Identifying High-Risk Subphenotypes and Associated Harms From Delayed Antibiotic Orders and Delivery

Abstract

Objectives: Early antibiotic administration is a central component of sepsis guidelines, and delays may increase mortality. However, prior studies have examined the delay to first antibiotic administration as a single time period even though it contains two distinct processes: antibiotic ordering and antibiotic delivery, which can each be targeted for improvement through different interventions. The objective of this study was to characterize and compare patients who experienced order or delivery delays, investigate the association of each delay type with mortality, and identify novel patient subphenotypes with elevated risk of harm from delays.

Design: Retrospective analysis of multicenter inpatient data.

Setting: Two tertiary care medical centers (2008-2018, 2006-2017) and four community-based hospitals (2008-2017).

Patients: All patients admitted through the emergency department who met clinical criteria for infection.

Interventions: None.

Measurements and main results: Patient demographics, vitals, laboratory values, medication order and administration times, and in-hospital survival data were obtained from the electronic health record. Order and delivery delays were calculated for each admission. Adjusted logistic regression models were used to examine the relationship between each delay and in-hospital mortality. Causal forests, a machine learning method, was used to identify a high-risk subgroup. A total of 60,817 admissions were included, and delays occurred in 58% of patients. Each additional hour of order delay (odds ratio, 1.04; 95% CI, 1.03-1.05) and delivery delay (odds ratio, 1.05; 95% CI, 1.02-1.08) was associated with increased mortality. A patient subgroup identified by causal forests with higher comorbidity burden, greater organ dysfunction, and abnormal initial lactate measurements had a higher risk of death associated with delays (odds ratio, 1.07; 95% CI, 1.06-1.09 vs odds ratio, 1.02; 95% CI, 1.01-1.03).

Conclusions: Delays in antibiotic ordering and drug delivery are both associated with a similar increase in mortality. A distinct subgroup of high-risk patients exist who could be targeted for more timely therapy.

Figure 1.. Association between different delay types and in-hospital mortality.

Associations are represented by adjusted odds ratios for A) Order Delay by hour, B) Delivery Delay by 30-minute increments, and C) Cumulative Delay by hour. P<0.05 is indicated by *.

Figure 2.. Association between Cumulative Delay and in-hospital mortality for patient subgroups and by lactate stratification.

A) Cluster analysis demonstrating associations between Cumulative Delay and in-hospital mortality, with adjusted odds ratios and 95% CI shown for the following groups: total study population (n=60,817), cluster 1 (n=54,067), cluster 2 (6,750), patients with initial lactate measurement <2mmol/L (n=46,042), and patients with initial lactate measurement ≥2mmol/L (n=14,755). B) Variable importance plot for causal forests model showing the top 20 most important variables in descending order.