Antibiotic clinical decision support for pneumonia in the ED: A randomized trial

Abstract

Background Electronic health record‐based clinical decision support (CDS) is a promising antibiotic stewardship strategy. Few studies have evaluated the effectiveness of antibiotic CDS in the pediatric emergency department (ED). Objective To compare the effectiveness of antibiotic CDS vs. usual care for promoting guideline‐concordant antibiotic prescribing for pneumonia in the pediatric ED. Design Pragmatic randomized clinical trial. Setting and Participants Encounters for children (6 months‐18 years) with pneumonia presenting to two tertiary care children s hospital EDs in the United States. Intervention CDS or usual care was randomly assigned during 4‐week periods within each site. The CDS intervention provided antibiotic recommendations tailored to each encounter and in accordance with national guidelines. Main Outcome and Measures The primary outcome was exclusive guideline‐concordant antibiotic prescribing within the first 24 h of care. Safety outcomes included time to first antibiotic order, encounter length of stay, delayed intensive care, and 3‐ and 7‐day revisits. Results 1027 encounters were included, encompassing 478 randomized to usual care and 549 to CDS. Exclusive guideline‐concordant prescribing did not differ at 24 h (CDS, 51.7% vs. usual care, 53.3%; odds ratio [OR] 0.94 [95% confidence interval [CI]: 0.73, 1.20]). In pre‐specified stratified analyses, CDS was associated with guideline‐concordant prescribing among encounters discharged from the ED (74.9% vs. 66.0%; OR 1.53 [95% CI: 1.01, 2.33]), but not among hospitalized encounters. Mean time to first antibiotic was shorter in the CDS group (3.0 vs 3.4 h; p = .024). There were no differences in safety outcomes. Conclusions Effectiveness of ED‐based antibiotic CDS was greatest among those discharged from the ED. Longitudinal interventions designed to target both ED and inpatient clinicians and to address common implementation challenges may enhance the effectiveness of CDS as a stewardship tool.

Methodological progress note: Choosing analytic methods for randomized trials

“…Typically, PP analyses will report stronger findings than ITT analyses. For example, a recent RCT considered the effectiveness of clinical decision support, compared with usual care, for guideline‐concordant antibiotic prescribing 8 . There were 321 usual care and 214 intervention participants in the ITT analyses, with a small favorable result observed (odds ratio [OR]: 1.08; 95% confidence interval [CI]: 0.76, 1.53).…”

User-Centered Design and Implementation of an Interoperable FHIR Application for Pediatric Pneumonia Prognostication in a Randomized Trial

“…The PIS at the VUMC is a natural language processing (NLP) system employing a random forest model that predicts the likelihood of pneumonia based on chest X-ray radiology reports and files its results to Epic flowsheet rows, which can then trigger clinical decision support (CDS). 17,18 To address these constraints, we began our architectural design using the five "rights" of CDS (►Table 1). 19 Given the PIS's ability to trigger native EHR workflows, we chose to use an interruptive alert (Epic BestPractice Advisory or BPA) to initiate the CDS workflow.…”

Making tools that work for us: Improving clinical decision support

“…2,4 In a survey of 45 institutions, Dziorny et al 5 found that pediatric intensive care practitioners viewed CDS tools as intrusive with concerns for diminished critical thinking. Williams et al 3 acknowledge these barriers as a potential explanation for the modest impact on improving their outcome of interest.…”

“…In this issue of the Journal of Hospital Medicine , Williams et al 3 report their findings from a pragmatic clinical trial comparing CDS to usual care at two different pediatric emergency departments (EDs) using two different electronic health record (EHR) systems. The goal of the CDS was to increase guideline‐concordant antibiotic prescribing for community‐acquired pneumonia.…”

“…While CDS tools are abundant in our daily work, there remain many barriers to achieving their intended effect. In addition to the rigorous methods utilized by Williams et al, 3 we must understand the systems into which they are implemented and invest in data‐driven surveillance to assess their performance. Only then will we realize the potential for CDS to enhance patient care and support the clinical decisions we make as hospitalists every day.…”