Sentinel Med AI identifies early physiologic deterioration in hospitalized patients—often hours before it becomes clinically apparent. The system analyzes routinely collected patient data to surface subtle changes that may signal rising risk.
By supporting earlier awareness and safer escalation, Sentinel Med AI helps care teams intervene sooner and improve patient outcomes without disrupting existing workflows.
Early Deterioration Detection
The same clinical intelligence used in the retrospective pilot can be deployed in near-real time to support early deterioration detection.
Sentinel continuously evaluates physiologic trends to generate actionable alerts, risk severity indicators, and projected time-to-deterioration. These insights are designed to support timely escalation decisions while integrating smoothly into existing clinical workflows.
How Sentinel Works
Sentinel Med AI analyzes patterns in routinely collected vital sign data to identify early physiologic instability. The system evaluates multiple indicators simultaneously, translating subtle changes into clear, clinician-readable insights.
Outputs are designed to support earlier awareness and safer escalation decisions without adding workflow burden or relying on opaque, black-box scoring.
Sentinel Med AI turns routine vital signs into early, actionable clinical intelligence. Hospitals start with a retrospective analysis using existing data (CSV export) to quantify missed deterioration windows, identify the highest-risk patterns, and estimate lead time before escalation events. After value is proven, the same logic engine can be deployed closer to real time—monitoring incoming vitals continuously and surfacing risk signals earlier than traditional thresholds. The system produces transparent outputs: alerts, a risk score, severity level, and an estimated time-to-deterioration window—so teams can act with clarity, not guesswork.
Retrospective Pilot
Sentinel Med AI begins with a retrospective pilot using a hospital’s historical vital sign data to identify missed or delayed opportunities for intervention.
This analysis provides measurable insight into lead time, escalation gaps, and patient populations most likely to benefit from earlier detection—establishing a data-driven foundation for prospective deployment.
Sentinel Med AI begins with a retrospective pilot using your hospital’s historical vital sign data to evaluate whether earlier physiologic deterioration signals were present before escalation events occurred. This zero-disruption analysis helps leadership understand where deterioration was delayed, missed, or not clearly visible at the bedside until it was clinically obvious.
During the pilot, Sentinel produces a structured report that highlights risk severity patterns, projected deterioration windows, and alert drivers (ex: hypoxemia, tachypnea, tachycardia, fever, hypertension). Findings are organized by unit type and patient categories, providing measurable insight into lead time, escalation gaps, and populations most likely to benefit—before any live integration or workflow change is introduced.
Ready to see what your own ICU data already knows?
Request a retrospective pilot review.
Designed for Clinical Teams
Sentinel is designed to support clinical decision-making, not replace it. The system presents risk information in a format that aligns with how care teams assess patients and prioritize escalation.
By reducing noise and emphasizing clinically meaningful signals, Sentinel supports safer, more confident decision-making across care settings.
Sentinel is built to support bedside decision-making without adding burden. Outputs are short, readable, and clinically interpretable—highlighting the key drivers behind each risk flag. The goal is not to replace judgment, but to strengthen situational awareness during high-volume, high-acuity moments. Sentinel can be reviewed by nurses, rapid response teams, and unit leadership in seconds, helping teams prioritize attention, standardize escalation conversations, and reduce “I wish we’d caught it sooner” events.
- Retrospective deterioration findings report (lead time, missed escalation patterns, severity distribution)
- High-risk patient trend analysis with key physiologic drivers (SpO₂, RR, HR, BP, temperature)
- Unit-level insights to identify where earlier detection would create the most impact
- Clear next-step recommendation for near–real-time deployment readiness
Why Sentinel
Clinical deterioration is rarely sudden. Meaningful physiologic changes often occur well before visible decline, yet these signals are easy to miss in busy clinical environments.
Sentinel brings those early signals into focus—supporting timely intervention, improving patient safety, and helping health systems move from reactive response to proactive care.
Most healthcare AI stays abstract—Sentinel is designed to deliver measurable impact quickly. We start with proof, not promises: a retrospective pilot that shows exactly where earlier detection could have changed the outcome, how much lead time is realistically achievable, and which patient groups benefit most. Sentinel is transparent by design, using explainable scoring and clear clinical language rather than black-box outputs. That makes adoption easier, supports governance, and builds the trust required for real deployment.
Contact
Interested in learning how Sentinel Med AI can help your organization identify early physiologic deterioration and uncover preventable risk?
We begin with a retrospective pilot using your existing vital sign data—no live integration required. This allows clinical and operational leaders to evaluate value, insight, and potential impact before any real-time deployment.
To start a conversation or request additional information, please contact us:
General inquiries
Pilot inquiries and clinical discussions
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