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Published on: May 15, 2020
Electronic health record-based clinical decision support alert for severe sepsis: a randomised evaluation
Norman Lance Downing1,2, Joshua Rolnick3,4, Sarah F Poole5
1Department of Medicine - Biomedical Informatics Research, Hospital Medicine, and Primary Care and Population Health, Stanford University, Stanford, California, USA ldowning@stanford.edu.
Background:
Sepsis remains the top cause of morbidity and mortality of hospitalised patients despite concerted efforts. Clinical decision support for sepsis has shown mixed results reflecting heterogeneous populations, methodologies and interventions.
Objectives:
To determine whether the addition of a real-time electronic health record (EHR)-based clinical decision support alert improves adherence to treatment guidelines and clinical outcomes in hospitalised patients with suspected severe sepsis.
Design:
Patient-level randomisation, single blinded.
Setting:
Medical and surgical inpatient units of an academic, tertiary care medical centre.
Patients:
1123 adults over the age of 18 admitted to inpatient wards (intensive care units (ICU) excluded) at an academic teaching hospital between November 2014 and March 2015.
Interventions:
Patients were randomised to either usual care or the addition of an EHR-generated alert in response to a set of modified severe sepsis criteria that included vital signs, laboratory values and physician orders.
Measurements And Main Results:
There was no significant difference between the intervention and control groups in primary outcome of the percentage of patients with new antibiotic orders at 3 hours after the alert (35% vs 37%, p=0.53). There was no difference in secondary outcomes of in-hospital mortality at 30 days, length of stay greater than 72 hours, rate of transfer to ICU within 48 hours of alert, or proportion of patients receiving at least 30 mL/kg of intravenous fluids.
Conclusions:
An EHR-based severe sepsis alert did not result in a statistically significant improvement in several sepsis treatment performance measures.
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