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https://doi.org/10.1177/2042098620968309 https://doi.org/10.1177/2042098620968309
Ther Adv Drug Saf
2020, Vol. 11: 1–29
DOI: 10.1177/ 2042098620968309
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Lay summary
Activities to reduce medication errors in adult medical and surgical hospital areas
Introduction: Medication errors or mistakes may happen at any time in hospital, and they are a major reason for death and harm around the world.
Interventions to reduce medication errors in adult medical and surgical settings: a systematic review Elizabeth Manias , Snezana Kusljic and Angela Wu
Abstract Background and Aims: Medication errors occur at any point of the medication management process, and are a major cause of death and harm globally. The objective of this review was to compare the effectiveness of different interventions in reducing prescribing, dispensing and administration medication errors in acute medical and surgical settings. Methods: The protocol for this systematic review was registered in PROSPERO (CRD42019124587). The library databases, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews and the Cochrane Central Register of Controlled Trials were searched from inception to February 2019. Studies were included if they involved testing of an intervention aimed at reducing medication errors in adult, acute medical or surgical settings. Meta-analyses were performed to examine the effectiveness of intervention types. Results: A total of 34 articles were included with 12 intervention types identified. Meta-analysis showed that prescribing errors were reduced by pharmacist-led medication reconciliation, computerised medication reconciliation, pharmacist partnership, prescriber education, medication reconciliation by trained mentors and computerised physician order entry (CPOE) as single interventions. Medication administration errors were reduced by CPOE and the use of an automated drug distribution system as single interventions. Combined interventions were also found to be effective in reducing prescribing or administration medication errors. No interventions were found to reduce dispensing error rates. Most studies were conducted at single-site hospitals, with chart review being the most common method for collecting medication error data. Clinical significance of interventions was examined in 21 studies. Since many studies were conducted in a pre–post format, future studies should include a concurrent control group. Conclusion: The systematic review identified a number of single and combined intervention types that were effective in reducing medication errors, which clinicians and policymakers could consider for implementation in medical and surgical settings. New directions for future research should examine interdisciplinary collaborative approaches comprising physicians, pharmacists and nurses.
Keywords: hospitals, medication errors, medical order entry systems, medication reconciliation, medication therapy management, nurses, patient safety, pharmacists, physicians, systematic review
Received: 27 May 2020; revised manuscript accepted: 23 September 2020.
Correspondence to: Elizabeth Manias School of Nursing and Midwifery, Centre for Quality and Patient Safety Research, Institute for Health Transformation, Deakin University, 221 Burwood Highway, Burwood, Victoria 3125, Australia
Melbourne School of Health Sciences, The University of Melbourne, Melbourne, Australia
Department of Medicine, Royal Melbourne Hospital [email protected]; [email protected]
Snezana Kusljic Department of Nursing, The University of Melbourne, Melbourne, Victoria, Australia
The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
Angela Wu Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia
968309TAW0010.1177/2042098620968309Therapeutic Advances in Drug SafetyE Manias, S Kusljic research-article20202020
Systematic Review
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Therapeutic Advances in Drug Safety 11
Objective: To compare the effectiveness of different activities in reducing medication errors occurring with prescribing, giving and supplying medications in adult medical and surgical settings in hospital. Methods: Six library databases were examined from the time they were developed to February 2019. Studies were included if they involved testing of an activity aimed at reducing medication errors in adult medical and surgical settings in hospital. Statistical analysis was used to look at the success of different types of activities. Results: A total of 34 studies were included with 12 activity types identified. Statistical analysis showed that prescribing errors were reduced by pharmacists matching medications, computers matching medications, partnerships with pharmacists, prescriber education, medication matching by trained physicians, and computerised physician order entry (CPOE). Medication-giving errors were reduced by the use of CPOE and an automated medication distribution system. The combination of different activity types were also shown to be successful in reducing prescribing or medication-giving errors. No activities were found to be successful in reducing errors relating to supplying medications. Most studies were conducted at one hospital with reviewing patient charts being the most common way for collecting information about medication errors. In 21 out of 34 articles, researchers examined the effect of activity types on patient harm caused by medication errors. Many studies did not involve the use of a control group that does not receive the activity. Conclusion: A number of activity types were shown to be successful in reducing prescribing and medication-giving errors. New directions for future research should examine activities comprising health professionals working together.
Introduction Medication errors occur at any point of the medi- cation management process involving prescrib- ing, transcribing, dispensing, administering and monitoring,1,2 have been reported to account for approximately one-quarter of all healthcare errors.3 Medication errors are a major cause of death and harm globally.4 According to the World Health Organisation (WHO), medication errors cost an estimated US$42 billion annually world- wide, which is 0.7% of the total global health expenditure.5
Systematic reviews examining interventions aimed at reducing medication errors have largely focused on specialty settings, such as patients sit- uated in adult and paediatric intensive care units, emergency departments, and neonatal intensive care and paediatric units.6–10 Previous relevant systematic reviews relating to testing interven- tions for reducing medication errors in general hospital settings have focused on administration errors only,11,12 have involved adult and paediat- ric settings or have tested interventions in spe- cialty and general hospital settings with no differentiation in results.11–13 This systematic review aims to compare the effectiveness of differ- ent interventions in reducing prescribing, dis- pensing and administration medication errors in
acute medical and surgical settings. Information obtained from this review can inform clinicians and policymakers about the types of interventions that have been shown to be effective, which can guide the development of comprehensive guide- lines for clinical practice and policy directives.
Methods In conducting this systematic review, the authors followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.14 The review protocol was registered with PROSPERO (CRD42019124587).
Search strategy A search was conducted of the following library databases, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews and the Cochrane Central Register of Controlled Trials, from inception to February 2019.
A search strategy was devised following consulta- tion with a university research librarian to yield relevant studies. Keywords used in the search comprised five categories: the setting, with key- words ‘hospital’, ‘acute’, ‘medical’, ‘surgical’;
E Manias, S Kusljic et al.
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perspective, with keywords ‘medication manage- ment’, ‘medication process’, ‘medicines manage- ment’, ‘prescribing’, ‘dispensing’, ‘administration’, ‘monitoring’; population, with keyword ‘adult’; activity, with keywords ‘pro- gram’ and ‘intervention’; and phenomenon of interest, with keywords ‘medication errors’, ‘pre- ventive adverse drug events’, and ‘medicine errors’. Keywords in each category were searched using the operator OR, and then combined between categories using the operator AND. Search histories for all databases are listed in Supplemental file S1. Key article cross-checking was performed using citation-linking databases, Scopus and Web of Science in an attempt to iden- tify further articles. Reference lists of relevant articles were checked to identify additional papers. Previous systematic reviews on a similar topic were also examined to determine possible papers for inclusion.11–13
Eligibility criteria Studies were included if they involved testing an intervention aimed at reducing medication errors in adult acute medical or surgical settings. Adults were defined as patients aged 18 years or over. If patients received the intervention during hospitali- sation and the effect on medication errors was measured in the hospital setting, these studies were included. Medication errors comprised any pre- ventable events that may cause or lead to inappro- priate medication use or patient harm during prescribing, dispensing or administration.15 The prevalence of medication errors must have been identified as a primary or secondary outcome to be included. Papers were considered for inclusion if they were published before 2000, as this was the year when the landmark publication, To Err is Human: Building a Safer Health System was released by the Institute of Medicine.16 This publication drew attention of the need for health services to develop tools and systems to address problems in patient safety, such as medication errors.
Near misses were not included as medication errors. Only papers published in English were included. Case studies, commentaries, editorials, reviews, epidemiological studies and conference abstracts were excluded. If studies examined medication-related problems as an outcome, which often comprised a combination of medica- tion errors, as well as problems with medication knowledge, medication adherence and other
aspects of medication management, these studies were not included. If the effect of the intervention was measured outside the hospital setting, these studies were excluded. Specialty wards such as intensive care, emergency care, perioperative care, neurological and cancer care were excluded. Outpatient settings and subacute settings, such as rehabilitation wards and geriatric evaluation and management units were excluded.
Study selection Rayyan (Qatar Computing Research Institute), an online platform, was used for independent screening of articles at the title and abstract level, and subsequently at the full text level.17 Two authors reviewed titles and abstracts indepen- dently. The third author assessed discrepancies at the title and abstract level. Any uncertainty or disagreement about articles meeting the inclusion criteria was resolved after discussion among all authors. Full texts of papers were then examined independently by two authors to determine if studies were eligible for inclusion in the review. Any discrepancies identified at the full-text level were examined by the third author. Previous sys- tematic reviews on similar topics were also exam- ined to determine possible papers for inclusion.
Quality assessment Quality assessment was undertaken using the Equator reporting guidelines whereby ran- domised controlled trials were assessed using the CONSORT guidelines,18 non-randomised stud- ies were assessed using the TREND guide- lines,19 and quality improvement studies were assessed using the SQUIRE guidelines.20 No study was excluded on the basis of the score obtained for quality assessment. Risk of bias assessment was also undertaken using Review Manager, version 5.3 (RevMan) (Cochrane Collaboration) software.
Data extraction Data were extracted from each paper to a stand- ard form for study design, country and setting, number of patients, intervention type, type of medication error analysed and effect of the inter- vention (Table 1). If the studies provided infor- mation about the severity of medication errors using their approach for measuring severity, these data were also included in data extraction.
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Therapeutic Advances in Drug Safety 11
Ta b
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ve rv
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ed ic
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E Manias, S Kusljic et al.
journals.sagepub.com/home/taw 5
R ef
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( p
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te rv
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N o
p- va
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n u
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-i n
te rv
en ti
on :
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5 to
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n u
m b
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ro rs
P os
t- in
te rv
en ti
on :
15 /4
5 to
ta l
n u
m b
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N o
p- va
lu e
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it h
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at ri
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ca rd
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in p
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31 7
(p re
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te rv
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2 43
(p
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ti on
)
IT -M
R D
is ch
ar ge
m ed
ic at
io n
e rr
or s
(p re
sc ri
b in
g er
ro rs
) (e
le ct
ro n
ic m
ed ic
al r
ec or
d a
n d
c h
ar t
re vi
ew )
P re
-i n
te rv
en ti
on :
64 5
er ro
rs /3
49 0
m ed
ic at
io n
v ar
ia n
ce P
os t-
in te
rv en
ti on
: 35
9 er
ro rs
/2 82
3 m
ed ic
at io
n v
ar ia
n ce
, p <
0 .0
01 C
li n
ic al
ly im
p or
ta n
t m
ed ic
at io
n e
rr or
s (w
it h
p ot
en ti
al f
or s
er io
u s
or l
if e-
th re
at en
in g
h ar
m )
P re
-i n
te rv
en ti
on :
9/ 64
5 er
ro rs
( 1.
4% )
P os
t- in
te rv
en ti
on :
11 /3
59 e
rr or
s (3
.1 %
), p
= 0
.1 0
M ed
ic at
io n
r ec
on ci
li at
io n
b y
tr ai
n ed
m en
to rs
S ch
n ip
p er
e t
al .2
9 (U
S )
Q u
al it
y im
p ro
ve m
en t
st u
d y
M ed
ic al
o r
su rg
ic al
u
n it
s ac
ro ss
5
h os
p it
al s,
n o
co n
tr ol
u n
it s
at
h os
p it
al s
it es
4 a
n d
5,
n o
in te
rv en
ti on
u
n it
s at
h os
p it
al
si te
1
85 7
(c on
tr ol
), 7
91
(i n
te rv
en ti
on )
L oc
al
im p
le m
en ta
ti on
of
m ed
ic at
io n
re
co n
ci li
at io
n b
es t
p ra
ct ic
es
P ot
en ti
al ly
h ar
m fu
l d
is cr
ep an
ci es
in a
d m
is si
on a
n d
d is
ch ar
ge o
rd er
s p
er p
at ie
n t
(c h
ar t
re vi
ew )
R es
u lt
s re
p or
te d
a s
m ea
n n
u m
b er
o f
er ro
rs p
er p
at ie
n t
S it
e 1:
d id
n ot
im p
le m
en t
th e
in te
rv en
ti on
. S
it e
2: C
on tr
ol u
n it
s P
re -i
m p
le m
en ta
ti on
: 0.
98 P
os t-
im p
le m
en ta
ti on
: 1.
32 In
te rv
en ti
on u
n it
s P
re -i
m p
le m
en ta
ti on
: 1.
00 P
os t-
im p
le m
en ta
ti on
: 0.
88 S
it e
3 C
on tr
ol u
n it
s P
re -i
m p
le m
en ta
ti on
: 0.
17 P
os t-
im p
le m
en ta
ti on
: 0.
23 In
te rv
en ti
on u
n it
s P
re -i
m p
le m
en ta
ti on
: 0.
30 P
os t-
im p
le m
en ta
ti on
: 0.
18 S
it e
4 an
d s
it e
5: d
id n
ot h
av e
co n
tr ol
u n
it s
at b
as el
in e.
N o
p- va
lu e
re p
or te
d
Ta b
le 1
. ( C
on ti
n u
ed )
(C on
ti nu
ed )
6 journals.sagepub.com/home/taw
Therapeutic Advances in Drug Safety 11 R
ef er
en ce
(c
ou n
tr y)
S tu
d y
d es
ig n
S et
ti n
g N
u m
b er
o f
p at
ie n
ts In
te rv
en ti
on t
yp e
Ty p
e of
m ed
ic at
io n
e rr
or a
n al
ys ed
( m
et h
od o
f d
at a
co ll
ec ti
on f
or m
ed ic
at io
n e
rr or
s) ,
ef fe
ct o
f in
te rv
en ti
on o
n m
ed ic
at io
n e
rr or
r at
e
C D
S S
H er
n an
d ez
e t
al .3
0 (F
ra n
ce )
B ef
or e
an d
a ft
er
ob se
rv at
io n
al s
tu d
y 66
-b ed
o rt
h op
ae d
ic
su rg
er y
u n
it o
f a
70 0-
b ed
t ea
ch in
g h
os p
it al
11 1
(p re
-C P
O E
), 8
6 p
at ie
n ts
( p
os t-
C P
O E
)
C P
O E
w it
h a
le rt
s fo
r d
ru g-
al le
rg y
ch ec
ki n
g,
th er
ap eu
ti c
d u
p li
ca ti
on s,
d os
e- ra
n ge
a n
d a
ge -
b as
ed c
h ec
ki n
g,
an d
d ru
g– d
ru g
in te
ra ct
io n
s. N
o m
en ti
on o
f C
D S
S
P re
sc ri
b in
g er
ro rs
( d
ir ec
t d
is gu
is ed
o b
se rv
at io
n )
P re
-i n
te rv
en ti
on :
47 9/
15 93
p re
sc ri
b ed
d ru
gs (
30 .1
% )
P os
t- in
te rv
en ti
on :
33 /1
38 8
p re
sc ri
b ed
d ru
gs (
2. 4%
), p
< 0
.0 00
1 D
is p
en si
n g
er ro
rs P
re -i
n te
rv en
ti on
: 43
0/ 12
19 o
p p
or tu
n it
ie s
(3 5.
3% )
P os
t- in
te rv
en ti
on :
44 9/
14 07
o p
p or
tu n
it ie
s (3
1. 9%
), p
= 0
.0 7
A d
m in
is tr
at io
n e
rr or
s P
re -i
n te
rv en
ti on
: 20
9/ 12
22 o
p p
or tu
n it
ie s
(1 7.
1% )
P os
t- in
te rv
en ti
on :
20 0/
14 13
o p
p or
tu n
it ie
s (1
4. 2%
), p
< 0
.0 5
M il
an i e
t al
.3 1
(U S
) P
ro sp
ec ti
ve
in te
rv en
ti on
P at
ie n
ts w
it h
ch
ro n
ic k
id n
ey
d is
ea se
a d
m it
te d
w
it h
a cu
te c
or on
ar y
sy n
d ro
m e
to
m ed
ic al
w ar
d
33 (
in te
rv en
ti on
),
47 (
co n
tr ol
) C
P O
E w
it h
al
er ts
a n
d C
D S
S
fo r
ch oi
ce o
f m
ed ic
at io
n , d
ru g
d os
in g
b as
ed o
n
cl in
ic al
r is
k, p
at ie
n t
w ei
gh t,
c al
cu la
te d
cr
ea ti
n in
e cl
ea ra
n ce
a n
d
co n
se n
su s
gu id
el in
es
A d
ve rs
e d
ru g
ev en
ts (
C h
ar t
re vi
ew )
C on
tr ai
n d
ic at
ed m
ed ic
at io
n s
C on
tr ol
: 8/
47 p
at ie
n ts
( 17
% )
In te
rv en
ti on
: 0/
33 p
at ie
n ts
( 0%
), p
= 0
.0 1
In -h
os p
it al
b le
ed in
g C
on tr
ol :
10 /4
7 p
at ie
n ts
In te
rv en
ti on
: 3/
33 p
at ie
n ts
, p =
0 .1
2 90
-d ay
m or
ta li
ty C
on tr
ol 7
( 15
% ),
In te
rv en
ti on
4 (
12 %
), p
= 0
.5 0
L en
gt h
o f
st ay
C on
tr ol
m ea
n 9
.1 , S
D 1
0. 2
In te
rv en
ti on
m ea
n 4
.8 , S
D 4
.0 , p
= 0
.0 1
P et
ti t
et a
l.3 2
(U S
) R
et ro
sp ec
ti ve
si
n gl
e ce
n tr
e, p
re -
p os
t in
te rv
en ti
on
st u
d y
P at
ie n
ts a
d m
it te
d
to a
8 11
-b ed
ac
ad em
ic
m ed
ic al
c en
tr e
w h
o co
n ti
n u
ed
on a
n ti
re tr
ov ir
al
th er
ap y
16 7
(p re
- in
te rv
en ti
on ),
1 31
(p
os t-
in te
rv en
ti on
)
C P
O E
w it
h a
le rt
s to
d
ru g-
in te
ra ct
io n
s an
d in
fo rm
at io
n
on m
ed ic
at io
n
gu id
el in
es . N
o m
en ti
on o
f C
D S
S
P re
sc ri
b in
g er
ro rs
( ch
ar t
re vi
ew )
P re
-i n
te rv
en ti
on :
84 /1
67 p
at ie
n ts
( 50
.2 %
) P
os t-
in te
rv en
ti on
: 37
/1 31
p at
ie n
ts (
28 .2
% ),
p <
0 .0
1
S h
aw ah
n a
et a
l.3 3
(P ak
is ta
n )
P ro
sp ec
ti ve
r ev
ie w
st
u d
y V
ar io
u s
w ar
d s
of
h os
p it
al , t
h re
e m
ed ic
al w
ar d
s in
o n
e te
ac h
in g
h os
p it
al
N ot
a va
il ab
le P
ap er
b as
ed
ve rs
us e
le ct
ro n
ic
p re
sc ri
b in
g w
it h
n
o al
er ts
o r
C D
S S
su
ch a
s ch
ec ks
o n
d
ru g
in te
ra ct
io n
s or
a ll
er gi
es
P re
sc ri
b in
g er
ro rs
( ch
ar t
re vi
ew )
(n o
n u
m er
at or
o r
d en
om in
at or
p ro
vi d
ed f
or m
ed ic
al
w ar
d s)
P re
sc ri
p ti
on e
rr or
s in
m ed
ic al
w ar
d 1
C on
tr ol
: 19
.6 %
( 95
% C
I 1 1.
0– 29
.3 )
In te
rv en
ti on
: 8.
3% (
95 %
C I 7
.2 –8
.9 ),
p <
0 .0
5 P
re sc
ri p
ti on
e rr
or s
in m
ed ic
al w
ar d
2 C
on tr
ol :
19 .6
% (
95 %
C I 1
3. 2–
24 .5
) In
te rv
en ti
on :
6. 3%
( 95
% C
I 5 .2
–7 .1
), p
< 0
.0 5
P re
sc ri
p ti
on e
rr or
s in
m ed
ic al
w ar
d 3
C on
tr ol
: 25
.0 %
( 95
% C
I 1 7.
0– 29
.7 )
In te
rv en
ti on
: 6.
0% (
95 %
C I 2
.0 –8
.0 ),
p <
0 .0
5 S
ev er
it y
of p
re sc
ri p
ti on
e rr
or s
– n
o b
re ak
d ow
n a
cc or
d in
g to
m ed
ic al
w ar
d s
P re
sc ri
p ti
on e
rr or
s m
ad e
b u
t n
o cl
in ic
al c
on se
q u
en ce
s C
on tr
ol :
51 0/
30 08
t ot
al in
p at
ie n
t p
re sc
ri p
ti on
e rr
or s
(1 7.
0% )
In te
rv en
ti on
: 31
5/ 11
47 t
ot al
in p
at ie
n t
p re
sc ri
p ti
on e
rr or
s (2
7. 5%
), p
< 0
.0 1
P re
sc ri
p ti
on e
rr or
s m
ad e
th at
c au
se p
at ie
n t
h ar
m C
on tr
ol :
41 5/
30 08
t ot
al in
p at
ie n
t p
re sc
ri p
ti on
e rr
or s
(1 3.
8% )
In te
rv en
ti on
: 21
5/ 11
47 t
ot al
in p
at ie
n t
p re
sc ri
p ti
on e
rr or
s (1
8. 7%
), p
< 0
.0 1
P re
sc ri
p ti
on e
rr or
s m
ad e
th at
c ou
ld p
ot en
ti al
ly r
es u
lt p
at ie
n t
d ea
th C
on tr
ol :
23 0/
30 08
t ot
al in
p at
ie n
t p
re sc
ri p
ti on
e rr
or s
(7 .6
% )
In te
rv en
ti on
: 17
0/ 11
47 t
ot al
in p
at ie
n t
p re
sc ri
p ti
on e
rr or
s (1
4. 8%
), p
< 0
.0 5
Ta b
le 1
. ( C
on ti
n u
ed )
(C on
ti nu
ed )
E Manias, S Kusljic et al.
journals.sagepub.com/home/taw 7
R ef
er en
ce
(c ou
n tr
y) S
tu d
y d
es ig
n S
et ti
n g
N u
m b
er o
f p
at ie
n ts
In te
rv en
ti on
t yp
e Ty
p e
of m
ed ic
at io
n e
rr or
a n
al ys
ed (
m et
h od
o f
d at
a co
ll ec
ti on
f or
m ed
ic at
io n
e rr
or s)
, ef
fe ct
o f
in te
rv en
ti on
o n
m ed
ic at
io n
e rr
or r
at e
va n
D oo
rm aa
l et
a l.3
4 (T
h e
N et
h er
la n
d s)
In te
rr u
p te
d t
im e-
se ri
es d
es ig
n T
w o
m ed
ic al
w ar
d s
of a
u n
iv er
si ty
h
os p
it al
a n
d t
w o
m ed
ic al
w ar
d s
of a
te
ac h
in g
h os
p it
al
59 2
(b as
el in
e) 60
3 (p
os t-
in te
rv en
ti on
)
C P
O E
w it
h
al er
ts f
or d
ru g
in te
ra ct
io n
s,
ov er
d os
es a
n d
al
le rg
ie s,
n o
C D
S S
P re
sc ri
b in
g er
ro rs
( ch
ar t
re vi
ew )
B as
el in
e: 5
72 4/
90 39
p re
sc ri
p ti
on s
(6 3.
3% )
In te
rv en
ti on
: 13
55 /7
21 0
p re
sc ri
p ti
on s
(1 8.
8% ),
p <
0 .0
5 S
ev er
e ad
ve rs
e d
ru g
ev en
ts :
B as
el in
e: 1
02 /9
03 9
(1 .1
% )
In te
rv en
ti on
5 4/
72 10
( 0.
7% ),
p <
0 .0
5
P P
G ar
ci a-
M ol
in a
S ae
z et
a l.3
5 (S
p ai
n )
Q u
as i-
ex pe
ri m
en ta
l in
te rr
u p
te d
t im
e- se
ri es
s tu
d y
C ar
di o-
pn eu
m ol
og y
u n
it o
f ge
n er
al
h os
p it
al
3 p
h as
es :
to ta
l 32
1 p
at ie
n ts
P re
-i n
te rv
en ti
on al
: 11
9 In
te rv
en ti
on al
: 10
5 P
os t-
in te
rv en
ti on
al :
97
P P
R ec
on ci
li at
io n
e rr
or s
(s tr
u ct
u re
d in
te rv
ie w
w it
h p
at ie
n ts
o r
fa m
il y)
P re
-i n
te rv
en ti
on (
p er
io d
1 ):
5 18
/1 08
7 to
ta l
re co
n ci
li at
io n
e rr
or s
(4 7.
7% )
In te
rv en
ti on
( p
er io
d 2
): 1
88 /1
08 7
to ta
l re
co n
ci li
at io
n e
rr or
s (1
7. 3%
) P
os t-
in te
rv en
ti on
( p
er io
d 3
): 3
81 /1
08 7
to ta
l re
co n
ci li
at io
n e
rr or
s (3
5. 1%
) p <
0 .0
01 b
et w
ee n
p er
io d
1 –2
a n
d 2
–3 p
= 0.
28 8
b et
w ee
n p
er io
d 1
–3 S
ev er
it y
E rr
or o
cc u
rr ed
b u
t d
id n
ot r
ea ch
p at
ie n
t P
re -i
n te
rv en
ti on
: 27
3/ 51
8 er
ro rs
( 52
.7 %
) P
os t-
in te
rv en
ti on
: 20
1/ 38
1 er
ro rs
( 52
.8 %
) E
rr or
o cc
u rr
ed b
u t
d id
n ot
c au
se p
at ie
n t
h ar
m P
re -i
n te
rv en
ti on
: 67
/5 18
e rr
or s
(1 2.
9% )
P os
t- in
te rv
en ti
on :
39 /3
81 e
rr or
s (1
0. 2%
) E
rr or
o cc
u rr
ed a
n d
r eq
u ir
ed m
on it
or in
g P
re -i
n te
rv en
ti on
: 12
0/ 51
8 er
ro rs
( 23
.2 %
) P
os t-
in te
rv en
ti on
: 11
8/ 38
1 er
ro rs
( 31
.0 %
) E
rr or
r eq
u ir
ed in
te rv
en ti
on P
re -i
n te
rv en
ti on
: 55
/5 18
e rr
or s
(1 0.
6% )
P os
t- in
te rv
en ti
on :
19 /3
81 e
rr or
s (5
.0 %
) E
rr or
r eq
u ir
ed h
os p
it al
is at
io n
P re
-i n
te rv
en ti
on :3
/5 18
e rr
or s
(0 .6
% )
P os
t- in
te rv
en ti
on :
4/ 38
1 er
ro rs
( 1.
0% )
N o
p- va
lu e
re p
or te
d
H as
sa n
e t
al .3
6 (M
al ay
si a)
P re
in te
rv en
ti on
an
d p
os t
in te
rv en
ti on
s tu
d y
35 -b
ed n
ep h
ro lo
gy
u n
it 30
0 (i
n te
rv en
ti on
),
30 0
(c on
tr ol
) P
P S
u sp
ec te
d A
D E
s (c
h ar
t re
vi ew
a n
d w
ar d
r ou
n d
p ar
ti ci
p at
io n
) C
on tr
ol :
73 e
ve n
ts , 6
4 p
at ie
n ts
/3 00
p at
ie n
ts In
te rv
en ti
on :
49 e
ve n
ts , 4
8 p
at ie
n ts
/3 00
p at
ie n
ts , p
< 0
.0 5
In ap
p ro
p ri
at e
m ed
ic at
io n
C on
tr ol
: 32
2/ 28
14 t
ot al
p re
sc ri
p ti
on s
(1 1.
4% )
In te
rv en
ti on
: 17
6/ 29
81 t
ot al
p re
sc ri
p ti
on s
(5 .9
% ),
p <
0 .0
01 S
ev er
it y
of A
D E
s S
er io
u s
C on
tr ol
: 20
e ve
n ts
/3 00
p at
ie n
ts In
te rv
en ti
on :
5 ev
en ts
/3 00
p at
ie n
ts S
ig n
if ic
an t
C on
tr ol
: 42
e ve
n ts
/3 00
p at
ie n
ts In
te rv
en ti
on :
36 e
ve n
ts /3
00 p
at ie
n ts
In si
gn if
ic an
t C
on tr
ol :
11 e
ve n
ts /3
00 p
at ie
n ts
In te
rv en
ti on
: 8
ev en
ts /3
00 p
at ie
n ts
N o
p- va
lu e
re p
or te
d
Ta b
le 1
. ( C
on ti
n u
ed )
(C on
ti nu
ed )
8 journals.sagepub.com/home/taw
Therapeutic Advances in Drug Safety 11 R
ef er
en ce
(c
ou n
tr y)
S tu
d y
d es
ig n
S et
ti n
g N
u m
b er
o f
p at
ie n
ts In
te rv
en ti
on t
yp e
Ty p
e of
m ed
ic at
io n
e rr
or a
n al
ys ed
( m
et h
od o
f d
at a
co ll
ec ti
on f
or m
ed ic
at io
n e
rr or
s) ,
ef fe
ct o
f in
te rv
en ti
on o
n m
ed ic
at io
n e
rr or
r at
e
L ie
d tk
e et
a l.3
7 (U
S )
R et
ro sp
ec ti
ve
ob se
rv at
io n
al s
tu d
y H
IV -s
er op
os it
iv e
p at
ie n
ts a
d m
it te
d
to a
l ar
ge t
ea ch
in g
h os
p it
al
T ot
al 3
30 p
at ie
n t
ad m
is si
on s:
P re
-i n
te rv
en ti
on :
15 3
p at
ie n
t ad
m is
si on
s (9
6 p
at ie
n ts
) In
te rv
en ti
on :
17 7
p at
ie n
t ad
m is
si on
s (1
14 p
at ie
n ts
)
P P
T ot
al n
u m
b er
o f
p re
sc ri
b in
g er
ro rs
( su
m o
f th
e ab
ov e
n u
m b
er s)
( ch
ar t
re vi
ew )
P re
-i n
te rv
en ti
on :
85 e
rr or
s/ 33
0 ad
m is
si on
s In
te rv
en ti
on :
24 e
rr or
s/ 33
0 ad
m is
si on
s, p
< 0
.0 01
P E
G u
rs an
sc ky
e t
al .3
8 (A
u st
ra li
a) C
lu st
er r
an d
om is
ed
tr ia
l in
vo lv
in g
p re
sc ri
b er
s
F ou
r ge
n er
al
m ed
ic al
u n
it s
of a
te
rt ia
ry h
os p
it al
In te
rv en
ti on
o n
d
oc to
rs :
12 in
te rn
s,
4 re
gi st
ra rs
P E
E d
u ca
ti on
: P
re sc
ri b
in g
fe ed
b ac
k an
d
ta rg
et ed
e d
u ca
ti on
; e-
le ar
n in
g on
s af
e- p
re sc
ri b
in g
P re
sc ri
b in
g er
ro rs
( ch
ar t
re vi
ew )
C on
tr ol
: B
as el
in e:
1 17
1 to
ta l
er ro
rs /2
38 9
to ta
l m
ed ic
at io
n o
rd er
s P
os t-
in te
rv en
ti on
: 16
30 t
ot al
e rr
or s/
27 71
t ot
al m
ed ic
at io
n o
rd er
s, p
< 0
.0 01
P h
ar m
ac is
t ed
u ca
ti on
: P
re -i
n te
rv en
ti on
: 62
1 to
ta l
er ro
rs /1
07 4
to ta
l m
ed ic
at io
n o
rd er
s (5
7. 8%
) P
os t-
in te
rv en
ti on
: 49
3 to
ta l
er ro
rs /1
33 3
to ta
l m
ed ic
at io
n o
rd er
s (3
7. 0%
), p
< 0
.0 01
E -l
ea rn
in g:
P re
-i n
te rv
en ti
on :
40 6
to ta
l er
ro rs
/6 97
t ot
al m
ed ic
at io
n o
rd er
s P
os t-
in te
rv en
ti on
: 88
2 to
ta l
er ro
rs /1
39 3
to ta
l m
ed ic
at io
n o
rd er
s, p
= 0
.0 25
R at
es o
f cl
in ic
al ly
s ig
n if
ic an
t p
re sc
ri b
in g
er ro
rs (
p ot
en ti
al ly
l et
h al
, s er
io u
s, s
ig n
if ic
an t
er ro
rs )
C on
tr ol
: B
as el
in e:
1 04
e rr
or s/
23 89
t ot
al m
ed ic
at io
n o
rd er
s P
os t-
in te
rv en
ti on
: 16
6 er
ro rs
/2 77
1 to
ta l
m ed
ic at
io n
o rd
er s,
p <
0 .0
1 P
h ar
m ac
is t
ed u
ca ti
on :
B as
el in
e: 7
0 er
ro rs
/1 07
4 to
ta l
m ed
ic at
io n
o rd
er s
(6 .5
2% )
P os
t- in
te rv
en ti
on :
64 e
rr or
s/ 13
33 t
ot al
m ed
ic at
io n
o rd
er s
(4 .8
0% ),
p =
0 .0
68 E
-l ea
rn in
g: B
as el
in e:
4 2
er ro
rs /6
97 t
ot al
m ed
ic at
io n
o rd
er s
P os
t- in
te rv
en ti
on :
83 e
rr or
s/ 13
93 t
ot al
m ed
ic at
io n
o rd
er s,
p =
0 .9
51
P T
E
W ei
n ga
rt e
t al
.3 9
(U S
) P
ro sp
ec ti
ve
ra n
d om
is ed
, co
n tr
ol le
d p
il ot
tr
ia l
40 -b
ed g
en er
al
m ed
ic in
e u
n it
o f
a B
os to
n t
ea ch
in g
h os
p it
al
10 7
(i n
te rv
en ti
on ),
10
2 (c
on tr
ol )
P T
E A
D E
s (c
h ar
t re
vi ew
) C
on tr
ol :
3/ 10
2 to
ta l
n u
m b
er o
f p
at ie
n ts
( 2.
9% )
In te
rv en
ti on
: 8/
10 7
to ta
l n
u m
b er
o f
p at
ie n
ts (
7. 5%
), p
= 0
.2 2
S ev
er it
y L
if e
th re
at en
in g
C on
tr ol
: 0
ev en
ts /1
02 p
at ie
n ts
In te
rv en
ti on
: 2
ev en
ts /1
07 p
at ie
n ts
S er
io u
s C
on tr
ol :
0 ev
en ts
/1 02
p at
ie n
ts In
te rv
en ti
on :
3 ev
en ts
/1 07
p at
ie n
ts S
ig n
if ic
an t
C on
tr ol
: 3
ev en
ts /1
02 p
at ie
n ts
In te
rv en
ti on
: 3
ev en
ts /1
07 p
at ie
n ts
L it
tl e
or n
on e
C on
tr ol
: 0
ev en
ts /1
02 p
at ie
n ts
In te
rv en
ti on
: 0
ev en
ts /1
07 p
at ie
n ts
, p =
0 .0
9
Ta b
le 1
. ( C
on ti
n u
ed )
(C on
ti nu
ed )
E Manias, S Kusljic et al.
journals.sagepub.com/home/taw 9
R ef
er en
ce
(c ou
n tr
y) S
tu d
y d
es ig
n S
et ti
n g
N u
m b
er o
f p
at ie
n ts
In te
rv en
ti on
t yp
e Ty
p e
of m
ed ic
at io
n e
rr or
a n
al ys
ed (
m et
h od
o f
d at
a co
ll ec
ti on
f or
m ed
ic at
io n
e rr
or s)
, ef
fe ct
o f
in te
rv en
ti on
o n
m ed
ic at
io n
e rr
or r
at e
T M
E
B aq
ir e
t al
.4 0
(U K
) Q
u as
i- ex
pe ri
m en
ta l
st u
d y
O n
e ac
u te
s u
rg ic
al
an d
o n
e ac
u te
m
ed ic
al w
ar d
a t
a d
is tr
ic t
ge n
er al
h
os p
it al
18 1
(i n
te rv
en ti
on ),
23
0 (i
n tr
a- w
ar d
co
n tr
ol ),
3 69
( in
te r-
w ar
d c
on tr
ol )
T M
E P
at ie
n t
w it
h a
t le
as t
on e
u n
ac ce
p ta
b le
o m
it te
d d
os e
(a d
m in
is tr
at io
n e
rr or
s) (
ch ar
t re
vi ew
) In
te r-
w ar
d c
on tr
ol :
68 /3
69 p
at ie
n ts
( 18
.5 %
) In
te rv
en ti
on :
2/ 18
1 p
at ie
n ts
( 1.
1% ),
p <
0 .0
00 1
C ri
ti ca
l u
n ac
ce p
ta b
le o
m it
te d
d os
e In
te r-
w ar
d c
on tr
ol :
51 /3
69 (
13 .8
% )
In te
rv en
ti on
: 2/
18 1
(1 .1
% ),
p =
0 .0
3
G re
en go
ld e
t al
.4 1
(U S
) R
an d
om is
ed , d
ir ec
t ob
se rv
at io
n s
tu d
y M
ed ic
al a
n d
su
rg ic
al u
n it
s of
a n
a ca
d em
ic
co m
m u
n it
y h
os p
it al
an
d a
u n
iv er
si ty
te
ac h
in g
h os
p it
al
T ot
al n
u m
b er
o f
n u
rs es
: M
ed ic
at io
n n
u rs
es :
10 G en
er al
n u
rs es
: 18
T M
E M
ed ic
at io
n a
d m
in is
tr at
io n
e rr
or s
(o b
se rv
at io
n )
C on
tr ol
: 54
5/ 36
61 o
p p
or tu
n it
ie s
fo r
er ro
r (1
4. 9%
) In
te rv
en ti
on :
91 2/
57 92
o p
p or
tu n
it ie
s fo
r er
ro r
(1 5.
7% ),
p <
0 .8
4 N
o kn
ow n
p at
ie n
t h
ar m
o r
d ea
th d
u ri
n g
st u
d y
p er
io d
s (d
at a
w er
e n
ot s
h ow
n )
N gu
ye n
e t
al .4
2 (U
S )
P ro
ce ss
im
p ro
ve m
en t
st u
d y
O n
e m
ed ic
al -
su rg
ic al
w ar
d in
ac
ad em
ic t
ea ch
in g
h os
p it
al
T ot
al n
u m
b er
o f
n u
rs es
: 45
T M
E -
T ea
ch in
g n
u rs
es
to u
n d
er ta
ke
m ed
ic at
io n
p as
s ti
m e
ou t
M ed
ic at
io n
a d
m in
is tr
at io
n e
rr or
s (o
b se
rv at
io n
) P
re -i
n te
rv en
ti on
: 2
er ro
rs /1
00 a
d m
in is
te re
d m
ed ic
at io
n s
P os
t- in
te rv
en ti
on :
0 er
ro rs
/1 00
a d
m in
is te
re d
m ed
ic at
io n
s, p
v al
u e
n ot
s ta
te d
S ch
n ei
d er
e t
al .4
3 (U
S )
R an
d om
is ed
, co
n tr
ol le
d , n
on -
b li
n d
ed s
tu d
y
M ed
ic al
o r
m ed
ic al
-s u
rg ic
al
u n
it s
of t
h re
e u
n iv
er si
ty h
os p
it al
s
T ot
al n
u m
b er
of
n u
rs es
: 30
, as
si gn
ed t
o ei
th er
c on
tr ol
o r
in te
rv en
ti on
g ro
u p
.
T M
E –
C D
-R O
M t
o n
u rs
es M
ed ic
at io
n a
d m
in is
tr at
io n
e rr
or r
at e
(i n
co rr
ec t
ti m
e, d
os e
p re
p ar
at io
n a
n d
t ec
h n
iq u
e)
(o b
se rv
at io
n ):
C on
tr ol
( p
re ):
2 9/
26 6
(1 0.
9% )
C on
tr ol
( p
os t)
: 25
/2 84
( 8.
8% )
In te
rv en
ti on
( p
re ):
1 6/
30 1
(5 .3
% )
In te
rv en
ti on
( p
os t)
: 41
/2 85
( 14
.4 %
) O
d d
s ra
ti o:
1 .9
2 (9
5% C
I 0 .8
1– 4.
58 ),
p =
0 .1
4
M D
D ea
n a
n d
B ar
b er
44
(U K
) P
ro sp
ec ti
ve
ob se
rv at
io n
al ,
b ef
or e
an d
a ft
er
st u
d y
M ed
ic al
w ar
d a
n d
su
rg ic
al w
ar d
o f
te ac
h in
g h
os p
it al
23 p
at ie
n ts
(s
u rg
ic al
w ar
d )
21 p
at ie
n ts
(m
ed ic
al w
ar d
)
P at
ie n
ts b
ri n
gi n
g in
o w
n m
ed ic
at io
n s
ve rs
us t
ra d
it io
n al
p
h ar
m ac
y su
p p
ly
A d
m in
is tr
at io
n e
rr or
s (o
b se
rv at
io n
): S
u rg
ic al
w ar
d :
T ra
d it
io n
al :
66 e
rr or
s/ 15
10 o
p p
or tu
n it
ie s
(4 .4
% )
In te
rv en
ti on
: 64
e rr
or s/
12 79
o p
p or
tu n
it ie
s (5
.0 %
) M
ed ic
al w
ar d
: T
ra d
it io
n al
: 86
e rr
or s/
20 66
o p
p or
tu n
it ie
s (4
.2 %
) In
te rv
en ti
on :
41 e
rr or
s/ 12
12 o
p p
or tu
n it
ie s
(3 .4
% )
O ve
ra ll
a d
m in
is tr
at io
n e
rr or
s: T
ra d
it io
n al
: 15
2 er
ro rs
/3 57
6 op
p or
tu n
it ie
s 4.
3% In
te rv
en ti
on :
10 5
er ro
rs /2
49 1
op p
or tu
n it
ie s
4. 2%
, p =
0 .9
9 S
ev er
it y
sc or
e (0
–1 0,
< 3
m in
or , 3
–7 m
od er
at e,
> 7
se ve
re )
S u
rg ic
al w
ar d
s C
on tr
ol :
M ea
n 1
.8 (
S D
1 .1
) In
te rv
en ti
on :
M ea
n 1
.8 (
S D
1 .1
), M
ed ic
al w
ar d
s C
on tr
ol :
M ea
n 1
.9 (
S D
1 .1
) In
te rv
en ti
on :
M ea
n 1
.9 (
1. 0)
, p =
0 .4
1
Ta b
le 1
. ( C
on ti
n u
ed )
(C on
ti nu
ed )
10 journals.sagepub.com/home/taw
Therapeutic Advances in Drug Safety 11 R
ef er
en ce
(c
ou n
tr y)
S tu
d y
d es
ig n
S et
ti n
g N
u m
b er
o f
p at
ie n
ts In
te rv
en ti
on t
yp e
Ty p
e of
m ed
ic at
io n
e rr
or a
n al
ys ed
( m
et h
od o
f d
at a
co ll
ec ti
on f
or m
ed ic
at io
n e
rr or
s) ,
ef fe
ct o
f in
te rv
en ti
on o
n m
ed ic
at io
n e
rr or
r at
e
S ch
im m
el e
t al
.4 5
(T h
e N
et h
er la
n d
s) P
ro sp
ec ti
ve
ob se
rv at
io n
al
b ef
or e
an d
a ft
er
st u
d y
30 -b
ed o
rt h
op ae
d ic
w
ar d
in a
u n
iv er
si ty
m
ed ic
al c
en tr
e
45 (
p re
- in
te rv
en ti
on ),
4 6
(p os
t- in
te rv
en ti
on )
M D
M ed
ic at
io n
a d
m in
is tr
at io
n e
rr or
s (o
b se
rv at
io n
) P
re -i
n te
rv en
ti on
: 11
4 er
ro rs
/5 89
t ot
al o
b se
rv ed
m ed
ic at
io n
a d
m in
is tr
at io
n (
19 .4
% )
P os
t- in
te rv
en ti
on :
17 0
er ro
rs /7
40 t
ot al
o b
se rv
ed m
ed ic
at io
n a
d m
in is
tr at
io n
( 23
.0 %
) O
d d
s ra
ti o:
1 .2
4 (9
5% C
I 0 .9
5– 1.
62 ),
p >
0 .0
5
D D
± e
M A
R
C ou
se in
e t
al .4
6 (F
ra n
ce )
B ef
or e–
af te
r ob
se rv
at io
n al
s tu
d y
40 -b
ed s
h or
t st
ay
ge ri
at ri
c u
n it
w it
h in
a
18 00
b ed
g en
er al
h
os p
it al
14 8
(p re
- in
te rv
en ti
on ),
1 66
(p
os t
in te
rv en
ti on
) B
as el
in e:
w ar
d
st oc
k sy
st em
D D
L in
ki n
g w
it h
o r
w it
h ou
t eM
A R
A d
m in
is tr
at io
n e
rr or
r at
es (
ob se
rv at
io n
) P
re -i
n te
rv en
ti on
: 74
/6 15
o p
p or
tu n
it ie
s of
e rr
or s
(1 0.
6% )
P os
t- in
te rv
en ti
on :
41 /7
83 o
p p
or tu
n it
ie s
of e
rr or
s (5
.0 %
) W
it h
ou t
eM A
R :
25 /3
78 o
p p
or tu
n it
ie s
of e
rr or
s (5
.8 %
) p
= 0.
02 W
it h
e M
A R
: 16
/4 05
o p
p or
tu n
it ie
s of
e rr
or s
(4 .1
% )
p =
0. 00
1 S
ev er
it y
of e
rr or
s N
o h
ar m
C on
tr ol
: 21
.1 %
In te
rv en
ti on
: 23
.2 %
M in
im u
m h
ar m
C on
tr ol
: 31
.7 %
In te
rv en
ti on
: 32
.7 %
M on
it or
in g
C on
tr ol
: 35
.0 %
In te
rv en
ti on
: 33
.3 %
N ee
d f
or in
te rv
en ti
on C
on tr
ol :
12 .2
% In
te rv
en ti
on :
10 .7
% , p
< 0
.0 1
C om
b in
at io
n o
f tw
o ty
p es
o f
in te
rv en
ti on
s
C an
n e
t al
.4 7
(A u
st ra
li a)
P re
–p os
t te
st
d es
ig n
29 -b
ed a
cu te
su
rg ic
al w
ar d
at
t er
ti ar
y- le
ve l
re gi
on al
h os
p it
al
11 15
( p
re -
in te
rv en
ti on
), 1
06 9
(p os
t- in
te rv
en ti
on )
P E
, P P
M ed
ic at
io n
e rr
or s
(d id
n ot
s p
ec if
y w
h ic
h t
yp e)
( on
li n
e cl
in ic
al in
ci d
en t
re p
or ti
n g)
P re
-i n
te rv
en ti
on :
12 .0
e rr
or s/
10 0,
00 0
p at
ie n
t h
ou rs
P os
t- in
te rv
en ti
on :
10 .9
e rr
or s/
10 0,
00 0
p at
ie n
t h
ou rs
, p =
0 .8
35 P
at ie
n t
fa ll
s P
re -i
n te
rv en
ti on
: 13
.9 /1
00 ,0
00 p
at ie
n t
h ou
rs P
os t-
in te
rv en
ti on
: 10
.9 /1
00 ,0
00 p
at ie
n t
h ou
rs , p
= 0
.5 0
D an
ie ls
e t
al .4
8 (U
S )
P ro
sp ec
ti ve
in
te rv
en ti
on H
IV -i
n fe
ct ed
p
at ie
n ts
a d
m it
te d
to
a 8
03 -b
ed
ac ad
em ic
m ed
ic al
ce
n tr
e
78 (
in te
rv en
ti on
),
68 (
co n
tr ol
) P
E , C
P O
E T
yp es
o f
er ro
rs (
in p
at ie
n t
p h
ar m
ac y
m ed
ic at
io n
s ys
te m
) P
re sc
ri b
in g
er ro
rs :
C on
tr ol
: 62
/1 19
t ot
al e
rr or
s (5
2% )
In te
rv en
ti on
: 12
/1 7
to ta
l er
ro rs
( 70
% )
D is
p en
si n
g er
ro rs
: C
on tr
ol :
39 /1
19 t
ot al
e rr
or s
(3 3%
) In
te rv
en ti
on :
4/ 17
t ot
al e
rr or
s (2
4% )
N o
p- va
lu e
re p
or te
d P
ot en
ti al
t o
ca u
se m
od er
at e
or s
ev er
e d
is co
m fo
rt o
r cl
in ic
al d
et er
io ra
ti on
C on
tr ol
: In
it ia
l re
gi m
en 3
8/ 68
( 56
% ),
D u
ri n
g h
os p
it al
is at
io n
4 4/
68 (
65 %
) In
te rv
en ti
on :
In it
ia l
re gi
m en
1 2/
78 (
15 %
), D
u ri
n g
h os
p it
al is
at io
n 1
7/ 78
( 22
% ),
p <
0 .0
00 1
G im
en ez
-M an
zo rr
o et
a l.4
9 (S
p ai
n )
P re
–p os
t in
te rv
en ti
on s
tu d
y w
it h
n o
eq u
iv al
en t
co n
tr ol
g ro
u p
G en
er al
s u
rg er
y d
ep ar
tm en
t 10
7 (p
re -
in te
rv en
ti on
), 8
4 (p
os t-
in te
rv en
ti on
)
C P
O E
, I T
-M R
U n
in te
n d
ed d
is cr
ep an
ci es
( p
re sc
ri b
in g
er ro
rs )
(p at
ie n
t in
te rv
ie w
) P
re -i
n te
rv en
ti on
: 10
2 u
n in
te n
d ed
d is
cr ep
an ci
es /8
87 t
ot al
n u
m b
er o
f d
is cr
ep an
ci es
(1
0. 6%
) P
os t-
in te
rv en
ti on
: 65
u n
in te
n d
ed d
is cr
ep an
ci es
/7 91
t ot
al n
u m
b er
o f
d is
cr ep
an ci
es
(6 .6
% ),
p =
0 .0
02
Ta b
le 1
. ( C
on ti
n u
ed )
(C on
ti nu
ed )
E Manias, S Kusljic et al.
journals.sagepub.com/home/taw 11
R ef
er en
ce
(c ou
n tr
y) S
tu d
y d
es ig
n S
et ti
n g
N u
m b
er o
f p
at ie
n ts
In te
rv en
ti on
t yp
e Ty
p e
of m
ed ic
at io
n e
rr or
a n
al ys
ed (
m et
h od
o f
d at
a co
ll ec
ti on
f or
m ed
ic at
io n
e rr
or s)
, ef
fe ct
o f
in te
rv en
ti on
o n
m ed
ic at
io n
e rr
or r
at e
G ri
m es
e t
al .5
0 (I
re la
n d
) U
n co
n tr
ol le
d
b ef
or e–
af te
r st
u d
y F
ou r
ac u
te m
ed ic
al
ca re
w ar
d s
11 2
in te
rv en
ti on
gr
ou p
, 1 21
st
an d
ar d
P L
-M R
, P P
E rr
or s
on a
d m
is si
on (
p re
sc ri
b in
g er
ro rs
) (p
re -a
d m
is si
on m
ed ic
at io
n l
is t,
c h
ar t
re vi
ew ,
d is
ch ar
ge m
ed ic
at io
n l
is t)
S ta
n d
ar d
: 49
p at
ie n
ts /1
21 t
ot al
n u
m b
er o
f p
at ie
n ts
( 40
.5 %
) In
te rv
en ti
on :
10 p
at ie
n ts
/1 12
t ot
al n
u m
b er
o f
p at
ie n
ts (
9% ),
p <
0 .0
00 1
E rr
or s
at d
is ch
ar ge
( p
re sc
ri b
in g
er ro
rs )
S ta
n d
ar d
: 66
p at
ie n
ts /1
01 t
ot al
n u
m b
er o
f p
at ie
n ts
( 65
.3 %
) In
te rv
en ti
on 1
5 p
at ie
n ts
/1 08
t ot
al n
u m
b er
o f
p at
ie n
ts (
13 .9
% ),
p <
0 .0
00 1
N o
h ar
m S
ta n
d ar
d :
35 (
34 .7
% )
In te
rv en
ti on
: 93
( 86
.1 %
) M
in or
h ar
m S
ta n
d ar
d :
6 (5
.9 %
) In
te rv
en ti
on :
2 (1
.9 %
) M
od er
at e
h ar
m S
ta n
d ar
d :
54 (
53 .5
% )
In te
rv en
ti on
: 13
( 12
.0 %
) S
ev er
e h
ar m
S ta
n d
ar d
: 6
(5 .9
% )
In te
rv en
ti on
: 0
(0 %
), p
< 0
.0 01
Jh ee
ta e
t al
.5 4
(U K
) In
te rr
u p
te d
t im
e se
ri es
, p re
–p os
t in
te rv
en ti
on s
tu d
y
A 1
4- b
ed e
ld er
ly
m ed
ic in
e in
p at
ie n
t w
ar d
in a
l ar
ge
te ac
h in
g h
os p
it al
86 (
p re
- in
te rv
en ti
on ),
8 6
(p os
t- in
te rv
en ti
on )
C P
O E
+ e
le ct
ro n
ic
ad m
in s
ys te
m (
C A
) M
ed ic
at io
n a
d m
in is
tr at
io n
e rr
or s
(o b
se rv
at io
n )
P re
-i n
te rv
en ti
on :
18 /4
28 o
p p
or tu
n it
ie s
fo r
er ro
r (4
.2 %
) P
os t-
in te
rv en
ti on
: 18
/5 28
o p
p or
tu n
it ie
s fo
r er
ro r
(3 .4
% ),
p =
0 .6
4 D
oc u
m en
ta ti
on d
is cr
ep an
ci es
P re
-i n
te rv
en ti
on :
5/ 46
0 ob
se rv
ed d
oc u
m en
ta ti
on s
(1 .1
% )
P os
t- in
te rv
en ti
on :
18 /5
57 o
b se
rv ed
d oc
u m
en ta
ti on
s (3
.2 %
), p
= 0
.0 4
M ou
ra e
t al
.5 1
(B ra
zi l)
Q u
as i-
ex pe
ri m
en ta
l st
u d
y A
1 72
-b ed
p
u b
li c
in st
it u
ti on
p
ro vi
d in
g p
ri m
ar y
an d
t er
ti ar
y ca
re
18 52
( p
re -
in te
rv en
ti on
), 2
95
(i n
te rv
en ti
on )
C P
O E
, P P
In ci
d en
ce r
at e
of a
ll d
ru g-
d ru
g in
te ra
ct io
n s
(c h
ar t
re vi
ew )
P re
-i n
te rv
en ti
on :
27 .5
/1 00
0 p
at ie
n t
d ay
s In
te rv
en ti
on :
13 .2
/1 00
0 p
at ie
n t
d ay
s, r
el at
iv e
ri sk
= 0
.4 8
(0 .4
4– 0.
52 )
In ci
d en
ce r
at e
of h
ig h
-s ev
er it
y d
ru g-
d ru
g in
te ra
ct io
n s:
P re
-i n
te rv
en ti
on :
8. 20
/1 00
0 p
at ie
n t
d ay
s In
te rv
en ti
on :
1. 36
/1 00
0 p
at ie
n t
d ay
s, r
el at
iv e
ri sk
= 0
.1 7
(0 .1
3– 0.
21 )
S h
ea e
t al
.5 2
(U S
) R
et ro
sp ec
ti ve
co
m p
ar at
iv e
co h
or t
st u
d y
H IV
-i n
fe ct
ed
p at
ie n
ts a
d m
it te
d
to a
2 44
-b ed
u rb
an
ac ad
em ic
m ed
ic al
ce
n tr
e
T ot
al 2
34 p
at ie
n t
ad m
is si
on s
P re
-i n
te rv
en ti
on :
12 6
P os
t- in
te rv
en ti
on :
10 8
P E
, P L
-M R
P at
ie n
t ad
m is
si on
s w
it h
p re
sc ri
b in
g er
ro rs
( ch
ar t
re vi
ew )
S u
m o
f in
co rr
ec t/
in co
m p
le te
m ed
ic at
io n
r eg
im en
, i n
co rr
ec t
d os
ag e
re gi
m en
, i n
co rr
ec t
re n
al d
os e
ad ju
st m
en t,
m aj
or d
ru g
in te
ra ct
io n
P re
-i n
te rv
en ti
on :
73 /1
26 t
ot al
a d
m is
si on
P os
t- in
te rv
en ti
on :
10 /1
08 t
ot al
a d
m is
si on
P at
ie n
t ad
m is
si on
s w
it h
m ed
ic at
io n
e rr
or t
yp es
In co
rr ec
t/ in
co m
p le
te m
ed ic
at io
n r
eg im
en P
re -i
n te
rv en
ti on
: 15
/1 26
t ot
al a
d m
is si
on (
11 .9
% )
P os
t- in
te rv
en ti
on :
0/ 10
8 to
ta l
ad m
is si
on , p
< 0
.0 01
In co
rr ec
t d
os ag
e re
gi m
en P
re -i
n te
rv en
ti on
: 13
/1 26
t ot
al a
d m
is si
on (
10 .3
% )
P os
t- in
te rv
en ti
on :
0/ 10
8 to
ta l
ad m
is si
on , p
< 0
.0 01
In co
rr ec
t re
n al
d os
e ad
ju st
m en
t P
re -i
n te
rv en
ti on
: 9/
12 6
to ta
l ad
m is
si on
( 7.
1% )
P os
t- in
te rv
en ti
on :
0/ 10
8 to
ta l
ad m
is si
on , p
= 0
.0 1
In co
rr ec
t ad
m in
is tr
at io
n P
re -i
n te
rv en
ti on
: 56
/1 26
t ot
al a
d m
is si
on (
44 .4
% )
P os
t- in
te rv
en ti
on :
3/ 10
8 to
ta l
ad m
is si
on (
2. 8%
), p
< 0
.0 01
M aj
or d
ru g
in te
ra ct
io n
P re
-i n
te rv
en ti
on :
36 /1
26 t
ot al
a d
m is
si on
( 28
.6 %
) P
os t-
in te
rv en
ti on
: 10
/1 08
t ot
al a
d m
is si
on (
9. 3%
), p
= 0
.0 01
Ta b
le 1
. ( C
on ti
n u
ed )
(C on
ti nu
ed )
12 journals.sagepub.com/home/taw
Therapeutic Advances in Drug Safety 11 R
ef er
en ce
(c
ou n
tr y)
S tu
d y
d es
ig n
S et
ti n
g N
u m
b er
o f
p at
ie n
ts In
te rv
en ti
on t
yp e
Ty p
e of
m ed
ic at
io n
e rr
or a
n al
ys ed
( m
et h
od o
f d
at a
co ll
ec ti
on f
or m
ed ic
at io
n e
rr or
s) ,
ef fe
ct o
f in
te rv
en ti
on o
n m
ed ic
at io
n e
rr or
r at
e
C om
b in
at io
n o
f th
re e
ty p
es o
f in
te rv
en ti
on s
S an
d er
s et
a l.5
3 (U
S )
R et
ro sp
ec ti
ve
b ef
or e–
af te
r st
u d
y H
IV in
fe ct
ed
p at
ie n
ts a
d m
it te
d
to a
l ar
ge a
ca d
em ic
m
ed ic
al c
en tr
e
16 2
(p re
- in
te rv
en ti
on ),
1 10
(p
os t-
in te
rv en
ti on
)
C P
O E
, P E
, I C
A n
ti m
ic ro
b ia
l st
ew ar
d sh
ip
p ro
gr am
: u
p d
at es
of
e le
ct ro
n ic
m
ed ic
at io
n
re co
rd s
w it
h in
C
P O
E , e
d u
ca ti
on ,
co ll
ab or
at iv
e st
ew ar
d sh
ip
ef fo
rt w
it h
in
fe ct
io u
s d
is ea
se s
d ep
ar tm
en t
P re
sc ri
b in
g er
ro rs
( ch
ar t
re vi
ew )
P re
-i n
te rv
en ti
on :
12 4
to ta
l er
ro rs
P os
t- in
te rv
en ti
on :
43 t
ot al
e rr
or s
N o
d en
om in
at or
g iv
en N
o p-
va lu
e re
p or
te d
N u
m b
er o
f ad
m is
si on
s w
it h
a m
ed ic
at io
n e
rr or
P re
-i n
te rv
en ti
on :
81 /1
62 a
d m
is si
on s
(5 0%
) P
os t-
in te
rv en
ti on
: 37
/1 10
a d
m is
si on
s (3
4% ),
p <
0 .0
01
A D
E , a
d ve
rs e
d ru
g ev
en t;
C A
, C P
O E
+ e
le ct
ro n
ic a
d m
in is
tr at
io n
s ys
te m
; C
D S
S , C
P O
E w
it h
o r
w it
h ou
t cl
in ic
al d
ec is
io n
s u
p p
or t
sy st
em ;
C P
O E
, c om
p u
te ri
se d
p h
ys ic
ia n
o rd
er e
n tr
y; D
D , a
u to
m at
ed d
ru g
d is
tr ib
u ti
on s
ys te
m ;
eM A
R , e
le ct
ro n
ic m
ed ic
at io
n a
d m
in is
tr at
io n
r ec
or d
; H
IV , h
u m
an im
m u
n od
ef ic
ie n
cy v
ir u
s; IC
, i n
te rd
is ci
p li
n ar
y co
ll ab
or at
io n
; IT
-M R
, c om
p u
te ri
se d
m ed
ic at
io n
r ec
on ci
li at
io n
; M
D ,
m ed
ic at
io n
d is
p en
si n
g; P
E , p
re sc
ri b
er e
d u
ca ti
on ;
P L
-M R
, p h
ar m
ac is
t- le
d m
ed ic
at io
n r
ec on
ci li
at io
n ;
P P
, p h
ar m
ac is
t p
ar tn
er sh
ip ;
P T
E , p
at ie
n t
ed u
ca ti
on ;
T M
E , t
ra in
ed m
ed ic
at io
n e
xp er
ts ;
U D
, u n
in te
n ti
on al
d
is cr
ep an
ci es
; U
K , U
n it
ed K
in gd
om ;
U S
, U n
it ed
S ta
te s.
Ta b
le 1
. ( C
on ti
n u
ed )
Data synthesis Data synthesis was undertaken qualitatively, which involved grouping results into meaningful clusters. These meaningful clusters comprised categorising results in terms of dispensing errors, prescribing errors, and administration errors, as well as examining the types of interventions used. Patterns of medication errors were examined across and between studies.
For the calculation of meta-analysis, data were entered into RevMan software according to inter- vention types. The risk ratio was calculated for categorical outcomes relating to dispensing, pre- scribing and administration medication errors. For medication error types expressed as continu- ous outcomes, the standard mean difference was calculated. Studies with incomplete data for RevMan entry were excluded from the meta-anal- ysis. Statistical heterogeneity was calculated and reported in forest plots.
Results The initial search identified 1980 studies. No additional articles were identified after perform- ing key article cross-checking on Web of Science and Scopus. There were 135 articles selected for full-text screening, of which 34 articles were included for data extraction. A PRISMA flow diagram is included in Figure 1. A total of 26 studies reported on prescribing errors, 11 studies on administration errors and 2 studies on dis- pensing errors (Table 1).
Study and patient characteristics The sample size ranged from 33 to 1115 patients in the intervention arm,31,47 and from 40 to 1852 patients in the control arm.23,51 The most common study design was a pre–post intervention design, used in 20 studies.27,28,30–32,35–37,40,44–54 Nine studies were randomised controlled trials (RCTs.21,23– 26,38,39,41,43 There were two quality improvement studies,42,29 one study involved a prospective chart review with a historical control,22 one study involved an interrupted time series design34 and one study comprised a prospective observational design.33
A total of 9 studies involved implementation of interventions in both medical and surgical units; 21 studies were conducted in medical units while 4 studies were conducted in surgical units. Chart review was the most common data collection
E Manias, S Kusljic et al.
journals.sagepub.com/home/taw 13
Note. Some studies examined more than one type of medication error.
Records identified through database searching (n=1980)
S cr ee n in g
In cl u d ed
E li g ib il it y
Id en ti fi ca ti on
Additional records identified through reference lists from systematic reviews
(n=5)
Records after duplicates removed (n=1503)
Titles and abstract records screened (n=1503)
Records excluded with reasons
(n = 1368) Wrong outcome (n=1368)
Full-text articles assessed for eligibility (n=135)
Full-text articles excluded with reasons
(n = 101) Wrong outcome (n=59) Wrong setting (n=24)
Conference abstract (n=9) Wrong population (n=6)
Wrong study design (n=3)Studies included in qualitative synthesis (n=34)
Studies included in quantitative synthesis
(meta-analysis) for administration errors
(n=11)
Studies included in quantitative synthesis
(meta-analysis) for prescribing errors (n=26)
Studies included in quantitative synthesis
(meta-analysis) for dispensing errors (n=2)
Figure 1. PRISMA flow diagram. Some studies examined more than one type of medication error. PRISMA, preferred reporting items for systematic reviews and meta-analyses.
method used to obtain information about medica- tion errors (n = 19), followed by observations (n = 8) and patient and family interviews (n = 5). Other methods used included review of discharge summaries (n = 2), electronic medical record review (n = 2), participation in ward rounds (n = 1), clinical incident reports (n = 1), the inpatient phar- macy system (n = 1), prescription coverage plan (n = 1), health provider interviews (n = 1), patient notes (n = 1) and the preadmission medication list (n = 1). In six studies, more than one method was used to collect data on medication errors. Out of the 34 included studies, 21 contained details about the clinical significance of the medication errors. This information was mainly in the form of severity of the medication errors in causing harm.
Other studies provided details about clinical sig- nificance in relation to the medication errors pro- longing length of hospital stay (n = 2), or contributing to hospital readmission (n = 1), patient mortality (n = 2) and falls (n = 1) (Table 1).
Quality of studies A total of 9 randomised controlled studies scored 49–70% using the CONSORT guideline (Table 2). The quality improvement studies scored 48–80% using the SQUIRE guideline (Table 3); 23 studies scored 36–73% according to the TREND guideline (Table 4). Figure 2 contains the risk of bias graph while Figure 3 shows the risk of bias summary.
14 journals.sagepub.com/home/taw
Therapeutic Advances in Drug Safety 11
Ta b
le 2
. Q
u al
it y
as se
ss m
en t
fo r
ra n
d om
iz ed
c on
tr ol
le d
t ri
al s
an d
c lu
st er
r an
d om
iz ed
c on
tr ol
le d
t ri
al s
u si
n g
th e
C O
N S
O R
T g
u id
el in
es (
n =
9) .
R ef
er en
ce
(C ou
n tr
y)
(i n
te rv
en ti
on )
S tu
d y
d es
ig n
Ti tl
e an
d
A bs
t
In tr
o Tr
ia l
D es
ig P
ar t
In t
O u
tc S
p S
z R
an d
S
eq
G en
R an
d
A ll
oc R
an d
Im
p l
B li
n d
S ta
t.
M et
h P
ar t
F lo
w R
ec ru
B as
. D
at a
N u
m
A n
a O
u t
&
E st
A n
c A
n al
H ar
m L
im .
G en
In tp
R eg
P ro
t F
u n
d n/
N %
A l-
H as
h ar
et
a l.2
1 (O
m an
) (P
L -M
R )
P ro
sp ec
ti ve
ra
n d
om is
ed
co n
tr ol
le d
st
u d
y
1/ 2
2/ 2
1/ 2
2/ 2
1/ 1
1/ 2
1/ 2
2/ 2
1/ 1
1/ 1
0/ 2
1/ 2
2/ 2
1/ 2
1/ 1
1/ 1
1/ 2
1/ 1
0/ 1
1/ 1
1/ 1
1/ 1
1/ 1
0/ 1
1/ 1
26 /3
7 70
%
B ec
ke tt
et
a l.2
3 (U
S )
(P L
-M R
)
P ro
sp ec
ti ve
ra
n d
om is
ed ,
n on
-b li
n d
ed
st u
d y
1/ 2
2/ 2
1/ 2
2/ 2
1/ 1
1/ 2
0/ 2
1/ 2
0/ 1
1/ 1
0/ 2
1/ 2
1/ 2
1/ 2
1/ 1
1/ 1
1/ 2
0/ 1
0/ 1
1/ 1
1/ 1
1/ 1
0/ 1
0/ 1
1/ 1
20 /3
7 54
%
B oo
ck va
r et
a l.2
4 (U
S )
(P L
-M R
)
C lu
st er
- ra
n d
om is
ed
co n
tr ol
le d
tr
ia l
2/ 2
2/ 2
2/ 2
2/ 2
1/ 1
1/ 2
1/ 2
0/ 2
0/ 1
0/ 3
1/ 2
2/ 2
2/ 2
1/ 2
1/ 1
1/ 1
1/ 2
1/ 1
0/ 1
1/ 1
1/ 1
1/ 1
1/ 1
1/ 1
1/ 1
27 /3
9 69
%
C ad
m an
et
a l.2
5 (U
K )
(P L
-M R
)
P il
ot
ra n
d om
is ed
co
n tr
ol le
d
tr ia
l
2/ 2
2/ 2
2/ 2
2/ 2
1/ 1
1/ 2
1/ 2
2/ 2
1/ 1
1/ 1
0/ 2
2/ 2
1/ 2
1/ 2
0/ 1
1/ 1
1/ 2
0/ 1
0/ 1
1/ 1
1/ 1
1/ 1
1/ 1
0/ 1
1/ 1
26 /3
7 70
%
T on
g et
a l.2
6 (A
u st
ra li
a) (P
L -M
R )
U n
b li
n d
ed ,
cl u
st er
ra
n d
om is
ed ,
co n
tr ol
le d
st
u d
y
2/ 2
2/ 2
1/ 2
2/ 2
1/ 1
1/ 2
1/ 2
1/ 2
1/ 1
2/ 3
0/ 2
1/ 2
2/ 2
1/ 2
1/ 1
1/ 1
1/ 2
0/ 1
0/ 1
1/ 1
1/ 1
1/ 1
1/ 1
0/ 1
1/ 1
26 /3
9 66
%
G u
rs an
sc ky
et
a l.3
8 (A
u st
ra li
a) (P
E )
C lu
st er
ra
n d
om is
ed
tr ia
l in
vo lv
in g
p re
sc ri
b er
s
1/ 2
2/ 2
2/ 2
2/ 2
1/ 1
0/ 2
0/ 2
1/ 2
1/ 1
1/ 3
1/ 2
2/ 2
1/ 2
1/ 2
0/ 1
1/ 1
1/ 2
1/ 1
0/ 1
1/ 1
1/ 1
1/ 1
0/ 1
0/ 1
0/ 1
22 /3
9 56
%
W ei
n ga
rt
et a
l.3 9
(U S
) (P
T E
)
P ro
sp ec
ti ve
ra
n d
om is
ed ,
co n
tr ol
le d
p
il ot
t ri
al
1/ 2
2/ 2
1/ 2
2/ 2
1/ 1
0/ 2
0/ 2
1/ 2
1/ 1
1/ 1
1/ 2
2/ 2
2/ 2
1/ 2
1/ 1
1/ 1
1/ 2
1/ 1
0/ 1
1/ 1
1/ 1
1/ 1
0/ 1
1/ 1
1/ 1
25 /3
7 68
%
G re
en go
ld
et a
l.4 1
(U S
) (T
M E
)
R an
d om
is ed
, d
ir ec
t ob
se rv
at io
n
st u
d y
2/ 2
2/ 2
1/ 2
1/ 2
1/ 1
1/ 2
0/ 2
1/ 2
1/ 1
1/ 1
0/ 2
1/ 2
0/ 2
1/ 2
0/ 1
1/ 1
1/ 2
0/ 1
0/ 1
1/ 1
1/ 1
1/ 1
0/ 1
0/ 1
0/ 1
18 /3
7 49
%
S ch
n ei
d er
et
a l.4
3 (U
S )
(T M
E )
R an
d om
is ed
, co
n tr
ol le
d ,
n on
-b li
n d
ed
st u
d y
1/ 2
1/ 2
2/ 2
2/ 2
1/ 2
1/ 2
1/ 2
2/ 2
0/ 1
0/ 1
0/ 2
1/ 2
1/ 2
0/ 2
2/ 2
2/ 2
2/ 2
1/ 1
0/ 1
0/ 1
0/ 1
1/ 1
0/ 1
0/ 1
1/ 1
22 /3
7 59
%
A n
c A
n al
, a n
ci ll
ar y
an al
ys es
; B
as D
at a,
b as
el in
e d
at a;
B li
n d
, b li
n d
in g;
F u
n d
, f u
n d
in g;
G en
, g en
er al
iz ab
il it
y; H
ar m
, h ar
m s,
In t,
in te
rv en
ti on
s; In
tp , i
n te
rp re
ta ti
on ;
In tr
o, in
tr od
u ct
io n
; L
im , l
im it
at io
n s;
N u
m A
n a,
n u
m b
er s
an al
ys ed
; O
u t
& E
st ,
ou tc
om es
a n
d e
st im
at io
n ;
O u
tc , o
u tc
om es
; P
ar t,
p ar
ti ci
p an
ts ;
P ar
t F
lo w
, p ar
ti ci
p an
t fl
ow ;
P E
, p re
sc ri
b er
e d
u ca
ti on
; P
L -M
R , p
h ar
m ac
is t-
le d
m ed
ic at
io n
r ec
on ci
li at
io n
; P
ro t,
p ro
to co
l; P
T E
, p at
ie n
t ed
u ca
ti on
; R
an d
A ll
oc , r
an d
om is
at io
n a
ll oc
at io
n ;
R an
d Im
p l,
r an
d om
is at
io n
im p
le m
en ta
ti on
; R
an d
S eq
G en
, r an
d om
is at
io n
s eq
u en
ce g
en er
at io
n ;
R ec
ru , r
ec ru
it m
en t;
R eg
, r eg
is tr
at io
n ;
S p
S z,
s am
p le
s iz
e; S
ta t
M et
h , s
ta ti
st ic
al m
et h
od s;
T it
le &
A b
st , t
it le
a n
d a
b st
ra ct
; T
M E
; tr
ai n
ed m
ed ic
at io
n
ex p
er ts
; Tr
ia l
D es
ig , t
ri al
d es
ig n
; U
S , U
n it
ed S
ta te
s.
E Manias, S Kusljic et al.
journals.sagepub.com/home/taw 15
Ta b
le 3
. Q
u al
it y
as se
ss m
en t
fo r
th e
q u
al it
y im
p ro
ve m
en t
st u
d y
u si
n g
th e
S Q
U IR
E g
u id
el in
es (
n =
2) .
R ef
er en
ce
(C ou
n tr
y)
(i n
te rv
en ti
on )
T it
le A
b st
P ro
b .
d es
c A
va il
k
n ow
R at
io n
S p
ec
ai m
s C
on te
xt In
te rv
S tu
d y
of t
h e
in te
rv
M ea
su A
n al
y E
th
co n
si d
R es
u lt
s S
u m
m ar
y In
te rp
L im
it C
on cl
u F
u n
d n/
N %
S ch
n ip
p er
et
a l.2
9 (U
S )
(M R
)
1/ 1
2/ 2
1/ 1
1/ 1
1/ 1
1/ 1
1/ 1
1/ 2
2/ 2
1/ 3
2/ 2
0/ 1
5/ 6
2/ 2
5/ 5
3/ 3
2/ 5
1/ 1
32 /4
0 80
%
N gu
ye n
et
a l.4
2 (U
S )
(T M
E )
1/ 1
1/ 1
1/ 1
1/ 1
0/ 1
0/ 1
0/ 1
1/ 2
1/ 2
1/ 3
0/ 2
1/ 1
3/ 6
1/ 2
2/ 5
2/ 3
2/ 5
1/ 1
19 /4
0 48
%
A b
st , a
b st
ra ct
; A
n al
y, a
n al
ys is
; A
va il
K n
ow , a
va il
ab le
k n
ow le
d ge
; C
on cl
u , c
on cl
u si
on s;
E th
C on
si d
, e th
ic al
c on
si d
er at
io n
; F
u n
d , f
u n
d in
g; In
te rp
, i n
te rp
re ta
ti on
; In
te rv
, i n
te rv
en ti
on ;
L im
it , l
im it
at io
n s,
M ea
su , m
ea su
re s;
M R
, m ed
ic at
io n
r ec
on ci
li at
io n
; P
ro b
D es
c, p
ro b
le m
d es
cr ip
ti on
; R
at io
n , r
at io
n al
e; S
p ec
A im
s, s
p ec
if ic
a im
s; S
tu d
y of
t h
e In
te rv
, s tu
d y
of t
h e
in te
rv en
ti on
; T
M E
, t ra
in ed
m ed
ic at
io n
e xp
er ts
; U
S , U
n it
ed S
ta te
s.
Identified interventions The 12 intervention types identified were: phar- macist-led medication reconciliation, computer- ised medication reconciliation, medication reconciliation by trained mentors, computerised physician order entry (CPOE) with or without a clinical decision support system, pharmacist part- nership, prescriber education, patient education, trained medication experts, medication dispens- ing, use of an automated drug distribution system with or without electronic medication administra- tion record, interdisciplinary collaboration and electronic administration system (Table 5). Various combinations of interventions were also identified.
Prescribing error rates were reduced in 14 out of 26 studies, while administration error rates were reduced in 4 out of 11 studies. Out of two studies using interventions for dispensing, no studies reported a significant reduction in dis- pensing errors. Figure 4 shows a summary of risk ratios for studies that reported on prescrib- ing errors as categorical variables. Figure 5 shows the mean differences for studies report- ing on prescribing errors as continuous varia- bles, whereas Figures 6 and 7 present the risk ratio summaries for administration and dis- pensing errors respectively.
Pharmacist-led medication reconciliation Six studies investigated the effect of pharmacist- led medication reconciliation on prescribing errors, with two out of the six studies reporting a reduction in prescribing error rates. Al-Hashar et al. showed a reduction of preventable adverse drug events (ADEs) from 16% to 9.1% (p = 0.008).21 The percentage of patients with prescribing errors reduced from 35.1% to 16.7% in the work of Batra et al.22 A pilot randomised controlled trial reported a reduction of uninten- tional discrepancies (UDs) from 2.71 errors per patient in the intervention group (268 UDs in 99 patients) to 0.02 errors per patient in the control group (2 UDs in 91 patients).25 There was no significant difference in prescribed medication discrepancies in the study by Beckett et al., with 45 medication discrepancies in the control group and 71 in the intervention group (p = 0.074).23 Boockvar et al. reported no difference in mean medication discrepancy (3.0 versus 3.2, p = 0.452).24
16 journals.sagepub.com/home/taw
Therapeutic Advances in Drug Safety 11
Ta b
le 4
. Q
u al
it y
as se
ss m
en t
fo r
q u
as i-
ex p
er im
en ta
l st
u d
ie s
u si
n g
th e
T R
E N
D g
u id
el in
es (
n =
23 ).
R ef
er en
ce
(C ou
n tr
y)
(i n
te rv
en ti
on )
T it
le
an d
ab
st
B g
d P
ar ti
c In
t O
b j
O u
tc S
p S
z A
ss ig
n .
m td
B ld
U n
it o
f an
al S
ta t
m td
P ar
t fl
ow R
ec ru
B as
el
d at
a B
as el
eq
u iv
N o
an al
O u
tc &
es
ti m
A n
c an
al A
d v
ev In
te r
G en
O v
ev id
n/ N
%
B at
ra e
t al
.2 2
(U S
) (P
L -M
R )
2/ 3
1/ 2
4/ 4
3/ 9
1/ 1
1/ 3
0/ 1
0/ 3
0/ 1
1/ 2
3/ 4
2/ 7
1/ 1
1/ 4
0/ 1
1/ 2
1/ 3
0/ 1
0/ 1
2/ 4
0/ 1
1/ 1
25 /5
9 42
%
A ll
is on
e t
al .2
7 (U
S )
(I T
-M R
)
1/ 3
1/ 2
4/ 4
5/ 9
1/ 1
2/ 3
0/ 1
0/ 3
0/ 1
1/ 2
3/ 4
4/ 7
1/ 1
3/ 4
1/ 1
1/ 2
1/ 3
0/ 1
0/ 1
3/ 4
1/ 1
1/ 1
34 /5
9 58
%
S m
it h
e t
al .2
8 (U
S )
(I T
-M R
)
2/ 3
1/ 2
4/ 4
4/ 9
1/ 1
2/ 3
1/ 1
0/ 3
0/ 1
1/ 2
2/ 4
1/ 7
1/ 1
3/ 4
1/ 1
1/ 2
3/ 3
1/ 1
0/ 1
3/ 4
0/ 1
1/ 1
33 /5
9 56
%
H er
n an
d ez
et
a l.3
0 (F
ra n
ce )
(C P
O E
)
2/ 3
1/ 2
4/ 4
4/ 9
1/ 1
1/ 3
0/ 1
0/ 3
1/ 1
1/ 2
2/ 4
1/ 7
1/ 1
3/ 4
0/ 1
1/ 2
2/ 3
1/ 1
0/ 1
3/ 4
0/ 1
1/ 1
30 /5
9 51
%
M il
an i e
t al
.3 1
(U S
) (C
P O
E +
C D
S S
)
2/ 3
1/ 2
4/ 4
4/ 9
1/ 1
1/ 3
0/ 1
0/ 3
0/ 1
1/ 2
3/ 4
3/ 7
1/ 1
2/ 4
1/ 1
1/ 2
1/ 3
1/ 1
0/ 1
3/ 4
1/ 1
1/ 1
32 /5
9 54
%
P et
ti t
et a
l.3 2
(U S
) (C
P O
E )
2/ 3
1/ 2
4/ 4
4/ 9
1/ 1
1/ 3
0/ 1
0/ 3
0/ 1
1/ 2
2/ 4
1/ 7
1/ 1
0/ 4
0/ 1
1/ 2
1/ 3
1/ 1
0/ 1
3/ 4
0/ 1
1/ 1
25 /5
9 42
%
S h
aw ah
n a
et a
l.3 3
(U S
) (C
P O
E )
3/ 3
1/ 2
2/ 4
5/ 9
1/ 1
2/ 3
0/ 1
1/ 3
1/ 1
0/ 2
2/ 4
0/ 7
0/ 1
0/ 4
0/ 1
1/ 2
2/ 3
1/ 1
1/ 1
2/ 4
0/ 1
1/ 1
26 /5
9 44
%
va n
D oo
rm aa
l et
a l.3
4 (T
h e
N et
h er
la n
d s)
(C
P O
E )
2/ 3
1/ 2
2/ 4
7/ 9
1/ 1
3/ 3
1/ 1
2/ 3
0/ 1
1/ 2
2/ 4
5/ 7
1/ 1
3/ 4
1/ 1
2/ 2
2/ 3
1/ 1
1/ 1
3/ 4
1/ 1
1/ 1
43 /5
9 73
%
G ar
ci a-
M ol
in a
S ae
z et
a l.3
5 (S
p ai
n )
(P P
)
2/ 3
1/ 2
4/ 4
5/ 9
1/ 1
1/ 3
0/ 1
0/ 3
0/ 1
1/ 2
3/ 4
2/ 7
1/ 1
3/ 4
1/ 1
1/ 2
1/ 3
1/ 1
0/ 1
3/ 4
1/ 1
1/ 1
33 /5
9 56
%
H as
sa n
e t
al .3
6 (M
al ay
si a)
(P P
)
2/ 3
1/ 2
4/ 4
4/ 9
1/ 1
1/ 3
0/ 1
0/ 3
0/ 1
1/ 2
3/ 4
0/ 7
1/ 1
1/ 4
1/ 1
1/ 2
1/ 3
0/ 1
0/ 1
3/ 4
1/ 1
1/ 1
27 /5
9 46
%
L ie
d tk
e et
a l.3
7 (U
S )
(P P
)
3/ 3
1/ 2
4/ 4
4/ 9
1/ 1
2/ 3
0/ 1
0/ 3
1/ 1
1/ 2
3/ 4
2/ 7
1/ 1
3/ 4
0/ 1
1/ 2
1/ 3
0/ 1
0/ 1
3/ 4
1/ 1
1/ 1
33 /5
9 56
%
D ea
n a
n d
B
ar b
er 44
( U
K )
(M D
)
1/ 3
1/ 2
2/ 4
4/ 9
1/ 1
3/ 3
1/ 1
2/ 3
0/ 1
2/ 2
3/ 4
2/ 7
0/ 1
0/ 4
0/ 1
1/ 2
3/ 3
1/ 1
1/ 1
4/ 4
1/ 1
1/ 1
34 /5
9 58
%
S ch
im m
el
et a
l. 45
(N
et h
er la
n d
) (M
D )
2/ 3
1/ 2
3/ 4
4/ 9
1/ 1
2/ 3
1/ 1
0/ 3
0/ 1
1/ 2
3/ 4
2/ 7
1/ 1
2/ 4
1/ 1
1/ 2
2/ 3
0/ 1
0/ 1
3/ 4
0/ 1
1/ 1
31 /5
9 53
%
(C on
ti nu
ed )
E Manias, S Kusljic et al.
journals.sagepub.com/home/taw 17
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Therapeutic Advances in Drug Safety 11
Computerised medication reconciliation Two studies employed computerised medication reconciliation to reduce medication errors at dis- charge and only one showed a significant reduc- tion in errors. In a medication antimicrobial reconciliation program at discharge, Allison et al. undertook a retrospective examination of patients’ medical records to investigate the presence of intravenous antibiotics in their discharge orders before and after the implementation of the inter- vention.27 Patients with at least one discharge medication error decreased from 23/100 in the pre-intervention period to 11/100 in the post- intervention period (p-value was not reported). Smith et al. conducted a quasi-experimental study and reported a significant reduction (p < 0.001) in discharge medication errors from 645 errors/3490 medication variance in the pre- intervention period to 359 errors/2823 medica- tion variance in the post-intervention period.28 The study also found no change in medication errors having the potential to produce serious or life-threatening harm with 1.4% (9/645 errors) at pre-intervention and 3.1% (11/359 errors at post- intervention, p = 0.10).
Medication reconciliation by trained mentors One study specified that trained mentors com- prising physicians with medication safety experi- ence carried out medication reconciliation.29 Three hospitals were intervention sites and two hospitals were concurrent controls. The outcome was reported as potentially harmful discrepancies in admission and discharge orders per patient. Only two sites (sites 2 and 3) out of five had results for both control units and intervention units. In site 2, the mean number of errors per patient decreased from 1.00 to 0.88. A similar
result was found in site 3 where the mean number of errors per patient decreased from 0.30 to 0.18.
CPOE with or without a clinical decision support system Five studies examined the use of CPOE and reported significant improvements in reduction of medication errors. Hernandez et al. conducted a before-and-after observational study in an ortho- paedic surgery unit using CPOE without a clinical decision support system.30 Prescribing errors decreased from 30.1% (479 errors/1593 prescribed medications) in the pre-intervention period to 2.4% (33 errors/1388 prescribed medications) in the post-intervention period (p < 0.0001). The study also found a significant reduction in adminis- tration errors (p < 0.05) but showed no significant change in dispensing errors. CPOE with a clinical decision support system was employed by Milani et al. for patients with chronic kidney disease who were admitted with acute coronary syndrome.31 The number of patients with contraindicated medi- cations decreased from 8/47 in the control group to 0/33 in the intervention group (p = 0.01). Pettit et al. found a significant reduction in the number of patients with prescribing errors from 84/167 (50.2%) in the pre-intervention period to 37/131 (28.2%) in the post-intervention period (p < 0.01).32 Shawahna et al. compared paper based with elec- tronic prescribing in Pakistan in a prospective chart review.33 They found prescribing errors differed significantly between control and intervention wards with a mean prescription errors of 21.4% and 6.9% errors respectively. van Doormaal et al. undertook an interrupted time series design and found following CPOE, prescribing errors reduced from 63.3% at baseline to 18.8% following the intervention.34
Figure 2. Risk of bias graph.
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Figure 3. Risk of bias summary.
Pharmacist partnership Three studies examined the effect of pharmacist partnership and showed significant reductions in prescribing errors. Garcia-Molina Saez et al. involved pharmacists who participated on the medical team who entered patients’ pre-admis- sion medications in a computerised tool, which were then integrated into their clinical history.35 Results showed a significant decrease in prescrip- tion reconciliation errors from 47.7% (518/1087) in the pre-intervention period to 17.3% (188/1087) following the intervention period (p < 0.001). Pharmacists were involved in ward rounds in the study conducted by Hassan et al., where the number of inappropriate medications were lower in the intervention group (11.4%, 322/2, 814 total prescriptions) compared with the control group (5.9%, 176/2, 981; p < 0.001).36 Liedtke et al. assessed the effect of a pharmacist monitoring service on admitted human immuno- deficiency virus (HIV)-seropositive patients. Prescribing errors reduced following the interven- tion comprising 24 errors/330 admissions com- pared with 85 errors/330 admissions at pre-intervention (p < 0.001).37
Prescriber education One study using a cluster randomised trial exam- ined prescriber education in general medicine units.38 Three groups, each consisting of junior doctors, were assigned to either a control group, a feedback and targeted education by pharmacist group, or an e-learning group. Detailed discus- sions regarding recently observed prescribing errors were provided by pharmacists during three 10-min sessions per week over the 4-week inter- vention period. The e-learning group completed an online course with modules on safe and correct prescribing practices. Both the control group and the e-learning group showed a significant increase in prescribing errors from their baselines, with the control group moving from 1171/2389 (49.0%) at baseline to 1630/2771 (58.8%) at post-inter- vention (p < 0.001), and the e-learning group moving from 406/697 (58.2%) at baseline to 882/1393 (63.3%) at post-intervention (p = 0.025). The pharmacist education group showed decreased prescribing errors from 57.8% (621 errors/1074 total medication orders) to 37.0% (493 errors/1333 total medication orders), p < 0.001. This study also reported on the rate of clinically significant prescribing errors, including potentially lethal, serious, and significant errors,
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Therapeutic Advances in Drug Safety 11
Table 5. Types of interventions.
PL-MR Pharmacists identify the most accurate list of medications and provide patients with the correct medications in hospital. This is usually conducted at admission and/or discharge.
IT-MR Electronic systems are used to identify the most accurate list of medications and provide patients with the correct medications in hospital. This is usually conducted at admission and/or discharge.
CPOE with or without CDSS
Electronic systems designed to automates the medication order process with the use of standardized and complete order. Sometimes this is complemented with the availability of CDSS, providing information on medication dose, route, and frequency.
PP Pharmacists involved as part of the team. This can include ward rounds, providing monitoring service and/or prescription reviews.
PE Educating the prescribers through online modules or pharmacist-led sessions.
PTE Patient education especially on the medical terms on how to take the medication. This is usually conducted by pharmacists.
IC Collaboration with various health care discipline groups for better medication management.
TME Experts who were trained in medication administration.
CA Electronic systems designed to facilitate medication administration.
DD Electronic systems designed to facilitate medication administration via automating drug distribution.
eMAR Electronic records that comprise tools for medication prescription and administration.
MD Different methods of medication cart filling methods to facilitate administration, for example, medications arranged by round time or by their names.
CA, CPOE + electronic administration system; CDSS, CPOE with or without clinical decision support system; CPOE, computerised physician order entry; DD, automated drug distribution system; IC, interdisciplinary collaboration; IT-MR, computerised medication reconciliation; MD, medication dispensing; PE, prescriber education; PL-MR, pharmacist-led medication reconciliation; PP, pharmacist partnership; PTE, patient education; TME, trained medication experts.
which showed no change in the pharmacist edu- cation group between baseline and intervention groups (p = 0.068).
Patient education One study involved examination of patient educa- tion. Weingart et al. conducted a randomised controlled pilot trial, in which patients received a copy of their current medication list with a glos- sary, explaining common medical terms upon dis- charge.39 The percentage of patients with potential ADEs did not differ between the control and intervention groups (10 potential ADEs/102 total number of patients versus 6/107 respectively, p = 0.30). This study also found no change in actual ADEs, comprising 2.9% (3 ADEs/102 total number of patients) in the control group and
7.5% (8 ADEs/107 total number of patients) in the intervention group (p = 0.22).
Trained medication experts Four studies examined the effect of trained medi- cation experts on administration errors and one showed a significant improvement. Baqir et al. investigated the effect of having dedicated trained pharmacy assistants participate in clinical settings and found that the administration error rate in the intervention group (2/181 patients) was less than the rate in the control ward group (68/369 patients), p < 0.0001.40 However, Greengold et al. found no significant change in the adminis- tration error rate (p = 0.84) in their study involved the use of dedicated medication nurses in the intervention group.41 The resulting
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Figure 4. Risk ratio summary for prescription errors.
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Therapeutic Advances in Drug Safety 11
Figure 5. Standard mean difference summary for prescribing errors.
administration error rate was 14.9% (545 errors/3661 opportunities for error) in the control group, while the administration error rate in the intervention group was 15.7% (912 errors/5792 opportunities for error). In the process improve- ment study undertaken by Nguyen et al., the goal was to teach nurses to focus on reconciling medi- cation orders, on administering medications, on checking medication labels, and on charting med- ication administration, while at the same time reducing interruptions.42 It was difficult to deter- mine the impact of the intervention as the admin- istration error rate reduced from 2 errors/100 medication administrations to 0 errors/100 medi- cation administrations. Schneider et al. com- pleted a randomised non-blinded controlled study in providing nurse training in medication administration.43 They found no difference in the medication administration error rate (odds ratio = 1.92, 95% CI 0.81–4.58, p = 0.14).
Medication dispensing Two studies examined the effects of medication dispensing. Using a prospective, observational, before-and-after study, Dean and Barber assessed the effects of patients using their own medications in hospital compared with pharmacists bringing in their supply to the clinical setting.44 Overall, there was no difference in administration errors between the traditional pharmacy supply approach (152 errors/3576 opportunities for error, 4.3%) and patients bringing in their medications (105 errors/2491 opportunities for error, 4.2%, p = 0.99). Using a prospective before-and-after study, Schimmel et al. implemented a medication
dispensing intervention in an orthopaedic ward involving medication cart filling by arranging medications by names, compared with usual care of arranging medications by what medications had to be delivered for a particular medication round.45 After the intervention, there was no change in medication administration error rates (19.4% at pre-intervention and 23.0% at post-intervention, odds ratio = 1.24, 95% CI 0.95–1.62).
Automated drug distribution system ± electronic medication administration record One study assessed the effect of an automated drug distribution system with and without an electronic medication administration record, showing significant reductions in administration errors in both interventions.46 In the pre-interven- tion period, 74 errors were identified out of 615 opportunities for errors (10.6%). Without the electronic medication administration record, the administration error reduced to 5.8% (25/378 opportunities for errors, p = 0.02). The error rate reduced even further with the use of electronic medication administration record, where only 16 errors were identified out of 405 opportunities for errors (4.1%, p = 0.001).
Combining intervention types The effect of combining interventions was also investigated in studies. Prescriber education, pharmacist partnership and CPOE were the most frequent components of combinations for pre- scribing errors. In studies examining the
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Figure 6. Risk ratio summary for administration errors.
combinations of two interventions to test the effects on prescribing errors, meta-analysis identi- fied mixed results. Grimes et al. assessed the
effectiveness of pharmacist-led medication recon- ciliation and pharmacist partnership in acute medical units, finding a lower prescribing error
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Therapeutic Advances in Drug Safety 11
rate at discharge in the intervention group (13.9%) compared with the control group (65.3%, p < 0.0001).50 Shea et al. demonstrated that the combination of prescriber education and pharmacist-led medication reconciliation was effective in reducing prescribing errors.52 However, the combination of prescriber educa- tion and CPOE in the study by Daniels et al. did not reduce prescribing errors.48 Cann et al. applied prescriber education (PE) and pharma- cist partnership in an acute surgical ward, with no significant change in medication errors with 12.0 errors at pre-intervention and 10.9 errors per 100,000 patient hours [relative risk (RR) 0.92, 95% confidence interval (CI) 0.40–2.08, p = 0.835].47 Gimenez-Manzorro et al. recruited patients from general surgical units and utilised computerised medication reconciliation inte- grated into the computerised physician order sys- tem.49 Unintended discrepancies decreased from 10.6% in the pre-intervention phase to 6.6% in the post-intervention phase (p = 0.002). The combination of three different types of interven- tions, CPOE, prescriber education and interdisci- plinary collaboration for HIV-infected patients admitted to acute medical and surgical services decreased the rate of medication errors from 50% in the pre-intervention period to 34% in the post- intervention period (p < 0.001).53
Three studies assessed the combination of two dif- ferent types of interventions involving administra- tion errors. Shea et al. found that administration errors reduced with pharmacist-led medication
reconciliation and prescriber education, p < 0.001.52 Jheeta et al. examined the effect of combining CPOE and electronic administration system, which showed no significant change in administration errors (p = 0.64).54 Cousein et al. found in examining an automated drug distribu- tion system and an electronic medication adminis- tration record, administration errors significantly reduced following the combined intervention.46
The study by Daniels et al. was the only one that assessed dispensing errors using a combination of interventions.48 Dispensing error rates were 39/119 (33%) at pre-intervention and 4/17 (24%) at post-intervention with the implementation of CPOE and prescriber education. However, this change was insignificant (RR 0.72, 95% CI 0.29– 1.76) (Figure 5).
Discussion This systematic review investigated the effective- ness of various types of interventions in reducing medication errors in adult acute medical and sur- gical settings. Meta-analysis results showed that prescribing errors were reduced by pharmacist- led medication reconciliation, computerised medication reconciliation, pharmacist partner- ship, prescriber education, medication reconcilia- tion by trained mentors, and CPOE as single interventions. Medication administration errors were reduced by CPOE and the use of an auto- mated drug distribution system as single interven- tions. Furthermore, combined interventions that
Figure 7. Risk ratio summary for dispensing errors.
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included CPOE, prescriber education and inter- disciplinary collaboration were effective for pre- scribing errors while combined interventions that included automated drug distribution and use of the electronic medical record, or prescriber edu- cation and pharmacist-led medication reconcilia- tion were found to be effective in reducing administration errors. No interventions were found to reduce dispensing error rates.
Pharmacist-led medication reconciliation showed mixed results in terms of effectiveness in reducing prescribing errors. Effectiveness of this interven- tion type was demonstrated in three studies, com- prising implementation of HIV-specialised pharmacists reconciling prescribing errors within 24 h by liaising with the inpatient team,22 targeting discharge summary errors by having pharmacists complete discharge medication documentation,26 and examining medication reconciliation on admission and discharge, while undertaking bed- side counselling.21 Results in two of these studies may be biased as the error-identifying assessor was not blinded as to who completed the discharge plans. Al-Hashar et al. found a lower effectiveness of pharmacist-led medication reconciliation com- pared with studies by Batra et al. and Tong et al. because patients were contacted 30 days after dis- charge and recall bias may have influenced the results.21,22,26 Beckett et al. found an increase in prescribing errors, which was explained by having a greater number of patients not being fully alert or oriented who were allocated to the intervention group under randomisation.23 These patients pos- sibly required medications to manage their mental state in addition to the treatment for their admis- sions. Boockvar et al. reported no change in error rates.24 The authors found that charging for accessing prescription information led to blocked availability of medication details if a transactional payment was not affordable. This issue demon- strates the importance of changing context in determining the impact of effectiveness.
Computerised medication reconciliation was comparatively less effective than pharmacist-led medication reconciliation at reducing prescrib- ing errors. Only two studies used computerised medication reconciliation, and neither of the studies included surgical patients.27,28 Further studies using this intervention could examine the effectiveness in surgical patients with a larger sample size.
The quality improvement study by Schnipper et al. achieved implementation of medication rec- onciliation by trained mentors across five differ- ent sites without providing additional resources to hospitals.29 The study was an example of a poten- tially cost-saving strategy of long-term implemen- tation. The study was conducted in diverse settings, including academic medical centres, community hospitals and veteran affairs medical centres, thereby indicating that the results could be generalised to other similar hospitals.
Studies utilising CPOE showed beneficial results. The results from Hernandez et al. favoured the intervention.30 However, with prescriptions rou- tinely checked by pharmacist post-intervention, it is difficult to assess the add-on effect from involv- ing the pharmacist. The study Milani of et al. was the only one examining the effects of both CPOE and clinical decision support31; however, it involved small sample sizes (n = 33 and 47 in the intervention and control groups, respectively). Other studies with alerts showed significant reductions in prescribing errors.32,34 Interestingly, Shawahna et al.’s study, which comprised neither alerts nor clinical decision support, also demon- strated reduced prescription errors in interven- tion wards.33 However, the effect of the intervention was more pronounced on minor errors without clinical consequences compared with those that were likely to cause patient harm.
Prescriber education as a single intervention was examined in one study, showing a significant effect on prescribing errors.38 However, it is dif- ficult to deduce the individual effect of prescriber education when combined with other interven- tions.47,48,52,53 One cluster randomised trial investigated the effect of e-learning tools in com- parison to pharmacists’ targeted feedback and education.38 In this study, prescribing errors showed no change in medication errors after prescribers finished e-learning modules. This lack of change could have occurred due to diffi- culties in prescribers applying general knowledge of prescribing practice learnt from e-learning modules to clinical scenarios, in the absence of targeted feedback and education sessions. There appears to be limited benefit in the use of e-learning modules and future research could focus on examining this use of this type of inter- vention with application to clinical scenarios and targeted feedback.
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Therapeutic Advances in Drug Safety 11
A total of 11 studies examined the effect of inter- ventions on administration errors. For all single and multifaceted interventions, generally a small number of studies were undertaken for each inter- vention type. Possible reasons for lack of impact of interventions for some studies included small patient samples and the short period for embed- ding the intervention before testing occurred.45,54 To understand the trends and impact of interven- tions, future work should encompass the conduct of well-designed studies with adequate sample sizes.
There were methodological concerns with included studies, which comprised lack of information about sample size calculations, how participants were recruited in studies and lack of blinding to the intervention. The quality improvement study con- ducted by Schnipper et al. scored the highest in the quality assessment. Most studies were conducted at a single site, relaying difficulties in generalising results to other hospitals and settings.29 Many studies were conducted in a pre–post format. Future studies should involve examining the effect of time on the intervention by including a concur- rent control group. Out of the 34 studies, only 21 studies contained information about the clinical significance of medication errors. Where clinical significance of medication errors was not provided, it is difficult to understand the true impact of inter- ventions. Such difficulties arise in medication reconciliation studies where relatively minor dis- crepancies may have been regarded as medication errors. It is important for intervention studies to have details provided about clinical significance of medication errors. The use of universal reporting standards, such as the one endorsed by the National Coordinating Council for Medication Error Reporting and Prevention,15 would enable consistent scoring and facilitate greater compre- hension of the impact of interventions on patient harm. In addition, it is vital to use independent panels to assess the likely clinical significance of medication errors.
Several interventions have been identified as effective in reducing prescribing and administra- tion errors, including medication reconciliation by trained mentors. While pharmacist-led medi- cation reconciliation was time-consuming and costly, computerised medication reconciliation could be a suitable alternative, although a com- puterised system may not be able to replace a pharmacist taking the best possible medication
history. With more hospitals adopting computer- ised systems, adding features to the system, such as computerised medication reconciliation and CPOE with or without clinical decision support system might cost proportionally less overall. The effectiveness of CPOE in reducing administration errors could also be an added benefit. Further research examining the effect of computerised medication reconciliation and CPOE should con- firm whether this combination is still effective in reducing both prescribing and administration errors. As the systematic review did not identify improvements in dispensing errors with pre- scriber education and CPOE, the addition of pharmacist-led medication reconciliation or phar- macist partnership may help to facilitate a reduc- tion in dispensing errors.
There are limitations of this systematic review. There may be unpublished studies that have demonstrated insignificant error results. Results reported in conference abstracts were not included. Similarly, studies not reported in English were also not included. Medication error calculations comprised a variety of formats, including the proportion of medication errors in relation to the opportunity for errors as well as the proportion of patients with medication errors. These error calculations were directly inserted into RevMan for meta-analysis. The variability of the units for medication errors probably contrib- uted to the extensive heterogeneity of meta-anal- ysis results. For the systematic review, the definition used for medication errors was broad, encompassing any preventable medication event that may cause inappropriate medication use or lead to patient harm. Subsequently, the system- atic review included studies where the outcome variables comprised medication errors, as well as ADEs, which involve harm caused by medica- tions as a result of medication errors, and unin- tended medication discrepancies where there were unexplained differences in medications pre- scribed across patient transfers. There was also variability in the calculation of medication error rates. Rates were variably expressed as the num- ber of errors obtained as a proportion of the total opportunities of errors, the number of patients experiencing as least one error compared with the total number of patients involved, and the num- ber of errors involved in relation to the total num- ber of patients. The data collection method used to determine medication errors also varied between studies. These factors all contributed to
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the relatively high level of heterogeneity between studies.
Conclusion This systematic review examined the efficacy of interventions in reducing medication errors within medical and surgical settings. The sys- tematic review identified a number of single and combined intervention types that were effective in reducing medication errors that clinicians and policymakers could consider for implemen- tation in medical and surgical settings. There were no effective interventions identified for reducing dispensing errors. More research is needed in the conduct of randomised interven- tion studies and well-constructed observational studies, with a greater focus on the clinical sig- nificance of the interventions. Interventions comprising interdisciplinary approaches includ- ing physicians, pharmacists and nurses are also warranted.
Acknowledgements Many thanks to Jim Berryman for his help with developing the search terms.
Conflict of interest statement The authors declare that there is no conflict of interest.
Funding The authors received no financial support for the research, authorship, and/or publication of this article.
ORCID iD Elizabeth Manias https://orcid.org/0000-0002 -3747-0087 Snezana Kusljic https://orcid.org/0000-0002 -2465-9884
Supplemental material Supplemental material for this article is available online.
References 1. Barker KN, Mikeal RL, Pearson RE, et al.
Medication errors in nursing homes and small hospitals. Am J Hosp Pharm 1982; 39: 987–991.
2. Fahimi F, Abbasi Nazari M, Abrishami R, et al. Transcription errors observed in a teaching hospital. Arch Iran Med 2009; 12: 173–175.
3. Patel I and Balkrishnan R. Medication error management around the globe: an overview. Indian J Pharm Sci 2010; 72: 539–545.
4. Makary MA and Daniel M. Medical error—the third leading cause of death in the US. BMJ 2016; 353: i2139.
5. Donaldson LJ, Kelley ET, Dhingra-Kumar N, et al. Medication without harm: WHO’s third global patient safety challenge. Lancet 2017; 389: 1680–1681.
6. Manias E, Kinney S, Cranswick N, et al. Interventions to reduce medication errors in pediatric intensive care. Ann Pharmacother 2014; 48: 1313–1331.
7. Manias E, Williams A and Liew D. Interventions to reduce medication errors in adult intensive care: a systematic review. Br J Clin Pharmacol 2012; 74: 411–423.
8. Nguyen M-NR, Mosel C and Grzeskowiak LE. Interventions to reduce medication errors in neonatal care: a systematic review. Ther Adv Drug Saf 2018; 9: 123–155.
9. Rinke ML, Bundy DG, Velasquez CA, et al. Interventions to reduce pediatric medication errors: a systematic review. Pediatrics 2014; 134: 338–360.
10. Weant KA, Bailey AM and Baker SN. Strategies for reducing medication errors in the emergency department. Open Access Emerg Med 2014; 6: 45–55.
11. Berdot S, Roudot M, Schramm C, et al. Interventions to reduce nurses’ medication administration errors in inpatient settings: a systematic review and meta-analysis. Int J Nurs Stud 2016; 53: 342–350.
12. Keers RN, Williams SD, Cooke J, et al. Impact of interventions designed to reduce medication administration errors in hospitals: a systematic review. Drug Saf 2014; 37: 317–332.
13. Acheampong F, Anto BP and Koffuor GA. Medication safety strategies in hospitals–a systematic review. Int J Risk Saf Med 2014; 26: 117–131.
14. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta- analyses: the PRISMA statement. Ann Intern Med 2009; 151: 264–269.
15. National Coordinating Council for Medication Error Reporting and Prevention. About medication errors, https://www.nccmerp.org/ about-medication-errors (2020).
16. Institute of Medicine Committee (US) on Quality of Health Care in America. In: Kohn
28 journals.sagepub.com/home/taw
Therapeutic Advances in Drug Safety 11
LT, Corrigan JM and Donaldson MS (eds) To err is human: building a safer health system. Washington, DC: National Academies Press, 2000.
17. Ouzzani M, Hammady H, Fedorowicz Z, et al. Rayyan QCRI, the systematic reviews web app, https://rayyan.qcri.org/welcome (2016).
18. Schulz KF, Altman DG and Moher D; CONSORT Group. CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. BMJ 2010; 340: c332.
19. Des Jarlais DC, Lyles C and Crepaz N. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement. Am J Public Health 2004; 94: 361–366.
20. Ogrinc G, Davies L, Goodman D, et al. SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence): revised publication guidelines from a detailed consensus process. BMJ Qual Saf 2016; 25: 986–992.
21. Al-Hashar A, Al-Zakwani I, Eriksson T, et al. Impact of medication reconciliation and review and counselling, on adverse drug events and healthcare resource use. Int J Clin Pharm 2018; 40: 1154–1164.
22. Batra R, Wolbach-Lowes J, Swindells S, et al. Impact of an electronic medical record on the incidence of antiretroviral prescription errors and HIV pharmacist reconciliation on error correction among hospitalized HIV-infected patients. Antivir Ther 2015; 20: 555–559.
23. Beckett RD, Crank CW and Wehmeyer A. Effectiveness and feasibility of pharmacist-led admission medication reconciliation for geriatric patients. J Pharm Pract 2012; 25: 136–141.
24. Boockvar KS, Ho W, Pruskowski J, et al. Effect of health information exchange on recognition of medication discrepancies is interrupted when data charges are introduced: results of a cluster- randomized controlled trial. J Am Med Inform Assoc 2017; 24: 1095–1101.
25. Cadman B, Wright D, Bale A, et al. Pharmacist provided medicines reconciliation within 24 hours of admission and on discharge: a randomised controlled pilot study. BMJ Open 2017; 7: e013647.
26. Tong EY, Roman CP, Mitra B, et al. Reducing medication errors in hospital discharge summaries: a randomised controlled trial. Med J Aust 2017; 206: 36–39.
27. Allison GM, Weigel B and Holcroft C. Does electronic medication reconciliation at hospital
discharge decrease prescription medication errors? Int J Health Care Qual Assur 2015; 28: 564–573.
28. Smith KJ, Handler SM, Kapoor WN, et al. Automated communication tools and computer- based medication reconciliation to decrease hospital discharge medication errors. Am J Med Qual 2016; 31: 315–322.
29. Schnipper JL, Mixon A, Stein J, et al. Effects of a multifaceted medication reconciliation quality improvement intervention on patient safety: final results of the MARQUIS study. BMJ Qual Saf 2018; 27: 954–964.
30. Hernandez F, Majoul E, Montes-Palacios C, et al. An observational study of the impact of a computerized physician order entry system on the rate of medication errors in an orthopaedic surgery unit. PLoS One 2015; 10: e0134101.
31. Milani RV, Oleck SA and Lavie CJ. Medication errors in patients with severe chronic kidney disease and acute coronary syndrome: the impact of computer-assisted decision support. Mayo Clin Proc 2011; 86: 1161–1164.
32. Pettit NN, Han Z, Choksi A, et al. Reducing medication errors involving antiretroviral therapy with targeted electronic medical record modifications. AIDS Care 2019; 31: 893–896.
33. Shawahna R, Rahman NU, Ahmad M, et al. Electronic prescribing reduces prescribing error in public hospitals. J Clin Nurs 2011; 20: 3233–3245.
34. van Doormaal JE, van den Bemt PM, Zaal RJ, et al. The influence that electronic prescribing has on medication errors and preventable adverse drug events: an interrupted time-series study. J Am Med Inform Assoc 2009; 16: 816–825.
35. García-Molina Sáez C, Urbieta Sanz E, Madrigal de Torres M, et al. Computerized pharmaceutical intervention to reduce reconciliation errors at hospital discharge in Spain: an interrupted time- series study. J Clin Pharm Ther 2016; 41: 203–208.
36. Hassan Y, Al-Ramahi RJ, Aziz NA, et al. Impact of a renal drug dosing service on dose adjustment in hospitalized patients with chronic kidney disease. Ann Pharmacother 2009; 43: 1598–1605.
37. Liedtke MD, Tomlin CR, Skrepnek GH, et al. HIV pharmacist’s impact on inpatient antiretroviral errors. HIV Med 2016; 17: 717–723.
38. Gursanscky J, Young J, Griffett K, et al. Benefit of targeted, pharmacist-led education for junior doctors in reducing prescription writing errors – a controlled trial. J Pharm Pract Res 2018; 48: 26–35.
E Manias, S Kusljic et al.
journals.sagepub.com/home/taw 29
39. Weingart SN, Toth M, Eneman J, et al. Lessons from a patient partnership intervention to prevent adverse drug events. Int J Qual Health Care 2004; 16: 499–507.
40. Baqir W, Jones K, Horsley W, et al. Reducing unacceptable missed doses: pharmacy assistant- supported medicine administration. Int J Pharm Pract 2015; 23: 327–332.
41. Greengold NL, Shane R, Schneider P, et al. The impact of dedicated medication nurses on the medication administration error rate: a randomized controlled trial. Arch Intern Med 2003; 163: 2359–2367.
42. Nguyen EE, Connolly PM and Wong V. Medication safety initiative in reducing medication errors. J Nurs Care Qual 2010; 25: 224–230.
43. Schneider PJ, Pedersen CA, Montanya KR, et al. Improving the safety of medication administration using an interactive CD-ROM program. Am J Health Syst Pharm 2006; 63: 59–64.
44. Dean B and Barber N. The effects of a patient’s own drugs scheme on the incidence and severity of medication administration errors. Int J Pharm Pract 2000; 8: 209–216.
45. Schimmel AM, Becker ML, van den Bout T, et al. The impact of type of manual medication cart filling method on the frequency of medication administration errors: a prospective before and after study. Int J Nurs Stud 2011; 48: 791–797.
46. Cousein E, Mareville J, Lerooy A, et al. Effect of automated drug distribution systems on medication error rates in a short-stay geriatric unit. J Eval Clin Pract 2014; 20: 678–684.
47. Cann T and Gardner A. Change for the better: an innovative model of care delivering positive
patient and workforce outcomes. Collegian 2012; 19: 107–113.
48. Daniels LM, Raasch RH and Corbett AH. Implementation of targeted interventions to decrease antiretroviral-related errors in hospitalized patients. Am J Health Syst Pharm 2012; 69: 422–430.
49. Gimenez-Manzorro A, Romero-Jimenez RM, Calleja-Hernandez MA, et al. Effectiveness of an electronic tool for medication reconciliation in a general surgery department. Int J Clin Pharm 2015; 37: 159–167.
50. Grimes TC, Deasy E, Allen A, et al. Collaborative pharmaceutical care in an Irish hospital: uncontrolled before-after study. BMJ Qual Saf 2014; 23: 574–583.
51. Moura CS, Prado NM, Belo NO, et al. Evaluation of drug-drug interaction screening software combined with pharmacist intervention. Int J Clin Pharm 2012; 34: 547–552.
52. Shea KM, Hobbs AL, Shumake JD, et al. Impact of an antiretroviral stewardship strategy on medication error rates. Am J Health Syst Pharm 2018; 75: 876–885.
53. Sanders J, Pallotta A, Bauer S, et al. Antimicrobial stewardship program to reduce antiretroviral medication errors in hospitalized patients with human immunodeficiency virus infection. Infect Control Hosp Epidemiol 2014; 35: 272–277.
54. Jheeta S and Franklin BD. The impact of a hospital electronic prescribing and medication administration system on medication administration safety: an observational study. BMC Health Serv Res 2017; 17: 547.
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