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What is Machine Learning for Risk Adjustment about?

This document introduces a machine learning framework for improving risk adjustment models used in health insurance plan payments. It compares various machine learning methods to traditional regression models on their ability to accurately predict healthcare expenditures using diagnostic codes and other patient data. The results show that ensemble and screening methods within the machine learning framework can create a simplified risk adjustment formula with high predictive accuracy, potentially reducing op

Author

30 12A2 Thảo Quyên

Language

EN