Turning AI into Real Results: A Population Health Blueprint from UC Davis Health

In this episode of Bright Spots in Healthcare, recorded live at the ViVE 2026 conference, Eric Glazer sits down with Dr. Reshma Gupta from UC Davis Health to explore how health systems can translate artificial intelligence and predictive analytics into real operational improvement.

As Chief of Population Health and Accountable Care, Reshma focuses on turning data and predictive insight into measurable outcomes across prevention, care management, and accountable care programs. Her work highlights a central challenge facing healthcare leaders today: many organizations have the models, but far fewer have built the workflows, governance, and operational alignment needed to turn those insights into action.

The conversation dives into:

• Why successful AI initiatives connect predictions directly to clinical workflows, incentives, and operational ownership

• How UC Davis Health expanded its high risk population health strategy into the Emergency Department

• Approaches to measuring the value of prevention including avoided admissions and downstream outcomes

• Where predictive analytics supports prevention and population health within accountable care models

• How UC Davis developed the BE FAIR framework to evaluate predictive models for bias and equity

• The governance structures that help health systems move quickly with AI while maintaining trust and accountability

• Practical lessons for moving AI from isolated pilots into measurable performance improvement

This discussion offers a practical blueprint for health system leaders working to strengthen prevention, population health, and accountable care through data driven insight. The organizations seeing real results are those aligning data, workflow, incentives, and governance so predictive insight translates into better decisions and measurable outcomes.

References:

• BE FAIR Framework: UC Davis Health's framework for assessing, implementing, and redesigning predictive models to reduce bias and improve equity in healthcare. https://pmc.ncbi.nlm.nih.gov/articles/PMC12405130/

• UC Davis Health AI for Population Health: How UC Davis Health uses predictive analytics to identify patients at risk and support earlier intervention in population health programs. https://health.ucdavis.edu/news/headlines/uc-davis-health-uses-ai-models-to-leave-no-patient-behind/2025/04

Reshma Gupta Bio: https://health.ucdavis.edu/population-health/leadership/reshma-gupta.html

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