Remote Patient Monitoring AI

Turn Device Data Into Actionable Clinical Insights.

Zabrizon's AI-powered RPM platform processes data streams from wearables, IoMT devices, and home monitoring equipment — surfacing only the alerts that matter and predicting deterioration before it becomes an emergency.

52%
Reduction in 30-day readmissions
70%
Decrease in clinically irrelevant alerts
4.2×
More chronic conditions managed per care manager
89%
Patient programme adherence rate
Zabrizon Clinical AI Platform
AI signal processing across all major RPM device types
Clinically meaningful alert stratification — eliminates 70%+ alarm noise
Predictive deterioration models for CHF, COPD, diabetes, and hypertension
Automated care team escalation and documentation
Patient-facing app with multilingual engagement
HIPAA-compliant cloud infrastructure with 99.9% uptime

Why RPM Programmes Fail to Deliver on Their Promise

The data is there — but without AI to process it, RPM creates workload rather than reducing it.

Alarm Fatigue at Scale

Unfiltered device alerts overwhelm care teams — 85–95% of RPM alarms are clinically insignificant. Without AI-based stratification, staff disable alerts entirely, eliminating programme value.

Lack of Predictive Intelligence

Raw threshold alerts tell you when something has already gone wrong. AI-powered RPM predicts deterioration 24–72 hours in advance, enabling proactive intervention.

Device & Data Fragmentation

CHF patients may use a scale, blood pressure cuff, pulse oximeter, and glucometer — each with separate data streams. Unified AI analytics make cross-device insights possible.

Documentation & Billing Burden

CMS requires specific time documentation for RPM billing (CPT 99453–99458). Manual logging consumes care manager capacity and risks undercapturing billable activity.

Platform Capabilities

Remote Patient Monitoring AI Capabilities

From device connectivity to care team intervention — every step intelligent.

AI Alert Stratification & Predictive Monitoring

Machine learning models trained on millions of patient-device interactions separate clinically actionable signals from background noise — and predict deterioration before thresholds are breached.

  • Predictive CHF, COPD, and hypertension decompensation models
  • Risk-tiered alert queues for care team triage
  • Cross-device pattern recognition (e.g. weight + BP + SpOâ‚‚ trend)
  • Automatic escalation pathways by risk score and condition

Unified Device Integration Layer

Pre-built connectors for 200+ RPM devices — Bluetooth, cellular, and WiFi — with a single unified data model normalising readings across manufacturers and modalities.

  • 200+ certified device integrations (cellular, Bluetooth, WiFi)
  • Real-time data ingestion with sub-minute latency
  • Automated device provisioning and patient onboarding
  • Firmware monitoring and troubleshooting automation

Automated Documentation & RPM Billing

AI-generated clinical notes and automatic CPT code time tracking ensure accurate RPM billing documentation with zero additional care manager effort.

  • Auto-populated RPM care plan notes from device data
  • CMS CPT 99453–99458 time tracking and billing support
  • EHR-integrated documentation for Epic, Cerner, athenahealth
  • Monthly billing summary reports per enrolled patient

Integrates with your existing systems

Works With Every Major EHR Platform

EpicOracle CernerathenahealthMeditechNextGeneClinicalWorks

HL7 FHIR R4 native • SMART on FHIR • REST APIs • Custom HL7 v2 connectors

Ready to Make Your RPM Programme Clinically and Financially Sustainable?

See how Zabrizon's AI layer transforms your existing RPM investment into measurable outcomes and revenue.