Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-30T20:06:11.110Z Has data issue: false hasContentIssue false
  • English
  • Français

Design, implementation, and analysis considerations for cluster-randomized trials in infection control and hospital epidemiology: A systematic review

Published online by Cambridge University Press:  02 May 2019

Lyndsay M. O’Hara ,
Natalia Blanco Open the ORCID record for Natalia Blanco [Opens in a new window] ,
Surbhi Leekha ,
Kristen A. Stafford ,
Gerard P. Slobogean ,
Emilie Ludeman ,
Anthony D. Harris  and
for the CDC Prevention Epicenters Program
Lyndsay M. O’Hara
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Natalia Blanco
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Surbhi Leekha
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Kristen A. Stafford
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Gerard P. Slobogean
Affiliation:
Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, Maryland
Emilie Ludeman
Affiliation:
University of Maryland Health Sciences and Human Services Library, Baltimore, Maryland
Anthony D. Harris*
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
for the CDC Prevention Epicenters Program
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, Maryland University of Maryland Health Sciences and Human Services Library, Baltimore, Maryland
*
Author for correspondence: Anthony D. Harris, Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background:

In cluster-randomized trials (CRT), groups rather than individuals are randomized to interventions. The aim of this study was to present critical design, implementation, and analysis issues to consider when planning a CRT in the healthcare setting and to synthesize characteristics of published CRT in the field of healthcare epidemiology.

Methods:

A systematic review was conducted to identify CRT with infection control outcomes.

Results:

We identified the following 7 epidemiological principles: (1) identify design type and justify the use of CRT; (2) account for clustering when estimating sample size and report intraclass correlation coefficient (ICC)/coefficient of variation (CV); (3) obtain consent; (4) define level of inference; (5) consider matching and/or stratification; (6) minimize bias and/or contamination; and (7) account for clustering in the analysis. Among 44 included studies, the most common design was CRT with crossover (n = 15, 34%), followed by parallel CRT (n = 11, 25%) and stratified CRT (n = 7, 16%). Moreover, 22 studies (50%) offered justification for their use of CRT, and 20 studies (45%) demonstrated that they accounted for clustering at the design phase. Only 15 studies (34%) reported the ICC, CV, or design effect. Also, 15 studies (34%) obtained waivers of consent, and 7 (16%) sought consent at the cluster level. Only 17 studies (39%) matched or stratified at randomization, and 10 studies (23%) did not report efforts to mitigate bias and/or contamination. Finally, 29 studies (88%) accounted for clustering in their analyses.

Conclusions:

We must continue to improve the design and reporting of CRT to better evaluate the effectiveness of infection control interventions in the healthcare setting.

Type
Review
Information
Infection Control & Hospital Epidemiology , Volume 40 , Issue 6 , June 2019 , pp. 686 - 692
Copyright
© 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Donner, A, Klar, N. Design and Analysis of Cluster Randomization Trials in Health Research. London: Arnold, 2000.Google Scholar
Moberg, J, Kramer, M. A brief history of the cluster randomized trial design. JLL Bulletin: Commentaries on the history of treatment evaluation. James Lind Library website. http://www.jameslindlibrary.org/articles/a-brief-history-of-the-cluster-randomized-trial-design/. Published 2015. Accessed March 8, 2019.Google Scholar
Hayes, RJ, Alexander, ND, Bennett, S, Cousens, SN. Design and analysis issues in cluster-randomized trials of interventions against infectious diseases. Statist Method Med Res 2000;9:95–116.CrossRefGoogle ScholarPubMed
Wolkewitz, M, Barnett, AG, Martinez, MP, Frank, U, Schumacher, M, IMPLEMENT Study Group. Interventions to control nosocomial infections: study designs and statistical issues. J Hosp Infect 2014;86:77–82.CrossRefGoogle Scholar
Simpson, JM, Klar, N, Donnor, A. Accounting for cluster randomization: a review of primary prevention trials, 1990 through 1993. Am J Pub Health 1995;85:1378–1383.CrossRefGoogle ScholarPubMed
Donner, A, Klar, N. Pitfalls of and controversies in cluster randomization trials. Am J Pub Health 2004;94:416–422.CrossRefGoogle ScholarPubMed
Arnup, SJ, McKenzie, JE, Hemming, K, Pilcher, D, Forbes, AB. Understanding the cluster randomized crossover design: a graphical illustration of the components of variation and a sample size tutorial. Trials 2007;18:381.CrossRefGoogle Scholar
Rothman, KJ, Greenland, S, Lash, TL. Modern Epidemiology, Third Edition. Philadelphia: Lippincott, Williams & Wilkins; 2008.Google Scholar
Donner, A, Birkett, N, Buck, C. Randomization by cluster sample size requirements and analysis. Am J Epidemiol 1981;114:906–914.CrossRefGoogle ScholarPubMed
Rutterford, C, Copas, A, Eldridge, S. Methods for sample size determination in cluster randomized trials. Int J Epidemiol 2015;44:1051–1067.CrossRefGoogle ScholarPubMed
Sim, J, Dawson, A. Informed consent and cluster-randomized trials. Am J Pub Health 2012;102:480–485.CrossRefGoogle ScholarPubMed
Edwards, SJL, Braunholz, DA. Lilford, RJ, et al. Ethical issues in the design and conduct of cluster randomized controlled trials. BMJ 1999;318:1407–1409.CrossRefGoogle Scholar
Martin, DC, Diehr, P, Perrin, EB, Koepsell, TD. The effect of matching on the power of randomized community intervention studies. Statist Med 1993;12:329–338.CrossRefGoogle ScholarPubMed
Puffer, S, Torgerson, D, Watson, J. Evidence for risk of bias in cluster randomised trials: review of recent trials published in three general medical journals. BMJ 2003;327:785–789.CrossRefGoogle ScholarPubMed
Fitzmaurice, GM, Laird, NM, Ware, JH. Applied Longitudinal Analysis. New York: John Wiley & Sons; 2012.Google Scholar
Siebenhofer, A, Paulitsch, MA, Pregartner, G, Berghold, A, Jeitler, K, Muth, C, Engler, J. Cluster-randomized controlled trials evaluating complex interventions in general practices are mostly ineffective: a systematic review. J Clin Epidemiol 2018;94:85–96.CrossRefGoogle ScholarPubMed
Campbell, MK, Piaggio, G, Elbourne, DR, Altman DG; for the CONSORT Group. Consort 2010 statement: extension to cluster randomised trials. BMJ 2012;345:e5661.Google Scholar
Hemming, K, Eldridge, S, Forbes, G, Weijer, C, Taljaard, M. How to design efficient cluster randomised trials. BMJ 2017;358:j3064.CrossRefGoogle ScholarPubMed
Reich, NG, Myers, JA, Obeng, D, Milstone, AM, Perl, TM. Empirical power and sample size calculations for cluster-randomized and cluster-randomized crossover studies. PLoS One 2012;7(4):e35564.CrossRefGoogle ScholarPubMed
Caille, A, Kerry, S, Tavernier, E, Leyrat, C, Eldridge, S, Giraudeau, B. Timeline cluster: a graphical tool to identify risk of bias in cluster randomised trials. BMJ 2016;354:i4291.CrossRefGoogle ScholarPubMed
Supplementary material: File

O’Hara et al. supplementary material

Appendix I

Download O’Hara et al. supplementary material(File)
File 21.6 KB
Supplementary material: PDF

O’Hara et al. supplementary material

Appendix II

Download O’Hara et al. supplementary material(PDF)
PDF 380.9 KB