HITEQ Resources & Events

This sprint established the  ongoing measurement and governance loop that ensures AI tools remain safe, effective, fair, and  aligned with organizational goals after deployment.

This sprint tested whether a selected AI use case improves work without introducing hidden safety or usability risks, emphasizing human AI interaction, clear role boundaries, and transparency in how outputs are generated and used.

This sprint converted general AI principles into a minimum viable governance operating model for each health center that defined how AI tools are approved, monitored, and held accountable across their lifecycle.

This sprint determined whether each health center has the data, workforce, and operational foundation to adopt AI safely, and where AI can create immediate value when starting with clearly defined problems.

Addressing the non-medical drivers of health is essential for improving patient outcomes. This training shared lessons learned and promising practices for embedding social drivers of health into your EHR and clinical workflows. Participants learned how to effectively capture this critical information and how to act on it to provide more comprehensive, whole-person care.