Change Healthcare Uses Amazon SageMaker and Amazon QuickSight to Reduce Overpayment and Claim Waste

Change Healthcare, a leading independent healthcare technology company in the US, sought to improve clinical, financial, and patient engagement outcomes by reducing overpayment and claim waste. They faced challenges in getting machine learning model predictions into business intelligence tools quickly and cost-effectively. The solution involved leveraging Amazon SageMaker for machine learning training and inference and integrating it with Amazon QuickSight to automate the data ingestion, inference pipeline, and reporting process. This integration allowed business analysts and data scientists to create predictive dashboards without specialized ML expertise, streamlining workflows and reducing the time to deliver insights to decision-makers. The approach eliminated heavy manual ETL tasks, enabled scheduled and programmatic predictions, and reduced costs by using SageMaker batch transform jobs without running costly inference endpoints continuously.