Preventing Patient Deterioration with Cognitive Machines
Based on an analysis performed as part of the Bedside Patient Rescue (BPR) project, failure to recognize acute patient deterioration is the most common contributor to mortality*. But current early warning scores that combine expert opinion and classical statistical models are not very effective in lowering mortality rates.
Developed in collaboration with the Mayo Clinic, Jvion’s BPR vector is designed to drive more effective care management and prevent patient deterioration by:
Supporting and automating detection efforts
Standardizing response with time-limited escalation of expertise at the bedside
Improving the time to escalation and iteration
Not only does the solution better account for the variables that drive deterioration, it also incorporates interaction terms and measures risk over time.
Initial results have demonstrated a 40% decrease in the time it takes to engage a provider and a 47% decrease in the time to a therapy order for at-risk patients.
Overall, the BPR solution reduced the time to patient intervention by 60 minutes and resulted in an 8% drop in mortality.