Claims Sciences

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Claims Sciences

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Protect shared savings from abnormal billing and utilization

Protect shared savings from abnormal billing and utilizationProtect shared savings from abnormal billing and utilizationProtect shared savings from abnormal billing and utilization

Protect shared savings from abnormal billing and utilization

Protect shared savings from abnormal billing and utilizationProtect shared savings from abnormal billing and utilizationProtect shared savings from abnormal billing and utilization

FWA Detection in Medicare: Advanced Machine Learning Techniques

Claims Sciences is comprised of a team of passionate machine learning researchers dedicated to enhancing Medicare fraud detection and anomalous utilization by focusing on ACO  analytics to identify fraudulent billing practices, waste, and abuse within Accountable Care Organizations. We develop advanced anomaly-detection models that utilize healthcare analytics to analyze claims and provider behavior, allowing us to surface abnormal patterns earlier and with greater precision. This helps ACOs identify high-cost outliers, prioritize investigations, and ultimately protect shared savings.

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