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Clinical informatics has the potential to transform chronic disease management by translating evidence-based guidelines into actionable workflows at the point of care. This session will examine how health systems can optimize COPD management through EHR-enabled interventions, including clinical decision support, risk stratification, registries, care pathways, and transitions-of-care workflows. The speaker [...]

Public health informatics plays a critical role in improving population health, yet the workforce supporting these efforts continues to evolve. Join Brian Dixon, PhD, MPA, FACMI, FAMIA, for a discussion on how national workforce datasets can be used to better understand career pathways, workforce trends, and opportunities within public health [...]

Healthcare organizations are investing rapidly in AI, but many efforts remain fragmented across applications, data pipelines, and workflows. This makes it difficult to govern AI consistently, evaluate results in context, and build the trusted foundation needed for enterprise adoption. This moderated panel will examine the digital backbone required for an [...]

Factors Influencing the Effectiveness of Artificial Intelligence-assisted Decision-Making in Medicine: A Scoping Review Read the abstract Moderator Presenter Statement of Purpose AI systems can now match or exceed clinician performance on a growing range of diagnostic tasks, and health systems are rapidly deploying AI-based clinical decision support (AI-CDS). However, a [...]

This timely session will explore how public health can evolve into a Learning Public Health System by integrating continuous learning, data-driven decision-making, and modern governance into local and state health departments. Participants will gain insights into the evolution of public health models, the foundational components of learning public health systems—including [...]

This webinar explores how AI can accelerate the creation and maintenance of clinically governed value sets and how those high-quality value sets, in turn, strengthen the accuracy and trustworthiness of AI-driven healthcare workflows.