The Latest from our Partners

What if AI medical transcription were twice as accurate?

When clinical terms are transcribed correctly the first time, handoffs tighten, coding aligns, and audits speed up. Speechmatics’ new medical model cuts overall word errors by 17% vs. the next best system and halves keyword errors on clinical terms. With 96% medical keyword recall and a 4% keyword error rate, you get first-pass notes you can trust. Read more.
 

The ambient AI playbook: Lessons from two leading health systems

At the recent CompassionIT Summit, leaders from Akron Children’s Hospital and Denver Health shared powerful lessons from rolling out ambient documentation to over 1,500 clinicians. Their biggest takeaway? Stories, not stats, drive adoption. Whether it was a heartfelt testimonial that swayed an entire department or a 60-second Nabla demo that eliminated training anxiety, the common thread was simplicity, authenticity, and clinician-centered design. Read more about the way these health systems are navigating ambient AI implementation: https://dhinsights.org/news/the-ambient-ai-playbook-lessons-from-two-leading-health-systems