Objective: This study tested the hypothesis that lactate testing in ED sepsis patients could be increased using a computer alert that automatically recognizes systemic inflammatory response syndrome (SIRS) criteria and recommends lactate testing in cases of sepsis defined as ≥2 SIRS criteria plus physician suspicion of infection. Secondary outcomes included the effect of the alert on lactate testing among admitted sepsis patients, the proportion of admitted patients with lactate ≥4.0 mmol/L identified and the in-patient mortality difference before and after alert implementation. Methods: After a 6 month pre-alert phase, a computer alert was implemented that computed and displayed abnormal vital signs and white blood cell counts for all patients with >2 SIRS criteria and recommended testing lactate if an infection was suspected. Data for admitted patients was collected electronically on consecutive patients meeting sepsis criteria for 6 months before and 6 months after implementation of the alert. Results: There were a total of 5,796 subjects enrolled. Among all septic patients, lactate testing increased from 5.2% in the pre-alert phase to 12.7% in the alert phase, a 7.5% (95% CI 6.0 to 9.0%) absolute increase in lactate testing, p<0.001. Among the 1,798 admitted patients with sepsis, lactate testing increased from 15.3% to 34.2%, an 18.9% (95% CI 15.0 to 22.8%) absolute increase, p<0.001. Among admitted patients with sepsis, there was a 1.9% (95% CI 0.03 to 3.8%, p = 0.05) increase in absolute number of patients with elevated lactate levels identified and a 0.5% (95% CI -1.6 to 2.6%, p=0.64) decrease in mortality. Conclusion: The proportion of ED patients who had lactate tested and the number of admitted patients identified with a lactate level ≥4.0 mmol/L improved significantly after the implementation of a computer alert identifying sepsis patients with >2 SIRS criteria while mortality among admitted sepsis patients remained unchanged.
- Computerized alert
ASJC Scopus subject areas
- Health Informatics
- Computer Science Applications
- Health Information Management