Clinical documentation · Production

DeepScribe Ambient AI for ICD-10 Coding Intelligence

The problem

Physicians must track ICD-10 codes and billing requirements manually during or after patient visits, creating administrative burden and risk of non-compliant or missed codes that affect reimbursement.

Workflow diagram · grounded in source
1
Clinical conversation begins
trigger
“the natural conversation between clinician and patient”
2
Ambient speech capture
ai_action
“The most advanced speech recognition models capture the natural conversation between clinician and patient with extreme accuracy”
3
Suggested ICD-10 codes
ai_action
“DeepScribe recommends new ICD-10 codes based on the natural conversation with your patient”
4
Direct diagnosis translation
ai_action
“DeepScribe translates diagnoses mentioned by the physician during (or after) the visit into the corresponding ICD-10 codes”
5
EHR history pull-forward
integration
“DeepScribe pulls in existing diagnosis codes from your EHR's problem list within the note as part of the patient history”
6
Code output delivered
output
“From conversation to code, with no clicks required”
Reported outcome

DeepScribe generates ICD-10 codes from clinical conversations with no clicks required, delivering audit-ready documentation, reducing administrative burden, and ensuring proper reimbursement.

Reported metrics
Administrative burdenreducing administrative burden
Reimbursement complianceensuring proper reimbursement
Documentation complianceaudit-ready documentation
Physician coding effortno clicks required
Reported stack
DeepScribeSmartPrepEHR
Source
https://www.deepscribe.ai/solutions/ai-coding/icd-10
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

DeepScribe generates ICD-10 codes from clinical conversations with no clicks required, delivering audit-ready documentation, reducing administrative burden, and ensuring proper reimbursement.

What tools did this team use?

DeepScribe, SmartPrep, EHR.

What results were reported?

Administrative burden: reducing administrative burden; Reimbursement compliance: ensuring proper reimbursement; Documentation compliance: audit-ready documentation; Physician coding effort: no clicks required (source-reported, not independently verified).

How is this clinical documentation AI workflow structured?

Clinical conversation begins → Ambient speech capture → Suggested ICD-10 codes → Direct diagnosis translation → EHR history pull-forward → Code output delivered.

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