Diagnostic Stewardship of Endotracheal Aspirate Cultures in a PICU

Abstract

Background: Clinicians commonly obtain endotracheal aspirate cultures (EACs) in the evaluation of suspected ventilator-associated infections. However, bacterial growth in EACs does not distinguish bacterial colonization from infection and may lead to overtreatment with antibiotics. We describe the development and impact of a clinical decision support algorithm to standardize the use of EACs from ventilated PICU patients.

Methods: We monitored EAC use using a statistical process control chart. We compared the rate of EACs using Poisson regression and a quasi-experimental interrupted time series model and assessed clinical outcomes 1 year before and after introduction of the algorithm.

Results: In the preintervention year, there were 557 EACs over 5092 ventilator days; after introduction of the algorithm, there were 234 EACs over 3654 ventilator days (an incident rate of 10.9 vs 6.5 per 100 ventilator days). There was a 41% decrease in the monthly rate of EACs (incidence rate ratio [IRR]: 0.59; 95% confidence interval [CI] 0.51-0.67; P < .001). The interrupted time series model revealed a preexisting 2% decline in the monthly culture rate (IRR: 0.98; 95% CI 0.97-1.0; P = .01), immediate 44% drop (IRR: 0.56; 95% CI 0.45-0.70; P = .02), and stable rate in the postintervention year (IRR: 1.03; 95% CI 0.99-1.07; P = .09). In-hospital mortality, hospital length of stay, 7-day readmissions, and All Patients Refined Diagnosis Related Group severity and mortality scores were stable. The estimated direct cost savings was $26 000 per year.

Conclusions: A clinical decision support algorithm standardizing EAC obtainment from ventilated PICU patients was associated with a sustained decline in the rate of EACs, without changes in mortality, readmissions, or length of stay.

FIGURE 1

Algorithm for obtaining endotracheal cultures from mechanically ventilated patients. CRP, C-reactive protein; ETA, endotracheal aspirate.

FIGURE 2

Control chart of the monthly rate of EACs per 100 ventilator days before and after implementation of a decision support algorithm. This U-chart was followed over the first year after implementation of the QI initiative.

FIGURE 3

Control chart of the monthly rate of EACs per 1000 patient days before and after implementation of a decision support algorithm. This U-chart was created by using data from an electronic dashboard established in February 2020. The data begin in July 2016, with the introduction of the electronic medical record system, Epic, and depict the EAC rate ∼2 years before and after the introduction of the clinical decision support algorithm in April 2018.