Healthcare
AI That Predicts Healthcare Demand Before It Happens
goal
Challenge Faced
Hospitals face unplanned patient readmissions, bed shortages, and mismanaged resource allocation — leading to high costs and poor patient outcomes.
solution
Our Solution
We built a predictive analytics engine to forecast readmission risks, ICU demand, and staff/resource requirements.
Tools we used
Approach
Step-by-Step Workflow
Step 1
Collect patient data (EHR, vitals, discharge notes).
Step 2
ML models predict readmission probability.
Step 3
Flag high-risk patients for proactive care.
Step 4
Forecast bed, medication, and staff requirements.
Quantifiable Benefits
Reduction in unplanned readmissions
%
Better allocation of critical resources
0
%
Improvement in hospital operational efficiency
%
Significant cost savings in staff and supply planning
0
%
Who’s Using This
Kaiser Permanente
Mount Sinai Health System
Indian hospital chains (AI-led capacity planning)
Why It Matters
AI-powered foresight saves costs, improves care quality, and prepares hospitals for demand spikes.