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1FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
Quality indicators for responsible use of medicines: a systematic review
Kenji Fujita, Rebekah J Moles, Timothy F Chen
To cite: FujitaK, MolesRJ, ChenTF. Quality indicators for responsible use of medicines: a systematic review. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Prepublication history and additional material for this paper are available online. To view these files, please visit the journal online (http:// dx. doi. org/ 10. 1136/ bmjopen- 2017- 020437).
Received 6 November 2017Revised 26 April 2018Accepted 13 June 2018
School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
Correspondence toKenjiFujita; kfuj2522@ uni. sydney. edu. au
Research
Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
AbstrACtObjective All healthcare systems require valid ways to evaluate service delivery. The objective of this study was to identify existing content validated quality indicators (QIs) for responsible use of medicines (RUM) and classify them using multiple frameworks to identify gaps in current quality measurements.Design Systematic review without meta-analysis.setting All care settings.search strategy CINAHL, Embase, Global Health, International Pharmaceutical Abstract, MEDLINE, PubMed and Web of Science databases were searched up to April 2018. An internet search was also conducted. Articles were included if they described medication-related QIs developed using consensus methods. Government agency websites listing QIs for RUM were also included.Analysis Several multidimensional frameworks were selected to assess the scope of QI coverage. These included Donabedians framework (structure, process and outcome), the Anatomical Therapeutic Chemical (ATC) classification system and a validated classification for causes of drug-related problems (c-DRPs; drug selection, drug form, dose selection, treatment duration, drug use process, logistics, monitoring, adverse drug reactions and others).results 2431 content validated QIs were identified from 131 articles and 5 websites. Using Donabedians framework, the majority of QIs were process indicators. Based on the ATC code, the largest number of QIs pertained to medicines for nervous system (ATC code: N), followed by anti-infectives for systemic use (J) and cardiovascular system (C). The most common c-DRPs pertained to drug selection, followed by monitoring and drug use process.Conclusions This study was the first systematic review classifying QIs for RUM using multiple frameworks. The list of the identified QIs can be used as a database for evaluating the achievement of RUM. Although many QIs were identified, this approach allowed for the identification of gaps in quality measurement of RUM. In order to more effectively evaluate the extent to which RUM has been achieved, further development of QIs may be required.
IntrODuCtIOnResponsible use of medicines (RUM) is an essential element in achieving quality of care for patients and the community. According to the WHO, RUM implies that the activi-ties, capabilities and existing resources of health system stakeholders are aligned to
ensure patients receive the right medicines at the right time, use them appropriately and benefit from them.1 RUM, however, is not easily achievable, and if medicines are used inappropriately, negative consequences for both patients and/or the society may occur. It is reported that worldwide more than 50% of all medicines are prescribed, dispensed or sold inappropriately, while 50% of patients fail to take them correctly.2 In addition, it has been reported that one-third of preventable drug-related admissions are associated with medication non-adherence, 31% are related to prescribing problems and 22% are related to monitoring problems.3 The frequency of these medication errors varies depending on the specific medicine. For example, previous systematic reviews have found that prevent-able drug-related admissions to hospital accounted for 3.7% of all admissions, of which four groups of drugs, antiplatelets, diuretics, non-steroidal anti-inflammatory and antico-agulants accounted for more than 50% of the drug groups associated with those prevent-able drug-related hospitalisations.3 From the economic perspective, globally, the cost associated with medication errors has been estimated at US$42 billion annually or almost
strengths and limitations of this study
A comprehensive literature search was undertaken across seven databases and government agency websites without restriction of disease categories and care settings.
The classification of quality indicators (QIs) was based on multiple frameworks (eg, Donabedians framework, the Anatomical Therapeutic Chemical classification system and a validated classification for causes of drug-related problems) for maximum understanding and profiling of the included QIs.
Content validated QIs that were developed using consensus methods were only included, and there-fore valid QIs might have been excluded during the screening process.
Although 5% of this review processes were verified by multiple authors to check for accuracy, most of the classification was undertaken by one author.
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2 FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
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1% of total global health expenditure.4 Given the health concerns and the economic burden associated with medi-cation errors, the achievement of RUM underpinned by an evidence-based approach has become increasingly important worldwide.
One critical element for any healthcare system or organisation is how to measure and evaluate RUM. A widely used method to do this is the use of quality indi-cators (QIs).5 6 QIs are explicitly defined and measurable items referring to the structures, processes or outcomes of care are usually described with a denominator and a numerator.7 The denominator is the total number of cases in the intended population, and the numerator is the number of cases that fulfil a predetermined crite-rion, and the calculated QI score indicates the quality of care.8 QIs can be used to monitor the quality of care provided by healthcare professionals in a single institu-tion, to promote quality improvement activities, to make comparisons over time between institutions or to support consumers to choose healthcare providers.5 For QIs to be useful, they must be developed with scientific rigour, and all quality dimensions of care must be measured to capture a comprehensive landscape of healthcare quality.5
To achieve RUM using QIs, it is first necessary to iden-tify existing QIs for RUM, independent of disease cate-gories and care settings. Additionally, in the light of the concept of RUM, multifaceted assessment is required to gain full understanding of the breadth of coverage by QIs. To our knowledge, however, previously conducted system-atic reviews have been restricted to setting (eg, hospital),9 disease state (eg, HIV/AIDS),10 specific to a healthcare group (eg, nursing sensitive QIs) or indicator name (eg, clinical indicators)11 and have only been classified based on Donabedians framework or implicit frameworks such as quality dimensions defined by the Institute of Medi-cine.12 Hence, the main purpose of this systematic review was to identify existing content validated QIs for RUM independent of disease category and care settings, and then classify them using multiple frameworks in order to identify gaps in current quality measurements.
MethODsData sourcesThis systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (see online supplementary table S1).13 Two approaches were used to identify relevant QIs.
First, CINAHL, Embase, Global Health, International Pharmaceutical Abstract, MEDLINE, PubMed and Web of Science databases were searched to identify relevant articles published up to 5 April 2018. No restriction on year of study was applied. Search strategies comprised keywords and, when available, controlled vocabulary such as Medical Subject Headings/EMTREE based on three main terms: quality indicators, development and consensus. Since quality indicators are referred to by wide variety of terms such as clinical indicators, or
performance measures, the finalised search strategies were developed using an iterative development process during which citations identified by various search terms were screened for relevance. We chose consensus as a main term because QIs are recommended to be devel-oped using expert panels based on rigorous evidence in order to ensure high face validity and content validity.14 Exact search dates for each database with the search strat-egies are included in online supplementary table S2.
Second, using Google, an internet search was also conducted (search terms: quality indicators, clinical indi-cators, performance indicator or performance measures) to capture additional QIs listed in the websites of rele-vant organisations responsible for quality improvement. Potentially relevant organisations websites, found in the process of literature review,9 12 1517 were also searched (see online supplementary table S3).
stuDy seleCtIOnInclusion criteriaArticles were included if they fulfilled the following criteria: (A) the article was peer reviewed and published in English, (B) numerators and denominators were defined for the QIs, or they could be directly deduced from the descriptions of the QIs, (C) the publication contained at least one medication-related QI, (D) the development of QIs was one of the objectives and (E) QIs were developed using consensus methods in order to confirm content validity. Furthermore, relevant organisations QIs found from websites were included if the organisation was a government agency for ensuring quality in healthcare, and at least one QI for RUM was reported with a clear description, as detailed above (B).
Given the concept of QIs and RUM mentioned above, we regarded a measurement tool as a QI for RUM when the definition of the QI referred to a medication. In addi-tion, if publications concerned the same project/QIs set, the descriptions of the QIs in the most recent publication were used for data extraction.
exclusion criteriaArticles were excluded if the consensus results for QI development were unclear, if QI lists were obtainable only by purchase or if QIs were for monitoring the effective-ness of national policies.
This study selection process was performed using a purposed designed screening proforma (see online supplementary table S4). The retrieved articles were transferred into Endnote to remove duplicates, then initial screening of journal names, titles and abstracts was conducted to remove irrelevant articles.
DAtA extrACtIOnOne researcher (KF) extracted the following data from the full text of included articles or websites: publication year, country or other targeted location in which QIs were
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intended to be used, name of measurement tools, total number of QIs, the number of relevant QIs for RUM, scope of the QIs and definition of QIs (numerator and denominator, if available). A data extraction proforma was designed, pilot-tested on five included studies, then refined accordingly.
AnAlysIsDescriptive statistics were computed for the results of the present review based on counts and proportions where relevant. Since the components of RUM are multidimen-sional, multiple frameworks were used to understand the breadth of coverage by QIs. That is, we used four types of classification: (1) problem type; (2) Donabedians frame-work; (3) the Anatomical Therapeutic Chemical (ATC) classification system; and (4) causes of drug-related prob-lems (c-DRPs) classification system.
Problem typeThe first step of a structured QI development process is to identify the problem for which measurement is needed.18 Classifying QIs according to problem type can highlight prioritised problems for QI development. Therefore, QI sets described in each source were classified into the following six problem types proposed by Evans et al18:1. Disease based: problems relevant to diseases, illnesses,
conditions, injuries or procedures for which the quali-ty of care needs to be measured.
2. Patient based: problems related to patient groups, such as vulnerable elders and paediatric patients.
3. Treatment modality based: problems relevant to ser-vice providing areas, such as intensive care units or pal-liative care settings.
4. Organisation based: problems relevant to organisation-al issues, such as whether organisations have effective structures in place at an organisational level to support quality and safety.
5. Generic problems: problems relevant to issues that are multidisciplinary in nature and relevant to any form of healthcare delivery in multiple physical settings, such as falls prevention, or pain management.
6. Profession based: problems unique to the different healthcare professions and include availability and competence of healthcare personnel.
If a QI set related to more than one problem type, they were classified accordingly (eg, an article about QIs for nursing practice in the operating room fell into treat-ment modality-based and profession-based problem).
Donabedians frameworkQIs were classified according to the widely used Donabe-dians framework of structure (referred to the factors that designate the conditions under which care is provided, such as material or human resources), process (referred to the actions of healthcare professionals, such as prescribing or monitoring) or outcome (referred to the changes in individuals that can be attributed to care
provided), irrespective of the category defined in the original source.19 Online supplementary table S5 lists examples of QIs classified into these three categories.
the AtC classification systemQIs were first classified into medicine class specific indi-cators or general medication indicators, depending on whether the definition of the QI described a specific class of medicines. For example, a QI numerator: patients with acute myocardial infarction (AMI) received aspirin within 3 hours of hospital arrival/denominator: AMI patients without aspirin contraindications20 was clas-sified as a medicine class specific indicator, while a QI numerator: number of patients aged 65 years and older whose current medications are documented and recon-ciled at admission/denominator: number of patients aged 65 years and older in sample21 was classified as a general medication indicator. After this process, medi-cine class specific indicators were classified using the first and second levels of the ATC code.22 A single QI was sometimes allocated into more than one ATC code. For example, a QI, percentage of patients using opioids with concomitant laxatives,23 represented A06 (drugs for constipation) and N02 (analgesics).
c-DrPs classification systemSince minimising the factors that contribute to drug-re-lated problems (ie, causes of DRPs) is closely linked to achieving RUM, the extracted QIs were classified using a comprehensive taxonomy of the causes of DRPs.24 This taxonomy divides c-DRPs into the following nine categories.1. Drug selection, for example, whether appropriate
drugs are selected by healthcare professionals.2. Drug form, for example, whether appropriate drug
forms are selected by healthcare professionals.3. Dose selection, for example, whether appropriate drug
dosages are selected by healthcare professionals.4. Treatment duration, for example, whether drugs are
being prescribed or dispensed for an appropriate du-ration by healthcare professionals.
5. Drug use process, for example, whether drugs are tak-en properly by patients.
6. Logistics, for example, whether necessary drugs are properly delivered to the patients.
7. Monitoring, for example, monitoring for the effect/adverse effects of drugs.
8. Adverse drug reactions, for example, the occurrence of adverse drug reactions.
9. Other.Note that a single QI was sometimes allocated into
more than one c-DRP category. Online supplementary table S6 illustrates how QIs were classified using the c-DRP taxonomy.
All processes were conducted independently by one author (KF), and 5% of these processes were verified by TFC and RJM. Any issues that arose during the process were resolved by discussion between the research team
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4 FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
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(KF, RJM and TFC). Meta-analysis was not applicable due to heterogeneity in interventions, methods and reported outcomes. We believed that it was not necessary to assess the quality of the content validated QIs included in our studies such as their feasibility, and reliability because problems affecting QIs (eg, feasibility of data collection, reliability of calculating QI scores and opportunities for gaming) vary depending on the healthcare infrastructure and healthcare remuneration system in each country.
PAtIent AnD PublIC InvOlveMentAs this was a literature review, there was no patient and public involvement in this study.
resultsstudy selectionInitially, a total of 39 430 articles were obtained. The sample included 17 822 duplicate records, which were removed. After the initial screening, 973 full texts were assessed for eligibility with 842 excluded based on the inclusion and exclusion criteria. Eventually 131 articles met all inclusion criteria and were included in our review. Additionally, through the internet search, five relevant
websites were identified and included in our review (figure 1).
study characteristicsOf the 131 articles, 78 articles (60%) developed QIs for use in three countries: USA (n=36),2560 Canada (n=26)6186 and Netherlands (n=16).23 87101 The remaining 53 arti-cles developed QIs for use in 16 other countries20 21 102145 and 4 other targeted locations (such as the Organisation for Economic Co-operation and Development (OECD) countries)146152 (figure 2). Of the five relevant websites, three were Australian organisations,153155 one was a UK organisation156 and the other was USA organisation.157 The three Australian and UK organisations developed QIs at the organisation level, while the American website, National Quality Measures Clearinghouse, sponsored by the Agency for Healthcare Research and Quality, stored QIs developed by various countries. Of 7750 QIs listed in the 131 articles and 5 websites, we identified 2431 QIs for RUM: 1947 QIs from journal articles and 484 QIs from the web.
While there were 21 different ways of labelling the measurement tools, quality Indicators (n=80, 59%) was the most commonly used term in our included articles
Figure 1 Study flow diagram.QI,quality indicator; RUM, responsible use of medicines.
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and websites, followed by quality measures (n=11, 8%), quality of care indicators (n=8, 6%) and indicators (n=7, 5%).
In terms of the problem type, 43% of QI sets pertained to disease-based problems (n=89, eg, knee osteoarthritis), then 27% for treatment modality-based problems (n=55, eg, primary care), 21% for patient-based problems (n=44, eg, geriatric care), 5% for profession based problems (n=11, eg, community pharmacists), 3% generic prob-lems (n=6, eg, long-term prescribing) or 1% organisa-tion-based practice (n=2, eg, centralised intake systems). The majority of QIs (n=2289, 94%) were process indica-tors, while structure (n=80) and outcome (n=62) indica-tors accounted for only 3% each (table 1).
Of 2431 QIs, 247 QIs (10%) were general medication indicators, and 2184 QIs (90%) were medicine class specific indicators. Some of the 2184 QIs represented more than one ATC code resulting in 2613 first level of ATC classifications. Of these, the most number of QIs covered medicines for nervous system (N, n=407, 16%), followed by the anti-infectives for systemic use (J, n=397, 15%), cardiovascular system (C, n=364, 14%) and blood and blood forming organs (B, n=345, 13%) (figure 3). Dermatological medicines (D) were covered by the least number of QIs (n=19, 0.7%) aside from antiparastic prod-ucts, insecticides and repellents (P, n=7, 0.3%).
The distribution of the QIs across the second level of ATC code and c-DRPs classification system is presented in table 2. General medication indicators were only clas-sified using c-DRPs category. Because some QIs repre-sented more than one ATC code and/or c-DRPs category, the total number of the QIs contained within each cell
of the matrix was 3666. Of these, when investigating the number of QIs in each c-DRPs category, the largest number of QIs for drug selection pertained to antibac-terials for systemic use (J01, 176 of 2117, 8%), followed by antithrombotic agents (B01, 172 of 2117, 8%). Anti-thrombotic agents (B01) also contributed the largest number of QIs for dose selection (20 of 142, 14%) and the drug use process (52 of 439, 12%) and monitoring (52 of 574, 9%). Likewise, the most number of QIs for treatment duration (13 of 85, 15%) pertained to psycho-analeptics (N06).
With regard to the c-DRPs classification system, the most common c-DRPs pertained to drug selection (n=2117, 58%), followed by monitoring (n=574, 16%) and the drug use process (n=439, 12%). The remaining six c-DRPs categories accounted for only 14% of the QIs. Interestingly, only QIs for analgesics (N02) covered all nine c-DRPs categories. In terms of general medication indicators, the largest number of QIs covered Logistics (n=73, 29%) among the c-DRPs category, which mainly focus on medication reconciliation problems during tran-sitions of care, such as hospital admission and discharge.
A complete list of 2431 QIs is available in online supple-mentary table S7.
DIsCussIOnThe RUM is important for almost every healthcare setting in every country across the globe. Knowledge of whether medicines are being used in an optimal manner there-fore presents a significant international challenge. In this systematic review, we identified 2431 QIs evaluating RUM
Figure 2 The number of publications by country and other target location.
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Tab
le 1
C
hara
cter
istic
s of
stu
die
s an
d q
ualit
y in
dic
ator
set
s
Ref
eren
ceYe
ar
Co
untr
y/o
ther
targ
et
loca
tio
nQ
I nam
e
Sco
pe
of
QIs
(set
ting
, co
ndit
ion,
tar
get
pat
ient
g
roup
, occ
upat
ion)
Pro
ble
m
typ
e*Q
Is f
or
RU
M
(%)
Do
nab
edia
ns
fram
ewo
rk
QI t
ype
SP
OM
eG
e
Bro
ccol
i et
al10
220
18A
fric
aQ
ualit
y in
dic
ator
sE
mer
genc
y ca
reT
19/7
6 (2
5)5
140
163
Trop
ea e
t al
2120
11A
ustr
alia
Clin
ical
ind
icat
ors
Old
er h
osp
italis
ed p
atie
nts
P4/
19 (2
1)0
40
13
AC
SQ
HC
153
2012
Aus
tral
iaP
ract
ice-
leve
l ind
icat
ors
Prim
ary
care
T3/
35 (9
)0
30
03
AC
SQ
HC
154
2014
Aus
tral
iaN
atio
nal Q
ualit
y U
se o
f M
edic
ines
Ind
icat
ors
Hos
pita
l car
eT
35/3
7 (9
5)2
330
2510
Cau
ghey
et
al10
320
14A
ustr
alia
Med
icat
ion-
rela
ted
in
dic
ator
sP
rimar
y ca
reT
28/2
8 (1
00)
028
028
0
Vic
toria
n G
over
nmen
t155
20
15A
ustr
alia
Qua
lity
ind
icat
ors
Res
iden
tial a
ged
car
eP,
T1/
5 (2
0)0
10
01
Nag
et
al10
420
16A
ustr
alia
Qua
lity
ind
icat
ors
Pro
stat
e ca
ncer
D1/
12 (8
)0
10
10
O'C
onno
r et
al1
0520
17A
ustr
alia
Qua
lity
ind
icat
ors
Psy
chot
rop
ic p
resc
ribin
g fo
r p
eop
le
with
dem
entia
in a
ged
psy
chia
try
inp
atie
nt u
nits
D, P
, T6/
6 (1
00)
06
06
0
Sib
thor
pe
et a
l106
2017
Aus
tral
iaIn
dic
ator
s
Otit
is m
edia
in p
rimar
y he
alth
care
for
Ab
orig
inal
and
Tor
res
Str
ait
Isla
nder
ch
ildre
nD
, P, T
2/12
(17)
02
02
0
Sto
rdeu
r et
al1
0720
12B
elgi
umQ
ualit
y in
dic
ator
sB
reas
t ca
ncer
D9/
32 (2
8)0
90
90
Gry
pd
onck
et
al10
820
14B
elgi
umQ
ualit
y in
dic
ator
sK
nee
oste
oart
hriti
sD
8/21
(38)
08
08
0
Sto
rdeu
r et
al1
0920
15B
elgi
umQ
ualit
y in
dic
ator
sO
esop
hage
al c
ance
r an
d g
astr
ic
canc
erD
4/29
(14)
04
04
0
De
Sch
reye
et
al11
020
17B
elgi
umQ
ualit
y in
dic
ator
s
End
-of-
life
care
in p
eop
le w
ith
Alz
heim
ers
dis
ease
, can
cer
or c
hron
ic
obst
ruct
ive
pul
mon
ary
dis
ease
D, P
23/8
1 (2
8)0
230
230
Leem
ans
et a
l111
2017
Bel
gium
Qua
lity
ind
icat
ors
Pal
liativ
e ca
reP
4/31
(13)
02
24
0
de
Car
valh
o et
al1
1220
17B
razi
lIn
dic
ator
sA
dul
t in
tens
ive
care
P, T
7/62
(11)
70
07
0
Mac
kinn
on a
nd H
eple
r61
2002
Can
ada
Clin
ical
ind
icat
ors
Ger
iatr
ic c
are
P52
/52
(100
)0
520
520
Rob
erts
on a
nd
Mac
Kin
non6
220
02C
anad
aC
linic
al in
dic
ator
sG
eria
tric
car
eP
52/5
2 (1
00)
052
052
0
Bur
ge e
t al
6320
07C
anad
aQ
ualit
y in
dic
ator
sC
ard
iova
scul
ar p
rimar
y ca
reD
, T11
/31
(35)
011
011
0
Kr
ger
et a
l64
2007
Can
ada
Qua
lity
ind
icat
ors
Old
er a
dul
ts w
ith c
ogni
tive
imp
airm
ent
or d
emen
tiaD
, P21
/72
(29)
021
09
12
Ko
et a
l65
2008
Can
ada
Qua
lity
ind
icat
ors
Per
cuta
neou
s co
rona
ry in
terv
entio
nD
7/26
(27)
25
07
0
Mac
Kin
non
et a
l66
2008
Can
ada
Clin
ical
ind
icat
ors
Typ
e 2
dia
bet
esD
12/2
1 (5
7)0
120
120
Nig
am e
t al
6720
08C
anad
aM
edic
atio
nus
e sa
fety
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jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
7FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
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2016
Chi
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sN
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11
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1
Li e
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116
2017
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dic
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rug
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mun
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acq
uire
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D, P
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044
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Wan
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1720
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Qua
lity
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118
2018
Chi
naQ
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mer
genc
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r, T
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03
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1
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t al
120
2017
Den
mar
kQ
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s
Dia
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acut
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ct in
fect
ions
in
gene
ral p
ract
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19/3
1 (6
1)0
190
190
Cam
pb
ell e
t al
146
2008
Eur
ope
Qua
lity
ind
icat
ors
Car
dio
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ular
dis
ease
in p
rimar
y ca
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010
08
2
Tab
le 1
C
ontin
ued
Con
tinue
d
on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
8 FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
Ref
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G, P
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021
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Pet
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148
2014
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121
2013
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nal
Qua
lity
ind
icat
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Car
dio
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atie
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sD
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02
02
0
Wak
ai e
t al
124
2013
Irela
ndK
ey p
erfo
rman
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ind
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form
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mer
genc
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140
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ator
sP
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/101
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018
119
0
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ry e
t al
126
2016
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sP
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12/1
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00)
012
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0
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ma
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l127
2016
Jap
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sis
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11 (3
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40
Mas
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t al
128
2017
Jap
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01
1
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al15
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300
551
Per
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3020
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sA
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car
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02
02
0
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scrib
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icat
ors
Gen
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ctic
eT
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4 (1
00)
034
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0
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al88
2007
Net
herla
nds
Qua
lity
ind
icat
ors
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fert
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(21)
08
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0
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8920
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rland
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sC
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sT
1/14
(7)
01
01
0
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l90
2008
Net
herla
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Pre
scrib
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qua
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Typ
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esD
14/1
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014
014
0
van
der
Plo
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9120
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ethe
rland
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ator
sG
ener
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for
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P, T
36/8
1 (4
4)0
360
2412
Per
ry e
t al
9220
10N
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sQ
ualit
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ator
sD
emen
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02
02
0
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l93
2011
Net
herla
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Qua
lity
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7 (4
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30
30
Wie
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420
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hosp
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harm
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tical
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nts
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r, T
85/8
7 (9
8)0
850
7114
Luitj
es e
t al
9520
13N
ethe
rland
sQ
ualit
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dic
ator
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yper
tens
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dis
ease
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gnan
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, P5/
14 (3
6)0
50
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van
den
Bos
ch e
t al
9620
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sis
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Tab
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C
ontin
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Con
tinue
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on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
9FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
Ref
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Co
untr
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, P, T
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29
011
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Woi
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9820
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Net
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160
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Teic
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Net
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Pha
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unity
p
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2143
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44
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Typ
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dia
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es in
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care
D, T
20/2
0 (1
00)
020
020
0
Idn
p
n-H
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il e
t al
152
2006
OE
CD
cou
ntrie
sQ
ualit
y in
dic
ator
sC
ard
iac
care
D8/
17 (4
7)0
80
80
Pet
ek e
t al
132
2012
Slo
veni
aQ
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ator
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ard
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scul
ar d
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r p
rimar
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reD
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014
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2
Min
aya-
Mu
oz e
t al
133
2013
Sp
ain
Qua
lity
mea
sure
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tera
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dyl
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aD
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02
02
0
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vet
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l134
2014
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ain
Qua
lity
ind
icat
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mm
ator
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owel
dis
ease
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/56
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anel
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cer
es e
t al
135
2015
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ain
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lity
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olor
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rman
ce m
easu
res
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ast
canc
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02
02
0
Chu
ng e
t al
139
2010
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erm
pre
scrib
ing
in g
ener
al
pra
ctic
eG
, T9/
9 (1
00)
09
01
8
Mor
ris a
nd C
antr
ill14
120
03U
KQ
ualit
y in
dic
ator
sP
reve
ntin
g d
rug-
rela
ted
mor
bid
ity in
p
rimar
y ca
reG
, T24
/24
(100
)0
240
240
Ste
el e
t al
142
2004
UK
Qua
lity
ind
icat
ors
Hea
lthca
re o
f old
er a
dul
ts in
prim
ary
and
sec
ond
ary
care
P40
/102
(39)
040
037
3
Tully
et
al14
320
05U
KIn
dic
ator
sLo
ng t
erm
pre
scrib
ing
in p
rimar
y an
d
seco
ndar
y ca
reG
, T14
/14
(100
)0
140
014
Gill
et
al14
420
14U
KQ
ualit
y in
dic
ator
sC
hild
hea
lthca
re in
gen
eral
pra
ctic
eP
10/3
5 (2
9)0
100
91
Sp
ence
r et
al1
4520
14U
KP
resc
ribin
gsa
fety
in
dic
ator
sS
afet
y of
pre
scrib
ing
in g
ener
al
pra
ctic
eG
, T56
/56
(100
)0
560
560
NIC
E15
6 3
2016
UK
NIC
E in
dic
ator
sG
ener
al p
ract
ice
T33
/125
(26)
030
333
0
Had
orn
et a
l25
1996
US
AR
evie
w c
riter
iaH
eart
failu
reD
4/8
(50)
04
03
1
Asc
h et
al2
620
01U
SA
Qua
lity
of c
are
ind
icat
ors
Wom
en w
ith h
yper
tens
ion
D, P
6/13
(46)
06
05
1
Mik
uls
et a
l27
2004
US
AQ
ualit
y of
car
e in
dic
ator
sG
out
D9/
10 (9
0)0
90
90
Sal
iba
et a
l28
2004
US
AQ
ualit
y in
dic
ator
sN
ursi
ng h
ome
resi
den
tsT
54/1
14 (4
7)1
530
540
Tab
le 1
C
ontin
ued
Con
tinue
d
on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
10 FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
Ref
eren
ceYe
ar
Co
untr
y/o
ther
targ
et
loca
tio
nQ
I nam
e
Sco
pe
of
QIs
(set
ting
, co
ndit
ion,
tar
get
pat
ient
g
roup
, occ
upat
ion)
Pro
ble
m
typ
e*Q
Is f
or
RU
M
(%)
Do
nab
edia
ns
fram
ewo
rk
QI t
ype
SP
OM
eG
e
Kru
mho
lz e
t al
2920
06U
SA
Per
form
ance
mea
sure
sS
T-el
evat
ion
and
non
-ST-
elev
atio
n m
yoca
rdia
l inf
arct
ion
D8/
11 (7
3)0
80
80
McG
ory
et a
l30
2006
US
AQ
ualit
y in
dic
ator
sP
atie
nts
und
ergo
ing
colo
rect
al c
ance
r su
rger
yD
20/9
2 (2
2)0
200
191
Mul
arsk
i et
al31
2006
US
AQ
ualit
y m
easu
res
Pal
liativ
e ca
reT
1/18
(6)
01
01
0
Man
gion
e-S
mith
et
al32
2007
US
AQ
ualit
y in
dic
ator
sP
aed
iatr
ic o
utp
atie
nts
P, T
58/1
75 (3
3)0
580
580
Sm
ith e
t al
3320
07U
SA
Qua
lity
ind
icat
ors
Hom
e-b
ased
prim
ary
care
T71
/200
(36)
170
059
12
Wen
ger
et a
l34
2007
US
AQ
ualit
y in
dic
ator
sVu
lner
able
eld
ers
P14
6/39
2 (3
7)0
146
012
917
Est
es e
t al
3520
08U
SA
Per
form
ance
mea
sure
sO
utp
atie
nt a
dul
ts w
ith n
on-v
alvu
lar
atria
l fib
rilla
tion
or a
tria
l flut
ter
D, P
, T2/
3 (6
7)0
20
20
Bili
mor
ia e
t al
3620
09U
SA
Qua
lity
ind
icat
ors
Pan
crea
tic c
ance
rD
3/43
(7)
12
03
0
Lore
nz e
t al
3720
09U
SA
Qua
lity
mea
sure
sS
upp
ortiv
e ca
ncer
car
eD
36/9
2 (3
9)0
360
351
McG
ory
et a
l38
2009
US
AQ
ualit
y in
dic
ator
sP
erio
per
ativ
e ca
re fo
r el
der
ly s
urgi
cal
pat
ient
sP,
T17
/91
(19)
017
013
4
Yazd
any
et a
l39
2009
US
AQ
ualit
y in
dic
ator
sS
yste
mic
lup
us e
ryth
emat
osus
D14
/20
(70)
014
014
0
Che
ng e
t al
4020
10U
SA
Qua
lity
ind
icat
ors
Mul
tiple
scl
eros
isD
19/7
6 (2
5)0
190
172
Kan
wal
et
al41
2010
US
AQ
ualit
y in
dic
ator
sN
onva
ricea
l up
per
gas
troi
ntes
tinal
ha
emor
rhag
eD
6/26
(23)
06
06
0
Kan
wal
et
al42
2010
US
AQ
ualit
y in
dic
ator
sC
irrho
sis
D12
/41
(29)
012
012
0
Sch
enck
et
al43
2010
US
AQ
ualit
y m
easu
res
Hos
pic
e an
d p
allia
tive
care
T7/
34 (2
1)0
70
70
Kha
nna
et a
l44
2011
US
AQ
ualit
y in
dic
ator
sS
yste
mic
scl
eros
isD
10/3
2 (3
1)0
100
100
Soo
Hoo
et
al45
2011
US
AQ
ualit
y of
car
e in
dic
ator
sP
atie
nts
und
ergo
ing
tota
l hip
or
tota
l kn
ee r
epla
cem
ent
D8/
68 (1
2)0
80
53
Wan
g et
al4
620
11U
SA
Qua
lity
of c
are
ind
icat
ors
Chi
ldre
n w
ith s
ickl
e ce
ll d
isea
seD
, P13
/41
(32)
013
013
0
Ang
er e
t al
4720
13U
SA
Qua
lity
of c
are
ind
icat
ors
Wom
en w
ith u
rinar
y in
cont
inen
ceD
, P7/
27 (2
6)0
70
70
Jack
son
et a
l48
2013
US
AQ
ualit
y in
dic
ator
sC
olor
ecta
l can
cer
D11
/34
(32)
011
011
0
Mel
med
et
al49
2013
US
AQ
ualit
y in
dic
ator
sIn
flam
mat
ory
bow
el d
isea
seD
8/21
(38)
05
38
0
Wan
g et
al5
020
13U
SA
Qua
lity
of c
are
ind
icat
ors
Infa
ntile
sp
asm
sD
, P10
/21
(48)
010
010
0
Yad
lap
ati e
t al
5120
15U
SA
Qua
lity
mea
sure
sG
astr
o-oe
sop
hage
al r
eflux
dis
ease
D15
/25
(60)
015
015
0
Faro
et
al52
2016
US
AQ
ualit
y in
dic
ator
s
Follo
w-u
p c
are
for
ind
ivid
uals
with
p
ositi
ve s
cree
ns fo
r si
ckle
cel
l dis
ease
an
d t
rait
D2/
9 (2
2)
02
02
0
Vila
et
al53
2016
US
AQ
ualit
y m
easu
res
Ad
ult
coch
lear
imp
lant
cen
tres
D, P
, T2/
8 (2
5)0
11
20
Yazd
any
et a
l54
2016
US
AQ
ualit
y m
easu
res
Rhe
umat
oid
art
hriti
sD
1/4
(25)
01
01
0
Cho
wd
hury
et
al55
2017
US
AQ
ualit
y m
etric
sA
dul
t co
ngen
ital h
eart
dis
ease
and
p
aed
iatr
ic c
ard
iolo
gy c
are
D, P
5/27
(19)
04
15
0
Tab
le 1
C
ontin
ued
Con
tinue
d
on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
11FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
and classified them using multiple frameworks. The large number of QIs reflects the multidimensional compo-nents of RUM and the different perspectives of multidis-ciplinary stakeholders involved in the RUM. The QI list presented in this review can be used as a comprehensive database and reference for existing content validated QIs pertaining to RUM. All stakeholders involved in quality assurance for RUM, for example, healthcare profes-sionals, researchers and decision makers, can select QIs from the multicategorised QI list for their own purpose. Since healthcare systems and medication guidelines may vary between countries when using the QIs at the local setting, it is important for users to critically review the QIs for their acceptability, feasibility of acquiring neces-sary data, reliability, sensitivity to change, work load and validity.8 14
The vast majority of the QIs for RUM identified were intended to be used in only a few high-income countries. Low-income and middle-income countries, however, are estimated to have similar rates of medication-related adverse events, and the impact has been reported to be about twice as much in terms of the number of years of healthy life lost.4 Since feasibility of data collection for calculating QI scores in low-income settings remain a concern,151 further efforts for improving the data collec-tion method might need to be made. We found that even though the role of all measurement tools (ie, QIs) rele-vant to RUM have the goal of quality improvement, the terminology used to describe QIs varied significantly. About 20 name variations were found, which reflects the absence of a universally accepted definition for such tools. For example, Campbell et al8 distinguished QIs from performance indicators, arguing that QIs infer a judge-ment about the quality of care provided, while perfor-mance indicators are statistical devices for monitoring care provided to populations without any necessary infer-ence about quality. However, we found that these terms, quality and performance, were used interchangeably. Hence, further research for standardising the definition that distinguishes these measurement tools is warranted.
We also found a significant gap in terms of the problem type (eg, disease-based problems (43%), treatment modality-based problems (27%) and profession-based problems (5%)). Since RUM is facilitated by collabo-ration in multidisciplinary teams, all healthcare profes-sionals involved in medication treatment should take responsibility for quality assurance, regardless of diseases, care settings and professions. When using Donabedians framework, about 94% of the identified QIs related to processes of care. This could be because processes of care are easier to measure, and because process indicators can provide interpretable feedback about care provided.158 In contrast, there was a paucity of outcome indicators. This may be because multiple factors influence health outcomes, many of which are outside the control of indi-vidual healthcare professionals. In addition, the diffi-culty of obtaining sufficient information for assessing outcomes, requiring the linkage of multiple data sources, R
efer
ence
Year
Co
untr
y/o
ther
targ
et
loca
tio
nQ
I nam
e
Sco
pe
of
QIs
(set
ting
, co
ndit
ion,
tar
get
pat
ient
g
roup
, occ
upat
ion)
Pro
ble
m
typ
e*Q
Is f
or
RU
M
(%)
Do
nab
edia
ns
fram
ewo
rk
QI t
ype
SP
OM
eG
e
Hep
ner
et a
l56
2017
US
AQ
ualit
y m
easu
res
Unh
ealth
y al
coho
l use
D3/
25 (1
2)0
30
30
Ingr
aham
et
al57
2017
US
AQ
ualit
y in
dic
ator
sE
mer
genc
y ge
nera
l sur
gery
car
eT
3/25
(12)
21
02
1
Man
gion
e-S
mith
et
al58
2017
US
AQ
ualit
y in
dic
ator
sH
osp
ital-
bas
ed c
are
for
com
mon
p
aed
iatr
ic r
esp
irato
ry il
lnes
ses
D, P
, T43
/76
(57)
043
043
0
Od
etol
a et
al5
920
17U
SA
Qua
lity
mea
sure
sIn
hosp
ital c
are
of p
aed
iatr
ic s
epsi
s sy
ndro
me
D, P
, T3/
7 (4
3)1
20
30
NQ
MC
157
2018
US
AQ
ualit
y m
easu
res
Vario
us c
are
All
412/
2525
(16)
037
834
376
36
Par
ast
et a
l60
2018
US
AQ
ualit
y m
easu
res
Hos
pita
l-b
ased
car
e fo
r su
icid
al y
outh
D, P
, T4/
4 (1
00)
04
02
2
Tota
l24
31/7
750
(31)
6022
8962
2184
247
*Pro
ble
m t
ype:
D, d
isea
se b
ased
; G, g
ener
ic; O
, org
anis
atio
n b
ased
; P, p
atie
nt b
ased
; Pr,
pro
fess
ion
bas
ed; T
, tre
atm
ent
mod
ality
bas
ed.
Don
abed
ian
s fr
amew
ork:
S, s
truc
ture
; P, p
roce
ss; O
,out
com
e.Q
I typ
e: M
e, m
edic
ine
clas
s sp
ecifi
c; G
e, g
ener
al m
edic
atio
n.G
over
nmen
t ag
ency
web
site
. A
CS
QH
C, T
he A
ustr
alia
n C
omm
issi
on o
n S
afet
y an
d Q
ualit
y in
Hea
lthca
re; N
ICE
, Nat
iona
l Ins
titut
e fo
r H
ealth
and
Clin
ical
Exc
elle
nce;
NQ
MC
, Nat
iona
l Qua
lity
Mea
sure
s C
lear
ingh
ouse
; QI,
qua
lity
ind
icat
or; R
UM
,res
pon
sib
le u
se o
f med
icin
es.
Tab
le 1
C
ontin
ued
on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
12 FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
could be another reason of the limited number of outcome indicators. For outcome indicators to become more useful, multiple confounders such as patient demo-graphic characteristics, and severity of illness, may need to be considered.159 Similarly, there was a low proportion of structural indicators. This may be because they are not sufficiently sensitive for monitoring ongoing perfor-mance and they have traditionally been used to monitor standards of healthcare facilities, not RUM.160 It is note-worthy that there is no set requirement for equal propor-tions of structural, process and outcome indicators in quality measurement. Instead, it is important to recognise the interconnectedness of these measures. For example, high structure indicator scores increase the likelihood of good process indicator scores, which in turn, may lead to higher outcome indicator scores.161 Further research is
needed to investigate the associations between the iden-tified QIs in each framework within healthcare settings.
We found large differences in the degree to which c-DRPs categories were covered by the identified QIs. Not surprisingly, Drug selection accounted for more than half of the QIs, as choosing an inappropriate drug is the main cause of DRPs.3 162 Since focusing on limited c-DRPs categories may divert attention and resources away from other factors contributing to DRPs,163 164 users of QIs should be aware of what c-DRPs categories are not being measured. Like Donabedians framework, we do not expect that QIs should be evenly distributed across each of the c-DRPs categories or ATC groups. We do, however, expect that there will be greater QIs in areas of greatest need. These clinical areas may include common areas of practice suspected to be associated with inappropriate
Figure 3 The number of QIs by first-level ATC code.ATC,Anatomical Therapeutic Chemical; QIs, quality indicators. on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
13FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
Tab
le 2
D
istr
ibut
ion
of Q
Is fo
r R
UM
by
the
ATC
cod
e (ro
ws)
and
the
c-D
RP
s ca
tego
ry (c
olum
ns)*
AT
C c
od
e 1.
Dru
g
sele
ctio
n2.
Dru
g
form
3. D
ose
se
lect
ion
4.
Trea
tmen
t d
urat
ion
5. D
rug
us
e p
roce
ss6.
Lo
gis
tics
7.
Mo
nito
ring
8.
Ad
vers
e d
rug
re
acti
on
9. O
ther
Tota
l, n
(%)
A: a
limen
tary
tra
ct a
nd m
etab
olis
m
A
01: S
tom
atol
ogic
al p
rep
arat
ions
7
5 12
(0.3
)
A
02: D
rugs
for
acid
rel
ated
dis
ord
ers
373
28
151
(1.4
)
A
03: D
rugs
for
func
tiona
l gas
troi
ntes
tinal
d
isor
der
s35
34
42 (1
.1)
A
04: A
ntie
met
ics
and
ant
inau
sean
ts23
45
32 (0
.9)
A
06: D
rugs
for
cons
tipat
ion
201
32
26 (0
.7)
A
07: A
ntid
iarr
heal
s, in
test
inal
an
tiinfl
amm
ator
y/an
tiinf
ectiv
e ag
ents
141
21
12
21 (0
.6)
A
08: A
ntio
bes
ity p
rep
arat
ions
, exc
l. d
iet
pro
duc
ts1
1 (0
)
A
10: D
rugs
use
d in
dia
bet
es40
14
193
192
88 (2
.4)
A
11: V
itam
ins
281
11
132
(0.9
)
A
12: M
iner
al s
upp
lem
ents
241
15
334
(0.9
)
B: B
lood
and
blo
od fo
rmin
g or
gans
B
01: A
ntith
rom
bot
ic a
gent
s17
220
852
652
19
320
(8.7
)
B
02: A
ntih
emor
rhag
ics
21
3 (0
.1)
B
03: A
ntia
nem
ic p
rep
arat
ions
91
13
21
17 (0
.5)
B
05: B
lood
sub
stitu
tes
and
per
fusi
on
solu
tions
331
92
41
555
(1.5
)
C: C
ard
iova
scul
ar s
yste
m
C
01: C
ard
iac
ther
apy
301
44
415
58 (1
.6)
C
02: A
ntih
yper
tens
ives
505
12
1068
(1.9
)
C
03: D
iure
tics
576
23
231
92 (2
.5)
C
04:P
erip
hera
l vas
odila
tors
51
6 (0
.2)
C
05: V
asop
rote
ctiv
es1
1 (0
)
C
07: B
eta
blo
ckin
g ag
ents
108
55
1110
139
(3.8
)
C
08: C
alci
um c
hann
el b
lock
ers
486
510
69 (1
.9)
C
09: A
gent
s ac
ting
on t
he r
enin
-an
giot
ensi
n sy
stem
128
72
71
3417
9 (4
.9)
C
10: L
ipid
mod
ifyin
g ag
ents
532
17
871
(1.9
)
Con
tinue
d
on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
14 FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
AT
C c
od
e 1.
Dru
g
sele
ctio
n2.
Dru
g
form
3. D
ose
se
lect
ion
4.
Trea
tmen
t d
urat
ion
5. D
rug
us
e p
roce
ss6.
Lo
gis
tics
7.
Mo
nito
ring
8.
Ad
vers
e d
rug
re
acti
on
9. O
ther
Tota
l, n
(%)
D: D
erm
atol
ogic
als
D
01: A
ntifu
ngal
s fo
r d
erm
atol
ogic
al u
se2
2 (0
.1)
D
02: E
mol
lient
s an
d p
r ote
ctiv
es3
3 (0
.1)
D
06: A
ntib
iotic
s an
d c
hem
othe
rap
eutic
s fo
r d
erm
atol
ogic
al u
se4
4 (0
.1)
D
07: C
ortic
oste
roid
s, d
erm
atol
ogic
al
pre
par
atio
ns4
15
(0.1
)
D
08: A
ntis
eptic
s an
d d
isin
fect
ants
11
(0)
D
10: A
nti-
acne
pre
par
atio
ns1
34
(0.1
)
D
11: O
ther
der
mat
olog
ical
pr e
par
atio
ns1
1 (0
)
G: G
enito
urin
ary
syst
em a
nd s
ex h
orm
ones
G
01: G
ynec
olog
ical
ant
iinfe
ctiv
es a
nd
antis
eptic
s4
12
18
(0.2
)
G
02: O
ther
gyn
ecol
ogic
als
22
(0.1
)
G
03: S
ex h
orm
ones
and
mod
ulat
ors
of
the
geni
tal s
yste
m29
98
46 (1
.3)
G
04: U
rolo
gica
ls16
52
23 (0
.6)
H: S
yste
mic
hor
mon
al p
rep
arat
ions
, exc
l. se
x ho
rmon
es a
nd in
sulin
s
H
01: P
ituita
ry a
nd h
ypot
hala
mic
ho
rmon
es a
nd a
nalo
gues
81
12
517
(0.5
)
H
02: C
ortic
oste
r oid
s fo
r sy
stem
ic u
se53
53
59
378
(2.1
)
H
03: T
hyro
id t
hera
py
22
25
11 (0
.3)
H
05: C
alci
um h
omeo
stas
is14
317
(0.5
)
J: A
ntiin
fect
ives
for
syst
emic
use
J0
1: A
ntib
acte
rials
for
syst
emic
use
176
79
1238
822
828
0 (7
.6)
J0
2: A
ntim
ycot
ics
for
syst
emic
use
21
3 (0
.1)
J0
4: A
ntim
ycob
acte
rials
21
3 (0
.1)
J0
5: A
ntiv
irals
for
syst
emic
use
122
26
43
29 (0
.8)
J0
7: V
acci
nes
9410
15
611
6 (3
.2)
L: A
ntin
eop
last
ic a
nd im
mun
omod
ulat
ing
agen
ts
L0
1: A
ntin
eop
last
ic a
gent
s94
35
353
453
1119
9 (5
.4)
Tab
le 2
C
ontin
ued
Con
tinue
d
on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
15FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
AT
C c
od
e 1.
Dru
g
sele
ctio
n2.
Dru
g
form
3. D
ose
se
lect
ion
4.
Trea
tmen
t d
urat
ion
5. D
rug
us
e p
roce
ss6.
Lo
gis
tics
7.
Mo
nito
ring
8.
Ad
vers
e d
rug
re
acti
on
9. O
ther
Tota
l, n
(%)
L0
2: E
ndoc
rine
ther
apy
151
44
24 (0
.7)
L0
3: Im
mun
ostim
ulan
ts4
26
(0.2
)
L0
4: Im
mun
osup
pre
ssan
ts23
41
62
1248
(1.3
)
M: M
uscu
losk
elet
al s
yste
m
M
01: A
ntiin
flam
mat
ory
and
ant
irheu
mat
ic
pro
duc
ts53
56
141
182
110
0 (2
.7)
M
02:T
opic
al p
rod
ucts
for
join
t an
d
mus
cula
r p
ain,
455
513
118
21
90 (2
.5)
M
03: M
uscl
e r e
laxa
nts
201
13
25 (0
.7)
M
04: A
ntig
out
pr e
par
atio
ns10
33
16 (0
.4)
M
05: D
rugs
for
trea
tmen
t of
bon
e d
isea
ses
271
13
32 (0
.9)
N: N
ervo
us s
yste
m
N
01: A
nest
hetic
s12
32
11
19 (0
.5)
N
02: A
nalg
esic
s82
19
124
524
33
152
(4.1
)
N
03: A
ntie
pile
ptic
s19
28
55
241
(1.1
)
N
04: a
nti-
Par
kins
on d
rugs
301
45
40 (1
.1)
N
05: P
sych
olep
tics
726
812
528
23
136
(3.7
)
N
06: P
sych
oana
lep
tics
738
139
229
213
6 (3
.7)
N
07: O
ther
ner
vous
sys
tem
dru
gs11
122
25 (0
.7)
P
: Ant
ipar
asiti
c p
rod
ucts
, ins
ectic
ides
an
d r
epel
lent
s (p
01: a
ntip
roto
zoal
s)
21
21
3
R: R
esp
irato
ry s
yste
m
R
01: N
asal
pre
par
atio
ns5
27
(0.2
)
R
03: D
rugs
for
obst
ruct
ive
airw
ay
dis
ease
s69
33
374
132
131
(3.6
)
R
05: C
ough
and
col
d p
rep
arat
ions
61
7(0
.2)
R
06: A
ntih
ista
min
es fo
r sy
stem
ic u
se31
23
36(1
)
S: S
enso
ry o
rgan
s
S
01: O
pht
halm
olog
ical
s23
53
233
(0.9
)
S
02: O
tolo
gica
ls2
2 (0
.1)
Tab
le 2
C
ontin
ued
Con
tinue
d
on 3 February 2019 by guest. P
rotected by copyright.http://bm
jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2017-020437 on 16 July 2018. D
ownloaded from
http://bmjopen.bmj.com/
16 FujitaK, etal. BMJ Open 2018;8:e020437. doi:10.1136/bmjopen-2017-020437
Open access
use of medicines and significant economic burden (eg, over use of antibiotics for upper respiratory tract infec-tion and overuse of opioid analgesics). Use of QIs in these areas may fill the evidencepractice gaps and minimise subsequent DRPs.165 166
QIs for antithrombotic agents (B01) accounted for the larger proportion of QIs targeting drug selection, dose selection, drug use process and monitoring in c-DRPs categories. This may be explained by the fact that the majorit