1 **TITLE PAGE**

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3 **Category: Systematic review - Antibiotic stewardship**

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5 **Title**

6 Systematic review of factors promoting behaviour change towards antibiotic use in hospitals

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8 **Authors and institutional affiliations**

9 Emilie Pouly¹, Maïder Coppry¹,², Anne-Marie Rogues¹,², Catherine Dumartin²,³

10 ¹Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, Team

11 Pharmacoepidemiology, UMR 1219, F-33000 Bordeaux, France.

12 ²CHU Bordeaux, Hygiène Hospitalière, Bordeaux, France.

13 ³CHU Bordeaux, CPias Nouvelle-Aquitaine, Bordeaux, France.

14

15 **Corresponding author**

16 Dr Catherine Dumartin

17 CPias Nouvelle-Aquitaine. Hôpital Pellegrin CHU de Bordeaux. Place Amélie Raba-Léon,

18 Bâtiment Le Tondu, 33076 Bordeaux, France

19 Tel. +33 (0)5 56 79 60 58

20 Fax. +33 (0)5 56 79 60 12

21 Email: catherine.dumartin@u-bordeaux.fr

22

23 **Length of abstract:** 299 words

24 **Length of the paper itself (excluding abstract and references):** 3,181 words
25 **ABSTRACT**

26 **Background:** Antimicrobial stewardship (AMS) programmes include actions to improve
27 antibiotic use.

28 **Objective:** To identify factors of AMS interventions associated with behaviour change
29 towards antibiotic use in hospitals, applying behavioural sciences.

30 **Data sources:** The following online databases were searched: PubMed and Scopus.

31 **Study eligibility criteria:** Studies published between January 2015 and December 2020.
32 Outcomes required were: effect of the intervention reported in terms of antibiotic
33 consumption, antibiotic costs, appropriateness of prescription, duration of therapy, proportion
34 of patients treated with antibiotics, or time to appropriate antibiotic therapy.

35 **Participants:** Healthcare professionals involved in antibiotic prescription and use in
36 hospitals, and patients receiving or susceptible to receive antibiotics.

37 **Interventions:** Studies investigating AMS interventions in hospitals.

38 **Assessment of risk of bias:** Risk of bias was determined using the “Integrated quality criteria
39 for review of multiple study designs” (ICROMS) tool.

40 **Methods of data synthesis:** Systematic review of AMS interventions, using “Behaviour
41 Change Wheel” to identify behaviour changes functions of interventions, and “Action, actor,
42 context, target, time (AACTT)” framework to describe how they are implemented.
43 Relationships between intervention functions and AACTT domains were explored to deduce
44 factors for optimal implementation.

45 **Results:** Among the 124 studies reporting 123 interventions, 64% were effective in reducing
46 antibiotic use or improving quality of antibiotic prescription. 91% of the studies had high risk
47 of bias. Main functions retrieved in effective interventions were enablement, environmental
48 restructuring, and education. The most common subcategories were audit and feedback and
49 real-time recommendation for enablement function; and material resources, human resources,
and new task for environmental restructuring function. Most AMS interventions focused on
prescription, targeted prescribers, and were implemented by pharmacists, infectious diseases
specialists, and microbiologists. Interventions focusing on specific clinical situation were
effective in 70% of cases.

**Conclusion:** Knowledge of factors associated with behaviour changes will help addressing
local barriers and enablers before implementing interventions.

The review protocol was registered in the International prospective register of systematic
reviews (PROSPERO CRD42021243939).
## 58 INTRODUCTION

The emergence and worldwide spread of antimicrobial resistance (AMR) is so alarming that tackling AMR has become a high priority for the World Health Organization [1].

In human medicine, AMR is associated with morbidity and mortality [2] and leads to prolonged hospital stay and increased health care costs [3]. One major driver of AMR is inappropriate use of antibiotics through the selection pressure mechanism [4]. Thus, improving antibiotic prescribing is a global emergency.

Hospitals are particularly affected by AMR [2]: inpatients generally present several risk factors, receive invasive care, and are often exposed to antibiotics for prophylaxis or treatment. Thus, improving antibiotic use in hospital context is challenging [5].

Antimicrobial stewardship (AMS) has been defined as “a coherent set of actions which promote using antimicrobials responsibly” [6]. AMS programmes generally consist of organizational policy and practice-based interventions. AMS interventions improve appropriate antibiotic use and patients’ outcomes, reduce AMR and health-care-associated infections, and save health-care costs [7–9]. However, variations in objectives and improvement strategies among hospitals and countries have been reported [6,10].

Indeed, improving antibiotic use is challenging because it depends on human factors within a context of a wide social network with continuous interactions between physicians, nurses, pharmacists, microbiologists, and patients. Behaviour change approaches are recommended to take into account psychological determinants [11], to optimise AMS interventions locally in hospitals and to maximise efficient implementation worldwide [1,7,12–14].

For example, interventions to change healthcare professionals’ behaviours can be characterized with nine functions from the “Behaviour Change Wheel” (BCW) [15]. This classification has already been used [7,16] to better describe AMS activities.
Furthermore, detailing the context for interventions implementation helps to clarify how it affects interventions effectiveness. The “Action, actor, context, target, time (AACTT)” framework [17] proposes five domains to describe interventions [16,18].

Understanding intervention functions and context should help to identify barriers and enablers for implementation of successful AMS activities. Indeed, implementation science has been defined as “scientific study of methods to promote the systematic uptake of research findings and other evidence-based practices into routine practice, and, hence, to improve health services” [19,20].

Previous literature reviews investigating appropriate antibiotic use in the hospital setting aimed to estimate the effectiveness and safety of interventions [7–9]. However, factors that make AMS interventions effective were not often precisely described.

Considering that improvements in the reported outcomes regarding antibiotic use was the result of a change in healthcare professionals’ behaviour, we conducted a systematic review to identify the most relevant factors that promote behaviour change towards antibiotic use in hospitals. We used behavioural sciences to identify the functions of AMS interventions related to changes in healthcare professionals’ behaviours [15], and to describe how interventions are implemented [17].

## 99 METHODS

### 100 Search strategy, data sources and selection process

The “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines were used to conduct this systematic review (Supplementary Table S1) [21]. The review protocol was registered in the International prospective register of systematic reviews (PROSPERO CRD42021243939).
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A systematic search was conducted electronically, using PubMed and Scopus databases. The
search included articles published from 01/01/2015 to 12/31/2020.

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The search strategy on PubMed combined the subject headings and free text keywords "antibacterial agents" AND "drug misuses" OR "antimicrobial stewardship" OR "inappropriate prescribing" OR "organizational policy" OR "health behaviour" OR "health knowledge, attitudes, practice" OR "decision making" OR "behavioural science" OR "attitude of health personnel" OR "guideline adherence" OR "barrier*" OR "perception" AND "hospitals".

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The search strategy on Scopus combined the free text keywords "antibiotic*" OR "antimicrobial*" OR "antibacterial agent*" AND "perception" OR "behaviour" OR "attitude*" OR "guideline adherence" OR "barrier*" OR "facilitator*" OR "knowledge" OR "practice*" OR "misuse" OR "*appropriate*" OR "stewardship" OR "implementation" AND "health* facilit*" OR "hospital*".

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Three reviewers performed article screening, according to inclusion criteria. Studies included in the systematic review were assessed and data were collected in duplicate by three reviewers. Potentially additional studies were searched using the reference lists of included articles.

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**Study eligibility criteria**

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The scope of the search was literature investigating AMS interventions in hospitals. Other inclusion criteria were:

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* Country: Studies performed in countries with national guidelines on antimicrobial stewardship for public and private hospitals involving actors such as infectious diseases (ID) specialists, pharmacists, and microbiologists (i.e., European Union member states, South Africa, Australia, Canada, United States of America, Iceland, Norway, New-Zealand, Switzerland, and the United Kingdom).

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* Population: Healthcare professionals involved in the process of antibiotic prescription and use in hospitals (i.e., physicians, nurses, pharmacists, microbiologists, infection control professionals, AMS teams, hospital managers) and patients receiving or susceptible to receive antibiotics.

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* Study design: Randomised controlled trials (RCT), controlled interrupted time series studies (CITS), non-controlled interrupted time series studies (NCITS), controlled before-after studies (CBA), non-controlled before-after studies (NCBA), and cohort studies (CS).

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* Outcomes: Effect of the intervention on AMS reported in terms of antibiotic consumption, antibiotic costs, appropriateness of prescription, duration of therapy, proportion of patients treated with antibiotics, and time to appropriate antibiotic therapy.

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We excluded studies not clearly describing AMS interventions, studies exploring AMS interventions in nursing homes, and studies involving healthcare professionals not working in hospitals. We also excluded qualitative study design, systematic reviews of interventions targeting antibiotic use in hospitals, and case studies.

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## Data collection

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By using a collection form, we performed data extraction and quality assessment of included studies in duplicate.

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## Assessment of risk of bias

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The risk of bias (ROB) was determined using the "Integrated quality criteria for review of multiple study designs" (ICROMS) tool [22]. Disagreements were resolved through discussion.
153 Methods of data analysis and synthesis

154 From AMS activities reported in included articles, we extracted the different factors
155 described and we classified them using the BCW framework [15]. BCW classification
156 identifies nine intervention functions: coercion, education, enablement, environmental
157 restructuring, incentivisation, modelling, persuasion, restriction, and training (Supplementary
158 Table S2). A given intervention may involve more than one behaviour change function. To
159 better describe intervention functions, we made subcategories for enablement function (alert,
160 algorithm, audit and feedback, decision aid tool, feedback on prescribing practices, real-time
161 recommendation), and for environmental restructuring function (human resources, material
162 resources, new diagnostic tool, new task).

163 We applied an adapted AACTT framework [17] to clearly describe interventions in AMS
164 context. We only described the main AMS action for which behaviour change was sought,
165 using the following modified AACTT definitions (Supplementary Table S3):

166 • Action: discrete observable behaviour to be changed (antibiotic administration,
167 diagnosis, initial prescription, review of prescription, prescription at discharge,
168 surgical prophylaxis prescription, and therapeutic drug monitoring);

169 • Actor: individual or group of individuals who conduct the intervention to change the
170 behaviour;

171 • Context: the physical, emotional, or social setting in which the actor performs the
172 intervention (focus on wards or clinical situation or specific antibiotics, AMS
173 programme or team already in place);

174 • Target: the individual or group of individuals who receive the intervention to change
175 their behaviour to perform the action;

176 • Time: the time period and duration that the actor performs the intervention.
We determined categories for intervention effectiveness based on study outcomes defined above. Interventions with significant outcomes were categorised as “effective interventions”, and interventions with non-significant outcomes as “not effective interventions”. When studies had both significant and non-significant outcomes, priority was given to primary outcome; if primary outcome was not clearly defined or was not an outcome of interest, interventions were classified as “inconclusive”.

In effective interventions, we explored relationships between AACTT domains and intervention functions to identify main factors retrieved.

## 185 RESULTS

The electronic search retrieved 830 publications. We identified 63 potential additional publications from reference list of included articles, resulting in a total of 875 publications after removal of duplicates. Title and abstract screening resulted in 205 full texts to assess. Finally, 124 studies met inclusion criteria for further analysis, reporting 123 AMS interventions (Figure 1 and Supplementary material Table S4).

## 191 Study characteristics and risk of bias assessment

Of the 124 studies, there were eight RCT, five CITS, 31 NCITS, three CBA, 76 NCBA, and one CS (Table 1). Most studies were conducted in North America (68 in United States of America and 11 in Canada). A total of 24 studies were conducted in the European Union, eight in Australia, and six in the United Kingdom.

According to ICROMS risk of bias assessment tool, 11 studies were judged as low ROB: two RCT, one CITS, one CBA, six NCBA, and one CS (Table 1).
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## Intervention functions of AMS interventions promoting behaviour change in hospitals

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Among the 123 interventions, 328 intervention functions were identified (Figures 2a and 2b; median number of intervention functions = 2; min = 1; max = 5).

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Of the nine intervention functions described in BCW, only coercion was not reported in any intervention. Enablement, environmental restructuring, and education were the most frequently intervention functions identified. Incentivisation, modelling and training were the less frequently identified. Among enablement function, the most common subcategory was audit and feedback. Among environmental restructuring function, the most common subcategories were material resources and human resources.

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## Conditions of AMS interventions implementation

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When modified AACTT framework was applied, all domains were described in 80% of interventions (99/123). Actor and time were among the least often described (Table 2).

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The most common action in AMS interventions was prescribing.

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The actor was clearly specified in 88% of interventions. The median number of actors categories involved per intervention was two (min = 1; max = 4). In 23% of interventions, actors were included within an AMS team, defined as a group of healthcare professionals working together to perform the main activity of the intervention.

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Pharmacists were involved in 75 interventions, ID specialists in 65 interventions, and microbiologists in 26 interventions. Nurses were involved in six interventions.

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Half of interventions (50%) focused on specific clinical situations: bloodstream infections (20 interventions), respiratory tract infections (13 interventions), urinary tract infections (seven interventions), and antibiotic allergies (six interventions).

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One third of interventions (32%) focused on specific wards: emergency department (nine interventions), surgical units (eight interventions), and intensive care units (seven interventions).
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The most common target was the prescriber i.e., medical physicians, medical and surgical residents, anaesthesia specialists, and surgeons. Two interventions also targeted patients in the specific context of antibiotic allergy, where patients received information (i.e., written recommendations regarding the revised antibiotic allergy labels and antibiotics that could be safely administered).

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The time period and duration of the main intervention action was clearly specified in 90% of interventions: interventions were mainly performed within 24 hours.

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## Functions and conditions of AMS interventions associated with an improvement in antibiotic use in hospitals

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A total of 79 interventions (i.e., 64%) were categorised as “effective”, 33 as “inconclusive”, and 11 as “not effective” (Table 1). We identified 211 intervention functions among the 79 effective interventions (median number of intervention functions = 2; min = 1; max = 5).

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The most effective intervention functions (Figure 2a) were restriction (72% of interventions using restriction were effective); environmental restructuring (65%); education (65%); and enablement (63%). Among environmental restructuring function (Figure 2b), the most effective subcategories were new task (81%) and material resources (70%). Among enablement function, the most effective subcategories were real-time recommendation (77%), algorithm (75%), and alert (70%).

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The three most common intervention functions identified in effective interventions were enablement, environmental restructuring, and education, with differences in the subcategories for enablement and environmental restructuring functions.

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## According to action types

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In effective interventions aimed at improving initial prescription (35/47), main subcategories identified among enablement function were audit and feedback and real-time

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recommendation. Among environmental restructuring function, main subcategory was
material resources.

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According to actor category

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In effective interventions involving one category of actor (24/40), main subcategory of enablement was audit and feedback. Among environmental restructuring, main subcategories were material resources and human resources.

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In effective interventions involving more than one category of actor (28/40), main subcategories of enablement were audit and feedback and real-time recommendation. Among environmental restructuring, main subcategories were material resources and new task.

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In effective interventions where actors were part of an AMS team (17/28), education was not among the main intervention functions. Main subcategories of enablement were real-time recommendation and audit and feedback. Among environmental restructuring, main subcategories were human resources and new task.

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According to the context

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In effective interventions focusing on specific clinical situation (43/61), main subcategories of enablement were real-time recommendation and audit and feedback. Among environmental restructuring, main subcategories were material resources and new task. All seven interventions focusing on bloodstream infections and combining real-time recommendation and new diagnostic tool performed within 24 hours were effective.

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In effective interventions focusing on specific antibiotics (33/52), interestingly, we identified restriction in addition to the three main intervention functions (e.g., pharmacist prospective review of all respiratory fluoroquinolone orders for consistency with the approved restriction criteria; pre-authorisation by a pharmacist or an ID specialist).

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272 According to the time

273 In effective interventions performed within 24 hours (54/85), main subcategories identified
274 among enablement were audit and feedback and real-time recommendation; it was audit and
275 feedback in effective interventions performed between 24 hours and 7 days (10/14).

276 As targets other than antibiotic prescribers were rare, we did not describe distribution of
277 intervention functions for this domain.

278 DISCUSSION AND CONCLUSION

279 We conducted this systematic review in order to identify the conditions of implementation of
280 AMS interventions and BCW intervention functions associated with improvement in
281 antibiotic use. We described multimodal interventions involving multiple behaviours and
282 most of them were assessed as effective in reducing antibiotic use or improving quality of
283 antibiotic prescription. Potential publication bias and inclusion of studies with high risk of
284 bias must be considered to interpret this finding.

285 When we explored functions used in effective interventions according to the conditions of
286 implementation (i.e., regarding AACTT domains), we retrieved three main functions:
287 enablement, environmental restructuring, and education. Surprisingly, in interventions
288 involving AMS team, education was not among the most frequent functions. This may result
289 from previous educational activities performed by AMS team before intervention
290 implementation [23]. As expected, restriction function was retrieved across the main
291 functions used in interventions focusing on specific antibiotics. This is consistent with
292 European Union guidelines [12] that recommend performing “policy for pre-authorisation
293 [...] of selected antimicrobial prescriptions” and AMS practices in United States hospitals
294 [23].
295 Enablement was one of the most common intervention functions in effective interventions.
296 This is consistent with findings of Davey et al who found that involving enablement and
297 restriction functions increased intervention effect [7]. Environmental restructuring was the
298 second most common intervention function identified. In their systematic review, Crayton et
299 al reported that "interventions involving enablement, environmental restructuring and
300 delivery of audit and feedback strategies were likely to enhance AMS" in nursing homes
301 [16]. This suggests that similar intervention components might be promising in the hospital
302 setting.

303 The most common subcategories of enablement in effective interventions were audit and
304 feedback and real-time recommendation. These findings show the relevance of implementing
305 audit and feedback, as recommended in European AMS guidelines [12], and in line with
306 another systematic review [24].

307 The detailed description of AACTT domains revealed the need for improving the
308 multidisciplinary of AMS activities. Indeed, AMS is a multidisciplinary approach [6],
309 recognized as a strong international recommendation [12]. However, an AMS team was
310 mentioned in only 23% of interventions. This finding is consistent with a previous review
311 [18] and calls for efforts to increase the availability of qualified professionals to conduct
312 AMS activities. Furthermore, targets of the studied interventions always included prescribers,
313 for the action of prescribing antibiotics. Yet, the prescribing process involves various
314 healthcare professionals in several steps. Surprisingly, in only 5% of interventions, nurses
315 were targeted although many publications showed the interest of their involvement in AMS
316 [25,26]. This description reveals room for improvement in action and target diversity in AMS
317 interventions.

318 When considering specific conditions of implementation, as defined by AACTT domains,
319 some subcategories were most commonly involved in effective interventions.
In effective interventions aimed at improving initial prescription, audit and feedback and real-time recommendation were frequently performed. Interventions using real-time recommendation seemed to be more often effective compared to audit and feedback performed within 24 hours. In fact, modifying a prescription already issued or after drug dispensation or administration may appear more complex and less acceptable for the prescriber. Thus, the difference in effectiveness for audit and feedback and real-time recommendation could be explained by prescribers' perceptions. This finding suggests the importance of choosing intervention function according to available resources and ability to act at the right time.

When interventions involved one category of actors, we retrieved most frequently human resources subcategory. This suggests that implementing an AMS intervention involving one single actor was made possible by recruiting healthcare professionals or by identifying dedicated time for professionals already working in the institution. This finding is in line with European AMS guidelines that require that healthcare facilities provide the necessary funding and resources for AMS programmes [12].

Regarding the context, half of interventions focused on a specific clinical situation and seemed to be associated with interventions effectiveness (70% of effectiveness). In interventions focusing on a specific clinical situation, prescriber's commitment may be enhanced because clinical outcomes are measured and/or because serious situations are addressed. Among bloodstream infections, all interventions combining real-time recommendation and new diagnostic tool functions performed within 24 hours were effective.

## Strengths and limitations

To our knowledge this is the first study that used two complementary behavioural sciences frameworks [15,17] to explore implementation of AMS strategies in hospitals. In addition, to improve description of AMS interventions, a strength of this systematic review is the
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specification of subcategories for enablement and environmental restructuring functions.

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Finally, despite no clear association between BCW functions and effectiveness, the large number of references included allowed us to clearly describe interventions and, thus, to identify criteria of interest to achieve optimal conditions for implementation of AMS interventions in hospitals.

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This study has several limitations. First, we limited our search to PubMed and Scopus. Other databases could have brought additional references. Second, identification of BCW intervention functions and AACTT domains was sometimes challenging as authors description could give way to different interpretations. Nevertheless, we discussed on disagreements to harmonize classifications. Third, 91% of studies had high ROB. This is consistent with findings from previous work and calls for significant improvements in the methods of AMS studies, building on professional recommendations and considering integration of implementation sciences aspects [27–29]. Fourth, when assessing interventions effectiveness, we focused on outcomes regarding antibiotic consumption and appropriateness; we did not consider other outcomes such as clinical results. Last, we cannot rule out that other factors played a role in the associations retrieved between AACTT domains and intervention functions.

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To conclude, this review highlighted relevant factors that should promote behaviour change towards antibiotic use in hospitals. Interventions including enablement, environmental restructuring, and education are likely to optimize antibiotic use. Taking into account the context, focusing on some subcategories of enablement and environmental restructuring could improve interventions effectiveness, such as performing real-time recommendation in interventions aimed at improving initial prescription. Therefore, assessment of the local situation before implementation of AMS activities should help to identify barriers and enablers and then, to check whether all conditions are met to effectively put in place the

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required intervention. Besides this state of play of the local situation, assessing healthcare

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professionals' perceptions is recommended to adapt interventions and increase their

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acceptance [19,30,31].

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**Transparency declaration**

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The authors declare that they have no conflicts of interest.

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There was no specific funding for this systematic review.

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**Authors' contributions**

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All authors have seen and approved the manuscript, contributed significantly to the work. All

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authors contributed equally to the study design, paper review, and data collection. E.P.

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performed the literature search, citations screening on title and abstract, full text screening,

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data collection, data analysis, data interpretation, figures and tables, wrote the first draft of

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the paper and finalised the writing. C.D. and M.C. conceived the project, contributed to

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abstract and full text screening and to data collection, reviewed all the pertinent data to check

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their validity and provided multiple drafts of the paper. A-M. R. conceived the project and

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provided multiple drafts of the paper.

385
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formation of a comprehensive framework. Clin Microbiol Infect 2019;25(5):538–45.
<table><caption>**Table 1** Studies characteristics and interventions effectiveness</caption><thead><tr><td>First author</td><td>Year</td><td>Country</td><td>Study design</td><td>Study period</td><td>Intervention effectiveness</td><td>ROB<sup>a</sup></td></tr></thead><tbody><tr><td>Anderson</td><td>2019</td><td>USA<sup>b</sup></td><td>CBA<sup>c</sup></td><td>2013-2015</td><td>Effective</td><td>High</td></tr><tr><td>Bai</td><td>2015</td><td>Canada</td><td>CS<sup>d</sup></td><td>2007-2010</td><td>Effective</td><td>Low</td></tr><tr><td>Blumenthal</td><td>2015</td><td>USA</td><td>NCBA<sup>e</sup></td><td>2011-2014</td><td>Effective</td><td>High</td></tr><tr><td>Boel</td><td>2016</td><td>Denmark</td><td>CITS<sup>f</sup></td><td>2008-2014</td><td>Effective</td><td>High</td></tr><tr><td>Bolten</td><td>2019</td><td>USA</td><td>NCBA</td><td>2015-2016</td><td>Effective</td><td>High</td></tr><tr><td>Bond</td><td>2017</td><td>Australia</td><td>NCBA</td><td>2013-2014</td><td>Effective</td><td>High</td></tr><tr><td>Bond (b)</td><td>2017</td><td>Australia</td><td>NCITS<sup>g</sup></td><td>2010-2014</td><td>Effective</td><td>High</td></tr><tr><td>Bonsignore</td><td>2018</td><td>Germany</td><td>NCBA</td><td>2015-2016</td><td>Effective</td><td>High</td></tr><tr><td>Bookstaver</td><td>2017</td><td>USA</td><td>NCBA</td><td>2010-2015</td><td>Effective</td><td>High</td></tr><tr><td>Box</td><td>2015</td><td>USA</td><td>NCBA</td><td>2011-2014</td><td>Effective</td><td>High</td></tr><tr><td>Brink</td><td>2016</td><td>South Africa</td><td>NCITS</td><td>2009-2014</td><td>Effective</td><td>High</td></tr><tr><td>Brink</td><td>2017</td><td>South Africa</td><td>NCBA</td><td>2013-2015</td><td>Effective</td><td>High</td></tr><tr><td>Burston</td><td>2017</td><td>Australia</td><td>CBA</td><td>2015</td><td>Effective</td><td>High</td></tr><tr><td>Campbell</td><td>2017</td><td>Canada</td><td>NCITS</td><td>2009-2014</td><td>Effective</td><td>High</td></tr><tr><td>Chrysou</td><td>2018</td><td>Greece</td><td>NCBA</td><td>2015-2016</td><td>Effective</td><td>High</td></tr><tr><td>Collins</td><td>2016</td><td>USA</td><td>NCBA</td><td>2014</td><td>Effective</td><td>High</td></tr><tr><td>Du Plessis</td><td>2019</td><td>New Zealand</td><td>NCBA</td><td>2015</td><td>Effective</td><td>High</td></tr><tr><td>Eby</td><td>2018</td><td>USA</td><td>NCBA</td><td>2012-2015</td><td>Effective</td><td>Low</td></tr><tr><td>Flett</td><td>2018</td><td>USA</td><td>NCITS</td><td>2014-2016</td><td>Effective</td><td>High</td></tr><tr><td>Frymoyer</td><td>2020</td><td>USA</td><td>NCITS</td><td>2015-2019</td><td>Effective</td><td>High</td></tr><tr><td>Giacobbe</td><td>2017</td><td>Italy</td><td>NCBA</td><td>2014-2016</td><td>Effective</td><td>High</td></tr><tr><td>Gibbons</td><td>2017</td><td>USA</td><td>NCITS</td><td>2011-2012</td><td>Effective</td><td>High</td></tr><tr><td>Gordon</td><td>2018</td><td>USA</td><td>NCBA</td><td>2012-2015</td><td>Effective</td><td>High</td></tr></tbody></table>
<table><tr><td>Haran</td><td>2020</td><td>USA</td><td>NCBA</td><td>2017</td><td>Effective</td><td>High</td></tr><tr><td>Hersh</td><td>2018</td><td>USA</td><td>NCITS</td><td>2013-2015</td><td>Effective</td><td>High</td></tr><tr><td>Hincker</td><td>2017</td><td>USA</td><td>NCBA</td><td>2014-2015</td><td>Effective</td><td>High</td></tr><tr><td>Hurst</td><td>2016</td><td>USA</td><td>NCITS</td><td>2010-2014</td><td>Effective</td><td>High</td></tr><tr><td>Irfan</td><td>2015</td><td>Canada</td><td>CITS</td><td>2012-2013</td><td>Effective</td><td>High</td></tr><tr><td>James</td><td>2019</td><td>USA</td><td>NCBA</td><td>2016-2017</td><td>Effective</td><td>High</td></tr><tr><td>Johnson</td><td>2016</td><td>USA</td><td>NCBA</td><td>2012-2013</td><td>Effective</td><td>High</td></tr><tr><td>Kandel</td><td>2016</td><td>Canada</td><td>NCBA</td><td>2010-2013</td><td>Effective</td><td>High</td></tr><tr><td>Kashtan</td><td>2020</td><td>USA</td><td>NCBA</td><td>2017-2019</td><td>Effective</td><td>High</td></tr><tr><td>Kirk</td><td>2019</td><td>USA</td><td>NCITS</td><td>2012-2018</td><td>Effective</td><td>High</td></tr><tr><td>Lambl</td><td>2017</td><td>USA</td><td>NCBA</td><td>2013-2016</td><td>Effective</td><td>High</td></tr><tr><td>Langford</td><td>2016</td><td>Canada</td><td>NCITS</td><td>2008-2015</td><td>Effective</td><td>High</td></tr><tr><td>Langford</td><td>2019</td><td>Canada</td><td>NCITS</td><td>2012-2016</td><td>Effective</td><td>High</td></tr><tr><td>Leis</td><td>2017</td><td>Canada</td><td>NCBA</td><td>2015-2016</td><td>Effective</td><td>High</td></tr><tr><td>Lesprit</td><td>2015</td><td>France</td><td>RCT<sup>h</sup></td><td>2010-2011</td><td>Effective</td><td>High</td></tr><tr><td>Li</td><td>2016</td><td>USA</td><td>NCBA</td><td>2010-2014</td><td>Effective</td><td>High</td></tr><tr><td>Libertin</td><td>2017</td><td>USA</td><td>NCBA</td><td>2013-2015</td><td>Effective</td><td>High</td></tr><tr><td>Lockwood</td><td>2016</td><td>USA</td><td>NCBA</td><td>2011-2014</td><td>Effective</td><td>High</td></tr><tr><td>Lowe</td><td>2017</td><td>Canada</td><td>NCBA</td><td>2014-2016</td><td>Effective</td><td>High</td></tr><tr><td>MacVane</td><td>2016</td><td>USA</td><td>NCBA</td><td>2010-2014</td><td>Effective</td><td>Low</td></tr><tr><td>Martin</td><td>2015</td><td>Canada</td><td>NCBA</td><td>2011-2012</td><td>Effective</td><td>High</td></tr><tr><td>McLellan</td><td>2016</td><td>UK<sup>i</sup></td><td>RCT</td><td>2013</td><td>Effective</td><td>High</td></tr><tr><td>Mediwala</td><td>2019</td><td>USA</td><td>NCBA</td><td>2013-2017</td><td>Effective</td><td>High</td></tr><tr><td>Messacar</td><td>2017</td><td>USA</td><td>NCBA</td><td>2010-2015</td><td>Effective</td><td>High</td></tr><tr><td>Messina</td><td>2015</td><td>South Africa</td><td>NCBA</td><td>2013-2014</td><td>Effective</td><td>High</td></tr><tr><td>Molina</td><td>2017</td><td>Spain</td><td>NCITS</td><td>2009-2015</td><td>Effective</td><td>High</td></tr><tr><td>Nguyen</td><td>2015</td><td>USA</td><td>NCBA</td><td>2012-2014</td><td>Effective</td><td>High</td></tr></table>
<table><tr><td>Papadimitriou-Olivgeris</td><td>2020</td><td>Switzerland</td><td>NCBA</td><td>2014-2018</td><td>Effective</td><td>High</td></tr><tr><td>Patton</td><td>2018</td><td>UK</td><td>NCITS</td><td>2006-2010</td><td>Effective</td><td>High</td></tr><tr><td>Pettit</td><td>2018</td><td>USA</td><td>NCBA</td><td>2014-2017</td><td>Effective</td><td>High</td></tr><tr><td>Phillips</td><td>2018</td><td>Australia</td><td>NCBA</td><td>2010-2014</td><td>Effective</td><td>High</td></tr><tr><td>Picart</td><td>2016</td><td>France</td><td>NCBA</td><td>2012-2014</td><td>Effective</td><td>High</td></tr><tr><td>Polen</td><td>2018</td><td>USA</td><td>NCBA</td><td>2016-2017</td><td>Effective</td><td>High</td></tr><tr><td>Popovski</td><td>2015</td><td>Canada</td><td>NCBA</td><td>2010-2011</td><td>Effective</td><td>High</td></tr><tr><td>Porter</td><td>2019</td><td>USA</td><td>NCBA</td><td>2014-2017</td><td>Effective</td><td>High</td></tr><tr><td>Rawlins</td><td>2018</td><td>Australia</td><td>NCBA</td><td>2015-2016</td><td>Effective</td><td>High</td></tr><tr><td>Rosa</td><td>2018</td><td>USA</td><td>NCITS</td><td>2014-2015</td><td>Effective</td><td>High</td></tr><tr><td>Scholze</td><td>2015</td><td>Germany</td><td>NCBA</td><td>2010-2013</td><td>Effective</td><td>High</td></tr><tr><td>Schröder</td><td>2020</td><td>Germany</td><td>NCBA</td><td>2008-2017</td><td>Effective</td><td>High</td></tr><tr><td>Shea</td><td>2017</td><td>USA</td><td>NCBA</td><td>2013-2014</td><td>Effective</td><td>High</td></tr><tr><td>Spruiell</td><td>2017</td><td>USA</td><td>NCBA</td><td>2009-2014</td><td>Effective</td><td>High</td></tr><tr><td>Stenehjem</td><td>2018</td><td>USA</td><td>RCT</td><td>2013-2015</td><td>Effective</td><td>High</td></tr><tr><td>Stultz</td><td>2019</td><td>USA</td><td>NCBA</td><td>2008-2017</td><td>Effective</td><td>High</td></tr><tr><td>Swearingen</td><td>2016</td><td>USA</td><td>NCBA</td><td>2012-2013</td><td>Effective</td><td>High</td></tr><tr><td>Tamma</td><td>2017</td><td>USA</td><td>NCITS</td><td>2013-2014</td><td>Effective</td><td>High</td></tr><tr><td>Tedeschi</td><td>2017</td><td>Italy</td><td>NCBA</td><td>2011-2014</td><td>Effective</td><td>High</td></tr><tr><td>Tischendorf</td><td>2020</td><td>USA</td><td>NCITS</td><td>2014-2018</td><td>Effective</td><td>High</td></tr><tr><td>Townsend</td><td>2016</td><td>USA</td><td>NCBA</td><td>2010-2014</td><td>Effective</td><td>High</td></tr><tr><td>Trubiano</td><td>2017</td><td>Australia</td><td>NCBA</td><td>2015-2016</td><td>Effective</td><td>Low</td></tr><tr><td>Turner</td><td>2017</td><td>USA</td><td>NCITS</td><td>2010-2015</td><td>Effective</td><td>High</td></tr><tr><td>Walsh</td><td>2018</td><td>USA</td><td>NCBA</td><td>2014-2015</td><td>Effective</td><td>High</td></tr><tr><td>Wenzler</td><td>2017</td><td>USA</td><td>NCBA</td><td>2015-2016</td><td>Effective</td><td>Low</td></tr><tr><td>Wilke</td><td>2015</td><td>Germany</td><td>NCBA</td><td>2014</td><td>Effective</td><td>High</td></tr><tr><td>Willis</td><td>2017</td><td>USA</td><td>NCITS</td><td>2009-2015</td><td>Effective</td><td>High</td></tr></table>
<table>
  <tr>
    <td>Wilson</td>
    <td>2019</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2015-2016</td>
    <td>Effective</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Wolfe</td>
    <td>2019</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2016-2017</td>
    <td>Effective</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Antonioli</td>
    <td>2018</td>
    <td>Italy</td>
    <td>NCBA</td>
    <td>2014-2015</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Asencio Egea</td>
    <td>2018</td>
    <td>Spain</td>
    <td>NCBA</td>
    <td>2016-2017</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Beaulac</td>
    <td>2016</td>
    <td>USA</td>
    <td>NCITS</td>
    <td>2010-2014</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Bouza</td>
    <td>2020</td>
    <td>Spain</td>
    <td>NCBA</td>
    <td>2015-2017</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Charani</td>
    <td>2017</td>
    <td>UK</td>
    <td>NCITS</td>
    <td>2008-2014</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Cona</td>
    <td>2020</td>
    <td>Italy</td>
    <td>NCBA</td>
    <td>2016-2018</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Cross</td>
    <td>2019</td>
    <td>UK</td>
    <td>NCBA</td>
    <td>2017</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Day</td>
    <td>2015</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2008-2012</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Donà</td>
    <td>2019</td>
    <td>Italy</td>
    <td>NCBA</td>
    <td>2016-2017</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Dustin Waters</td>
    <td>2015</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2006-2012</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Eljaaly</td>
    <td>2018</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2012-2013</td>
    <td>Inconclusive</td>
    <td>Low</td>
  </tr>
  <tr>
    <td>García-López</td>
    <td>2017</td>
    <td>Spain</td>
    <td>NCBA</td>
    <td>2010-2013</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>García-Martínez</td>
    <td>2016</td>
    <td>Spain</td>
    <td>NCBA</td>
    <td>2011-2014</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Graber</td>
    <td>2015</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2012-2013</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Griebel</td>
    <td>2018</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2013-2017</td>
    <td>Inconclusive</td>
    <td>Low</td>
  </tr>
  <tr>
    <td>Hartley</td>
    <td>2016</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2011-2013</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Hecker</td>
    <td>2020</td>
    <td>USA</td>
    <td>NCBA</td>
    <td>2013-2015</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Høgli</td>
    <td>2016</td>
    <td>Norway</td>
    <td>NCITS</td>
    <td>2014-2015</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Jenkins</td>
    <td>2015</td>
    <td>USA</td>
    <td>NCITS</td>
    <td>2005-2014</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Jenkins</td>
    <td>2018</td>
    <td>USA</td>
    <td>NCITS</td>
    <td>2014-2016</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>Kreitmeyr</td>
    <td>2017</td>
    <td>Germany</td>
    <td>NCBA</td>
    <td>2014-2015</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>MacBrayne</td>
    <td>2020</td>
    <td>USA</td>
    <td>NCITS</td>
    <td>2010-2018</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>May</td>
    <td>2015</td>
    <td>USA</td>
    <td>RCT</td>
    <td>2011-2014</td>
    <td>Inconclusive</td>
    <td>Low</td>
  </tr>
  <tr>
    <td>Morrill</td>
    <td>2016</td>
    <td>USA</td>
    <td>NCITS</td>
    <td>2010-2013</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
  <tr>
    <td>O'Callaghan</td>
    <td>2019</td>
    <td>Australia</td>
    <td>NCBA</td>
    <td>2017-2018</td>
    <td>Inconclusive</td>
    <td>High</td>
  </tr>
</table>
<table><tr><td>Phillips</td><td>2015</td><td>Australia</td><td>NCBA</td><td>Not specified</td><td>Inconclusive</td><td>High</td></tr><tr><td>Sarma</td><td>2015</td><td>UK</td><td>NCITS</td><td>2007-2012</td><td>Inconclusive</td><td>High</td></tr><tr><td>Taggart</td><td>2015</td><td>Canada</td><td>CITS</td><td>2012-2014</td><td>Inconclusive</td><td>Low</td></tr><tr><td>Tavares</td><td>2018</td><td>Portugal</td><td>CITS</td><td>2012-2016</td><td>Inconclusive</td><td>High</td></tr><tr><td>Trautner</td><td>2015</td><td>USA</td><td>CBA</td><td>2010-2013</td><td>Inconclusive</td><td>Low</td></tr><tr><td>Velasco-Arnaiz</td><td>2020</td><td>Spain</td><td>NCITS</td><td>2015-2018</td><td>Inconclusive</td><td>High</td></tr><tr><td>Wathne</td><td>2018</td><td>Norway</td><td>RCT</td><td>2014</td><td>Inconclusive</td><td>High</td></tr><tr><td>Wattier</td><td>2017</td><td>USA</td><td>NCITS</td><td>2011-2016</td><td>Inconclusive</td><td>High</td></tr><tr><td>Zhang</td><td>2017</td><td>USA</td><td>NCBA</td><td>2014-2015</td><td>Inconclusive</td><td>High</td></tr><tr><td>Bouchand</td><td>2017</td><td>France</td><td>NCBA</td><td>2012-2014</td><td>Not effective</td><td>High</td></tr><tr><td>Branche</td><td>2015</td><td>USA</td><td>RCT</td><td>2013-2014</td><td>Not effective</td><td>High</td></tr><tr><td>Brendish</td><td>2017</td><td>UK</td><td>RCT</td><td>2015-2016</td><td>Not effective</td><td>High</td></tr><tr><td>Klatte</td><td>2018</td><td>USA</td><td>CITS</td><td>2013-2016</td><td>Not effective</td><td>High</td></tr><tr><td>Nzegwu</td><td>2017</td><td>USA</td><td>NCITS</td><td>2011-2016</td><td>Not effective</td><td>High</td></tr><tr><td>O'Sullivan</td><td>2019</td><td>USA</td><td>NCITS</td><td>2013-2017</td><td>Not effective</td><td>High</td></tr><tr><td>Pitiriga</td><td>2018</td><td>Greece</td><td>NCBA</td><td>2014-2017</td><td>Not effective</td><td>High</td></tr><tr><td>Saarela</td><td>2020</td><td>Finland</td><td>RCT</td><td>2014-2015</td><td>Not effective</td><td>Low</td></tr><tr><td>Smoke</td><td>2019</td><td>USA</td><td>NCITS</td><td>2016-2017</td><td>Not effective</td><td>High</td></tr><tr><td>Thom</td><td>2019</td><td>USA</td><td>NCBA</td><td>2014-2015</td><td>Not effective</td><td>High</td></tr><tr><td>Yogo</td><td>2017</td><td>USA</td><td>NCBA</td><td>2012-2015</td><td>Not effective</td><td>High</td></tr></table>

ªROB = risk of bias; ᵇUSA = United States of America; ᶜCBA = controlled before-after study; ᵈCS = cohort study; ᵉNCBA = non-controlled before-after study; ᶠCITS = controlled interrupted time series study; ᶣNCITS = non-controlled interrupted time series study; ᵤRCT = randomised controlled trial; ᶜUK = United Kingdom
<table><caption>**Table 2** Action, Actor, Context, Target and Time (ACCTT) domains identified in the 123 interventions, distribution of study design and risk of bias</caption><thead><tr><th colspan="2">AACTT<sup>a</sup> domain</th><th>Study design</th><th>ROB<sup>b</sup></th><th>Effective interventions (n)</th><th>Total interventions (n)</th></tr></thead><tbody><tr><td rowspan="10">Action</td><td>Initial and review of prescription</td><td>3 RCT<br>3 CITS; 14 NCITS<br>28 NCBA</td><td>45 high ROB</td><td>29</td><td>48</td></tr><tr><td>Initial prescription</td><td>5 RCT<sup>c</sup><br>1 CITS<sup>d</sup>; 11 NCITS<sup>e</sup><br>2 CBA<sup>f</sup>; 27 NCBA<sup>g</sup><br>1 CS<sup>h</sup></td><td>41 high ROB</td><td>35</td><td>47</td></tr><tr><td>Review of prescription</td><td>1 NCITS<br>10 NCBA</td><td>10 high ROB</td><td>5</td><td>11</td></tr><tr><td>Surgical prophylaxis prescription</td><td>1 NCITS<br>4 NCBA</td><td>5 high ROB</td><td>3</td><td>5</td></tr><tr><td>Diagnosis and initial prescription</td><td>1 NCITS<br>1 CBA; 2 NCBA</td><td>3 high ROB</td><td>2</td><td>4</td></tr><tr><td>Prescription at discharge</td><td>1 NCITS<br>2 NCBA</td><td>3 high ROB</td><td>1</td><td>3</td></tr><tr><td>Initial and surgical prophylaxis prescription</td><td>1 CITS; 1 NCITS</td><td>2 high ROB</td><td>2</td><td>2</td></tr><tr><td>Therapeutic drug monitoring and initial prescription</td><td>2 NCBA</td><td>2 high ROB</td><td>1</td><td>2</td></tr><tr><td>Antibiotic administration</td><td>1 NCBA</td><td>1 high ROB</td><td>1</td><td>1</td></tr><tr><td rowspan="5">Actor</td><td>One category of actor</td><td>4 RCT<br>2 CITS; 5 NCITS<br>2 CBA; 26 NCBA<br>1 CS</td><td>38 high ROB</td><td>24</td><td>40</td></tr><tr><td>More than one category of actor (excluding AMS<sup>i</sup> team)</td><td>3 RCT<br>2 CITS; 11 NCITS<br>24 NCBA</td><td>35 high ROB</td><td>28</td><td>40</td></tr><tr><td>AMS team</td><td>1 CITS; 9 NCITS<br>18 NCBA</td><td>26 high ROB</td><td>17</td><td>28</td></tr><tr><td>Not specified</td><td>1 RCT<br>5 NCITS<br>1 CBA; 8 NCBA</td><td>13 high ROB</td><td>10</td><td>15</td></tr><tr><td>Specific clinical situation</td><td>4 RCT<br>2 CITS; 9 NCITS<br>2 CBA; 43 NCBA<br>1 CS</td><td>54 high ROB</td><td>43</td><td>61</td></tr><tr><td rowspan="4">Context</td><td>AMS programme or team already in place</td><td>1 RCT<br>2 CITS; 20 NCITS<br>1 CBA; 29 NCBA</td><td>48 high ROB</td><td>36</td><td>53</td></tr><tr><td>Specific antibiotics</td><td>1 RCT<br>3 CITS; 16 NCITS<br>1 CBA; 31 NCBA</td><td>33 high ROB</td><td>33</td><td>52</td></tr><tr><td>Specific wards</td><td>6 RCT<br>3 CITS; 11 NCITS<br>1 CBA; 18 NCBA</td><td>35 high ROB</td><td>19</td><td>39</td></tr></tbody></table>
<table><tbody><tr><td rowspan="5">Target</td><td>Prescribers</td><td>8 RCT<br>5 CITS; 29 NCITS<br>2 CBA; 69 NCBA<br>1 CS</td><td>105 high ROB</td><td>73</td><td>114</td></tr><tr><td>Prescribers and nurses</td><td>1 NCITS<br>1 CBA; 2 NCBA</td><td>3 high ROB</td><td>3</td><td>4</td></tr><tr><td>Prescribers, nurses,<br>microbiologists, and<br>pharmacists</td><td>2 NCBA</td><td>2 high ROB</td><td>0</td><td>2</td></tr><tr><td>Prescribers and patients</td><td>2 NCBA</td><td>1 high ROB</td><td>2</td><td>2</td></tr><tr><td>Not specified</td><td>1 NCBA</td><td>1 high ROB</td><td>1</td><td>1</td></tr><tr><td rowspan="4">Time</td><td>Within 24 hours</td><td>6 RCT<br>1 CITS; 19 NCITS<br>2 CBA; 57 NCBA</td><td>76 high ROB</td><td>54</td><td>85</td></tr><tr><td>Between 24 hours and 7 days</td><td>1 RCT<br>2 CITS; 4 NCITS<br>7 NCBA</td><td>14 high ROB</td><td>10</td><td>14</td></tr><tr><td>Other (after 7 days or punctual<br>sessions)</td><td>1 RCT<br>2 CITS; 2 NCITS<br>1 CBA; 6 NCBA</td><td>11 high ROB</td><td>6</td><td>12</td></tr><tr><td>Not specified</td><td>5 NCITS<br>6 NCBA<br>1 CS</td><td>11 high ROB</td><td>9</td><td>12</td></tr></tbody></table>

ᵃAACTT = action, actor, context, target, time; ᵇROB = risk of bias; ᶜRCT = randomised controlled trial; ᵈCITS = controlled interrupted time series study; ᵉNCITS = non-controlled interrupted time series study; ᶠCBA = controlled before-after study; ᵃNCBA = non-controlled before-after study; ᶠCS = cohort study; ᶠAMS = antimicrobial stewardship
<figure><img src="image_1.png" /><figcaption>**Figure 1** Study flow diagram (PRISMA)</figcaption></figure>
<figure><img src="image_2.png" /><figcaption>**Figure 2a** Repartition of interventions effective or not according to intervention functions</figcaption></figure>

<table><thead><tr><th></th><th>Education<br>(n = 71)</th><th>Enablement<br>(n = 107)</th><th>Environmental<br>restructuring<br>(n = 90)</th><th>Incentivisation<br>(n = 1)</th><th>Modelling<br>(n = 5)</th><th>Persuasion<br>(n = 21)</th><th>Restriction<br>(n = 25)</th><th>Training<br>(n = 8)</th></tr></thead><tbody><tr><td>Effective intervention</td><td>46</td><td>68</td><td>59</td><td>1</td><td>1</td><td>12</td><td>18</td><td>6</td></tr><tr><td>Not effective intervention/inconclusive</td><td>25</td><td>39</td><td>31</td><td>0</td><td>4</td><td>9</td><td>7</td><td>2</td></tr><tr><td></td><td>71</td><td>107</td><td>90</td><td>1</td><td>5</td><td>21</td><td>25</td><td>8</td></tr></tbody></table>
<figure><img src="image_3.png" /><figcaption>**Figure 2b** Repartition of interventions effective or not according to subcategories of enablement and environmental restructuring functions</figcaption></figure>

<table><thead><tr><th></th><th>Alert<br>(n = 10)</th><th>Algorithm<br>(n = 12)</th><th>Audit and<br>feedback<br>(n = 60)</th><th>Decision aid<br>tool<br>(n = 13)</th><th>Feedback on<br>prescribing<br>practices<br>(n = 17)</th><th>Real-time<br>recommendation<br>(n = 22)</th><th>Human<br>resources<br>(n = 37)</th><th>Material<br>resources<br>(n = 47)</th><th>New<br>diagnostic<br>tool<br>(n = 13)</th><th>New task<br>(n = 26)</th></tr></thead><tbody><tr><th>Effective intervention</th><td>7</td><td>9</td><td>37</td><td>6</td><td>8</td><td>17</td><td>23</td><td>33</td><td>8</td><td>21</td></tr><tr><th>Not effective intervention/inconclusive</th><td>3</td><td>3</td><td>23</td><td>7</td><td>9</td><td>5</td><td>14</td><td>14</td><td>5</td><td>5</td></tr><tr><th></th><td>10</td><td>12</td><td>60</td><td>13</td><td>17</td><td>22</td><td>37</td><td>47</td><td>13</td><td>26</td></tr></tbody></table>