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      Impact of interactive computerised decision support for hospital antibiotic use (COMPASS): an open-label, cluster-randomised trial in three Swiss hospitals

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          Abstract

          Background

          Computerised decision-support systems (CDSSs) for antibiotic stewardship could help to assist physicians in the appropriate prescribing of antibiotics. However, high-quality evidence for their effect on the quantity and quality of antibiotic use remains scarce. The aim of our study was to assess whether a computerised decision support for antimicrobial stewardship combined with feedback on prescribing indicators can reduce antimicrobial prescriptions for adults admitted to hospital.

          Methods

          The Computerised Antibiotic Stewardship Study (COMPASS) was a multicentre, cluster-randomised, parallel-group, open-label superiority trial that aimed to assess whether a multimodal computerised antibiotic-stewardship intervention is effective in reducing antibiotic use for adults admitted to hospital. After pairwise matching, 24 wards in three Swiss tertiary-care and secondary-care hospitals were randomised (1:1) to the CDSS intervention or to standard antibiotic stewardship measures using an online random sequence generator. The multimodal intervention consisted of a CDSS providing support for choice, duration, and re-evaluation of antimicrobial therapy, and feedback on antimicrobial prescribing quality. The primary outcome was overall systemic antibiotic use measured in days of therapy per admission, using adjusted-hurdle negative-binomial mixed-effects models. The analysis was done by intention to treat and per protocol. The study was registered with ClinicalTrials.gov (identifier NCT03120975).

          Findings

          24 clusters (16 at Geneva University Hospitals and eight at Ticino Regional Hospitals) were eligible and randomly assigned to control or intervention between Oct 1, 2018, and Dec 31, 2019. Overall, 4578 (40·2%) of 11 384 admissions received antibiotic therapy in the intervention group and 4142 (42·8%) of 9673 in the control group. The unadjusted overall mean days of therapy per admission was slightly lower in the intervention group than in the control group (3·2 days of therapy per admission, SD 6·2, vs 3·5 days of therapy per admission, SD 6·8; p<0·0001), and was similar among patients receiving antibiotics (7·9 days of therapy per admission, SD 7·6, vs 8·1 days of therapy per admission, SD 8·4; p=0·50). After adjusting for confounders, there was no statistically significant difference between groups for the odds of an admission receiving antibiotics (odds ratio [OR] for intervention vs control 1·12, 95% CI 0·94–1·33). For admissions with antibiotic exposure, days of therapy per admission were also similar (incidence rate ratio 0·98, 95% CI 0·90–1·07). Overall, the CDSS was used at least once in 3466 (75·7%) of 4578 admissions with any antibiotic prescription, but from the first day of antibiotic treatment for only 1602 (58·9%) of 2721 admissions in Geneva. For those for whom the CDSS was not used from the first day, mean time to use of CDSS was 8·9 days. Based on the manual review of 1195 randomly selected charts, transition from intravenous to oral therapy was significantly more frequent in the intervention group after adjusting for confounders (154 [76·6%] of 201 vs 187 [87%] of 215, +10·4%; OR 1·9, 95% CI 1·1–3·3). Consultations by infectious disease specialists were less frequent in the intervention group (388 [13·4%] of 2889) versus the control group (405 [16·9%] of 2390; OR 0·84, 95% CI 0·59–1·25).

          Interpretation

          An integrated multimodal computerised antibiotic stewardship intervention did not significantly reduce overall antibiotic use, the primary outcome of the study. Contributing factors were probably insufficient uptake, a setting with relatively low antibiotic use at baseline, and delays between ward admission and first CDSS use.

          Funding

          Swiss National Science Foundation.

          Translations

          For the French and Italian translations of the abstract see Supplementary Materials section.

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          Most cited references31

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          Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis

          (2022)
          Summary Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. Methods We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. Findings On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. Interpretation To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
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            Implementing an Antibiotic Stewardship Program: Guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America.

            Evidence-based guidelines for implementation and measurement of antibiotic stewardship interventions in inpatient populations including long-term care were prepared by a multidisciplinary expert panel of the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. The panel included clinicians and investigators representing internal medicine, emergency medicine, microbiology, critical care, surgery, epidemiology, pharmacy, and adult and pediatric infectious diseases specialties. These recommendations address the best approaches for antibiotic stewardship programs to influence the optimal use of antibiotics.
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              A conceptual framework for implementation fidelity

              Background Implementation fidelity refers to the degree to which an intervention or programme is delivered as intended. Only by understanding and measuring whether an intervention has been implemented with fidelity can researchers and practitioners gain a better understanding of how and why an intervention works, and the extent to which outcomes can be improved. Discussion The authors undertook a critical review of existing conceptualisations of implementation fidelity and developed a new conceptual framework for understanding and measuring the process. The resulting theoretical framework requires testing by empirical research. Summary Implementation fidelity is an important source of variation affecting the credibility and utility of research. The conceptual framework presented here offers a means for measuring this variable and understanding its place in the process of intervention implementation.
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                Author and article information

                Journal
                Lancet Infect Dis
                Lancet Infect Dis
                The Lancet. Infectious Diseases
                Elsevier Ltd.
                1473-3099
                1474-4457
                20 July 2022
                October 2022
                20 July 2022
                : 22
                : 10
                : 1493-1502
                Affiliations
                [a ]Division of Infectious Diseases, Geneva University Hospital and Faculty of Medicine, University of Geneva, Geneva, Switzerland
                [b ]Division of Infection Control, Geneva University Hospital and Faculty of Medicine, University of Geneva, Geneva, Switzerland
                [c ]Medical Directorate, Geneva University Hospital and Faculty of Medicine, University of Geneva, Geneva, Switzerland
                [d ]Division of Clinical Informatics, Ente Ospdaliero Cantonale, Bellinzona, Switzerland
                [e ]Division of Infectious Diseases, Ospedale San Giovanni, Ente Ospdaliero Cantonale, Bellinzona, Switzerland
                [f ]Division of Infectious Diseases, Ospedale Regionale di Lugano, Ente Ospedaliero Cantonale and University of Southern Switzerland, Lugano, Switzerland
                [g ]Division of Informatics, Geneva University Hospital, Geneva, Switzerland
                [h ]Division of Internal Medicine, Geneva University Hospital, Geneva, Switzerland
                [i ]Division of Geriatrics, Geneva University Hospital, Geneva, Switzerland
                Author notes
                [* ]Correspondence to: Dr Gaud Catho, Division of Infectious Diseases, Geneva University Hospitals and Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
                [†]

                Members of the COMPASS study group are listed at the end of the manuscript

                Article
                S1473-3099(22)00308-5
                10.1016/S1473-3099(22)00308-5
                9491854
                35870478
                d825459d-3129-4859-99c7-aa6b9d665954
                © 2022 Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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                Infectious disease & Microbiology
                Infectious disease & Microbiology

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