Identify Critical
ED Patients
Before They Crash
Sentrelia is an AI-powered triage risk stratification tool that integrates directly into Epic — delivering real-time ICU risk scores to nurses at the moment of triage, with zero additional data entry.
Chest pain · HR 112 · BP 88/60 · SpO₂ 93% · Age 71 · Known CAD
ED Triage Misses 1 in 5 High-Risk Patients
The Emergency Severity Index (ESI) — the gold standard for ED triage across the United States — was designed for speed, not precision. Patients presenting with non-specific complaints, atypical symptoms, or early decompensation routinely receive lower acuity scores than their clinical trajectory warrants.
ICU / Critical Outcome Prediction
Receiver Operating Characteristic (ROC) curves — MIMIC-IV-ED anchor-era temporal holdout (PRIMARY; n = 77,026) · Outcome: ICU admission within 6 hours or ED death
Robust Performance Across Two Independent Datasets
Validated on both a nationally representative sample (NHAMCS) and a large academic medical center dataset (MIMIC-IV-ED) totaling over 512,000 emergency department encounters.
NHAMCS 2018–2022
National Hospital Ambulatory Medical Care Survey
MIMIC-IV-ED v2.2
Beth Israel Deaconess Medical Center
MIMIC-IV-ED Operating Points — Structured + NLP Model
Clinician-selectable sensitivity thresholds allow tuning the model to institutional priorities (catch more vs. flag less). Outcome: any ICU admission during hospitalization (broader definition; AUC 0.898 for any-ICU vs. 0.943 for 6-hour ICU on the anchor-era temporal holdout).
| Target Sensitivity | Actual Sensitivity | Specificity | PPV | NPV | Use Case |
|---|---|---|---|---|---|
| 80% | 80.0% | 81.0% | 25.5% | 98.0% | Busy EDs, minimize false alerts |
| 85% | 85.0% | 75.3% | 21.9% | 98.4% | Balanced approach |
| 90% ★ | 90.0% | 67.3% | 18.3% | 98.8% | Recommended default |
| 95% | 95.0% | 54.2% | 14.5% | 99.3% | Safety-first, maximum catch |
Zero Workflow Disruption
Sentrelia runs invisibly in the background and surfaces only when it matters.
Nurse Opens Triage Encounter
The triage nurse opens a new encounter in Epic Hyperspace as usual. No extra steps, no separate login, no new application to open.
Sentrelia Reads FHIR Data
Via CDS Hooks, Epic automatically sends demographics, chief complaint, and vital signs to the Sentrelia API. The model scores the patient in <200ms.
Risk Card Appears in Hyperspace
A color-coded CDS card surfaces inline — below or beside the standard triage documentation — with risk score, level, and the top clinical drivers. High-risk patients get an immediate alert.
Truly Plug & Play
CDS Hooks + SMART on FHIR
Sentrelia uses the open CDS Hooks standard — the same protocol Epic uses for drug-interaction alerts and sepsis warnings. No custom Epic build. No HL7 interface. One URL registration and you're live.
GET /cds-services → Discovery
POST /cds-services/ed-triage-risk → Hook
A Partnership Built for Your Health System
We are seeking a strategic health system partner for our inaugural prospective trial. A multi-site Epic environment offers the ideal opportunity to validate real-world impact at scale.
Silent Deployment
Model runs in observation mode alongside standard care. Predictions are logged but not shown to clinicians. Establishes baseline metrics, validates FHIR data quality, and confirms technical integration at 2–4 pilot EDs.
Active CDS Alerts
CDS cards go live for triage nurses. Randomized stepped-wedge design across sites allows causal inference while ensuring all sites eventually benefit. Primary endpoint: door-to-ICU time for high-risk patients.
Analysis & Publication
Full outcome analysis, fairness audit by demographic subgroups, and co-authored publication in a high-impact emergency medicine journal. System-wide rollout decision informed by trial results.
What Your Health System Receives
Estimated Clinical Impact
Conservative projections for a large health system adoption (scaled per annual ED volume)
Built on Rigorous Science
(2018–2022)
SHAP explainability
dataset
academic medical center
Audited
age, sex, and race subgroups
Clinicians Who Build Technology
Sentrelia was co-founded by emergency physicians — including a former U.S. Army medical evacuation helicopter pilot. Built from real experience triaging patients in ERs and combat zones, Sentrelia brings clinical credibility and cutting-edge AI together.
J. Avery Harrell, MD
Emergency medicine physician, Wilderness EMT (NOLS), former U.S. Army medevac and mountain search and rescue helicopter pilot, and Montana ski patroller. Brings firsthand experience in high-stakes emergency care across austere and clinical environments to every aspect of Sentrelia's design. Co-developed the NHAMCS and MIMIC-IV triage models underlying Sentrelia's clinical engine.
Ayed Mahmoud, MD
Emergency medicine physician and developer with a passion for applying AI to solve high-stakes clinical problems and drive meaningful innovation in health systems. Co-developed the NHAMCS and MIMIC-IV triage models underlying Sentrelia's clinical engine.
Sentrelia AI Engine
XGBoost ensemble model with SHAP explainability, CDS Hooks API, FHIR R4 integration, real-time inference at <200ms, and HIPAA-compliant audit logging.
Let's Bring This to
Your Emergency Department
We're seeking one strategic health system to partner on our inaugural prospective trial. If your system runs Epic and cares about patient safety, we'd love to talk.
Request a Technical Deep Dive
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