Moving the needle on health equity through artificial intelligence (AI) requires clean, unified data from electronic health records (EHRs), health information exchanges (HIEs), public health, and more. Coupled with a governance strategy to mitigate risk and avoid bias, a centralized data repository is key to deploying AI. Unstructured, siloed data in legacy formats presents a unique multimodal data challenge. How can health care organizations harmonize disparate data and use AI to identify at-risk populations, enable proactive interventions, and reduce care disparities? In this session we'll highlight: the challenges of harmonizing data for AI use cases; how an AI governance strategy can mitigate data risk and avoid bias; and how unified data can help health care organizations ensure better access to care, improve clinical decision support, and provide more proactive health care.
2. Understand key components of a governance strategy to securely and ethically manage data for AI applications.
3. Understand key AI use cases that a unified data strategy can enable.