Medical Device Giant Implements Pattern Detector for Patient Insights
One of the largest medical device companies in the world, with operations in 150 countries. The company offers an integrated system combining insulin pumps and Continuous Glucose Monitoring.
Needs
Develop a platform for pattern detection and insights on patient data.
Identify sequences leading to life-threatening hypo/hyperglycemic events.
Create dynamic features based on user requirements.
Filter patients based on specified conditions.
Display outcomes for events across variable timeframes.
Train models on multiple target columns for single/multiple patients.
Solution
Gained insights into patient behavior through frequent pattern observation.
Utilized machine learning algorithms (Apriori, Random Forest, XGBoost) for advanced analysis.
Provisioned a highly scalable cloud-based user interface for dynamic feature generation.
Generates alerts by predicting patient behavior.
Provided actionable insights for corrective measures and lifestyle recommendations.
Impact
2X
Improvement in patient outcomes
30%
Boost in CSAT – patient delight for receiving recommendations in their inbox
50%
Clinical support team able to resolve patient calls in half the time.
