AI triage layer cut alarm fatigue while catching the events that actually matter
Nurses were ignoring alarms. Not because they didn't care — because 87% of the 350+ daily alarms per unit were false positives. When a real crisis hit at 3 AM, the response was 4 minutes slower than protocol required. A near-miss sentinel event forced the hospital system to act.
This Irvine-based patient monitoring company's hardware was excellent — but its threshold-based alerting was drowning clinical staff. A heart rate above 120 triggered an alarm whether the patient was anxious, exercising in bed, or genuinely deteriorating. The company's hospital customers were threatening to switch vendors. They needed smarter software without replacing any hardware.
We built an AI triage layer that sits on top of existing monitoring infrastructure. Multi-variate models analyze SpO2, heart rate, respiratory rate, and blood pressure together — not as isolated thresholds. Patient-specific baseline models distinguish between 'abnormal for this patient' and 'abnormal for anyone.' Our overnight ML team monitors model performance across hospital deployments and validates accuracy metrics for regulatory compliance.
Our nurses trust the system now. When it alarms, they move. That's the difference between a product that generates noise and one that saves lives.— Chief Nursing Officer, Partner Hospital
Let's talk about what AI + a supplemental engineering team can do for your business.
Talk to a Dev Lead →