Health Equity: Measure and Manage Disparities with Machine Learning

As gaps in health grow larger and more persistent across the nation, health equity becomes a critical challenge faced by healthcare organizations. This year, ChristianaCare launched multiple initiatives focusing on health equity and closing the gaps between different racial groups. To better support the initiatives, ChristianaCare developed a platform to quantify, visualize, and interpret the current state of health equity on multiple health outcomes using machine learning algorithms.

Join this session to discover how to support your organization’s health equity initiatives by:

• Designing a scalable and flexible data architecture that includes machine learning
• Architecting data processing workflows
• Building user-centered visualizations designs optimized for interpretations and usability