Back to Research Associate at AI/Hub, Durham College
Predicting Emergency-Department Wait Times
Built a forecasting model that gives triage teams an early estimate of how long incoming patients may wait before being seen.
HealthcarePredictive AnalyticsPython
Project Details
Hospitals often lack an accurate real-time picture of queue length, so by merging triage, staffing, and census data we developed a gradient-boosted model that delivered wait-time estimates within eight minutes. Nurses reported improved scheduling confidence and clearer communication with patients, and their feedback guided refinements to the user interface. Development relied on pandas for feature engineering, SHAP for model explainability, and a lightweight Flask application for demonstration.
Key Achievements
- Pilot deployment across three hospitals achieved mean absolute error of roughly eight minutes.
- User surveys indicated a 20 percent improvement in scheduling confidence.