Decreasing ICU-associated Clostridioides difficile infection through fluoroquinolone restriction, the FIRST trial: a study protocol

Nasia Safdar, Vishala Parmasad, Roger Brown, Pascale Carayon, Alexander Lepak, John C O'Horo, Lucas Schulz, Nasia Safdar, Vishala Parmasad, Roger Brown, Pascale Carayon, Alexander Lepak, John C O'Horo, Lucas Schulz

Abstract

Introduction: Clostridioides difficile infection (CDI) is one of the most common healthcare-associated infections in the USA, having high incidence in intensive care units (ICU). Antibiotic use increases risk of CDI, with fluoroquinolones (FQs) particularly implicated. In healthcare settings, antibiotic stewardship (AS) and infection control interventions are effective in CDI control, but there is little evidence regarding the most effective AS interventions. Preprescription authorisation (PPA) restricting FQs is a potentially promising AS intervention to reduce CDI. The FQ Restriction for the Prevention of CDI (FIRST) trial will evaluate the effectiveness of an FQ PPA intervention in reducing CDI rates in adult ICUs compared with preintervention care, and evaluate implementation effectiveness using a human-factors and systems engineering model.

Methods and analysis: This is a multisite, stepped-wedge, cluster, effectiveness-implementation clinical trial. The trial will take place in 12 adult medical-surgical ICUs with ≥10 beds, using Epic as electronic health record (EHR) and pre-existing AS programmes. Sites will receive facilitated implementation support over the 15-month trial period, succeeded by 9 months of follow-up. The intervention comprises a clinical decision support system for FQ PPA, integrated into the site EHRs. Each ICU will be considered a single site and all ICU admissions included in the analysis. Clinical data will be extracted from EHRs throughout the trial and compared with the corresponding pretrial period, which will constitute the baseline for statistical analysis. Outcomes will include ICU-onset CDI rates, FQ days of therapy (DOT), alternative antibiotic DOT, average length of stay and hospital mortality. The study team will also collect implementation data to assess implementation effectiveness using the Systems Engineering Initiative for Patient Safety model.

Ethics and dissemination: The trial was approved by the Institutional Review Board at the University of Wisconsin-Madison (2018-0852-CP015). Results will be made available to participating sites, funders, infectious disease societies, critical care societies and other researchers.

Trial registration number: NCT03848689.

Keywords: adult intensive & critical care; infection control; infectious diseases; internal medicine; medical education & training; qualitative research.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Schematic depiction of the trial design and procedures. CDI, Clostridioides difficile infection; EHR, electronic health record; FQ, fluoroquinolone; IRB, Institutional Review Board; PPA, preprescription authorisation.
Figure 2
Figure 2
SEIPS framework: FQ PPA implementation in acute care settings. Abx, antibiotics; CDI, Clostridioides difficile infection; FQ, fluoroquinolone; HAI, healthcare-associated infection; ID, infectious disease; PPA, preprescription authorisation; SEIPS, Systems Engineering Initiative for Patient Safety.

References

    1. Magill SS, Edwards JR, Fridkin SK, et al. . Survey of health care-associated infections. N Engl J Med 2014;370:2542–3. 10.1056/NEJMc1405194
    1. Balsells E, Shi T, Leese C, et al. . Global burden of Clostridium difficile infections: a systematic review and meta-analysis. J Glob Health 2019;9:010407. 10.7189/jogh.09.010407
    1. Lessa FC, Winston LG, McDonald LC, et al. . Burden of Clostridium difficile infection in the United States. N Engl J Med 2015;372:825–34. 10.1056/NEJMoa1408913
    1. Dubberke ER, Olsen MA. Burden of Clostridium difficile on the healthcare system. Clin Infect Dis 2012;55 Suppl 2:S88–92. 10.1093/cid/cis335
    1. Bloomfield LE, Riley TV. Epidemiology and risk factors for community-associated Clostridium difficile infection: a narrative review. Infect Dis Ther 2016;5:231–51. 10.1007/s40121-016-0117-y
    1. Eze P, Balsells E, Kyaw MH, et al. . Risk factors for Clostridium difficile infections - an overview of the evidence base and challenges in data synthesis. J Glob Health 2017;7:010417. 10.7189/jogh.07.010417
    1. Crowther GS, Wilcox MH. Antibiotic therapy and Clostridium difficile infection - primum non nocere - first do no harm. Infect Drug Resist 2015;8:333–7. 10.2147/IDR.S87224
    1. Gerding DN, File TM, McDonald LC. Diagnosis and treatment of Clostridium difficile infection. Infect Dis Clin Pract 2016;24:3–10. 10.1097/IPC.0000000000000350
    1. Cohen SH, Gerding DN, Johnson S, et al. . Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the Society for healthcare epidemiology of America (SheA) and the infectious diseases Society of America (IDSA). Infect Control Hosp Epidemiol 2010;31:431–55. 10.1086/651706
    1. Weiner LM, Fridkin SK, Aponte-Torres Z, et al. . Vital Signs: Preventing Antibiotic-Resistant Infections in Hospitals - United States, 2014. Am J Transplant 2016;16:2224–30. 10.1111/ajt.13893
    1. Fridkin S, Baggs J, Fagan R, et al. . Vital signs: improving antibiotic use among hospitalized patients. MMWR Morb Mortal Wkly Rep 2014;63:194–200.
    1. Centers for Disease Control and Prevention (CDC) . Vital signs: preventing Clostridium difficile infections. MMWR Morb Mortal Wkly Rep 2012;61:157–62.
    1. Antimicrobial Stewardship . Society for healthcare epidemiology of America, 2021.
    1. Louh IK, Greendyke WG, Hermann EA, et al. . Clostridium difficile infection in acute care hospitals: systematic review and best practices for prevention. Infect Control Hosp Epidemiol 2017;38:476–82. 10.1017/ice.2016.324
    1. Wagner B, Filice GA, Drekonja D, et al. . Antimicrobial stewardship programs in inpatient hospital settings: a systematic review. Infect Control Hosp Epidemiol 2014;35:1209–28. 10.1086/599172
    1. Feazel LM, Malhotra A, Perencevich EN, et al. . Effect of antibiotic stewardship programmes on Clostridium difficile incidence: a systematic review and meta-analysis. J Antimicrob Chemother 2014;69:1748–54. 10.1093/jac/dku046
    1. Davey P, Marwick CA, Scott CL. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev 2017;2:Cd003543. 10.1002/14651858.CD003543.pub4
    1. Hsu J, Abad C, Dinh M, et al. . Prevention of endemic healthcare-associated Clostridium difficile infection: reviewing the evidence. Am J Gastroenterol 2010;105:2327–39. 10.1038/ajg.2010.254
    1. Wenzler E, Mulugeta SG, Danziger LH. The antimicrobial stewardship approach to combating Clostridium difficile. Antibiotics 2015;4:198–215. 10.3390/antibiotics4020198
    1. Moffa MA, Walsh TL, Tang A, et al. . Impact of an antimicrobial stewardship program on healthcare-associated Clostridium difficile rates at a community-based teaching hospital. J Infect Prev 2018;19:191–4. 10.1177/1757177418767760
    1. Moehring RW, Anderson DJ, Cochran RL, et al. . Expert consensus on metrics to assess the impact of patient-level antimicrobial stewardship interventions in acute-care settings. Clin Infect Dis 2017;64:377–83. 10.1093/cid/ciw787
    1. Baur D, Gladstone BP, Burkert F, et al. . Effect of antibiotic stewardship on the incidence of infection and colonisation with antibiotic-resistant bacteria and Clostridium difficile infection: a systematic review and meta-analysis. Lancet Infect Dis 2017;17:990–1001. 10.1016/S1473-3099(17)30325-0
    1. White AC, Atmar RL, Wilson J, et al. . Effects of requiring prior authorization for selected antimicrobials: expenditures, susceptibilities, and clinical outcomes. Clin Infect Dis 1997;25:230–9. 10.1086/514545
    1. Buising KL, Thursky KA, Robertson MB, et al. . Electronic antibiotic stewardship--reduced consumption of broad-spectrum antibiotics using a computerized antimicrobial approval system in a hospital setting. Journal of Antimicrobial Chemotherapy 2008;62:608–16. 10.1093/jac/dkn218
    1. Pakyz AL, Oinonen M, Polk RE. Relationship of carbapenem restriction in 22 university teaching hospitals to carbapenem use and carbapenem-resistant Pseudomonas aeruginosa. Antimicrob Agents Chemother 2009;53:1983–6. 10.1128/AAC.01535-08
    1. Metjian TA, Prasad PA, Kogon A, et al. . Evaluation of an antimicrobial stewardship program at a pediatric teaching hospital. Pediatr Infect Dis J 2008;27:106–11. 10.1097/INF.0b013e318158603a
    1. Lewis GJ, Fang X, Gooch M, et al. . Decreased Resistance of Pseudomonas aeruginosa with Restriction of Ciprofloxacin in a Large Teaching Hospital’s Intensive Care and Intermediate Care Units. Infect Control Hosp Epidemiol 2012;33:368–73. 10.1086/664763
    1. Carling P, Fung T, Killion A, et al. . Favorable impact of a multidisciplinary antibiotic management program conducted during 7 years. Infect Control Hosp Epidemiol 2003;24:699–706. 10.1086/502278
    1. DiazGranados CA. Prospective audit for antimicrobial stewardship in intensive care: impact on resistance and clinical outcomes. Am J Infect Control 2012;40:526–9. 10.1016/j.ajic.2011.07.011
    1. Elligsen M, Walker SAN, Pinto R, et al. . Audit and feedback to reduce broad-spectrum antibiotic use among intensive care unit patients: a controlled interrupted time series analysis. Infect Control Hosp Epidemiol 2012;33:354–61. 10.1086/664757
    1. Newland JG, Stach LM, De Lurgio SA, et al. . Impact of a Prospective-Audit-With-Feedback antimicrobial stewardship program at a children's Hospital. J Pediatric Infect Dis Soc 2012;1:179–86. 10.1093/jpids/pis054
    1. Di Pentima MC, Chan S, Hossain J. Benefits of a pediatric antimicrobial stewardship program at a children’s Hospital. Pediatrics 2011;128:1062–70. 10.1542/peds.2010-3589
    1. van Kasteren MEE, Mannien J, Kullberg B-J, et al. . Quality improvement of surgical prophylaxis in Dutch hospitals: evaluation of a multi-site intervention by time series analysis. J Antimicrob Chemother 2005;56:1094–102. 10.1093/jac/dki374
    1. Cosgrove SE, Seo SK, Bolon MK, et al. . Evaluation of postprescription review and feedback as a method of promoting rational antimicrobial use: a multicenter intervention. Infect Control Hosp Epidemiol 2012;33:374–80. 10.1086/664771
    1. Talpaert MJ, Gopal Rao G, Cooper BS, et al. . Impact of guidelines and enhanced antibiotic stewardship on reducing broad-spectrum antibiotic usage and its effect on incidence of Clostridium difficile infection. J Antimicrob Chemother 2011;66:2168–74. 10.1093/jac/dkr253
    1. Fridkin SK, Lawton R, Edwards JR, et al. . Monitoring antimicrobial use and resistance: comparison with a national benchmark on reducing vancomycin use and vancomycin-resistant enterococci. Emerg Infect Dis 2002;8:702–7. 10.3201/eid0807.010465
    1. Kazakova SV, Baggs J, McDonald LC, et al. . Association between antibiotic use and Hospital-onset Clostridioides difficile infection in US acute care hospitals, 2006-2012: an ecologic analysis. Clin Infect Dis 2020;70:11–18. 10.1093/cid/ciz169
    1. Garg AX, Adhikari NKJ, McDonald H, et al. . Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005;293:1223–38. 10.1001/jama.293.10.1223
    1. Lobach DF, Hammond WE. Computerized decision support based on a clinical practice guideline improves compliance with care standards. Am J Med 1997;102:89–98. 10.1016/S0002-9343(96)00382-8
    1. Patterson BW, Pulia MS, Ravi S, et al. . Scope and influence of electronic health Record-Integrated clinical decision support in the emergency department: a systematic review. Ann Emerg Med 2019;74:285–96. 10.1016/j.annemergmed.2018.10.034
    1. Carayon P, Schoofs Hundt A, Karsh B-T, et al. . Work system design for patient safety: the SEIPS model. Qual Saf Health Care 2006;15 Suppl 1:i50–8. 10.1136/qshc.2005.015842
    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. Holden RJ, Carayon P, Gurses AP, et al. . SEIPS 2.0: a human factors framework for studying and improving the work of healthcare professionals and patients. Ergonomics 2013;56:1669–86. 10.1080/00140139.2013.838643
    1. Eisenhardt KM. Building theories from case study research. Business and management research methodologies: multi-method research and case studies 2006:218–40.
    1. Yin RK. Enhancing the quality of case studies in health services research. Health Serv Res 1999;34:1209–24.
    1. Carayon P, Kianfar S, Li Y, et al. . A systematic review of mixed methods research on human factors and ergonomics in health care. Appl Ergon 2015;51:291–321. 10.1016/j.apergo.2015.06.001
    1. Creswell JW. Research design : qualitative, quantitative, and mixed methods approaches. 3rd ed. Thousand Oaks, CA: Sage Publications, 2009.
    1. Miles MB, Huberman AM, Saldana J. Qualitative Data Analysis - A Methods Sourcebook. 3rd ed. Sage Publications, 2014.
    1. Chan A-W, Tetzlaff JM, Gøtzsche PC, et al. . Spirit 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ 2013;346:e7586. 10.1136/bmj.e7586
    1. Huynh AK, Lee ML, Farmer MM, et al. . Application of a nonrandomized stepped wedge design to evaluate an evidence-based quality improvement intervention: a proof of concept using simulated data on patient-centered medical homes. BMC Med Res Methodol 2016;16:143. 10.1186/s12874-016-0244-x
    1. Karsh B-T. Beyond usability: designing effective technology implementation systems to promote patient safety. Qual Saf Health Care 2004;13:388–94. 10.1136/qshc.2004.010322
    1. Xie A, Carayon P, Cox ED. Application of participatory ergonomics to the redesign of the family-centered rounds process. Ergonomics 2015:1–49.
    1. Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci 2013;8:139. 10.1186/1748-5908-8-139
    1. Powell BJ, Waltz TJ, Chinman MJ, et al. . A refined compilation of implementation strategies: results from the expert recommendations for implementing change (ERIC) project. Implement Sci 2015;10:21. 10.1186/s13012-015-0209-1
    1. Powell BJ, McMillen JC, Proctor EK, et al. . A compilation of strategies for implementing clinical innovations in health and mental health. Med Care Res Rev 2012;69:123–57. 10.1177/1077558711430690
    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. MLwiN Version 2.02 . Centre for multilevel modelling, 2005.
    1. Lee H, Munk T. Using regression discontinuity design for program evaluation, 2008.
    1. Linden A. Conducting interrupted time-series analysis for single- and multiple-group comparisons. Stata J 2015;15:480–500. 10.1177/1536867X1501500208
    1. Yin RK. Case study research: design and methods. 2nd ed. Thousand Oaks, CA: Sage, 1994.
    1. Dowding D. Best practices for mixed methods research in the health sciences John W. Creswell, Ann Carroll Klassen, Vicki L. Plano Clark, Katherine Clegg Smith for the office of behavioral and social sciences research; qualitative methods overview Jo Moriarty. Qualitative Social Work 2013;12:541–5. 10.1177/1473325013493540a
    1. Donaldson MS, Mohr JJ. (US) IoM. exploring innovation and quality improvement in health care Micro-Systems: a Cross-Case analysis, 2001.
    1. NHSN . Multidrug-Resistant Organism & Clostridium difficile Infection (MDRO/CDI) Module, 2017.
    1. Kellum JA, Lameire N, Aspelin P. Kidney disease: improving global outcomes (KDIGO) acute kidney injury work group. KDIGO clinical practice guideline for acute kidney injury. Kidney International Supplements 2012;2:1–138.
    1. D'Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inf Med 1993;32:382–7.
    1. D'Hoore W, Bouckaert A, Tilquin C. Practical considerations on the use of the Charlson comorbidity index with administrative data bases. J Clin Epidemiol 1996;49:1429–33. 10.1016/S0895-4356(96)00271-5
    1. Knaus WA, Zimmerman JE, Wagner DP, et al. . APACHE-acute physiology and chronic health evaluation: a physiologically based classification system. Crit Care Med 1981;9:591–7. 10.1097/00003246-198108000-00008
    1. Wagner DP, Knaus WA, Draper EA. Statistical validation of a severity of illness measure. Am J Public Health 1983;73:878–84. 10.2105/AJPH.73.8.878
    1. Tamma PD, Avdic E, Keenan JF, et al. . What is the more effective antibiotic stewardship intervention: Preprescription authorization or Postprescription review with feedback? Clin Infect Dis 2017;64:537–43. 10.1093/cid/ciw780
    1. NIH Grants Policy Statement . National Institutes of health, 2021.
    1. The AHRQ Safety Program for Improving Antibiotic Use . Available:

Source: PubMed

Sponsorer og samarbeidspartnere

Medisinsk tilstand

Legemiddelintervensjoner

3
Abonnere