AI for Population Health Management: Assessing Risk, Building Trust, and Driving Better Outcomes
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Artificial Intelligence (AI) is increasingly leveraged for population health management by healthcare organizations seeking to improve patient care while reducing costs. Used as a predictive tool, AI can identify at-risk and emerging-risk populations, enabling limited clinical resources to target patient populations that will most benefit from — and respond to — hands-on intervention.
In this white paper, we take a deep dive into:
ZeOmega’s methodology around using AI for population health management
Existing models that can accurately predict risk for some of healthcare’s biggest cost drivers: opioid use and diabetes
How these and other AI models are developed, tested, iterated on, and integrated into existing population health management workflows
Machine Learning (ML) techniques and how they improve AI models over time
The tremendous possibility of applying predictive AI models to other chronic conditions
Additional Population Health Management Resources: