Published Ahead of Print on January 2, 2008, as 10.2105/AJPH.2007.114249
Characteristics of Recipients of Free Prescription Drug Samples: A Nationally Representative Analysis
| Sarah L. Cutrona, MD, MPH, Steffie Woolhandler, MD, MPH, Karen E. Lasser, MD, MPH, David H. Bor, MD, Danny McCormick, MD, MPH, and David
Free prescription drug samples are used widely
Objectives. Free prescription drug samples are used widely in the United States.
in the United States. The retail value of drug
We sought to examine characteristics of free drug sample recipients nationwide.
samples distributed in the United States totaled
Methods. We analyzed data on 32 681 US residents from the 2003 Medical Ex-
more than $4.9 billion in 1996 and climbed to
penditure Panel Survey (MEPS), a nationally representative survey.
Results. In 2003, 12% of Americans received at least 1 free sample. A higher pro-
Controversy surrounds the use of free sam-
portion of persons who had continuous health insurance received a free sample
ples.4 Studies have described potential safety
(12.9%) than did persons who were uninsured for part or all of the year (9.9%;P < .001). The poorest third of respondents were less likely to receive free samples
problems,5,6 health professionals who divert
than were those with incomes at 400% of the federal poverty level or more. After
samples for self-administration or resale,7–10
we controlled for demographic factors, we found that neither insurance status nor
the influence of pharmaceutical representa-
income were predictors of the receipt of drug samples. Persons who were unin-
tives who distribute samples,11–13 and the con-
sured all or part of the year were no more likely to receive free samples (odds ratio
tribution of samples to rising drug and health
[OR]=0.98; 95% confidence interval [CI]=0.087, 1.11) than were those continuously
insurance costs.14–16 In addition, numerous
studies suggest that free samples may influ-
Conclusions. Poor and uninsured Americans are less likely than are wealthy or
ence the prescribing behavior of physicians
insured Americans to receive free drug samples. (Am J Public Health. 2008;98:
and trainees.7,14,16–22 In its most recent report,
the Institute of Medicine has called for furtherinvestigation of sample use, citing concernsover patient safety, provider prescribing hab-
Component. MEPS is a nationally representa-
its, and consumer adherence to prescribed
tive longitudinal survey of the civilian nonin-
participants to name all filled prescriptions re-
stitutionalized US population. The MEPS co-
ceived in conjunction with a hospital discharge,
Nonetheless, many physicians believe that
emergency department visit, or medical outpa-
samples allow them to give free medications
previous year’s National Health Interview
tient visit. Surveyors then ask respondents to
to their neediest patients.10,15 This view is also
Survey, conducted by the National Center for
name any medications purchased or received
Health Statistics at the Centers for Disease
that have not already been listed. The sur-
Manufacturers of America, whose vice presi-
Control and Prevention. The National Health
veyor then asked: “Since [the last interview]
dent wrote in the New York Times, “many
Interview Survey uses a stratified, multistage
did [you] get any free samples of prescribed
uninsured and low-income patients benefit
probability cluster sampling design with an
medicines from a medical or dental provider
from these free samples, which often serve as
oversampling of Blacks and Hispanics.27 The
that we have not yet talked about?”28 MEPS
defines free samples as “limited amounts of a
However, few data are available on recipi-
prescription medication which are given out by
ents of free samples. Although a few studies
doctors to patients free of charge, sometimes in
have looked at the receipt of free samples in
over 2.5 years. Interviewers travel to the
lieu of a written or verbal prescription.”28
selected populations,6,25,26 no national study
homes of respondents and conduct in-person,
If a respondent answers “yes” to this ques-
has examined this issue. We analyzed the re-
computer-assisted interviews. The MEPS sur-
tion, the names of any medicines received as
ceipt of free samples using nationally repre-
veyors collect detailed information on health
sentative data from the United States in 2003
care expenditures, health care utilization,
We were interested in 3 questions that re-
to determine the characteristics of free sam-
health insurance, and sociodemographic char-
quired us to analyze the complex MEPS data
acteristics, as well as information on all outpa-
set in different ways: (1) Are free drug sam-
ples more frequently given to uninsured and
low-income persons than to insured and afflu-
search and Quality provides weights that ad-
ent persons? (2) Does type of drug coverage
just for the complex sample design and sur-
influence the likelihood of receiving free sam-
Research and Quality’s 2003 Medical Ex-
vey nonresponse and facilitate extrapolation
February 2008, Vol 98, No. 2 | American Journal of Public Health
Cultrona et al. | Peer Reviewed | Research and Practice | 1
initially including our income and insurance
atory multivariate analysis to evaluate the
variables in the logistic regression model. We
whether free drug samples were given more
role of potential intermediary variables re-
then entered into the model all demographic
frequently to uninsured and low-income per-
lated to access to care: site of usual medical
variables that were significant on bivariate
sons. First, we analyzed bivariate associations
care (hospital based vs office vs no usual site
analysis (P < .1) or that we considered to be
between receipt of at least 1 free sample in
of care) and total number of prescription
clinically significant. We ran a secondary mul-
2003, and insurance status and income, re-
medications received including refills.
tivariate model that included income, insur-
spectively. For this analysis, we classified re-
ance, and all significant demographic vari-
spondents as “insured all year” if they indi-
ables and added (1) site of usual medical care
We then examined the effect of prescription
and (2) total number of prescription medica-
drug coverage on sample receipt. For this anal-
medical insurance, or both, for every month
ysis we focused on a single round of MEPS in-
of 2003. We classified respondents as “unin-
We used the SAS version 9.1 (SAS Institute
terviews that collected data for the preceding
sured part or all year” if they reported having
Inc, Cary, NC). To account for sample design
2 to 6 months. We conducted this single-round
insurance during some but not all months or
effects, we used SAS survey commands that
analysis to identify as accurately as possible
if they had no insurance during any month of
make it possible to estimate confidence intervals
the type of drug coverage at the time any sam-
2003. We excluded individuals for whom in-
in the presence of stratification and clustering.
ple was received. We analyzed bivariate associ-
ations between type of drug coverage during
available for all of 2003 (2.8% of respon-
the interview round and receipt of at least 1
those with family incomes less than 200% of
the federal poverty line, middle-income per-
health insurance and no drug coverage, (2)
Medicaid at any point in the round, (3) non-
and 400% of the poverty line, and high-in-
received at least 1 drug as a free sample.
Medicare private insurance with drug coverage,
(4) non-Medicare private insurance without
more than or equal to 400% of the poverty
health care use characteristics of sample re-
drug coverage, (5) Medicare with supplemental
line. In 2003, the federal poverty line was set
cipients and nonrecipients. Low-income re-
drug coverage, and (6) Medicare without sup-
spondents who were uninsured all or part of
plemental drug coverage. We chose the inter-
2003 were less likely to receive free samples
view round for our analysis by selecting the
of other demographic features on the rela-
than were high-income and insured respon-
only MEPS interview that collected data for a
tion between receipt of free drug samples
dents. Among persons who were insured all
and insurance status or income. We devel-
year, 12.9% received a sample, versus 9.9%
of those uninsured for part or all of the year
For our estimate of the most frequently dis-
same definitions for outcome (receipt of at
(P < .001). Of all persons who received a sam-
tributed drugs, we reviewed the names of all
least 1 free sample in 2003), insurance clas-
ple, 82.1% were insured all year; only 17.9%
medications given as samples during calendar
sification, and income as were used in our
of sample recipients were uninsured for all or
year 2003. To provide a comparison, we re-
bivariate analyses. We examined the effect
part of the year. Similarly, of all sample recipi-
of insurance and income on receipt of free
ents, 71.9% had an income 200% or more of
data. Because the MEPS data do not indicate
samples and we controlled for demographic
the federal poverty line, whereas 28.1% had
features including age, gender, race, His-
patient received, we were able to estimate the
panic ethnicity, place of birth, education
line. The poor were the least likely to receive
level, and language spoken. Information on
free samples, whereas individuals in the high-
ications but were not able to establish an
all demographic features, including ethnicity
est income category were the most likely to
and race, was provided by the respondents
receive free samples (10.8% of low-income
through the survey questionnaire. To deter-
persons received at least 1 sample vs 12.3%
mine Hispanic ethnicity, respondents were
asked to characterize themselves as either
received free drug samples in 2003 as a per-
higher-income persons; P < .001 for ordered
centage of all respondents and as a percentage
race, respondents were asked to character-
of all those taking 1 or more prescription
Non-Whites, Hispanics, non-English speak-
drugs. We used the χ2 test to study the bivari-
Indian/Alaska Native, Asian, Native Hawaiian/
ate association between categorical predictors
States were less likely to receive a free sample
Pacific Islander, or multiple races. For our
States, repsctively. Respondents who usually
2 | Research and Practice | Peer Reviewed | Cultrona et al.
American Journal of Public Health | February 2008, Vol 98, No. 2
TABLE 1—Percentage of Respondents Who Received at Least 1 Free Prescription Drug
received their medical care in an office were
Sample in 2003, by Demographic Group: Medical Expenditure Panel Survey, 2003
much more likely to receive samples (14.3%)than were those who used hospital clinics or
hospital emergency departments (10.0%) or
P < .001). Persons who were uninsured part
or all of the year were much more likely to
Total persons who received prescription drugs (n = 19 848)
lack a usual source of medical care (42.9%
P < .001) and were less likely than those in-
sured continuously to report receiving med-
ical care in an office (14.5% of uninsured
part or all year vs 85.5% of continuously
insured; P < .001). They were also less
likely than those insured continuously to
report receiving medication in 2003 (46.5%
< 200% of poverty line and uninsured part or all year
≥200% of poverty line or insured all year
Table 2 presents the results of our multi-
variate analyses of sample receipt. In our
principle model, we analyzed income and in-
surance as predictors of the receipt of free
drug samples; we also controlled for age, gen-
der, race, Hispanic versus non-Hispanic eth-
nicity, place of birth (United States vs foreign
born), education level, and language spoken.
Persons who were uninsured for part or all of
the year were no more likely to receive free
samples (odds ratio [OR] = 0.98; 95% confi-
dence interval [CI] = 0.87, 1.11) than were
those continuously insured. Likewise, being in
the lowest income group was not a significant
predictor of sample receipt (OR = 1.05; 95%
model, keeping all of the afore-mentioned de-
mographic variables and adding 2 intermedi-
ary variables related to access to health care:
the number of prescription medications re-
ceived and the site of usual medical care. In
this model, persons who were uninsured for
part or all of the year were more likely than
those insured continuously to receive free
samples (OR = 1.25; 95% CI = 1.10, 1.43).
The association between income and receipt
of free samples remained nonsignificant.
In our bivariate analysis of type of drug
coverage and receipt of free drug samples
Hospital (clinic or emergency department)
during the 2- to 6-month period in 2003(Table 3), respondents with Medicaid at any
point in the round had the lowest likelihood
of receiving a sample (4.12%), followed bythose with no insurance coverage (4.66%).
February 2008, Vol 98, No. 2 | American Journal of Public Health
Cultrona et al. | Peer Reviewed | Research and Practice | 3
pills received as samples and, therefore, we
TABLE 1—Continued
are unable to determine the percentage of
No. of medications in 2003 (by quartile for those who
total medications represented by free sam-
ples. Such information would be useful to ob-
tain in future studies. We may have underesti-
have forgotten to report samples that they re-
ceived for brief durations earlier in the inter-view reference period, although the relatively
Note. CI = confidence interval. aWeighted percentages are representative of the noninstitutionalized US civilian population. Totals may not add to 100
short duration of interview reference periods
(ranging from 2- to 6-month intervals) should
bP < .001, for χ2 analysis measuring difference between categories for this variable.
have minimized recall bias. Poor or uninsuredrespondents may have perceived receipt of
free samples as shameful or embarrassing and
named free drug samples in 2003 were: (1)
gests that the relation of health coverage and
underreported these events. It is not our ex-
Lipitor (atorvastatin), (2) Allegra (fexofenadine),
affluence to sample receipt is mediated by 2
perience, however, that free samples carry
and (3) Advair diskus (fluticasone/salmeterol).
access-related factors: site of usual medical
such a stigma. Free samples obtained directly
The 3 most frequently prescribed drug samples
care and total use of pharmacotherapy. Office-
from manufacturers by mail order may have
in 2002 were: (1) Vioxx (rofecoxib), (2) Lipitor
been undercounted, but as of 2002, the ma-
(atorvastatin), and (3) Celebrex (celecoxib).
likely to have received at least 1 free drug
jority of such programs required that applica-
sample. If we include site of medical care in
tions be filled out by a physician and (in ap-
our multivariate model, uninsured persons ap-
pear more likely to receive a free sample than
delivered to the doctor’s office.29 Hence, we
To our knowledge, ours was the first popu-
do insured persons. We interpret this finding
believe that many, perhaps most, of such free
lation-based study of free drug sample distri-
to reflect office-based practitioners’ sincere ef-
medications would be classified as free sam-
bution. We found that 12% of US residents
fort to give free samples to their neediest pa-
received free samples during 2003 but less
tients. Unfortunately, these efforts do not ap-
than one third of all sample recipients were
pear to compensate for larger access barriers
lowed by filled prescriptions within a single
low income and less than one fifth of all sam-
that prevent uninsured and other disadvan-
ple recipients were uninsured at any point
taged patients from consulting physicians who
undercounted, because the interviewer asked
during the year. Indeed, the poor were less
are office based. People who were uninsured
respondents about free samples received only
likely to receive free samples than were those
in 2003 were more likely to use hospital clin-
after reviewing filled prescriptions. If 2 pa-
ics or hospital emergency departments or to
tients were each given a free sample along
were less likely to receive free samples than
report no usual source of care and were less
with prescriptions to be filled, the patient with
likely to have purchased or received medica-
lower income and no insurance is probably
Several other vulnerable groups, including
tion compared with people who were insured.
less likely to fill the prescription because of
non-Whites, Hispanics, non-English-speakers,
Previous studies have looked at receipt of
and persons born outside the United States were
free samples in selected populations and gen-
therefore be more likely to report having re-
also less likely to receive a free sample than
erated similar findings. Stevens et al.25 found
ceived a sample in our survey design; if so,
were those born in the United States. In a study
that insured adults with asthma were more
our study may understate the relation of so-
of Medicare patients in Hawaii, Taira et al. simi-
likely to receive samples than were their unin-
larly found that being White was associated with
sured counterparts. A survey of elderly en-
a greater likelihood of receiving a drug sample.26
rollees in a single health insurer in Hawaii26
likely to receive free samples than those
Although overt discrimination might explain the
found that 50% to 60% had received a free
racial and ethnic disparities, we suspect that they
sample in the previous 12 months. That study,
with insurance coverage. Although physicians
reflect unmeasured differences in overall access
like ours, found that race, ethnicity, and age
to care. Persons from these minority groups may
were associated with likelihood of receiving a
enter their offices, these individual efforts fail
also be seeing providers who distribute fewer
sample. Lack of drug coverage among insured
to counteract society-wide factors that deter-
samples. We found that women and older per-
persons was also associated with greater likeli-
mine access to care and selectively direct free
sons had a greater likelihood of receiving sam-
samples to the affluent. Our findings suggest
ples, which was possibly a reflection of increased
that free drug samples serve as a marketing
use of health care services by these groups.
not have information on the total number of
4 | Research and Practice | Peer Reviewed | Cultrona et al.
American Journal of Public Health | February 2008, Vol 98, No. 2
TABLE 2—Multivariate Odds of Free Drug Sample Receipt in 2003: Medical Expenditure
About the AuthorsAll of the authors are with the Department of Medicine,Panel Survey, 2003 Cambridge Health Alliance, Cambridge, Mass, and theHarvard Medical School, Cambridge.Requests for reprints should be sent to Sarah L.Cutrona, Department of Medicine, Cambridge Hospital,1493 Cambridge St, Cambridge, MA 02139 (e-mail:This article was accepted May 22, 2007.
All of the authors participated in designing the study, ana-
lyzing and interpreting the data, writing and revising the
article. S.L. Cutrona, S. Woolhandler, and D.U. Himmel-
stein performed the statistical analysis. D.H. Bor providedsupervision and obtained funding. S.L. Cutrona has had
full access to all the data in the study and has final re-
sponsibility for the decision to submit for publication.
AcknowledgmentsThis work was supported by a National Research Ser-
We are indebted to Amy Cohen, Department of In-
formation Technology, and E. John Orav, Departmentof Biostatistics, both at the Harvard School of Public
Health, for advice on statistical programming. We are
also indebted to Neal S. LeLeiko, from the Department
of Gastroenterology and Nutrition at Hasbro Children’sHospital for valuable discussions and careful reading of
This study was deemed exempt from review by the
Cambridge Health Alliance institutional review board.
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TABLE 3—Percentage of Respondents Receiving at Least 1 Free Drug Sample in a Single TABLE 4—Most Frequently Reported Interview Round in 2003, by Detailed Insurance Coverage: Medical Expenditure Panel Free Drug Samples: Medical Survey, 2003 Expenditure Panel Survey 2002–2003
Received at Least 1 Free Sample, % (95% CI)
Non-Medicare private insurance with drug coverage
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Medicare with private supplemental drug coverage
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American Journal of Public Health | February 2008, Vol 98, No. 2
4. WHY THE CONCERN? 4.1 Prevalence of Obesity The global burden of overweight (BMI 25.0 – 29.9) and obesity (BMI≥30.0) is estimatedat more than 1.1 billion. There is evidence that the risk of obesity related diseases amongAsians rises from a lower BMI of 23.0 (James et al. 2002). If this were adopted as a newbenchmark for overweight Asians, it would require a major revision of approac