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Children's Mercy Patient Satisfaction

Machine Learning

The Notre Dame Capstone team was tasked with improving the patient experience for the different divisions and facilities that make up Children’s Mercy Kansas City. Over the course of four months, our team was able to identify several “time-sensitive divisions” (health divisions where patients were most affected by wait time and scheduling time). This sensitivity, coupled with longer-than-desired wait and scheduling times, has led to a low patient experience (indicated by low facility ratings) for various Children’s Mercy divisions. Given this, our team was determined to answer—“What can Children’s Mercy do in order to improve low-performing divisions?” After running many different models, our findings indicated that just a 5-minute change in wait time at those sensitive divisions improved positive ratings by nearly 5% while reducing scheduling times at those sensitive locations increased positive facility ratings up to 16.8%.





Tags:
  • XGBoost
  • Medical
  • Health Care
  • Philanthropy