Interventions to control nosocomial infections: study designs and statistical issues

Area of Science:

• Epidemiology
• Clinical Trial Design
• Infectious Disease Control

Background:

• Nosocomial infections pose a significant threat in healthcare settings.
• Evaluating interventions to decrease these infections requires careful study design.
• Complex analytical factors include competing events and time-dependent variables.

Purpose of the Study:

• To review and compare various study designs for intervention studies aimed at reducing nosocomial infections.
• To discuss the strengths and limitations of pre-post quasi-experimental and different randomized designs.
• To provide guidance on selecting appropriate designs based on bias, control, and generalizability.

Main Methods:

• Comparison of pre-post quasi-experimental design with randomized designs: parallel cluster, cross-over, and stepped-wedge.
• Discussion of key design aspects: bias, control for non-intervention factors, and generalizability.
• Consideration of statistical issues, including the recommendation of extended competing risk models.

Main Results:

• Pre-post designs may be informative for retrospective outbreak analysis but lack causality.
• Randomized designs are necessary for internally valid results.
• Parallel cluster randomized trials are generally preferred for internal validity, while stepped-wedge designs may offer better generalizability.

Conclusions:

• Randomization is crucial for establishing causality in intervention studies for nosocomial infections.
• The choice between parallel cluster and stepped-wedge designs depends on the balance between internal validity and generalizability.
• Appropriate statistical models, such as extended competing risk models, are recommended for complex analyses.