Sample Size Estimates for Cluster-Randomized Trials in Hospital Infection Control and Antimicrobial Stewardship

Natalia Blanco; Anthony D Harris; Laurence S Magder; John A Jernigan; Sujan C Reddy; Justin O'Hagan; Kelly M Hatfield; Lisa Pineles; Eli Perencevich; Lyndsay M O'Hara

doi:10.1001/jamanetworkopen.2019.12644

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Sample Size Estimates for Cluster-Randomized Trials in Hospital Infection Control and Antimicrobial Stewardship

Journal article

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Sample Size Estimates for Cluster-Randomized Trials in Hospital Infection Control and Antimicrobial Stewardship

Natalia Blanco, Anthony D Harris, Laurence S Magder, John A Jernigan, Sujan C Reddy, Justin O'Hagan, Kelly M Hatfield, Lisa Pineles, Eli Perencevich and Lyndsay M O'Hara

JAMA network open, Vol.2(10), pp.e1912644-e1912644

10/02/2019

DOI: 10.1001/jamanetworkopen.2019.12644

PMCID: PMC6784749

PMID: 31584684

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Abstract

An important step in designing, executing, and evaluating cluster-randomized trials (CRTs) is understanding the correlation and thus nonindependence that exists among individuals in a cluster. In hospital epidemiology, there is a shortage of CRTs that have published their intraclass correlation coefficient or coefficient of variation (CV), making prospective sample size calculations difficult for investigators. To estimate the number of hospitals needed to power parallel CRTs of interventions to reduce health care-associated infection outcomes and to demonstrate how different parameters such as CV and expected effect size are associated with the sample size estimates in practice. This longitudinal cohort study estimated parameters for sample size calculations using national rates developed by the Centers for Disease Control and Prevention for methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, central-line-associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and Clostridium difficile infections (CDI) from 2016. For MRSA and vancomycin-resistant enterococci (VRE) acquisition, outcomes were estimated using data from 2012 from the Benefits of Universal Glove and Gown study. Data were collected from June 2017 through September 2018 and analyzed from September 2018 through January 2019. Calculated number of clusters needed for adequate power to detect an intervention effect using a 2-group parallel CRT. To study an intervention with a 30% decrease in daily rates, 73 total clusters were needed (37 in the intervention group and 36 in the control group) for MRSA bacteremia, 82 for CAUTI, 60 for CLABSI, and 31 for CDI. If a 10% decrease in rates was expected, 768 clusters were needed for MRSA bacteremia, 875 for CAUTI, 631 for CLABSI, and 329 for CDI. For MRSA or VRE acquisition, 50 or 40 total clusters, respectively, were required to observe a 30% decrease, whereas 540 or 426 clusters, respectively, were required to detect a 10% decrease. This study suggests that large sample sizes are needed to appropriately power parallel CRTs targeting infection prevention outcomes. Sample sizes are most associated with expected effect size and CV of hospital rates.

Details

Title: Subtitle: Sample Size Estimates for Cluster-Randomized Trials in Hospital Infection Control and Antimicrobial Stewardship
Creators: Natalia Blanco - Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore
Anthony D Harris - Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore
Laurence S Magder - Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore
John A Jernigan - Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Sujan C Reddy - Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Justin O'Hagan - Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Kelly M Hatfield - Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Lisa Pineles - Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore
Eli Perencevich - Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City
Lyndsay M O'Hara - Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore
Resource Type: Journal article
Publication Details: JAMA network open, Vol.2(10), pp.e1912644-e1912644
DOI: 10.1001/jamanetworkopen.2019.12644
PMID: 31584684
PMCID: PMC6784749
NLM abbreviation: JAMA Netw Open
ISSN: 2574-3805
eISSN: 2574-3805
Publisher: United States
Grant note: U54 CK000450 / NCEZID CDC HHS R01 AI121146 / NIAID NIH HHS P30 AG028747 / NIA NIH HHS
Language: English
Date published: 10/02/2019
Academic Unit: Epidemiology; Internal Medicine
Record Identifier: 9984001238102771

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