Webinar

Webinar: An LLM-based Framework for Aligning Evolving Evidence to Order Sets

Webinar: An LLM-based Framework for Aligning Evolving Evidence to Order Sets

Order sets in the electronic health record (EHR) system frequently lag behind evolving medical evidence, contributing to variation in care, inefficiency, and potential patient safety risks.

What if there were a framework that automatically links external knowledge to local EHR order sets and then identifies differences between the two?

This two-step approach identifies missing elements, highlights inconsistencies, and enables targeted proactive content reviews.

Early deployments of Knowledge Sync at two pilot health systems found errors of omission and commission in minutes; a process that would have otherwise taken months or not been detected until a years-long rotation of auditing.

Join to see the tool in action and hear the details behind these use cases.

Live Webinar:
Wed., June 24
2:00pm ET

And on-demand soon after. Register to join live or to receive the recording.

Written by

Jun 2, 2026

Written by

Jun 2, 2026

Order sets in the electronic health record (EHR) system frequently lag behind evolving medical evidence, contributing to variation in care, inefficiency, and potential patient safety risks.

What if there were a framework that automatically links external knowledge to local EHR order sets and then identifies differences between the two?

This two-step approach identifies missing elements, highlights inconsistencies, and enables targeted proactive content reviews.

Early deployments of Knowledge Sync at two pilot health systems found errors of omission and commission in minutes; a process that would have otherwise taken months or not been detected until a years-long rotation of auditing.

Join to see the tool in action and hear the details behind these use cases.

Live Webinar:
Wed., June 24
2:00pm ET

And on-demand soon after. Register to join live or to receive the recording.

MORE RESEARCH FROM PHRASE HEALTH