Departments of Pediatrics and
Hospital Epidemiology and Infection Control, Johns Hopkins Hospital, Baltimore, Maryland.
Pediatrics. 2021 May;147(5). doi: 10.1542/peds.2020-1634. Epub 2021 Apr 7.
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.
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.
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; < .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; = .01), immediate 44% drop (IRR: 0.56; 95% CI 0.45-0.70; = .02), and stable rate in the postintervention year (IRR: 1.03; 95% CI 0.99-1.07; = .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.
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.
临床医生常在评估疑似呼吸机相关性感染时获取气管内吸出物培养(EAC)。然而,EAC 中的细菌生长并不能区分细菌定植与感染,并且可能导致抗生素的过度治疗。我们描述了一种临床决策支持算法的开发和影响,该算法用于标准化对重症监护病房(PICU)机械通气患者的 EAC 使用。
我们使用统计过程控制图监测 EAC 的使用情况。我们使用泊松回归和准实验中断时间序列模型比较了 EAC 的使用率,并在引入算法前后 1 年评估了临床结局。
在干预前一年,在 5092 个机械通气日中有 557 次 EAC;引入算法后,在 3654 个机械通气日中有 234 次 EAC(发生率分别为 10.9 和 6.5/100 机械通气日)。EAC 的月发生率下降了 41%(发生率比 [IRR]:0.59;95%置信区间 [CI]:0.51-0.67;<.001)。中断时间序列模型显示,每月培养物的发生率呈 2%的预先下降趋势(IRR:0.98;95%CI:0.97-1.0;=0.01),立即下降 44%(IRR:0.56;95%CI:0.45-0.70;=0.02),并且在干预后年度的发生率保持稳定(IRR:1.03;95%CI:0.99-1.07;=0.09)。院内死亡率、住院时间、7 天再入院率以及所有患者修正诊断相关组严重程度和死亡率评分均保持稳定。估计每年可节省直接成本 26000 美元。
一种标准化重症监护病房机械通气患者 EAC 获取的临床决策支持算法与 EAC 使用率的持续下降相关,而死亡率、再入院率或住院时间无变化。