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Reviews
Abstract
Objectives: To determine whether adherence interventions should be adminis-tered to all medication takers or targeted to nonadherers.
Data sources and study selection: Systematic search (Medline and Embase, 1966–2009) of randomized controlled trials of interventions to improve adherence to medications for preventing or treating cardiovascular disease or diabetes.
Data extraction: Articles were classified as (1) broad interventions (targeted all medication takers), (2) focused interventions (targeted nonadherers), or (3) dynamic interventions (administered to all medication takers; real-time adherence informa-tion targets nonadherers as intervention proceeds). Cohen’s d effect sizes were cal-culated.
Data synthesis: We identified 7,190 articles; 59 met inclusion criteria. Broad interventions were less likely (18%) to show medium or large effects compared with focused (25%) or dynamic (32%) interventions. Of the 33 dynamic interventions, 6 used externally generated adherence data to target nonadherers. Those with exter-nally generated data were less likely to have a medium or large effect (20% vs. 34.8% self-generated data).
Conclusion: Adherence interventions targeting nonadherers are heterogeneous but may have advantages over broad interventions. Dynamic interventions show promise and require further study.
Keywords: Medication adherence, cardiovascular disease, diabetes.J Am Pharm Assoc. 2012;52:381–397.
doi: 10.1331/JAPhA.2012.10211
Targeting cardiovascular medication adherence interventionssarah L. Cutrona, Niteesh K. Choudhry, Michael A. Fischer, Amber D. servi, Margaret stedman, Joshua N. Liberman, Troyen A. Brennan, and william H. shrank
Received November 23, 2010, and in revised form March 8, 2011. Accepted for publication April 6, 2011.
Sarah L. Cutrona, MD, MPH, was a research associate, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Wom-en’s Hospital, Harvard Medical School, Boston, at the time this study was conducted; she is cur-rently Assistant Professor of Medicine, Division of General Medicine/Primary Care, University of Massachusetts Medical School, Worcester. Niteesh K. Choudhry, MD, PhD, is Assistant Professor of Medicine; Michael A. Fischer, MD, MS, is Assistant Professor of Medicine; and Amber D. Servi, BA, is a research assistant, Di-vision of Pharmacoepidemiology and Pharma-coeconomics, Brigham and Women’s Hospital, Harvard Medical School, Boston. Margaret Stedman, PhD, MPH, is a postdoctoral research fellow, Orthopedics and Arthritis Center for Out-comes Research, Department of Orthopedics, Brigham and Women’s Hospital, Boston. Josh-ua N. Liberman, PhD, is Vice President, Strate-gic Research; and Troyen A. Brennan, MD, JD, is Chief Medical Officer and Executive Vice Pres-ident, CVS Caremark, Hunt Valley, MD. William H. Shrank, MD, MSHS, is Assistant Professor of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Wom-en’s Hospital, Harvard Medical School, Boston, and Associate Faculty, Center for American Political Studies, Faculty of Arts and Sciences, Harvard University, Boston.
Correspondence: Sarah L. Cutrona, MD, MPH, University of Massachusetts Medical School, 377 Plantation St., Biotech 4, Suite 315, Worces-ter, MA 01605. Fax: 508-856-5024. E-mail: sarah.cutrona@umassmemorial.org
Disclosure: Dr. Cutrona is supported by award no. KL2RR031981 from the National Center for Research Resources (NCRR). Dr. Stedman is supported by National Institutes of Health grant NRSA/T32 AR055885-03. Drs. Liberman and Brennan are employees of CVS Caremark and participated in manuscript preparation and re-view. Dr. Shrank is supported by a career devel-opment award from the National Heart, Lung, and Blood Institute (HL-090505). The authors declare no conflicts of interest or financial in-terests in any product or service mentioned in this article, including grants, employment, gifts, stock holdings, or honoraria.
Funding: Research grant from CVS Caremark.
All data analysis and evaluation occurred at Brigham and Women’s Hospital. CVS Caremark did not play a role in the design and conduct of the study; the collection, management, analy-sis, or interpretation of the data; or the prepa-ration, review, or approval of the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NCRR or the National Insti-tutes of Health.
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Reviews MEDICATION ADHERENCE INTERVENTIONS
Medications for preventing and treating cardiovascular disease can reduce morbidity and mortality, but nonad-herence limits their benefits. Nonadherence is widely
recognized as a major public health concern that contributes to patient morbidity, mortality, and health care costs.1,2 Recent estimates indicate that nonadherence to essential chronic med-ications may contribute as much as $290 billion in excess costs to the U.S. health care system annually.3 Improving adherence to therapy should be a priority for our health care system.
Despite broad recognition of the importance of medication adherence, little consensus exists about how to best change behavior and support appropriate use.4 Studies show that mul-tifactorial interventions tend to be more effective than simple ones4; however, the best manner in which to target these inter-ventions remains unknown. Specifically, whether interventions should be targeted to nonadherers only or to all medication tak-ers is unclear. Nonadherence may be improved more effectively if the patients most likely to benefit are targeted. Alternatively, waiting for nonadherence to occur may introduce missed op-portunities if the optimal moment for intervention has already passed.
ObjectiveWe conducted a systematic review of interventions to improve adherence to cardiovascular and diabetes medications, in order
to explore what is known about how to target interventions. We evaluated existing evidence regarding delivery of interventions (1) exclusively to nonadherent patients, (2) to all patients re-gardless of adherence behavior, or (3) to all patients but us-ing real-time adherence information during the intervention to identify nonadherers and thereby target resources.
MethodsA systematic search of peer-reviewed journals between 1966 and 2009 was performed using Medline and Embase. We lim-ited our search to randomized controlled trials. Our search terms related to the type of study (randomized controlled trial), adherence (i.e., adherence, compliance, medication adherence, treatment adherence), prescription drugs (i.e. drug, medica-tion, antihypertensive, antihyperlipidemic, hypoglycemic), and cardiovascular disease and diabetes (i.e., myocardial infarc-tion, coronary heart disease, heart failure, hypertension, dys-lipidemia, diabetes.) Articles with at least one search term in three of the main categories (study type and adherence and ei-ther drug or disease) met criteria for review. Search terms and parameters were adjusted for both databases (Medline and Em-base) while maintaining a common overall architecture. Search results then were screened for duplicate entries.
study selectionStudies were included if they reported results of randomized controlled trials studying interventions to improve adherence to medications used for preventing or treating cardiovascular disease or diabetes. Studies were limited to adult patients (age ≥18 years). We included only studies that reported long-term outpatient medication adherence. Studies were excluded if they described an intervention characterized by regimen simplifica-tion (either unit-of-use packaging or changes in dose frequency or formulation), as they could not be placed into one of our pre-specified study strata (described below), and previous studies have demonstrated their effectiveness.4 Non-English studies and those with a follow-up period of less than 24 weeks also were excluded.
study classificationAfter exclusions, 59 articles (Figure 1) were classified based on the target of the main intervention as (1) focused interventions (targeted exclusively to nonadherers), (2) broad interventions (targeted to the entire population of medication takers), or (3) dynamic interventions (administered to all medication takers but using real-time adherence information to identify and target nonadherers). To meet criteria for classification as a dynamic intervention, interventions were required to report that infor-mation was gathered on adherence and acted on before the con-clusion of the study in a way that would differentiate adherers from nonadherers (i.e., an adherence feedback loop). Ongoing measurements of clinical outcomes (e.g., blood pressure) were not considered substitutes for real-time measurements of ad-herence. However, we considered patient self-reported adher-ence to be an acceptable measure (as in a situation where a patient discussed adherence challenges with a pharmacist in the absence of calculations of a numerical adherence outcome).
At a GlanceSynopsis: Medline and Embase were searched for
articles on medication adherence interventions clas-sified as broad interventions (targeting all medication takers), focused (targeting nonadherers), or dynamic (administered to all medication takers, with real-time adherence information targeting nonadherers as in-tervention proceeded). Broad interventions were less likely (18%) to show medium or large effects com-pared with focused (25%) or dynamic (32%) interven-tions. Targeting nonadherent patients may lead to bet-ter adherence; however, data are limited and studies in the literature are highly heterogeneous.
Analysis: Focused interventions allow limited re-sources to be directed toward fewer, higher-risk pa-tients, and dynamic interventions share this advantage when the more costly portion of the intervention is re-served for identified nonadherers. However, attention must be paid to the method of identifying nonadher-ers. None of the focused interventions identified here used pharmacy claims data to identify nonadherence. Dynamic interventions were overwhelmingly depen-dent on self-generated adherence data (often requiring intensive interaction with a health provider), and very few used any form of external data. The accuracy, cost, and reproducibility of methods for identifying target populations must be a central consideration in future studies.
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MEDICATION ADHERENCE INTERVENTIONS Reviews
We further classified dynamic studies based on the type of adherence data used in the adherence feedback loop: (1) self-generated data alone or (2) external data (either alone or as a supplement to self-generated data). Self-generated data feed-back loops were those in which the intervention was tailored on the basis of patient self-reported nonadherence. For example, in a pharmacist counseling session in which the pharmacist does not have access to pharmacy records, a patient could re-port nonadherence and that would stimulate additional patient contact to support appropriate use. External data feedback loops were those in which information such as medication pos-session ratio derived from pharmacy records or other external sources was used to tailor the intervention. Authors were re-quired to explicitly state that external data were accessed in real time before a study was characterized as using an exter-nal data feedback loop. We did not consider patient-controlled sources such as medication diary cards to be external data but did consider a pill count conducted by someone other than the patient to meet this criterion.
This classification was often distinct from the way adher-ence was ultimately measured as the study outcome. For ex-ample, patients might describe themselves as nonadherent in a pharmacist counseling session and receive appropriate in-
terventions, while adherence outcomes were measured with claims data. In this scenario, we would classify the feedback loop as using self-generated adherence information.
Data extractionData were extracted by two investigators (S.L.C. and W.H.S.) with disagreements resolved by consensus. We assessed a number of variables related to the organization and outcome of studies, including study design, setting, characteristics of study population, number of participants, mean age (or age range) of participants, characteristics of intervention, meth-ods used to measure medication adherence, clinical outcomes, medication adherence outcomes, and source of funding. CIs are reported when available and P values when no CIs were available. The methodological quality of studies was assessed using the five-point Jadad scale.5 Because the overwhelming majority of adherence interventions identified in this study were not able to be double blinded, Jadad scores tended to be low. For this reason, we chose not to use a cut-off value and did not ultimately consider Jadad scores to be a useful means of ascertaining study quality. Jadad scores and funding sources for all studies are presented in Appendix 1 (electronic version of this article, available online at www.japha.org).
We identified randomized controlled trials in which means
Figure 1. Included and excluded articles
7,008 excluded
123 excluded
7,190 articles found 3,471 Embase 3,719 Medline
- 6,516 did not meet inclusion criteria for title and abstract - 492 citations overlapped in both databases
182 articles considered for inclusion
- 5 duplicate citation - 63 did not meet criteria: 19 excluded due to study design 19 excluded due to medication adherence outcome incomplete 5 excluded due to non-English 9 excluded due to wrong participants - 8 participants <18 years of age - 1 participant no cardiovascular disease 3 excluded due to different intervention (not designed to improve medication adherence) 8 excluded due to no empirical results reported - 29 duration <6 months - 26 used regimen simplification
59 included
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Reviews MEDICATION ADHERENCE INTERVENTIONS
and SDs for medication adherence outcomes were presented. A wide range of adherence outcome measures were observed, in-cluding binary (e.g., survey responses or predefined adherence cutoffs) and continuous measures (e.g., proportion of days cov-ered), making interpretation of absolute changes difficult. To compare studies with differing outcomes, we used Cohen’s d statistics, which can be calculated for outcomes that are either binary or continuous.6,7 The effect sizes (ESs) compare the dif-ference in effect between the study groups divided by the SD of this difference.8 When SDs were not reported, we derived them from the P value or t test statistic.
Using standard methods, we considered an ES less than 0.2 to be very small, 0.2 to less than 0.5 small, 0.5 to less than 0.8 medium, and 0.8 or greater large. We used this categoriza-tion to simplify interpretability for readers so that magnitude of effect is more intuitive. We assumed that the estimated Co-hen’s d statistics were independent of scale, sample size, and the SD of the outcome studied.
We attempted a fixed-effects meta-analysis in which ESs were pooled. We performed an analysis of statistical heteroge-neity in the intervention groups with at least 10 studies (broad intervention, dynamic self-generated intervention), and after finding high statistical heterogeneity in these groups (broad heterogeneity = 4.1, dynamic heterogeneity = 2.6), we removed outlying and influential studies and performed the analysis again. Heterogeneity measures remained high (broad hetero-geneity = 1.7, dynamic heterogeneity = 1.8). Heterogeneity statistics above 1.5 indicate high heterogeneity.9 Based on this finding and the clinical heterogeneity of the identified studies, we did not feel that presenting summary estimates was appro-priate.
ResultsFocused interventionsWe found only four focused interventions10–13 (Table 1), with mean participant ages ranging from 62 to 67 years. Adherence was measured differently in each study, and none of the studies made use of pharmacy claims data to determine inclusion cri-teria. One study showed a medium ES; the other three showed small ESs.
Haynes et al.10 identified 39 nonadherent hypertensive pa-tients from an initial group of 245 patients found to be hyper-tensive during workplace screening and advised home blood pressure self-checks, biweekly home visits by research assis-tants, and tailoring of the regimen. They found a medium ES by pill count at 6 months (0.73 [CI 0.07–1.39]).
Of an initial group of 79 patients with diabetes, Rosen et al.11 selected 33 patients on metformin with poor adherence measured with electronic pill bottles. These patients were ran-domized to 16 weeks of programmable electronic pill caps ver-sus nonprogrammable electronic caps. Although Rosen et al. described significantly improved adherence at 16 weeks based on medication possession ratio (80% intervention vs. 60% con-trol, P = 0.017; ES 0.43 [CI –0.27 to 1.14]), the study provides only a graphic representation of outcomes at 28 weeks (both groups declined). Saunders et al.12 identified a group of hyper-
tensive “infrequent attenders” to a medical clinic in Soweto, South Africa, where medications were dispensed at the clinic appointment. They identified 109 nonadherent patients, 72 of whom were included in the analysis. Appointment reminders, patient-retained records, and targeted home visits yield signifi-cant improvement in the intervention group (68% vs. 37% con-trol, P = 0.009) with a small calculated ES.
Taylor et al.13 randomized 81 patients at high risk for medi-cation events and analyzed 69 of them. Inclusion criteria in-cluded (but were not limited to) patient- or physician-reported nonadherence. Intervention patients received 20-minute coun-seling session at the pharmacy before physician office visits. Baseline data for the study indicated that 84.9% of the inter-vention patients and 88.9% of control patients had self-re-ported mean adherence scores between 80% and 100%. At 12 months, self-reported mean adherence scores showed a small ES difference between the intervention (100% adherence) and control (88.9%) groups. High initial adherence rates (or artifi-cially inflated self-reports of adherence) may render this study less representative of a focused intervention than the previous three.
Broad interventionsWe identified 25 broad interventions14–38 (Table 2) and cal-culated ESs in all but three cases.22,25,32 Mean ages of partici-pants ranged from 46 to 76 years. We found medium to large effects on adherence in 18.2% of studies; 68.2% had very small or small effects and 13.6% had no effect or negative effects. The vast majority of interventions (19 of 25 studies) examined hypertensive patients; others addressed patients with diabe-tes (2 studies), dyslipidemia (1), congestive heart failure (1), myocardial infarction (1), and both cardiac and noncardiac dis-eases (1).
A total of 13 studies described interventions dependent on involvement of a health professional: physician medi-ated,14,15,17,25,29,32,38 pharmacist mediated,20,22 or nurse medi-ated.19,22,23,31 Among these studies, ESs could be calculated for 10 studies, with 7 showing small or very small ESs, 1 a me-dium effect, and 2 negative or null effects. Yilmaz et al.,38 who showed an ES in the medium range, implemented a primarily educational intervention. The study involved comprehensive education on statins but allowed for consultation as needed with a physician and showed that intervention patients were more likely to adhere to statins (odds ratio [OR] 1.98) than control patients, based on self-report. The study with an ES of zero (Hamet et al.19) involved nurse counseling by phone com-bined with reminder letters and mailed education brochures, with adherence measured using a single-question self-report.
Six studies described the introduction of an electronic re-source including computerized decision aid,18 electronic moni-tor with reminder,16 or home blood pressure monitor.21,26,27,37 We calculated ESs for all six of these studies, and all but one showed very small or small effects on adherence. Johnson et al.21 conducted a 2 × 2 factorial study combining self-record-ed blood pressure values with monthly home visits, with a calculated ES of 1.51 (CI 0.96–2.05). We identified six stud-
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MEDICATION ADHERENCE INTERVENTIONS ReviewsTa
ble
1. Fo
cuse
d in
terv
entio
ns: T
arge
ted
to n
onad
here
rs
Aut
hor,
year
, site
Parti
cipa
nts;
dur
atio
naIn
terv
entio
nb
Met
hod
of ta
rget
ing
inte
rven
tion
grou
p no
nadh
erer
sA
dher
ence
mea
-su
res
Out
com
es, C
ohen
’s d
ES
(95%
CI)c
Hayn
es, 1
976,
Ca
nada
39 h
yper
tens
ive
patie
nts
iden
tified
as n
onad
here
nt
(pill
cou
nt <
80%
) afte
r 6
mon
ths o
f tre
atm
ent,
also
no
t at g
oal d
iast
olic
BP;
12
mon
ths
I: Ho
me
BP se
lf-ch
ecks
, m
edic
atio
n an
d BP
cha
rting
re
view
ed a
t 2-w
eek i
nter
vals
by
rese
arch
ass
ista
nt d
urin
g ho
me
visi
t, ta
ilorin
g of
regi
men
Posi
tive
rein
forc
emen
t for
per
fect
ad
here
nce,
reas
ons f
or n
onad
-he
renc
e so
ught
and
atte
mpt
s at
prob
lem
solv
ing
thro
ugh
tailo
ring
of
regi
men
for n
onad
here
nce
Prop
ortio
n of
pr
escr
ibed
pill
s re
mov
ed fr
om c
on-
tain
ers.
Mea
n ±
SD: I
, 65.
8% ±
8.2%
, w
ithin
-gro
up P
= 0.
001;
C:
43.2
% ±
10.1
%, w
ithin
-gro
up
P =
NS;
bet
wee
n-gr
oup
P =
0.02
5; E
S 0.
73 (0
.07–
1.39
)
Rose
n, 20
04,
Conn
ectic
ut
33 d
iabe
tes p
atie
nts o
n m
et-
form
in w
ith <
80%
adh
eren
ce
afte
r 4-w
eek b
asel
ine;
28
wee
ks
I: Cu
e-do
se tr
aini
ng:
give
n el
ectro
nic
pill c
aps p
ro-
gram
med
to b
eep,
inst
ruct
ion
on o
ther
cue
s
Adhe
renc
e da
ta g
iven
mon
thly
to
prov
ider
s; p
rovi
ders
con
tact
ed b
e-fo
re a
ppoi
ntm
ents
, urg
ed to
dis
cuss
ad
here
nce
data
Mea
n M
PR (d
oses
ne
eded
to b
e ta
ken
on ti
me)
; ele
ctro
nic
pill b
ottle
s
16 w
eeks
of i
nter
vent
ion:
I,
80%
; C, 6
0%, P
= 0.
017;
no
num
bers
giv
en fo
r 28 w
eeks
(g
raph
onl
y); E
S 0.
43 (–
0.27
to
1.14
)Sa
unde
rs, 1
991,
So
wet
o, S
. Afri
ca
Hype
rtens
ive
patie
nts d
i-vi
ded
into
new
ly tr
eate
d (1
15,
not s
how
n he
re) a
nd n
onad
-he
rent
(109
); 6 m
onth
s
I: Ap
poin
tmen
t rem
inde
rs
sent
; pat
ient
-ret
aine
d BP
and
m
edic
atio
n re
cord
s; m
edic
a-tio
ns o
btai
ned
at c
linic
visi
ts
Targ
eted
fiel
dwor
ker h
ome
visi
t fo
llow
-up
if no
resp
onse
to tw
o ca
ll-ba
ck le
tters
MPR
bas
ed o
n cl
inic
in
stru
ctio
ns; a
dher
-en
t if 8
0% c
onsu
med
Non
adhe
rent
: I, 6
8%; C
, 37
%, P
= 0.
009;
ES
0.39
(–0.
20
to 0.
97)
Tayl
or, 2
003,
Al
abam
a
81 p
atie
ntsd a
t hig
h ris
k for
m
edic
atio
n ev
ents
due
to
poly
phar
mac
y, n
onad
her-
ence
(per
med
ical
reco
rd,
self-
repo
rt, o
r refi
ll his
tory
), ot
her;
1 yea
r
I: Ph
arm
acy c
are:
20-m
inut
e in
-per
son
mee
tings
bef
ore
phys
icia
n of
fice
visi
ts, in
-cl
uded
med
ical
his
tory
, med
i-ca
tion
revi
ew, e
duca
tion,
and
m
onito
ring
Phar
mac
ist r
evie
w, a
dvic
e to
phy
si-
cian
(spo
ken
or vi
a m
edic
al re
cord
) an
d to
pat
ient
; sug
gest
ions
for n
on-
adhe
rers
incl
uded
sim
plifi
ed re
gi-
men
, pill
box
es, m
inim
izing
adv
erse
ef
fect
s, c
onso
lidat
ing
regi
men
s,
devi
sing
rem
inde
rs
Estim
ated
MPR
: sel
f-re
port;
mea
n ad
her-
ence
scor
e ca
lcu-
late
d fro
m sc
ores
for
each
med
icat
ion
12 m
onth
: I, 1
00%
; C, 8
8.9%
±
6.3%
, P =
0.11
5; E
S 0.
38
(–0.
11 to
0.87
)
Abbr
evia
tions
use
d: B
P, b
lood
pre
ssur
e; C
, con
trol g
roup
; ES,
effe
ct si
ze; I
, inte
rven
tion
grou
p; M
PR, m
edic
atio
n po
sses
sion
ratio
; NS,
non
sign
ifica
nt.
a Dura
tion
indi
cate
s tim
e un
til la
st fo
llow
-up
at w
hich
adh
eren
ce w
as m
easu
red.
b Co
ntro
l pat
ient
s rec
eive
d us
ual c
are
unle
ss o
ther
wis
e sp
ecifi
ed.
c 95%
CI u
nles
s oth
erw
ise
spec
ified
. Fo
r all s
tudi
es w
here
mea
ns (±
SD) f
or a
dher
ence
out
com
es w
ere
avai
labl
e, C
ohen
’s d
stat
istic
s wer
e ca
lcul
ated
. The
ESs
com
pare
the
diffe
renc
e in
effe
ct b
etw
een
the
stud
y gro
ups d
ivid
ed b
y the
SD
of th
is d
iffer
ence
. We
cons
ider
ed a
n ES
<0.
2 to
be ve
ry sm
all, 0
.2–0
.5 sm
all, 0
.5–0
.8 m
ediu
m, a
nd >
0.8 l
arge
. d Al
l pat
ient
s in
this
stud
y had
thre
e or
mor
e di
seas
es, w
ith h
yper
tens
ion,
dys
lipid
emia
, and
dia
bete
s bei
ng m
ost c
omm
on.
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Reviews MEDICATION ADHERENCE INTERVENTIONSTa
ble
2. B
road
inte
rven
tions
(tar
gete
d to
all m
edic
atio
n ta
kers
) des
igne
d to
impr
ove
adhe
renc
e to
car
diov
ascu
lar m
edic
atio
nsA
utho
r, ye
ar, s
itePa
rtici
pant
s; d
urat
iona
Inte
rven
tionb
Adh
eren
ce m
easu
res
Out
com
es, C
ohen
’s d
ESs
(95%
CI)c
Avan
zini, 2
002,
Ita
ly
1,77
1 tre
ated
hyp
erte
nsiv
e pa
tient
s; 1
year
Pa
tient
s fol
low
ed b
y phy
sici
ans w
ho w
rote
gu
idel
ines
for h
yper
tens
ion
man
agem
ent
% o
f pat
ient
s with
poo
r adh
er-
ence
; sel
f-rep
ort (
not d
efine
d fu
rther
)
Poor
adh
eren
ce: I
, 3.8
%; C
, 9.5
%, P
=
0.00
4; E
S 0.
20 (0
.13–
0.27
)
Birtw
hist
le, 2
004,
ur
ban
and
rura
l Ca
nada
614 h
yper
tens
ive
patie
nts;
36
mon
ths
3- vs
. 6-m
onth
phy
sici
an fo
llow
-up
M
oris
ky sc
ale
ques
tions
, incl
ud-
ing
ever
forg
et b
lood
pre
ssur
e pi
lls; s
elf-r
epor
t
I: 3 m
onth
, 30%
; I: 6
mon
th, 2
7%; d
iffer
-en
ce: 2
.96%
± 3.
92%
(mea
n ±
SE);
90%
CI
(–3.
48 to
9.41
); ES
0.24
(0.0
7–0.
42)
Chris
tens
en, 2
010,
Po
land
784 h
yper
tens
ive
patie
nts o
n te
lmis
arta
n; 1
year
(6 m
onth
s pe
r cro
ssov
er a
rm)
Elec
troni
c ad
here
nce
mon
itorin
g w
ith a
u-di
ovis
ual r
emin
der d
evic
e
Self-
repo
rt: n
umbe
r of d
ays i
n pa
st w
eek t
akin
g m
edic
atio
n as
pr
escr
ibed
; mea
n fo
r pop
ulat
ion
give
n as
per
cent
12 m
onth
s: I,
86.3
%; C
, 88.
4%, P
= 0.
812;
ES
0.06
(0.0
1–0.
12)
Düsi
ng, 2
009,
m
ultip
le si
tes i
n Ge
rman
y
206 h
yper
tens
ive
patie
nts
new
ly d
iagn
osed
or u
ntre
ated
fo
r 1 ye
ar; 3
4 wee
ks
Stru
ctur
ed p
hysi
cian
–pat
ient
inte
ract
ion,
pr
inte
d hy
perte
nsio
n in
form
atio
n, re
min
der
stic
kers
, hom
e tim
er, a
nd B
P m
easu
re-
men
ts
Daily
inta
ke o
f med
icat
ion
at c
or-
rect
tim
e; M
EMS
For o
vera
ll stu
dy d
urat
ion:
adh
eren
ce
for I
is g
reat
er th
an C
; P =
0.18
6; E
S 0.
08
(0.2
1–0.
37)
Emm
ett,
2005
, Br
isto
l, U.K
.
217 n
ewly
dia
gnos
ed h
yper
-te
nsiv
e pa
tient
s, p
rimar
y car
e pr
actic
es; 3
year
s
(1) I
n-pe
rson
adm
inis
tratio
n of
dec
isio
n ai
d on
hyp
erte
nsio
n, c
ardi
ovas
cula
r ris
k; (2
) vi
deo
and
leafl
et; (
3) d
ecis
ion
anal
ysis
and
vi
deo,
leafl
et vs
. usu
al c
are
Prop
ortio
n of
pat
ient
s who
repo
rt ta
king
all t
heir
med
icat
ions
Deci
sion
ana
lysi
s: 90
%, a
djus
ted
OR 1.
56
(0.4
9–4.
96),
P =
0.45
; vid
eo p
lus l
eafle
t: 94
%, a
djus
ted
OR 0.
53 (0
.15–
1.84
), P
= 0.
32; E
S 0.
15 (–
0.12
to 0.
42)
Ham
et, 2
003,
Ca
nada
4,86
4 pat
ient
s with
ess
entia
l hy
perte
nsio
n on
irbe
sarta
n;
12 m
onth
s
Beha
vior
al m
odifi
catio
n pr
ogra
m: p
hone
nu
rse
coun
sel, r
emin
der l
ette
rs, B
P di
arie
s,
mai
led
educ
atio
n br
ochu
res
“Are
you
taki
ng yo
ur A
vapr
o ev
ery d
ay?”
(no
= no
nadh
eren
t);
self-
repo
rt
% n
onad
here
nt p
atie
nts:
I, 25
.4%
(23.
7–27
.2);
C, 25
.5%
(23.
8–27
.3);
betw
een-
grou
p di
ffere
nce,
–0.
1% (–
2.6 t
o 2.
3), P
=
0.94
; ES
0 (–0
.61 t
o 0.
62)
Haw
kins
, 197
9,
Texa
s 20
0 hyp
erte
nsiv
e pa
tient
s on
a di
uret
ic w
ith/w
ithou
t met
hyl-
dopa
; 29 m
onth
s
Clin
ical
pha
rmac
ist m
anag
ed h
yper
tens
ion
in p
lace
of p
hysi
cian
%
of a
dher
ent p
atie
nts (
MPR
>0
.80 c
onsi
dere
d ad
here
nt);
phar
mac
y rec
ords
Diur
etic
onl
y: I,
60.5
%; C
, 52.
9%, P
≤ 0.
7;
diur
etic
plu
s met
hyld
opa:
I, 84
.6%
; C,
65.4
%, P
≤ 0.
2; E
S 0.
45 (–
0.07
to 0.
97)
John
son,
1978
, Ha
milt
on, C
anad
a
140 p
eopl
e w
ith p
ersi
s-te
ntly
ele
vate
d di
asto
lic B
P; 6
m
onth
s
2 × 2
fact
oria
l: (1)
self-
reco
rdin
g BP
, (2)
m
onth
ly h
ome
visi
ts, (
3) se
lf-re
cord
ing
and
hom
e vi
sits
; con
trol (
neith
er)
% a
dher
ence
est
imat
ed b
y co
mpa
ring
pills
on
hand
with
pr
escr
iptio
n re
cord
s; se
lf-re
port,
pi
ll cou
nt
Mea
n Δ
adhe
renc
e (±
SD):
I1, s
elf-
reco
rdin
g BP
, 11.
8% ±
4.5%
; I2,
mon
thly
ho
me
visi
ts: 2
.2%
± 5.
6%; I
3, se
lf-re
cord
-in
g +
hom
e vi
sits
, 10.
1% ±
4.9%
; C, 1
.0%
±
7.0%
, P =
NS;
ES
1.51
(0.9
6–2.
05)
Kirs
cht,
1981
, Te
cum
seh,
MI
417 p
atie
nts w
ith h
yper
ten-
sion
; 3 ye
ars
Assi
gned
to fo
ur in
terv
entio
ns in
a fa
ctor
ial
desi
gn, 3
× 2
× 3 ×
2: (1
) prin
ted
mes
sage
s,
(2) n
urse
pho
ne re
min
der a
nd re
info
rce-
men
t, (3
) sel
f-mon
itorin
g w
ith c
harts
, (4)
nu
rse
wor
ked
with
supp
ort p
erso
n
MPR
; pha
rmac
y rec
ords
; ave
r-ag
ed o
ver t
he se
t of h
yper
ten-
sion
med
icat
ions
Prin
ted
info
rmat
ion:
I, 0.
689;
C, 0
.684
, be
twee
n-gr
oup
P =
NS;
nur
se p
hone
co
ntac
t: I,
0.74
9; C
, 0.6
90, b
etw
een-
grou
p P
< 0.
05; s
elf-m
onito
ring:
cha
rts, 0
.683
; BP
, 0.6
65; C
, 0.6
65, b
etw
een-
grou
p P
= N
S; n
urse
supp
ort:
I, 0.
654;
C, 0
.545
, be
twee
n-gr
oup
P <
0.05
; ES
unab
le to
ca
lcul
ate
J o u r n a l o f t h e A m e r i c a n P h a r m a c i s t s A s s o c i a t i o n www.japha.org M ay /J u n 2012 • 52:3 • JAPhA • 387
MEDICATION ADHERENCE INTERVENTIONS Reviews
Tabl
e 2.
Bro
ad in
terv
entio
ns (t
arge
ted
to a
ll med
icat
ion
take
rs) d
esig
ned
to im
prov
e ad
here
nce
to c
ardi
ovas
cula
r med
icat
ions
Tabl
e 2 c
ontin
ued
Loga
n, 19
79, T
o-ro
nto,
Can
ada
457 h
yper
tens
ive
patie
nts s
e-le
cted
from
vario
us w
orks
ites;
6 m
onth
s
Wor
ksite
car
e: n
urse
wor
king
und
er p
hysi
-ci
an su
perv
isio
n m
anag
ed a
ll asp
ects
of
hype
rtens
ion
Adhe
renc
e: ≥
80%
of p
resc
ribed
m
edic
atio
ns w
ere
cons
umed
(p
ill c
ount
) and
pat
ient
cla
imed
to
be
taki
ng th
e m
edic
atio
n as
in
stru
cted
(sel
f-rep
ort)
% o
f adh
eren
t pat
ient
s: I,
67.6
%; C
, 49
.1%
, P <
0.00
5; E
S 0.
38 (0
.13–
0.63
)
Lope
z Cab
ezas
, 20
06, B
arce
lona
, Sp
ain
134 h
ospi
taliz
ed p
atie
nts w
ith
CHF;
1 ye
ar
Phar
mac
ist p
rogr
am: e
duca
tiona
l inte
rvie
w
with
pat
ient
and
car
egiv
er a
t dis
char
ge,
follo
w-u
p ph
one
calls
Adhe
rent
: 95–
100%
of p
resc
ribed
do
ses t
aken
%
of a
dher
ent p
atie
nts a
t 1 ye
ar: I
, 85.
0%;
C, 73
.9%
, P =
NS;
ES
0.28
(–0.
26 to
0.81
)
Man
n, 20
09, N
ew
York
15
0 dia
bete
s pat
ient
s fro
m p
ri-m
ary c
are
cent
ers;
6 m
onth
s In
-per
son
revi
ew o
f sta
tin ri
sks a
nd b
enefi
ts
with
prim
ary c
are
prov
ider
, usi
ng st
atin
de
cisi
on a
id a
t pro
vide
r’s d
iscr
etio
n
Adhe
renc
e as
sess
ed vi
a 8-
item
M
oris
ky a
dher
ence
scal
e; d
oes
not d
efine
“goo
d ad
here
nce”
80%
of p
artic
ipan
ts re
porte
d go
od a
d-he
renc
e in
bot
h gr
oups
; P =
NS;
ES
un-
able
to c
alcu
late
Mar
quez
-Con
tre-
ras,
2006
, Spa
in
250 h
yper
tens
ive
patie
nts
from
prim
ary c
are
cent
ers;
6
mon
ths
Hom
e au
tom
atic
BP
mon
itorin
g
MPR
(exp
ress
ed a
s %);
adhe
rent
is
>80
%; M
EMS
% o
f adh
eren
t pat
ient
s (m
ean
± SD
): I,
92 ±
14.2
); C,
74 ±
18.1
, P =
0.00
07; E
S 0.
29
(0.0
0–0.
58)
Meh
os, 2
000,
Co
lora
do
36 h
yper
tens
ive
patie
nts (
with
ph
arm
acis
t pro
vidi
ng d
irect
cl
inic
al se
rvic
es);
6 mon
ths
Hom
e BP
mon
itors
, dia
ry fo
r BP
and
mis
sed
dose
s; p
harm
acis
t eva
luat
ed B
P by
pho
ne
mon
thly
MPR
(mea
n), e
xpre
ssed
as %
; ph
arm
acy r
efill d
ata
I, 82
%; C
, 89%
, P =
0.29
; ES
0.35
(–0.
32 to
1.
02)
Mor
isky
, 198
5,
Balti
mor
e, M
D
290 h
yper
tens
ive
patie
nts;
18
mon
ths
Fam
ily su
ppor
t: ho
me
inte
rvie
w, t
rain
ing
with
fam
ily m
embe
r Se
lf-re
port:
scal
e 0–
4 (1 p
oint
per
ye
s; 4
= lo
w a
dher
ence
) In
terv
entio
n gr
oup
had
impr
oved
sc
ores
(0.8
76 vs
. 1.9
32, P
< 0.
01);
ES 0.
87
(0.6
3–1.
11)
Mul
lan,
2009
, M
inne
sota
85
dia
bete
s pat
ient
s (ra
ndom
-ize
d 40
clin
icia
ns);
6 mon
ths
Deci
sion
aid
revi
ewin
g 5 d
iabe
tes d
rugs
us
ed d
urin
g in
-per
son
clin
icia
n vi
sit v
s.
cont
rol: e
duca
tiona
l pam
phle
t
Prop
ortio
n of
day
s cov
ered
,%;
phar
mac
y rec
ords
%
(ran
ge):
I, 97
.5 (0
.0–1
00);
C, 10
0 (73
.9–
100)
; adj
uste
d m
ean
diffe
renc
e, –
8.88
(–
13.6
to –
4.14
); ES
–0.
09 (–
0.14
to –
0.04
)Po
wel
l, 199
5, m
id-
wes
t U.S
. 4,
246 p
atie
nts o
n be
nzap
ril,
met
opro
lol, s
imva
stat
in, o
r es
troge
n; 9
mon
ths
Mai
led
1 of 4
edu
catio
nal v
ideo
tape
s
MPR
; pha
rmac
y cla
ims
N
o si
gnifi
cant
bet
wee
n-gr
oup
diffe
renc
-es
in m
ean
MPR
s; E
S 0.
04 (–
0.02
to 0.
10)
Rudd
, 200
4, C
ali-
forn
ia
150 p
atie
nts o
n m
edic
atio
n fo
r hy
perte
nsio
n; 6
mon
ths
Phys
icia
n-di
rect
ed, n
urse
-man
aged
, al
gorit
hm-b
ased
hom
e hy
perte
nsio
n m
an-
agem
ent,
base
d on
self-
BP c
heck
s
Adhe
renc
e: a
vera
ge %
of d
ays
on w
hich
the
corr
ect n
umbe
r of
dose
s wer
e ta
ken;
ele
ctro
nic
pill
mon
itors
Mea
n ±
SD: I
, 80.
5 ± 23
.0%
; C, 6
9.2%
±
31.1
%, P
= 0.
03; E
S 0.
41 (0
.07–
0.76
)
Sack
ett,
1975
, Ha
milt
on, C
anad
a
230 C
anad
ian
stee
lwor
kers
w
ith h
yper
tens
ion
dete
cted
on
scre
enin
g; 6
mon
ths
AC h
yper
tens
ion
treat
ed b
y wor
ksite
phy
si-
cian
; AE:
pro
gram
on
hype
rtens
ion,
pill
-ta
king
rem
inde
rs; C
: no
AC, n
o AE
; I1:
AC,
no
AE; I
2: n
o AC
, AE;
I3, A
C, A
E
Adhe
renc
e: M
PR in
6th
mon
th;
pill c
ount
; adh
eren
t is M
PR ≥
0.8
% a
dher
ent a
t 6 m
onth
s: A
C, 54
%; n
o AC
: 51
%; A
E, 50
%; n
o AE
, 56%
; AE:
with
AC,
48
%; w
ithou
t AC,
53%
; no
AE: w
ith A
C,
62%
; with
out A
C, 48
%; n
onsi
gnifi
cant
di
ffere
nce;
ES
unab
le to
cal
cula
teSc
lar,
1991
, Del
a-w
are,
Tex
as, a
nd
Wis
cons
in
453 h
yper
tens
ive
patie
nts o
n at
enol
ol; 1
80 d
ays
On re
fill, e
duca
tiona
l mat
eria
l giv
en; p
hone
co
ntac
t, re
fill r
emin
der,
mai
lings
(4 a
rms,
ea
ch g
roup
div
ided
: pre
viou
sly t
reat
ed/
new
ly d
iagn
osed
)
MPR
: mul
tiplie
d th
e nu
mbe
r of
requ
este
d at
enol
ol re
fills
by 3
0 an
d di
vide
d by
180
MPR
(mea
n ±
SD):
prev
ious
ly tr
eate
d:
C, 0.
48 ±
0.06
; I, 0
.82 ±
0.04
; new
ly d
iag-
nose
d: C
, 0.5
2 ± 0.
06; I
, 0.9
3 ± 0.
05, P
<
0.05
; ES
7.42
(6.3
4–8.
51)
Smith
, 200
8, U
.S.
urba
n ce
nter
s
907 p
atie
nts a
t hos
pita
l di
scha
rge
post
-MI,
with
be
ta b
lock
er p
resc
riptio
ns; 9
m
onth
s
Two
mai
lings
to p
atie
nts,
PCP
s add
ress
ing
impo
rtanc
e of
bet
a bl
ocke
rs, g
uide
lines
% o
f pat
ient
s with
≥80
% o
f day
s co
vere
d in
the
9 mon
ths a
fter 1
st
mai
ling;
pha
rmac
y cla
ims a
nd
othe
r ele
ctro
nic
data
Trea
tmen
t pat
ient
s wer
e 17
% m
ore
likel
y to
hav
e 80
% o
f day
s cov
ered
(RR
1.17
[1
.02–
1.29
]); E
S 0.
09 (–
0.23
to 0.
42)
J o u r n a l o f t h e A m e r i c a n P h a r m a c i s t s A s s o c i a t i o nwww.japha.org388 • JAPhA • 52:3 • M ay /J u n 2012
Reviews MEDICATION ADHERENCE INTERVENTIONS
ies28,30,33–36 that assessed the impact of family support and edu-cation interventions, all of which had calculable ESs. As with previous groups of broad interventions, the majority were clas-sified as having very small or small effects (three studies). This is a particularly hard group about which to generalize because an additional two studies yielded large effects28,33 and one showed a negative effect.35
Although broad interventions did not incorporate ad-herence feedback loops, more than one-third of these stud-ies15–17,19,20,22,24,25,29,31,35 gathered adherence data at multiple time points. Several of these studies considered avoidance of a feedback loop to be an intentional part of the design. Chris-tensen et al.,16 who used electronic adherence monitoring with an audio-visual reminder device, explicitly stated that “treating physicians had no access to the questionnaire data during the study to avoid social desirability bias.” Rudd et al.,31 describ-ing an intervention in which project staff downloaded data from electronic medication monitors at 3 and 6 month clinic visits, stated that they “provided no feedback on drug adherence to patients, physicians, or nurse care managers.” For many oth-ers, the lack of a feedback loop appeared to be mediated by a separation between the person administering the intervention and those gathering data.
Dynamic interventionsWe found 30 dynamic interventions39–68 (Table 3), 28 of which had ESs that could be calculated.47,68 Mean ages of partici-pants ranged from 49 to 78 years. Of those with calculated ESs, 32.1% of studies had medium or large effects, 50.0% very small or small effects, and 17.9% no effect or negative effects. When examining the percentage of studies yielding medium or large ESs across all groups, dynamic interventions (32.1%) compared favorably with broad (18.2%) or focused (25%) in-terventions.
The majority of interventions (12 of 30) examined hyper-tensive patients; others addressed patients with diabetes (3), dyslipidemia (5), congestive heart failure (6), cardiac disease (3), and mixed diseases (1).
Use of self-generated data in adherence feedback loop. We identified 24 articles (Table 3) that described adher-ence feedback loops based on self-generated data, and all but 1 had calculable ESs. Of those with calculated ESs, 34.8% yield-ed medium or large effects, 43.5% very small or small effects, and 21.7% negative or no effects.
All eight studies39–41,43,53,54,57,58 found to have a medium or large effect were dependent on the involvement of health pro-fessionals, and in all but one case,39 the professional was a pharmacist. Antonicelli et al.39 studied the effect of home tele-monitoring managed by a specialized heart failure team and did not specify the training of the person making the phone calls. Adherence feedback loops were initiated in these studies when a pharmacist (or in the case of Antonicelli et al., a caller whose training was not specified) inquired about medication adherence either in person or by phone. This often occurred multiple times during the intervention. When a patient self-identified as nonadherent, an individualized intervention was Ta
ble
2. B
road
inte
rven
tions
(tar
gete
d to
all m
edic
atio
n ta
kers
) des
igne
d to
impr
ove
adhe
renc
e to
car
diov
ascu
lar m
edic
atio
ns
Tabl
e 2 c
ontin
ued
Stew
art,
2005
, Jo
hann
esbu
rg, S
. Af
rica
83 h
yper
tens
ive
patie
nts,
ma-
jorit
y ind
igen
t; 36
wee
ks
Supp
ort o
f phy
siot
hera
pist
and
fam
ily m
em-
ber b
y pho
ne
Self-
desc
ribed
as a
dher
ent t
o m
edic
atio
ns
I, 82
.4%
; C, 8
6.7%
, P =
0.56
; ES
–0.1
2 (–
0.85
to 0.
61)
Taka
la, 1
983,
so
uthw
est F
inla
nd
147 u
ntre
ated
hyp
erte
nsiv
e pa
tient
s; 2
year
s M
aile
d in
form
atio
n on
hyp
erte
nsio
n
2 yea
rs a
fter i
nter
vent
ion,
ask
ed
if “s
till u
nder
trea
tmen
t afte
r 2
year
s”
Adhe
rent
: I, 9
0%; C
, 79%
, P =
NS;
ES
0.28
(–
0.14
to 0.
69)
van
Onze
noor
t, 20
09, t
he N
ethe
r-la
nds
228 h
yper
tens
ive
patie
nts;
1
year
Ho
me
self-
BP m
easu
rem
ent
%
of d
ays w
ith c
orre
ct d
osin
g;
MEM
S M
edia
n (IQ
R): I
, 92.
3% (8
6.9–
94.4
); C,
90
.9%
(82.
9–93
.7),
P =
0.04
3; E
S 0.
07
(0.0
4–0.
18)
Yilm
az, 2
005,
An-
kara
, Tur
key
202 p
atie
nts o
n st
atin
for s
ec-
onda
ry p
reve
ntio
n; 15
mon
ths
Educ
atio
n in
clud
ing
phys
icia
n co
nver
satio
n on
stat
ins
Odds
of b
eing
on
cont
inu-
ous s
tatin
(afte
r med
ian
of 15
m
onth
s); s
elf-r
epor
t
I, m
ore
likel
y to
be o
n co
ntin
uous
stat
in,
OR 1.
977 (
1.12
7–3.
468)
; ES
0.53
(0.2
5, 0.
82)
Abbr
evia
tions
use
d: A
C, a
ugm
ente
d co
nven
ienc
e; A
E, a
dditi
onal
edu
catio
n; B
P, b
lood
pre
ssur
e; C
, con
trol g
roup
; CHF
, con
gest
ive
hear
t fai
lure
; ES,
effe
ct si
ze; I
, inte
rven
tion
grou
p; IQ
R, in
terq
uarti
le ra
nge;
MEM
S, m
edic
atio
n ev
ent m
onito
ring
syst
em; M
I, m
yoca
rdia
l infa
rctio
n; M
PR, m
edic
atio
n po
sses
sion
ratio
; NS,
non
sign
ifica
nt; O
R, o
dds r
atio
; PCP
, prim
ary c
are
prov
ider
; RR,
rate
ratio
. a Du
ratio
n in
dica
tes t
ime
until
last
follo
w-u
p at
whi
ch a
dher
ence
was
mea
sure
d.
b Cont
rol p
atie
nts r
ecei
ved
usua
l car
e un
less
oth
erw
ise
spec
ified
c 95
% C
I unl
ess o
ther
wis
e sp
ecifi
ed.
For a
ll stu
dies
whe
re m
eans
(±SD
) for
adh
eren
ce o
utco
mes
wer
e av
aila
ble,
Coh
en’s
d st
atis
tics w
ere
calc
ulat
ed. T
he E
Ss c
ompa
re th
e di
ffere
nce
in e
ffect
bet
wee
n th
e st
udy g
roup
s div
ided
by t
he S
D of
this
diff
eren
ce. W
e co
n-si
dere
d an
ES
<0.2
to b
e ve
ry sm
all, 0
.2–0
.5 sm
all, 0
.5–0
.8 m
ediu
m, a
nd >
0.8 l
arge
.
J o u r n a l o f t h e A m e r i c a n P h a r m a c i s t s A s s o c i a t i o n www.japha.org M ay /J u n 2012 • 52:3 • JAPhA • 389
MEDICATION ADHERENCE INTERVENTIONS ReviewsTa
ble
3. D
ynam
ica m
edic
atio
n ad
here
nce
inte
rven
tions
: Cla
ssifi
ed b
y typ
e of
adh
eren
ce d
ata
used
in a
dher
ence
feed
back
loop
b
Aut
hor,
year
, site
Pa
rtici
pant
s,
dura
tionc
Inte
rven
tiond
Met
hod
of ta
rget
ing
inte
rven
tion
grou
p no
nadh
erer
sA
dher
ence
mea
sure
se O
utco
mes
, Coh
en’s
d E
Ss
(95%
CI)f
Self-
gene
rate
d ad
-he
renc
e da
ta o
nly
Anto
nice
lli, 2
008,
Ita
ly
57 h
ospi
taliz
ed C
HF
patie
nts,
age
>70
ye
ars;
12 m
onth
s
I: ho
me
tele
mon
itorin
g m
anag
ed
by sp
ecia
lized
CHF
team
Wee
kly c
alls
by C
HF te
am c
ol-
lect
ing
info
rmat
ion
on sy
mpt
oms,
ad
here
nce.
Reg
imen
adj
ustm
ent
base
d on
feed
back
% a
dher
ent p
atie
nts (
no
furth
er d
efini
tion)
I: 91
%; C
: 46%
, P <
0.03
; ES
1.12
(0.5
2–1.
69)
Blen
kins
opp,
2000
, U.
K.
282 h
yper
tens
ive
patie
nts f
rom
com
-m
unity
pha
rmac
ies;
6 m
onth
s
I: Ph
arm
acis
t cou
nsel
: stru
ctur
ed
ques
tions
, med
icat
ion
advi
ce,
hype
rtens
ion
teac
hing
, eve
ry 2
m
onth
s
Phar
mac
ist g
ave
advi
ce (v
erba
l or
writ
ten)
; pha
rmac
ist m
ight
re
fer t
o GP
or s
peak
dire
ctly
with
GP
% a
dher
ent p
atie
nts;
mod
i-fie
d ve
rsio
n of
Hor
ne’s
m
edic
atio
n ad
here
nce
repo
rt sc
ale
used
I: 62
.9%
; C: 5
0.0%
, P <
0.05
; ES
0.56
(0.2
9–0.
84)
Bouv
y, 20
03, t
he
Net
herla
nds
152 C
HF p
atie
nts,
in
patie
nt a
nd o
utpa
-tie
nt; 6
mon
ths
I: Co
mm
unity
pha
rmac
ist:
stru
c-tu
red
inte
rvie
w u
sing
com
pute
r-ize
d m
edic
atio
n re
cord
at i
nitia
l en
coun
ter,
disc
usse
d m
edic
a-tio
ns, n
onad
here
nce
Mon
thly
pha
rmac
ist c
onta
ct; d
is-
cuss
ion
of re
ason
s for
non
adhe
r-en
ce a
nd re
info
rced
adh
eren
ce
Adhe
renc
e ba
sed
on %
of
day
s with
out o
peni
ng
pill b
ottle
; non
adhe
renc
e de
fined
as <
80%
of d
ays;
M
EMS
% n
onad
here
nt p
atie
nts;
I:
0%; C
: 14%
; RR
0.5;
CI
0.4–
0.6;
ES
0.57
(0.1
4–1.
00)
Edw
orth
y, 20
07, C
al-
gary
, Can
ada
2,64
3 car
diac
pa-
tient
s afte
r hos
pita
l-iza
tion;
19 m
onth
s
I: In
-hos
pita
l indi
vidu
al a
nd g
roup
co
unse
ling
on m
edic
atio
ns a
nd
med
ical
con
ditio
ns; v
ideo
s,
prin
ted
mat
eria
ls; d
evel
oped
long
-te
rm m
edic
atio
n pl
ans;
follo
w-u
p co
ntac
t by p
harm
acis
t onc
e an
d m
onth
ly b
y nur
se
Nur
ses a
nd p
harm
acis
ts id
enti-
fied
and
addr
esse
d m
edic
atio
n pr
oble
ms;
com
mun
ity p
harm
a-ci
sts c
ouns
eled
inte
rven
tion
patie
nts
% o
f adh
eren
t pat
ient
s (no
t fu
rther
defi
ned)
; sel
f-rep
ort
data
on
med
icat
ion
use
colle
cted
by:
I: n
urse
s; C
: no
nmed
ical
staf
f
Beta
-blo
cker
s: I:
89%
; C:
80%
, P <
0.01
; lipi
d-lo
wer
-in
g ag
ents
: I: 8
3%; C
: 78%
, P
< 0.
05; E
S 0.
04 (–
0.07
to 0.
14)
Faul
kner
, 200
0,
Omah
a, N
E
30 p
atie
nts p
ost-
CABG
, PTC
A, o
r bo
th (7
–30 d
ays)
; 2
year
s
I: W
eekl
y pha
rmac
ist c
alls
(12
wee
ks);
all r
ecei
ved
lova
stat
in
daily
and
col
estip
ol tw
ice
daily
Wee
kly p
hone
cal
l to
chec
k on
adhe
renc
e, m
edic
atio
n is
sues
, an
d co
sts;
ask
ed a
bout
spec
ific
reas
ons f
or n
onad
here
nce.
Patie
nts r
etur
ning
mor
e th
an 20
% o
f pre
scrib
ed
pills
and
thos
e fa
iling
to
fill 8
0% o
r mor
e of
scrip
ts
at 1
and
2 yea
rs w
ere
cons
ider
ed n
onad
here
nt;
phar
mac
y rec
ords
% a
dher
ent p
atie
nts:
lo-
vast
atin
: I: 1
year
, 67%
; 2
year
s: 60
%; C
: 1 ye
ar: 3
3%;
2 yea
rs: 2
7%, P
< 0.
05 fo
r all
valu
es (c
oles
tipol
find
ings
si
mila
r, no
t sho
wn
here
); ES
0.54
(–0.
19 to
1.27
)Fr
iedm
an, 1
996,
Bo
ston
299 h
yper
tens
ive
patie
nts;
6 m
onth
s
I: In
tera
ctiv
e co
mpu
ter-
base
d ho
me
mon
itorin
g. P
atie
nt se
lf-BP
ch
ecks
, wee
kly c
alls
to c
ouns
el
on a
dher
ence
Auto
mat
ed p
hone
cou
nsel
ing
on
adhe
renc
e; d
ata
colle
cted
wee
kly
and
trans
mitt
ed to
PCP
MPR
(exp
ress
ed a
s per
-ce
nt);
hom
e pi
ll cou
nt;
adhe
rers
: MPR
≥80
%
Mea
n Δ
adhe
renc
e, u
nad-
just
ed: I
: +2.
4%; C
: –0.
4%,
P =
0.29
; adj
uste
d fo
r bas
e-lin
e ad
here
nce:
I: 17
.7%
; C:
11.7
%, P
= 0.
03; E
S 0.
13
(–0.
12 to
0.37
)Gu
thrie
, 200
1, O
hio
13,1
00 p
atie
nts w
ith
elev
ated
tota
l cho
-le
ster
ol; 6
mon
ths
I: Po
stal
, pho
ne re
min
ders
abo
ut
coro
nary
risk
redu
ctio
n an
d m
edi-
catio
n ad
here
nce
Dire
ctly
repo
rted
prav
asta
tin a
d-he
renc
e to
thei
r phy
sici
ans (
alon
g w
ith lif
esty
le c
hang
es, a
dver
se
even
ts) a
t 3 m
onth
s
Taki
ng p
rava
stat
in a
s pr
escr
ibed
per
self-
repo
rt:
yes/
no
Taki
ng a
s pre
scrib
ed: I
: 79
.7%
; C: 7
7.4%
; aut
hors
co
nclu
de “n
o m
eani
ngfu
l di
ffere
nce”
; ES
0.06
(–0.
02
to 0.
13)
J o u r n a l o f t h e A m e r i c a n P h a r m a c i s t s A s s o c i a t i o nwww.japha.org390 • JAPhA • 52:3 • M ay /J u n 2012
Reviews MEDICATION ADHERENCE INTERVENTIONS
Tabl
e 3.
Dyn
amic
a med
icat
ion
adhe
renc
e in
terv
entio
ns: C
lass
ified
by t
ype
of a
dher
ence
dat
a us
ed in
adh
eren
ce fe
edba
ck lo
opb
Tabl
e 3 c
ontin
ued
Hunt
, 200
8, O
rego
n
463 u
ncon
trolle
d hy
perte
nsiv
e pa
-tie
nts;
12 m
onth
s
I: Co
mm
unity
pha
rmac
ists
man
-ag
ed h
yper
tens
ion
in P
CP o
ffice
(h
ad P
CP in
put)
Indi
vidu
alize
d ph
arm
acis
t cou
n-se
ling
incl
udin
g id
entifi
catio
n of
ad
here
nce
barr
iers
; fol
low
-up
inte
rval
varie
d
% w
ith h
igh
adhe
renc
e,
cate
goriz
ed b
y Mor
isky
sc
ale;
self-
repo
rt
I: 67
%; C
: 69%
, P =
0.77
; ch
ange
in I:
P =
0.08
; ch
ange
in C
: P =
0.52
; ES
–0.0
4 (–0
.29 t
o 0.
20)
Jaffr
ay, 2
007,
U.K
.
1,49
3 CAD
pat
ient
s fro
m p
rimar
y car
e or
gani
zatio
ns; 1
2 m
onth
s
Com
mun
ity p
harm
acis
t ass
esse
d th
erap
y, a
dher
ence
, life
styl
e, so
-ci
al su
ppor
t
All p
artic
ipan
ts g
ot in
itial
con
sult;
fu
rther
con
sults
at p
harm
acis
t di
scre
tion
base
d on
ass
esse
d ad
here
nce
and
othe
r nee
ds
Adhe
renc
e sc
ore
(12–
60)
base
d on
12 q
uest
ions
; se
lf-re
port
I: 59
(IQR
57–6
0); C
: 59
(57–
60);
OR 1.
0 (95
% C
I 0.
61–1
.65)
, P =
0.99
; ES:
un
able
to c
alcu
late
Kran
tz, 2
008,
Den
ver,
CO
64 C
HF p
atie
nts w
ith
ejec
tion
fract
ion
<40%
; 6 m
onth
s
Preh
ospi
tal d
isch
arge
car
vedi
lol
initi
atio
n an
d nu
rse
coun
selin
g w
ith o
utpa
tient
nur
se m
anag
e-m
ent
2 wee
ks a
fter d
isch
arge
, met
w
ith n
urse
man
ager
, the
n ev
ery 2
w
eeks
unt
il dee
med
stab
le; c
oun-
selin
g, in
clud
ing
on a
dher
ence
Beta
-blo
cker
util
izatio
n;
on m
edic
atio
n (y
es/n
o); p
ill
coun
t
Beta
-blo
cker
util
izatio
n:
at d
isch
arge
: C: 9
.4%
; I:
96.9
%; 6
mon
ths:
C: 4
7.8%
; I:
96.2
%; u
tiliza
tion
sig-
nific
antly
hig
her f
or I a
t all
time
perio
ds (P
< 0.
001)
; ES
0.30
(–0.
29 to
0.89
)Lo
gan,
1983
, Tor
onto
, Ca
nada
194 h
yper
tens
ive
patie
nts;
1 ye
ar
I: W
orks
ite c
are
by p
hysi
cian
plu
s nu
rse
Non
adhe
rent
pat
ient
s cou
nsel
ed
on m
edic
atio
n di
ary,
tailo
red
regi
-m
en, h
ome
BP; in
crea
sed
visi
t fre
quen
cy; n
urse
hom
e ph
one
call
for m
isse
d vi
sits
% a
dher
ent p
atie
nts (
≥80%
of
pre
scrib
ed m
edic
atio
n ta
ken)
; hom
e pi
ll cou
nt
I: 55
.4%
; C: 5
5.7%
, P =
NS;
ES
–0.
01 (–
0.31
to 0.
29)
Odeg
ard,
2005
, Se-
attle
, WA
77 p
artic
ipan
ts w
ith
A1C
≥9%
taki
ng
diab
etes
med
ica-
tion;
12 m
onth
s
I: Pr
imar
y car
e ph
arm
acis
t de-
velo
ped
care
pla
n, in
-per
son
or
phon
e m
eetin
gs (w
eekl
y, th
en
mon
thly
)
Adhe
renc
e as
sess
ed a
t bas
elin
e,
6 mon
ths,
and
12 m
onth
s; p
harm
a-ci
st g
ave
regu
lar a
dvic
e to
pat
ient
an
d pr
ovid
er w
here
nee
ded;
ad-
dres
sed
diab
etes
car
e, m
edic
a-tio
n pr
oble
ms
Adhe
renc
e ba
sed
on 2
qu
estio
ns: “
Do yo
u ev
er
find
it di
fficu
lt to
rem
em-
ber t
o ta
ke (m
edic
atio
n na
me)
?” If
yes,
“How
man
y tim
es o
ver t
he la
st 2
wee
ks
have
you
mis
sed
a do
se?”
C sh
owed
bet
ter a
dher
-en
ce th
an I t
hrou
ghou
t st
udy (
P =
0.00
3); E
S –0
.73
(–1.
25 to
–0.
21)
Oged
egbe
, 200
8,
New
Yor
k
190 h
yper
tens
ive
patie
nts,
bla
ck
race
/eth
nici
ty, m
ost
wom
en; 1
2 mon
ths
I: M
otiv
atio
nal in
terv
iew
ing
with
pa
tient
-cen
tere
d co
unse
ling
by
rese
arch
ass
ista
nts w
ho e
licite
d ad
here
nce
barr
iers
, dis
cuss
ed
solu
tions
Asse
ssm
ents
eve
ry 3
mon
ths
base
d on
pat
ient
verb
ally
dis
-cu
ssin
g ad
here
nce
barr
iers
; M
EMS
data
are
dow
nloa
ded
but
not u
sed
at th
ose
visi
ts
MPR
, exp
ress
ed a
s %;
MEM
S
I: 60
%; C
: 47%
, P =
0.05
4;
inte
nt-to
-trea
t ana
lysi
s sh
owed
mod
el-p
redi
cted
ra
tes:
I: 57
%; C
: 43%
, P =
0.
027;
ES
0.13
(–0.
01 to
0.27
)Pi
ette
, 200
0, C
ali-
forn
ia
280 d
iabe
tes p
a-tie
nts o
n hy
pogl
y-ce
mic
med
icat
ions
; in
clud
ed S
pani
sh-
spea
king
pat
ient
s;
12 m
onth
s
I: Bi
wee
kly a
utom
ated
ass
ess-
men
t/edu
catio
n ca
lls: h
iera
rchi
-ca
lly st
ruct
ured
mes
sage
s with
ta
rget
ed n
urse
follo
w-u
p ca
lls
In a
utom
ated
cal
ls, p
atie
nts g
iven
po
sitiv
e fe
edba
ck a
nd re
info
rce-
men
t; no
nadh
erer
s wer
e as
ked
abou
t bar
riers
, giv
en a
utom
ated
ad
vice
with
targ
eted
, prio
ritize
d nu
rse
phon
e fo
llow
-up;
nur
se
calle
d th
ose
who
rare
ly re
spon
d-ed
to a
utom
ated
cal
ls
Abbr
evia
ted
Mor
isky
in-
dex;
pat
ient
s con
side
red
nona
dher
ent i
f the
y som
e-tim
es fo
rgot
or s
topp
ed
med
icat
ion;
pho
ne in
ter-
view
s, se
lf-re
port
I: “S
ubst
antia
lly le
ss lik
ely”
to
repo
rt ad
here
nce
prob
-le
ms (
P =
0.00
3); E
S 0.
38
(0.1
2–0.
63)
J o u r n a l o f t h e A m e r i c a n P h a r m a c i s t s A s s o c i a t i o n www.japha.org M ay /J u n 2012 • 52:3 • JAPhA • 391
MEDICATION ADHERENCE INTERVENTIONS Reviews
Tabl
e 3.
Dyn
amic
a med
icat
ion
adhe
renc
e in
terv
entio
ns: C
lass
ified
by t
ype
of a
dher
ence
dat
a us
ed in
adh
eren
ce fe
edba
ck lo
opb
Tabl
e 3 c
ontin
ued
Plan
as, 2
009,
Okl
a-ho
ma
52 d
iabe
tes a
nd
hype
rtens
ive
man
-ag
ed c
are
patie
nts;
9 m
onth
s
I: M
onth
ly in
-per
son
com
mun
ity
phar
mac
ist c
ouns
elin
g; id
entifi
ed
and
addr
esse
d m
edic
atio
n pr
ob-
lem
s, lif
esty
le c
ouns
elin
g
Phar
mac
ist a
sses
ses a
nd e
n-co
urag
es a
dher
ence
, com
mun
i-ca
tes p
robl
ems t
o PC
P vi
a no
te
Used
MPR
bas
ed o
n pr
escr
iptio
n cl
aim
s dat
a fro
m m
anag
ed c
are
or-
gani
zatio
n; o
nly i
nclu
ded
pres
crip
tions
with
≥3
cons
ecut
ive
refil
ls in
the
9 mon
ths b
efor
e or
afte
r ba
selin
e vi
sit
Mea
n ad
here
nce
(%):
I: 87
.5 (C
I 82.
1–93
.0);
C: 78
.8
(CI 6
9.7–
87.9
); ES
0.54
(0
.13–
1.21
)
Sadi
k, 20
05, A
l-Ain
, Un
ited
Arab
Em
irate
s
221 C
HF p
atie
nts;
12
mon
ths
I: St
ruct
ured
pha
rmac
ist c
ouns
el
(in c
linic
or h
ospi
tal);
CHF
and
m
edic
atio
n ed
ucat
ion,
boo
klet
Phar
mac
ist v
isits
with
cou
nsel
ing
ever
y 3 m
onth
s; se
lf-m
onito
ring:
1-
mon
th c
ard
(pha
rmac
ist r
e-vi
ewed
regu
larly
, tol
d to
brin
g to
PC
P); p
harm
acis
t spo
ke w
ith P
CP
as n
eede
d
“Pat
ient
self-
repo
rt on
m
issi
ng d
ose
or ta
k-in
g ex
tra d
oses
with
out
med
ical
adv
ice”
; no
furth
er
defin
ition
Num
ber o
f adh
eren
t pa-
tient
s: I:
85; C
: 35,
P <
0.05
; ES
1.26
(0.9
9–1.
54)
Sche
ctm
an, 1
994,
M
ilwau
kee,
WI
162 p
atie
nts w
ith
dysl
ipid
emia
; 6
mon
ths
I: W
eekl
y pho
ne c
ouns
el in
1st
mon
th o
f the
rapy
by m
edic
al
assi
stan
t; ea
ch g
roup
als
o ra
n-do
mize
d to
nia
cin
vs. b
ile a
cid
sequ
estra
nts
Info
rmat
ion
on m
edic
atio
n ad
her-
ence
and
pro
blem
s gat
here
d by
ph
one
and
at 2-
mon
th c
linic
visi
ts;
med
ical
ass
ista
nt o
ffere
d ad
vice
on
adv
erse
effe
cts,
arr
ange
d ph
arm
acis
t or p
hysi
cian
pho
ne
cont
act a
s nee
ded
MPR
; pha
rmac
y cla
ims
% a
dher
ence
(mea
n ±
SD):
bile
aci
d se
ques
trant
s (m
ean
± SD
): I:
88 ±
SD
4;
C: 82
± 4,
P =
0.32
; nia
cin:
I:
90 ±
2; C
: 84 ±
3, P
= 0.
07; E
S 0.
41 (–
0.05
to 0.
86)
Schr
oede
r, 20
05,
Avon
, U.K
.
245 h
yper
tens
ive
patie
nts;
6 m
onth
s
I: N
urse
-led
adhe
renc
e su
ppor
t se
ssio
ns
Rein
forc
emen
t con
sult
2 mon
ths
afte
r ran
dom
izatio
n: n
urse
spok
e to
pat
ient
s abo
ut a
dher
ence
ch
alle
nges
but
had
no
acce
ss to
M
EMS
data
at t
hat t
ime
MPR
(exp
ress
ed a
s %);
MEM
S, u
sed
for 1
med
ica-
tion
only
Mea
n ±
SD: I
: 95.
6 ± 16
.4; C
: 95
.6 ±
15.7
, P =
0.76
; ES
0.06
(–
0.24
to 0.
35)
Solo
mon
, 199
8, m
ul-
tiple
site
s
133 h
yper
tens
ive
patie
nts;
6 m
onth
s
I: St
anda
rdize
d ph
arm
acy c
are:
m
onth
ly p
atie
nt a
sses
smen
t, di
s-ea
se m
anag
emen
t, an
d ed
ucat
ion
Mon
thly
pha
rmac
ist a
dher
ence
as
sess
men
t, in
clud
es d
evel
op-
men
t of a
dher
ence
aid
as n
eede
d
Adhe
renc
e sc
ore
base
d on
4-po
int M
oris
ky sc
ale;
se
lf-re
port
Mea
n ±
SD: I
: 0.2
3 ± 0.
054;
C:
0.61
± 0.
094,
P <
0.05
co
mpa
red
with
in a
nd
betw
een
grou
ps; E
S 0.
57
(0.2
1–0.
93)
Sook
anek
nun,
2004
, ur
ban
and
rura
l Th
aila
nd
235 h
yper
tens
ive
patie
nts f
rom
pha
r-m
acy a
nd p
rimar
y ca
re; 6
mon
ths
I: Re
sear
ch p
harm
acis
t con
sult:
as
sess
ed m
edic
atio
n un
ders
tand
-in
g, a
dher
ence
, cou
nsel
ed o
n us
e, lif
esty
le; e
duca
tiona
l leafl
ets,
di
ary
Regu
lar p
harm
acis
t vis
its (a
ppea
r to
be
mon
thly
) to
iden
tify a
nd
addr
ess m
edic
atio
n pr
oble
ms;
re
com
men
datio
ns g
iven
to p
hy-
sici
ans b
y let
ter a
nd b
y not
e in
m
edic
al re
cord
Calc
ulat
ed M
PR, e
x-pr
esse
d as
%; ≥
80%
nec
-es
sary
to b
e co
nsid
ered
ad
here
nt
% o
f adh
eren
t pat
ient
s:
I: 63
.64%
; C: 5
5.56
%, P
=
0.01
4; E
S 0.
60 (0
.33–
0.87
)
J o u r n a l o f t h e A m e r i c a n P h a r m a c i s t s A s s o c i a t i o nwww.japha.org392 • JAPhA • 52:3 • M ay /J u n 2012
Reviews MEDICATION ADHERENCE INTERVENTIONS
Tabl
e 3.
Dyn
amic
a med
icat
ion
adhe
renc
e in
terv
entio
ns: C
lass
ified
by t
ype
of a
dher
ence
dat
a us
ed in
adh
eren
ce fe
edba
ck lo
opb
Tabl
e 3 c
ontin
ued
Stac
y, 20
09, M
assa
-ch
uset
ts
497 n
ew st
atin
us-
ers;
6 m
onth
s
I: In
tera
ctiv
e vo
ice
resp
onse
te
leph
one
tech
nolo
gy p
rovi
ding
ta
ilore
d m
edic
atio
n co
unse
ling;
m
aile
d le
tters
Inte
ract
ive
voic
e re
spon
se p
ro-
vide
d ta
ilore
d m
essa
ges r
einf
orc-
ing
adhe
renc
e ba
sed
on p
atie
nt
resp
onse
s
6-m
onth
poi
nt p
reva
lenc
e pe
rsis
tenc
y: p
osse
ssio
n of
stat
in a
t end
of 1
80-d
ay
perio
d ba
sed
on c
laim
s re
cord
s; a
lso
prov
ide
MPR
Poin
t pre
vale
nce
pers
is-
tenc
y: I:
70.4
%; C
: 60.
7%, P
<
0.05
; MPR
>80
%: I
: 47.
0%;
C: 38
.9%
, P <
0.10
; ES
0.08
(0
.01–
0.17
)Ts
uyuk
i, 200
4,
Cana
da
276 p
atie
nts w
ith
CHF d
isch
arge
d fro
m h
ospi
tal; 6
m
onth
s
I: Ph
one
call a
t 2 w
eeks
, 4 w
eeks
, th
en m
onth
ly; e
duca
tion;
adh
er-
ence
aid
s (or
gani
zer,
sche
dule
), ph
one,
mai
l fol
low
-up;
C: p
amph
let
Rese
arch
coo
rdin
ator
cal
led
patie
nts t
o as
sess
ACE
I use
, re
info
rced
adh
eren
ce; a
dvis
ed
patie
nts t
o co
nsul
t phy
sici
an fo
r AC
EI d
ose
chan
ge, m
edic
atio
n pr
oble
ms
MPR
for A
CE in
hibi
tor,
expr
esse
d as
%; p
harm
acy
reco
rds
% a
dher
ence
(mea
n ±
SD):
I: 83
.5 ±
31.2
; C: 8
6.2 ±
29.0
, P
= 0.
691;
ES
–0.0
9 (–0
.33
to 0.
15)
Varm
a, 19
99, N
orth
-er
n Ire
land
83 e
lder
ly C
HF p
a-tie
nts f
ollo
wed
afte
r ho
spita
l dis
char
ge;
12 m
onth
s
I: In
-per
son
com
mun
ity p
harm
a-ci
st c
ouns
elin
g on
CHF
med
ica-
tions
, adh
eren
ce, li
fest
yle;
dos
e si
mpl
ifica
tion;
sym
ptom
mon
itor-
ing
Ever
y 3 m
onth
s: a
sses
sed
adhe
r-en
ce w
ith p
resc
ribed
dru
gs, in
-cl
udin
g re
view
of d
rug
diar
y car
ds
Adhe
renc
e de
fined
as
80–1
20%
of m
edic
atio
ns
take
n fo
r all C
HF d
rugs
as-
sess
ed; p
harm
acy r
ecor
ds
% o
f adh
eren
t pat
ient
s: I:
76
.9; C
: 30,
P =
0.03
9; E
S 0.
30
(–0.
29 to
0.89
)
Vivi
an, 2
002,
Phi
la-
delp
hia
56 m
ale
hype
r-te
nsiv
e pa
tient
s,
maj
ority
bla
ck; 6
m
onth
s
I: M
onth
ly p
harm
acis
t cou
nsel
ing;
ch
ange
d dr
ugs,
adj
uste
d do
ses
Adhe
renc
e as
sess
men
t and
co
unse
ling
at e
ach
visi
t
Non
adhe
renc
e m
eant
fail-
ure
to re
fill w
ithin
2 w
eeks
of
sche
dule
d re
fill d
ate
or m
issi
ng >
3 dos
es in
1
wee
k; p
harm
acy r
ecor
ds
% o
f adh
eren
t pat
ient
s: I:
85
; C: 9
3, P
> 0.
42; E
S –0
.26
(–0.
81 to
0.29
)
Exte
rnal
adh
eren
ce
data
(alo
ne o
r in
com
bina
tion
with
se
lf-ge
nera
ted
data
)Jo
hnso
n, 20
06,
Mas
sach
uset
ts a
nd
Rhod
e Is
land
404 a
dults
with
dy
slip
idem
ia; 1
8 m
onth
s
I: Po
pula
tion-
base
d, c
ompu
ter-
gene
rate
d in
divi
dual
ized
inte
rven
-tio
n as
sess
ing
stag
e of
cha
nge
(pre
cont
empl
atio
n, c
onte
mpl
a-tio
n, p
repa
ratio
n, a
ctio
n, m
aint
e-na
nce)
via
ques
tionn
aire
Writ
ten
repo
rt m
aile
d to
pat
ient
(w
ithin
1 w
eek o
f ass
essm
ent)
prov
idin
g fe
edba
ck: (
1) a
t bas
e-lin
e (c
ompa
rison
with
oth
ers t
ry-
ing
to c
hang
e ad
here
nce
beha
v-io
r) an
d (2
) at t
wo
follo
w-u
p po
ints
(c
ompa
rison
with
gro
up a
nd w
ith
indi
vidu
al’s
pas
t res
pons
es)
Resp
onse
s to
5 que
stio
ns
(on
Like
rt sc
ale)
sum
med
to
cre
ate
a co
ntin
uous
m
easu
re; c
alcu
late
d od
ds
of a
ppro
pria
te a
dher
ence
; se
lf-re
port
Adhe
renc
e as
con
tinuo
us
mea
sure
: 6-m
onth
OR
2.03
, P
> 0.
05; 1
8-m
onth
OR
2.86
, P
< 0.
05; E
S 0.
18 (–
0.08
to
0.45
)
Mur
ray,
2007
, Ind
ia-
napo
lis, I
N
314 h
yper
tens
ive
patie
nts f
rom
inne
r-ci
ty p
ract
ice;
12
mon
ths
I: Ph
arm
acis
t med
icat
ion
hist
ory,
kn
owle
dge
asse
ssm
ent,
verb
al,
writ
ten
educ
atio
n; b
oth
in-p
erso
n an
d m
onth
ly p
hone
con
tact
Phar
mac
ist a
dher
ence
cou
nsel
-in
g in
clud
ed o
ptio
n to
revi
ew
MEM
S pl
ot w
ith p
atie
nt, e
ngag
e pa
tient
in p
robl
em so
lvin
g
% o
f pre
scrib
ed m
edic
a-tio
n ta
ken;
MEM
S
Durin
g in
terv
entio
n: I:
78
.8%
; C: 6
7.9%
; diff
eren
ce:
10.9
% (C
I 5.0
–16.
7); p
ostin
t-er
vent
ion
diffe
renc
e: 3.
9%
(CI:
–2.8
to 10
.7);
ES 0.
08
(–0.
89 to
1.06
)
J o u r n a l o f t h e A m e r i c a n P h a r m a c i s t s A s s o c i a t i o n www.japha.org M ay /J u n 2012 • 52:3 • JAPhA • 393
MEDICATION ADHERENCE INTERVENTIONS Reviews
Tabl
e 3.
Dyn
amic
a med
icat
ion
adhe
renc
e in
terv
entio
ns: C
lass
ified
by t
ype
of a
dher
ence
dat
a us
ed in
adh
eren
ce fe
edba
ck lo
opb
Tabl
e 3 c
ontin
ued
Phum
ipa-
mor
n,
2008
, Kra
bi P
rovi
nce,
Th
aila
nd
135 M
uslim
di
abet
es p
atie
nts;
8
mon
ths
I: Ph
arm
acis
t mee
ting
day o
f phy
-si
cian
visi
t; vi
sit r
emin
der 3
day
s pr
ior;
give
n re
fills
, life
styl
e an
d m
edic
atio
n ed
ucat
ion
Rese
arch
pha
rmac
ist r
efille
d m
edic
atio
ns, c
heck
ed p
ill c
ount
, an
d ad
vise
d on
med
icat
ions
be
fore
usu
al P
CP vi
sit (
ever
y 4–8
w
eeks
).
MPR
(exp
ress
ed a
s %);
pill
coun
t
Mea
n di
ffere
nce
(CI):
I:
+6.8
% (2
.1–1
1.4)
, P =
0.00
5;
C: –
2.8 (
–7.3
1 to
1.7)
, P =
0.
29; b
etw
een-
grou
p m
ean
diffe
renc
e P
= 0.
004;
ES
0.50
(0.1
5–0.
86)
Robi
nson
, 201
0,
Tam
pa, F
L
376 p
atie
nts o
n hy
perte
nsio
n m
edic
atio
ns w
ith
unco
ntro
lled
BP;
7–12
mon
ths
I: M
onth
ly (o
r mor
e fre
quen
t) in
-per
son
phar
mac
ist c
ouns
el-
ing
incl
udes
lifes
tyle
, med
icat
ion
adhe
renc
e ed
ucat
ion
Phar
mac
ist g
ives
tailo
red
adhe
r-en
ce im
prov
emen
t stra
tegi
es,
base
s fee
dbac
k on
self-
repo
rt an
d us
e of
refil
l his
tory
to o
btai
n es
timat
ed ra
te o
f adh
eren
ce
MPR
(mea
n ad
here
nce
rate
); ph
arm
acy r
ecor
ds
1–6 m
onth
per
iod
(mea
n ±
SD):
I: 0.
91 ±
0.15
; C: 0
.78 ±
0.
30, P
= 0.
02; 7
–12 m
onth
pe
riod:
I: 0.
91 ±
0.15
; C: 0
.83
± 0.
28, P
= 0.
09; E
S 0.
36
(0.1
5–0.
86)
Tam
blyn
, 200
9, M
on-
treal
and
Que
bec,
Ca
nada
2,29
3 pat
ient
s on
lipid
-low
erin
g or
hy
perte
nsio
n m
edi-
catio
ns; 6
mon
ths
I: Co
mpu
teriz
ed c
ompl
ete
drug
pr
ofile
with
gra
phic
dis
play
s,
refil
l adh
eren
ce c
alcu
latio
n, a
nd
adhe
renc
e al
erts
as p
art o
f com
-pu
teriz
ed m
edic
al re
cord
use
d by
pr
imar
y car
e ph
ysic
ians
; C: c
om-
pute
rized
med
icat
ion
list a
lone
(u
sual
car
e)
Gaps
in g
raph
ical
ly d
ispl
ayed
m
edic
atio
n pr
ofile
(or n
umer
ical
da
ta) i
nfor
m p
hysi
cian
of n
on-
adhe
renc
e; if
adh
eren
ce <
80%
, ph
ysic
ian
got a
lert
whe
n op
enin
g m
edic
al c
hart,
told
to c
heck
dru
g pr
ofile
Mea
n re
fill a
dher
ence
: pr
opor
tion
of d
ays c
ov-
ered
; acc
esse
d vi
a da
ily
retri
eval
of c
ompu
teriz
ed
disp
ensi
ng in
form
atio
n;
real
-tim
e up
date
s of r
e-co
rds
I: 73
.5%
; C: 7
2.9%
; Δ m
ean
adhe
renc
e ±
SD: I
: –6.
2 ±
24.1
; C: –
6.4 ±
24.1
, P =
0.90
; ES
0.01
(–0.
08, 0
.09)
Vrije
ns, 2
006,
Bel
-gi
um
392 p
atie
nts w
ith
dysl
ipid
emia
on
ator
vast
atin
; 12
mon
ths
I: Ph
arm
acy p
rogr
am: m
edic
atio
n hi
stor
y edu
catio
nal r
emin
ders
, w
ritte
n in
form
atio
n; C
: writ
ten
info
rmat
ion
Phar
mac
ist s
its w
ith p
atie
nt a
nd
revi
ews e
lect
roni
cally
com
pile
d do
sing
his
tory
of p
ast m
onth
s;
patie
nt ta
ught
to re
ad M
EMS
grap
hics
% o
f day
s tha
t med
icat
ion
cont
aine
r ope
ning
was
re
cord
ed; M
EMS
I: 95
.89%
(CI 9
0.28
–98.
66);
C: 89
.37 (
69.7
0–96
.33)
, P <
0.
001;
ES:
una
ble
to c
al-
cula
te
Abbr
evia
tions
use
d: A
1C, g
lyco
syla
ted
hem
oglo
bin;
ACE
I, an
giot
ensi
n-co
nver
ting
enzy
me
inhi
bito
r; BP
, blo
od p
ress
ure;
C, c
ontro
l gro
up; C
AD, c
oron
ary a
rtery
dis
ease
; CHF
, con
gest
ive
hear
t fai
lure
; ES,
effe
ct si
ze; G
P, g
ener
al
prac
titio
ner;
I, in
terv
entio
n gr
oup;
IQR,
inte
rqua
rtile
rang
e; M
EMS,
med
icat
ion
even
t mon
itorin
g sy
stem
; MPR
, med
icat
ion
poss
essi
on ra
tio; N
S, n
onsi
gnifi
cant
; OR,
odd
s rat
io; P
CP, p
rimar
y car
e pr
ovid
er; P
TCA,
per
cuta
neou
s tra
nslu
min
al c
oron
ary a
ngio
plas
ty; R
R, ra
te ra
tio.
a Dyna
mic
inte
rven
tions
are
firs
t adm
inis
tere
d to
all m
edic
atio
n ta
kers
, the
n re
al-ti
me
adhe
renc
e in
form
atio
n is
use
d to
furth
er ta
rget
non
adhe
rers
. b An
adh
eren
ce fe
edba
ck lo
op is
cre
ated
whe
reby
adh
eren
ce d
ata
are
gene
rate
d an
d th
en fe
d ba
ck in
to th
e in
terv
entio
n. A
dher
ence
feed
back
loop
s use
eith
er (1
) sel
f-gen
erat
ed d
ata
alon
e or
(2) e
xter
nal d
ata
alon
e or
alo
ng w
ith
self-
gene
rate
d da
ta. S
elf-g
ener
ated
dat
a fe
edba
ck lo
ops w
ere
thos
e in
whi
ch th
e ta
ilorin
g of
the
inte
rven
tion
was
bas
ed e
ntire
ly o
n pa
tient
self-
repo
rt of
non
adhe
renc
e. E
xter
nal d
ata
feed
back
loop
s wer
e th
ose
in w
hich
info
rma-
tion
such
as M
PR d
eriv
ed fr
om p
harm
acy r
ecor
ds o
r oth
er e
xter
nal s
ourc
es w
as u
sed
to ta
ilor t
he in
terv
entio
n.
c Dura
tion
indi
cate
s tim
e un
til la
st fo
llow
-up
in w
hich
adh
eren
ce is
mea
sure
d.
d Cont
rol p
atie
nts r
ecei
ved
usua
l car
e un
less
oth
erw
ise
spec
ified
. e M
PR: m
edic
atio
n do
ses t
aken
div
ided
by d
oses
pre
scrib
ed. M
oris
ky sc
ale
has f
our q
uest
ions
(1 p
oint
for e
very
“yes
” res
pons
e): (
1) D
o yo
u ev
er fo
rget
to ta
ke yo
ur m
edic
atio
n?; (
2) A
re yo
u ca
rele
ss a
t tim
es a
bout
taki
ng yo
ur
med
icat
ion?
; (3)
Whe
n yo
u fe
el b
ette
r, do
you
som
etim
es st
op ta
king
your
med
icat
ion?
; (4)
Som
etim
es if
you
feel
wor
se w
hen
you
take
your
med
icat
ion,
do
you
stop
taki
ng it
?f 95
% C
I unl
ess o
ther
wis
e sp
ecifi
ed.
For a
ll stu
dies
whe
re m
eans
(±SD
) for
adh
eren
ce o
utco
mes
wer
e av
aila
ble,
Coh
en’s
d st
atis
tics w
ere
calc
ulat
ed. T
he E
Ss c
ompa
re th
e di
ffere
nce
in e
ffect
bet
wee
n th
e st
udy g
roup
s div
ided
by t
he S
D of
this
diff
eren
ce. W
e co
n-si
dere
d an
ES
<0.2
to b
e ve
ry sm
all, 0
.2–0
.5 sm
all, 0
.5–0
.8 m
ediu
m, a
nd >
0.8 l
arge
.
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Reviews MEDICATION ADHERENCE INTERVENTIONS
delivered based on the patient’s unique situation, incorporating components such as regimen adjustment, reinforcement, edu-cation, lifestyle counseling, advice on contacting physicians, and, in some cases, direct contact of primary physicians by the pharmacist.
A total of 10 studies yielded very small or small effects. Of these, four42,48,56,61 relied on health professionals. These four interventions had similar feedback structures to those described above, although nurses played the main role, with only one intervention mediated primarily by a pharmacist.61 Two interventions51,55 were carried out by lay persons including research assistants who conducted motivational interviews51 and medical assistants who provided medication counseling by phone.55 Three interventions44,52,59 made use of electronic systems including interactive computer-based home monitor-ing,44 interactive phone technology with tailored messages,59 and automated calls with structured messages and targeted nurse follow-up.52 One study in this group45 consisted mainly of postal and phone reminders but had patients reporting ad-herence directly to physicians at 3 months. There was no pre-specified physician response to nonadherence; in this case, we assumed that discussion occurred or medication changes were administered if patients reported nonadherence directly to the physician.
Similar to the most effective group, the five studies that showed no improvement in adherence23,46,50,60,62 were almost all conducted by health professionals. Hunt et al.46 reported the effect of pharmacist-managed hypertension, and Logan et al.23 described worksite hypertension management carried out by a nurse with physician support. Both had ESs very close to zero, as did Tsuyuki et al.,60 who examined the effect of lay person (research coordinator) phone calls in which adherence was reinforced and patients were referred to their physicians for questions or adherence concerns.
In contrast, Vivian62 studied monthly pharmacist counsel-ing, including regimen adjustments as needed, and found a small negative effect. Odegard et al.50 described the effect of a diabetes care plan developed by a primary care pharmacist along with follow-up meetings and calls but followed a group in which control patients showed better adherence than interven-tion patients.
Use of external data in adherence feedback loop. We identified six articles63–68 that described adherence feedback loops reliant on externally generated data; for one of these,68 an ES could not be calculated. Of those with calculated ESs, 20% (one study) yielded medium or large effects and 80% (four studies) very small or small effects.
The study of Phumipamorn et al. 65 was the only dynamic in-tervention to yield a medium to large ES while using an external adherence data feedback loop, and this study did not rely on au-tomated adherence data. Research pharmacists meeting with patients with diabetes on the day of their physician visit con-ducted pill counts and provided counseling along with refills.
The four dynamic interventions with very small or small ef-fects included three in which a health professional (pharmacist or physician) had access to electronic adherence data during
the patient interaction. Robinson et al.66 studied the effect of pharmacist adherence counseling using both self-reported ad-herence and pharmacy refill history.
Murray et al.64 described pharmacist adherence counseling in which pharmacists had the option to review electronic pill-box adherence data with patients and engage in problem-solv-ing based on these data. Pillbox data were reported to be avail-able in plot form for ease of communication; however, such a review was at the pharmacist’s discretion and not conducted with every patient. Tamblyn et al.67 described an intervention in which computerized complete drug profiles with graphic displays were made available to primary care physicians, in-corporating refill adherence calculation and adherence alerts as part of an electronic medical record already in use by physi-cians. One of the more complex systems for delivery of external adherence data directly to physicians, this study had a small and likely clinically insignificant ES (0.01 [CI –0.08 to 0.09]), although physicians overwhelmingly requested to have access to the graphics at the conclusion of the trial.
Johnson et al.21 used a computer-generated intervention assessing stage of change with respect to adherence behavior based on a questionnaire administered to patients.21 The exter-nal data in this feedback loop were a computerized interpreta-tion of patients’ readiness to change adherence behaviors that was delivered with patient-appropriate recommendations via a mailed written report to patients. The authors found that the odds of appropriate adherence were improved in the interven-tion group (OR 2.86) with a small ES (0.18 [–0.08 to 0.45]).
DiscussionCompared with broadly administered interventions, those that targeted nonadherers (either exclusively or in a dynamic fash-ion) tended to have a larger effect on medication adherence. In addition to the statistical heterogeneity reflected in our analy-ses, we found considerable clinical heterogeneity among the studies identified. Adherence measures differed between stud-ies both as an outcome and a means of defining a target group. This heterogeneity prevented us from pursuing a meta-analysis and prompted us to interpret all findings with caution. Our find-ings highlight the need for standardized approaches to adher-ence measurement.
With respect to dynamic interventions, our findings sup-port further attention to the unique components of the self-gen-erated dynamic intervention. Possible mechanisms for the rel-ative success we found among individuals participating in self-generated adherence feedback loops included an increased ability to provide tailored medication advice in real time and the requirement that patients have at least a degree of insight into their nonadherent behaviors.
Vrijens et al.68 called for increased use of health informa-tion technology to identify “patients for whom poor medica-tion adherence may undermine clinical goals and patients who could benefit from interventions aimed at achieving optimal medication use.” Despite this emphasis on health information technology, our study did not find any advantage to using ex-ternally generated data for dynamic feedback loops. Although
J o u r n a l o f t h e A m e r i c a n P h a r m a c i s t s A s s o c i a t i o n www.japha.org M ay /J u n 2012 • 52:3 • JAPhA • 395
MEDICATION ADHERENCE INTERVENTIONS Reviews
we acknowledge the heterogeneity of the studies and our dif-ficulty drawing firm conclusions on that basis, our findings do not support widescale implementation of automated electronic adherence feedback at this time. Further study in this regard is needed to demonstrate incremental benefit of this approach.
Focused interventions identify nonadherers before starting the intervention. This group provides very limited data, and the studies that exist do not consistently make use of reproducible, standardized methods for identifying nonadherers. This is an area that would benefit from additional studies, particularly ones in which better methods for identifying the focused popu-lation are presented.
Broad interventions appear to be least effective. Such in-terventions aim to prevent nonadherence by educating and motivating patients to adhere to treatment. Although many of these interventions were effective, their benefits were likely diluted because of the small effect of the intervention on pa-tients already inclined toward adherence. Moreover, without the benefit of identifying patients and their specific barriers to nonadherence, these interventions may have been too general to motivate individual patients to meaningfully change their behavior. In a resource-constrained health care system, broad interventions without a feedback loop may not provide the best return on investment.
The current results have important implications. Broad interventions are the least effective and potentially the most expensive; research is needed to more fully evaluate focused and dynamic interventions. Focused interventions allow limit-ed resources to be directed toward fewer, higher-risk patients, and dynamic interventions share this advantage when the more costly portion of the intervention is reserved for identified non-adherers. Attention must be paid, however, to the method of identifying nonadherers. None of the focused interventions that we identified made use of pharmacy claims data to iden-tify nonadherence. Focused studies were administered after a baseline period in which adherence data were gathered from a larger group of patients, or ascertainment of nonadherent status was based more loosely on a combination of physician documentation, self-report, and refill history. Dynamic inter-ventions were overwhelmingly dependent on self-generated adherence data (often requiring intensive interaction with a health provider), and very few used any form of external data. The accuracy, cost, and reproducibility of methods for identify-ing target populations must be a central consideration in future studies.
Based on our findings, we recommend further investigation of targeted adherence improvement efforts aimed at patients who are nonadherent. Methods for identifying nonadherence should be defined in advance as clearly as possible and evalu-ated for cost, validity, and reproducibility. As electronic phar-macy data become increasingly available, external adherence data should be explored as a means of focusing interventions from the outset and informing dynamic feedback loops; how-ever, we must keep in mind the limited effectiveness demon-strated to date.
LimitationsLimitations of our review included the substantial clinical and statistical heterogeneity of the identified studies, thereby pre-venting meta-analysis estimates from being presented. Other limitations included the variable quality of study methodology, the possibility for publication bias, the paucity of available information on intervention costs, and the lack of standard-ized methods to study this issue. Heterogeneous adherence outcome measures prompted us to translate adherence out-comes into Cohen’s d ESs, allowing for between-study com-parison but possibly providing a less direct measure of adher-ence improvement. Because variability existed in the degree of detail offered on the adherence interventions, we may have misclassified some interventions, although we do not expect that this would have occurred in a biased manner. Our deci-sion to exclude studies characterized by regimen simplifica-tion limits our ability to comment on this important group of adherence interventions. Success rates seen in focused inter-ventions may reflect their exclusion of already-adherent pa-tients, for whom any intervention would yield little additional improvement. Because dynamic and broad interventions mea-sure improvements in adherence for the whole population, we were unable to directly compare the impact of dynamic, broad, and focused interventions on each group’s subset of nonadherent patients. Thus, considerable gaps remain in the existing evidence base for targeting medication adherence in-terventions.
ConclusionTargeting patients who are nonadherent to their cardiovas-cular medications may lead to better adherence; however, data are limited and studies are highly heterogeneous. With cost an ever-present consideration, future efforts to improve adherence may best be directed at patients who demonstrate that they do not adhere to therapy.
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Author, Year, Site
Funding source Jadad Score
From Table 1
Haynes, RB, 1976 Canada
Grant no. MA-‐5159 from Medical Research Council of Canada, National Health Grant from Health and Welfare Canada, and a grant from Dominion Foundries and Steel company of Canada. One of authors is Physicians Services Inc. foundation fellow.
3
Rosen, 2004
Connecticut
VA Merit Review grant, an RO1 and the VISN1 . Not supported by any company making MEMS or related products.
3
Saunders, LD, 1991
Soweto, S Africa
Supported by the S. African Medical Research Council. 2
Taylor, 2003
Alabama
ASHP Research and Education Foundation 2
From Table 2 Avanzini, 2002 Italy
Supported in part by an educational grant from Hoechst-‐Roussel and Du Pont Pharma Italia
2
Birtwhistle, 2004
Urban, rural Canada
Canadien Institute for Health Research and McKnight Fund for Queen's University
3
Christensen , 2010 Poland
Bang & Olufsen Medicom A/S and the Danish Ministry of Science, Technology and Innovation.
2
Düsing R 2009
multiple sites, Germany
Novartis Pharma GmBH, NÜrnberg, Germany 2
Emmett, CL, 2005 Bristol, England.
Royal College of General Practitioners Scientific Foundation Board, Training Fellowship in Health Services Research at MRC and Royal College of General Practitioners Scientific Foundation
Board
2
Hamet, P, 2003 Canada
Bristol-‐Myers Squibb Canda and Sanofi Canada 3
Hawkins, 1979
DHEW public service grant 2
Johnson, Health research grant from Ontario Ministry of Health 2
1978 Hamilton, Ontario, Canada.
Kirscht, JP,
1981 Tecumseh, Michigan
Grant HL18401 from the National Heart Lung and Blood Institute.
2
Logan, 1979
Toronto, Canada
Grant from Ontario Ministry of Health 2
Lopez Cabezas,C,
2006 Barcelona,
Spain
Health research Fund (Fonodo de Investigacion Sanitaria, FIS) and the European Regional Development Fund (ERDF).
2
Mann, 2009
New York Not given 1
Marquez-‐Contreras,
2006 Spain
Novartis Farmaceutica, Spain 3
Mehos, 2000
Colorado
1998-‐99 Bristol-‐Myers Squibb Pharmacy Practice Hypertension Program grant from American Association of Colleges of
Pharmacy
3
Morisky, 1985
Baltimore, Maryland.
NHLBI grants, NCHRS and BRSG grant from the Biomedical Research Support Grant Program, NIH.
2
Mullan, 2009
Minnesota
American Diabetes Association. Novo Nordisk, a maker of insulin, subsidized the ADA grant program but did not have
direct contact with the investigators and idd not play any role in the awarding the grant to the research team
3
Powell, KM, 1995
Ciba Geigy Corp, Merck (education grants) 1
Rudd, 2004
California Grant from CorSolutions, Inc (Buffalo Grove, IL)
3
Sackett, 1975
Hamilton, Ontario
Not specified 2
Sclar, DA, 1991
Delaware, Texas and Wisconsin.
grant from ICI Pharmaceuticals, Wilmington, Delaware 1
Smith, 2008
U.S. urban centers
"ccoperative agreement" from AHRQ 2
Stewart, A, 2005
Johannesburg, S. Africa.
Not specified 2
Takala, J, 1983
Southwest Finland
Not specified 2
van Onzenoort, 2009 The
Netherlands
The Netherlands Organzation for Health Research and Development (Healthcare Efficiency Research Program; grant
945-‐01-‐043) 2
Yilmaz, MB, 2005
Ankara, Turkey. Not specified 2
From Table 3 Antonicelli,
2008 Italy
Grants from the Italian Ministry of Health 2
Blenkinsopp, 2000
England
(England) Dept of Health as part of its Community Pharmacy Wider Role Programme
2
Bouvy, 2003 The
Netherlands
Unrestricted research grant from independent nonprofit foundation for efficient ues of eds (DGMN)
3
Edworthy, 2007
Calgary, Alberta. Canada.
Supported by grant from Merck Frost Canada 2
Faulkner, 2000
Omaha, Nebraska
Not specified 3
Friedman, 1996 Boston
grant from NHLBI 2
Guthrie, 2001 Ohio
Bristol-‐Myers Squibb Co, Princeton, NJ 2
Hunt, 2008
Oregon
grant from Boehringer Ingelheim 3
Jaffray, 2007 England
Dept Health for England and Wales managed by collaboration of Nat'l Pharm Assoc'n, Poyal Pharm Society of Great Britain, Company Chemist Assoc and Coop Pharmacy Technical Panel
3
Krantz, 2008
Denver, Colorado
Glaxo Smith Kline. 3
Logan, 1983
Toronto Ontario Ministry of Health, Public Health grant CHS-‐R21 1
Odegard, 2005
Seattle, Washington
grant from Academic and Managed care Forum, Quality Care Research Fund
3
Ogedegbe, 2008
New York, NY.
NHLBI, NIH grants 3
Piette, 2000
Clinical research grants program o f the ADA and the Health Services Research and Devlopment Service and mental Health
Strategic Health Group, Dept of VA 3
Planas, 2009
American Pharmacists Association Foundation, the American Society of Health-‐System Pharmacists Foundation, and USA
Drug Stores
Sadik, 2005
Al-‐Ain, United Arab Emirates
Not specified 3
Schectman, G, HSR&D Grant from the VA and grant from Squibb-‐Bristol 2
1994 Milwaukee
company
Schroeder, K, 2005
Avon, UK
Medical Research Council Trianing Fellowship in Health Services Research
3
Solomon, 1998
Multiple sites
Educational grant Novartis pharmaceuticals corp 2
Sookaneknun 2004
Urban and rural Thailand
Research grant from Chiang Mai University, Thailand 2
Stacy, 2009
Not available 3
Tsuyuki, RT, 2004 Canada
Unrestricted educational grant from Parke Davis Canada (now Pfizer Canada) and the U of Alberta Hospital Foundation
3
Varma, 1999
Northern Ireland
Not specified 3
Vivian, EM, 2002
Philadelphia, Pennsylvania
Supported by the Christian R and Mary F Lindback Foundation 2
External adherence
data (alone or in
combination with self-‐generated
data)
Johnson, SS, 2006
Massachusetts and Rhode Island
Grant from the National Heart. Lung and Blood Institute (grant no. R44 HL64504)
2
Murray, 2007
National Institutes of Health grants R01 AG19105 and R01 HL 69399 and AG01799
3
Indianapolis, Indiana Phumipa-‐morn, S, 2008 Krabi
Province, Thailand.
Research grants from Graduate School, Prince of Songkla University and the Provincial Public Health Dept of Krabi
Province, Thailand 3
Robinson, 2010
Tampa, FL
Pfizer unrestricted grant 1
Tamblyn, 2009
Montreal and Quebec, Canada
Canadien Institutes of Health Research and Pfizer Canada Inc 2
Vrijens, 2006
Belgium Contract grant sponsor is Pfizer Belgium 1