Two hundred nine titles were identified and their abstracts were
reviewed. Fifty abstracts included information on both adherence
and costs in patients with diabetes, and their full articles were
retrieved. Ten studies [17,28–36] fulfilled the inclusion criteria
(Fig. 1). All studies analyzed US claims data using retrospective
cohort studies designs [17,28–36] (Table 1). Three studies
utilized Medicare or Medicaid databases [28,30,32], while
all others used commercial or managed care organizations data
Association between Medication Nonadherence
There were important variations in the items included in order to
estimate costs. For example, one study included only claims for
physician office visits, outpatient services, and hospital stays ,
while another was more comprehensive, and included: costs
for hospitalization, outpatient care, emergency care, clinic visits,
laboratory tests, professional services, and pharmaceuticals .
Two studies took into account the net cost to the plan but they
did not include patients’ copayments and deductibles [33,35],
while a third study included copayments and deductibles .
The study by Wagner used its own internal accounting system
that included overhead costs . It was unclear in some studies
as to which specific costs were included [17,28,32].
Low medication possession ratios (MPRs) were generally
associated with higher costs. For example, one study reported an
association of MPR of 60% with mean total costs of $8699 .
Balkrishnan et al. found that a 10% increase in MPR for an
antidiabetic medication was associated with an 8.6% reduction
in total annual health care costs . Studies generally reported
increments of mean annual costs according to baseline HbA1c
values. For example, the mean annual costs for patients with
baseline HbA1c < 8% were $4475, while for those with
HbA1c > 10 were $8088  (Table 2).
The specific International Classification of Diseases (ICD-9) or
ICD-9 Clinical Modification (ICD-9-CM) codes used to identify
the study population were not mentioned in three studies
[30,34,35], and among those that were reported, there were
important variations in the codes included (Tables 1 and 2). For
example, some studies included type 1 and type 2 diabetes
[28,31,33], while others excluded type 1 diabetes [17,29,36].
The population varied by study, as well by period of observation.
The maximum follow-up was 5 years, and half of the studies
followed patients for only 1 year.
Table 2 presents measures of adherence, costs, statistical
analysis, results of each study, and quality score. All studies used
claims data to collect drug utilization information. Five studies
used MPR as a measure of medication adherence [17,28–30,32],
two studies did not report a specific medication adherence
measure [34,36], and three used various measures of medication
adherence such as medication adherence rate , percentage
days supplies , and percentage of adherence . All studies
used the total follow-up period to calculate adherence and costs,
and used charges as proxy for costs. In terms of type of costs,
some studies reported total health-care costs [17,28–30,34–36],
while others focused on overall costs of health care , or costs
related with diabetes care [32,33]. Two studies used Poisson
regression models for costs [17,29], and the remainder used
multivariate regression analysis for costs. Few studies log-
transformed costs [32,34,36], and only one study  tried to
deal with the skewed distribution of both health-care costs and
MPRs. Seven studies were able to adjust for some potential
confounders [17,28,29,31–33,36], while only one adjusted costs
for inflation and duration of hospitalizations . Most studies
were assigned a low quality score (<50% of required informa-
tion), ranging from 8/30 to 14/30.
We identified various methodological issues that hinder compari-
sons from being made across studies, and which might result in
significant differences in the reported associations between non-
adherence to medicines and costs in patients with diabetes.
Based on the International Society for Pharmacoeconomics
and Outcomes Research (ISPOR) recommendations on improv-
ing the quality of adherence studies [37,38], we found that the
type of study design was not clearly established, and studies were
unable to distinguish prevalent from incident cases. Incident
cases are more expensive than prevalent cases in terms of hospi-
talization rates, length of stay, case mix, and service intensity, and
have higher discontinuation rates [39–41]. Studies included dif-
ferent population groups, which has an impact on costs: some
focused on codes for type 2 diabetes only, type 1 and type 2,
gestational diabetes, and/or diabetes-related complications. For
example, gestational diabetes is more expensive than type 2
diabetes because of the frequency and duration of hospitaliza-
tions . None of the studies described if primary, secondary, or
both codes were used. Previous studies have shown an increase in
costs by up to twofold when both primary and secondary ICD-9
codes were used .
Contrary to accepted recommendations, none of the studies
validated ICD-9/ICD-9-CM codes . Wilchesky et al. showed
64% sensitivity of claims data to detect patients with diabetes
, which means that an appreciable number of cases may be
missed. Similarly, none of the studies validated prescription
claims data that are vulnerable to errors from sampling, misiden-
tification of newly treated patients, and misclassification of
added versus switched medications [45,46]. ICD-9/ICD-9-CM
codes to measure utilization and costs also requires validation,
because some studies have found that 9% of discharges incor-
rectly omit codes for diabetes, and 13% of discharges are regis-
tered without any foot-related diagnosis code .
Most studies used medication possession ratios, but there
were important variation in the definition. For some, MPR was
the sum of days of antidiabetic prescription supply dispensed
divided by the number of days between prescription refills, from
the first date of dispensing within each year until the dispensing
Costs of Nonadherence in Diabetes Mellitus
Continuation of studies identified with costs reported by adherence level in diabetic patients
in the health
or other location
MPR defined as the days of
supply dispensed divided by
the number of days between
observation period began
with the first date of
dispensing within each year
and ended as the dispensing
date of the last prescription
data of the HMO
Total costs not specified
and regression analysis
Charlson index was
used to adjust by
Number of days during
subtracted from the
MPR for 1 to 5 years of follow
up were 0.70, 0.71, 0.75, 0.77, and0.78; and mean health care costs
were $8,306, $5,947, $5,821,
10% increase in antidiabetic MPR
was associated with an 8.6%
decrease in total annual health
care costs (P < 0.001). After 5
years, high adherence = $4,000
while low adherence = $10,500
MPR: sum of the days’ supply
of drug divided by the
number of days between the first fill and the last refillplus the days’ supply of the
visits, pharmacy data
Total health care costs,
annual adjusted meanall-cause health care
inflation to 2005 dollars
adjusted by length of
regression model and
MPR of 80% or greater was
associated with significant
reduction in all-cause health care
costs (OR 0.55, 95% CI
0.31–0.80, P < 0.05). MPR of 68%
was associated with total mean
costs of $8,056 ? 8,559, while an
MPR of 59% had total mean costs
of $8,699 ? 9,268.
Total annual health care
13% increase in MPR was
associated with 16.1% lower totalannual health care costs
(P < 0.001).
Medication adherence rate
calculated as percentage of
days that the patient
possessed any available
diabetic drug during the year
emergency care, clinic
visits, laboratory tests,
Overall cost of
healthcare and cost
related with diabetes
regression model and
Illness severity using
diagnosis cost group.
20% to 39% adherence level wasneeded before medical care costs
were reduced. For diabetes
related costs, the threshold was
seen until 40% to 59% adherence
0% = $6,500,
1–19% = $7,250,
20–39% = $7,750,
40%–59% = $7,500,
60%–79% = $7,700,
80%–99% = $7,300,
100% = $7,900.
Lee WC, 2006
MPR: sum of the days’ supply
of medication divided by the
number of days between thefirst fill and the last refillplus the days’ supply of the
Total health care costs/
Costs adjusted to 2005
dollars using the
consumer price index
models and incident
at least 6
the index date
and at least 2
62% MPR to insulin pen
therapy = mean annual all-cause
health care costs $14,769
Salas et al.
RA, 2006 
MPR: Number of days of
supply dispensed (e.g., a
30-day supply) divided by thenumber of days between the first and last dispensation.
Med-Total approach: ratio of
total number of days the
drug was supplied to the difference in the number ofdays between the first and
last prescription dates.
Medical and dental care,
in patient and
outpatient care, regular
checkups, office visits,
home health care,
long-term facility care
and prescription drugs.
Annual total and
analysis adjusted by
covariates. Costs were
logarithm and they
were transformed back
using antilogarithms of
the parameter estimate
Mean rate of adherence to new
medication of 59% = $9,546 ?
$14,861 mean total health care
costs for year 2 and mean
diabetes-related costs for year 2
of $4,576 ? $8,208;The
estimated coefficients and
standard errors for total annual
health care cots as a function of
covariates were: male sex
1,117.35 ? 1,001.69, high total
number of prescriptions8,223.48 ? 1,002.38;African
American race 1,125.49 ? 914.39;
rate of adherence—2,721.68
(932.50), constant 728.82 (1,180.29) and adjusted r2 = 0.06.
Percentage of days during
the analysis period that
patients had a supply of 1 or
more maintenancemedications for the
Medical and drug
ER service, outpatient
physician office visits
and outpatient visits.
Nursing home and
home care services
were not included
Total health care costs
(Sum of medical—
outpatient services, ER
and drug costs), and
Net cost to the plan
deductibles were not
Costs were adjusted for
age, sex, comorbidity,
employment group and
medical plan type.
model. No detail for
included in the
Adherence level and total costs:
1–19% = $8,867; 20–39% =
$7,124; 40–59% = $6,522;
60–79% = $6,291; 80–100% =
$4,570. Differences were
statistically significant for most
adherence levels when compared
with the highest level of
adherence (P < 0.05).
Not included a measure of
adherence and HbA1c was
used as a proxy of
Annual utilization rates
Total health care costs
and mean costs per
Baseline HbA1c, Level, % and
mean annual costs$, (p values
were calculated for the difference
in log costs)
<8 = $4,475 (P = 0.18);
8–10 = $5,898 (P = 0.32);
>10 = $8,088 (P = 0.53)
Percentage of adherence
Hospitalization and ER
Patients with ?75, >75 to ?95
and 95% adherence, adjusted total
healthcare costs were $US 5,706,
$5,314 and $4,835 (P < 0.001).
Not included but HbA1c
was used as a proxy of
Costs of 6 months
transformation of cost
data was done prior
Adjustment by age,
gender, specialty of the
and total baseline costs.
Predicted total diabetes-related
cost for target HbA1c level group
during the first year of follow up
was $1,540 per patient, 32%
higher than the total diabetes
related cost ($1,171) for the
same target group (P < 0.001).
ER, emergency room; HMO, health maintenance organization; MPR, medication possession ratio; NR, not reported. HbA1c, glycosylated hemoglobin.
Costs of Nonadherence in Diabetes Mellitus
date of the last prescription [28,32]. Others added the days’
supply of the last refill to the denominator [17,29], or they used
the percentage of days that the patient possessed any available
diabetic drug during the year . None of the studies consid-
ered the effects of censoring, which is important, because six
filled prescriptions evaluated over 12 months equals an MPR of
50%, but if they are evaluated over 6 months, the six filled
prescriptions equals an MPR of 100%.
The non-MPR measures included were: Med-total approach
defined as the ratio of total number of days the drug was supplied
to the difference in the number of days between the first and last
prescription dates ; the percentage of days during the analysis
period that patients had a supply of one or more maintenance
medications for the condition , and the percentage of adher-
ence . The problem is that these measures are not compa-
rable. Hess  analyzed various adherence measures and found
that only 4—Continuous Measure of Medication Acquisition;
Continuous Multiple Interval Measure of Oversupply; MPR; and
Medication Refill Adherence—out of 11 measures were identical
for measuring adherence to prescription refills throughout the
With regard to confounders, 6 out of 10 studies made some
effort to adjust their estimates by disease severity, but most did
not adjust by comorbidities, thereby potentially underestimating
the real costs. None of the databases used by analysts contain
information of behavioral variables such as smoking and alcohol
that are closely related to adherence [49–53]. There was also lack
of information on adverse drug events, such as hypoglycemia,
which has been shown to be a costly component of diabetes-
related treatment . None of the studies were able to measure
the direct consequences of either nonadherence (e.g., hyperosmo-
lar coma) or associated utilization-based outcomes. Costs were,
therefore, not disaggregated according to the main drivers
that are a consequence of loss of therapeutic effect through
All studies used charges as proxy for costs. However, charges
have been criticized because they do not reflect real costs ,
and they do not take into account the various levels of copay-
ment, deductibles, and coinsurance for prescriptions and other
medical services, including physician office care, medical emer-
gency care, and inpatient hospitalization.
Only one study tried to deal with skewed distribution of
health-care costs and MPR . This is important, because inap-
propriate analysis of costs will produce biased estimates for the
mean. For costs, nonparametric bootstrap techniques or GLM
regression analyses are recommended [56,57].
The research assessing the association between medication
adherence/nonadherence and health-care costs is limited and of
poor quality. There are important methodological differences
among studies of costs of adherence/nonadherence in patients
with diabetes, making robust comparisons difficult; and those
differences might explain the inconsistency in the reported
associations between medication adherence and costs. Readers
should be cautious when interpreting or comparing the results of
such studies. More research is needed to validate measures of
medication adherence using claims data and to determine the
impact of nonadherence on health-care costs.
This article is written by members of the International Society for
Pharmacoeconomics & Outcomes Research (ISPOR) Economics
of Medication Compliance Working Group; part of the Medica-
tion Compliance and Persistence Special Interest Group.
Source of financial support: None.
Supporting information for this article can be found at: http://
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Titles related to diabetes =
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costs = 85,252
Identified abstracts= 209
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Non-English language = 2
Not directly related to
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