A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study

OBJECTIVE: To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. DESIGN: Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients\u27 designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. SETTING: Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. PARTICIPANTS: Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. MAIN OUTCOME MEASURE: \u27Suspected infection\u27 was the established gold standard to assess clinical decision support clinimetric performance. RESULTS: A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying \u27suspected infection\u27 as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. CONCLUSION: A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis