Clinical Decision Support for Septic Shock in the Emergency Department A Cluster Randomized Trial

A 7-year-old female presents to the pediatric emergency department with fever, tachycardia, and suspected sepsis. She has a history of asthma and no known drug allergies. Her current medications include albuterol inhaler as needed. The ED uses a machine-learning-based CDS system that alerts providers when a child is at high risk for hypotensive septic shock. The pharmacist is reviewing the patient’s care plan and considering the impact of the CDS alert on timely treatment.

Based on the findings from the recent cluster randomized trial of a machine-learning CDS system in pediatric EDs, what is the most appropriate pharmacist action regarding the CDS alert for this patient?

A 3-year-old male with no significant past medical history presents to the ED with suspected sepsis. The electronic health record triggers a high-risk alert for hypotensive septic shock from the CDS system. The pharmacist notes that the patient has not yet received antibiotics or fluid bolus. The ED team is considering the timing of interventions.

According to the cluster randomized trial evaluating the CDS system, what is the expected impact of the CDS alert on the timing of antibiotic administration in pediatric patients with suspected sepsis?

A 12-year-old female with suspected sepsis is evaluated in a pediatric ED that recently implemented a machine-learning CDS system for septic shock risk prediction. The pharmacist is discussing with the ED team the sustainability and provider perceptions of the CDS tool after the trial period.

What did the cluster randomized trial reveal about provider acceptance and sustained use of the machine-learning CDS system in pediatric emergency departments?