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The Broad Spectrum Project. Factors determining the quality of antibiotic use in primary care: an observational study protocol from Italy. ForJournal: peerBMJ Open review only Manuscript ID bmjopen-2020-038843

Article Type: Protocol

Date Submitted by the 26-Mar-2020 Author:

Complete List of Authors: Kurotschka, Peter; University of Cagliari, Department of Medical Science and Public Health; Istituto Superiore di Sanita, National Centre for pre- clinical and clinical drug research and surveillance (CNRVF) Serafini, Alice; General Practitioner in training, Local Health Trust Modena Massari, Marco; Istituto Superiore di Sanita, National Centre for pre- clinical and clinical drug research and surveillance (CNRVF) Da Cas, Roberto; Istituto Superiore di Sanita, National Centre for pre- clinical and clinical drug research and surveillance (CNRVF) Figueiras, Adolfo; Universidade de Santiago de Compostela, Department of Preventive Medicine and Public Health

Forte, Viviana; General Practitioner, Regional Health Trust, Sardinia, http://bmjopen.bmj.com/ Italy Moro, Maria Francesca; Columbia University Mailman School of Public Health Massidda, Matteo; General Practitioner in training, Regional Health Trust, Sardinia, Italy Contu, Federico; General Practitioner in training, Regional Health Trust, Sardinia, Italy Minerba, Luigi; University of Cagliari, Department of Medical Science and

Public Health on September 23, 2021 by guest. Protected copyright. Marcias, Maurizio; Health Technology Assessment Unit - Regional Health Trust of Sardinia Nardelli, Marco; Tower Hamlets Primary Care Trust, Brayford Square Surgery Perra, Alessandra; University of Cagliari, Department of Medical Science and Public Health Carta, M; University of Cagliari, Department of Medical Science and Public Health Spila Alegiani, Stefania; Istituto Superiore di Sanita, National Centre for pre-clinical and clinical drug research and surveillance (CNRVF)

PRIMARY CARE, PUBLIC HEALTH, Quality in health care < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, EPIDEMIOLOGY, Keywords: EDUCATION & TRAINING (see Medical Education & Training), Epidemiology < INFECTIOUS DISEASES

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44 on September 23, 2021 by guest. Protected copyright. 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 The Broad Spectrum project.

4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Factors determining the quality of antibiotic use in primary care: an 6 7 observational study protocol from Italy 8 9 Peter Konstantin Kurotschka1,2,3,4 * & Alice Serafini5*, Marco Massari2, Roberto Da Cas2, Adolfo 10 Figueiras6, Viviana Forte3,7, Maria Francesca Moro8, Matteo Massidda3,4, Federico Contu3,4, Luigi 11 1 9 10 1 1 12 Minerba , Maurizio Marcias , Marco Nardelli , Alessandra Perra , Mauro Giovanni Carta **, Stefania 2 13 Spila Alegiani ** 14 15 * These authors contributed equally to this work (shared first authorship) 16 17 ** These authors also contributed equally to this work (shared last authorship) 18 For peer review only 19 (1) Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy 20 (2) Italian National Institute of Health, National Centre for pre-clinical and clinical drug research and surveillance 21 (CNRVF), Rome, Italy 22 (3) Italian Secretariat of Physician Scientists – SIMeR (SIGM), Italy (4) General Practitioner in training, Regional Health Trust, Sardinia, Italy 23 (5) General Practitioner in training, Local Health Trust Modena, Emilia-Romagna, Italy 24 (6) Department of Preventive Medicine and Public Health, University of Santiago de Compostela, Consortium for 25 Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), 26 Santiago de Compostela, Spain 27 (7) General Practitioner, Regional Health Trust, Sardinia, Italy 28 (8) Mailman School of Public Health, Columbia University, New York City, USA 29 (9) Health Technology Assessment Unit - Regional Health Trust, Sardinia, Italy 30 (10) General Practitioner, Tower Hamlets Primary Care Trust, Brayford Square Surgery, London, United Kingdom 31 32 Correspondence to: 33 Peter Konstantin Kurotschka 34 Via Genovesi 34, 09124 Cagliari 35 E-Mail [email protected] 36 Phone +393924712115 http://bmjopen.bmj.com/ 37 38 KEYWORDS: antibiotic, prescription, general practice, family medicine, appropriate, use, consumption, 39 questionnaire, knowledge, attitudes, factors, determinants. 40 41 WORD COUNT: 4000 42 43

44 on September 23, 2021 by guest. Protected copyright. 45 ABSTRACT 46 47 Introduction. The overuse of antibiotics (ABs) is causing worldwide spread of antimicrobial 48 resistance (AMR). Italy has a high consumption rate of ABs and if compared to other European 49 countries, one of the highest rates of AMR. 50 Due to the fact that around 90% of ABs are prescribed by General Practitioners (GPs), this 51 study aims to measure the impact of knowledge, attitudes and socio-demographic and 52 workplace related factors on the quality of AB prescriptions filled by GPs in the Italian Region 53 54 of Sardinia. 55 Methods and analysis. Knowledge, attitude, socio-demographic and workplace-related 56 factors deemed to influence physicians prescribing behaviour will be evaluated in a cross- 57 sectional study conducted among all GPs of the Italian Region of Sardinia (n~1200). A 58 knowledge and attitudes questionnaire (ITA-KAAR) accompanied by a socio-demographic 59 form will be linked to drug prescription data reimbursed by the National Health System 60 (NHS). European Surveillance of AB Consumption (ESAC) quality indicators for outpatient AB

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1 2 3 use will be calculated from drug prescription records. Every GP will be deemed to have 4 demonstrated an adequate quality of prescriptions of ABs (AQPA) if half of the indicator score BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 plus one is better than the median of the region. A multivariate Poisson regression model with 7 robust variance estimation will be used to evaluate the impact of the determinants of AB 8 prescriptions on the actual prescribing quality of each physician. 9 Ethics and dissemination. The project has been approved by the ethics committee of the 10 Regional Health Trust of Sardinia (176/2019/CE, 24th September 2019). The results will be 11 useful to inform evidence-based interventions to tackle irrational antibiotic use in the 12 13 community. 14 15 16 ARTICLE SUMMARY 17 Strengths and limitations of this study. 18 - The “Broad Spectrum”For peerproject will reviewshed new light ononly the context-specific physician and 19 20 workplace related determinants of appropriate use of outpatient antibiotics in General 21 Practice. 22 - Addressing the above factors will inform the development of interventions to tackle 23 inappropriate use of antibiotics. 24 - The use of internationally accepted indicators of antibiotic consumption allows 25 comparability to similar studies performed across Europe, enhances external validity 26 27 of the results and makes it possible that the study design could serve as a 28 methodological framework to address the determinants of antibiotic misuse in other 29 European regions. 30 - The main weakness of the study is that no clinical data about the reason for the 31 encounter resulting in an antibiotic prescription is available. Therefore, the complexity 32 33 of patient-doctor relationship could not be taken into proper account but possible bias 34 resulting from inaccurate registration of the reason for the encounter will be avoided. 35

36 http://bmjopen.bmj.com/ 37 INTRODUCTION 38 Antimicrobial resistance (AMR) has emerged, alongside climate change, as a global threat to 39 1 40 public health and wealth. Every year in Europe 33,000 people die due to infections caused by 41 resistant bacteria and globally approximately 700,000 cases of such infections occur every 42 year.2,3 Within 2050, antimicrobial resistant bacteria will cause more then 10 million deaths 43 each year and a global loss of gross domestic product of more than 100 billion US dollars.3 44 The overuse of antibiotics is one of the main drivers of AMR, but on a global scale antibiotic on September 23, 2021 by guest. Protected copyright. 45 use is still rising.4,5 Italy has a higher consumption rate of antibiotics compared to many other 46 6 47 European countries. In 2018 the annual consumption rate of Italian hospital and primary 48 care sectors combined was 21.4 Defined Daily Doses (DDDs) / 1000 inhabitants / day (DIDs). 49 The vast majority of antibiotic prescriptions (i.e. 90%, 19 DIDs) are filled by General 50 Practitioners (GPs). Aggregated level data show that there is a high variability of antibiotic 51 prescription rates among different regions of the country and a high variability of antibiotic 52 prescription rates in different seasons of the year, with highest rates occurring in flu season.7 53 54 Moreover, the consumption of broad-spectrum antibiotics is approximately twice as high as in 55 other European countries like Norway, Sweden or the United Kingdom.6 56 For all these reasons it seems to be very likely that the majority of antibiotic prescriptions in 57 Italy could be avoided. Both, qualitative and quantitative methodologies have been used in 58 different settings of low-, middle- and high-income countries to understand the determinants 59 of antibiotic overuse.8-12 Prescribing, especially antibiotic prescribing, is a complex behaviour, 60 with intrinsic factors (socio-demographic variables, knowledge, attitudes) and extrinsic

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1 2 3 factors (signs and symptoms at presentations, comorbidity, socio-demographic variables, 4 workload, influence of pharmaceutical companies, cost saving) that impact the healthcare BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 13 6 professional decision. Therefore, to inform stakeholders (GPs, European and national 7 agencies, scientific societies) in the development of effective interventions to tackle irrational 8 antibiotic use, an understanding of the context specific determinants of antibiotic prescription 9 is needed.13 10 GPs have a key role in Italy’s National Health System (NHS). Virtually all of the resident 11 population is compulsorily registered on a GP list and a pharmaceutical prescription can be 12 13 charged to the NHS only if filled by a GP or a specialist consultant working directly for the 14 NHS. Consequently, taking into consideration that in public healthcare systems GPs act as 15 pharmaceutical gatekeepers, they could play an active role in tackling the phenomenon of 16 antibiotic overuse and non-evidence based prescription habits. 17 At the best of our knowledge, there are no published studies that measure, with validated 18 tools, the knowledgeFor and attitudes peer of GPsreview on AMR and only antibiotic prescriptions in Italy. 19 20 Moreover, we were not able to retrieve any study that evaluated the influence of knowledge 21 and attitudes of GPs on their prescriptions of antibiotics in our settings. 22 23 24 AIMS and OBJECTIVES 25 The study will be divided into two distinct but related parts: Study axis A and Study axis B. 26 27 Study axis A. 28 AIM. To describe the attitudes and knowledge of GPs regarding AMR and antibiotic 29 prescriptions by administering a questionnaire adapted from Spanish to Italian language 30 (ITA-KAAR).14 31 OBJECTIVES 32 33 1. Measure the attitudes and knowledge of GPs through the administration of the ITA- 34 KAAR questionnaire. 35 2. Describe the characteristics and working context of GPs by filling a socio-demographic

36 form. http://bmjopen.bmj.com/ 37 3. Evaluate the reliability and validity of the ITA-KAAR questionnaire. 38 Study axis B. 39 40 AIM. To describe the quantity, pharmacological classes, appropriateness and inter-individual 41 variability of GPs prescriptions of antibiotics in the Italian region of Sardinia and to 42 investigate the determinants of inappropriate prescriptions. 43 OBJECTIVES 44 1. Evaluate GPs antibiotic prescribing behaviour (quantity, pharmacological class, on September 23, 2021 by guest. Protected copyright. 45 appropriateness, inter-individual variability) through the analysis of prescription data 46 47 of antibiotics for systemic use recorded in the administrative database of the Regional 48 Health Trust of Sardinia (ATS Sardegna). 49 2. Evaluate the association between the determinants of GPs prescribing behavior 50 (demographic factors, work environment, territorial context, attitudes and knowledge 51 regarding antibiotic resistance, resulting from the objectives A1 and A2) and the 52 appropriateness of antibiotic prescriptions (resulting from the objective B1). 53 54 55 56 METHODS AND ANALYSIS 57 Study design 58 A cross-sectional study will be carried out for both study axis A and study axis B. 59 Study axis A An attitudes and knowledge questionnaire (ITA-KAAR) and a socio-demographic 60 form will be administered to all GPs working in the Italian region of Sardinia, to measure

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1 2 3 attitudes, knowledge and socio-demographic factors deemed to be related to AMR and 4 antibiotic prescriptions. BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 Study axis B A drug utilization study will be conducted to evaluate the prescriptions and the 7 appropriateness of antibiotic choice for systemic use of all Sardinian GPs and to investigate 8 the influence of determinants of inappropriate prescription. 9 10 Study Population and setting. 11 All residents of the Sardinia Region are covered by the NHS, which provides comprehensive 12 13 hospital and outpatient care for those registered with a GP. GPs provide primary care for the 14 whole temporarily or permanently resident population. A pharmaceutical prescription can be 15 charged to the NHS only if filled by a GP or a specialist consultant working directly for the 16 NHS.15 17 Study axis A The entire Sardinian GP workforce (n~1200), providing care to 1,639,591 18 Sardinian inhabitantsFor at the peer date of 1st review January 2019, only will be recruited.16 The ITA-KAAR 19 20 questionnaire and a socio-demographic form will be filled by all GPs included in the study 21 through an online platform. 22 Study axis B All prescriptions of antibiotics for systemic use (Anatomical Therapeutic 23 Classification – ATC J01) filled by Sardinian GPs will be extracted from the pharmaceutical 24 database of the Regional Health Trust of Sardinia during the period 2017-2019. The database 25 contains all prescriptions covered by the NHS and is regularly updated. 26 27 28 Outcome and Covariates assessment. 29 Study axis A The knowledge and attitudes section of ITA-KAAR measures, by means of a 30 Visual Analogue Scale (VAS), some of the GPs attitudes on AMR and AB prescriptions, namely 31 lack of knowledge, fear, external responsibility and complacency to patient demands and 32 33 expectations. The 7-item accessorial section of the questionnaire focuses on some of the main 34 information sources for good clinical practice deemed to be relevant for GPs. 35 The questionnaire, including an additional section assessing potential socio-demographic and

36 work-context related factors potentially associated with the appropriateness of antibiotic use, http://bmjopen.bmj.com/ 37 will be sent through an online platform via E-mail to all GPs of the region of Sardinia. 38 Reminders will be sent to non-responders every 10-14 days. The first 100 responders will be 39 40 asked to complete the questionnaire a second time after 10-14 days (test-retest reliability). 41 After this first phase of data collection, in case of low response rate, a comprehensive 42 stepwise approach (including phone calls, postal reminders, reminders at continuous medical 43 education events, involvement of locally known network leaders, professional associations 44 and the state medical boards) will be used to achieve an acceptable response rate (see on September 23, 2021 by guest. Protected copyright. 45 “sample size” below).17 46 47 The KAAR-11 questionnaire has shown to be a reliable and valid instrument to assess 48 attitudes and knowledge of GPs on AMR and antibiotic prescriptions. The questionnaire was 49 developed taking into account the findings of a literature review and a qualitative focus group 50 study.13,18 51 The ITA-KAAR (KAAR-11 adapted to Italian language and culture) has been produced using 52 the cross-cultural adaptation methodology described by Beaton and colleagues.19 Four 53 54 professional translators and two bilingual physicians performed independently three forward 55 and three backward translations of the original Spanish questionnaire. All the translators 56 were naïve to the aims and scopes of the study. An expert committee, composed by primary 57 care physicians, research methodologists, a mental health expert, a university professor for 58 pharmacology, a university professor for microbiology, two university professors for Italian 59 and Spanish language and all the involved translators, reviewed the translations and 60 produced a pre-final version of the questionnaire. A pilot study was carried out by

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1 2 3 administering the pre-final version of ITA-KAAR to an opportunistic sample of the target 4 population (45 GPs working in different regions of Italy). Among these, 2 GPs from the BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 Sardinian Region participated in the pilot study of the cross-cultural adaptation process and 7 will be therefore excluded from the study (axis A). Comments and suggestions of the 8 responders were registered and the necessary amendments to the pre-final version were 9 made to produce the final version of the ITA-KAAR. The detailed process of cross-cultural 10 adaptation and preliminary validation are described elsewhere.20 11 Study Axis B The Regional Health Trust of Sardinia will provide the data of all prescriptions 12 st st 13 of antibiotics for systemic use (ATC J01) filled by GPs between 1 January 2017 and 31 14 December 2019. For each GP and for each year of the study, DDDs and DIDs of the prescribed 15 antibiotics and ESAC quality indicators for outpatient antibiotic use21 will be calculated. 16 The following ESAC quality indicators will be considered: 17  J01_DID: consumption of antibacterials for systemic use (ATC J01) expressed in DID; 18 For peer review only 19  J01C_DID: consumption of penicillins (ATC J01C) expressed in DID; 20  J01D_DID: consumption of cephalosporins (ATC J01D) expressed in DID; 21  J01F_DID: consumption of macrolides, lincosamides and streptogramins (ATC J01F) 22 expressed in DID; 23  J01M_DID: consumption of quinolones (ATC J01M) expressed in DID; 24 25  J01CE_%: consumption of b-lactamase-sensitive penicillins (ATC J01CE) expressed as a 26 percentage; 27  J01CR_%: consumption of combinations of penicillins, including b-lactamase inhibitors 28 (ATC J01CR), expressed as a percentage; 29  J01DD+DE_%: consumption of third- and fourth-generation cephalosporins (ATC 30 31 J01DD+J01DE) expressed as a percentage; 32  J01MA_%: consumption of fluoroquinolones (ATC J01MA) expressed as a percentage; 33  J01_B/N: ratio of the consumption of broad-spectrum (ATC J01CR+J01DC+J01DD+J01F 34 excluded J01FA01) to the consumption of narrow-spectrum penicillins, cephalosporins 35 and macrolides (ATC J01CE+J01DB+J01FA01)] 36 http://bmjopen.bmj.com/ 37  J01_SV: seasonal variation in total antibiotic consumption (ATC J01); 38  J01M_SV: seasonal variation in quinolone consumption (ATC J01M). 39 To take into account the different prevalence of consumption of antibiotics by patient’s age 40 and gender, all the indicators will be calculated on the weighted population (based on the 41 weights set up by the Department of Programming of the Italian Ministry of Health, 42 43 supplementary file 1) of the patients registered in the list of each physician. In particular,

44 patients will be classified in age and gender classes; the number of subjects in each age and on September 23, 2021 by guest. Protected copyright. 45 gender class will be multiplied by the corresponding weight; the sum of the values obtained 46 will be proportionally reported to the regional population. 47 For each physician, a better performance in half plus one of the ESAC quality indicators 48 compared to the median of the region, will be considered as an indicator of adequate quality 49 50 of antibiotic prescriptions (AQPA). 51 52 Statistical analysis. 53 All statistical analysis will be performed using R or MPLUS.22,23 Continuous variables will be 54 described by mean and standard deviation and, in case of asymmetric distributions, the 55 median and interquartile range will be used. Categorical variables will be represented 56 57 through frequency distributions (absolute and percentage values). Comparisons between 58 groups will be made, for continuous variables through the t test (Mann – Whitney U test 59 where necessary), while for categorical variables through the Chi-squared test (Fisher's exact 60 test where necessary). Statistical significance will be expressed in terms of p-values (p≤0.05) and the 95% confidence intervals will be added to the point estimates.

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1 2 3 Study axis A Handling of missing data will be dealt by imputation methods if the percentage 4 of missing values is low (<3% for each item). Otherwise, observations with missing values will BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 be excluded from the analysis. 7 Cronbach's alpha will be used to assess the internal consistency of the total scale. The 8 correlations between the items of the questionnaire will also be examined: items with a 9 correlation lower than 0.30 will be considered for removal from the questionnaire, as well as 10 items whose exclusion leads to an improvement in Cronbach's alpha value of 0.001 or more. 11 To evaluate the test-retest reliability, the Pearson correlation coefficients will be calculated 12 13 between the scores at the first and second administration. Furthermore, the intra-class 14 correlation coefficients (ICC) will be calculated. 15 The factorial structure of the ITA-KAAR will be evaluated through an Exploratory Factor 16 Analysis (EFA), using the MLE estimator. The number of factors to be included in the EFA will 17 be decided after i) evaluation of the number of eigenvalues ≥1, ii) the screenplot and iii) the 18 parallel analysis. TheFor following peer Goodness review of Fit indexes willonly be used to evaluate the different 19 20 models: Tucker-Lewis Index (TLI) ≥0.95 and ≥0.90 indicating a good or sufficient fit 21 respectively and the Root Mean Square Error of Approximation (RMSEA) ≤0.05 or ≤0.08 22 indicating good or sufficient fit respectively. The correlation between factors will be estimated 23 using the Pearson coefficient. Indicators with loadings less than 0.30 will be considered for 24 the removal from the questionnaire. Path diagrams will be used to compare the loadings of 25 each factor. 26 27 To evaluate the known-group validity, the medians of the questionnaire as a whole, for groups 28 of items that explore the same domains and for the single items of the ITA-KAAR for the two 29 groups of opposing doctors will be compared. These groups will be identified as the first and 30 last decile of the percentage of ESAC indicators that, for each doctor, are greater than the 31 reference value (median of the region). 32 33 To determine the ability of the ITA-KAAR in discriminating the prescribers with adequate 34 quality of prescriptions (AQPA=1) from those with inadequate quality of prescriptions 35 (AQPA=0), a ROC analysis will be performed with evaluation of the area under the curve

36 ("Area Under the Curve" AUC). The following scheme will be used for the interpretation of the http://bmjopen.bmj.com/ 37 AUC values: AUC=0.5: no discriminative ability; 0.5

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1 2 3 The calculation of the sample size (number of GPs to be interviewed) was performed on the 4 basis of the results of a previous study26 and a literature review27. Assuming a log-normal BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 distribution, a difference in the medians of each item between the compared groups (AQPA=1 7 vs. AQPA=0) of 0.25 points on the VAS scale and a standard deviation of 0.83 (corresponding 8 to a range of variability of 99% of the values per single item equal to half of the VAS scale), a 9 population of 1200 GPs, a response rate equal to or greater than 40% (N=480) guarantees a 10 power of the association study greater than 80%.28 11 12 13 Patient and public involvement 14 GPs developed the research questions, the overall conception of the project and the present 15 research protocol in collaboration with epidemiologists and public health professionals, in 16 order to gain a better understanding of their own prescribing behaviours. Local medical 17 boards are involved in the dissemination of the ITA-KAAR questionnaire and in a peer-led 18 dissemination of the resultsFor of peer this study. review only 19 20 21 22 ETHICS AND DISSEMINATION. 23 This project has been approved by the Ethics committee of the Regional Health Trust of 24 Sardinia (protocol number 176/2019/CE, 24th September 2019). 25 The results of this study will be disseminated through publications in peer reviewed journals, 26 27 relevant meetings, congresses and teaching sessions addressed to GPs and the public. 28 29 30 DISCUSSION. 31 There are few doubts that AMR is strongly related to antibiotic consumption.4 Prescribing is a 32 33 complex process and, as highlighted by Teixeira in a systematic review of qualitative studies, 13 34 antibiotic prescribing is influenced by multiple determinants. 35 Our study is intended to uncover the relationship between some of the most important

36 hypothesized determinants of antibiotic prescriptions and the quality of prescription itself by http://bmjopen.bmj.com/ 37 using a theoretical framework of antibiotic prescribing behaviour.13 This model considers 38 both, intrinsic and external factors to the healthcare professional that influences antibiotic 39 40 prescription habits of primary care physicians (Figure 1). 41 42 43

44 on September 23, 2021 by guest. Protected copyright. 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3

4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 7 8 9 10 11 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 Fig. 1 Theoretical model of Antibiotic prescribing behaviour of GP, adapted from Teixeira et al.13. Continuous 27 arrows represent factors that are deemed to influence antibiotic prescriptions directly. Dotted arrows represent 28 factors that are deemed do influence antibiotic prescriptions indirectly through the influence of knowledge 29 and/or attitudes. 30 31 Despite the comprehensiveness of the proposed theoretical model, few studies tested it in 32 practice.26,29 Therefore, we have designed a study to fill this lack of knowledge using the 33 widely accepted knowledge, attitudes and practice (KAP) survey methodology to assess the 34 35 educational needs of General Practitioners on AMR and antibiotic prescriptions.

36 The chosen study design has a number of strengths. http://bmjopen.bmj.com/ 37 First, the ITA-KAAR, Italian version of the KAAR-11 questionnaire, which is the only fully 38 validated scale developed to assess knowledge and attitudes of GPs regarding AMR and 39 antibiotic prescriptions, was translated and adapted to Italian using a methodology aimed to 40 19,20 41 maintain the psychometric properties of the original version of the scale and will undergo 42 a full validation study. 43 Secondly, in order to fully validate the ITA-KAAR against an external “gold standard” (known-

44 group validity) and to measure the magnitude of the association between each explanatory on September 23, 2021 by guest. Protected copyright. 45 variable and the quality of antibiotic prescription, we will use a set of valid, reliable and 46 internationally accepted indicators21, calculated using data from clinical practice. This leads to 47 48 further strengths of our study design: (1) they allow comparability to similar studies 49 performed across Europe; (2) their use excludes any opportunistic selection of indicators for 50 the purpose to meet the study objectives. 51 Thirdly, the data source of the drug utilization study (study axis B) is an administrative 52 database containing any antibiotic prescription covered by the NHS, filled by every single GP 53 in the examined period of time. This completeness is a well-known strength of drug utilization 54 30 55 studies performed on large administrative databases. 56 A further strength of the study refers to the estimation methodology that will be used to 57 measure the magnitude of the association between the hypothesized determinants of 58 antibiotic prescriptions and the real prescription data used in this study, namely a 59 multivariate Poisson model with robust estimation of variance. This model is generally 60 preferred to the traditional logistic model in cross-sectional studies when the dependent

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1 2 3 variable is not rare. In fact, in the case of frequent outcomes, typical in cross-sectional studies, 4 the Odds Ratio (OR), obtained from the application of the traditional logistic model, can lead BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 to a strong overestimation of the prevalence ratio and therefore of the magnitude of the 7 association. Moreover, similarly to the multivariate logistic model, the Poisson model 8 produces association measures that are adjusted with respect to the other confounding 9 factors.24 10 Some potential limitations need to be mentioned. 11 First, the response rate to a questionnaire could be low even if a comprehensive data 12 31 13 collection strategy is planned. To minimize non-response bias (a type of selection bias) and 14 exclude the risk that responders differ in meaningful ways from non-responders, a subgroup 15 analysis of responders and non-responders to the questionnaire will be performed in relation 16 to each ESAC indicator. In particular, for both subgroups the percentages of GPs who have 17 shown an AQPA=1 or an AQPA=0 as defined above, will be calculated. In case of differences 18 that do not reach statisticalFor significance peer betweenreview the two onlysubgroups, non-response bias could 19 20 be reasonably excluded. 21 A second limitation could be that the ESAC quality indicators21 used in our study are not 22 developed to consider the underlying reason of the prescription (i.e. the diagnosis). The 23 choice of these indicators above others that take into account the clinical reason for 24 encounter32 was made because data regarding the underlying diagnosis are not available in 25 our setting (GP health records that could be used for research purpose does not exist in the 26 27 region of Sardinia). Nevertheless, we feel that the ESAC quality indicators without the 28 underlying clinical diagnosis21 are appropriate indicators for the purposes of our study. In 29 fact, after adjustment for patients age and gender, we have no reason to believe that the 30 population of patients registered in the list of any single GP differ from each other 31 significantly with respect of the occurrence neither of diseases for which antibiotics are 32 33 currently prescribed in General Practice, nor for other conditions that could act as relevant 34 confounding factors. 35

36 Future perspectives. http://bmjopen.bmj.com/ 37 Considering that 90% of antibiotic prescriptions in human health are filled by GPs, the results 38 of this study will be useful to inform stakeholders on the educational needs and the context 39 40 specific determinants of antibiotic use and will serve the development and implementation of 41 further targeted interventions to reduce antibiotic consumption and prescriptions in the 42 community, namely:33 43 - The design, administration and implementation of a multifaceted intervention targeted 44 to the needs of physicians, as revealed in the first phase of the study. on September 23, 2021 by guest. Protected copyright. 45 - The assessment, in a prospective design, of the impact of this intervention on reducing 46 47 antibiotic prescriptions. 48 49 Due to the fact that determinants of inappropriate use of antibiotics are context-specific, the 50 overall aim of the “Broad spectrum” project is to create a methodological framework to be 51 applied in other Italian and European regions to tackle inappropriate antibiotic use, thereby 52 reducing and preventing the spread of antibiotic resistance. 53 54 55 SUPPLEMENTARY FILES. 56 Supplementary file 1 57 58 59 ACKNOWLEDGMENTS. This project is funded by a grant from the Foundation of Sardinia and is conducted 60 within a scientific collaboration between the Italian National Institute of Health and the Department of Medical

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1 2 3 Sciences and Public Health of the University of Cagliari (Resolution of Italian National Institute of Health 17-12-

4 2019). BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 The authors thank Micaela Morelli, vice-president of the University of Cagliari, for her substantial contribution in 6 fostering the “Broad Spectrum” project at an institutional level. 7 The authors thank Noel Baxter (GP, Southwark, London, UK) for his critical revision of this work. 8 9 AUTHOR CONTRIBUTIONS. PKK, AS and MN developed the research question. PKK and AS designed, together 10 with the substantial contribution of SSA, MarMas, RDC, VF, AF and MFM, the overall conception of the project. 11 PKK wrote the protocol and, together with AS the project proposal. PKK and AS, in collaboration with SSA, 12 MarMas, RDC, wrote the first draft of the manuscript. All authors red the manuscript, made relevant critiques 13 and amendments and approved the final draft. 14 PKK, AS, VF, FC, MauMar and MatMas will collect data. MarMas, SSA, RDC, MFM and PKK will perform data 15 analysis. 16 17 FUNDING. Public Health, Preventive Medicine and Rehabilitation Grant programme (Foundation of Sardinia, 18 Grant n. 30718). For peer review only 19 20 DISCLAIMER. The views expressed are those of the authors are not necessarily those of the Italian National 21 Institute of Health, the University of Cagliari, the University of Santiago de Compostela, the Columbia University 22 or the Italian Secretariat of physician scientists. 23 24 COMPETING INTERESTS. None declared. 25 26 ETHICS APPROVAL. Ethics committee of the Regional Health Trust of Sardinia (protocol number 176/2019/CE, 27 24th September 2019) 28 29 PROVENANCE AND PEER REVIEW. Not commissioned; externally peer reviewed. 30 DATA SHARING STATEMENT. Principal investigator (PKK) will have direct access to the full data set. Since data 31 are anonymised, data are blinded of any identifying information. Anonymised and aggregated data will be stored 32 on password-protected computers at the University of Cagliari and the Italian National Institute of Health. 33 Communication between researchers which might involve confidential data will be performed using password- 34 protected emails. Full study protocol will be made publicly available; however, no public access will be granted 35 to data set or statistical code.

36 http://bmjopen.bmj.com/ 37 38 REFERENCES. 39 40 1. ECDC/EMEA Joint Technical Report. The Bacterial Challenge: Time To React. 2009. 41 Available on: https://ecdc.europa.eu/en/publications-data/ecdcemea-joint-technical-report- 42 bacterial-challenge-time-react. 43 2. European Commission . A European One Health Action Plan against Antimicrobial 44 Resistance (AMR). 2017. Available on: on September 23, 2021 by guest. Protected copyright. 45 46 https://ec.europa.eu/health/amr/sites/amr/files/amr_action_plan_2017_en.pdf. 47 3. Cassini A, Hogberg LD, Plachouras D, et al. Attributable deaths and disability-adjusted 48 life-years caused by infections with antibiotic-resistant bacteria in the EU and the European 49 Economic Area in 2015: a population-level modelling analysis. Lancet Infect Dis 2019; 19(1): 50 56-66. 51 4. Bell BG, Schellevis F, Stobberingh E, Goossens H, Pringle M. A systematic review and 52 53 meta-analysis of the effects of antibiotic consumption on antibiotic resistance. BMC Infect Dis 54 2014; 14: 13. 55 5. Shallcross LJ, Davies DS. Antibiotic overuse: a key driver of antimicrobial resistance. Br 56 J Gen Pract 2014; 64(629): 604-5. 57 6. European Centre for Disease Prevention and Control. Antimicrobial consumption 58 surveillance in Europe 2018. Annual report of the European Antimicrobial Consumption 59 60 Surveillance Network (ESAC-Net). Stockholm: ECDC; 2019.

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1 2 3 7. Osservatorio Nazionale sull’impiego dei Medicinali. L’uso degli an bio ci in Italia. 4 Rapporto Nazionale 2018. Roma: Agenzia Italiana del Farmaco, 2019. BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 8. Ciofi Degli Atti ML, Massari M, Bella A, et al. Clinical, social and relational determinants 7 of paediatric ambulatory drug prescriptions due to respiratory tract infections in Italy. 2006. 8 9. Harbarth S, Monnet DL. Cultural and socioeconomic determinants of antibiotic use. 9 2005. 10 10. Masiero G, Filippini M, Ferech M, Goossens H. Socioeconomic determinants of 11 outpatient antibiotic use in Europe. 2010. 12 13 11. Touboul-Lundgren P, Jensen S, Drai J, Lindbaek M. Identification of cultural 14 determinants of antibiotic use cited in primary care in Europe: a mixed research synthesis 15 study of integrated design "Culture is all around us". BMC Public Health 2015; 15: 908. 16 12. Giusti A, Spila Alegiani S, Ciofi degli Atti ML, et al. Surgical antibiotic prophylaxis in 17 children: A mixed method study on healthcare professionals attitudes. BMC Pediatr 2016; 18 16(1). For peer review only 19 20 13. Teixeira Rodrigues A, Roque F, Falcão A, Figueiras A, Herdeiro MT. Understanding 21 physician antibiotic prescribing behaviour: a systematic review of qualitative studies. 22 International Journal of Antimicrobial Agents 2013; 41(3): 203-12. 23 14. López-Vázquez P, Vázquez-Lago JM, Gonzalez-Gonzalez C, et al. Development and 24 validation of the knowledge and attitudes regarding antibiotics and resistance (KAAR-11) 25 questionnaire for primary care physicians. Journal of Antimicrobial Chemotherapy 2016; 26 27 71(10): 2972-9. 28 15. Accordo Collettivo Nazionale per la disciplina dei rapporti con i medici di medicina 29 generale ai sensi dell'art.8 del D.Lgs. n. 502 del 1992 e successive modificazioni e integrazioni. 30 2018. 31 16. ISTAT - Direzione centrale per le statistiche e le indagini sulle istituzioni sociali, 32 33 Popolazione residente al 1° gennaio 2019. Available on: http://demo.istat.it. 34 17. Ebert JF, Huibers L, Christensen B, Christensen MB. Paper- or Web-Based 35 Questionnaire Invitations as a Method for Data Collection: Cross-Sectional Comparative Study

36 of Differences in Response Rate, Completeness of Data, and Financial Cost. J Med Internet Res http://bmjopen.bmj.com/ 37 2018; 20(1): e24-e. 38 18. Teixeira Rodrigues A, Ferreira M, Roque F, et al. Physicians' attitudes and knowledge 39 40 concerning antibiotic prescription and resistance: questionnaire development and reliability. 41 BMC Infect Dis 2016; 16: 7. 42 19. Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross- 43 cultural adaptation of self-report measures. Spine (Phila Pa 1976) 2000; 25(24): 3186-91. 44 20. Kurotschka PK, Moro MF, Demurtas J, Serafini A. General practitioners knowledge and on September 23, 2021 by guest. Protected copyright. 45 attitudes about antibiotics and prescriptions: cross-cultural adaptation and preliminary 46 47 Italian validation of kaar-11 questionnaire. Recenti Prog Med 2020; 111: in press. 48 21. Coenen S, Ferech M, Haaijer-Ruskamp FM, et al. European Surveillance of Antimicrobial 49 Consumption (ESAC): quality indicators for outpatient antibiotic use in Europe. Qual Saf 50 Health Care 2007; 16(6): 440-5. 51 22. R Core Team (2019). R: A language and environment for statistical computing. R 52 Foundation for Statistical Computing V, Austria. , https://www.R-project.org/. Ao. 53 54 23. Muthén LK & Muthén BO. Mplus User's Guide. Sixth Edition. Los Angeles C-. 55 24. Barros AJD, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: 56 an empirical comparison of models that directly estimate the prevalence ratio. BMC Medical 57 Research Methodology 2003; 3(1): 21. 58 25. Sakamoto Y. IM, Kitagawa G. Akaike information criterion statistics, 1986, New York, 59 Springer. 60

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1 2 3 26. Gonzalez-Gonzalez C, Lopez-Vazquez P, Vazquez-Lago JM, et al. Effect of Physicians' 4 Attitudes and Knowledge on the Quality of Antibiotic Prescription: A Cohort Study. PLoS One BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 2015; 10(10): e0141820. 7 27. Anthoine E, Moret L, Regnault A, Sebille V, Hardouin JB. Sample size used to validate a 8 scale: a review of publications on newly-developed patient reported outcomes measures. 9 Health Qual Life Outcomes 2014; 12: 176. 10 28. O'Keeffe AG, Ambler G, Barber JA. Sample size calculations based on a difference in 11 medians for positively skewed outcomes in health care studies. BMC medical research 12 13 methodology 2017; 17(1): 157-. 14 29. Liu C, Liu C, Wang D, Zhang X. Intrinsic and external determinants of antibiotic 15 prescribing: A multi-level path analysis of primary care prescriptions in Hubei, China. 2019. 16 30. Latry P, Molimard M, Bégaud B, Martin-Latry K. How reimbursement databases can be 17 used to support drug utilisation studies: example using the main French national health 18 insurance system database.For Eur peer J Clin Pharmacol review 2010; 66 (7):only 743-8. 19 20 31. Aitken C, Power R, Dwyer R. A very low response rate in an on-line survey of medical 21 practitioners. Australian and New Zealand Journal of Public Health 2008; 32(3): 288-9. 22 32. Adriaenssens N, Coenen S, Tonkin-Crine S, et al. European Surveillance of 23 Antimicrobial Consumption (ESAC): disease-specific quality indicators for outpatient 24 antibiotic prescribing. BMJ Qual Saf 2011; 20(9): 764-72. 25 33. Teixeira Rodrigues A, Roque F, Pineiro-Lamas M, Falcao A, Figueiras A, Herdeiro MT. 26 27 Effectiveness of an intervention to improve antibiotic-prescribing behaviour in primary care: 28 a controlled, interrupted time-series study. Journal of Antimicrobial Chemotherapy 2019; 30: 29 30. 30 31 Alice Serafini ([email protected]) 32 33 Marco Massari ([email protected]) 34 Roberto Da Cas ([email protected]) 35 Adolfo Figueiras ([email protected])

36 Viviana Forte ([email protected]) http://bmjopen.bmj.com/ 37 Maria Francesca Moro ([email protected]) 38 Luigi Minerba ([email protected]) 39 40 Matteo Massidda ([email protected]) 41 Federico Contu ([email protected]) 42 Maurizio Marcias ([email protected]) 43 Marco Nardelli ([email protected]) 44 Alessandra Perra ([email protected]) on September 23, 2021 by guest. Protected copyright. 45 Mauro Giovanni Carta ([email protected]) 46 47 Stefania Spila Alegiani ([email protected]) 48 49 50 51 52 53 54 55 56 57 58 59 60

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The Broad Spectrum Project. Factors determining the quality of antibiotic use in primary care: an observational study protocol from Italy. ForJournal: peerBMJ Open review only Manuscript ID bmjopen-2020-038843.R1

Article Type: Protocol

Date Submitted by the 08-May-2020 Author:

Complete List of Authors: Kurotschka, Peter; University of Cagliari, Department of Medical Science and Public Health; Istituto Superiore di Sanita, National Centre for pre- clinical and clinical drug research and surveillance (CNRVF) Serafini, Alice; General Practitioner in training, Local Health Trust Modena Massari, Marco; Istituto Superiore di Sanita, National Centre for pre- clinical and clinical drug research and surveillance (CNRVF) Da Cas, Roberto; Istituto Superiore di Sanita, National Centre for pre- clinical and clinical drug research and surveillance (CNRVF) Figueiras, Adolfo; Universidade de Santiago de Compostela, Department of Preventive Medicine and Public Health

Forte, Viviana; General Practitioner, Regional Health Trust, Sardinia, http://bmjopen.bmj.com/ Italy Moro, Maria Francesca; Columbia University Mailman School of Public Health Massidda, Matteo; General Practitioner in training, Regional Health Trust, Sardinia, Italy Contu, Federico; General Practitioner in training, Regional Health Trust, Sardinia, Italy Minerba, Luigi; University of Cagliari, Department of Medical Science and

Public Health on September 23, 2021 by guest. Protected copyright. Marcias, Maurizio; Health Technology Assessment Unit - Regional Health Trust of Sardinia Nardelli, Marco; Tower Hamlets Primary Care Trust, Brayford Square Surgery Perra, Alessandra; University of Cagliari, Department of Medical Science and Public Health Carta, M; University of Cagliari, Department of Medical Science and Public Health Spila Alegiani, Stefania; Istituto Superiore di Sanita, National Centre for pre-clinical and clinical drug research and surveillance (CNRVF)

Primary Subject General practice / Family practice Heading:

Secondary Subject Heading: Epidemiology, Public health, Evidence based practice

PRIMARY CARE, PUBLIC HEALTH, Quality in health care < HEALTH Keywords: SERVICES ADMINISTRATION & MANAGEMENT, EPIDEMIOLOGY, EDUCATION & TRAINING (see Medical Education & Training),

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1 2 3 The Broad Spectrum project.

4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Factors determining the quality of antibiotic use in primary care: an 6 7 observational study protocol from Italy 8 9 Peter Konstantin Kurotschka1,2,3* & Alice Serafini4*, Marco Massari 5, Roberto Da Cas 5, Adolfo 10 Figueiras6, Viviana Forte3,7, Maria Francesca Moro8, Matteo Massidda2,3, Federico Contu2,3, Luigi 11 1 9 10 1 1 12 Minerba , Maurizio Marcias , Marco Nardelli , Alessandra Perra , Mauro Giovanni Carta **, Stefania 13 Spila Alegiani5** 14 15 * Contributed equally (shared first authorship) 16 17 ** Contributed equally (shared last authorship) 18 For peer review only 19 1 Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy 20 2 General Practitioner in training, Regional Health Trust, Sardinia, Italy 21 3 Italian Secretariat of Physician Scientists – SIMeR (SIGM), Italy 22 4 General Practitioner in training, Local Health Trust Modena, Emilia-Romagna, Italy 23 5 Italian National Institute of Health, National Centre for pre-clinical and clinical drug research and surveillance 24 (CNRVF), Rome, Italy 25 6 Department of Preventive Medicine and Public Health, University of Santiago de Compostela, Consortium for 26 Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), 27 Santiago de Compostela, Spain 28 7 General Practitioner, Regional Health Trust, Sardinia, Italy 29 8 Mailman School of Public Health, Columbia University, New York City, USA 30 9 Health Technology Assessment Unit - Regional Health Trust, Sardinia, Italy 31 10 General Practitioner, Tower Hamlets Primary Care Trust, Brayford Square Surgery, London, United Kingdom 32 33 Correspondence to: 34 Peter Konstantin Kurotschka 35 Via Genovesi 34, 09124 Cagliari

36 E-Mail [email protected] http://bmjopen.bmj.com/ 37 Phone +393924712115 38 39 KEYWORDS: antibiotic, prescription, general practice, family medicine, appropriate, use, consumption, 40 questionnaire, knowledge, attitudes, factors, determinants. 41 42 WORD COUNT: 4000 43

44 ABSTRACT on September 23, 2021 by guest. Protected copyright. 45 Introduction. The overuse of antibiotics is causing worldwide spread of antimicrobial 46 resistance (AMR). Compared to other countries, Italy has both high antibiotic consumption 47 48 rates and high rates of AMR. 49 Due to the fact that around 90% of antibiotics are prescribed by General Practitioners (GPs), 50 this study aims to measure the impact of knowledge, attitudes and socio-demographic and 51 workplace related factors on the quality of antibiotic prescriptions filled by GPs in the Italian 52 Region of Sardinia. 53 Methods and analysis. Knowledge, attitude, socio-demographic and workplace-related 54 55 factors deemed to influence physicians prescribing behaviour will be evaluated in a cross- 56 sectional study conducted among all GPs of the Italian Region of Sardinia (n~1200). A 57 knowledge and attitudes questionnaire (ITA-KAAR) accompanied by a socio-demographic 58 form will be linked to drug prescription data reimbursed by the National Health System 59 (NHS). European Surveillance of antibiotic Consumption (ESAC) quality indicators for 60 outpatient antibiotic use will be calculated from drug prescription records. Every GP will be

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1 2 3 deemed to have demonstrated an adequate quality of prescriptions of antibiotics (AQPA) if 4 half of the indicator score plus one is better than the median of the region. A multivariate BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 Poisson regression model with robust variance estimation will be used to evaluate the impact 7 of the determinants of antibiotic prescriptions on the actual prescribing quality of each 8 physician. 9 Ethics and dissemination. The project has been approved by the ethics committee of the 10 Regional Health Trust of Sardinia (176/2019/CE, 24th September 2019). The results will be 11 useful to inform evidence-based interventions to tackle irrational antibiotic use in the 12 13 community. 14 15 16 STRENGTHS AND LIMITATIONS OF THIS STUDY. 17 - The use of internationally accepted indicators of antibiotic consumption developed by 18 ESAC-net and Forthe comprehensiveness peer review of the data source only selected to perform this study 19 20 allows comparability to similar studies performed across Europe and enhances 21 external validity of the results. 22 - The questionnaire that will be used to assess factors deemed to influence antibiotic 23 prescribing practices of GPs is the cross-cultural adaptation of a fully validated scale in 24 Spanish language and the adapted version will undergo a full validation study to 25 maintain the psychometric properties of the original version of the scale. 26 27 - The main limitation of the study is that no clinical data about the reason for the 28 encounter resulting in an antibiotic prescription is available 29 - This limitation is addressed by the use, on the weighted population of each physician, 30 of the ESAC quality indicators, specifically developed and validated to be used on 31 administrative databases; furthermore, the use of this indicators will avoid bias 32 33 resulting from inaccurate registration of the reason for the encounter. 34 35

36 INTRODUCTION http://bmjopen.bmj.com/ 37 Antimicrobial resistance (AMR) has emerged, alongside climate change, as a global threat to 38 public health and wealth.1 Every year in Europe 33,000 people die due to infections caused by 39 40 resistant bacteria and, globally approximately 700,000 cases of such infections occur every 2,3 41 year. According to current estimates, AMR is causing an excess of healthcare system costs 42 up to 1 billion US dollars (USD) and a loss of gross domestic product (GDP) of 3 trillion USD 43 per year.4 By 2050, antimicrobial resistant bacteria will cause more then 10 million deaths 44 each year and a global loss of GDP of more than 100 trillion USD.5 on September 23, 2021 by guest. Protected copyright. 45 The overuse of antibiotics is one of the main drivers of AMR, but on a global scale antibiotic 46 6-9 47 use is still rising. Italy has a higher consumption rate of antibiotics compared to many other 10 48 European countries. In 2018 the annual consumption rate of Italian hospital and primary 49 care sectors combined was 21.4 Defined Daily Doses (DDDs) / 1000 inhabitants / day (DIDs) 50 and the vast majority of antibiotic prescriptions (i.e. 90%, 19 DIDs) are filled by General 51 Practitioners (GPs). Aggregated level data show that there is a high variability of antibiotic 52 prescription rates among different regions of the country and a high variability of antibiotic 53 11 54 prescription rates in different seasons of the year, with highest rates occurring in flu season. 55 The finding of a strong seasonal variability seems to be consistent with previous studies that 56 showed that, in General Practice, the majority of antibiotics are prescribed for acute 57 respiratory infections (ARIs), such as acute bronchitis, otitis media, sinusitis or pharyngitis. In 58 these conditions, according to guidelines, antibiotics are not routinely recommended and 59 often inappropriately prescribed. 12,13 60

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1 2 3 Moreover, the consumption of broad-spectrum antibiotics is approximately twice as high as in 4 other European countries like Norway, Sweden or the United Kingdom.10 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 For all these reasons it seems to be very likely that the majority of antibiotic prescriptions in 7 Italy could be avoided. Both, qualitative and quantitative methodologies have been used in 8 different settings of low-, middle- and high-income countries to understand the determinants 9 of antibiotic overuse.14-19 Prescribing, especially antibiotic prescribing, is a complex 10 behaviour, with intrinsic factors (socio-demographic variables, knowledge, attitudes) and 11 extrinsic factors (signs and symptoms at presentations, comorbidity, socio-demographic 12 13 variables, workload, influence of pharmaceutical companies, cost saving) that impact the 20 14 healthcare professional decision. Therefore, to inform stakeholders (GPs, European and 15 national agencies, scientific societies) in the development of effective interventions to tackle 16 irrational antibiotic use, an understanding of the context specific determinants of antibiotic 17 prescription is needed.20,21 18 GPs have a key roleFor in Italy’s peer National review Health System (NHS).only Virtually all of the resident 19 20 population is compulsorily registered on a GP list and a pharmaceutical prescription can be 21 charged to the NHS only if filled by a GP or a specialist consultant working directly for the 22 NHS. Consequently, taking into consideration that in public healthcare systems GPs act as 23 pharmaceutical gatekeepers, they could play an active role in tackling the phenomenon of 24 antibiotic overuse and non-evidence-based prescription habits.22 25 At the best of our knowledge, there are no published studies that measure, with validated 26 27 tools, the knowledge and attitudes of GPs on AMR and antibiotic prescriptions in Italy. 28 Moreover, we were not able to retrieve any study that evaluated the influence of knowledge 29 and attitudes of GPs on their prescriptions of antibiotics in our settings. 30 Findings of this study will be useful to develop evidence-based physician-targeted 31 interventions to improve the quality of antibiotic prescriptions among Italian GPs. Moreover, 32 33 this study could serve as a generalizable methodological framework to gain an understanding 34 of GPs prescription practices and, therefore, to develop effective interventions to foster good 35 clinical practice in primary care.

36 http://bmjopen.bmj.com/ 37 38 AIMS and OBJECTIVES 39 40 The study will be divided into two distinct but related parts: Study axis A and Study axis B. 41 Study axis A AIM. To describe the attitudes and knowledge of GPs regarding AMR and 42 antibiotic prescriptions by administering a questionnaire adapted from Spanish to Italian 43 language (ITA-KAAR).23 44 OBJECTIVES on September 23, 2021 by guest. Protected copyright. 45 1. Measure the attitudes and knowledge of GPs through the administration of the ITA- 46 47 KAAR questionnaire. 48 2. Describe the characteristics and working context of GPs by filling a socio-demographic 49 form. 50 3. Evaluate the reliability and validity of the ITA-KAAR questionnaire. 51 Study axis B AIM. To describe the quantity, pharmacological classes, appropriateness and 52 inter-individual variability of GPs prescriptions of antibiotics in the Italian region of Sardinia 53 54 and to investigate the determinants of inappropriate prescriptions. 55 OBJECTIVES 56 1. Evaluate GPs antibiotic prescribing behaviour (quantity, pharmacological class, 57 appropriateness, inter-individual variability) through the analysis of prescription data 58 of antibiotics for systemic use recorded in the administrative database of the Regional 59 Health Trust of Sardinia (ATS Sardegna). 60

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1 2 3 2. Evaluate the association between the determinants of GPs prescribing behavior 4 (demographic factors, work environment, territorial context, attitudes and knowledge BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 regarding antibiotic resistance, resulting from the objectives A1 and A2) and the 7 appropriateness of antibiotic prescriptions (resulting from the objective B1). 8 9 10 METHODS AND ANALYSIS 11 Study design 12 13 A cross-sectional study will be carried out for both study axis A and study axis B. 14 Study axis A An attitudes and knowledge questionnaire (ITA-KAAR) and a socio-demographic 15 form will be administered to all GPs working in the Italian region of Sardinia, to measure 16 attitudes, knowledge and socio-demographic factors deemed to be related to AMR and 17 antibiotic prescriptions. 18 Study axis B A drug Forutilization peer study will review be conducted toonly evaluate the prescriptions and the 19 20 appropriateness of antibiotic choice for systemic use of all Sardinian GPs and to investigate 21 the influence of determinants of inappropriate prescription. 22 23 Study Population and setting 24 All residents of the Sardinia Region are covered by the NHS, which provides comprehensive 25 hospital and outpatient care for those registered with a GP. GPs provide primary care for the 26 27 whole temporarily or permanently resident population and a pharmaceutical prescription 28 must be filled by a GP or a specialist consultant to be charged to the NHS .24 29 Study axis A The entire Sardinian GP workforce (n~1200), providing care to 1,639,591 30 Sardinian inhabitants at the date of 1st January 2019, will be recruited.25 The ITA-KAAR 31 questionnaire and a socio-demographic form will be filled by all GPs included in the study 32 33 through an online platform. 34 Study axis B All prescriptions of antibiotics for systemic use (Anatomical Therapeutic 35 Classification – ATC J01) filled by Sardinian GPs will be extracted from the pharmaceutical

36 database of the Regional Health Trust of Sardinia during the period 2017-2019. The database http://bmjopen.bmj.com/ 37 contains all prescriptions covered by the NHS and is regularly updated. 38 39 40 Outcome and Covariates assessment 41 Study axis A The knowledge and attitudes section of ITA-KAAR measures, by means of a 42 Visual Analogue Scale (VAS), some of the GPs attitudes on AMR and antibiotic prescriptions, 43 namely lack of knowledge, fear, external responsibility and complaisance to patient’s 44 demands and expectations. The 7-item accessorial section of the questionnaire focuses on on September 23, 2021 by guest. Protected copyright. 45 some of the main information sources for good clinical practice deemed to be relevant for GPs. 46 47 The questionnaire, including an additional section assessing socio-demographic and work- 48 context related factors potentially associated with the appropriateness of antibiotic use, will 49 be sent through an online platform via E-mail to all GPs of the region of Sardinia. Reminders 50 will be sent to non-responders every 10-14 days. The first 100 responders will be asked to 51 complete the questionnaire a second time after 10-14 days (test-retest reliability). After this 52 first phase of data collection, in case of low response rate, a comprehensive stepwise 53 54 approach (including phone calls, postal reminders, reminders at continuous medical 55 education events, involvement of locally known network leaders, professional associations 56 and the state medical boards) will be used to achieve an acceptable response rate (see 57 “sample size” below).26 58 The KAAR-11 questionnaire has shown to be a reliable and valid instrument to assess 59 attitudes and knowledge of GPs on AMR and antibiotic prescriptions. The questionnaire was 60

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1 2 3 developed taking into account the findings of a literature review and a qualitative focus group 4 study.20,27 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 The ITA-KAAR (KAAR-11 adapted to Italian language and culture, table 1) has been produced 28 7 using the cross-cultural adaptation methodology described by Beaton and colleagues. 8 9 10 ITA-KAAR 11 questionnaire 11 12 Knowledge and Attitudes regarding Antibiotic prescriptions and 13 Resistance 14 15 1. Antibiotic resistance is a major public health problem in our 16 setting 17 18 2. InFor primary peer care it is usefulreview to wait for only microbiology results 19 before treating infectious diseases. 20 3. Prescribing an antibiotic to a patient does not influence the 21 development of resistance. 22 23 4. New antibiotics will be developed to solve the problem of 24 resistance. 25 5. The use of antibiotics in animals is a major cause of the 26 occurrence of new resistance. 27 28 6. When in doubt, it is better to ensure that a patient is cured of an 29 infection by using a broad-spectrum antibiotic. 30 7. I often prescribe antibiotics because it is impossible to track the 31 patient accurately. 32 33 8. When in doubt as to whether a patient has a bacterial disease, it 34 is best to prescribe an antibiotic. 35 9. I often prescribe antibiotics because patients ask me for them 36 10. If a patient believes that he needs an antibiotic and the doctor http://bmjopen.bmj.com/ 37 38 does not prescribe it, he will get it at the pharmacy without a 39 prescription. 40 11. Amoxicillin is useful for resolving most respiratory infections in 41 primary care. 42 43

44 on September 23, 2021 by guest. Protected copyright. 45 Table 1: ITA-KAAR questionnaire, main section exploring physician 46 knowledge and attitudes (translated in English by authors) 47 48 49 50 51 Four professional translators and two bilingual physicians performed independently three 52 forward and three backward translations of the original Spanish questionnaire. All the 53 translators were naïve to the aims and scopes of the study. An expert committee, composed 54 by primary care physicians, research methodologists, a mental health expert, a university 55 56 professor for pharmacology, a university professor for microbiology, two university 57 professors for Italian and Spanish language and all the involved translators, reviewed the 58 translations and produced a pre-final version of the questionnaire. A pilot study was carried 59 out by administering the pre-final version of ITA-KAAR to an opportunistic sample of the 60 target population (45 GPs working in different regions of Italy). Among these, 2 GPs from the Sardinian Region participated in the pilot study of the cross-cultural adaptation process and

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1 2 3 will be therefore excluded from the study (axis A). Comments and suggestions of the 4 responders were registered and the necessary amendments to the pre-final version were BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 made to produce the final version of the ITA-KAAR. The detailed process of cross-cultural 29 7 adaptation and preliminary validation are described elsewhere. 8 An English version of ITA-KAAR and the socio-demographic form is provided in 9 supplementary file 1. 10 Study Axis B The Regional Health Trust of Sardinia will provide the data of all prescriptions 11 of antibiotics for systemic use (ATC J01) filled by GPs between 1st January 2017 and 31st 12 13 December 2019. For each GP and for each year of the study, DDDs and DIDs of the prescribed 30 14 antibiotics and ESAC quality indicators for outpatient antibiotic use will be calculated. 15 The following ESAC quality indicators will be considered: 16  J01_DID: consumption of antibacterials for systemic use (ATC J01) expressed in DID; 17  J01C_DID: consumption of penicillins (ATC J01C) expressed in DID; 18 For peer review only 19  J01D_DID: consumption of cephalosporins (ATC J01D) expressed in DID; 20  J01F_DID: consumption of macrolides, lincosamides and streptogramins (ATC J01F) 21 expressed in DID; 22  J01M_DID: consumption of quinolones (ATC J01M) expressed in DID; 23  J01CE_%: consumption of b-lactamase-sensitive penicillins (ATC J01CE) expressed as a 24 25 percentage; 26  J01CR_%: consumption of combinations of penicillins, including b-lactamase inhibitors 27 (ATC J01CR), expressed as a percentage; 28  J01DD+DE_%: consumption of third- and fourth generation cephalosporins (ATC 29 J01DD+J01DE) expressed as a percentage; 30 31  J01MA_%: consumption of fluoroquinolones (ATC J01MA) expressed as a percentage; 32  J01_B/N: ratio of the consumption of broad-spectrum (ATC J01CR+J01DC+J01DD+J01F 33 excluded J01FA01) to the consumption of narrow spectrum penicillins, cephalosporins 34 and macrolides (ATC J01CE+J01DB+J01FA01)] 35  J01_SV: seasonal variation in total antibiotic consumption (ATC J01); 36 http://bmjopen.bmj.com/ 37  J01M_SV: seasonal variation in quinolone consumption (ATC J01M). 38 To take into account the different prevalence of consumption of antibiotics by patient’s age 39 and gender, all the indicators will be calculated on the weighted population (based on the 40 weights set up by the Department of Programming of the Italian Ministry of Health, 41 supplementary file 2) of the patients registered in the list of each physician. In particular, 42 43 patients will be classified in age and gender classes; the number of subjects in each age and

44 gender class will be multiplied by the corresponding weight; the sum of the values obtained on September 23, 2021 by guest. Protected copyright. 45 will be proportionally reported to the regional population. 46 For each physician, a better performance in half plus one of the ESAC quality indicators 47 compared to the median of the region, will be considered as an indicator of adequate quality 48 of antibiotic prescriptions (AQPA). 49 50 In order to better describe the variability of antibiotic prescribing behaviour of the study 51 subjects in terms of use of first- and second-line drugs, for each GP and for each year of the 52 study, prescriptions of antibiotics for systemic use (ATC J01) will be classified in the three 53 groups of the WHO Essential Medicines List Access, Watch, and Reserve (AWaRe) 54 classification.31 55 For the correspondence between ATC and WHO Essential Medicines List Access, Watch, and 56 57 Reserve (AWaRe) classification see supplementary file 3. 58 59 Statistical analysis. 60 All statistical analysis will be performed using R or MPLUS.32,33 Continuous variables will be described by mean and standard deviation and, in case of asymmetric distributions, the

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1 2 3 median and interquartile range will be used. Categorical variables will be represented 4 through frequency distributions (absolute and percentage values). Comparisons between BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 groups will be made, for continuous variables through the t test (Mann – Whitney U test 7 where necessary), while for categorical variables through the Chi-squared test (Fisher's exact 8 test where necessary). Statistical significance will be expressed in terms of p-values (p≤0.05) 9 and the 95% confidence intervals will be added to the point estimates. 10 Study axis A Handling of missing data will be dealt by imputation methods if the percentage 11 of missing values is low (<3% for each item). Otherwise, observations with missing values will 12 13 be excluded from the analysis. 14 Cronbach's alpha will be used to assess the internal consistency of the total scale. The 15 correlations between the items of the questionnaire will also be examined: items with a 16 correlation lower than 0.30 will be considered for removal from the questionnaire, as well as 17 items whose exclusion leads to an improvement in Cronbach's alpha value of 0.001 or more. 18 To evaluate the test-retestFor reliability, peer the Pearsonreview correlation only coefficients will be calculated 19 20 between the scores at the first and second administration. Furthermore, the intra-class 21 correlation coefficients (ICC) will be calculated. 22 The factorial structure of the ITA-KAAR will be evaluated through an Exploratory Factor 23 Analysis (EFA), using the MLE estimator. The number of factors to be included in the EFA will 24 be decided after i) evaluation of the number of eigenvalues ≥1, ii) the screenplot and iii) the 25 parallel analysis. The following Goodness of Fit indexes will be used to evaluate the different 26 27 models: Tucker-Lewis Index (TLI) ≥0.95 and ≥0.90 indicating a good or sufficient fit 28 respectively and the Root Mean Square Error of Approximation (RMSEA) ≤0.05 or ≤0.08 29 indicating good or sufficient fit respectively. The correlation between factors will be estimated 30 using the Pearson coefficient. Indicators with loadings less than 0.30 will be considered for 31 the removal from the questionnaire. Path diagrams will be used to compare the loadings of 32 33 each factor. 34 To evaluate the known-group validity, the medians of the questionnaire as a whole, for groups 35 of items that explore the same domains and for the single items of the ITA-KAAR for the two

36 groups of opposing doctors will be compared. These groups will be identified as the first and http://bmjopen.bmj.com/ 37 last decile of the percentage of ESAC indicators that, for each doctor, are greater than the 38 reference value (median of the region). 39 40 To determine the ability of the ITA-KAAR in discriminating the prescribers with adequate 41 quality of prescriptions (AQPA=1) from those with inadequate quality of prescriptions 42 (AQPA=0), a ROC analysis will be performed with evaluation of the area under the curve 43 ("Area Under the Curve" AUC). The following scheme will be used for the interpretation of the 44 AUC values: AUC=0.5: no discriminative ability; 0.5

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1 2 3 The variables associated with the outcome in the univariate analysis (p<0.10) will be 4 considered eligible for inclusion in the multivariate model. The final model will be obtained BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 through a stepwise forward selection method with a stopping rule based on the Akaike 35 7 Information Criterion (AIC). 8 9 Sample size 10 The calculation of the sample size (number of GPs to be interviewed) was performed on the 11 basis of the results of a previous study36 and a literature review37. Assuming a log-normal 12 13 distribution, a difference in the medians of each item between the compared groups (AQPA=1 14 vs. AQPA=0) of 0.25 points on the VAS scale and a standard deviation of 0.83 (corresponding 15 to a range of variability of 99% of the values per single item equal to half of the VAS scale), a 16 population of 1200 GPs, a response rate equal to or greater than 40% (N=480) guarantees a 17 power of the association study greater than 80%.38 18 For peer review only 19 20 Patient and public involvement 21 GPs developed the research questions, the overall conception of the project and the present 22 research protocol in collaboration with epidemiologists and public health professionals, in 23 order to gain a better understanding of their own prescribing behaviours. Local medical 24 boards are involved in the dissemination of the ITA-KAAR questionnaire and in a peer-led 25 dissemination of the results of this study. 26 27 28 29 ETHICS AND DISSEMINATION. 30 This project has been approved by the Ethics committee of the Regional Health Trust of 31 Sardinia (protocol number 176/2019/CE, 24th September 2019). 32 33 The results of this study will be disseminated through publications in peer reviewed journals, 34 relevant meetings, congresses and teaching sessions addressed to GPs and the public. 35

36 http://bmjopen.bmj.com/ 37 DISCUSSION. 38 There are few doubts that AMR is strongly related to antibiotic consumption.6 Prescribing is a 39 40 complex process and, as highlighted by Teixeira in a systematic review of qualitative studies, 20 41 antibiotic prescribing is influenced by multiple determinants. 42 Our study is intended to uncover the relationship between some of the most important 43 hypothesized determinants of antibiotic prescriptions and the quality of prescription itself by 44 using a theoretical framework of antibiotic prescribing behaviour.20 This model considers on September 23, 2021 by guest. Protected copyright. 45 both, intrinsic and external factors to the healthcare professional that influences antibiotic 46 47 prescription habits of primary care physicians (Figure 1). 48 Despite the comprehensiveness of the proposed theoretical model, few studies tested it in 49 practice.36,39 Therefore, we have designed a study to fill this lack of knowledge using the 50 widelyaccepted knowledge, attitudes and practice (KAP) survey methodology to assess the 51 educational needs of General Practitioners on AMR and antibiotic prescriptions. 52 The chosen study design has a number of strengths. 53 54 First, the ITA-KAAR, Italian version of the KAAR-11 questionnaire, which is the only fully 55 validated scale developed to assess knowledge and attitudes of GPs regarding AMR and 56 antibiotic prescriptions, was translated and adapted to Italian using a methodology aimed to 57 maintain the psychometric properties of the original version of the scale28,29 and will undergo 58 a full validation study. 59 Secondly, in order to fully validate the ITA-KAAR against an external “gold standard” (known- 60 group validity) and to measure the magnitude of the association between each explanatory

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1 2 3 variable and the quality of antibiotic prescription, we will use a set of valid, reliable and 4 internationally accepted indicators30, calculated using data from clinical practice. This leads to BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 further strengths of our study design: (1) they allow comparability to similar studies 7 performed across Europe; (2) their use excludes any opportunistic selection of indicators for 8 the purpose to meet the study objectives. 9 Thirdly, the categorisation of the prescriptions of antibiotics for systemic use (ATC J01 10 subclasses) according to the WHO AWaRe classification, will enhance the comparability of the 11 results of the present study to these of similar studies performed globally40,41 and will be 12 13 useful to shape an appropriate communication strategy in the context of antibiotic 42 14 stewardship interventions targeted to GPs in the Sardinia Region and nationally. 15 Fourthly, the data source of the drug utilization study (study axis B) is an administrative 16 database containing any antibiotic prescription covered by the NHS, filled by every single GP 17 in the examined period of time. This completeness is a well-known strength of drug utilization 18 studies performed onFor large administrative peer review databases, that only have been widely used as reliable 19 43,44 20 data sources among European countries to inform policy. 21 A further strength of the study refers to the estimation methodology that will be used to 22 measure the magnitude of the association between the hypothesized determinants of 23 antibiotic prescriptions and the real prescription data used in this study, namely a 24 multivariate Poisson model with robust estimation of variance. This model is generally 25 preferred to the traditional logistic model in cross-sectional studies when the dependent 26 27 variable is not rare. In fact, in the case of frequent outcomes, typical in cross-sectional studies, 28 the Odds Ratio (OR), obtained from the application of the traditional logistic model, can lead 29 to a strong overestimation of the prevalence ratio and therefore of the magnitude of the 30 association. Moreover, similarly to the multivariate logistic model, the Poisson model 31 produces association measures that are adjusted with respect to the other confounding 32 34 33 factors. 34 Some potential limitations need to be mentioned. 35 First, the response rate to a questionnaire could be low even if a comprehensive data

36 collection strategy is planned.45 To minimize non-response bias (a type of selection bias) and http://bmjopen.bmj.com/ 37 exclude the risk that responders differ in meaningful ways from non-responders, a subgroup 38 analysis of responders and non-responders to the questionnaire will be performed in relation 39 40 to each ESAC indicator. In particular, for both subgroups the percentages of GPs who have 41 shown an AQPA=1 or an AQPA=0 as defined above, will be calculated. In case of differences 42 that do not reach statistical significance between the two subgroups, non-response bias could 43 be reasonably excluded. 44 A second limitation could be that the ESAC quality indicators30 used in our study are not on September 23, 2021 by guest. Protected copyright. 45 developed to consider the underlying reason of the prescription (i.e. the diagnosis). The 46 47 choice of these indicators above others that take into account the clinical reason for 46 48 encounter was made because data regarding the underlying diagnosis are not available in 49 our setting (GP health records that could be used for research purpose does not exist in the 50 region of Sardinia). Nevertheless, we feel that the ESAC quality indicators without the 51 underlying clinical diagnosis30 are appropriate indicators for the purposes of our study. In 52 fact, after adjustment for patients age and gender, we have no reason to believe that the 53 54 population of patients registered in the list of any single GP differ from each other 55 significantly with respect of the occurrence neither of diseases for which antibiotics are 56 currently prescribed in General Practice, nor for other conditions that could act as relevant 57 confounding factors. 58 59 Future perspectives. 60 Considering that 90% of antibiotic prescriptions in human health are filled by GPs, the results

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1 2 3 of this study will be useful to inform stakeholders on the educational needs and the context 4 specific determinants of antibiotic use and will serve the development and implementation of BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 further targeted interventions to reduce antibiotic consumption and prescriptions in the 47 7 community, namely: 8  The design, administration and implementation of a multifaceted intervention targeted 9 to the needs of physicians, as revealed in the first phase of the study. 10  The assessment, in a prospective design, of the impact of this intervention on reducing 11 12 antibiotic prescriptions. 13 Due to the fact that determinants of inappropriate use of antibiotics are context-specific, the 14 overall aim of the “Broad spectrum” project is to create a methodological framework to be 15 applied in other Italian and European regions to tackle inappropriate antibiotic use, thereby 16 reducing and preventing the spread of antibiotic resistance. 17 18 For peer review only 19 20 SUPPLEMENTARY FILES. 21 Supplementary file 1 22 Supplementary file 2 23 Supplementary file 3 24 25 26 ACKNOWLEDGMENTS. This project is funded by a grant from the Foundation of Sardinia and is conducted 27 within a scientific collaboration between the Italian National Institute of Health and the Department of Medical 28 Sciences and Public Health of the University of Cagliari (Resolution of Italian National Institute of Health 17-12- 29 2019). 30 The authors thank: Micaela Morelli, vice-president of the University of Cagliari, Emilio Montaldo (GP, Specialist in 31 Allergology and Immunology, Cagliari, Italy, Member of the Central Committee of the Italian National Federation 32 of Medical Boards) and Raimondo Ibba (president of the Medical Board of the Province of Cagliari, Italy) for their 33 substantial contribution in fostering the Broad Spectrum project at an institutional level. 34 The authors would like to thank also: Maria Teresa Zedda (GP, Specialist in Allergology and Immunology, 35 Cagliari, Italy), Orietta Massidda (Professor for Clinical Microbiology, University of Trento, Italy) for their advices

36 and encouragements, and Noel Baxter (GP, Southwark, London, UK) for his critical revision of this work. http://bmjopen.bmj.com/ 37 38 39 AUTHOR CONTRIBUTIONS. PKK, AS and MN developed the research question. PKK and AS designed, together 40 with the substantial contribution of SSA, MarMas, RDC, MGC, VF, AF and MFM, the overall conception of the 41 project. PKK wrote the protocol and, together with AS, LM and AP the project proposal. PKK and AS, in 42 collaboration with SSA, MarMas, RDC, wrote the first draft of the manuscript. All authors read the manuscript, 43 made relevant critiques and amendments and approved the final draft.

44 PKK, AS, VF, FC, AP, LM, MauMar and MatMas will collect data. MarMas, SSA, RDC, MFM, MGC and PKK will on September 23, 2021 by guest. Protected copyright. 45 perform data analysis. 46 . 47 48 FUNDING. Public Health, Preventive Medicine and Rehabilitation Grant programme (Foundation of Sardinia, 49 Grant n. 30718). 50 51 DISCLAIMER. The views expressed are those of the authors and are not necessarily those of the Italian National 52 Institute of Health, the University of Cagliari, the University of Santiago de Compostela, the Columbia University, 53 the Regional Health Trust of Sardinia or the Italian Secretariat of physician scientists. 54 55 COMPETING INTERESTS. None declared. 56 ETHICS APPROVAL. Ethics committee of the Regional Health Trust of Sardinia (protocol number 176/2019/CE, 57 24th September 2019) 58 59 PROVENANCE AND PEER REVIEW. Not commissioned; externally peer reviewed. 60 DATA SHARING STATEMENT. Principal investigator (PKK) will have direct access to the full data set. Since data

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1 2 3 are anonymised, data are blinded of any identifying information. Anonymised and aggregated data will be stored

4 on password-protected computers at the University of Cagliari and the Italian National Institute of Health. BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Communication between researchers which might involve confidential data will be performed using password- 6 protected emails. Full study protocol will be made publicly available; however, no public access will be granted 7 to data set or statistical code. 8 9 10 REFERENCES. 11 1. ECDC/EMEA Joint Technical Report. The Bacterial Challenge: Time To React. 2009. 12 Available on: https://ecdc.europa.eu/en/publications-data/ecdcemea-joint-technical-report- 13 14 bacterial-challenge-time-react. 15 2. European Commission . A European One Health Action Plan against Antimicrobial 16 Resistance (AMR). 2017. Available on: 17 https://ec.europa.eu/health/amr/sites/amr/files/amr_action_plan_2017_en.pdf. 18 3. Cassini A, HogbergFor LD, peer Plachouras review D, et al. Attributable only deaths and disability-adjusted 19 life-years caused by infections with antibiotic-resistant bacteria in the EU and the European 20 21 Economic Area in 2015: a population-level modelling analysis. Lancet Infect Dis 2019; 19(1): 22 56-66. 23 4. Naylor NR, Atun R, Zhu N, et al. Estimating the burden of antimicrobial resistance: a 24 systematic literature review. Antimicrobial Resistance & Infection Control 2018; 7(1): 58. 25 5. O'Neil J. Tackling drug-resistant infections globally: final report and recommendations. 26 In: Ro A eRL, United Kingdom: 2016; 1, 84. 27 28 6. Bell BG, Schellevis F, Stobberingh E, Goossens H, Pringle M. A systematic review and 29 meta-analysis of the effects of antibiotic consumption on antibiotic resistance. BMC Infect Dis 30 2014; 14: 13. 31 7. Shallcross LJ, Davies DS. Antibiotic overuse: a key driver of antimicrobial resistance. Br 32 J Gen Pract 2014; 64(629): 604-5. 33 34 8. Klein EY, Van Boeckel TP, Martinez EM, et al. Global increase and geographic 35 convergence in antibiotic consumption between 2000 and 2015. Proc Natl Acad Sci U S A

36 2018; 115(15): E3463-E70. http://bmjopen.bmj.com/ 37 9. Van Boeckel TP, Gandra S, Ashok A, et al. Global antibiotic consumption 2000 to 2010: 38 an analysis of national pharmaceutical sales data. Lancet Infect Dis 2014; 14(8): 742-50. 39 10. European Centre for Disease Prevention and Control. Antimicrobial consumption 40 41 surveillance in Europe 2018. Annual report of the European Antimicrobial Consumption 42 Surveillance Network (ESAC-Net). Stockholm: ECDC; 2019. 43 11. Osservatorio Nazionale sull’impiego dei Medicinali. L’uso degli an bio ci in Italia.

44 Rapporto Nazionale 2018. Roma: Agenzia Italiana del Farmaco, 2019. on September 23, 2021 by guest. Protected copyright. 45 12. Fleming-Dutra KE, Hersh AL, Shapiro DJ, et al. Prevalence of Inappropriate Antibiotic 46 Prescriptions Among US Ambulatory Care Visits, 2010-2011. JAMA 2016; 315(17): 1864-73. 47 48 13. Havers FP, Hicks LA, Chung JR, et al. Outpatient Antibiotic Prescribing for Acute 49 Respiratory Infections During Influenza Seasons. JAMA Network Open 2018; 1(2): e180243-e. 50 14. Ciofi Degli Atti ML, Massari M, Bella A, et al. Clinical, social and relational determinants 51 of paediatric ambulatory drug prescriptions due to respiratory tract infections in Italy. 2006. 52 15. Harbarth S, Monnet DL. Cultural and socioeconomic determinants of antibiotic use. 53 2005. 54 55 16. Masiero G, Filippini M, Ferech M, Goossens H. Socioeconomic determinants of 56 outpatient antibiotic use in Europe. 2010. 57 17. Touboul-Lundgren P, Jensen S, Drai J, Lindbaek M. Identification of cultural 58 determinants of antibiotic use cited in primary care in Europe: a mixed research synthesis 59 study of integrated design "Culture is all around us". BMC Public Health 2015; 15: 908. 60

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1 2 3 18. Godman B, Haque M, McKimm J, et al. Ongoing strategies to improve the management 4 of upper respiratory tract infections and reduce inappropriate antibiotic use particularly BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 among lower and middle-income countries: findings and implications for the future. Current 7 Medical Research and Opinion 2020; 36(2): 301-27. 8 19. Giusti A, Spila Alegiani S, Ciofi degli Atti ML, et al. Surgical antibiotic prophylaxis in 9 children: A mixed method study on healthcare professionals attitudes. BMC Pediatr 2016; 10 16(1). 11 20. Teixeira Rodrigues A, Roque F, Falcão A, Figueiras A, Herdeiro MT. Understanding 12 13 physician antibiotic prescribing behaviour: a systematic review of qualitative studies. 14 International Journal of Antimicrobial Agents 2013; 41(3): 203-12. 15 21. Dyar OJ, Beović B, Vlahović-Palčevski V, Verheij T, Pulcini C. How can we improve 16 antibiotic prescribing in primary care? Expert Rev Anti-Inf 2016; 14(4): 403-13. 17 22. Colliers A, Coenen S, Philips H, Remmen R, Anthierens S. Optimising the quality of 18 antibiotic prescribingFor in out-of-hours peer primary review care in Belgium: only a study protocol for an action 19 20 research project. BMJ Open 2017; 7(10): e017522. 21 23. López-Vázquez P, Vázquez-Lago JM, Gonzalez-Gonzalez C, et al. Development and 22 validation of the knowledge and attitudes regarding antibiotics and resistance (KAAR-11) 23 questionnaire for primary care physicians. Journal of Antimicrobial Chemotherapy 2016; 24 71(10): 2972-9. 25 24. Accordo Collettivo Nazionale per la disciplina dei rapporti con i medici di medicina 26 27 generale ai sensi dell'art.8 del D.Lgs. n. 502 del 1992 e successive modificazioni e integrazioni. 28 2018. 29 25. ISTAT - Direzione centrale per le statistiche e le indagini sulle istituzioni sociali, 30 Popolazione residente al 1° gennaio 2019. Available on: http://demo.istat.it. 31 26. Ebert JF, Huibers L, Christensen B, Christensen MB. Paper- or Web-Based 32 33 Questionnaire Invitations as a Method for Data Collection: Cross-Sectional Comparative Study 34 of Differences in Response Rate, Completeness of Data, and Financial Cost. J Med Internet Res 35 2018; 20(1): e24-e.

36 27. Teixeira Rodrigues A, Ferreira M, Roque F, et al. Physicians' attitudes and knowledge http://bmjopen.bmj.com/ 37 concerning antibiotic prescription and resistance: questionnaire development and reliability. 38 BMC Infect Dis 2016; 16: 7. 39 40 28. Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross- 41 cultural adaptation of self-report measures. Spine (Phila Pa 1976) 2000; 25(24): 3186-91. 42 29. Kurotschka PK, Moro MF, Demurtas J, Serafini A. General practitioners knowledge and 43 attitudes about antibiotics and prescriptions: cross-cultural adaptation and preliminary 44 Italian validation of kaar-11 questionnaire. Recenti Prog Med 2020; 111: in press. on September 23, 2021 by guest. Protected copyright. 45 30. Coenen S, Ferech M, Haaijer-Ruskamp FM, et al. European Surveillance of Antimicrobial 46 47 Consumption (ESAC): quality indicators for outpatient antibiotic use in Europe. Qual Saf 48 Health Care 2007; 16(6): 440-5. 49 31. Sharland M, Pulcini C, Harbarth S, et al. Classifying antibiotics in the WHO Essential 50 Medicines List for optimal use-be AWaRe. Lancet Infect Dis 2018; 18(1): 18-20. 51 32. R Core Team (2019). R: A language and environment for statistical computing. R 52 Foundation for Statistical Computing V, Austria. , https://www.R-project.org/. Ao. 53 54 33. Muthén LK & Muthén BO. Mplus User's Guide. Sixth Edition. Los Angeles C-. 55 34. Barros AJD, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: 56 an empirical comparison of models that directly estimate the prevalence ratio. BMC Medical 57 Research Methodology 2003; 3(1): 21. 58 35. Sakamoto Y. IM, Kitagawa G. Akaike information criterion statistics, 1986, New York, 59 Springer. 60

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1 2 3 36. Gonzalez-Gonzalez C, Lopez-Vazquez P, Vazquez-Lago JM, et al. Effect of Physicians' 4 Attitudes and Knowledge on the Quality of Antibiotic Prescription: A Cohort Study. PLoS One BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 2015; 10(10): e0141820. 7 37. Anthoine E, Moret L, Regnault A, Sebille V, Hardouin JB. Sample size used to validate a 8 scale: a review of publications on newly-developed patient reported outcomes measures. 9 Health Qual Life Outcomes 2014; 12: 176. 10 38. O'Keeffe AG, Ambler G, Barber JA. Sample size calculations based on a difference in 11 medians for positively skewed outcomes in health care studies. BMC medical research 12 13 methodology 2017; 17(1): 157-. 14 39. Liu C, Liu C, Wang D, Zhang X. Intrinsic and external determinants of antibiotic 15 prescribing: A multi-level path analysis of primary care prescriptions in Hubei, China. 2019. 16 40. Robertson J, Iwamoto K, Hoxha I, et al. Antimicrobial Medicines Consumption in 17 Eastern Europeand Central Asia – An Updated Cross-National Study and Assessment of 18 QuantitativeMetrics forFor Policy peer Action. Frontiers review in Pharmacology only 2019; 9(1156). 19 20 41. Hsia Y, Lee BR, Versporten A, et al. Use of the WHO Access, Watch, and Reserve 21 classification to define patterns of hospital antibiotic use (AWaRe): an analysis of paediatric 22 survey data from 56 countries. The Lancet Global Health 2019; 7(7): e861-e71. 23 42. Sharland M, Gandra S, Huttner B, et al. Encouraging AWaRe-ness and discouraging 24 inappropriate antibiotic use; the new Essential Medicines List becomes a global antibiotic 25 stewardship tool. Lancet Infect Dis 2019; 19(12): 1278-80. 26 27 43. Latry P, Molimard M, Bégaud B, Martin-Latry K. How reimbursement databases can be 28 used to support drug utilisation studies: example using the main French national health 29 insurance system database. Eur J Clin Pharmacol 2010; 66(7): 743-8. 30 44. Leporowski A, Godman B, Kurdi A, et al. Ongoing activities to optimize the quality and 31 efficiency of lipid-lowering agents in the Scottish national health service: influence and 32 33 implications. Expert Review of Pharmacoeconomics & Outcomes Research 2018; 18(6): 655-66. 34 45. Aitken C, Power R, Dwyer R. A very low response rate in an on-line survey of medical 35 practitioners. Australian and New Zealand Journal of Public Health 2008; 32(3): 288-9.

36 46. Adriaenssens N, Coenen S, Tonkin-Crine S, et al. European Surveillance of http://bmjopen.bmj.com/ 37 Antimicrobial Consumption (ESAC): disease-specific quality indicators for outpatient 38 antibiotic prescribing. BMJ Qual Saf 2011; 20(9): 764-72. 39 40 47. Teixeira Rodrigues A, Roque F, Pineiro-Lamas M, Falcao A, Figueiras A, Herdeiro MT. 41 Effectiveness of an intervention to improve antibiotic-prescribing behaviour in primary care: 42 a controlled, interrupted time-series study. Journal of Antimicrobial Chemotherapy 2019; 30: 43 30.

44 on September 23, 2021 by guest. Protected copyright. 45 46 47 48 49 50 LEGENDS 51 52 53 Table 1: ITA-KAAR questionnaire, main section exploring physician knowledge and attitudes (translated in 54 English by authors) 55 56 57 58 Figure 1: Theoretical model of Antibiotic prescribing behaviour of GPs, adapted from Teixeira et al.20. Continuous 59 arrows represent factors that are deemed to influence antibiotic prescriptions directly. Dotted arrows represent 60 factors that are deemed do influence antibiotic prescriptions indirectly through the influence of knowledge and/or attitudes.

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4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 7 8 9 AUTHORS 10 11 Alice Serafini [email protected] 12 13 Marco Massari [email protected] 14 Roberto Da Cas [email protected] 15 Adolfo Figueiras [email protected] 16 Viviana Forte [email protected] 17 Maria Francesca Moro [email protected] 18 Luigi Minerba For [email protected] review only 19 20 Matteo Massidda [email protected] 21 Federico Contu [email protected] 22 Maurizio Marcias [email protected] 23 Marco Nardelli [email protected] 24 Alessandra Perra [email protected] 25 Mauro Giovanni Carta [email protected] 26 27 Stefania Spila Alegiani [email protected] 28 29 30 31 32 33 34 35

36 http://bmjopen.bmj.com/ 37 38 39 40 41 42 43

44 on September 23, 2021 by guest. Protected copyright. 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 7 8 9 10 11 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

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1 2 3

4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 7 ITA-KAAR 11 8 9 10 ITA-KAAR: Read the statements in the 11 left column and draw an X in the right 12 column according to your level of 13 agreement with the statement 14 expressed 15 Totally Totally 16 disagree agree 17 18 1. ​Antibiotic resistanceFor is apeer major public review only 19 health problem in our setting 20 21 2. In primary care it is useful to wait for a ​ 22 microbiology results before treating an 23 infectious diseases. 24 25 3. Prescribing an antibiotic to a patient ​ 26 does not influence the development of 27 28 resistance. 29 4. New antibiotics will be developed to 30 ​ solve the problem of resistance. 31 32 5. The use of antibiotics in animals is a 33 ​ 34 major cause of the occurrence of new resistance. 35

36 http://bmjopen.bmj.com/ 6. When in doubt, it is better to ensure that 37 ​ 38 a patient is cured of an infection by using a 39 broad-spectrum antibiotic. 40 7. I often prescribe antibiotics because it is 41 ​ 42 impossible to track the patient accurately. 43

44 8. When in doubt as to whether a patient on September 23, 2021 by guest. Protected copyright. ​ 45 has a bacterial disease, it is best to 46 prescribe an antibiotic. 47 48 9. I often prescribe antibiotics because ​ 49 patients ask me for them 50 51 10. If a patient believes that he needs an ​ 52 antibiotic and the doctor does not 53 prescribe it, he will get it at the pharmacy 54 55 without a prescription. 56 11. Amoxicillin is useful for resolving most 57 ​ 58 respiratory infections in primary care. 59 60

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4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 7 How do you evaluate the usefulness of the 8 following sources of information in the 9 treatment of respiratory infection? Draw an 10 X in the right column depending on your 11 level of agreement with the statement 12 Not useful at all Very useful 13 ​ ​ 14 15 1. Guidelines 16

17 18 For peer review only 19 2. Informative materials provided by 20 pharmaceutical companies 21 22 23 24 3. Courses provided by 25 pharmaceutical companies 26 27 28 29 4. Medical sales representatives 30 31 32 33 5. Previous clinical experience 34 35

36 http://bmjopen.bmj.com/ 37 6. Online resources (Guidelines, 38 Medical Apps, etc.) 39 40 41 42 7. Other specialists (microbiologists, 43 pneumologists etc.);

44 on September 23, 2021 by guest. Protected copyright. 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 7 Third section: we added this section to understand if, and how, some 8 ❏ 9 organizational aspects can influence the How many minutes on average do 10 prescription of antibiotics. Please answer you have for each patient? 11 to the following short contextual 12 questions 13 14 15 16 ❏ What is your year of birth? 17 ❏ Do you have a study collaborator? 18 For peer review only 19 20 Yes No 21 22 23 ❏ To which gender identity do you 24 ❏ What is the indicative number of 25 most identify? 26 your daily contacts (outpatient visits 27 28 Male Female + home visits + telephone advice) 29 on a typical day in the flu season 30 prefer not to answer 31 (from mid-October to the end of 32 33 April)? 34 ❏ What is your graduation year? 35

36 http://bmjopen.bmj.com/ 37 38 39 40 ❏ How do you organize access to 41 ❏ Do you have the diploma of the your clinic? 42 43 Specific Training Course in General

44 mainly by mainly free on September 23, 2021 by guest. Protected copyright. 45 Practice? appointment access 46 47 48 Yes No 49 50 51 52 ❏ Do you have a Universitary 53 specialization? 54 55 56 SI NO 57 58 59 60

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1 2 3 Weights system, set up by the Department of Programming of the Italian Ministry of Health

4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from

5 6 7 Age 0 1-4 5-14 15-44 15-44 45-64 65-74 > of 74 8 group Men Women 9 10 11 Weight 1 0,969 0,695 0,693 0,771 2,104 4,176 4,29 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

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4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 6 The 2019 WHO AWaRe classification of antibiotics 7 8 for evaluation and monitoring of use. 9 10 WHO/EMP/IAU/2019.11 11 12 © World Health Organization 2019 13 14 Some rights reserved. This work is available under the Creative Commons Attribution- 15 NonCommercial-ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; 16 https://creativecommons.org/licenses/by-nc-sa/3.0/igo). 17 18 Suggested citation. TheFor 2019 WHO peer AWaRe classification review of antibiotics only for evaluation and 19 monitoring of use. Geneva: World Health Organization; 2019. (WHO/EMP/IAU/2019.11). 20 Licence: CC BY-NC-SA 3.0 IGO. 21 22 Cataloguing-in-Publication (CIP) data. CIP data are available at http://apps.who.int/iris. 23 24 Sales, rights and licensing. To purchase WHO publications, see 25 http://apps.who.int/bookorders. To submit requests for commercial use and queries on rights 26 and licensing, see http://www.who.int/about/licensing. 27 28 General disclaimers. The designations employed and the presentation of the material in this 29 publication do not imply the expression of any opinion whatsoever on the part of WHO 30 concerning the legal status of any country, territory, city or area or of its authorities, or 31 concerning the delimitation of its frontiers or boundaries. Dotted and dashed lines on maps 32 33 represent approximate border lines for which there may not yet be full agreement. The 34 mention of specific companies or of certain manufacturers’ products does not imply that they 35 are endorsed or recommended by WHO in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are 36 http://bmjopen.bmj.com/ 37 distinguished by initial capital letters. 38 All reasonable precautions have been taken by WHO to verify the information contained in 39 this publication. However, the published material is being distributed without warranty of any 40 kind, either expressed or implied. The responsibility for the interpretation and use of the 41 material lies with the reader. In no event shall WHO be liable for damages arising from its use. 42 43

44 on September 23, 2021 by guest. Protected copyright. 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 The 2019 WHO AWaRe classification of antibiotics for evaluation and monitoring of use 3 To assist in the development of tools for antibiotic stewardship at local, national and global levels and to reduce antimicrobial resistance, the Access, Watch, Reserve (AWaRe) classification of antibiotics was developed – where antibiotics are classified into different groups to emphasize the importance of their

4 appropriate use. BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 This classification is intended to be used as a tool for countries to better support antibiotic monitoring and stewardship activities. It is not intended as model for the inclusion of antibiotics on national essential medicine lists. Antibiotics classified under AWaRe and also included on the WHO Model LIsts of Essential 6 Medicines are indicated in the worksheets. 7 Antibiotic Class ATC code Category Listed on EML 2019 8 Amikacin Aminoglycosides J01GB06 Access Yes 9 Amoxicillin Penicillins J01CA04 Access Yes Amoxicillin/clavulanic Acid Beta lactam - beta lactamase inhibitor J01CR02 Access Yes 10 Ampicillin Penicillins J01CA01 Access Yes 11 Ampicillin/sulbactam Beta lactam - beta lactamase inhibitor J01CR01 Access No Arbekacin Aminoglycosides J01GB12 Watch No 12 Azithromycin Macrolides J01FA10 Watch Yes 13 Azlocillin Penicillins J01CA09 Watch No 14 Aztreonam Monobactams J01DF01 Reserve No Bacampicillin Penicillins J01CA06 Access No 15 Benzathine benzylpenicillin Penicillins J01CE08 Access Yes 16 Benzylpenicillin Penicillins J01CE01 Access Yes Biapenem Carbapenems J01DH05 Watch No 17 Carbenicillin Carboxypenicillins J01CA03 Watch No 18 Cefacetrile First-generation cephalosporinsFor peer reviewJ01DB10 AccessonlyNo Cefaclor Second-generation cephalosporins J01DC04 Watch No 19 Cefadroxil First-generation cephalosporins J01DB05 Access No 20 Cefalexin First-generation cephalosporins J01DB01 Access Yes Cefalotin First-generation cephalosporins J01DB03 Access No 21 Cefamandole Second-generation cephalosporins J01DC03 Watch No 22 Cefapirin First-generation cephalosporins J01DB08 Access No Cefatrizine First-generation cephalosporins J01DB07 Access No 23 Cefazedone First-generation cephalosporins J01DB06 Access No 24 Cefazolin First-generation cephalosporins J01DB04 Access Yes 25 Cefbuperazone Second-generation cephalosporins J01DC13 Watch No Cefcapene pivoxil Third-generation cephalosporins J01DD17 Watch No 26 Cefdinir Third-generation cephalosporins J01DD15 Watch No 27 Cefditoren pivoxil Third-generation cephalosporins J01DD16 Watch No Cefepime Fourth-generation cephalosporins J01DE01 Watch No 28 Cefetamet pivoxil Third-generation cephalosporins J01DD10 Watch No 29 Cefixime Third-generation cephalosporins J01DD08 Watch Yes Cefmenoxime Third-generation cephalosporins J01DD05 Watch No 30 Cefmetazole Second-generation cephalosporins J01DC09 Watch No 31 Cefminox Second-generation cephalosporins J01DC12 Watch No Cefodizime Third-generation cephalosporins J01DD09 Watch No 32 Cefonicid Second-generation cephalosporins J01DC06 Watch No 33 Cefoperazone Third-generation cephalosporins J01DD12 Watch No Ceforanide Second-generation cephalosporins J01DC11 Watch No 34 Cefoselis Fourth-generation cephalosporins to be assigned Watch No 35 Cefotaxime Third-generation cephalosporins J01DD01 Watch Yes Cefotetan Second-generation cephalosporins J01DC05 Watch No 36 http://bmjopen.bmj.com/ Cefotiam Second-generation cephalosporins J01DC07 Watch No 37 Cefotiam hexetil Second-generation cephalosporins J01DC07 Watch No 38 Cefoxitin Second-generation cephalosporins J01DC01 Watch No Cefozopran Fourth-generation cephalosporins J01DE03 Watch No 39 Cefpiramide Third-generation cephalosporins J01DD11 Watch No 40 Cefpirome Fourth-generation cephalosporins J01DE02 Watch No Cefpodoxime proxetil Third-generation cephalosporins J01DD13 Watch No 41 Cefprozil Second-generation cephalosporins J01DC10 Watch No 42 Cefradine First-generation cephalosporins J01DB09 Access No Cefroxadine First-generation cephalosporins J01DB11 Access No 43 Ceftaroline fosamil Fifth-generation cephalosporins J01DI02 Reserve No

44 Ceftazidime Third-generation cephalosporins J01DD02 Watch Yes on September 23, 2021 by guest. Protected copyright. Ceftazidime-avibactam Third-generation cephalosporins J01DD52 Reserve Yes 45 Cefteram pivoxil Third-generation cephalosporins J01DD18 Watch No 46 Ceftezole First-generation cephalosporins J01DB12 Access No 47 Ceftibuten Third-generation cephalosporins J01DD14 Watch No Ceftizoxime Third-generation cephalosporins J01DD07 Watch No 48 Ceftobiprole medocaril Fifth-generation cephalosporins J01DI01 Reserve No 49 Ceftolozane-tazobactam Fifth-generation cephalosporins J01DI54 Reserve No Ceftriaxone Third-generation cephalosporins J01DD04 Watch Yes 50 Cefuroxime Second-generation cephalosporins J01DC02 Watch Yes 51 Chloramphenicol Amphenicols J01BA01 Access Yes Chlortetracycline Tetracyclines J01AA03 Watch No 52 Ciprofloxacin Fluoroquinolones J01MA02 Watch Yes 53 Clarithromycin Macrolides J01FA09 Watch Yes Clindamycin Lincosamides J01FF01 Access Yes 54 Clofoctol Phenol derivatives J01XX03 Watch No 55 Clometocillin Penicillins J01CE07 Access No Cloxacillin Penicillins J01CF02 Access Yes 56 Colistin Polymyxins J01XB01 Reserve Yes 57 Dalbavancin Glycopeptides J01XA04 Reserve No 58 Dalfopristin-quinupristin Streptogramins J01FG02 Reserve No Daptomycin Lipopeptides J01XX09 Reserve No 59 Delafloxacin Fluoroquinolones J01MA23 Watch No 60 Dibekacin Aminoglycosides J01GB09 Watch No Dicloxacillin Penicillins J01CF01 Access No Dirithromycin Macrolides J01FA13 Watch No Doripenem Carbapenems J01DH04 Watch No

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1 Doxycycline Tetracyclines J01AA02 Access Yes 2 Enoxacin Fluoroquinolones J01MA04 Watch No 3 Ertapenem Carbapenems J01DH03 Watch No Eravacycline Tetracyclines J01AA13 Reserve No

4 Erythromycin Macrolides J01FA01 Watch No BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Faropenem Penems J01DI03 Reserve No Fleroxacin Fluoroquinolones J01MA08 Watch No 6 Flomoxef Second-generation cephalosporins J01DC14 Watch No 7 Flucloxacillin Penicillins J01CF05 Access No Flumequine Fluoroquinolones J01MB07 Watch No 8 Fosfomycin (IV) Phosphonics J01XX01 Reserve Yes 9 Fosfomycin (oral) Phosphonics J01XX01 Watch No 10 Fusidic Acid Steroid antibacterials J01XC01 Watch No Garenoxacin Fluoroquinolones J01MA19 Watch No 11 Gatifloxacin Fluoroquinolones J01MA16 Watch No 12 Gemifloxacin Fluoroquinolones J01MA15 Watch No Gentamicin Aminoglycosides J01GB03 Access Yes 13 Imipenem/cilastatin Carbapenems J01DH51 Watch No 14 Isepamicin Aminoglycosides J01GB11 Watch No Josamycin Macrolides J01FA07 Watch No 15 Kanamycin Aminoglycosides J01GB04 Watch No 16 Latamoxef Third-generation cephalosporins J01DD06 Watch No Levofloxacin Fluoroquinolones J01MA12 Watch No 17 Lincomycin Macrolides J01FF02 Watch No 18 Linezolid OxazolidinonesFor peer reviewJ01XX08 ReserveonlyYes Lomefloxacin Fluoroquinolones J01MA07 Watch No 19 Lymecycline Tetracyclines J01AA04 Watch No 20 Mecillinam Penicillins J01CA11 Access No 21 Meropenem Carbapenems J01DH02 Watch Yes Meropenem-vaborbactam Carbapenems J01DH52 Reserve Yes 22 Metacycline Tetracyclines J01AA05 Watch No 23 Metronidazole (IV) Imidazoles J01XD01 Access Yes Metronidazole (oral) Imidazoles P01AB01 Access Yes 24 Mezlocillin Penicillins J01CA10 Watch No 25 Micronomicin Aminoglycosides to be assigned Watch No Midecamycin Macrolides J01FA03 Watch No 26 Minocycline (IV) Tetracyclines J01AA08 Reserve No 27 Minocycline (oral) Tetracyclines J01AA08 Watch No Moxifloxacin Fluoroquinolones J01MA14 Watch No 28 Nafcillin Penicillins J01CF06 Access No 29 Neomycin Aminoglycosides J01GB05 Watch No Netilmicin Aminoglycosides J01GB07 Watch No 30 Nitrofurantoin Nitrofurantoin J01XE01 Access Yes 31 Norfloxacin Fluoroquinolones J01MA06 Watch No 32 Ofloxacin Fluoroquinolones J01MA01 Watch No Oleandomycin Macrolides J01FA05 Watch No 33 Omadacycline Tetracyclines to be assigned Reserve No 34 Oritavancin Glycopeptides J01XA05 Reserve No Oxacillin Penicillins J01CF04 Access No 35 Oxytetracycline Tetracyclines J01AA06 Watch No

36 Panipenem Carbapenems to be assigned Watch No http://bmjopen.bmj.com/ Pazufloxacin Fluoroquinolones J01MA18 Watch No 37 Pefloxacin Fluoroquinolones J01MA03 Watch No 38 Penamecillin Penicillins J01CE06 Access No Pheneticillin Penicillins J01CE05 Watch No 39 Phenoxymethylpenicillin Penicillins J01CE02 Access Yes 40 Piperacillin Penicillins J01CA12 Watch No Piperacillin/tazobactam Beta lactam - beta lactamase inhibitor (anti-pseudomonal) J01CR05 Watch Yes 41 Pivampicillin Penicillins J01CA02 Access No 42 Pivmecillinam Penicillins J01CA08 Access No 43 Plazomicin Aminoglycosides to be assigned Reserve Yes Polymyxin B Polymyxins J01XB02 Reserve Yes

44 Pristinamycin Streptogramins J01FG01 Watch No on September 23, 2021 by guest. Protected copyright. 45 Procaine benzylpenicillin Penicillins J01CE09 Access Yes Prulifloxacin Fluoroquinolones J01MA17 Watch No 46 Ribostamycin Aminoglycosides J01GB10 Watch No 47 Rifabutin Rifamycins J04AB04 Watch No Rifampicin Rifamycins J04AB02 Watch No 48 Rifamycin Rifamycins J04AB03 Watch No 49 Rifaximin Rifamycins A07AA11 Watch No Roxithromycin Macrolides J01FA06 Watch No 50 Rufloxacin Fluoroquinolones J01MA10 Watch No 51 Sisomicin Aminoglycosides J01GB08 Watch No Sitafloxacin Fluoroquinolones J01MA21 Watch No 52 Sparfloxacin Fluoroquinolones J01MA09 Watch No 53 Spectinomycin Aminocyclitols J01XX04 Access Yes 54 Spiramycin Macrolides J01FA02 Watch No Spiramycin/metronidazole Combination of antibiotics J01RA04 Watch No 55 Streptomycin Aminoglycosides J01GA01 Watch No 56 Sulbenicillin Penicillins J01CA16 Watch No Sulfadiazine/trimethoprim Trimethoprim - sulfonamide combinations J01EE02 Access No 57 Sulfamethizole/trimethoprim Trimethoprim - sulfonamide combinations J01EB02 Access No 58 Sulfamethoxazole/trimethoprim Trimethoprim - sulfonamide combinations J01EE01 Access Yes Sulfametrole/trimethoprim Trimethoprim - sulfonamide combinations J01EE03 Access No 59 Sulfamoxole/trimethoprim Trimethoprim - sulfonamide combinations J01EE04 Access No 60 Sultamicillin Beta lactam - beta lactamase inhibitor J01CR04 Access No Tebipenem Carbapenems J01DH06 Watch No Tedizolid Oxazolidinones J01XX11 Reserve No

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1 Teicoplanin Glycopeptides J01XA02 Watch No 2 Telavancin Glycopeptides J01XA03 Reserve No 3 Telithromycin Macrolides J01FA15 Watch No Temocillin Carboxypenicillins J01CA17 Watch No

4 Tetracycline Tetracyclines J01AA07 Access No BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Thiamphenicol Amphenicols J01BA02 Access No Ticarcillin Carboxypenicillins J01CA13 Watch No 6 Tigecycline Glycylcyclines J01AA12 Reserve No 7 Tobramycin Aminoglycosides J01GA01 Watch No Tosufloxacin Fluoroquinolones J01MA22 Watch No 8 Trimethoprim Trimethoprim J01EA01 Access No 9 Vancomycin (IV) Glycopeptides J01XA01 Watch Yes 10 Vancomycin (oral) Glycopeptides A07AA09 Watch Yes 11 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

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1 2 Access group antibiotics 3

4 This group includes antibiotics that have activity against a wide range of commonly encountered susceptible pathogens while also showing lowerBMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 resistance potential than antibiotics in the other groups. Selected Access group antibiotics are recommended as essential first or second choice 6 empiric treatment options for infectious syndromes reviewed by the EML Expert Committee and are listed as individual medicines on the Model 7 Lists of Essential Medicines to improve access and promote appropriate use. 8 9 10 Antibiotic Class ATC code 11 Amikacin Aminoglycosides J01GB06 12 Amoxicillin Penicillins J01CA04 13 Amoxicillin/clavulanic Acid Beta lactam - beta lactamase inhibitor J01CR02 14 15 Ampicillin Penicillins J01CA01 16 Ampicillin/sulbactam Beta lactam - beta lactamase inhibitor J01CR01 17 Bacampicillin Penicillins J01CA06 18 Benzathine benzylpenicillinFor peerPenicillins review only J01CE08 19 Benzylpenicillin Penicillins J01CE01 20 21 Cefacetrile First-generation cephalosporins J01DB10 22 Cefadroxil First-generation cephalosporins J01DB05 23 Cefalexin First-generation cephalosporins J01DB01 24 Cefalotin First-generation cephalosporins J01DB03 25 26 Cefapirin First-generation cephalosporins J01DB08 27 Cefatrizine First-generation cephalosporins J01DB07 28 Cefazedone First-generation cephalosporins J01DB06 29 Cefazolin First-generation cephalosporins J01DB04 30 Cefradine First-generation cephalosporins J01DB09 31 32 Cefroxadine First-generation cephalosporins J01DB11 33 Ceftezole First-generation cephalosporins J01DB12 34 Chloramphenicol Amphenicols J01BA01 35 Clindamycin Lincosamides J01FF01 36 Clometocillin Penicillins J01CE07 http://bmjopen.bmj.com/ 37 38 Cloxacillin Penicillins J01CF02 39 Dicloxacillin Penicillins J01CF01 40 Doxycycline Tetracyclines J01AA02 41 Flucloxacillin Penicillins J01CF05 42 Gentamicin Aminoglycosides J01GB03 43 Mecillinam Penicillins J01CA11 44 on September 23, 2021 by guest. Protected copyright. 45 Metronidazole (IV) Imidazoles J01XD01 46 Metronidazole (oral) Imidazoles P01AB01 47 Nafcillin Penicillins J01CF06 48 Nitrofurantoin Nitrofurantoin J01XE01 49 50 Oxacillin Penicillins J01CF04 51 Penamecillin Penicillins J01CE06 52 Phenoxymethylpenicillin Penicillins J01CE02 53 Pivampicillin Penicillins J01CA02 54 Pivmecillinam Penicillins J01CA08 55 56 Procaine benzylpenicillin Penicillins J01CE09 57 Spectinomycin Aminocyclitols J01XX04 58 Sulfadiazine/trimethoprim Trimethoprim - sulfonamide combinations J01EE02 59 Sulfamethizole/trimethoprim Trimethoprim - sulfonamide combinations J01EB02 60 Sulfamethoxazole/trimethoprim Trimethoprim - sulfonamide combinations J01EE01 Sulfametrole/trimethoprim Trimethoprim - sulfonamide combinations J01EE03

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1 2 Sulfamoxole/trimethoprim Trimethoprim - sulfonamide combinations J01EE04 3 Sultamicillin Beta lactam - beta lactamase inhibitor J01CR04

4 Tetracycline Tetracyclines J01AA07 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Thiamphenicol Amphenicols J01BA02 6 7 Trimethoprim Trimethoprim J01EA01 8 9 10 11 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

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1 Access group antibiotics 2 3

This group includes antibiotics that have activity against a wide range of commonly encountered susceptible pathogens while also showing lower4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from resistance potential than antibiotics in the other groups. Selected Access group antibiotics are recommended as essential first or second choice5 empiric treatment options for infectious syndromes reviewed by the EML Expert Committee and are listed as individual medicines on the Model6 7 Lists of Essential Medicines to improve access and promote appropriate use. 8 9 10 Category Listed on EML 2019 11 Access Yes 12 Access Yes 13 Access Yes 14 15 Access Yes 16 Access No 17 Access No 18 Access Yes For peer review only 19 Access Yes 20 21 Access No 22 Access No 23 Access Yes 24 Access No 25 26 Access No 27 Access No 28 Access No 29 Access Yes 30 Access No 31 32 Access No 33 Access No 34 Access Yes 35 Access Yes 36 Access No http://bmjopen.bmj.com/ 37 38 Access Yes 39 Access No 40 Access Yes 41 Access No 42 Access Yes 43 Access No 44 on September 23, 2021 by guest. Protected copyright. 45 Access Yes 46 Access Yes 47 Access No 48 Access Yes 49 50 Access No 51 Access No 52 Access Yes 53 Access No 54 Access No 55 56 Access Yes 57 Access Yes 58 Access No 59 Access No 60 Access Yes Access No

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1 2 Access No 3 Access No

4 Access No BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Access No 6 7 Access No 8 9 10 11 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

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1 2 Watch group antibiotics 3 This group includes antibiotic classes that have higher resistance potential and includes most of the highest priority agents among the Critically Important 4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Antimicrobials for Human Medicine1 and/or antibiotics that are at relatively high risk of selection of bacterial resistance. These medicines should be 6 prioritized as key targets of stewardship programs and monitoring. Selected Watch group antibiotics are recommended as essential first or second choice 7 empiric treatment options for a limited number of specific infectious syndromes and are listed as individual medicines on the WHO Model Lists of Essential 8 9 Medicines. 10 1 Critically Important Antimicrobials for Human Medicine 6th Revision 2018 11 Antibiotic Class 12 13 Arbekacin Aminoglycosides 14 Azithromycin Macrolides 15 Azlocillin Penicillins 16 Biapenem Carbapenems 17 Carbenicillin Carboxypenicillins 18 For peer review only 19 Cefaclor Second-generation cephalosporins 20 Cefamandole Second-generation cephalosporins 21 Cefbuperazone Second-generation cephalosporins 22 Cefcapene pivoxil Third-generation cephalosporins 23 24 Cefdinir Third-generation cephalosporins 25 Cefditoren pivoxil Third-generation cephalosporins 26 Cefepime Fourth-generation cephalosporins 27 Cefetamet pivoxil Third-generation cephalosporins 28 Cefixime Third-generation cephalosporins 29 30 Cefmenoxime Third-generation cephalosporins 31 Cefmetazole Second-generation cephalosporins 32 Cefminox Second-generation cephalosporins 33 Cefodizime Third-generation cephalosporins 34 Cefonicid Second-generation cephalosporins 35 Cefoperazone Third-generation cephalosporins 36 http://bmjopen.bmj.com/ 37 Ceforanide Second-generation cephalosporins 38 Cefoselis Fourth-generation cephalosporins 39 Cefotaxime Third-generation cephalosporins 40 Cefotetan Second-generation cephalosporins 41 42 Cefotiam Second-generation cephalosporins 43 Cefotiam hexetil Second-generation cephalosporins

44 Cefoxitin Second-generation cephalosporins on September 23, 2021 by guest. Protected copyright. 45 Cefozopran Fourth-generation cephalosporins 46 Cefpiramide Third-generation cephalosporins 47 48 Cefpirome Fourth-generation cephalosporins 49 Cefpodoxime proxetil Third-generation cephalosporins 50 Cefprozil Second-generation cephalosporins 51 Ceftazidime Third-generation cephalosporins 52 Cefteram pivoxil Third-generation cephalosporins 53 54 Ceftibuten Third-generation cephalosporins 55 Ceftizoxime Third-generation cephalosporins 56 Ceftriaxone Third-generation cephalosporins 57 Cefuroxime Second-generation cephalosporins 58 59 Chlortetracycline Tetracyclines 60 Ciprofloxacin Fluoroquinolones Clarithromycin Macrolides

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1 2 Clofoctol Phenol derivatives 3 Delafloxacin Fluoroquinolones

4 Dibekacin Aminoglycosides BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Dirithromycin Macrolides 6 7 Doripenem Carbapenems 8 Enoxacin Fluoroquinolones 9 Ertapenem Carbapenems 10 Erythromycin Macrolides 11 Fleroxacin Fluoroquinolones 12 13 Flomoxef Second-generation cephalosporins 14 Flumequine Fluoroquinolones 15 Fosfomycin (oral) Phosphonics 16 Fusidic Acid Steroid antibacterials 17 Garenoxacin Fluoroquinolones 18 For peer review only 19 Gatifloxacin Fluoroquinolones 20 Gemifloxacin Fluoroquinolones 21 Imipenem/cilastatin Carbapenems 22 Isepamicin Aminoglycosides 23 Josamycin Macrolides 24 25 Kanamycin Aminoglycosides 26 Latamoxef Third-generation cephalosporins 27 Levofloxacin Fluoroquinolones 28 Lincomycin Macrolides 29 30 Lomefloxacin Fluoroquinolones 31 Lymecycline Tetracyclines 32 Meropenem Carbapenems 33 Metacycline Tetracyclines 34 Mezlocillin Penicillins 35 Micronomicin Aminoglycosides 36 http://bmjopen.bmj.com/ 37 Midecamycin Macrolides 38 Minocycline (oral) Tetracyclines 39 Moxifloxacin Fluoroquinolones 40 Neomycin Aminoglycosides 41 42 Netilmicin Aminoglycosides 43 Norfloxacin Fluoroquinolones

44 Ofloxacin Fluoroquinolones on September 23, 2021 by guest. Protected copyright. 45 Oleandomycin Macrolides 46 Oxytetracycline Tetracyclines 47 48 Panipenem Carbapenems 49 Pazufloxacin Fluoroquinolones 50 Pefloxacin Fluoroquinolones 51 Pheneticillin Penicillins 52 Piperacillin Penicillins 53 54 Piperacillin/tazobactam Beta lactam - beta lactamase inhibitor (anti-pseudomonal) 55 Pristinamycin Streptogramins 56 Prulifloxacin Fluoroquinolones 57 Ribostamycin Aminoglycosides 58 Rifabutin Rifamycins 59 60 Rifampicin Rifamycins Rifamycin Rifamycins

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1 2 Rifaximin Rifamycins 3 Roxithromycin Macrolides

4 Rufloxacin Fluoroquinolones BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Sisomicin Aminoglycosides 6 7 Sitafloxacin Fluoroquinolones 8 Sparfloxacin Fluoroquinolones 9 Spiramycin Macrolides 10 Spiramycin/metronidazole Combination of antibiotics 11 Streptomycin Aminoglycosides 12 13 Sulbenicillin Penicillins 14 Tebipenem Carbapenems 15 Teicoplanin Glycopeptides 16 Telithromycin Macrolides 17 Temocillin Carboxypenicillins 18 For peer review only 19 Ticarcillin Carboxypenicillins 20 Tobramycin Aminoglycosides 21 Tosufloxacin Fluoroquinolones 22 Vancomycin (IV) Glycopeptides 23 Vancomycin (oral) Glycopeptides 24 25 26 27 28 29 30 31 32 33 34 35

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1 Watch group antibiotics 2 3 This group includes antibiotic classes that have higher resistance potential and includes most of the highest priority agents among the Critically Important 4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from Antimicrobials for Human Medicine1 and/or antibiotics that are at relatively high risk of selection of bacterial resistance. These medicines should be5 prioritized as key targets of stewardship programs and monitoring. Selected Watch group antibiotics are recommended as essential first or second choice6 empiric treatment options for a limited number of specific infectious syndromes and are listed as individual medicines on the WHO Model Lists of Essential7 8 Medicines. 9 1 Critically Important Antimicrobials for Human Medicine 6th Revision 2018 10 11 ATC code Category Listed on EML 2019 12 13 J01GB12 Watch No 14 J01FA10 Watch Yes 15 J01CA09 Watch No 16 J01DH05 Watch No 17 J01CA03 Watch No 18 For peer review only 19 J01DC04 Watch No 20 J01DC03 Watch No 21 J01DC13 Watch No 22 J01DD17 Watch No 23 24 J01DD15 Watch No 25 J01DD16 Watch No 26 J01DE01 Watch No 27 J01DD10 Watch No 28 J01DD08 Watch Yes 29 30 J01DD05 Watch No 31 J01DC09 Watch No 32 J01DC12 Watch No 33 J01DD09 Watch No 34 J01DC06 Watch No 35 J01DD12 Watch No 36 http://bmjopen.bmj.com/ 37 J01DC11 Watch No 38 to be assigned Watch No 39 J01DD01 Watch Yes 40 J01DC05 Watch No 41 42 J01DC07 Watch No 43 J01DC07 Watch No

44 J01DC01 Watch No on September 23, 2021 by guest. Protected copyright. 45 J01DE03 Watch No 46 J01DD11 Watch No 47 48 J01DE02 Watch No 49 J01DD13 Watch No 50 J01DC10 Watch No 51 J01DD02 Watch Yes 52 J01DD18 Watch No 53 54 J01DD14 Watch No 55 J01DD07 Watch No 56 J01DD04 Watch Yes 57 J01DC02 Watch Yes 58 59 J01AA03 Watch No 60 J01MA02 Watch Yes J01FA09 Watch Yes

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1 2 J01XX03 Watch No 3 J01MA23 Watch No

4 J01GB09 Watch No BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 J01FA13 Watch No 6 7 J01DH04 Watch No 8 J01MA04 Watch No 9 J01DH03 Watch No 10 J01FA01 Watch No 11 J01MA08 Watch No 12 13 J01DC14 Watch No 14 J01MB07 Watch No 15 J01XX01 Watch No 16 J01XC01 Watch No 17 J01MA19 Watch No 18 For peer review only 19 J01MA16 Watch No 20 J01MA15 Watch No 21 J01DH51 Watch No 22 J01GB11 Watch No 23 J01FA07 Watch No 24 25 J01GB04 Watch No 26 J01DD06 Watch No 27 J01MA12 Watch No 28 J01FF02 Watch No 29 30 J01MA07 Watch No 31 J01AA04 Watch No 32 J01DH02 Watch Yes 33 J01AA05 Watch No 34 J01CA10 Watch No 35 to be assigned Watch No 36 http://bmjopen.bmj.com/ 37 J01FA03 Watch No 38 J01AA08 Watch No 39 J01MA14 Watch No 40 J01GB05 Watch No 41 42 J01GB07 Watch No 43 J01MA06 Watch No

44 J01MA01 Watch No on September 23, 2021 by guest. Protected copyright. 45 J01FA05 Watch No 46 J01AA06 Watch No 47 48 to be assigned Watch No 49 J01MA18 Watch No 50 J01MA03 Watch No 51 J01CE05 Watch No 52 J01CA12 Watch No 53 54 J01CR05 Watch Yes 55 J01FG01 Watch No 56 J01MA17 Watch No 57 J01GB10 Watch No 58 J04AB04 Watch No 59 60 J04AB02 Watch No J04AB03 Watch No

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1 2 A07AA11 Watch No 3 J01FA06 Watch No

4 J01MA10 Watch No BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 J01GB08 Watch No 6 7 J01MA21 Watch No 8 J01MA09 Watch No 9 J01FA02 Watch No 10 J01RA04 Watch No 11 J01GA01 Watch No 12 13 J01CA16 Watch No 14 J01DH06 Watch No 15 J01XA02 Watch No 16 J01FA15 Watch No 17 J01CA17 Watch No 18 For peer review only 19 J01CA13 Watch No 20 J01GA01 Watch No 21 J01MA22 Watch No 22 J01XA01 Watch Yes 23 A07AA09 Watch Yes 24 25 26 27 28 29 30 31 32 33 34 35

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1 2 Reserve group antibiotics 3

4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 This group includes antibiotics and antibiotic classes that should be reserved for treatment of confirmed or suspected infections due to 6 7 multi-drug-resistant organisms. Reserve group antibiotics should be treated as “last resort” options. 8 Selected Reserve group antibiotics are listed as individual medicines on the WHO Model Lists of Essential Medicines when they have a 9 favourable risk-benefit profile and proven activity against “Critical Priority” or “High Priority” pathogens identified by the WHO Priority 10 Pathogens List1, notably carbapenem resistant Enterobacteriaceae. These antibiotics should be accessible, but their use should be 11 tailored to highly specific patients and settings, when all alternatives have failed or are not suitable. 12 13 These medicines could be protected and prioritized as key targets of national and international stewardship programs involving 14 monitoring and utilization reporting, to preserve their effectiveness.

15 1 16 WHO Priority Pathogens List 17 Antibiotic Class ATC code 18 Aztreonam ForMonobactams peer review onlyJ01DF01 19 Ceftaroline fosamil Fifth-generation cephalosporins J01DI02 20 Ceftazidime-avibactam Third-generation cephalosporins J01DD52 21 Ceftobiprole medocaril Fifth-generation cephalosporins J01DI01 22 23 Ceftolozane-tazobactam Fifth-generation cephalosporins J01DI54 24 Colistin Polymyxins J01XB01 25 Dalbavancin Glycopeptides J01XA04 26 Dalfopristin-quinupristin Streptogramins J01FG02 27 28 Daptomycin Lipopeptides J01XX09 29 Eravacycline Tetracyclines J01AA13 30 Faropenem Penems J01DI03 31 Fosfomycin (IV) Phosphonics J01XX01 32 Linezolid Oxazolidinones J01XX08 33 34 Meropenem-vaborbactam Carbapenems J01DH52 35 Minocycline (IV) Tetracyclines J01AA08

36 Omadacycline Tetracyclines to be assigned http://bmjopen.bmj.com/ 37 Oritavancin Glycopeptides J01XA05 38 Plazomicin Aminoglycosides to be assigned 39 40 Polymyxin B Polymyxins J01XB02 41 Tedizolid Oxazolidinones J01XX11 42 Telavancin Glycopeptides J01XA03 43 Tigecycline Glycylcyclines J01AA12

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1 Reserve group antibiotics 2 3

4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from This group includes antibiotics and antibiotic classes that should be reserved for treatment of confirmed or suspected infections due to5 6 multi-drug-resistant organisms. Reserve group antibiotics should be treated as “last resort” options.7 Selected Reserve group antibiotics are listed as individual medicines on the WHO Model Lists of Essential Medicines when they have a8 favourable risk-benefit profile and proven activity against “Critical Priority” or “High Priority” pathogens identified by the WHO Priority9 Pathogens List1, notably carbapenem resistant Enterobacteriaceae. These antibiotics should be accessible, but their use should be10 tailored to highly specific patients and settings, when all alternatives have failed or are not suitable.11 12 These medicines could be protected and prioritized as key targets of national and international stewardship programs involving13 monitoring and utilization reporting, to preserve their effectiveness. 14

1 15 WHO Priority Pathogens List 16 17 Category Listed on EML 2019 18 Reserve NoFor peer review only 19 Reserve No 20 Reserve Yes 21 Reserve No 22 23 Reserve No 24 Reserve Yes 25 Reserve No 26 Reserve No 27 28 Reserve No 29 Reserve No 30 Reserve No 31 Reserve Yes 32 Reserve Yes 33 34 Reserve Yes 35 Reserve No

36 Reserve No http://bmjopen.bmj.com/ 37 Reserve No 38 Reserve Yes 39 40 Reserve Yes 41 Reserve No 42 Reserve No 43 Reserve No

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1 2 Antibiotics not recommended 3 The use of the fixed-dose combinations of multiple broad-spectrum antibiotics listed here is 4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 not evidence-based, nor recommended in high-quality international guidelines. WHO does 6 not recommend their use in clinical practice. 7 8 9 Antibiotic 10 acetylspiramycin/metronidazole 11 amikacin/cefepime 12 amoxicillin/bacillus coagulans/cloxacillin 13 amoxicillin/bacillus coagulans/dicloxacillin 14 15 amoxicillin/clavulanic acid/lactic ferments 16 amoxicillin/clavulanic acid/lactobacillus acidophilus 17 amoxicillin/clavulanic acid/nimesulide 18 amoxicillin/cloxacillin For peer review only 19 amoxicillin/cloxacillin/lactic acid 20 21 amoxicillin/cloxacillin/lactobacillus acidophilus/serrapeptase 22 amoxicillin/cloxacillin/lactobacillus lactis 23 amoxicillin/cloxacillin/serrapeptase 24 amoxicillin/dicloxacillin 25 amoxicillin/dicloxacillin/saccharomyces boulardii 26 27 amoxicillin/flucloxacillin 28 amoxicillin/flucloxacillin/lactobacillus acidophilus 29 amoxicillin/metronidazole 30 amoxicillin/pivsulbactam 31 32 amoxicillin/sulbactam 33 ampicillin/bacillus coagulans/cloxacillin 34 ampicillin/cloxacillin 35 ampicillin/cloxacillin/lactobacillus acidophilus 36 ampicillin/cloxacillin/saccharomyces boulardii http://bmjopen.bmj.com/ 37 38 ampicillin/dicloxacillin 39 ampicillin/dicloxacillin/lactobacillus acidophilus 40 ampicillin/flucloxacillin 41 ampicillin/lidocaine/sulbactam 42 ampicillin/oxacillin 43 ampicillin/sultamicillin 44 on September 23, 2021 by guest. Protected copyright. 45 ascorbic acid/metamizole sodium/penicillin g /streptomycin 46 azithromycin/cefixime 47 azithromycin/cefixime/lactobacillus acidophilus 48 azithromycin/cefpodoxime proxetil 49 50 azithromycin/fluconazole/secnidazole 51 azithromycin/levofloxacin 52 azithromycin/ofloxacin 53 benzyl penicillin/streptomycin 54 bromelains/doxycycline/lactobacillus reuteri/lactobacillus rhamnosus/ornidazole 55 56 bromhexine/sulfamethoxazole/trimethoprim 57 cefaclor/clavulanic acid 58 cefadroxil/clavulanic acid 59 cefadroxil/trimethoprim 60 cefalexin/trimethoprim cefdinir/clavulanic acid

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1 2 cefepime/sulbactam 3 cefepime/tazobactam

4 cefixime/cefpodoxime proxetil BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 cefixime/clavulanic acid 6 7 cefixime/clavulanic acid/lactobacillus acidophilus 8 cefixime/cloxacillin 9 cefixime/cloxacillin/lactobacillus acidophilus 10 cefixime/dicloxacillin 11 cefixime/lactobacillus acidophilus/ofloxacin 12 13 cefixime/levofloxacin 14 cefixime/linezolid 15 cefixime/moxifloxacin 16 cefixime/ofloxacin 17 cefixime/ornidazole 18 For peer review only 19 cefoperazone/sulbactam 20 cefoperazone/tazobactam 21 cefotaxime/sulbactam 22 cefpodoxime proxetil/clavulanic acid 23 cefpodoxime proxetil/cloxacillin/lactobacillus acidophilus 24 25 cefpodoxime proxetil/dicloxacillin 26 cefpodoxime proxetil/dicloxacillin/lactobacillus acidophilus 27 cefpodoxime proxetil/levofloxacin 28 cefpodoxime proxetil/ofloxacin 29 30 cefpodoxime proxetil/sulbactam 31 ceftazidime/sulbactam 32 ceftazidime/tazobactam 33 ceftazidime/tobramicin 34 ceftibuten/clavulanic acid 35 ceftriaxone/sulbactam 36 http://bmjopen.bmj.com/ 37 ceftriaxone/tazobactam 38 ceftriaxone/vancomycin 39 cefuroxime axetil/clavulanic acid 40 cefuroxime axetil/linezolid 41 42 cefuroxime axetil/sulbactam 43 cefuroxime/clavulanic acid

44 cefuroxime/sulbactam on September 23, 2021 by guest. Protected copyright. 45 chloramphenicol/tetracycline 46 ciprofloxacin/metronidazole 47 48 ciprofloxacin/ornidazole 49 ciprofloxacin/tinidazole 50 doxycycline/tinidazole 51 erythromycin/sulfamethoxazole/trimethoprim 52 erythromycin/trimethoprim 53 54 fosfomycin/trimethoprim 55 gatifloxacin/ornidazole 56 kanamycin/penicillin g 57 levofloxacin/metronidazole 58 levofloxacin/ornidazole 59 60 meropenem/sodium/sulbactam meropenem/sulbactam

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1 2 metronidazole/norfloxacin 3 metronidazole/spiramycin

4 metronidazole/tetracycline BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 mezlocillin/sulbactam 6 7 ofloxacin/ornidazole 8 oleandomycin/tetracycline 9 piperacillin/sulbactam 10 rifampicin/trimethoprim 11 sulfadiazine/sulfamethoxazole/trimethoprim 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

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1 2 Antibiotics on 21st WHO Model List of Essential Medicines 2019 3

4 Section 6.2.1 Access group antibiotics BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Section 6.2.2 Watch group antibiotics 6 Section 6.2.3 Reserve group antibiotics 7 8 9 Antibiotic Class 10 Amikacin Aminoglycosides 11 Amoxicillin Penicillins 12 Amoxicillin/clavulanic Acid Beta lactam - beta lactamase inhibitor 13 Ampicillin Penicillins 14 15 Azithromycin Macrolides 16 Benzathine benzylpenicillin Penicillins 17 Benzylpenicillin Penicillins 18 Cefalexin For peerFirst-generation cephalosporins review only 19 Cefazolin First-generation cephalosporins 20 21 Cefixime Third-generation cephalosporins 22 Cefotaxime Third-generation cephalosporins 23 Ceftazidime Third-generation cephalosporins 24 Ceftazidime-avibactam Third-generation cephalosporins 25 26 Ceftriaxone Third-generation cephalosporins 27 Cefuroxime Second-generation cephalosporins 28 Chloramphenicol Amphenicols 29 Ciprofloxacin Fluoroquinolones 30 Clarithromycin Macrolides 31 32 Clindamycin Lincosamides 33 Cloxacillin Penicillins 34 Colistin Polymyxins 35 Doxycycline Tetracyclines 36 Fosfomycin (IV) Phosphonics http://bmjopen.bmj.com/ 37 38 Gentamicin Aminoglycosides 39 Linezolid Oxazolidinones 40 Meropenem Carbapenems 41 Meropenem-vaborbactam Carbapenems 42 Metronidazole Imidazoles 43 Metronidazole Imidazoles 44 on September 23, 2021 by guest. Protected copyright. 45 Nitrofurantoin Nitrofurantoin 46 Phenoxymethylpenicillin Penicillins 47 Piperacillin/tazobactam Beta lactam - beta lactamase inhibitor (anti-pseudomonal) 48 Plazomicin Aminoglycosides 49 50 Polymyxin B Polymyxins 51 Procaine benzylpenicillin Penicillins 52 Spectinomycin Aminocyclitols 53 Sulfamethoxazole/trimethoprim Trimethoprim - sulfonamide combinations 54 55 Vancomycin (IV) Glycopeptides 56 Vancomycin (oral) Glycopeptides 57 58 59 60

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1 Antibiotics on 21st WHO Model List of Essential Medicines2 2019 3

Section 6.2.1 Access group antibiotics 4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from Section 6.2.2 Watch group antibiotics 5 Section 6.2.3 Reserve group antibiotics 6 7 8 9 ATC code Category 10 J01GB06 Access 11 J01CA04 Access 12 J01CR02 Access 13 J01CA01 Access 14 15 J01FA10 Watch 16 J01CE08 Access 17 J01CE01 Access 18 J01DB01 Access For peer review only 19 J01DB04 Access 20 21 J01DD08 Watch 22 J01DD01 Watch 23 J01DD02 Watch 24 J01DD52 Reserve 25 26 J01DD04 Watch 27 J01DC02 Watch 28 J01BA01 Access 29 J01MA02 Watch 30 J01FA09 Watch 31 32 J01FF01 Access 33 J01CF02 Access 34 J01XB01 Reserve 35 J01AA02 Access 36 J01XX01 Reserve http://bmjopen.bmj.com/ 37 38 J01GB03 Access 39 J01XX08 Reserve 40 J01DH02 Watch 41 J01DH52 Reserve 42 J01XD01 Access 43 P01AB01 Access 44 on September 23, 2021 by guest. Protected copyright. 45 J01XE01 Access 46 J01CE02 Access 47 J01CR05 Watch 48 to be assigned Reserve 49 50 J01XB02 Reserve 51 J01CE09 Access 52 J01XX04 Access 53 J01EE01 Access 54 55 J01XA01 Watch 56 A07AA09 Watch 57 58 59 60

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1 2 Antibiotics on 7th WHO Model List of Essential Medicines for Children 2019 3

4 Section 6.2.1 Access group antibiotics BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from 5 Section 6.2.2 Watch group antibiotics 6 Section 6.2.3 Reserve group antibiotics 7 8 9 Antibiotic Class 10 Amikacin Aminoglycosides 11 Amoxicillin Penicillins 12 Amoxicillin/clavulanic Acid Beta lactam - beta lactamase inhibitor 13 Ampicillin Penicillins 14 15 Azithromycin Macrolides 16 Benzathine benzylpenicillin Penicillins 17 Benzylpenicillin Penicillins 18 Cefalexin For peerFirst-generation cephalosporins review only 19 Cefazolin First-generation cephalosporins 20 21 Cefixime Third-generation cephalosporins 22 Cefotaxime Third-generation cephalosporins 23 Ceftazidime Third-generation cephalosporins 24 Ceftazidime-avibactam Third-generation cephalosporins 25 26 Ceftriaxone Third-generation cephalosporins 27 Cefuroxime Second-generation cephalosporins 28 Chloramphenicol Amphenicols 29 Ciprofloxacin Fluoroquinolones 30 Clarithromycin Macrolides 31 32 Clindamycin Lincosamides 33 Cloxacillin Penicillins 34 Colistin Polymyxins 35 Doxycycline Tetracyclines 36 Fosfomycin (IV) Phosphonics http://bmjopen.bmj.com/ 37 38 Gentamicin Aminoglycosides 39 Linezolid Oxazolidinones 40 Meropenem Carbapenems 41 Metronidazole Imidazoles 42 Metronidazole Imidazoles 43 Nitrofurantoin Nitrofurantoin 44 on September 23, 2021 by guest. Protected copyright. 45 Phenoxymethylpenicillin Penicillins 46 Piperacillin/tazobactam Beta lactam - beta lactamase inhibitor (anti-pseudomonal) 47 Polymyxin B Polymyxins 48 49 Procaine benzylpenicillin Penicillins 50 Sulfamethoxazole/trimethoprim Trimethoprim - sulfonamide combinations 51 Vancomycin (IV) Glycopeptides 52 Vancomycin (oral) Glycopeptides 53 54 55 56 57 58 59 60

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1 Antibiotics on 7th WHO Model List of Essential Medicines 2for Children 2019 3

Section 6.2.1 Access group antibiotics 4 BMJ Open: first published as 10.1136/bmjopen-2020-038843 on 6 July 2020. Downloaded from Section 6.2.2 Watch group antibiotics 5 Section 6.2.3 Reserve group antibiotics 6 7 8 9 ATC code Category 10 J01GB06 Access 11 J01CA04 Access 12 J01CR02 Access 13 J01CA01 Access 14 15 J01FA10 Watch 16 J01CE08 Access 17 J01CE01 Access 18 J01DB01 Access For peer review only 19 J01DB04 Access 20 21 J01DD08 Watch 22 J01DD01 Watch 23 J01DD02 Watch 24 J01DD52 Reserve 25 26 J01DD04 Watch 27 J01DC02 Watch 28 J01BA01 Access 29 J01MA02 Watch 30 J01FA09 Watch 31 32 J01FF01 Access 33 J01CF02 Access 34 J01XB01 Reserve 35 J01AA02 Access 36 J01XX01 Reserve http://bmjopen.bmj.com/ 37 38 J01GB03 Access 39 J01XX08 Reserve 40 J01DH02 Watch 41 J01XD01 Access 42 P01AB01 Access 43 J01XE01 Access 44 on September 23, 2021 by guest. Protected copyright. 45 J01CE02 Access 46 J01CR05 Watch 47 J01XB02 Reserve 48 49 J01CE09 Access 50 J01EE01 Access 51 J01XA01 Watch 52 A07AA09 Watch 53 54 55 56 57 58 59 60

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