Digital Mission

Value-Based Health

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Financial and Clinical Risk Management Clinical Outcomes Management

Machine Learning-Driven Predictive Analytics

Current Situation

Rules-based and heuristic methods of predictive analytics use limited data and often do not include identification of the drivers of risk and consequently do not identify next best action.

Goals and Objectives

Predictive analytics need to be applied to operations, clinical, and financial domains and include all available appropriate data. Critical to success is providing insight into action and to learn what is successful within different contexts.

Technology Deployed

AI-driven advanced analytics for predictive modeling, machine learning, and prebuilt algorithms

Use Case Summary

Today’s analytics are limited in the data they use and focus on reporting, not insight. The use of AI-based predictive models can generate more personalized insights with the benefit of learning from past experiences.

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