Reducing the rate of central line-associated bloodstream infections; a quality improvement project

Abstract

Background: The burden of central line-associated bloodstream infections is significant and has negative implications for healthcare, increasing morbidity and mortality risks, increasing inpatient hospital stays, and increasing the cost of hospitalization. Efforts to reduce the incidence of central line-associated bloodstream infections have utilized quality improvement projects that implement, measure, and monitor outcomes. However, variations in location, healthcare organization, patient risks, and practice gaps are key to the success of interventions and approaches. This study aims to evaluate interventions of a quality improvement project on the reduction of central line-associated bloodstream infection rates at a university teaching hospital.

Methods: This was a retrospective review of a quality improvement project that was implemented using the Plan-Do-Study-Act quality improvement cycle. Active surveillance of processes and outcomes was performed in the critical care areas; compliance to central line care bundles, and central line-associated bloodstream infections. Interrupted time series was used to analyze trends pre and post-intervention and regression modeling to estimate data segments preceding and succeeding the interventions.

Results: There were 350 central line insertions, 3912 catheter days, and 20 central line-associated bloodstream infection events during the intervention period. Compliance with central line care bundles was at 94%. There was a trend in the reduction of central line-associated bloodstream infections by 18% that did not reach statistical significance (p = 0.252).

Conclusions: Improvement projects to reduce central line-associated bloodstream infections face challenges and complexities associated with implementing interventions in real-world healthcare settings. There is a great need to continuously monitor, evaluate, readjust, and adapt interventions to achieve desired results, sustain improvements in patient outcomes, and investigate reasons for non-adherence as keys to achieving desired outcomes.

Keywords: CLABSI- central line-associated bloodstream Infections; CQI- continuous quality improvement.

Fig. 1

PDSA Implementation Framework

Fig. 2

Auto Correlation Function Plot. Durbin-Watson test. data: model1. DW = 2.151, p-value = 0.3814. Alternative hypothesis: true autocorrelation is greater than 0

Fig. 3

Trend line of monthly CLABSI Rate before and after intervention