SYSTEMATIC REVIEW Open Access
Organizational- and system-levelcharacteristics that influenceimplementation of shared decision-makingand strategies to address them — a scopingreviewIsabelle Scholl1,2* , Allison LaRussa1, Pola Hahlweg2, Sarah Kobrin3 and Glyn Elwyn1
Abstract
Background: Shared decision-making (SDM) is poorly implemented in routine care, despite being promoted byhealth policies. No reviews have solely focused on an in-depth synthesis of the literature around organizational-and system-level characteristics (i.e., characteristics of healthcare organizations and of healthcare systems) that mayaffect SDM implementation. A synthesis would allow exploration of interventions to address these characteristics.The study aim was to compile a comprehensive overview of organizational- and system-level characteristics that arelikely to influence the implementation of SDM, and to describe strategies to address those characteristics describedin the literature.
Methods: We conducted a scoping review using the Arksey and O’Malley framework. The search strategy includedan electronic search and a secondary search including gray literature. We included publications reporting onprojects that promoted implementation of SDM or other decision support interventions in routine healthcare. Wescreened titles and abstracts, and assessed full texts for eligibility. We used qualitative thematic analysis to identifyorganizational- and system-level characteristics.
Results: After screening 7745 records and assessing 354 full texts for eligibility, 48 publications on 32 distinctimplementation projects were included. Most projects (N = 22) were conducted in the USA. Several organizational-levelcharacteristics were described as influencing the implementation of SDM, including organizational leadership, culture,resources, and priorities, as well as teams and workflows. Described system-level characteristics included policies,clinical guidelines, incentives, culture, education, and licensing. We identified potential strategies to influence thedescribed characteristics, e.g., examples how to facilitate distribution of decision aids in a healthcare institution.(Continued on next page)
* Correspondence: [email protected]; [email protected] Dartmouth Institute for Health Policy and Clinical Practice, DartmouthCollege, Level 5, Williamson Translational Research Building, One MedicalCenter Drive, Lebanon, NH 03756, USA2Department of Medical Psychology, University Medical CenterHamburg-Eppendorf, Martinistr. 52, W26, 20246 Hamburg, GermanyFull list of author information is available at the end of the article
© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Scholl et al. Implementation Science (2018) 13:40 https://doi.org/10.1186/s13012-018-0731-z
(Continued from previous page)
Conclusions: Although infrequently studied, organizational- and system-level characteristics appear to play a role inthe failure to implement SDM in routine care. A wide range of characteristics described as supporting and inhibitingimplementation were identified. Future studies should assess the impact of these characteristics on SDMimplementation more thoroughly, quantify likely interactions, and assess how characteristics might operate acrosstypes of systems and areas of healthcare. Organizations that wish to support the adoption of SDM should carefullyconsider the role of organizational- and system-level characteristics. Implementation and organizational theory couldprovide useful guidance for how to address facilitators and barriers to change.
Keywords: Shared decision-making, Decision aids, Implementation, Routine care, Organizational -level characteristics,Health system -level characteristics, Implementation science, Leadership, Incentives, Health policy,
BackgroundAlthough recognized as ethically important and fre-quently included in healthcare policies [1], the practiceof engaging patients in their healthcare decisions is in-frequently implemented in routine care [2–6]. Researchon shared decision-making (SDM) has identified thisfailure of implementation, but has focused primarily onthe associated patient- and provider-level characteristics[7–10]. Studies of other practice-changing interventionshave similarly identified implementation challenges, butin other areas, the search for solutions has extended tocharacteristics of healthcare delivery beyond the patientand clinician to the organizational characteristics andthe system-level policies. How these findings from theimplementation literature, and research onorganizational- and system-level characteristics specif-ically, might affect efforts to implement SDM is notwell known.SDM is a widely recognized approach to cultivate
patient-centered care [11, 12]. It is an approach whereclinicians and patients share the best available evidencewhen faced with the task of making decisions, and wherepatients are supported to consider options and toachieve informed preferences [13]. SDM is a communi-cative process that can be supported by the use of deci-sion aids, also called decision support interventions. Inthe last several years, there has been growing interest inadvancing SDM in routine healthcare. In many coun-tries, health policies include implementation of SDM. Ina series of articles recently published on the develop-ment of activities to promote SDM in 22 different coun-tries, it was shown that 19 countries have health policiesthat foster or even demand SDM implementation [1].Despite this health policy commitment to SDM and itsinclusion in a range of clinical practice guidelines, studyresults from other countries point towards poor imple-mentation in routine clinical practice [2–6].These results have led to work that attempts to explain
the difficulty of implementing SDM in routine care. Re-search on barriers to and facilitators of SDM mostlyidentifies contributing factors at the individual level of
care, i.e., characteristics of individual patients, clinicians,or the direct patient-clinician interaction [8–10]. Twosystematic reviews on perceived barriers and facilitatorsof SDM implementation not only reported individualfactors (i.e., knowledge, attitudes, and behavior), but alsoincluded a few environmental factors (e.g., time, re-sources) [10, 14]. A similarly narrow focus on attitudes,skills, and behavior of individual clinicians and patientsmanifest in most interventions developed for SDM [15].Recent work has acknowledged the importance of takingorganizational-level characteristics into account. Theseare the characteristics of specific healthcare organiza-tions (i.e., entities that deliver healthcare, e.g., hospitals,practices) that affect the implementation of SDM. Forexample, Müller and colleagues [16] highlighted the im-portance of organizational culture, leadership support,and changes in workflow structures to better implementSDM in cancer care. Additionally, little is known aboutthe role of system-level characteristics in the implemen-tation of SDM. These are the characteristics of thehealthcare system that guide the work of healthcare or-ganizations (i.e., the political, economic, and social con-text in which healthcare organizations are embedded,e.g., policies and legislation) [17].Research on the implementation of health innovations
has shown that it is crucial to take into account charac-teristics of healthcare institutions and of the healthcaresystem at large in order to change practice [18–20].Those characteristics may otherwise function as power-ful barriers to implementing SDM at the individual en-counter level. Nevertheless, implementation strategiesare often targeted to change knowledge, attitudes, andbehavior of individual providers [21], hindered perhaps,by the lack of measures available to assess system-levelcharacteristics [18]. Similarly, in research on SDM, nostudies have focused solely on an in-depth synthesis ofthe literature around organizational- and system-levelcharacteristics that may influence the implementation ofSDM in routine care. A greater understanding of theorganizational- and system-level characteristics thatcould impede or support implementation of SDM in
Scholl et al. Implementation Science (2018) 13:40 Page 2 of 22
routine care may be helpful in finding ways to addressthese characteristics in implementation strategies. Thus,the aim of this scoping review is to compile a compre-hensive overview of experiences with organizational-and system-level characteristics in implementing SDMin routine care. The following research questions guidedthis scoping review:
1. What experiences with organizational- and system-level characteristics are reported in SDM implemen-tation projects?
2. What strategies to address these characteristics arediscussed in the literature?
MethodsDesignWe performed a scoping review rather than a systematicreview due to the broad nature of our research ques-tions, the young field of SDM research, and our anticipa-tion of high variation in study designs andmethodologies [22]. We used the definition of scopingreview given by Colquhoun and colleagues: “a form ofknowledge synthesis that addresses an exploratory re-search question aimed at mapping key concepts, types ofevidence, and gaps in research related to a defined areaor field by systematically searching, selecting, and syn-thesizing existing knowledge” [23].
ProtocolWe developed our protocol based on the Arksey andO’Malley framework [22], as well as on subsequentlypublished guidance on how to conduct scoping reviews[24–26]. The final version of the protocol can be foundin Additional file 1.
Eligibility criteriaWe included publications that reported on the results ofprojects, quality improvement programs, or studies thataimed to implement SDM, decision aids (i.e., tools foruse inside or outside the clinical encounter [27]) orother decision support interventions (i.e., mediated bymore interactive or social technologies [27]) in routinehealthcare through a certain implementation strategy oreffort. To be included, these full texts also needed to re-port on organizational-level and/or system-level charac-teristics described to influence the implementation, and/or describe strategies that might address organizational-level and/or system-level characteristics. Opinion pieces,reviews, and study protocols were excluded, but reviewswere used in the secondary search process, as describedbelow. The full list of inclusion and exclusion criteria,specifying concepts and contexts of this scoping review,is displayed in Table 1.
Search strategyWe performed an electronic literature search in Med-line, CINAHL, and Web of Science Core Collection. Weincluded articles published between January 1997, theyear in which Charles and colleagues described the con-cept of SDM in their seminal article [28], and October10, 2016. The search was limited to articles published inEnglish or German, as these were the only languagesspoken by a minimum of two members of the reviewteam. Details of the search strategies in the different da-tabases can be found in Additional file 2.Our primary electronic search was complemented by a
comprehensive secondary search strategy. All recordsexcluded through criterion E2 (systematic, scoping, andstructured literature reviews) [10, 14, 15, 29–42] werechecked to see whether they reported on studies thatcould potentially be relevant for this scoping review.Subsequently, the reference lists of six of these reviews
Table 1 Inclusion and exclusion criteria
Inclusion criteria Excluded full texts(N = 306)
I1 The full text is accessible. 2
I2 Context: the language of the fulltext is English or German.
0
I3 Concept: the main subjectof the full text is shareddecision-making (SDM) ordecision aids or otherdecision support interventions.
33
I4 Concept: the full text reportson the results of a project,quality improvement program,or study that aims to implementSDM or decision aids orother decision supportinterventions in routinehealthcare through a certainimplementation strategy or effort.
157
I5 Concept: the full textreports on the role of experiencedorganizational- and/orsystem-level characteristicsthat influenced theimplementation of SDM,decision aids, or otherdecision support interventions.
10
Exclusion criteria
E1 Context: the full text is anopinion piece, commentary,editorial, analysis article, orletter, i.e., does not reporton a primary data collection.
61
E2 Context: the full text is asystematic review, a scopingreview or a structuredliterature review.
22
E3 Context: the full textis a study protocol.
21
Scholl et al. Implementation Science (2018) 13:40 Page 3 of 22
[10, 15, 29, 36, 39] were assessed for eligibility. Further-more, two books were searched for chapters meeting theinclusion criteria [43, 44], and a gray literature searchwas conducted on a range of websites listed inAdditional file 3.
Study selection processWe imported all identified records into reference man-agement software (Endnote) and removed duplicates.First, IS and a second reviewer (PH, AL, or RPM) per-formed an independent title and abstract screening tocheck for potential inclusion of records. A record wasincluded into the next step of full text assessment if atleast one reviewer deemed it appropriate. Second, fulltext assessment was conducted. To ensure quality andconsistency of full text assessments, the first 20% of ran-domly selected full texts were assessed by two teammembers (IS and PH or IS and AL). In 83% of the cases,the team members agreed on inclusion or exclusion.Discrepant assessments were subsequently discussed bythe team members. This process led to minor revisionsin the exact wording of the inclusion and exclusion cri-teria and an instruction of how to use the criteria. Then,another round of double assessment using another set of10% of randomly selected full texts was conducted, lead-ing to agreement in 93% of the cases. The subsequentassessment of the remaining 70% of full texts was con-ducted by one reviewer (IS) using a conservative ap-proach. Whenever the single assessor (IS) was in slightdoubt about whether to include or exclude a full text, asecond reviewer was assigned to assess that full text, andfinal decision regarding inclusion was made by discus-sion. This procedure was done for a total of 14 full texts.
Data extractionWe extracted general information on each study andspecific information related to the research questions.We extracted any information on experiences related toorganizational- and system-level characteristics and po-tential strategies to address them. As we wanted to givea broad overview, we extracted all information on expe-riences reported in the publications, including experi-ences derived from results (empirical) and from theinterpretation of results (opinion-based). The number offull texts identified and selected is described using thePRISMA flowchart. The initial data extraction sheet wasdeveloped by one team member (IS), based on experi-ence from other reviews [12, 15, 45, 46]. It was pilottested by IS and AL, using two included full texts [47,48]. We compared the extracted data and found onlyvery minor differences in the level of detail of the re-spective extractions. As a result, the extraction sheet wasslightly revised (e.g., by adding definitions of what to ex-tract). Further data extraction was conducted by one
person (either AL or IS). Whenever one data extractorwas in doubt regarding what to extract for a certain cat-egory, the second person checked the full text and bothmet to discuss agreement on what to extract.
Methodological quality appraisalWe did not appraise the methodological quality or riskof bias of the included studies, which is consistent withguidance on the conduct of scoping reviews [22].
SynthesisWe conducted a descriptive analysis of characteristics ofthe included studies (e.g., types of study design, years ofpublication) as well as a qualitative thematic analysis ofthe organizational- and system-level characteristics iden-tified in the studies. We decided to report what otherstudies reported as influential characteristics, rather thanclassify them as barriers or facilitators. This analysisdrew on principles of qualitative content analysis de-scribed by Hsieh and Shannon [49] and consisted of thefollowing steps: first, two researchers (AL and IS) readthe entire set of extracted data to gain an overview. Sec-ond, one researcher (AL) coded the material (initial in-ductive coding). Third, comments by a secondresearcher (IS) led to adaptation of the coding system.Fourth, the revised codes were organized into a codingsystem using clusters and subcategories, agreed in dis-cussion with two other team members (GE and SK).Fifth, the material was re-coded by one researcher (AL)using the established coding system. Sixth, the re-codedmaterial was cross-checked by a second researcher (IS)and minimal changes were made in discussion (IS andAL). Potential strategies mentioned in the publicationsto address organizational- and system- level characteris-tics were synthesized and mapped onto identified char-acteristics in a team discussion (IS, AL, GE). Noqualitative data analysis software was used. Analyseswere conducted on the level of distinct implementationprojects, i.e., publications reporting on the same imple-mentation project were grouped under one single pro-ject ID.
ResultsIncluded studiesAfter screening 7745 titles and abstracts for eligibility,and checking 354 full texts against the inclusion and ex-clusion criteria, we included 48 full texts (see Fig. 1).Reasons for exclusion of full texts are displayed inTable 1. The included full texts report on a total of 32distinct implementation projects. While most projectswere only reported in a single publication, several pro-jects were described in two or more publications.Twenty-two projects were conducted in the USA, and26 projects focused on the implementation of decision
Scholl et al. Implementation Science (2018) 13:40 Page 4 of 22
aids or other forms of decision support. Projects focusedon various settings and a broad range of decisional con-texts. Table 2 gives an overview on the included projectsand publications.
Characteristics influencing SDM implementationFigure 2 gives an overview of the identified characteristics.
Organizational-level characteristicsTable 3 displays the organizational-level characteristicsreported in the included full texts as influencing the im-plementation of SDM, decision aids, or other decisionsupport interventions. The table includes descriptions ofall identified characteristics. Six main categories oforganizational characteristics were described in the in-cluded studies: organizational leadership, culture, team-work, resources, priorities, and workflows. Five of thesix main categories also included several subcategoriesof organizational-level characteristics; for example, thecategory “organizational resources” included the subcat-egories time (that healthcare providers have per patient),financial resources (that are available for certain activ-ities within a healthcare organization), workforce (i.e.,employees available for and assigned to certain activitieswithin a healthcare organization), and space (i.e., roomavailable for certain activities within a healthcareorganization). Both the availability of resources withinan organization and organizational workflows (e.g., pa-tient information dissemination strategies, scheduling
routines, use of the electronic health record) were de-scribed to have influenced SDM implementation effortsin over three quarters of the projects, and facets of theorganizational culture and teamwork within anorganization were reported in only a third of the projects(see column “Project IDs” in Table 3).
System-level characteristicsWhile many organizational characteristics were identi-fied in the included full texts, only four main categoriesof characteristics of the healthcare system were de-scribed: incentives (i.e., the role of payment models andaccreditation/certification criteria), policies and guide-lines (i.e. the role of healthcare legislation and clinicalpractice guidelines), culture of healthcare delivery, andhealthcare provider education and licensing. Table 4gives an overview of the characteristics of the healthcaresystem that were reported as influencing implementa-tion. The table includes descriptions of all identifiedcharacteristics. While only four projects reported thatthe culture of healthcare delivery influenced SDM im-plementation, about one third of the projects reportedthat incentives, policies and guidelines, and healthcareprofessional education and licensing influenced SDMimplementation (see column “Project IDs” in Table 4).
Strategies to address organizational- and system-levelcharacteristicsA range of possible strategies to address organizational-and system-level characteristics and thereby potentiallyfoster SDM implementation were discussed in the publi-cations and mapped onto the identified characteristics.They are displayed in Table 5. Similar to the results on ex-perienced characteristics, most proposed strategies fo-cused on the organizational level. Most studies identifiedworkflow as an organizational-level characteristic influen-cing SDM implementation and also generated potentialstrategies to tackle that characteristic. Few strategies weresuggested to change organizational culture [50–52], whichwas also described in fewer studies. A large range of po-tential strategies were also described to promote leader-ship activities that might facilitate SDM implementation(see full list in Table 5). At the system-level, fewer strat-egies were described. Suggestions included changes inpayment models [53–55], legislation [51, 56, 57], andhealth professional education [51, 58–60].
DiscussionSummary of the review findingsWe described a broad range of organizational- andsystem-level characteristics that were experienced as influ-encing the implementation of SDM in routine care, as wellas strategies to potentially address those characteristics.Included studies reported more often on characteristics
Fig. 1 Flow chart of study selection. *Reasons for exclusion: I1: 2 intotal (1 full text from primary search, 1 full text from secondarysearch). I2: none. I3: 33 in total (29 full texts from primary search, 4full texts from secondary search). I4: 157 in total (113 full texts fromprimary search, 44 full texts from secondary search). I5: 10 in total (8full texts from primary search, 2 full texts from secondary search). E1:61 in total (58 full texts from primary search, 3 full texts fromsecondary search). E2: 22 in total (17 full texts from primary search, 5full texts from secondary search). E3: 21 in total (20 full texts fromprimary search, 1 full texts from secondary search)
Scholl et al. Implementation Science (2018) 13:40 Page 5 of 22
Table
2Includ
edim
plem
entatio
nprojects
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
P1Abrines-Jaumeet
al.(2016)[47]
UK
Qualityim
provem
entstud
yOutpatient,inp
atient,
commun
ity,and
outreach
Child
andadolescent
men
talh
ealth
SDM
inge
neral
Team
swereen
couraged
totry
arang
eof
toolsto
supp
ort
SDM
andreceived
cross-site
learning
even
tsevery3
mon
thsinclud
inginform
ation
andmaterials,g
roup
discussion
s,andactio
nlearning
setsas
partof
theClosing
theGap
prog
ram.The
yalso
received
regu
lar
site
meetin
gsandph
one
andem
ailg
uidance.
P2And
rewset
al.(2016)[68]
Berg
etal.(2011)[69]
Friedb
erget
al.(2013)[70]
USA
n/r(descriptive
implem
entatio
nstud
y)Specialty
andprim
ary
care
inan
academ
icmed
icalcenter
Ortho
pedics,b
reast
cancer,h
ipandknee
osteoarthritis,prostate
cancer,cancerscreen
ing,
spinecond
ition
s,he
art/chronic/othe
r
Decisionaids
andothe
rform
ofde
cision
supp
ort
Whe
nindicated,
individu
al’s
treatm
entpreferen
ces,qu
estio
ns,
andothe
rde
cision
-makingdata
wereshared
with
theirclinician
andrecorded
intheirelectron
icmed
icalrecord
(EMR).Shared
decision
-makingsummaries
(dashb
oards)wererepo
rted
tode
partmen
tsat
regu
larintervals
inan
effortto
system
atically
mon
itorandevaluate
theuse
ofde
cision
supp
ortprog
rams
inclinicalcare.
P3Arterbu
rnet
al.(2016)[71]
Con
radet
al.(2011)[55]
Hsu
etal.(2013)[52]
Hsu
etal.(2013)[72]
King
andMou
lton(2013)
[51]
USA
Mixed
-metho
dscase
stud
ySpecialty
care
inan
integrated
health
system
Focuson
decision
sregardingsurgical
treatm
ents:b
reast
cancer
andDCIS,hip
andknee
osteoarthritis,
chroniclow
back
pain,
livingbe
tter
with
chronic
pain,colon
cancer
screen
ing,
depression
,diabetes,PSA
testing
Decisionaids
Senior
projectmanagem
ent
consultantsworkedwith
service
lineleadersto
develop
implem
entatio
nagreem
ents
andprocessflow
diagramsfor
each
serviceline.Onceadraft
distrib
utionprocesswas
gene
rated,
theproject
managersmet
with
frontline
providersandstaffto
introd
ucetheDAs,the
distrib
utionprocessand
answ
erqu
estio
ns.Process
revision
swerebasedon
provider
reactio
nsand
sugg
estio
ns.O
ncean
implem
entatio
nprocess
was
agreed
upon
,a“go-live”
date
was
set,afterwhich
theprojectmanagersvisited
each
clinicsite
atleaston
ceto
mon
itorim
plem
entatio
nprocessesandprog
ress.Sites
expe
riencingchalleng
esreceived
additio
nalvisits
and
calls
asne
cessary.DAswere
distrib
uted
usingan
existin
gservicethat
supp
lies
educationalm
aterialsto
patientsviaUSmail.The
DVD
versions
oftheDAs
couldbe
orde
redforpatients
Scholl et al. Implementation Science (2018) 13:40 Page 6 of 22
Table
2Includ
edim
plem
entatio
nprojects(Con
tinued)
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
byclinicalstaffusingthe
electron
iche
alth
record.
Patientscouldalso
view
theDAon
lineviathe
patient
portal,and
providers
couldem
bedalinkto
the
vide
oDAin
thepatient’s
after-visitsummary.In
treatm
entde
cision
for
which
thetim
ebe
tween
apatient’sinitialappo
intm
ent
andtheproced
urewas
very
short,theDAscouldalso
bedistrib
uted
intheoffice.
Processwas
mon
itored
usingtw
ice-mon
thly
distrib
utionrepo
rtsgiven
toclinicalleaders.In
the
second
year,the
serepo
rts
includ
edmorespecific
numbe
rsforindividu
alclinicians.
P4Belkora(2011)
[73]
Belkoraet
al.(2008)[74]
Belkoraet
al.(2011)[75]
Belkoraet
al.(2012)[48]
Belkoraet
al.(2015)[76]
USA
Qualityim
provem
entstud
yBreastcare
center
(inan
NCId
esignated
compreh
ensive
care
center)
Breastcancer
Decisionaids
and
othe
rform
ofde
cision
supp
ort
Long
-term
projectwith
multip
leiteratio
ns.
Implem
entatio
nsconsisted
ofconsultatio
nplanning
,recording,
summarizing
services
inwhich
supp
ort
staffassisted
patientsin
commun
icatingwith
their
providersbe
fore
avisit
(questionbrainstorm
ing)
anddu
ringavisit(aud
iorecording).Improvem
ents
onthisserviceconsisted
ofadjustingthesche
duling
system
andworkflow
ofde
cision
supp
ort,mailing
DAsto
patientsat
home,
andmakingfollow-upcalls
P5Belkoraet
al.2008[77]
USA
Post-im
plem
entatio
nqu
alitativestud
yCom
mun
ityclinics
andcommun
ityresource
centers
Breastcancer
Other
form
ofde
cision
supp
ort
One
-tim
eCon
sultatio
nPlanning
training
worksho
psinclud
edlectures,structured
roleplaying,
andgrou
pdiscussion
sessions.
P6Brackettet
al.(2010)[78]
USA
n/r(descriptive
implem
entatio
nstud
y)Prim
arycare
inon
eacadem
icmed
ical
center
andon
eVeteran’s
Affairs
Med
icalCen
ter
Prostate
cancer
andcolorectal
cancer
screen
ing
Decisionaids
Four
metho
dswerecompared:
(1)
automaticpre-visitmailing
toallp
oten
tially
eligible
patients,(2)letter
mailed
toallp
oten
tially
eligible
patientsofferin
gpre-visit
DA(3)e
ligiblepatients
offeredDAat
checkout
from
prim
arycare
visit
(4)clinicianprescribes
DA
Scholl et al. Implementation Science (2018) 13:40 Page 7 of 22
Table
2Includ
edim
plem
entatio
nprojects(Con
tinued)
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
toeligiblepatients
durin
gprim
arycare
visit
P7Clayet
al.(2013)[79]
Friedb
erget
al.(2013)[70]
USA
n/r(descriptive
implem
entatio
nstud
y)Acade
micmed
icalcenter
departmen
tof
orthop
edics
Ortho
pedics
Decisionaids
Embe
ddingde
cision
aidinto
new
EMRto
system
aticallyandautomatically
deliver
DAto
therig
htpatient
attherig
httim
e.
P8Elwyn
andThom
son
(2013)
[80]
King
etal.(2013)[58]
Lloydet
al.(2013)[81]
LloydandJoseph
-Williams(2016)
[82]
UK
Servicede
velopm
ent/qu
ality
improvem
entprog
ram
NHSho
spitalsand
prim
aryandsecond
ary
care
team
s
Headandne
ckcancer,
breastcancer,p
ediatric
tonsillectomy,ob
stetrics,
urolog
icalprob
lems,ear,
nose
andthroat,kne
eosteoarthritis,statins,
managingmoo
ddisorders,
sexualhe
alth
and
contraception,
uppe
rrespiratory
tractinfection,
managingcarpaltunn
elsynd
rome,sm
oking
cessation,
men
orrhagia,
long
-term
care,b
enign
prostatic
hype
rplasia
SDM
inge
neral
Makinggo
odde
cision
sin
collabo
ratio
n(M
AGIC)
improvem
entprog
ram:an
approach
that
integrates
shared
decision
-making
into
routinecare
throug
htraining
inshared
decision
-making
andtheuseof
decision
supp
orttools,pe
ersupp
ort
forclinicians,and
supp
ort
forpatientsto
become
moreen
gage
din
theircare.
Thisprog
ram
hasbe
enim
plem
entedat
several
sitesandisadaptedfor
bestusein
thecontext
ofeach
site.
P9Elwyn
etal.(2012)[83]
UK
Post-im
plem
entatio
nmixed
-metho
dsstud
yNHShe
althcare
profession
als
Knee
osteoarthritis,
amniocen
tesis,
breastcancer,b
enign
prostatic
hype
rplasia,
localized
prostate
cancer
Decisionaids
Toolsweremadeavailable
onNHSDirect’sweb
platform
andpatientswere
directed
totoolsby
staff.
P10
Feibelmannet
al.
(2011)
[84]
USA
n/r(descriptive
implem
entatio
nstud
y)Cancercenters,ho
spitals,
privatepractices,
andresource
centers
Breastcancer
Decisionaids
Lettersweremailedto
providers
atsites.Sitescouldfaxor
mailb
ackarequ
estfora
sampleprog
ram
andthen
sign
aparticipantagreem
ent
toreceivecopies
ofde
cision
aids
tousewith
patients.
Vario
usim
plem
entatio
ntechniqu
eswereused
atindividu
alsites.
P11
Fortnu
met
al.(2015)[85]
Australia
n/r(descriptive
implem
entatio
nstud
y)Renalu
nits
End-stagekidn
eydisease
Decisionaids
DecisionaidPD
Fsweremadeavailable
natio
nally
(dow
nloadable
from
Kidn
eyHealth
Australia
andKidn
eyHealth
New
Zealandweb
sites).Edu
catio
nwas
provided
toover
2000
ANZ
health
profession
alsthroug
hteleconferen
ces,web
inar,
web
site
distrib
ution,
state
worksho
ps,u
nitvisits,
conferen
cepresen
tatio
ns,
andem
ail.
P12
Frosch
etal.(2011)[50]
Uyet
al.(2014)[86]
USA
n/r(descriptive
implem
entatio
nstud
y)Prim
arycare
offices
and
commun
ityhe
alth
centers
Firstprostate
andcolon
cancer
screen
ingthen
Decisionaids
Theinitialim
plem
entatio
npractices
received
eviden
ce-based
Scholl et al. Implementation Science (2018) 13:40 Page 8 of 22
Table
2Includ
edim
plem
entatio
nprojects(Con
tinued)
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
expand
edto
vario
uscontextswith
24different
decision
aids
available
brochu
rede
cision
supp
ort
interven
tions
(DESIs).Thego
alwas
toprovidetheDESIsto
patientsat
thetim
eof
anofficevisitandto
review
before
theconsultatio
nwith
theph
ysician.
Inan
expansionof
this
implem
entatio
nindividu
alpractices
selected
DESIs
toprovideto
patients.
Phase1:du
ringapatient
visit,ph
ysicianor
staff
wou
ldassess
approp
riatene
ssof
DAprescriptio
nthen
eligiblepatientsreceived
packagewith
DAto
take
homeandreview
before
follow
up-app
ointmen
t.Theexactlogisticsof
DA
distrib
utionwereestablishe
dby
practices
individu
ally.
Weekly“acade
micde
tailing
”visitswerecond
uctedwith
amem
berof
theresearch
team
toiden
tifybarriers
andde
veloppo
tential
solutio
ns.Phase
2:introd
uctio
nof
afinancial
incentiveto
compe
nsate
fortim
espen
tprescribing
DAsandinclusion/exclusion
criteria
(toen
sure
that
only
eligiblepatientsreceive
theDA)andph
one
survey
insteadof
questio
nnaire.
P13
Friedb
erget
al.(2013)[70]
Frosch
(2011)
[73]
Linet
al.(2013)[87]
May
etal.(2013)[88]
Tietbo
hlet
al.(2015)[89]
USA
Casestud
y(descriptive
implem
entatio
nstud
y)Prim
arycare
clinics
inan
integrated
health
system
Vario
uscontexts:16
different
decision
aids
available
Decisionaids
Theprojectteam
collabo
rated
with
clinicsto
tailorde
cision
aiddistrib
utionmetho
dsto
individu
alclinicworkflows.
Each
clinichadaph
ysician
andstaffcham
pion
respon
sible
forprom
otingtheprog
ram.
Theleadership
team
ateach
clinic,w
hich
includ
edbo
thph
ysicians
andleadersof
clinicalsupp
ortstaff,
selected
decision
aid
topics
fordistrib
utionfro
mthelistof
availabletools.
Projectteam
mem
bers
engage
din
academ
icde
tailing
visitsandsocial
marketin
geffortsto
prom
ote
distrib
utionof
thede
cision
aids.
Scholl et al. Implementation Science (2018) 13:40 Page 9 of 22
Table
2Includ
edim
plem
entatio
nprojects(Con
tinued)
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
P14
Garde
n(2008)
[59]
Wirrman
andAskham
(2006)
[90]
UK
n/r(descriptive
implem
entatio
nstud
y)Urology
departmen
tsEarly
localized
prostate
cancer
orbe
nign
prostatic
hype
rplasia
Decisionaids
Nurse
specialistswere
traine
dto
implem
ent
DecisionSupp
ortAids
andDecisionQuality
Assessm
entForm
sto
patients(im
plem
ented
atdifferent
pointsin
thecare
pathway
atdifferent
sites).
P15
Holmes-Rovne
ret
al.
(2000)
[91]
USA
Mixed
-metho
dsfeasibility
stud
yHospitalcom
mun
ityhe
alth
educationcenters,
cardiology
education
andresearch
departmen
ts,
andhe
alth
educationlibraries
Breastcancer
and
ischem
iche
artdisease
Decisionaids
Toen
sure
localaccep
tance
oftheprog
ramsandto
fittheprog
ram
into
existin
groutines,h
ospitalswere
askedto
iden
tifystud
ycoordinatorswho
wou
ldworkwith
localp
hysicians
andnu
rses
toim
plem
ent
theprog
rams.Participating
clinicians
wereaskedto
review
decision
aidand
completesurvey
priorto
distrib
utingto
patients.
Clinicians
received
reminde
rsandstud
ycoordinatorsrepe
ated
lydiscussedtheDAswith
them
.
P16
Holmes-Rovne
ret
al.
(2011)
[92]
USA
Retrospe
ctive
post-the
n-prede
sign
Internalmed
icine
andfamily
med
icineclinics
Stablecoronary
artery
disease
SDM
inge
neral
Thecomplex
decision
supp
ort
system
calledShared
DecisionMakingGuidance
Reminde
rsin
Practice
(SDM-GRIP)
consistedof:(1)
provider
training
(2)patient
education.
Tofacilitatediscussion
intheclinicalen
coun
ter,a
dedicatedSD
Mprovider
visitwas
establishe
d,andan
encoun
terde
cision
guide(EDG)was
givento
patients.TheED
Gprovided
aneviden
cesummaryand
decision
page
sto
record
choicesarrived
atin
theclinicalen
coun
ter.
P17
Julianet
al.(2011)[93]
USA
n/r(descriptive
implem
entatio
nstud
y)Com
preh
ensive
breastcare
center
Breastcancer,D
CIS
Decisionaids
and
othe
rform
ofde
cision
supp
ort
Anu
rsenavigator
coordinatedpatient
care
andprovided
decision
aids
towom
en.
P18
Korsen
etal.(2011)[73]
USA
n/r(descriptive
implem
entatio
nstud
y)Prim
arycare
inan
integrated
health
system
PSAtesting,
colorectal
cancer
screen
ing,
diabetes,acute
low
back
pain,chron
iclow
back
pain,d
epression,
men
opause,
advancedirectives
Decisionaids
Implem
entatio
ninclud
ed(1)pre-visit,visit-based,
andpo
st-visitdistrib
ution
mod
els,(2)useof
EHRforDA
referral,(3)
vario
ustraining
s,worksho
ps,and
presen
tatio
nsat
different
sites
Scholl et al. Implementation Science (2018) 13:40 Page 10 of 22
Table
2Includ
edim
plem
entatio
nprojects(Con
tinued)
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
P19
Friedb
erget
al.(2013)[70]
Lewiset
al.(2011)[73]
Lewiset
al.(2013)[57]
Miller
etal.(2012)[94]
USA
n/r(descriptive
implem
entatio
nstud
y)Prim
arycare
clinic
PSAtestingand
weigh
tloss
surgery
Decisionaids
Thefocuswas
onautomated
DVD
DAde
liverythroug
hEH
Randsocialmarketin
gcampaign.
Five
delivery
mod
elswereused
:(1)
mailingDAs
priorto
visit(2)u
sing
Patient
Health
Survey
toiden
tifyeligiblepatients
andallow
them
torequ
est
aDA,(3)
requ
estin
gDAs
byph
ysician(4)distrib
uting
DAswith
inchronicdisease
managem
entprog
ram
(5)pre-visiton
line
screen
ingforDAeligibility
P20
McG
railet
al.(2016)[95]
USA
n/r(descriptive
implem
entatio
nstud
y)One
prim
arycare
clinic,
onege
neralh
ospital
Statins,anticoagu
latio
nin
patientswith
atrial
fibrillatio
n,osteop
orosis
andknee
osteoarthritis,
urinaryincontinen
ce
SDM
inge
neral
TheSH
ARE
approach
“train-the
-trainer”
worksho
pwas
followed
bytraining
sessions
forreside
ntsand
med
icalgrou
pstaff.
P21
Mollicon
eet
al.(2013)[96]
USA
n/r(descriptive
implem
entatio
nstud
y)Specialty
care
center
Chron
ickidn
eydisease
SDM
inge
neral
Treatm
entOptions
Prog
ram
(TOPs)consistsof
free
classesofferedlocally,
natio
nwide,by
traine
dFM
CNApe
rson
neltoed
ucate
patientsandfamily
mem
bers
abou
ttheop
tions
fortreatm
ent.
Follow
upcalls
encourage
patientsto
discussop
tions
with
theirdo
ctorsand
participatein
theircare.
P22
Friedb
erget
al.(2013)[70]
MorrisseyandElwyn
(2013)
[97]
MorrisseyandMiche
ls(2011)
[98]
USA
n/r(descriptive
implem
entatio
nstud
y)Prim
arycare
Benign
prostatic
hype
rplasia,
prostate
cancer,b
reast
cancer,d
epression,
uterinefib
roids,chronic
low
back
pain,chron
icpain,m
enop
ause
Decisionaids
and
othe
rform
ofde
cision
supp
ort
Threemod
elsfor
implem
entatio
nwereused
:(1)
patient
referred
from
prim
arycare
orspecialistforcare
coordinatio
n/na
vigatio
nwhich
includ
edface
toface
visitwith
DA(2)
provider
teed
upSD
Mconversatio
nin
exam
room
andhand
edpatient
offto
nursewho
provided
inform
ationandDA(3)
patient
requ
estedDAand
care
coordinatorfollows
upwith
acallfordiscussion
P23
New
someet
al.(2012)[60]
USA
Post-im
plem
entatio
nqu
alitativestud
yFamily
med
icineclinics
Cancerscreen
ing,
chronicillne
sscare
Decisionaids
Physicians
used
theDAs
inclinicalpracticeand
med
icalassistantswere
involved
indistrib
ution
ofDAs(detailsno
tspecified
,repo
rted
inaseparate
publication).
Scholl et al. Implementation Science (2018) 13:40 Page 11 of 22
Table
2Includ
edim
plem
entatio
nprojects(Con
tinued)
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
P24
Pasternack
etal.(2011)[99]
Finland
n/r(descriptive
implem
entatio
nstud
y)Breastcancer
screen
ingproviders
Breastcancer
screen
ing
Decisionaids
Letter
templates
with
invitatio
nto
screen
ingandshort
decision
aidon
theback
whe
remadeavailableto
allb
reastcancer
screen
ing
facilitiesandmun
icipalities
inthecoun
try.Theshort
DAwas
puton
theback
oftheletter
toavoid
extracostsfortheproviders,
who
usually
justsend
out
theinvitatio
n.Aweb
site
containe
damorein
depth
decision
aid.
Theservice
providersreceived
inform
ation
onlegislation,
thene
wletter
templates,and
postersfor
thewaitin
groom
s.
P25
Sepu
chaandSimmon
s(2011)
[73]
Sepu
chaet
al.(2016)[100]
Simmon
set
al.(2016)[101]
USA
n/r(descriptive
implem
entatio
nstud
y)Prim
arycare
clinics
Vario
uscontexts:40
different
decision
aids
available
Decisionaids
Clinicians
wereableto
orde
rDAsthroug
htheelectron
icmed
icalrecord
(EMR).
TheEM
Rapplicationthen
gene
ratedano
tein
the
patient’schartdo
cumen
ting
that
thematerialh
asbe
ensent.The
distrib
utionand
inventoryof
DAwere
managed
centrally.The
DAswereavailablein
several
form
ats(e-m
ailm
essage
with
alinkto
access
theDAon
line;
DVD
andbo
okletin
themail).
Early
onDAprescriptio
nwas
done
inavisitby
theclinician,
buttheSD
Mim
plem
entatio
nteam
workedwith
clinicians
andadministratorsto
automatize
prescriptio
ns.Som
eyearsinto
theim
plem
entatio
nprog
ram,
ashort1htraining
mod
ule
was
delivered
toclinicians
toincrease
familiarity
with
theDAs,show
them
orde
ring
inEM
Randdiscussim
plem
entatio
nchalleng
es.The
yreceived
CMEpo
intsfortraining
.Further
into
theim
plem
entatio
nprog
ram,
patientsreceived
theop
portun
ityto
orde
rDAsthem
selves
(patient-directed
orde
ring).
Therewereno
mandatesor
long
-term
financialincentives
orpe
nalties
associated
with
usingor
notusingDAs
Scholl et al. Implementation Science (2018) 13:40 Page 12 of 22
Table
2Includ
edim
plem
entatio
nprojects(Con
tinued)
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
P26
Silviaet
al.(2008)[102]
SilviaandSepu
cha(2006)
[103]
USA
Post-im
plem
entatio
nqu
alitativestud
yCom
mun
ityresource
centers,commun
ityho
spitals,acade
mic
centers,commun
ityon
cology
center
Breastcancer
Decisionaids
Providersandresource
centersacross
thecoun
try
wereinform
edabou
tthe
availabilityof
theprog
rams
throug
hlettersande-mail.
Interested
sitesreceived
free
copies
andwereleftto
decide
them
selves
how
tousethem
.
P27
Stacey
etal.(2006)[104]
Canada
n/r(descriptive
implem
entatio
nstud
y)Callcen
ter
Vario
ushe
alth
issues;b
irth
controlm
etho
ds,b
reast
versus
bottlefeed
ing,
malene
wbo
rncircum
cision
,wisdo
mteethremoval,
andtreatm
entof
miscarriage
mostcommon
Decisionaids
and
othe
rform
ofde
cision
supp
ort
Interven
tions
includ
edan
onlineauto
tutorial,
skill-buildingworksho
p,de
cision
supp
ortprotocol,
andfeed
back
onqu
ality
ofde
cision
supp
ort
provided
tosimulated
callers
P28
Stacey
etal.(2008)[105]
Australia
Pre-po
stteststud
yCancercallcenter
Cancer
Other
form
ofde
cision
supp
ort
Interven
tions
includ
eda
decision
supp
orttutorial,
skill-buildingworksho
p,andde
cision
coaching
protocol.Sup
ervisors
weretraine
din
decision
supp
ort,atraine
rworksho
pwas
held
forsupe
rvisory
staffmem
bers,and
the
director
ofthecancer
helplineaddressedworksho
pparticipantsto
validatethat
decision
supp
ortisan
impo
rtantpartof
their
callcenter
role.
P29
Stacey
etal.(2015)[106]
Canada
Prospe
ctivepragmatic
observationaltrial
Cystic
fibrosisclinics
Adu
ltswith
cysticfib
rosis
consideringreferral
forlung
transplant
Decisionaids
and
othe
rform
ofde
cision
supp
ort
Implem
entatio
nstrategy
was
basedon
results
ofpriorbarrierssurvey.It
consistedof
training
(worksho
pandon
line
tutorial),easy
access
tode
cision
aids,and
conferen
cecalls
for
ongo
ingsupp
ort.
Patientscompleted
DA
ontheirow
nanddiscussed
results
with
provider
atasubseq
uent
encoun
ter,
andasummarywas
includ
edin
theclinicrecord.
P30
Stapletonet
al.(2002)[107]
UK
Post-im
plem
entatio
nqu
alitativestud
yWom
en’sho
mes,
maternity
clinics
Anten
atalcare
and
maternity
services
Decisionaids
Leafletswereprovided
aspartof
aclusterrand
omized
controlledtrial.Health
profession
alsreceived
atraining
sessionin
how
tousethem
.
Scholl et al. Implementation Science (2018) 13:40 Page 13 of 22
Table
2Includ
edim
plem
entatio
nprojects(Con
tinued)
ProjectID
Autho
r(year)
Cou
ntry
Stud
yde
sign
*Setting
Con
text
Implem
entedinterven
tion
Implem
entatio
nstrategy
P31
Swieskow
ski(2011)[73]
USA
n/r(descriptive
implem
entatio
nstud
y)Prim
arycare
clinics
Acute
andchroniclow
back
pain,d
iabe
tes,
wom
en’she
alth
issues,
knee
andhiposteoarthritis,
cardiaccond
ition
s,spinal
care,end
oflife
care,PSA
testing
Decisionaids
Potentialp
atientswereiden
tified
bypre-visitchartreview
and
DAswereprescribed
byproviders
orhe
alth
coache
sdu
ring
thevisit.Follow-upde
cision
supp
ortwas
provided
bythe
physicianor
thehe
alth
coachat
afollow-upvisit.
P32
Tapp
etal.(2014)[53]
USA
Process
improvem
entstud
yPrim
arycare
practices
Asthm
aSD
Min
gene
ral
Acommun
itybasedparticipatory
research
approach
was
used
toform
anadvisory
board
(includ
ingpatients,ph
ysician
cham
pion
s,othe
rhe
althcare
profession
als,administrative
staff)that
met
mon
thlyto
tailorinterven
tionto
need
sof
each
practice(e.g.,adaptin
ginterven
tionto
deliveryby
different
type
sof
staffmem
bers,
adaptin
gmaterialfor
useby
Spanish-speaking
,low
literacy
andpe
diatric
popu
latio
n,de
cide
onrollou
tsche
dule).
Allpractices
startedwith
kick-
offmeetin
g,then
discussion
roun
dsarou
ndlogistics,
training
sessions
(includ
ing
useof
decision
supp
ort
materials),regu
larfollow-up
meetin
gs.
UKUnitedKing
dom,U
SAUnitedStates
ofAmerica,SD
Mshared
decision
-making,
DCISdu
ctal
carcinom
ain
situ,P
SAprostate-spe
cific
antig
en,N
CINationa
lCan
cerInstitu
te,N
HSNationa
lHealth
Service,
*Study
design
:asrepo
rted
inpu
blication;
ifno
trepo
rted
(n/r),au
thorscatego
rized
basedon
stud
yde
scrip
tionin
brackets
Scholl et al. Implementation Science (2018) 13:40 Page 14 of 22
influencing the organizational level than the health systemlevel. The reported organizational characteristics arestrongly influenced by health system characteristics; forexample, the amount of time that a HCP has for a pa-tient’s visit is linked to payment models, the organizationalculture is influenced by the general culture of healthcaredelivery, and the leadership decisions within anorganization are affected by policies, payment models, andaccreditation criteria. As the identified characteristics canbe barriers, facilitators or both barriers and facilitators toSDM implementation, we described them in a value-neutral way.
Strengths and limitationsWe extracted reports from implementation studies de-scribed in any part of the included publications. Ouranalyses therefore cannot differentiate between experi-ences based on results and those reflecting interpret-ation of results. However, for a young research field, webelieve this broad scoping review is an important firststep to gaining an overview of the topic.A second limitation is that the primary search was
limited to three electronic databases, so we might havemissed relevant publications. However, we prioritizedsensitivity in our electronic search, which is reflected bythe high number of screened abstracts, to identify mostrelevant work. Furthermore, we conducted an extensivesecondary search, including gray literature to find morework not indexed in the electronic databases searched.Another limitation is that we did not conduct a fulldouble assessment and double data extraction. However,
we did our best to minimize error by consulting with asecond reviewer whenever there was the slightest doubt.A main strength of this review is that it is the first of itskind to focus solely on the impact of organizational andsystem characteristics on the implementation of SDM.In previous work, the focus had mainly been on the indi-vidual clinician-patient level, and organizational- andsystem-level characteristics had not been examined indepth [10, 14]. Furthermore, it was conducted in aninter-professional and international team.
Comparison to previous workFirst, these findings need to be compared to previouswork on SDM. Our results reinforce prior calls for bettercoordination of care, engagement of non-physicianpersonnel, and the use of the electronic health record(EHR) to implement SDM in previous work [61]. Thesuggestions to use clinical practice guidelines, post-graduate training, and accreditation as means to betterimplement SDM [5] are also reflected in the data col-lected in this scoping review. Many of the characteristicsidentified in this review have been discussed in trials ofSDM interventions or decision aids, in studies of clini-cians’ perceptions, or in opinion pieces, but this is thefirst piece of work looking at characteristics experiencedin actual implementation studies.Second, the results need to be compared to more gen-
eral work in healthcare implementation science, beyondthe case of SDM as a particular innovation to imple-ment. Implementation frameworks and conceptualmodels like the one postulated by Greenhalgh and
Leadership• Encouragement• Feedback• Mission / vision
Culture• Autonomy (staff)• Shared views / goals
Teamwork• Communication• Coordination of care
Resources• Time• Money• Space• Workforce
Organizational priorities
Workflows• Information dissemination
strategies• Electronic health record• Scheduling & timeframes
Health care provider education & licensing
Culture of health care delivery
Incentives• Payment model• Accreditation /
certification
Policies and guidelines• Legislation• Practice guidelines• Quality indicators
Organizational Characteristics
Health System Characteristics
Fig. 2 Overview of identified characteristics. Main categories are displayed in bold; subcategories are listed as bullet points. The dashed linearound the organizational characteristics indicates that these characteristics are influenced by health system characteristics
Scholl et al. Implementation Science (2018) 13:40 Page 15 of 22
Table
3Iden
tifiedorganizatio
nal-levelcharacteristics
Characteristics
Descriptio
ns#
ProjectIDs*
Organizationalleade
rship
2003
corporatemission
andvision
statem
ent
Deg
reeto
which
thede
scrip
tionof
theorganizatio
n’score
purposeandvision
forthefuture
supp
ortsSD
MP3,P8,P13,P25,P27,P28
Encouragem
ent
Deg
reeto
which
leadersin
organizatio
nproactivelysupp
ortSD
MP1,P2,P3,P4,P5,P8,P12,P13,P14,P25,P26,P27,P31
Perfo
rmance
measuremen
tand
feed
back
Use
ofresults
ofpe
rform
ance
measuremen
tor
quality
indicatormetricsto
indicate
room
forim
provem
ent
P2,P3,P7,P8,P13,P16,P18,P25,P27,P28,P32
Organizationalculture
Deg
reeto
which
anorganizatio
n’scultu
resupp
ortsSD
MP2,P3,P8,P12,P13,S14
Auton
omyof
staff
Deg
reeof
flexibilitythat
healthcare
providers(HCPs)have
toachieveorganizatio
nalg
oals
P1,P3,P8,P26
Shared
view
sandgo
als
Deg
reeto
which
team
mem
berssharethesameview
sandgo
als
P4,P8,P9,P13,P21,P31
Organizationalteamwork
Com
mun
ication
How
inform
ationisshared
with
inandbe
tweenteam
sP7,P8,P12,P13,P22,P32
Coo
rdinationof
care
Deliberateorganizatio
nof
care
byHCPs
from
different
specialties
P3,P7,P12,P13,P14,P16,P26,P32
Organizationalresou
rces
Availabilityof
resources
P12,P22,P26
Time
Amou
ntof
timeHCPs
have
perpatient/patient
visit
P1,P3,P5,P8,P9,P10,P12,P13,P14,P15,P19,P26,P27,P28,P29,
P30,P31,P32
Financialresou
rces
Amou
ntof
mon
eyavailableforcertainactivities
with
inorganizatio
nP2,P3,P4,P5,P11,P14,P19,P31
Space
Amou
ntof
room
availableforcertainactivities
with
inorganizatio
nP4,P5,P8,P26
Workforce
Availabilityandassign
men
tof
employeesforcertainactivities
with
inorganizatio
nP3,P4,P5,P8,P10,P12,P14,P18,P19,P22,P23,P27,P31,P32
Organizationalp
riorities
Deg
reeto
which
othe
raspe
ctsof
care
deliveryconflictor
alignwith
SDM
P2,P3,P4,P5,P8,P9,P10,P12,P13,P14,P18,P19,P26,P27,P31
Organizationalw
orkflows
Patient
inform
ationdissem
ination
strategies
Availabilityof
metho
dsto
dissem
inateinform
ationto
patientsandcompatib
ility
ofworkflowswith
decision
aid
distrib
utionprocesses
P2,P3,P4,P5,P6,P8,P12,P13,P14,P17,P22,P24,P25,P26,P27,
P28,P29,P31
Sche
dulingroutines
andtim
eframes
Deg
reeto
which
sche
duling(e.g.,of
appo
intm
entsor
forproced
ures)andtim
eframeavailableun
tilde
cision
isne
eded
impactsSD
MP3,P4,P6,P8,P10,P12,P13,P14,P15,P21,P22,P26,P29
Electron
iche
alth
record
(EHR)
Availabilityof
anEH
Rto
beused
inSD
M(e.g.,do
cumen
tatio
nof
process)
P2,P3,P6,P7,P8,P13,P14,P17,P18,P19,P20,P23,P27,P31
HCP
sHealth
care
prov
iders,EH
Relectron
iche
alth
record,SDM
shared
decision
-making
# The
descrip
tions
aretheresultof
thethem
atican
alysis
* For
projects
describ
edin
morethan
onepu
blication,
atleaston
epu
blicationha
dto
repo
rton
aspecificcharacteristic
tobe
listedin
thistable
Scholl et al. Implementation Science (2018) 13:40 Page 16 of 22
colleagues [20] or the Consolidated Framework for Im-plementation Research (CFIR) [19] have described ele-ments in the inner and outer settings to influenceimplementation. Our results found a range of very simi-lar characteristics on the organizational level to the onesdescribed in the inner setting, e.g., communication andculture within an organization, leadership engagement,resources, and priorities. However, some of the charac-teristics we found (e.g., workflows) were not described inthe CFIR [19]. One could hypothesize that these aspectsare more focused around decision aid implementationand therefore not included in a more general implemen-tation framework. Similarly, several of our system-levelcharacteristics map well onto the CFIR’s outer setting(i.e., aspects around policies, guidelines, and incentives),but the culture of the healthcare system and educationand licensing of healthcare professionals cannot befound in the framework [19]. Furthermore, a systematicreview on determinants of implementation of preventiveinterventions on patient handling identified a total of 45environmental barriers and facilitators [62] that overlapwith experienced organizational characteristics identifiedin our scoping review, particularly the availability of re-sources, leadership support, and the organization ofworkflows. Overall, our results in the field of SDM dis-play many similarities with the characteristics describedin implementation science frameworks and in otherfields of health innovation. However, as we also identifycharacteristics less described in implementation scienceliterature, we believe it is important to not to be re-stricted by such frameworks, but enrich them with de-rived empirical evidence.Third, some of the strategies recommended by the in-
cluded projects to intervene on characteristics influen-cing SDM implementation (Table 5) are vague andrequire further specification and tailoring to a specific
context [63]. For example, some of the strategies that fallinto the leadership category could benefit from distin-guishing which level of leadership should take action forwhich strategy. While the people in a governing board ofan organization might be the ones to revise missionstatements, executive leadership, and departmental man-agement might be the ones who create a culture thatsupports SDM [64]. Furthermore, all other categoriesidentified as organizational-level characteristics, despitenot specifying who should be in charge of making spe-cific changes, imply that organizational leadership is theactor here. Although it is not specified, for example,who should implement multidisciplinary teams or createan SDM coordinator position, there is an implicit as-sumption that these are leadership tasks. Beyond lookingat implementation literature, it might therefore beworthwhile for stakeholders working on SDM imple-mentation to look into organizational theories in health-care [65], e.g., on the effective organization of healthcareteams or on strategies to restructure healthcareorganizations.
Implications and suggestions for further workAs healthcare systems are complex and composed ofcomponents that act nonlinearly [66], a certain identifiedcharacteristic can be a facilitator to one stakeholder anda barrier to another. Therefore, more work is needed tomove beyond the descriptive stage of this review, espe-cially as differences in the numbers of studies reportingon certain characteristics do not necessarily mean thatthose characteristics are the most important. Similarly toKoppelaar et al. [62], we believe there is a need to quan-tify the influence of the identified characteristics, espe-cially as this scoping review’s broad nature is notdistinguishing between experiences based on results ofimplementation studies and interpretation of those
Table 4 Identified system-level characteristics
Characteristics Descriptions# Project IDs*
Incentives
Payment model Impact of payment models on the use of SDM P2, P3, P8, P13, P15, P16, P21, P26, P31, P32
Accreditation/certificationcriteria
Degree to which SDM is included as a criterion inaccreditation/certification standards for healthcare institutions
P3
Policies and guidelines
Legislation Degree to which state or national legislation requires the useof SDM/decision support
P3, P14, P19, P21, P29
Practice guidelines Degree to which relevant practice guidelines support the use of SDM P2, P3, P9, P26, P27, P28
Quality indicators Degree to which quality indicators support the use of SDM P3, P8, P13, P15
Culture of healthcare delivery Degree to which the culture of healthcare delivery supports SDM P13, P14, P16, P22
HCP education and licensing Degree to which HCP initial and continuing education and licensing includesSDM training
P3, P8, P10, P13, P14, P16, P23, P25, P26,P31
HCPs healthcare providers, SDM shared decision-making#The descriptions are the result of the thematic analysis*For projects described in more than one publication, at least one publication had to report on a specific characteristic to be listed in this table
Scholl et al. Implementation Science (2018) 13:40 Page 17 of 22
Table 5 Described strategies to address identified characteristics
Characteristics Strategies described
Organizational-level strategies
Organizational leadership
Corporate mission and vision statement Develop and promote a strong consistent message about importance of SDM [72]Make the value of SDM clear to physicians [83]Revise policy and procedure documents to include SDM in those directives [104, 105]
Encouragement Appoint an internal champion/have clinical champions [7, 54, 58, 59, 68, 87, 100, 103, 108]Provide personal testimonials from leaders [51]Support healthcare professionals (HCPs) in learning SDM skills, e.g., by protecting time to gettrained [7, 47, 51, 58]Support SDM implementation at all levels of the organization’s leadership [51, 59, 100, 102]Show interest by doing site visits to clinics/teams implementing SDM [7]Share success stories in grand rounds [58]
Performance measurement and feedback Provide continuous performance monitoring and feedback on SDM performance, decision aid distributionrate, decision quality, and patient satisfaction rates [7, 52, 53, 58, 69, 72, 81, 92, 104, 105, 108, 109]
Organizational culture Foster a well-organized and amicable work environment [50]Align SDM implementation with organization’s existing patient-centered philosophy and qualityimprovement spirit [51, 52]
Autonomy of staff Allow flexible use of decision aids and freedom on how to achieve SDM implementation goals [7, 47, 51]
Shared views and goals Address relational dynamics of healthcare teams before SDM implementation [89]Hold regular meeting to share goals and successes [54]
Organizational teamwork
Communication Foster frequent, timely, accurate, and problem solving communication about SDM implementationwithin and between teams [7, 89, 97]
Coordination of care Implement multidisciplinary teams [79, 102]Have a patient navigator [102]Have a clear definition of team members’ roles [50, 53]
Organizational resources
Time Decrease pressure for short patient interactions [105]/expand time to spend with patient [58, 103]Tailor interaction length guidelines for type of interaction [104]
Financial resources Obtain funding for SDM activities [90]Have access to high quality decision aids at low or no cost [52]
Space Use offices instead of clinical exam rooms for delivering decision support [74]
Workforce Engage non-physician personnel (e.g., nurses, office staff) [60, 70, 73, 90]Use unpaid or paid student interns or volunteers to deliver decision support [76, 77]Reorganize workforce responsibilities from over utilized to underutilized staff [74]Fund/hire a decision support/ care coordinator [77, 98]Salaried physicians for which SDM is part of employment obligations [51]
Organizational priorities Integrate SDM into other interventions or changes (e.g., health coaching, chronic disease managementprogram) [7, 94, 110]Align SDM with wider objectives of the organization (e.g., quality and safety) [7, 58]
Organizational workflows
Patient information dissemination strategies Automate decision aid distribution, e.g., pre-visit [78], based on triggers [70], send by mail [58, 75, 90]Keep decision aids/tools accessible in exam rooms and workspaces [7, 86, 87] and make them easilyavailable electronically [7, 58, 105]Offer in-office viewing of decision aids as well as other options (e.g., lending them to patients) [52]Align delivery of decision aids with other aspects of care (e.g., obtaining informed consent) [91]Partner with resource centers to deliver decision support [77]Clarify the place that decision aids have in the clinical pathway [103]Make decision aids available via a state-run website [51]Create protocols to prompted staff members to prescribe decision aid corresponding to the reasonfor referral [70]
Scheduling routines and time frames Get decision aids to patients prior to consultations [50, 52]Install scheduling system for SDM/decision aids/decision support [74, 103, 108]Require slowing down the flow of decision-making/reduce time pressure on patient path to treatmentdecision [58, 91]Allow for flexible patient pathways and scheduling [7, 75]
Scholl et al. Implementation Science (2018) 13:40 Page 18 of 22
results. By evaluating the influencing characteristics inimplementation studies, we could analyze interactionsbetween characteristics and find out which of them pre-dict implementation outcomes [18].As the included studies were predominantly from the
USA, future work needs to assess the importance of theidentified characteristics in different healthcare systemswith variation in financing, coverage, spending, utilization,capacity, and performance [67], as well as different fieldsof healthcare (e.g., cancer care, mental healthcare). Thiswould help to gain a more specific insight that could fos-ter prioritization of the most important characteristics in aparticular setting and strategies to address them.
ConclusionAlthough infrequently studied, organizational- andsystem-level characteristics appear to play a role in thefailure to implement SDM in routine care. A widerange of characteristics described as supporting andinhibiting implementation were identified. Futurestudies should quantify these characteristics’ differen-tial impact on SDM implementation, their likely inter-actions, and how different characteristics mightoperate across types of healthcare systems and areasof healthcare. Healthcare organizations that wish tosupport the adoption of SDM should carefully con-sider the role of organizational- and system-level
characteristics. Implementation and organizationaltheory could provide useful guidance for how to ad-dress facilitators and barriers to change.
Additional files
Additional file 1: Protocol. (PDF 129 kb)
Additional file 2: Electronic searches. (PDF 24 kb)
Additional file 3: Gray literature search. (XLSX 15 kb)
AbbreviationsCFIR: Consolidated Framework for Implementation Research; EHR: Electronichealth record; RCTs: Randomized controlled trials; SDM: Shared decision-making
AcknowledgementsWe thank Pamela Bagley for her support in developing the final electronicsearch strategy and for running the electronic database searches.Furthermore, we thank Robin Paradis Montibello for her work in the processof screening titles and abstracts.
FundingSupport for this research was provided by The Commonwealth Fund andthe B. Braun Foundation. The views presented here are those of the authorsand should not be attributed to The Commonwealth Fund or its directors,officers, or staff. The funding bodies were not involved in the design of thestudy and collection, analysis, and interpretation of data and in writing themanuscript.
Availability of data and materialsAll data generated or analyzed during this study are included in thispublished article and its supplementary information files.
Table 5 Described strategies to address identified characteristics (Continued)
Characteristics Strategies described
Electronic health record (EHR) Use EHR to prompt and document SDM process [7, 54, 70, 73]Use EHR (and merge it with computerized scheduling data) to identify patients eligible fordecision aids [69, 73, 78, 87, 90]Have decision aids available on EHR for easy access and have them available of patient portal onEHR [52, 58, 95, 104, 108]
System-level strategies
Incentives
Payment model Use a payment model that motivates providers to engage in SDM (e.g., patient-centered medicalhome) [51, 52, 92]Reimburse the use of a decision aid and time spent engaging in SDM conversation [91, 96, 103]Move away from fee-for-service to alternative model (e.g., pay-for-performance) [53–55]
Accreditation/certification criteria Revise accreditation/certification criteria by adding the implementation of SDM as criterion/qualityindicator [51]
Policies and guidelines
Legislation Create state legislation that fosters SDM (e.g., comparable to Washington state: enhanced legalprotection when doing SDM) [51, 56, 57]Create legislation that encourages healthcare organization structures that support SDM [51]
Practice guidelines Incorporate the use of SDM in clinical practice guidelines [103, 105]
Quality indicators Make the use of decision aids a quality of care indicator/list SDM as performance metric [55, 87, 91]Health plans could collect and distribute SDM performance data [51]Use a national set of measures [58]
Culture of healthcare delivery Promote culture of patient engagement in medical school [59]
Education and licensing Incorporate SDM communication skills (as compulsory) into medical school and residency curricula,as well as into state medical licensing criteria [51, 58–60]Offer CME/CEU credits for watching decision aids/for SDM training [54, 84, 109]
HCPs healthcare providers, EHR electronic health record, SDM shared decision-making, CME continuing medical examination, CEU continuing education units
Scholl et al. Implementation Science (2018) 13:40 Page 19 of 22
Authors’ contributionsIS, SK, and GE contributed to the conceptualization. IS, PH, SK, and GEcontributed to the design. IS, AL, and PH carried out the data selection andextraction. IS, AL, SK, and GE contributed to the data analysis. IS and ALconducted the data synthesis. IS, SK, and GE were involved in theinterpretation. SK and GE supervised the project. IS, GE and AL contributedto the visualization. IS and AL wrote the first manuscript draft. All authorswere engage in reviewing and editing the manuscript. All authors read andapproved the final manuscript.
Ethics approval and consent to participateNot applicable
Consent for publicationNot applicable
Competing interestsIS conducted one physician training in shared decision-making for which shereceived travel compensation from Mundipharma GmBH in 2015. AL and PHhave no competing interests to declare. SK has no competing interests todeclare and is an employee of the US government. GE reports personal feesfrom EMMI Solutions LLC, National Quality Forum, Washington State HealthDepartment, PatientWisdom LLC, SciMentum LLC, Access Community HealthNetwork, and Radcliffe Press outside the submitted work. GE has initiatedand led the Option Grid TM patient decisions aids collaborative, which pro-duces and publishes patient knowledge tools.
Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.
Author details1The Dartmouth Institute for Health Policy and Clinical Practice, DartmouthCollege, Level 5, Williamson Translational Research Building, One MedicalCenter Drive, Lebanon, NH 03756, USA. 2Department of Medical Psychology,University Medical Center Hamburg-Eppendorf, Martinistr. 52, W26, 20246Hamburg, Germany. 3Healthcare Delivery Research Program, National CancerInstitute, 9609 Medical Center Drive, Rockville, MD 20852, USA.
Received: 3 August 2017 Accepted: 27 February 2018
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