Cerbo EHR · Governance

Call Quality & QA for Cerbo AI Practices

Review process using AI transcripts plus Cerbo Chart Parts notes — close the loop on every interaction.

Section 1

QA is how you improve AI over time

AI receptionist performance degrades without active QA. Scripts become outdated, edge cases accumulate, and patient experience erodes before anyone notices.

A structured QA process — reviewing a sample of AI transcripts against Cerbo documentation each week — catches issues early and gives the AI team clear improvement targets.

Section 2

The weekly QA protocol

Review 10–15 AI call transcripts per week, selected randomly from each call type (scheduling, referral, after-hours, inquiry). Compare AI transcript to the resulting Cerbo entry — do they match? Is anything missing? Did the AI route correctly?

  • Transcript review: did the AI capture the right information in the right format?
  • Cerbo comparison: does the Cerbo task or encounter match the transcript content?
  • Routing accuracy: did the call go to the right destination?
  • Script gaps: any questions the AI couldn't handle that should be added to the script?
  • Escalation accuracy: were escalations triggered at the right threshold?

Section 3

Feeding QA back into the AI

QA findings feed directly into script updates. If patients are repeatedly asking a question that AI can't handle, add an approved response. If routing errors cluster around a specific call type, audit the routing rule for that type.

Most QA-driven improvements take 24–48 hours to implement and immediately improve AI resolution rate for the affected call type.

Ready to implement this for your Cerbo practice?

Book a demo and we'll walk through your specific Cerbo workflow — scheduling rules, Chart Parts templates, and after-hours coverage — and show you exactly how MedReception AI handles it.

Call Quality & QA for Cerbo AI Practices | MedReception AI | Medreception AI