HealthTech // Client Project

Sepsis Detection:
Up to 4 Hours Earlier.

We built a practical HealthTech solution combining multiple types of vital data collection, streaming ml inference, and AI-powered clinical alerting. The project delivered 4.1h Detection Gain and 18% Mortality Reduc..

Key Results RESULTS
4.1h
Detection Gain
vs Baseline
18%
Mortality Reduc.
ROI: 14 Weeks
<100ms
Vital Data collection
HIPAA GATED

Trusted by teams building ambitious products

What We Set Out to Improve.

Industry
HealthTech

High-acuity clinical environment requiring live processing of multiple types of patient vitals.

How We Worked
Dedicated product team

Bio-Medical Engineer + MLOps Lead + Healthcare Data Architect embedded with Clinical Ops.

Goal
Patient Outcome Optimization

Moving from reactive post-onset treatment to early intervention via sub-second data streaming.

What We Built
Patient Vital Platform

A practical solution designed around the client’s existing tools, teams, and day-to-day workflow.

What Was Getting in the Way.

The health system’s ICU relied on disconnected monitor alerts and static EMR thresholds that often triggered after the inflammatory response was well underway. Every hour of delay in sepsis treatment increases mortality risk by 8%, yet clinical staff were buried in False Positive monitor noise.

The biggest issues were information response time, alarm fatigue, and data fragmentation. The team needed a faster, clearer way to manage the work while keeping the right checks in place.

Information Response Time
Critical vital shifts were only identified during 4-hour nursing rounds, missing the critical Golden Hour for intervention.
Alarm Fatigue
Over 70% of device alerts were clinically irrelevant, leading to alert desensitization among ICU nursing staff.
Data Fragmentation
Blood pressure, heart rate, and lactate levels were processed in separate separate systems, obscuring systemic patient decline.
The Solution

What We Built.

01
Multiple types of Vital Data Collection
Unified streaming data from bedside monitors (HL7) and lab results (Health-record) into a contract-locked schema to eliminate feature drift in live use use use use use use.
Key details
Protocol Health-Record Standard
Encryption AES 256 Gated
Response time Sub Second
02
Streaming ML Inference
Introduced a gradient-boosted model platform on a Cloud-based streaming engine to analyze sequence anomalies across 12 vital parameters simultaneously.
Key details
Engine Apache Flink
Model XGBoost Ensemble
Deployment Ready to Grow
03
AI-powered Clinical Alerting
Built an automated clinical agent that routes prioritized alerts directly to nurse workstations with SHAP-based reason codes for immediate action.
Key details
Logic AI Assisted
Audit Traceable Data
Standard HIPAA Aligned
Before and After

How the Workflow Improved.

Area
Before
After
Lead Time

Post-Onset

Alerts triggered only after white cell counts or BP hit critical low thresholds.

4-Hour Lead

Pattern recognition identifies systemic decline before clinical thresholds are breached.

Data Integrity

Manual Entry

Analysis was dependent on nurse chart entries, which are often delayed during high-acuity shifts.

Stream-Native

Direct monitor data collection ensures 100% vital fidelity with zero manual documentation delay.

Scale

Per-Patient

Monitoring was isolated to bedside devices without cross-unit analytics.

Cloud-based Platform

Ready to grow system design monitors 500+ ICU beds simultaneously with sub-100ms scoring response time.

Key Features

What Made the Solution Useful.

Live Updates

Contextual Feature Store

Calculates rolling averages and speed of vitals (MAP, SpO2) per patient to eliminate noisy monitor spikes.

Business impact
65% Fewer False Alarms
HIPAA GATED

Privacy-Preserved Scoring

Models process de-identified vital streams in memory. personal information is only re-linked at the secure clinical endpoint.

Business impact
HIPAA compliance
AI Assisted

Prioritization Agent Workflow

Automatically escalates alerts based on clinical unit staffing and patient acuity levels.

Business impact
18% Mortality Reduction
Faster Delivery

How We Reduced Build Time.

Tested foundations helped the team spend less time on setup and more time on the parts that made this product useful.

What accelerated the work

4 reusable building blocks
01

HIPAA Connected Data Platform Module

A tested starting point for hipaa connected data platform module reduced repeated setup work.

02

Vital Signal Module

Reusable work for vital signal module let the team focus more time on the client’s specific needs.

03

Clinical Monitoring Platform

This made it easier to add clinical monitoring platform without rebuilding common foundations.

04

Edge Compute Safety controls

A tested starting point for edge compute safety controls reduced repeated setup work.

Results

The Business Difference.

A straightforward before-and-after view of what changed for the team and their customers.

RESULT: INTERVENTION01

Early Detection Gain

Streaming ML identified septic markers 4.1 hours earlier than the hospital's previous manual protocol.

Older ProtocolReactive
Coretus Platform4h Early
Outcome4.1h Detection Lead
RESULT: OPS EFFICIENCY02

Alarm Fatigue Suppression

Multi-vital contextual scoring eliminated random monitor noise, allowing nurses to focus on high-acuity events.

BeforeNoisy
AfterFiltered
Outcome65% Less False Alarm Rate
RESULT: OUTCOME03

Systemic Mortality Reduction

Earlier intervention was linked to an 18% reduction in sepsis-related mortality within the trial ICU units.

BaselineStandard
Post-AI18% Lower
Outcome18% Less Mortality Rate
Results4.1h Detection Lead • 65% Less False Alarm Rate
Trust and Control

How We Kept It Safe and Reliable.

01
Clinical Explainability
Alerts include live SHAP reason-codes (e.g., Rising Heart Rate + Falling SpO2) for clinical trust.
COMPLIANCE READY
02
Data Privacy
All workflows operate within the hospital's private cloud environment. No Patient health information leaves the high-security environment.
HIPAA COMPLIANT
03
Fail-Safe System design
Redundant Cloud services ensure warning systems remain active even during EHR or hospital Wi-Fi outages.
CLOUD NATIVE
04
Code and IP Ownership
Hospital retains 100% IP ownership of the sepsis models and clinical alerting logic upon completion.
100% OWNED
Client Testimonial

In their own words.

Coretus didn't just build an app, they built a clinical vital platform . We are now detecting sepsis 4 hours earlier, and our staff is finally free from the constant noise of low-signal alarms. This is the new standard of governed ICU care.

Turn Clinical Data into Saved Lives.

Have a similar challenge? We can help you plan and build a practical HealthTech solution around your goals, budget, and existing systems.

HIPAA & Regulatory Gated

Sub-100ms Vital Data collection

100% IP & Model Ownership