AI Diagnostics — Faster Triage
Scan, score, and act in real time: our clinically‑validated AI suite accelerates diagnostic workflows from images to EHR orders—cutting emergency‑department wait times, slashing radiology backlog, and giving clinicians super‑human sight when speed matters most.
Industry
Healthcare Technology · Clinical Decision Support · Imaging & EHR
Service
AI Model Engineering · Workflow Orchestration · FDA‑Ready Compliance
Team Setup
1 Clinical Product Lead · 3 Data Scientists · 4 Machine‑Learning Engineers · 3 Full‑Stack Developers · 2 PACS/EHR Integrators · 2 QA Specialists · 2 DevOps
Timeline
10 Months
Story
Goal
Deliver a bedside‑to‑back‑office diagnostic copilot that would:
- Trim emergency‑department (ED) triage wait times by ≥ 30 %.
- Cut radiologist chest‑X‑ray reading time 42 % without accuracy loss.
- Surface high‑risk patients 15 minutes sooner, lowering adverse events.
- Achieve FDA clearance pathway readiness and HIPAA/HITRUST compliance.
Challenge
Data fragmentation, tight latency, and regulatory demands tested every dimension:
- Data fragmentation — PACS, EHR, vitals, and lab queues siloed.
- Latency ceiling < 60 s from image capture to triage score.
- Accuracy mandate — AI must meet or exceed board‑certified sensitivity.
- Clinical trust gap — explainability & override essential.
- Regulatory maze — FDA SaMD, GDPR, PHI audit logs.
- Infrastructure — GPU bursts during peak CT/MRI loads.
Our Approach
Discover
Shadowed 30 ED nurses & 18 radiologists; found 26 % of CTs waited > 2 h for preliminary read.
Design
Prototype triage dashboard; ran reader‑study with 8 M de‑identified images; tuned prompts for GPT‑4o report synthesis.
Deploy
Hybrid edge/cloud inference—on‑prem GPUs for stat scans, cloud batch for routine; blue/green roll‑outs by service line.
The Mountain to Climb
Creating an FDA‑ready, multi‑site triage solution within strict performance and compliance parameters:
1,016 FDA‑cleared AI/ML devices
Ours needed novel indication for triage across multiple image types.
240‑image/second ingestion
CT, MRI, X‑ray modalities—peak throughput without dropping frames.
< 60 s end‑to‑end
Including reconstruction & scoring; essential for ED triage.
Explainable heat maps
Plus natural‑language rationale to earn clinician trust.
SMART‑on‑FHIR launch
Seamless inside Epic & Cerner with single sign‑on.
Global model updates
Without downtime or retraining local staff each time.
Additional Hurdles
GPU cost spikes during peak imaging hours—burst autoscaling required.
Model registry + version control for FDA, with each release documented.
User override + full audit trails preserve clinician autonomy and accountability.
Meeting these demands meant building a robust, cloud‑edge architecture that respects privacy, reliability, and clinical trust at every turn.
Key Modules Engineered
Each piece accelerated patient care, relieved staff burnout, and built regulatory confidence.
Realtime Triage Engine
Prioritises STAT scans; ED wait ‑28 %.
CXR 42 Model
42 % faster reads; non‑inferior AUROC 0.94.
Derm AI Assist
13‑pt sensitivity gain for non‑derm clinicians.
Risk Heat‑Map Explainer
Grad‑CAM overlay builds trust in seconds.
FHIR Orders Bot
Auto‑writes follow‑up labs & meds directly in EHR.
Smart Worklist Sorter
Dynamic queue; backlog −36 %.
ED Wait‑Time Predictor
AI ETA for each patient; informs staffing.
Sepsis Early‑Warn
Flags vitals‑lab combo 2 h sooner; mortality −4 pp.
FDA Audit Vault
Stores versioned models, data lineage, deployment logs.
GPU Burst Autoscale
Spot GPUs cut infra cost 38 %.
Zero‑Trust PHI Mask
SHA‑256 hashed IDs; GDPR delete < 60 s.
Analytics Command Center
Live AUROC, latency, patient outcomes dashboard.
User Research Insights
AI triage cut ED wait time ~30 % in peer hospitals. PMC, ScienceDirect
Radiology AI decreased read time 36 – 42 % and backlog to zero. Diagnostic Imaging, AuntMinnie
Clinicians value AI most when it explains decisions—heat‑map + NL note increased acceptance to 92 %.
Technology Stack
A/B Test Wins
ROI / Business Impact
Outcome
A next‑gen triage ecosystem: faster scans, sharper reads, and better patient outcomes—FDA readiness included.
Patient & Revenue Growth
- ED wait 110 → 78 min; 14 K additional patients/year.
- Imaging backlog cleared; same‑day results rate 94 %.
Clinician Experience
- Documentation time −30 %; burnout survey –9 pts.
- 92 % acceptance of AI recommendations with explainers.
Operational Efficiency
- GPU cost −38 % via burst autoscale.
- 99.98 % inference uptime; P95 latency 54 s.
Compliance & Brand Impact
- Live on 20 hospitals; FDA pre‑sub cleared.
- Featured by Nature Digital Medicine as “Top AI Triage Platform 2025.”
Feature Highlights
Realtime Triage Engine
CXR 42 Model
Derm Assist
Heat‑Map Explainer
FHIR Orders Bot
Smart Worklist
Sepsis Early‑Warn
GPU Burst Autoscale
FDA Audit Vault
Zero‑Trust PHI Mask
ED Wait‑Time Predictor
Analytics Command Center
Speech‑to‑Report
Multisite Model Hub
KPI Heat‑map
Want triage that thinks in milliseconds?
Book a clinical sprint—we’ll ingest your PACS feed, plug into your EHR, and prove faster diagnosis in 30 days.