A real-time patient monitoring platform that uses ML to predict adverse events 6 hours before they occur, deployed across 12 hospital networks.
Client
MedSync Health
Category
AI & Machine Learning
Year
2024
Technologies
7 in stack
Challenge
MedSync Health was drowning in fragmented patient data spread across 12 hospital networks. Nurses were spending 40% of their shift time manually reviewing vitals, and early warning signs were being missed — leading to preventable ICU admissions.
Solution
We built a unified real-time data pipeline ingesting vitals from 8 different EHR systems, then trained a gradient-boosted model on 3 years of historical outcomes data. The result was a predictive alert system that surfaces risk scores per patient, surfaced through a clean nurse-facing dashboard.
Outcome
Deployed across all 12 networks within 4 months. ICU transfers dropped 31% in the first year, and nursing documentation time fell by 22%. The platform now monitors 18,000+ patients daily.
Stack
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