Evaluating antibiotic stewardship and healthcare-associated infections surveillance assisted by computer: protocol for an interrupted time series study

Alexandre Baudet, Nelly Agrinier, Alexandre Charmillon, Céline Pulcini, Alain Lozniewski, Nejla Aissa, Julie Lizon, Nathalie Thilly, Béatrice Demoré, Arnaud Florentin, Alexandre Baudet, Nelly Agrinier, Alexandre Charmillon, Céline Pulcini, Alain Lozniewski, Nejla Aissa, Julie Lizon, Nathalie Thilly, Béatrice Demoré, Arnaud Florentin

Abstract

Introduction: Antibiotic resistance is one of the most pressing health threats that mankind faces now and in the coming decades. Antibiotic resistance leads to longer hospital stays, higher medical costs and increased mortality. In order to tackle antibiotic resistance, we will implement in our tertiary care university hospital a computerised-decision support system (CDSS) facilitating antibiotic stewardship and an electronic surveillance software (ESS) facilitating infection prevention and control activities. We describe the protocol to evaluate the impact of the CDSS/ESS combination in adult inpatients.

Methods and analysis: We conduct a pragmatic, prospective, single-centre, before-after uncontrolled study with an interrupted time-series analysis 12 months before and 12 months after the introduction of the CDSS for antibiotic stewardship (APSS) and ESS for infection surveillance (ZINC). APSS and ZINC will assist, respectively, the antibiotic stewardship and the infection prevention and control teams of Nancy University Hospital (France). We will evaluate the impact of the CDSS/ESS on the antibiotic use in adult (≥18 years) inpatients (hospitalised ≥48 hours). The primary outcome is the prescription rate by all healthcare professionals from the hospital of all systemic antibiotics expressed in defined daily doses/1000 patients/month. Concurrently, we will assess the safety of the intervention, its impact on the appropriateness of antibiotic prescriptions and on additional precautions (isolation precautions) as recommended in guidelines, and on bacterial epidemiology (multidrug-resistant bacteria and Clostridioides difficile infections) in the hospital. Finally, we will evaluate the users' satisfaction and the cost of this intervention from the hospital perspective.

Ethics and dissemination: The protocol has been approved by the Ethics Committee of Nancy University Hospital and registered on the ClinicalTrials platform. Results will be disseminated through conferences' presentations and publications in peer-reviewed journals.

Trial registration number: NCT04976829.

Keywords: Infection control; Protocols & guidelines; clinical pharmacology; public health.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

References

    1. O’Neill J. Tackling drug-resistant infections globally: final report and recommendations, 2016. Available: [Accessed April 2021].
    1. European Centre for Disease Prevention and Control (ECDC) . European Medecines agency (EMA). the bacterial challenge: time to react, 2009. Available: [Accessed April 2021].
    1. Cassini A, Högberg LD, Plachouras D, et al. . Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European economic area in 2015: a population-level modelling analysis. Lancet Infect Dis 2019;19:56–66. 10.1016/S1473-3099(18)30605-4
    1. European center for disease prevention and control (ECDC). surveillance of antimicrobial resistance in Europe, annual report 2018. Stockholm: ECDC 2019.
    1. European Center for Disease Prevention and Control (ECDC), Santé Publique France. EARS-Net France . Contribution de la France Au réseau Européen de surveillance de la résistance bactérienne aux antibiotiques, 2002-2017. Available: [Accessed April 2021].
    1. Bell BG, Schellevis F, Stobberingh E, et al. . A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance. BMC Infect Dis 2014;14:13. 10.1186/1471-2334-14-13
    1. European Center for Disease Prevention and Control (ECDC) . Antimicrobial consumption in EU/EEA, annual epidemiological report for 2018. Stockholm: ECDC, 2019.
    1. World Health Organization (WHO) . Global action plan on antimicrobial resistance [Internet]. World Health Organization, 2015.
    1. Dyar OJ, Huttner B, Schouten J. Escmid Study Group for antimicrobial stewardshiP). What is antimicrobial stewardship? Clin Microbiol Infect 2017;23:793–8.
    1. Thursky K. Use of computerized decision support systems to improve antibiotic prescribing. Expert Rev Anti Infect Ther 2006;4:491–507. 10.1586/14787210.4.3.491
    1. de Bruin JS, Seeling W, Schuh C. Data use and effectiveness in electronic surveillance of healthcare associated infections in the 21st century: a systematic review. J Am Med Inform Assoc 2014;21:942–51. 10.1136/amiajnl-2013-002089
    1. Barlam TF, Cosgrove SE, Abbo LM, et al. . Implementing an antibiotic stewardship program: guidelines by the infectious diseases Society of America and the Society for healthcare epidemiology of America. Clin Infect Dis 2016;62:e51–77. 10.1093/cid/ciw118
    1. Nault V, Pepin J, Beaudoin M, et al. . Sustained impact of a computer-assisted antimicrobial stewardship intervention on antimicrobial use and length of stay. J Antimicrob Chemother 2017;72:933–40. 10.1093/jac/dkw468
    1. Mahamat A, MacKenzie FM, Brooker K, et al. . Impact of infection control interventions and antibiotic use on hospital MRSA: a multivariate interrupted time-series analysis. Int J Antimicrob Agents 2007;30:169–76. 10.1016/j.ijantimicag.2007.04.005
    1. Freeman R, Moore LSP, García Álvarez L, et al. . Advances in electronic surveillance for healthcare-associated infections in the 21st century: a systematic review. J Hosp Infect 2013;84:106–19. 10.1016/j.jhin.2012.11.031
    1. Russo PL, Shaban RZ, Macbeth D, et al. . Impact of electronic healthcare-associated infection surveillance software on infection prevention resources: a systematic review of the literature. J Hosp Infect 2018;99:1–7. 10.1016/j.jhin.2017.09.002
    1. Carracedo-Martinez E, Gonzalez-Gonzalez C, Teixeira-Rodrigues A, et al. . Computerized clinical decision support systems and antibiotic prescribing: a systematic review and meta-analysis. Clin Ther 2019;41:552–81. 10.1016/j.clinthera.2019.01.018
    1. Schweitzer VA, van Werkhoven CH, Rodríguez Baño J, et al. . Optimizing design of research to evaluate antibiotic stewardship interventions: consensus recommendations of a multinational Working group. Clin Microbiol Infect 2020;26:41–50. 10.1016/j.cmi.2019.08.017
    1. de Kraker MEA, Abbas M, Huttner B, et al. . Good epidemiological practice: a narrative review of appropriate scientific methods to evaluate the impact of antimicrobial stewardship interventions. Clin Microbiol Infect 2017;23:819–25. 10.1016/j.cmi.2017.05.019
    1. Centre Hospitalier Régional Universitaire de Nancy . Chiffres clés 2019, 2020. Available: [Accessed April 2021].
    1. Centers for Disease Control and Prevention . The core elements of hospital antibiotic stewardship programs, 2019, 2019. Available: [Accessed April 2021].
    1. World Health Organization (WHO) . Antimicrobial stewardship programmes in health-care facilities in low- and middle-income countries: a who practical toolkit. Geneva: who, 2019. Available: [Accessed April 2021].
    1. World Health Organization (WHO) . Infection prevention and control assessment framework at the facility level. Geneva: WHO, 2018. Available: [Accessed April 2021].
    1. World Health Organization (WHO) . Guidelines on core components of infection prevention and control programmes at the National and acute health care facility level. Geneva: who, 2016. Available: [Accessed April 2021].
    1. France SP. Enquête nationale de prévalence des infections nosocomiales et des traitements anti-infectieux en établissements de santé. mai-juin 2019;2017
    1. France SP. Surveillance de la consommation des antibiotiques – Réseau ATB-Raisin, France. Résultats 2017. 2019. Available: [Accessed April 2021].
    1. Bevilacqua S, Demoré B, Boschetti E, et al. . 15 years of antibiotic stewardship policy in the Nancy teaching hospital. Med Mal Infect 2011;41:532–9. 10.1016/j.medmal.2011.08.001
    1. Demoré B, Humbert P, Boschetti E, et al. . Evaluation of effects of an operational multidisciplinary team on antibiotic use in the medium to long term at a French university hospital. Int J Clin Pharm 2017;39:1061–9. 10.1007/s11096-017-0516-5
    1. Bevilacqua S, Demoré B, Erpelding M-L, et al. . Effects of an operational multidisciplinary team on hospital antibiotic use and cost in France: a cluster controlled trial. Int J Clin Pharm 2011;33:521–8. 10.1007/s11096-011-9499-9
    1. Agence nationale de sécurité Du médicament et des produits de santé. Liste des antibiotiques critiques. Actualisation 2016;2015
    1. AntibioEst . AntibioEst - Conseil, information, bon usage des antibiotiques. Available: [Accessed April 2021].
    1. Beaudoin M, Kabanza F, Nault V, et al. . An antimicrobial prescription surveillance system that learns from experience. AI Mag 2014;35:15. 10.1609/aimag.v35i1.2500
    1. LUMED . ZINC Monitoring System: Prevent & Control Healthcare Related Infections. Available: [Accessed April 2021].
    1. Haut Conseil de Santé Publique (HCSP) . Actualisation des recommandations relatives La maîtrise de la diffusion des bactéries hautement résistantes aux antibiotiques émergentes (BHRe), 2019. Available: [Accessed April 2021].
    1. Société Français d’Hygiène Hospitalière (SF2H) . Recommandations nationales - Prévention de la transmission croisée : précautions complémentaires contact. Consensus formalisé d’experts. HygièneS, 2009. Available: [Accessed April 2021].
    1. Société Français d’Hygiène Hospitalière (SF2H) . Recommandations nationales - Prévention de la transmission croisée par voie respiratoire : Air ou Gouttelettes. Recommandations pour la pratique clinique (RPC). HygièneS, 2013. Available: [Accessed April 2021].
    1. Zhang F, Wagner AK, Ross-Degnan D. Simulation-Based power calculation for designing interrupted time series analyses of health policy interventions. J Clin Epidemiol 2011;64:1252–61. 10.1016/j.jclinepi.2011.02.007
    1. Ramsay CR, Matowe L, Grilli R, et al. . Interrupted time series designs in health technology assessment: lessons from two systematic reviews of behavior change strategies. Int J Technol Assess Health Care 2003;19:613–23. 10.1017/S0266462303000576
    1. Wagner AK, Soumerai SB, Zhang F, et al. . Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 2002;27:299–309. 10.1046/j.1365-2710.2002.00430.x
    1. Chabaud A, Jouzeau A, Dugravot L. Antibiotic use and antibiotic resistance in French healthcare facilities in 2020: data from the National spares network. Bull Epidémiol Hebd 2021;18:342–50.
    1. Corbin JM, Strauss A. Grounded theory research: procedures, canons, and evaluative criteria. Qual Sociol 1990;13:3–21. 10.1007/BF00988593
    1. Penfold RB, Zhang F. Use of interrupted time series analysis in evaluating health care quality improvements. Acad Pediatr 2013;13:S38–44. 10.1016/j.acap.2013.08.002
    1. Kontopantelis E, Doran T, Springate DA, et al. . Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. BMJ 2015;350:h2750. 10.1136/bmj.h2750
    1. Davey P, Marwick CA, Scott CL, et al. . Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev 2017;2:CD003543. 10.1002/14651858.CD003543.pub4
    1. Cochrane Effective Practice and Organisation of Care (EPOC) . What study designs can be considered for inclusion in an EPOC review and what should they be called? Cochrane effective practice and organisation of care, 2017. Available: [Accessed April 2021].
    1. Stone SP, Cooper BS, Kibbler CC, et al. . The ORION statement: guidelines for transparent reporting of outbreak reports and intervention studies of nosocomial infection. Lancet Infect Dis 2007;7:282–8. 10.1016/S1473-3099(07)70082-8
    1. Bernal JL, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol 2017;46:348–55. 10.1093/ije/dyw098
    1. Lopez Bernal J, Cummins S, Gasparrini A. The use of controls in interrupted time series studies of public health interventions. Int J Epidemiol 2018;47:2082–93. 10.1093/ije/dyy135
    1. Abeysinghe T, Balasooriya U, Tsui A. Small-Sample forecasting regression or Arima models? J Quant Econ 2003;1:103–13. 10.1007/BF03404652
    1. Durbin J, Watson GS. Testing for serial correlation in least squares regression. I. Biometrika 1950;37:409–28.
    1. Durbin J, Watson GS. Testing for serial correlation in least squares regression. II. Biometrika 1951;38:159–78. 10.1093/biomet/38.1-2.159
    1. Lopez Bernal J, Soumerai S, Gasparrini A. A methodological framework for model selection in interrupted time series studies. J Clin Epidemiol 2018;103:82–91. 10.1016/j.jclinepi.2018.05.026

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