Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies.
Quasi-experimental study designs are frequently used to assess interventions that aim to limit the emergence of antimicrobial-resistant pathogens. However, previous studies using these designs have often used suboptimal statistical methods, which may result in researchers making spurious conclusions. Methods used to analyze quasi-experimental data include 2-group tests, regression analysis, and time-series analysis, and they all have specific assumptions, data requirements, strengths, and limitations. An example of a hospital-based intervention to reduce methicillin-resistant Staphylococcus aureus infection rates and reduce overall length of stay is used to explore these methods.
Shardell
Michelle
M
Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Harris
Anthony D
AD
El-Kamary
Samer S
SS
Furuno
Jon P
JP
Miller
Ram R
RR
Perencevich
Eli N
EN
D035061:Control Groups; D003428:Cross Infection / Q000517:prevention & control*; D003627:Data Interpretation, Statistical; D024901:Drug Resistance, Multiple, Bacterial; D006801:Humans; D017053:Infection Control / Q000379:methods*; D017063:Outcome Assessment, Health Care / Q000379:methods*; D012044:Regression Analysis; D012107:Research Design